1<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="image" imageSrcSet="/_next/image?url=%2Fimages%2Flogo.png&w=256&q=75 1x, /_next/image?url=%2Fimages%2Flogo.png&w=384&q=75 2x"/><link rel="stylesheet" href="/_next/static/chunks/14alqosszpf9s.css" data-precedence="next"/><link rel="preload" as="script" fetchPriority="low" href="/_next/static/chunks/0tmid5v1qi6nw.js"/>
1<script src="/_next/static/chunks/02llmmxb47g4t.js" async=""></script>
1<script src="/_next/static/chunks/12uj0p0otefpa.js" async=""></script>
1<script src="/_next/static/chunks/0os47u9vh-w1~.js" async=""></script>
1<script src="/_next/static/chunks/0o6x9b_hdpbfu.js" async=""></script>
1<script src="/_next/static/chunks/turbopack-07k--d.us.v20.js" async=""></script>
1<script src="/_next/static/chunks/0jyvuu-rh3tqf.js" async=""></script>
1<script src="/_next/static/chunks/0x9hbt.2lqqoh.js" async=""></script>
1<script src="/_next/static/chunks/15tev3v-k6ykn.js" async=""></script>
1<script src="/_next/static/chunks/0j6zc1fd6nfww.js" async=""></script>
1<script src="/_next/static/chunks/014.cojmeu8r7.js" async=""></script>
1<script src="/_next/static/chunks/0rkt4vczk~qc7.js" async=""></script>
1<script src="/_next/static/chunks/0b_bz3qblxdp-.js" async=""></script>
1<script src="/_next/static/chunks/06a45a7j5k-js.js" async=""></script>
1<script src="/_next/static/chunks/08n_t7-3qaqxt.js" async=""></script>
1<script src="/_next/static/chunks/14fu6zf9vwf4c.js" async=""></script>
1<script src="/_next/static/chunks/0mtxwrtj1pimg.js" async=""></script>
1<script src="/_next/static/chunks/09220hua3xdwb.js" async=""></script>
1<script src="/_next/static/chunks/0wx.~0vo7c8j-.js" async=""></script>
1<script src="/_next/static/chunks/0~p_uee4sxnt6.js" async=""></script>
1<script src="/_next/static/chunks/06uysyk4dsnp..js" async=""></script>
1<script src="/_next/static/chunks/0ieejselqt4sb.js" async=""></script>
1<script src="/_next/static/chunks/0p-k.~tfn1t4o.js" async=""></script>
1<script src="/_next/static/chunks/0uy~38govsi.j.js" async=""></script>
1<script src="/_next/static/chunks/102.xx_c910ig.js" async=""></script>
1<script src="/_next/static/chunks/0qia6hd26k~vx.js" async=""></script>
1<script src="/_next/static/chunks/12coqwet6qxr0.js" async=""></script>
1<script src="/_next/static/chunks/0.xr3l.uor6_o.js" async=""></script>
1<script src="/_next/static/chunks/07xu0f7a_b-vv.js" async=""></script>
1<script src="/_next/static/chunks/120.i~vx9g2x~.js" async=""></script>
1<script src="/_next/static/chunks/0ghr.qsuu5a8s.js" async=""></script>
1<script src="/_next/static/chunks/0ticqhfaxqa9m.js" async=""></script>
1<script src="/_next/static/chunks/0sk9j1giok5~z.js" async=""></script>
1<script src="/_next/static/chunks/06mb6yniv~mh_.js" async=""></script>
1<script src="/_next/static/chunks/15tbim000cf6s.js" async=""></script>
1<script src="/_next/static/chunks/0ivt8q6yvg__5.js" async=""></script>
1<script src="/_next/static/chunks/08z1r-elw.3u4.js" async=""></script>
vendor: 66 bytes, line 1
1<script async="" src="https://www.googletagmanager.com/gtag/js?id=
1AW-18384924145
vendor: 11 bytes, line 1
1"></script>
1<script src="/_next/static/chunks/0wpt7ub5rom57.js" async=""></script>
1<link rel="preconnect" href="https://ai.ailyze.com" crossorigin="anonymous"/><link rel="preconnect" href="https://bzrcdn.openai.com" crossorigin="anonymous"/><link rel="dns-prefetch" href="https://ipapi.co"/><link rel="dns-prefetch" href="https://api.frankfurter.dev"/><title>AI Qualitative Research Blog | Evidano</title><meta name="description" content="Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano."/><meta name="application-name" content="Evidano"/><meta name="author" content="Evidano"/><link rel="manifest" href="/manifest.webmanifest"/><meta name="robots" content="index, follow"/><link rel="canonical" href="https://www.evidano.com/blogs"/><link rel="alternate" type="application/rss+xml" href="https://www.evidano.com/blogs/rss.xml" title="Evidano Blog RSS Feed"/><meta property="og:title" content="AI Qualitative Research Blog | Evidano"/><meta property="og:description" content="Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano."/><meta property="og:url" content="https://www.evidano.com/blogs"/><meta property="og:type" content="website"/><meta name="twitter:card" content="summary_large_image"/><meta name="twitter:title" content="AI Qualitative Research Blog | Evidano"/><meta name="twitter:description" content="Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano."/><link rel="icon" href="/favicon.ico?favicon.0oz7g567qe3_2.ico" sizes="48x48" type="image/x-icon"/><link rel="apple-touch-icon" href="/apple-icon.png?apple-icon.15j4gpa5nlhmt.png" sizes="180x180" type="image/png"/>
1<script id="google-ads-gtag-bootstrap">window.dataLayer = window.dataLayer || []; 2function gtag(){dataLayer.push(arguments);} 3window.gtag = window.gtag || gtag; 4gtag('js', new Date()); 5gtag('config', "AW-18384924145");</script>
5<meta name="sentry-trace" content="9ab21c823c98474698e3971cb3b7a423-a3ae9a96581117f1-0"/><meta name="baggage" content="sentry-environment=production,sentry-release=e10779ec5aa4bffa3a9f4cb7f7e4cf754792c82a,sentry-public_key=689444fec702bf034538e58e9a29f099,sentry-trace_id=9ab21c823c98474698e3971cb3b7a423,sentry-org_id=4507590273007616,sentry-sampled=false,sentry-sample_rand=0.4321962256872709,sentry-sample_rate=0.05"/>
5<script src="/_next/static/chunks/03~yq9q893hmn.js" noModule=""></script>
5<style data-emotion="css-global 1qcbkg8">html{-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale;box-sizing:border-box;-webkit-text-size-adjust:100%;}*,*::before,*::after{box-sizing:inherit;}strong,b{font-weight:700;}body{margin:0;color:#212B36;line-height:1.5;font-size:1rem;font-family:Inter,-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-weight:400;background-color:#F8FAFF;}@media print{body{background-color:#fff;}}body::backdrop{background-color:#F8FAFF;}*{box-sizing:border-box;}html{margin:0;padding:0;width:100%;height:100%;-webkit-overflow-scrolling:touch;}body{margin:0;padding:0;width:100%;height:100%;max-width:100vw;overflow-x:hidden;}body::-webkit-scrollbar{width:8px;}body::-webkit-scrollbar-thumb{background-color:#1F77CE;border-radius:2px;}body::-webkit-scrollbar-track{background-color:#303030;}.shadow-material-md{box-shadow:rgba(0, 0, 0, 0.2) 0px 2px 1px -1px,rgba(0, 0, 0, 0.14) 0px 1px 1px 0px,rgba(0, 0, 0, 0.12) 0px 1px 3px 0px!important;}#root{width:100%;height:100%;}input[type=number]{-moz-appearance:textfield;}input[type=number]::-webkit-outer-spin-button{margin:0;-webkit-appearance:none;}input[type=number]::-webkit-inner-spin-button{margin:0;-webkit-appearance:none;}img{display:block;max-width:100%;}.footnote-btn{font-weight:500;color:#0D6EFD;}.app-main-menu{padding:20px 0;-webkit-transition:.420s;transition:.420s;}.app-main-menu.logged-in{padding:17px 0;}.app-main-menu.active-scroll{padding:7px 0;z-index:1000000;}.MuiOutlinedInput-root{border-radius:1px;}.MuiOutlinedInput-root:hover .MuiOutlinedInput-notchedOutline{border-color:primary.main;}.MuiOutlinedInput-root.Mui-focused .MuiOutlinedInput-notchedOutline{border-width:2px;}.app-main-menu.active-scroll a.nav-link{color:#000!important;}.app-main-menu.active-scroll .navbar-brand img{max-width:160px;-webkit-transition:.420s;transition:.420s;}.active-menu{font-weight:700!important;}.cm-bottom-scrolllbar::-webkit-scrollbar{height:5px;}.hide_scrollbar::-webkit-scrollbar{display:none;}.shodow-none{box-shadow:none!important;}.cm-bottom-scrolllbar::-webkit-scrollbar-track{background:#f1f1f1;}.cm-bottom-scrolllbar{scrollbar-color:#f1f1f1 transparent;}.cm-bottom-scrolllbar::-webkit-scrollbar-thumb{background:#888!important;}.cm-bottom-scrolllbar::-webkit-scrollbar-thumb:hover{background:#555;}.cm-right-scrolllbar{padding-right:15px;}.cm-right-scrolllbar::-webkit-scrollbar{width:5px;}.cm-right-scrolllbar::-webkit-scrollbar-track{background:#f1f1f1;}.cm-right-scrolllbar::-webkit-scrollbar-thumb{background:#888;}.cm-right-scrolllbar::-webkit-scrollbar-thumb:hover{background:#555;}#uppyWrapper .uppy-Dashboard-inner{height:300px!important;}.carousel.carousel-slider{overflow:visible;}ul.control-dots{left:50px;text-align:left!important;}ul.control-dots li{-webkit-transition:.420s!important;transition:.420s!important;height:15px!important;width:15px!important;}ul.control-dots .selected{background:#1363c6!important;width:40px!important;border-radius:100px!important;}.app-accordion-style-1{margin:15px 0;}.app-accordion-style-1 .Mui-expanded{color:#FFFFFF;background:#1363c6;box-shadow:none;}.app-ft-link-list-item{color:#fff;padding-right:15px;border-right:1px solid rgba(255, 255, 255, .1);}.app-ft-link-list-item:last-child{border-right:none;padding-right:0px;}.app-ft-link-list-item a{-webkit-text-decoration:underline;text-decoration:underline;color:rgba(255,255,255,.5);font-size:14px;}.app-ft-link-list-item a:hover{color:#fff;}.text-error{color:red;font-size:12px;}.text-error::before{content:"*";color:red;}.MuiTablePagination-root label.MuiFormLabel-root.MuiInputLabel-root{font-size:0.999rem;}.MuiTablePagination-root span.MuiTypography-root.MuiTypography-body2{font-size:0.989rem;}.alice-carousel__dots,.alice-carousel__next-btn{display:none!important;}.alice-carousel__prev-btn{display:none!important;}@media (min-width: 1400px){.app-cm-container{max-width:1320px;}}.css-1ju6sw4-MuiPaper-root-MuiCard-root{box-shadow:none!important;}.hide_scrollbar{overflow-style:none!important;scrollbar-width:none!important;}</style><style data-emotion="css k008qs 18lwniu vs3rwa 1f2izne 0 51b6kh 13420go 3q9hkd 1qyrfb u812zq 87glm6 levejw depviu 1m4n54b 1glia5i 19n0kdf q7mezt 185zj69 9wvnva havf2x 1qz13as 2le0 1c68enq 1twzmnh r8jj44 begwwo 1jgznv1 wubtha 12zs3lt powfqf 1cjromv 19egsyp 1hmu0g8 efwuvd 12g5ai9">.css-k008qs{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;}.css-18lwniu{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:column;-ms-flex-direction:column;flex-direction:column;width:100%;box-sizing:border-box;-webkit-flex-shrink:0;-ms-flex-negative:0;flex-shrink:0;position:fixed;z-index:1100;top:0;left:auto;right:0;--AppBar-color:inherit;box-shadow:0 8px 16px 0 rgba(145, 158, 171, 0.16);background-image:none;z-index:1300;top:var(--rebrand-banner-height, 0px);-webkit-transition:margin-left 300ms ease-in-out,width 300ms ease-in-out;transition:margin-left 300ms ease-in-out,width 300ms ease-in-out;}@media print{.css-18lwniu{position:absolute;}}.css-vs3rwa{background-color:#FFFFFF;color:#212B36;
5-webkit-transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;box-shadow:var(--Paper-shadow);background-image:var(--Paper-overlay);background-image:none;border-radius:10px;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:column;-ms-flex-direction:column;flex-direction:column;width:100%;box-sizing:border-box;-webkit-flex-shrink:0;-ms-flex-negative:0;flex-shrink:0;position:fixed;z-index:1100;top:0;left:auto;right:0;--AppBar-color:inherit;box-shadow:0 8px 16px 0 rgba(145, 158, 171, 0.16);background-image:none;z-index:1300;top:var(--rebrand-banner-height, 0px);-webkit-transition:margin-left 300ms ease-in-out,width 300ms ease-in-out;transition:margin-left 300ms ease-in-out,width 300ms ease-in-out;}@media print{.css-vs3rwa{position:absolute;}}.css-1f2izne{width:100%;margin-left:auto;box-sizing:border-box;margin-right:auto;padding-left:16px;padding-right:16px;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:justify;-webkit-justify-content:space-between;justify-content:space-between;}@media (min-width:600px){.css-1f2izne{padding-left:24px;padding-right:24px;}}@media (min-width:1200px){.css-1f2izne{max-width:1200px;}}.css-51b6kh{-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;cursor:pointer;position:relative;margin:0px;}@media (min-width:0px){.css-51b6kh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;height:50px;padding:0px;}}@media (min-width:900px){.css-51b6kh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;height:70px;padding:0px;}}.css-13420go{-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}@media (min-width:0px){.css-13420go{display:none;}}@media (min-width:900px){.css-13420go{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;}}.css-3q9hkd{text-align:center;-webkit-flex:0 0 auto;-ms-flex:0 0 auto;flex:0 0 auto;font-size:1.5rem;padding:8px;border-radius:50%;color:#637381;-webkit-transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;--IconButton-hoverBg:rgba(99, 115, 129, 0.08);border-radius:8px;}.css-3q9hkd:hover{background-color:var(--IconButton-hoverBg);}@media (hover: none){.css-3q9hkd:hover{background-color:transparent;}}.css-3q9hkd.Mui-disabled{background-color:transparent;color:rgba(145, 158, 171, 0.8);}.css-3q9hkd.MuiIconButton-loading{color:transparent;}.css-1qyrfb{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;position:relative;box-sizing:border-box;-webkit-tap-highlight-color:transparent;background-color:transparent;outline:0;border:0;margin:0;border-radius:0;padding:0;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;-moz-appearance:none;-webkit-appearance:none;-webkit-text-decoration:none;text-decoration:none;color:inherit;text-align:center;-webkit-flex:0 0 auto;-ms-flex:0 0 auto;flex:0 0 auto;font-size:1.5rem;padding:8px;border-radius:50%;color:#637381;-webkit-transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;--IconButton-hoverBg:rgba(99, 115, 129, 0.08);border-radius:8px;}.css-1qyrfb::-moz-focus-inner{border-style:none;}.css-1qyrfb.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-1qyrfb{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-1qyrfb:hover{background-color:var(--IconButton-hoverBg);}@media (hover: none){.css-1qyrfb:hover{background-color:transparent;}}.css-1qyrfb.Mui-disabled{background-color:transparent;color:rgba(145, 158, 171, 0.8);}.css-1qyrfb.MuiIconButton-loading{color:transparent;}
5.css-u812zq{-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;width:1em;height:1em;display:inline-block;-webkit-flex-shrink:0;-ms-flex-negative:0;flex-shrink:0;-webkit-transition:fill 200ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:fill 200ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;fill:currentColor;font-size:1.5rem;color:#176CC7;}.css-87glm6{z-index:1500;pointer-events:none;pointer-events:auto;pointer-events:none;}.css-levejw{z-index:1500;pointer-events:none;pointer-events:auto;pointer-events:none;}@media print{.css-depviu{position:absolute!important;}}@media (min-width:900px){.css-1m4n54b{display:none;}}.css-1glia5i{text-align:center;-webkit-flex:0 0 auto;-ms-flex:0 0 auto;flex:0 0 auto;font-size:1.5rem;padding:8px;border-radius:50%;color:#637381;-webkit-transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;--IconButton-hoverBg:rgba(99, 115, 129, 0.08);color:inherit;border-radius:8px;}.css-1glia5i:hover{background-color:var(--IconButton-hoverBg);}@media (hover: none){.css-1glia5i:hover{background-color:transparent;}}.css-1glia5i.Mui-disabled{background-color:transparent;color:rgba(145, 158, 171, 0.8);}.css-1glia5i.MuiIconButton-loading{color:transparent;}@media (min-width:900px){.css-1glia5i{display:none;}}.css-19n0kdf{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;position:relative;box-sizing:border-box;-webkit-tap-highlight-color:transparent;background-color:transparent;outline:0;border:0;margin:0;border-radius:0;padding:0;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;vertical-align:middle;-moz-appearance:none;-webkit-appearance:none;-webkit-text-decoration:none;text-decoration:none;color:inherit;text-align:center;-webkit-flex:0 0 auto;-ms-flex:0 0 auto;flex:0 0 auto;font-size:1.5rem;padding:8px;border-radius:50%;color:#637381;-webkit-transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:background-color 150ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;--IconButton-hoverBg:rgba(99, 115, 129, 0.08);color:inherit;border-radius:8px;}.css-19n0kdf::-moz-focus-inner{border-style:none;}.css-19n0kdf.Mui-disabled{pointer-events:none;cursor:default;}@media print{.css-19n0kdf{-webkit-print-color-adjust:exact;color-adjust:exact;}}.css-19n0kdf:hover{background-color:var(--IconButton-hoverBg);}@media (hover: none){.css-19n0kdf:hover{background-color:transparent;}}.css-19n0kdf.Mui-disabled{background-color:transparent;color:rgba(145, 158, 171, 0.8);}.css-19n0kdf.MuiIconButton-loading{color:transparent;}@media (min-width:900px){.css-19n0kdf{display:none;}}.css-q7mezt{-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;width:1em;height:1em;display:inline-block;-webkit-flex-shrink:0;-ms-flex-negative:0;flex-shrink:0;-webkit-transition:fill 200ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:fill 200ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;fill:currentColor;font-size:1.5rem;}.css-185zj69{padding:32px 0 16px 0;background:#212529;background-image:url(/images/footer.png);-webkit-background-size:contain;background-size:contain;-webkit-background-position:center;background-position:center;background-repeat:no-repeat;color:#d1d5db;}.css-9wvnva{width:100%;margin-left:auto;box-sizing:border-box;margin-right:auto;padding-left:16px;padding-right:16px;}@media (min-width:600px){.css-9wvnva{padding-left:24px;padding-right:24px;}}@media (min-width:1200px){.css-9wvnva{max-width:1200px;}}.css-havf2x{box-sizing:border-box;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-box-flex-wrap:wrap;-webkit-flex-wrap:wrap;-ms-flex-wrap:wrap;flex-wrap:wrap;width:100%;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;margin-top:calc(-1 * 32px);width:calc(100% + 32px);margin-left:calc(-1 * 32px);margin-bottom:24px;}.css-havf2x>.MuiGrid-item{padding-top:32px;}.css-havf2x>.MuiGrid-item{padding-left:32px;}.css-1qz13as{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}@media (min-width:600px){.css-1qz13as{-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}}
5@media (min-width:900px){.css-1qz13as{-webkit-flex-basis:12.5%;-ms-flex-preferred-size:12.5%;flex-basis:12.5%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:12.5%;}}@media (min-width:1200px){.css-1qz13as{-webkit-flex-basis:12.5%;-ms-flex-preferred-size:12.5%;flex-basis:12.5%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:12.5%;}}@media (min-width:1536px){.css-1qz13as{-webkit-flex-basis:12.5%;-ms-flex-preferred-size:12.5%;flex-basis:12.5%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:12.5%;}}.css-2le0{margin:0;font-weight:600;line-height:1.5;font-size:1rem;font-family:Inter,-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";color:#ffffff;font-size:18px;font-weight:600;margin-bottom:16px;border-bottom:2px solid #ffffff;padding-bottom:8px;display:inline-block;}.css-1c68enq{display:grid;grid-template-columns:1fr;-webkit-column-gap:24px;column-gap:24px;row-gap:4px;}.css-1twzmnh{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:100%;-ms-flex-preferred-size:100%;flex-basis:100%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:100%;}@media (min-width:600px){.css-1twzmnh{-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}}@media (min-width:900px){.css-1twzmnh{-webkit-flex-basis:33.333333%;-ms-flex-preferred-size:33.333333%;flex-basis:33.333333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:33.333333%;}}@media (min-width:1200px){.css-1twzmnh{-webkit-flex-basis:33.333333%;-ms-flex-preferred-size:33.333333%;flex-basis:33.333333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:33.333333%;}}@media (min-width:1536px){.css-1twzmnh{-webkit-flex-basis:33.333333%;-ms-flex-preferred-size:33.333333%;flex-basis:33.333333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:33.333333%;}}.css-r8jj44{display:grid;-webkit-column-gap:24px;column-gap:24px;row-gap:4px;}@media (min-width:0px){.css-r8jj44{grid-template-columns:1fr;}}@media (min-width:600px){.css-r8jj44{grid-template-columns:1fr 1fr;}}.css-begwwo{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}@media (min-width:600px){.css-begwwo{-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}}@media (min-width:900px){.css-begwwo{-webkit-flex-basis:20.833333%;-ms-flex-preferred-size:20.833333%;flex-basis:20.833333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:20.833333%;}}@media (min-width:1200px){.css-begwwo{-webkit-flex-basis:20.833333%;-ms-flex-preferred-size:20.833333%;flex-basis:20.833333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:20.833333%;}}@media (min-width:1536px){.css-begwwo{-webkit-flex-basis:20.833333%;-ms-flex-preferred-size:20.833333%;flex-basis:20.833333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:20.833333%;}}.css-1jgznv1{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}@media (min-width:600px){.css-1jgznv1{-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}}@media (min-width:900px){.css-1jgznv1{-webkit-flex-basis:16.666667%;-ms-flex-preferred-size:16.666667%;flex-basis:16.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:16.666667%;}}@media (min-width:1200px){.css-1jgznv1{-webkit-flex-basis:16.666667%;-ms-flex-preferred-size:16.666667%;flex-basis:16.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:16.666667%;}}@media (min-width:1536px){.css-1jgznv1{-webkit-flex-basis:16.666667%;-ms-flex-preferred-size:16.666667%;flex-basis:16.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:16.666667%;}}.css-wubtha{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:100%;-ms-flex-preferred-size:100%;flex-basis:100%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:100%;}@media (min-width:600px){.css-wubtha{-webkit-flex-basis:50%;-ms-flex-preferred-size:50%;flex-basis:50%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:50%;}}
5@media (min-width:900px){.css-wubtha{-webkit-flex-basis:16.666667%;-ms-flex-preferred-size:16.666667%;flex-basis:16.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:16.666667%;}}@media (min-width:1200px){.css-wubtha{-webkit-flex-basis:16.666667%;-ms-flex-preferred-size:16.666667%;flex-basis:16.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:16.666667%;}}@media (min-width:1536px){.css-wubtha{-webkit-flex-basis:16.666667%;-ms-flex-preferred-size:16.666667%;flex-basis:16.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:16.666667%;}}.css-12zs3lt{margin:0;line-height:1.5;font-size:1rem;font-family:Inter,-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-weight:400;color:#9ca3af;font-size:14px;line-height:1.5;margin-bottom:16px;}.css-powfqf{border-top:1px solid #374151;padding-top:24px;}.css-1cjromv{box-sizing:border-box;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-box-flex-wrap:wrap;-webkit-flex-wrap:wrap;-ms-flex-wrap:wrap;flex-wrap:wrap;width:100%;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;margin-top:calc(-1 * 16px);width:calc(100% + 16px);margin-left:calc(-1 * 16px);-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}.css-1cjromv>.MuiGrid-item{padding-top:16px;}.css-1cjromv>.MuiGrid-item{padding-left:16px;}.css-19egsyp{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:100%;-ms-flex-preferred-size:100%;flex-basis:100%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:100%;}@media (min-width:600px){.css-19egsyp{-webkit-flex-basis:100%;-ms-flex-preferred-size:100%;flex-basis:100%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:100%;}}@media (min-width:900px){.css-19egsyp{-webkit-flex-basis:33.333333%;-ms-flex-preferred-size:33.333333%;flex-basis:33.333333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:33.333333%;}}@media (min-width:1200px){.css-19egsyp{-webkit-flex-basis:33.333333%;-ms-flex-preferred-size:33.333333%;flex-basis:33.333333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:33.333333%;}}@media (min-width:1536px){.css-19egsyp{-webkit-flex-basis:33.333333%;-ms-flex-preferred-size:33.333333%;flex-basis:33.333333%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:33.333333%;}}.css-1hmu0g8{margin:0;line-height:1.5;font-size:0.875rem;font-family:Inter,-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-weight:400;color:#6b7280;font-size:14px;}@media (min-width:0px){.css-1hmu0g8{text-align:center;}}@media (min-width:900px){.css-1hmu0g8{text-align:left;}}.css-efwuvd{box-sizing:border-box;margin:0;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-flex-basis:100%;-ms-flex-preferred-size:100%;flex-basis:100%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:100%;}@media (min-width:600px){.css-efwuvd{-webkit-flex-basis:100%;-ms-flex-preferred-size:100%;flex-basis:100%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:100%;}}@media (min-width:900px){.css-efwuvd{-webkit-flex-basis:66.666667%;-ms-flex-preferred-size:66.666667%;flex-basis:66.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:66.666667%;}}@media (min-width:1200px){.css-efwuvd{-webkit-flex-basis:66.666667%;-ms-flex-preferred-size:66.666667%;flex-basis:66.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:66.666667%;}}@media (min-width:1536px){.css-efwuvd{-webkit-flex-basis:66.666667%;-ms-flex-preferred-size:66.666667%;flex-basis:66.666667%;-webkit-box-flex:0;-webkit-flex-grow:0;-ms-flex-positive:0;flex-grow:0;max-width:66.666667%;}}.css-12g5ai9{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-box-flex-wrap:wrap;-webkit-flex-wrap:wrap;-ms-flex-wrap:wrap;flex-wrap:wrap;}.css-12g5ai9>:not(style):not(style){margin:0;}.css-12g5ai9>:not(style)~:not(style){margin-left:24px;}@media (min-width:0px){.css-12g5ai9{-webkit-box-pack:center;-ms-flex-pack:center;
5-webkit-justify-content:center;justify-content:center;}}@media (min-width:900px){.css-12g5ai9{-webkit-box-pack:end;-ms-flex-pack:end;-webkit-justify-content:flex-end;justify-content:flex-end;}}</style></head><body><div hidden=""><!--$--><!--/$--></div><!--$--><!--/$--><!--$--><!--/$--><div class="has-rebrand-banner"><div class="MuiBox-root css-k008qs"><header class="MuiPaper-root MuiPaper-elevation MuiPaper-elevation4 MuiAppBar-root MuiAppBar-colorInherit MuiAppBar-positionFixed mui-fixed css-vs3rwa" style="--Paper-shadow:0 12px 24px -4px rgba(145, 158, 171, 0.16)"><div style="padding:20px 0;transition:none" class="app-main-menu "><div class="MuiContainer-root MuiContainer-maxWidthLg app-cm-container css-1f2izne"><div class="flex gap-3 justify-center items-center MuiBox-root css-0"><a class="MuiBox-root css-51b6kh" href="/"><img alt="Site Logo" width="180" height="100" decoding="async" data-nimg="1" style="color:transparent;object-fit:contain;margin:0;padding:0;display:block" srcSet="/_next/image?url=%2Fimages%2Flogo.png&w=256&q=75 1x, /_next/image?url=%2Fimages%2Flogo.png&w=384&q=75 2x" src="/_next/image?url=%2Fimages%2Flogo.png&w=384&q=75"/></a></div><div class="MuiBox-root css-13420go"><nav aria-label="Main" data-orientation="horizontal" dir="ltr" class="relative z-10 flex max-w-max flex-1 items-center justify-center"><div style="position:relative"><ul data-orientation="horizontal" class="group flex flex-1 list-none items-center justify-center space-x-1" dir="ltr"><li><a class="mx-3 !text-md font-semibold" data-radix-collection-item="" href="/"><span class="">Home</span></a></li><li><button id="radix-_R_3adacllbbtb_-trigger-radix-_R_iradacllbbtb_" data-state="closed" aria-expanded="false" class="group inline-flex h-9 w-max items-center justify-center rounded-md !bg-transparent px-4 py-2 text-md transition-colors hover:bg-accent hover:text-accent-foreground focus:bg-accent focus:text-accent-foreground focus:outline-none disabled:pointer-events-none disabled:opacity-50 data-[active]:bg-accent/50 data-[state=open]:bg-accent/50 group font-semibold cursor-pointer" data-radix-collection-item="">About<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-down relative top-[1px] ml-1 h-3 w-3 transition duration-300 group-data-[state=open]:rotate-180" aria-hidden="true"><path d="m6 9 6 6 6-6"></path></svg></button></li><li><button id="radix-_R_3adacllbbtb_-trigger-radix-_R_qradacllbbtb_" data-state="closed" aria-expanded="false" class="group inline-flex h-9 w-max items-center justify-center rounded-md !bg-transparent px-4 py-2 text-md transition-colors hover:bg-accent hover:text-accent-foreground focus:bg-accent focus:text-accent-foreground focus:outline-none disabled:pointer-events-none disabled:opacity-50 data-[active]:bg-accent/50 data-[state=open]:bg-accent/50 group font-semibold cursor-pointer" data-radix-collection-item="">Preview Evidano<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-down relative top-[1px] ml-1 h-3 w-3 transition duration-300 group-data-[state=open]:rotate-180" aria-hidden="true"><path d="m6 9 6 6 6-6"></path></svg></button></li><li><a class="mx-3 !text-md font-semibold" data-radix-collection-item="" href="/contact"><span class="">Contact</span></a></li><li><a class="mx-3 !text-md font-semibold" data-radix-collection-item="" href="/blogs"><span class="active-menu">Blogs</span></a></li><li><a class="mx-3 !text-md font-semibold" data-radix-collection-item="" href="/guides"><span class="">Guides</span></a></li><li><a class="mx-3 !text-md font-semibold" data-radix-collection-item="" href="/login"><span class="">Login</span></a></li><li><button class="!m-0 items-center justify-center transition-all duration-300 ease-in-out focus:outline-none focus:ring-2 focus:ring-offset-2 disabled:opacity-50 disabled:cursor-not-allowed cursor-pointer bg-gradient-to-r from-[#176CC7] to-[#64A8EA] hover:from-[#1257A6] hover:to-[#176CC7] text-white shadow-lg hover:shadow-xl hover:-translate-y-0.5 focus:ring-[#176CC7]/50 active:scale-95 px-4 py-2 text-sm rounded-full min-h-[36px] gap-2 mx-3 font-semibold !text-white flex flex-col !text-xs !px-3 !py-2" data-radix-collection-item="">Register for Free Plan <span class="!text-[10px] -mt-2">(free forever, no expiry)</span></button></li><li><button class="!m-0 items-center justify-center transition-all duration-300 ease-in-out focus:outline-none focus:ring-2 focus:ring-offset-2 disabled:opacity-50 disabled:cursor-not-allowed cursor-pointer bg-gradient-to-r from-[#176CC7] to-[#64A8EA] hover:from-[#1257A6] hover:to-[#176CC7] text-white shadow-lg hover:shadow-xl hover:-translate-y-0.5 focus:ring-[#176CC7]/50 active:scale-95 px-4 py-2 text-sm rounded-full min-h-[36px] gap-2 mx-3 font-semibold !text-white flex flex-col !text-xs !px-3 !py-2" data-radix-collection-item="">Book demo</button></li><div class="flex items-center gap-4 MuiBox-root css-0"><div class="relative"><button class="MuiButtonBase-root MuiIconButton-root MuiIconButton-sizeMedium !ml-[10px] transition-transform duration-100 ease-in-out css-1qyrfb" tabindex="0" type="button" data-tawk-trigger="true" aria-label="Toggle customer support chat"><svg class="MuiSvgIcon-root MuiSvgIcon-colorPrimary MuiSvgIcon-fontSizeMedium css-u812zq" focusable="false" aria-hidden="true" viewBox="0 0 24 24" data-testid="HeadsetMicRoundedIcon"><path d="M11.4 1.02C6.62 1.33 3 5.52 3 10.31V17c0 1.66 1.34 3 3 3h1c1.1 0 2-.9 2-2v-4c0-1.1-.9-2-2-2H5v
5-1.71C5 6.45 7.96 3.11 11.79 3 15.76 2.89 19 6.06 19 10v2h-2c-1.1 0-2 .9-2 2v4c0 1.1.9 2 2 2h2v1h-6c-.55 0-1 .45-1 1s.45 1 1 1h5c1.66 0 3-1.34 3-3V10c0-5.17-4.36-9.32-9.6-8.98"></path></svg></button></div></div></ul></div><div class="absolute top-full -right-20"></div></nav></div><div class="flex justify-center items-center gap-2 MuiBox-root css-1m4n54b"><div class="!flex !items-center !gap-4 MuiBox-root css-0"><div class="relative"><button class="MuiButtonBase-root MuiIconButton-root MuiIconButton-sizeMedium !ml-[10px] transition-transform duration-100 ease-in-out css-1qyrfb" tabindex="0" type="button" data-tawk-trigger="true" aria-label="Toggle customer support chat"><svg class="MuiSvgIcon-root MuiSvgIcon-colorPrimary MuiSvgIcon-fontSizeMedium css-u812zq" focusable="false" aria-hidden="true" viewBox="0 0 24 24" data-testid="HeadsetMicRoundedIcon"><path d="M11.4 1.02C6.62 1.33 3 5.52 3 10.31V17c0 1.66 1.34 3 3 3h1c1.1 0 2-.9 2-2v-4c0-1.1-.9-2-2-2H5v-1.71C5 6.45 7.96 3.11 11.79 3 15.76 2.89 19 6.06 19 10v2h-2c-1.1 0-2 .9-2 2v4c0 1.1.9 2 2 2h2v1h-6c-.55 0-1 .45-1 1s.45 1 1 1h5c1.66 0 3-1.34 3-3V10c0-5.17-4.36-9.32-9.6-8.98"></path></svg></button></div></div><button class="MuiButtonBase-root MuiIconButton-root MuiIconButton-colorInherit MuiIconButton-sizeMedium css-19n0kdf" tabindex="0" type="button" aria-label="open drawer"><svg class="MuiSvgIcon-root MuiSvgIcon-fontSizeMedium css-q7mezt" focusable="false" aria-hidden="true" viewBox="0 0 24 24" data-testid="MenuIcon"><path d="M3 18h18v-2H3zm0-5h18v-2H3zm0-7v2h18V6z"></path></svg></button></div></div></div></header></div><div class="transition-[margin-left] duration-300 ease-in-out" style="padding-top:var(--rebrand-banner-height, 0px)"><main class="min-h-screen bg-white pb-20 pt-[84px]">
5<script type="application/ld+json">{"@context":"https://schema.org","@graph":[{"@type":"Blog","@id":"https://www.evidano.com/blogs","name":"Evidano AI Qualitative Research Blog","description":"Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano.","url":"https://www.evidano.com/blogs","inLanguage":"en","publisher":{"@type":"Organization","name":"Evidano","url":"https://www.evidano.com"},"blogPost":[{"@type":"BlogPosting","headline":"Two Definitions: Climate Change Acceptance for Undergrads","description":"How a PLoS One Delphi study (Aug 25, 2026) defined climate change acceptance for undergraduate science students, and how AI-enabled qualitative analysis applies it.","url":"https://www.evidano.com/blogs/climate-change-acceptance-definition-undergrads","image":"https://www.evidano.com/blogs/climate-change-acceptance-definition-undergrads/opengraph-image","datePublished":"2026-08-27T02:32:23.121788Z","keywords":"climate change acceptance definition, climate change acceptance undergraduate, Delphi study climate acceptance, qualitative analysis climate education","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"Researcher-in-the-loop: AI-enabled UX research","description":"How the researcher-in-the-loop model governs AI-enabled UX research. Learn practical governance, stats from the August 2026 piece, and how Evidano supports this workflow.","url":"https://www.evidano.com/blogs/researcher-in-the-loop-ai-ux-research-ce94f8ed","image":"https://www.evidano.com/blogs/researcher-in-the-loop-ai-ux-research-ce94f8ed/opengraph-image","datePublished":"2026-08-27T02:31:27.618383Z","keywords":"researcher-in-the-loop, AI-enabled UX research, governed research AI, research governance AI","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"Researcher-in-the-Loop: Governance for AI UX Research","description":"Govern AI in qualitative UX research with the researcher-in-the-loop model from Jennifer L. Bowie (Aug 25, 2026): practical rules, risks, and tool mappings.","url":"https://www.evidano.com/blogs/researcher-in-the-loop","image":"https://www.evidano.com/blogs/researcher-in-the-loop/opengraph-image","datePublished":"2026-08-27T02:30:35.794981Z","keywords":"researcher-in-the-loop, AI-enabled qualitative research, AI governance for UX research","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"Why LARC/PM Uptake Is Low: Qualitative Analysis in Bangladesh","description":"Actionable guidance for researchers: qualitative analysis of LARC uptake in rural Bangladesh using AI-enabled workflows to code interviews, surface themes, and inform rights-based programs.","url":"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake-bangladesh","image":"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake-bangladesh/opengraph-image","datePublished":"2026-08-27T02:30:14.783359Z","keywords":"qualitative analysis of LARC uptake, LARC uptake Bangladesh qualitative, AI-enabled qualitative research, long-acting contraception qualitative","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"AI for Qualitative Analysis: LARC Uptake in Bangladesh","description":"How AI-enabled qualitative analysis reveals multilevel barriers to
5LARC/PM uptake in rural Bangladesh, with practical steps for researchers and program teams. Read actionable methods.","url":"https://www.evidano.com/blogs/qualitative-analysis-larc-uptake-bangladesh-d333f5d9-3","image":"https://www.evidano.com/blogs/qualitative-analysis-larc-uptake-bangladesh-d333f5d9-3/opengraph-image","datePublished":"2026-08-27T02:29:22.936258Z","keywords":"qualitative analysis of LARC uptake, LARC PM uptake Bangladesh, AI-enabled qualitative research, thematic analysis family planning","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"Consensus definitions: climate change acceptance definition","description":"PLoS One (Aug 25, 2026) presents two consensus climate change acceptance definitions for undergraduates; see stats and how AI qualitative analysis accelerates survey design.","url":"https://www.evidano.com/blogs/climate-change-acceptance-definition-delphi","image":"https://www.evidano.com/blogs/climate-change-acceptance-definition-delphi/opengraph-image","datePublished":"2026-08-27T02:28:29.626300Z","keywords":"climate change acceptance definition, Delphi climate acceptance undergraduates, climate acceptance definitions PLoS One, AI qualitative analysis for survey design","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"AI synthesis: qualitative analysis of LARC/PM uptake","description":"AI-enabled synthesis of a PLOS ONE qualitative analysis of LARC/PM uptake in rural Bangladesh (Aug 25, 2026). Read methods, key stats, quotes, and AI research workflows.","url":"https://www.evidano.com/blogs/qualitative-analysis-larc-pm-bangladesh","image":"https://www.evidano.com/blogs/qualitative-analysis-larc-pm-bangladesh/opengraph-image","datePublished":"2026-08-27T02:27:53.966224Z","keywords":"qualitative analysis of LARC/PM uptake, LARC uptake Bangladesh qualitative, AI-enabled qualitative research, thematic analysis family planning","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"Simulation Testing: AI Simulation Testing for Clinical Care","description":"How Mayo Clinic uses AI simulation testing to close the clinical AI translation gap; practical steps for qualitative researchers and UX teams plus tools to scale evaluation.","url":"https://www.evidano.com/blogs/ai-simulation-testing-clinical","image":"https://www.evidano.com/blogs/ai-simulation-testing-clinical/opengraph-image","datePublished":"2026-08-27T02:26:52.908224Z","keywords":"AI simulation testing, clinical AI evaluation, simulation-based AI testing, AI translation gap, qualitative AI testing","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"AI-ready Guide: qualitative analysis of contraceptive uptake","description":"Apply AI-enabled qualitative analysis to LARC/PM uptake in rural Bangladesh: study stats, direct quotes, and practical researcher steps. Learn methods and next steps.","url":"https://www.evidano.com/blogs/qualitative-analysis-contraceptive-uptake-bangladesh-d333f5d9","image":"https://www.evidano.com/blogs/qualitative-analysis-contraceptive-uptake-bangladesh-d333f5d9/opengraph-image","datePublished":"2026-08-27T02:26:42.453403Z","keywords":"qualitative analysis of contraceptive uptake, LARC uptake Bangladesh qualitative, AI-enabled qualitative research, family planning qualitative methods","author":{"@type":"Organization","name":"Evidano"}},{"@type":"BlogPosting","headline":"AI-enabled qualitative analysis of LARC uptake","description":"How AI speeds thematic, cross-segment insight from interviews: an AI-enabled qualitative analysis of LARC uptake in rural Bangladesh, with practical research workflows.","url":"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake","image":"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake/opengraph-image","datePublished":"2026-08-27T02:25:28.418465Z","keywords":"qualitative analysis of LARC uptake, AI qualitative research, LARC uptake Bangladesh, thematic analysis interviews","author":{"@type":"Organization","name":"Evidano"}}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://www.evidano.com"},{"@type":"ListItem","position":2,"name":"Blog","item":"https://www.evidano.com/blogs"}]}]}</script>
5<div class="mx-auto max-w-7xl px-5 sm:px-8"><header class="pb-8 pt-10"><nav aria-label="Breadcrumb" class="mb-4 text-sm text-gray-500"><a class="transition-colors hover:text-[rgb(31,119,206)]" href="/">Home</a><span aria-hidden="true" class="mx-2 text-gray-300">/</span><span class="text-gray-700">Blog</span></nav><h1 class="max-w-4xl text-3xl font-black tracking-tight text-gray-900 text-balance sm:text-4xl md:text-5xl">AI & Qualitative Research Blog</h1><p class="mt-5 max-w-3xl text-sm text-gray-500">New to Evidano? Start with the<!-- --> <a class="font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/features">feature overview</a>, <a class="font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/case-studies">published case studies</a>, or <a class="font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/blogs/rss.xml">subscribe via RSS</a>.</p></header><section aria-label="Research spotlights" aria-roledescription="carousel" class="mx-auto w-[95%] max-w-7xl px-2 py-10 md:w-[90%] md:py-14"><div class="mb-8 flex flex-col items-center gap-3 text-center"><h2 class="text-2xl font-bold tracking-tight text-gray-900 text-balance sm:text-3xl">Researchers' Voices</h2></div><div class="relative"><div class="overflow-hidden rounded-2xl"><div class="flex transition-transform duration-[600ms] ease-in-out motion-reduce:transition-none" style="transform:translateX(-0%)"><div aria-label="1 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/public-preferences-police-chief-leadership"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in the Journal of Experimental Criminology</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="The University of Texas at Austin logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fut-austin.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fut-austin.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fut-austin.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Gordon Abner, Associate Professor at the LBJ School of Public Affairs at the University of Texas at Austin" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fabner-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fabner-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fabner-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Gordon Abner</p><p class="text-sm text-gray-500">Associate Professor, LBJ School of Public Affairs<br/>University of Texas at Austin</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After the first author completed an inductive thematic analysis of 224 open-ended survey responses on police chief credentials, Professor Abnerâs team ran an independent Evidano analysis to check the human coding for oversights, alternative frames, and researcher bias â and declined the one extra theme it proposed.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->We found that AI can strengthen qualitative research by providing an independent check on human coding, but final decisions about theme validity should remain with researchers, who must assess whether a theme is sufficiently coherent, frequent, and supported by the data.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="2 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/anthrax-risk-farming-communities-zambia"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in PLOS Neglected Tropical Diseases</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="PLOS Neglected Tropical Diseases logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fimages%2Fpublications%2Fplos.png&w=256&q=75 1x, /_next/image?url=%2Fimages%2Fpublications%2Fplos.png&w=640&q=75 2x" src="/_next/image?url=%2Fimages%2Fpublications%2Fplos.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Chisoni Mumba, Associate Professor of Animal Health Economics at the University of Zambia" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fmumba-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fmumba-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fmumba-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Chisoni Mumba</p><p class="text-sm text-gray-500">Associate Professor of Animal Health Economics<br/>University of Zambia</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">In a hybrid qualitative study of six focus groups near Zambiaâs game management areas, Professor Mumbaâs team used Evidano to run sentiment analysis on the transcripts, then checked every theme it surfaced against the original transcripts and verbatim quotes.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano gave us a layer of insight we would have struggled to capture through manual coding alone. It picked up the emotional tone running through the transcripts, the anxiety around eating meat that might be infected, the fear tied to livestock losses, and the frustration participants expressed toward formal health campaigns.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="3 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/cornell-clasp-adult-learning"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>
5Cornell University · Malcolm Knowles Award 2023</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Cornell University logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fcornell.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fcornell.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fcornell.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Annalisa Raymer, Senior Lecturer at Cornell University and Director of CLASP" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fraymer-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fraymer-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fraymer-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Annalisa Raymer</p><p class="text-sm text-gray-500">Senior Lecturer & Director of CLASP<br/>Cornell University</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">Dr. Raymer uploaded the transcript of an in-house CLASP film into Evidano to summarize four stakeholder groupsâ perspectives and run a thematic analysis, then compared the AIâs reading with feedback from adult-education colleagues at the AAACE conference.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->With Evidano, I feel that I have a straightforward thinking partner, rather than an internet pet eager to please.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="4 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/ai-qualitative-interview-analysis"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in the Journal of Education Research</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="National Chengchi University logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fchengchi.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fchengchi.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fchengchi.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Cheng-Ta Wu, Distinguished Professor in the College of Education at National Chengchi University" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fwu-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fwu-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fwu-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Cheng-Ta Wu</p><p class="text-sm text-gray-500">Distinguished Professor, College of Education<br/>National Chengchi University, Taiwan</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">His teamâs published article is itself a case study of Evidano: the authors demonstrate its full qualitative workflow â summaries, themes, codebook, frequency analysis, and key quotes â on elementary-school leadership interview data. They propose a humanâAI collaborative model for qualitative research.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano provided transparent traceability between extracted themes, viewpoint-driven queries, and source transcripts, which greatly streamlined the early, laborious stages of coding and quote mapping.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="5 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/preservice-teachers-generative-ai"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Educational Psychology</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Routledge logo, publisher of Educational Psychology" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Froutledge.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Froutledge.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Froutledge.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Siv M. Gamlem, Professor at Volda University College" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fgamlem-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fgamlem-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fgamlem-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Siv M. Gamlem</p><p class="text-sm text-gray-500">Professor of Education<br/>Volda University College, Norway</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After two researchers completed the initial inductive thematic analysis of 11 interviews, Professor Gamlemâs team ran the anonymised transcripts through Evidano and compared the results with their manual analysis for triangulation and validation.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano supported our research process by offering an additional lens on the interview data, helping us identify patterns that could be compared with our initial manual analysis. Its value was not in replacing interpretation, but in strengthening the transparency and robustness of our analytic decisions.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="6 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/gendered-language-student-evaluations"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Education Sciences</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="University of North Carolina Wilmington logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Funcw.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Funcw.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Funcw.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Shawn S. Savage, Assistant Professor in the Watson College of Education at UNC Wilmington" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fsavage-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fsavage-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fsavage-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Shawn S. Savage</p><p class="text-sm text-gray-500">Assistant Professor<br/>University of North Carolina Wilmington</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After multiple rounds of human coding of narrative student evaluations, Dr. Savage and Dr. Parker used Evidano to interrogate the data from a different analytic vantage point, surfacing gendered comparative distinctions they then verified through collaborative analysis.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano was most helpful because it encouraged Dr. Parker and me to revisit the data from a different analytic vantage point. It didnât replace our interpretation; it expanded the kinds of questions we asked.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="7 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/early-intervention-special-educational-needs"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>
5Published in Frontiers in Education</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Frontiers logo, publisher of Frontiers in Education" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Lawrence Meda, Director of Research and Associate Professor at Sharjah Education Academy" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fmeda-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fmeda-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fmeda-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Lawrence Meda</p><p class="text-sm text-gray-500">Director of Research & Associate Professor<br/>Sharjah Education Academy, UAE</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After translating, transcribing, and manually coding nine teacher interviews, Professor Medaâs team used Evidano to categorize participant quotes into researcher-defined themes â with every allocation manually verified by the research team.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->AI-supported tools like Evidano can enhance qualitative research when used carefully and transparently.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="8 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/bioplastic-public-acceptance"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Cambridge Prisms: Plastics</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Cambridge University Press logo, publisher of Cambridge Prisms: Plastics" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Fcambridge-university-press.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Fcambridge-university-press.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Fcambridge-university-press.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Adriana Cunha Neves, researcher at South East Technological University, Carlow" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fneves-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fneves-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fneves-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Adriana Cunha Neves</p><p class="text-sm text-gray-500">Researcher, Department of Applied Science<br/>South East Technological University, Ireland</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">Her team used Evidano for AI-assisted thematic analysis of focus group discussions about starch-protein bioplastics, helping mitigate unintentional researcher bias during interpretation.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano is particularly valuable for researchers who lack extensive experience in qualitative data analysis, offering an efficie
5nt way to organize large datasets while minimizing the influence of pre-existing knowledge and researcher bias.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="9 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/ai-literacy-employment-prospects"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published at IEEE ACDSA 2026</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="IEEE logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Fieee.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Fieee.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Fieee.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Munn Hong Lam, researcher at Universiti Tunku Abdul Rahman" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Flam-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Flam-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Flam-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Munn Hong Lam</p><p class="text-sm text-gray-500">Researcher, Faculty of Accountancy and Management<br/>Universiti Tunku Abdul Rahman, Malaysia</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">In a sequential mixed-methods pilot on AI literacy and employment prospects, his team entered the qualitative interview data into Evidano and interpreted it thematically to add depth to their survey results.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->The qualitative element of our research was supported by Evidano through assistance with thematic organisation and interpretation of interview data. This was helpful in our research workflow, particularly in identifying patterns within the responses received during the interviews.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="10 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/unmet-needs-highly-intelligent-adults"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Editor, Gifted Child Quarterly</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="William & Mary logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fwilliam-mary.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fwilliam-mary.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fwilliam-mary.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Jennifer Riedl Cross, Editor of Gifted Child Quarterly and Research Professor at the University of Louisiana at Lafayette" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fcross-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fcross-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fcross-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Jennifer Riedl Cross</p><p class="text-sm text-gray-500">Editor of Gifted Child Quarterly & Research Professor<br/>University of Louisiana at Lafayette</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">Facing more than 19,000 open-ended comments from a Mensa Foundation study of 3,443 highly intelligent adults, her team ran the responses through Evidano in batches, compared repeated analyses, and manually verified every theme and supporting quote before finalizing the findings.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Researchers can work together with Evidano, but they have a responsibility to stay in touch with the data and take steps to confirm the output is accurate and unbiased.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="11 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/fragmented-digital-identity-soft-power"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Revista de Cercetare si Interventie Sociala</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]">
5<img alt="Coat of arms of the National University of Ostroh Academy" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Fostroh-academy.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Fostroh-academy.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Fostroh-academy.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Yuliia Maslova, Professor and Head of the Department of Journalism and PR Management at the National University of Ostroh Academy" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fmaslova-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fmaslova-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fmaslova-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Yuliia Maslova</p><p class="text-sm text-gray-500">Professor & Head of Journalism and PR Management<br/>National University of Ostroh Academy, Ukraine</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">Building a conceptual model that links fragmented digital identity with soft power, Professor Maslovaâs team processed a literature sample of 51 sources with Evidano to surface recurring themes and candidate categories, then verified and interpreted every category manually during theory construction.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano helped us identify recurring themes and formulate candidate categories across a corpus of 51 literature sources. Its function was supportive rather than substitutive. The authors verified the outputs, interpreted the categories within the theoretical framework, and retained responsibility for every conceptual relation and conclusion.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="12 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/costa-rica-national-evaluation-agenda"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published by CICAP, University of Costa Rica</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="University of Costa Rica logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Funiversidad-de-costa-rica.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Funiversidad-de-costa-rica.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Funiversidad-de-costa-rica.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Esteban O. Mora-MartÃnez, lecturer and researcher at the University of Costa Rica and head of the Evaluation Section of its Planning Office" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fmora-martinez-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fmora-martinez-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fmora-martinez-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Esteban O. Mora-MartÃnez</p><p class="text-sm text-gray-500">Lecturer & Head of the Evaluation Section<br/>University of Costa Rica</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a book chapter meta-evaluating Costa Ricaâs National Evaluation Agenda, Dr. Mora-MartÃnez used Evidano to apply a single evaluation framework across ten reports spanning employment, education, health, culture, and the environment, acting as evaluator while Evidano analyzed the documents.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano helped apply the same analytical framework consistently across a diverse set of evaluation reports, making it easier to organize evidence, identify recurring patterns, and compare findings across sectors. At the same time, evaluators should remember that AI does not replace professional judgment.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="13 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/holistic-student-wellbeing-yoga-
5higher-education"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Doctoral dissertation published by UCLA</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="UCLA logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fucla.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fucla.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Johnnie Yang, Postdoctoral Fellow at the UCLA Semel Healthy Campus Initiative Center" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fyang-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fyang-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fyang-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Johnnie Yang</p><p class="text-sm text-gray-500">Postdoctoral Fellow, Semel Healthy Campus Initiative Center<br/>University of California, Los Angeles</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a convergent mixed-methods dissertation on the student wellness crisis, Johnnie Yang used Evidano to run three analyses of student journals and interview transcripts â journals alone, interviews alone, and a combined dataset â then re-read every transcript and made all final interpretations through reflexive thematic analysis.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano came in on the qualitative side, helping me organize and get an initial read on a huge amount of journal and interview data. I was also the instructor for these students, so I already had relationships and instincts going in, which meant I couldnât just take the toolâs output at face value. I went back to every transcript myself, checked it against what I actually knew about these students, looked for the stuff that didnât fit the pattern.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="14 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/hungarian-sign-language-learners"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Three TESOL Treats (TESOL-Hungary)</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="TESOL-Hungary logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Ftesol-hungary.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Ftesol-hungary.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Ftesol-hungary.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Zsuzsanna Soproni, College Professor at International Business Sc
5hool in Budapest" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fsoproni-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fsoproni-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fsoproni-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Zsuzsanna Soproni</p><p class="text-sm text-gray-500">College Professor of English and Research Methods<br/>International Business School, Budapest</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After coding 229 Hungarian-language comments from 31 adult sign language learners with the constant comparative method and an independent co-coder, Professor Soproni ran one set of open-ended responses through Evidano as an exploratory check â and found the five themes it proposed pointed to the same priority she had identified by hand.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->It was the first time Iâd used an AI tool for thematic analysis, and I was genuinely surprised by how well it handled Hungarian. At the same time, researchers need to remember that while AI can speed up and support the analysis process, it still needs careful human oversight.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="15 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/return-to-office-mandates-federal-employee-wellbeing"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Public Personnel Management</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Sage Publishing logo, publisher of Public Personnel Management" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fsage.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fsage.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fsage.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Geneviève Morin, postdoctoral researcher at the Ãcole nationale dâadministration publique and Vermont Law and Graduate School" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fmorin-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fmorin-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fmorin-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Geneviève Morin</p><p class="text-sm text-gray-500">Postdoctoral Researcher<br/>Ãcole nationale dâadministration publique</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">To study how U.S. federal employees reacted to the January 2025 return-to-office mandate, Dr. Morinâs team imported 39,788 open-ended comments from three national survey waves into Evidano, coded them against a predefined thematic grid, and manually verified the output before drawing any conclusions.<
5/p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->AI-assisted coding is a starting point, not a substitute for judgment. We validated every theme against the original comments ourselves before drawing any conclusions.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="16 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/master-health-professions-education-medical-educators"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Annals of Medicine and Medical Sciences</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="University of the Philippines seal" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fup-manila.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fup-manila.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fup-manila.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Roland Joseph D. Tan, ophthalmologist and health professions educator at the University of the Philippines Manila" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Ftan-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Ftan-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Ftan-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Roland Joseph D. Tan</p><p class="text-sm text-gray-500">Ophthalmologist & Health Professions Educator<br/>University of the Philippines Manila</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After coding semi-structured interviews and document reviews manually through reflexive thematic analysis, Dr. Tan ran the transcripts through Evidano for a second pass, which produced a complementary codebook and 11 granular themes that he compared with his own analysis before integrating both into the final thematic structure.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Researchers need to verify AI-generated interpretations against the original data, remain alert to bias and loss of contextual nuance, protect participant confidentiality, and transparently disclose how AI was used. AI should support the researcherâs analytical process, not become the researcher.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="17 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/doctoral-writing-groups-peer-feedback"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Studies in Educational Evaluation</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Monash University logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Fmonash-university.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Fmonash-university.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Fmonash-university.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Lynette Pretorius, Senior Lecturer in the School of Learning and Teaching at Monash University" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fpretorius-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fpretorius-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fpretorius-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Lynette Pretorius</p><p class="text-sm text-gray-500">Senior Lecturer, School of Learning and Teaching<br/>Monash University, Australia</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After completing reflexive thematic analysis of open-ended survey responses from 29 PhD students and their own editor reflections, Dr. Pretorius and Dr. Cahusac de Caux trialled Evidano for a different perspective on the key ideas in those reflections â and reported the overlap with their constructed themes as evidence for the trustworthiness of their coding strategy.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->AI tools can support your research, but they are not there to do the research for you. In this study, we tested Evidano to illuminate any unconscious biases we may have had about our data. As qualitative researchers, we must stay deeply engaged with our data, and we are responsible for constructing the themes that are included in the final paper.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="18 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/civilian-personnel-modern-policing"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>
5Published in Policing: An International Journal</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="Université du Québec à Trois-Rivières logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Fuqtr.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Fuqtr.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Fuqtr.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Vincent Mousseau, Professor of Forensic Science at Université du Québec à Trois-Rivières" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fmousseau-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fmousseau-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fmousseau-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Vincent Mousseau</p><p class="text-sm text-gray-500">Professor of Forensic Science<br/>Université du Québec à Trois-Rivières, Canada</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a scoping review covering 25 years of research on civilian police staff, Professor Mousseauâs team used Evidano to structure data extraction from 60 studies around a predefined coding grid, with two coders independently checking flagged studies against the original material.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->I believe researchers using AI-assisted analysis should first remain focused on their research goals: is AI actually helping to achieve those goals, or is it simply being used because it is a new and attractive technology? AI outputs should also always be checked against the original data.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="19 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/open-educational-resources-zambian-community-schools"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published in Social Sciences & Humanities Open</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="University of Zambia coat of arms" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Funiversity-of-zambia.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Funiversity-of-zambia.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Funiversity-of-zambia.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Enala Sharon Lufungulo, Lecturer and Researcher in the School of Education at the University of Zambia" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Flufungulo-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Flufungulo-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Flufungulo-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Enala Sharon Lufungulo</p><p class="text-sm text-gray-500">Lecturer & Researcher, School of Education<br/>University of Zambia</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">In a multi-method study of OER adoption across Lusaka and Chipata, Dr. Lufungulo used Evidano for document analysis, summarisation, and the initial coding of interview transcripts, then cross-checked every output against the original data, her manual coding in Microsoft Word and MAXQDA, and the studyâs theoretical framework.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->I also used Evidano as a critical sounding board during the meaning-making process. I compared its proposed interpretations with my own reflections, assumptions and deductions, which helped me consider alternative meanings and critically examine my emerging interpretations.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="20 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/neurodivergent-workplace-inclusion-belonging"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Doctoral dissertation published by the University of La Verne</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="University of La Verne wordmark" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Funiversity-of-la-verne.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Funiversity-of-la-verne.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Funiversity-of-la-verne.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Allison Leanos, adjunct professor in the LaFetra College of Education at the University of La Verne" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fleanos-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fleanos-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fleanos-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Allison Leanos</p><p class="text-sm text-gray-500">Adjunct Professor, LaFetra College of Education<br/>University of La Verne</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a descriptive phenomenological dissertation on how neurodivergent adults experience workplace inclusion and belonging initiatives, Dr. Leanos used Evidano to apply the Moustakas method to ten interview transcripts and generate initial codes and theme concepts, then cross-referenced the codebook against the transcripts and revised the meaning units by hand.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->
5Nowadays, itâs difficult to avoid AI â itâs everywhere. However, AI is not a properly trained researcher, so itâs important to use it responsibly. Using Evidano helped generate initial codes and theme concepts based on the Moustakas method, which I found helpful and time-effective. I then dissected and interpreted the data manually, which enhances the validity of the results.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="21 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/sustaining-agile-change-after-coaching"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published by Springer at XP 2026</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="University of Glasgow arms" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=256&q=75 1x, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=640&q=75 2x" src="/_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Ehikioya Obode, researcher in the College of Science & Engineering at the University of Glasgow" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fobode-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fobode-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fobode-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Ehikioya Obode</p><p class="text-sm text-gray-500">Researcher, College of Science & Engineering<br/>University of Glasgow, United Kingdom</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">After completing the thematic analysis of 16 agile-coach interviews manually, Ehikioya Obodeâs team uploaded the anonymized transcripts to Evidano for an independent thematic overview, then compared its groupings with their own and returned to the transcripts wherever the two differed.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano gave us an independent thematic overview after the manual analysis was complete. We did not use it to determine the final themes; instead, we compared its groupings with our own and returned to the transcripts where there were differences.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="22 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/autism-communication-parents-emotional-wellbeing"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>
5Published in Advance Social Science Archive Journal</span><span class="flex h-10 w-[88px] flex-shrink-0 items-center justify-end sm:w-[104px]"><img alt="GIFT University logo" loading="lazy" width="240" height="120" decoding="async" data-nimg="1" class="max-h-10 w-auto max-w-full object-contain" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-logos%2Fgift-university.webp&w=256&q=75 1x, /_next/image?url=%2Fspotlight-logos%2Fgift-university.webp&w=640&q=75 2x" src="/_next/image?url=%2Fspotlight-logos%2Fgift-university.webp&w=640&q=75"/></span></div><div class="mt-5 flex items-center gap-4"><img alt="Mehak Afzal, MPhil Applied Linguistics Scholar at GIFT University in Gujranwala, Pakistan" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fafzal-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fafzal-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fafzal-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Mehak Afzal</p><p class="text-sm text-gray-500">MPhil Applied Linguistics Scholar<br/>GIFT University, Pakistan</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a qualitative study of parents of autistic children in Gujranwala, Pakistan, Mehak Afzalâs team coded in-depth interviews in ATLAS.ti and used Evidano for theme extraction, then reviewed the generated themes themselves â merging duplicates and clarifying the ones that needed further interpretation.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano was useful in assisting with thematic analysis since it helped in grouping codes and generating themes. It helped organize patterns within the qualitative data and facilitated theme identification. However, AI-assisted analysis should complement rather than replace the researcherâs judgement and interpretation.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="23 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/actualized-leadership-profile-leadership-theories"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Doctoral dissertation published by the University of La Verne</span></div><div class="mt-5 flex items-center gap-4"><img alt="University of La Verne, where Racha Zeitoun completed her doctoral research in the LaFetra College of Education" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fzeitoun-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fzeitoun-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fzeitoun-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Racha Zeitoun</p><p class="text-sm text-gray-500">Doctor of Education, LaFetra College of Education<br/>University of La Verne</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a theory-based dissertation, Racha Zeitoun mapped the Actualized Leadership Profile against transformational, adaptive, connective, and servant leadership through a qualitative comparative analysis of the foundational literature â the kind of document-heavy conceptual work Evidano is built to supp
5ort.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->I see AI-assisted analysis as a useful support tool rather than a substitute for scholarly judgment. It can help identify patterns, organize data, and generate potential coding suggestions, but the researcher has to determine whether those patterns are actually supported by the theory and the data.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div><div aria-label="24 of 24" aria-roledescription="slide" class="flex-none p-2" role="group" style="width:33.333333333333336%"><div class="grid h-full gap-4" style="grid-template-rows:repeat(1, minmax(0, 1fr))"><a class="group flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-6 shadow-sm transition-all duration-300 hover:-translate-y-1 hover:border-blue-200 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[rgb(31,119,206)] focus-visible:ring-offset-2" href="/research-spotlights/cop29-climate-leadership-rhetoric-azerbaijan"><div class="flex items-start justify-between gap-3"><span class="inline-flex w-fit items-center gap-1.5 rounded-full bg-[rgb(31,119,206)] px-3 py-1 text-xs font-semibold text-white shadow-sm"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-award h-3.5 w-3.5 flex-shrink-0" aria-hidden="true"><path d="m15.477 12.89 1.515 8.526a.5.5 0 0 1-.81.47l-3.58-2.687a1 1 0 0 0-1.197 0l-3.586 2.686a.5.5 0 0 1-.81-.469l1.514-8.526"></path><circle cx="12" cy="8" r="6"></circle></svg>Published on SSRN</span></div><div class="mt-5 flex items-center gap-4"><img alt="Chau Pham, independent researcher from Vietnam" loading="lazy" width="80" height="80" decoding="async" data-nimg="1" class="h-20 w-20 flex-shrink-0 rounded-full border-2 border-blue-100 object-cover" style="color:transparent" srcSet="/_next/image?url=%2Fspotlight-photos%2Fpham-card.webp&w=96&q=75 1x, /_next/image?url=%2Fspotlight-photos%2Fpham-card.webp&w=256&q=75 2x" src="/_next/image?url=%2Fspotlight-photos%2Fpham-card.webp&w=256&q=75"/><div class="min-w-0"><p class="text-lg font-bold text-gray-900">Chau Pham</p><p class="text-sm text-gray-500">Independent Researcher<br/>Vietnam</p></div></div><p class="mt-4 text-sm leading-relaxed text-gray-600">For a thematic analysis of President Ilham Aliyevâs COP29 speeches, Chau Pham used Evidano to visualize recurring patterns in the language â including the prominence of words such as gas, energy, green, and oil â while the coding, theme development, and interpretation stayed with the researcher.</p><blockquote class="mt-4 border-l-[3px] border-[rgb(31,119,206)]/50 pl-4"><p class="text-sm italic leading-relaxed text-gray-700 line-clamp-5">â<!-- -->Evidano was helpful in identifying rhetorical patterns, a crucial step in the initial research phase. Researchers should keep in mind, however, the importance of original critical analysis and the development of a more nuanced argumentation, which cannot be replaced by any AI tool.<!-- -->â</p></blockquote><span class="mt-auto inline-flex items-center gap-1.5 pt-5 text-sm font-semibold text-[rgb(31,119,206)]">Read the spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right h-4 w-4 transition-transform group-hover:translate-x-1"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></span></a></div></div></div></div><button aria-label="Previous spotlight" class="absolute -left-3 top-1/2 hidden h-10 w-10 -translate-y-1/2 items-center justify-center rounded-full border border-gray-200 bg-white text-gray-600 shadow-md transition-colors hover:bg-blue-50 hover:text-[rgb(31,119,206)] sm:flex" type="button"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-left h-5 w-5"><path d="m15 18-6-6 6-6"></path></svg></button><button aria-label="Next spotlight" class="absolute -right-3 top-1/2 hidden h-10 w-10 -translate-y-1/2 items-center justify-center rounded-full border border-gray-200 bg-white text-gray-600 shadow-md transition-colors hover:bg-blue-50 hover:text-[rgb(31,119,206)] sm:flex" type="button"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-right h-5 w-5"><path d="m9 18 6-6-6-6"></path></svg></button></div><div class="mt-6 flex flex-wrap justify-center gap-x-1.5 gap-y-2 px-4 sm:gap-x-2"><button aria-current="true" aria-label="Go to slide 1" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-7 bg-[rgb(31,119,206)]"></span></button><button aria-current="false" aria-label="Go to slide 2" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 3" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 4" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 5" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 6" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 7" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 8" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 9" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 10" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 11" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 12" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 13" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 14" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 15" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 16" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 17" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 18" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 19" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 20" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 21" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button><button aria-current="false" aria-label="Go to slide 22" class="flex h-6 w-5 shrink-0 items-center justify-center sm:w-6" type="button"><span class="h-2.5 rounded-full transition-all w-2.5 bg-gray-300 hover:bg-gray-400"></span></button></div></section><section aria-labelledby="evidence-explorer-heading" class="mt-14"><div class="flex flex-wrap items-end justify-between gap-3"><div><h2 class="text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl" id="evidence-explorer-heading">Published research that used Evidano</h2></div><a class="text-sm font-semibold text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/case-studies">All case studies</a></div><div class="mt-6 flex flex-wrap gap-2" role="group" aria-label="Filter published research"><button aria-pressed="true" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-[rgb(31,119,206)] bg-[rgb(31,119,206)] text-white" type="button">All<!-- --> <span class="tabular-nums opacity-70">54</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Dissertations, faculty research, peer-reviewed studies and methodological transparency." type="button">Academia<!-- --> <span class="tabular-nums opacity-70">35</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="UN and donor evaluations, monitoring and evaluation, multi-country programmes." type="button">Evaluation<!-- --> <span class="tabular-nums opacity-70">15</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Public consultations, citizen comments, policy evaluation and departmental research." type="button">Government<!-- --> <span class="tabular-nums opacity-70">
59</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Patient and clinician research, implementation science, service evaluation, public health." type="button">Healthcare<!-- --> <span class="tabular-nums opacity-70">7</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Reflexive, semantic and latent coding of patterns across a corpus." type="button">Thematic<!-- --> <span class="tabular-nums opacity-70">33</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Systematic, scoping, rapid and integrative reviews; meta-synthesis and meta-ethnography." type="button">Synthesis<!-- --> <span class="tabular-nums opacity-70">4</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Glaserian, Straussian and constructivist grounded theory; constant comparison; the Gioia method." type="button">Grounded theory<!-- --> <span class="tabular-nums opacity-70">3</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Narrative inquiry and analysis, discourse and critical discourse analysis, conversation analysis." type="button">Narrative<!-- --> <span class="tabular-nums opacity-70">3</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Conventional, directed and summative content analysis; framework and template analysis; document analysis." type="button">Content analysis<!-- --> <span class="tabular-nums opacity-70">23</span></button><button aria-pressed="false" class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-200 bg-white text-gray-600 hover:border-[rgb(31,119,206)]/40 hover:text-[rgb(31,119,206)]" title="Outcome harvesting and mapping, QCA, case-based impact evaluation, ripple effects mapping." type="button">Outcomes<!-- --> <span class="tabular-nums opacity-70">2</span></button></div><div aria-live="polite" class="sr-only">54<!-- --> <!-- -->studies shown</div><ul class="mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3"><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="University of Melbourne logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=16&q=75 16w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=32&q=75 32w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=48&q=75 48w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=64&q=75 64w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=96&q=75 96w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=128&q=75 128w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=256&q=75 256w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=384&q=75 384w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=640&q=75 640w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=750&q=75 750w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=828&q=75 828w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=1080&q=75 1080w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=1200&q=75 1200w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=1920&q=75 1920w, /_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fimages%2Fpublications%2Fmelbourne.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/oxford-melbourne-ai-interview-analysis">
5Volda and Melbourne researchers used AI interview analysis to triangulate manual coding</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">Two researchers coded 11 interviews by hand with over 90% agreement, then ran the anonymised transcripts through Evidano and compared the results for triangulation and validation.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">209</span> <span class="text-gray-500">survey participants, a 97% response rate</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Educational Psychology 46(1): 27â51 (Routledge / Taylor & Francis), open access</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/cite-us#pub-gamlem-2025">See how it was cited<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/research-spotlights/preservice-teachers-generative-ai">Read the researcher spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="Stanford University logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Fstanford.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/stanford-uc-davis-ai-cross-check-coding">Stanford and UC Davis researchers used AI to cross-check their qualitative coding</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">A published mixed-methods study uploaded deidentified transcripts into Evidano to cross-check its themes. Every AI code was reviewed by the researcher.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">9</span> <span class="text-gray-500">interviews analyzed</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Getting Down to Facts III technical report (Stanford Graduate School of Education / SCALE Initiative), May 2026</p></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="Education Sciences journal logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=16&q=75 16w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=32&q=75 32w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=48&q=75 48w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=64&q=75 64w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=96&q=75 96w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=128&q=75 128w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=256&q=75 256w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=384&q=75 384w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=640&q=75 640w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=750&q=75 750w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=828&q=75 828w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=1080&q=75 1080w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=1200&q=75 1200w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=1920&q=75 1920w, /_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fimages%2Fpublications%2Feducation_science.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/education-sciences-2026-ai-qualitative-analysis">UNC Wilmington: AI-assisted qualitative coding of student evaluations across 22 courses</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">A peer-reviewed 2026 Education Sciences study used Evidano (previously AILYZE) as a thought partner after three rounds of human coding, surfacing a gender pattern the team had missed.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">
522</span> <span class="text-gray-500">coursesâ open-ended student evaluation comments analyzed</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Education Sciences (MDPI), 16(3), 448, open access</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/cite-us#pub-parker-savage-2026">See how it was cited<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/research-spotlights/gendered-language-student-evaluations">Read the researcher spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="Cambridge University Press logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Fcambridge-university-press.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/cambridge-prisms-bioplastics-focus-groups">South East Technological University: AI focus group thematic analysis of bioplastics</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">Peer-reviewed, open-access research from Ireland used Evidano (previously AILYZE) to support focus group thematic analysis and help mitigate unintentional bias.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">9</span> <span class="text-gray-500">themes from the focus group thematic analysis</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Cambridge Prisms: Plastics (Cambridge University Press), 4, e7, open access with open peer review</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/research-spotlights/bioplastic-public-acceptance">Read the researcher spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="Frontiers logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Ffrontiers.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/frontiers-education-braun-clarke-thematic-analysis">Sharjah Education Academy: AI thematic analysis of 9 teacher interviews, human-verified</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">
5Published in Frontiers in Education (2026): encrypted data, human-verified themes, and a transparent AI coding workflow across English and Arabic interviews.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">9</span> <span class="text-gray-500">Teachers interviewed</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Frontiers in Education, 11:1690181 (Frontiers Media, 2026), open access</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/cite-us#pub-meda-2026">See how it was cited<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/research-spotlights/early-intervention-special-educational-needs">Read the researcher spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="LUT University logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Flut.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Flut.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Flut.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/lut-michigan-global-survey-triangulation">LUT University & University of Michigan: AI triangulation of a 490-response global survey</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">A research team at LUT University (Finland) and the University of Michigan (USA) used Evidano (previously AILYZE) alongside manual coding to analyze a global survey, published by Springer in 2026.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">490</span> <span class="text-gray-500">end-user responses analyzed</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Lecture Notes in Business Information Processing vol. 574 (Springer), ICSOB 2025 proceedings, pp. 394â410, open access</p></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="University of Glasgow arms" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Fglasgow.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/glasgow-springer-xp-triangulation">University of Glasgow used AI triangulation on a 16-interview thematic analysis</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">Inside a Springer-published University of Glasgow study that used Evidano to generate an independent thematic overview and triangulate its six themes.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">16</span> <span class="text-gray-500">semi-structured interviews, about 60 minutes each</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Agile Processes in Software Engineering and Extreme Programming, XP 2026, Springer LNB
5IP 578, pp. 3â19, open access</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/research-spotlights/sustaining-agile-change-after-coaching">Read the researcher spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="UCLA logo" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Fucla.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Fucla.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Fucla.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/ucla-dissertation-holistic-wellbeing-ai-coding">UCLA dissertation used AI-assisted qualitative coding on student journals and interviews</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">A UCLA doctoral dissertation ran three separate Evidano analyses across 18 studentsâ journals and interview transcripts, then reviewed and refined every code by hand.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">18</span> <span class="text-gray-500">students in the qualitative sample</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">UCLA Electronic Theses and Dissertations, eScholarship (University of California), 2026</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/cite-us#pub-yang-2026">See how it was cited<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/research-spotlights/holistic-student-wellbeing-yoga-
5higher-education">Read the researcher spotlight<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Published research</span><span class="text-xs text-gray-400">2026</span></div><span class="relative block h-9 w-[104px] flex-shrink-0"><img alt="University of Split arms" loading="lazy" decoding="async" data-nimg="fill" class="object-contain object-right" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="104px" srcSet="/_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=16&q=75 16w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=32&q=75 32w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=48&q=75 48w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=64&q=75 64w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=96&q=75 96w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=128&q=75 128w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=256&q=75 256w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=384&q=75 384w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=640&q=75 640w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=750&q=75 750w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=828&q=75 828w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=1080&q=75 1080w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=1200&q=75 1200w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=1920&q=75 1920w, /_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=2048&q=75 2048w" src="/_next/image?url=%2Fcase-study-logos%2Funiversity-split.png&w=2048&q=75"/></span></div><h3 class="mt-3 font-semibold text-gray-900 text-lg"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/case-studies/university-split-transgender-media-representation">University of Split thesis used AI-triangulated thematic coding on 8 interviews</a></h3><p class="mt-2 text-gray-600 line-clamp-3 text-sm">Initial thematic coding of 8 in-depth interviews was processed through Evidano to support analytic triangulation, then reviewed and verified by the authors.</p><p class="mt-3 text-sm"><span class="font-bold text-[rgb(31,119,206)]">8</span> <span class="text-gray-500">in-depth interviews with transgender women</span></p><div class="mt-auto pt-4"><p class="truncate text-xs text-gray-400">Bachelorâs thesis, University of Split, Repository of the Faculty of Humanities and Social Sciences (2026)</p><div class="relative z-10 mt-2 flex flex-wrap gap-x-3 gap-y-1"><a class="inline-flex items-center gap-1 text-xs font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700" href="/cite-us#pub-stanicic-2026">See how it was cited<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right h-3 w-3" aria-hidden="true"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></a></div></div></article></li></ul><button class="mt-6 rounded-full border border-gray-200 bg-white px-5 py-2.5 text-sm font-semibold text-gray-700 transition-colors hover:border-[rgb(31,119,206)] hover:text-[rgb(31,119,206)] focus:outline-none focus:ring-4 focus:ring-blue-100" type="button">Show all 54 studies</button></section><section aria-labelledby="methods-heading" class="mt-14"><h2 class="text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl" id="methods-heading">Research methods, explained</h2><ul class="mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3"><li><article class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="h-24 w-full"><div aria-hidden="true" class="relative h-full w-full overflow-hidden" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #1E3A8A 0%, #3B82F6 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><rect fill="rgba(255,255,255,0.20)" height="52" rx="4" transform="rotate(-8 62 52)" width="40" x="42" y="26"></rect><rect fill="rgba(255,255,255,0.42)" height="52" rx="4" transform="rotate(-3 74 50)" width="40" x="54" y="24"></rect><rect fill="rgba(255,255,255,0.92)" height="54" rx="4" width="42" x="72" y="23"></rect><g fill="#0F2F5C" opacity="0.35"><rect height="3" rx="1.5" width="26" x="80" y="33"></rect><rect height="3" rx="1.5" width="20" x="80" y="42"></rect><rect height="3" rx="1.5" width="24" x="80" y="51"></rect><rect height="3" rx="1.5" width="14" x="80" y="60"></rect></g></g></svg></div></div><div class="flex flex-1 flex-col p-5">
5<span class="w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Social and Cultural Insights</span><h3 class="mt-3 text-base font-semibold leading-snug text-gray-900"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/blogs/social-listening">Social Listening: qualitative analysis of public digital talk</a></h3><p class="mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600">Beyond dashboards: designing queries, cleaning and sampling social data, reading conversations in context, and the representativeness caveats that keep findings honest.</p></div></article></li><li><article class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="h-24 w-full"><div aria-hidden="true" class="relative h-full w-full overflow-hidden" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z" fill="rgba(255,255,255,0.92)"></path><g fill="#2A0F5E" opacity="0.45"><rect height="4" rx="2" width="34" x="58" y="36"></rect><rect height="4" rx="2" width="24" x="58" y="46"></rect></g><path d="M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z" fill="rgba(255,255,255,0.92)"></path></g></svg></div></div><div class="flex flex-1 flex-col p-5"><span class="w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Customer Experience and Voice-of-Customer Research</span><h3 class="mt-3 text-base font-semibold leading-snug text-gray-900"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/blogs/voice-of-customer-interviews">Voice-of-Customer Interviews: from customer words to design requirements</a></h3><p class="mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600">The VoC discipline: eliciting needs in customersâ own language, structuring them without losing the voice â Griffin and Hauserâs empirical findings.</p></div></article></li><li><article class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="h-24 w-full"><div aria-hidden="true" class="relative h-full w-full overflow-hidden" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #3730A3 0%, #6366F1 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><rect fill="rgba(255,255,255,0.20)" height="60" rx="5" width="56" x="52" y="20"></rect><rect fill="rgba(255,255,255,0.92)" height="7" rx="3.5" width="7" x="60" y="30"></rect><rect fill="rgba(255,255,255,0.42)" height="4" rx="2" width="30" x="72" y="31.5"></rect><rect fill="rgba(255,255,255,0.92)" height="7" rx="3.5" width="7" x="60" y="46"></rect><path d="M61.5 49.5l2 2 3.5-3.5" stroke="#0F2F5C" stroke-linecap="round" stroke-width="1.6"></path><rect fill="rgba(255,255,255,0.92)" height="4" rx="2" width="24" x="72" y="47.5"></rect><rect fill="rgba(255,255,255,0.42)" height="7" rx="3.5" width="7" x="60" y="62"></rect><rect fill="rgba(255,255,255,0.42)" height="4" rx="2" width="34" x="72" y="63.5"></rect></g></svg></div></div><div class="flex flex-1 flex-col p-5"><span class="w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">User Experience and Human-Centered Design</span>
5<h3 class="mt-3 text-base font-semibold leading-snug text-gray-900"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/blogs/think-aloud-protocol">Think-Aloud Protocol: hearing reasoning as it happens</a></h3><p class="mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600">Concurrent and retrospective think-aloud: the EricssonâSimon rules that keep verbal reports valid, running sessions without leading, and analysing the streams.</p></div></article></li><li><article class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="h-24 w-full"><div aria-hidden="true" class="relative h-full w-full overflow-hidden" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0E7490 0%, #22B8D4 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M42 26h44a6 6 0 0 1 6 6v20a6 6 0 0 1-6 6H60l-12 9V58h-6a6 6 0 0 1-6-6V32a6 6 0 0 1 6-6z" fill="rgba(255,255,255,0.92)"></path><path d="M100 44h18a6 6 0 0 1 6 6v16a6 6 0 0 1-6 6h-4v8l-10-8h-4a6 6 0 0 1-6-6V50a6 6 0 0 1 6-6z" fill="rgba(255,255,255,0.42)"></path></g></svg></div></div><div class="flex flex-1 flex-col p-5"><span class="w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Exploratory and Contextual Inquiry</span><h3 class="mt-3 text-base font-semibold leading-snug text-gray-900"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/blogs/diary-studies-or-experience-sampling">Diary Studies and Experience Sampling: research across time</a></h3><p class="mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600">Capturing life as it is lived: interval, signal, and event-based designs, protocol and burden decisions, compliance, and analysing within-person change.</p></div></article></li><li><article class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="h-24 w-full"><div aria-hidden="true" class="relative h-full w-full overflow-hidden" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0E7490 0%, #22B8D4 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M42 26h44a6 6 0 0 1 6 6v20a6 6 0 0 1-6 6H60l-12 9V58h-6a6 6 0 0 1-6-6V32a6 6 0 0 1 6-6z" fill="rgba(255,255,255,0.92)"></path><path d="M100 44h18a6 6 0 0 1 6 6v16a6 6 0 0 1-6 6h-4v8l-10-8h-4a6 6 0 0 1-6-6V50a6 6 0 0 1 6-6z" fill="rgba(255,255,255,0.42)"></path></g></svg></div></div><div class="flex flex-1 flex-col p-5"><span class="w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Participatory and Collaborative Approaches</span><h3 class="mt-3 text-base font-semibold leading-snug text-gray-900"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/blogs/empowerment-evaluation">Empowerment Evaluation: building a programmeâs capacity to evaluate itself</a></h3><p class="mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600">Fettermanâs approach: communities assess their own programmes with an evaluator as coach â the three steps, ten principles, a worked case, and the independence debate.</p></div></article></li><li><article class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="h-24 w-full"><div aria-hidden="true" class="relative h-full w-full overflow-hidden" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z" fill="rgba(255,255,255,0.92)"></path><g fill="#2A0F5E" opacity="0.45"><rect height="4" rx="2" width="34" x="58" y="36"></rect><rect height="4" rx="2" width="24" x="58" y="46"></rect></g><path d="M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z" fill="rgba(255,255,255,0.92)"></path></g></svg></div></div><div class="flex flex-1 flex-col p-5">
5<span class="w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Developmental and Utilization-Focused Evaluation</span><h3 class="mt-3 text-base font-semibold leading-snug text-gray-900"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/blogs/utilization-focused-evaluation">Utilization-Focused Evaluation: designing for use from day one</a></h3><p class="mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600">Pattonâs UFE: identify the primary intended users, negotiate intended uses, and make every design decision with them â framework, worked case, and the turnover risk.</p></div></article></li></ul><p class="mt-6 text-sm text-gray-600"><a class="font-semibold text-[rgb(31,119,206)] hover:text-blue-700" href="/blogs/methods">Browse all<!-- --> <!-- -->116<!-- --> <!-- -->methodologies in the directory â</a></p></section><section aria-labelledby="trust-heading" class="mt-14"><h2 class="text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl" id="trust-heading">Research, accuracy and responsible AI</h2><p class="mt-2 max-w-3xl text-base leading-relaxed text-gray-600">How Evidano's output has been evaluated, how its models were built, how your data is handled, and how to disclose or cite it in your own work.</p><ul class="mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3"><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-scale h-[18px] w-[18px]"><path d="m16 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z"></path><path d="m2 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z"></path><path d="M7 21h10"></path><path d="M12 3v18"></path><path d="M3 7h2c2 0 5-1 7-2 2 1 5 2 7 2h2"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/human-vs-ai">Human vs AI: validated accuracy benchmarks</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Three head-to-head comparisons against expert human analysis â 371 interview transcripts with Arizona State and Penn State, 298 evaluation reports for a UN evaluation group, and UNICEFâs manual-coding review.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-cpu h-[18px] w-[18px]"><rect width="16" height="16" x="4" y="4" rx="2"></rect><rect width="6" height="6" x="9" y="9" rx="1"></rect><path d="M15 2v2"></path><path d="M15 20v2"></path><path d="M2 15h2"></path><path d="M2 9h2"></path><path d="M20 15h2"></path><path d="M20 9h2"></path><path d="M9 2v2"></path><path d="M9 20v2"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/how-we-trained-our-ai-models">How Evidanoâs models were trained</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Model provenance for research-ethics review: a provenance-tiered curated corpus, and customer uploads, prompts and outputs excluded from training entirely.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">
5Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-shield-check h-[18px] w-[18px]"><path d="M20 13c0 5-3.5 7.5-7.66 8.95a1 1 0 0 1-.67-.01C7.5 20.5 4 18 4 13V6a1 1 0 0 1 1-1c2 0 4.5-1.2 6.24-2.72a1.17 1.17 0 0 1 1.52 0C14.51 3.81 17 5 19 5a1 1 0 0 1 1 1z"></path><path d="m9 12 2 2 4-4"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/data-security">Data security for qualitative research</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Encryption in transit and at rest, customer-controlled deletion, regional storage, and SOC 2 Type 2, GDPR, HIPAA-ready and CCPA/CPRA compliance.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-book-open-check h-[18px] w-[18px]"><path d="M12 21V7"></path><path d="m16 12 2 2 4-4"></path><path d="M22 6V4a1 1 0 0 0-1-1h-5a4 4 0 0 0-4 4 4 4 0 0 0-4-4H3a1 1 0 0 0-1 1v13a1 1 0 0 0 1 1h6a3 3 0 0 1 3 3 3 3 0 0 1 3-3h6a1 1 0 0 0 1-1v-1.3"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/cite-us">How to cite and disclose Evidano</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Citation formats in APA, MLA, Chicago, Harvard and Vancouver, methods-section wording per workflow, and an AI-policy review of 41 journals across 8 disciplines.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-leaf h-[18px] w-[18px]"><path d="M11 20A7 7 0 0 1 9.8 6.1C15.5 5 17 4.48 19 2c1 2 2 4.18 2 8 0 5.5-4.78 10-10 10Z"></path><path d="M2 21c0-3 1.85-5.36 5.08-6C9.5 14.52 12 13 13 12"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/environmental-impact">Environmental impact of an analysis workflow</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Measured energy and water footprint of a typical project, with regional comparisons and mitigation.</p><div class="mt-auto pt-4"></div></article></li></ul></section><section aria-labelledby="comparisons-heading" class="mt-14"><h2 class="text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl" id="comparisons-heading">Compare qualitative analysis software</h2><p class="mt-2 max-w-3xl text-base leading-relaxed text-gray-600">Evidence-based comparisons against NVivo, MAXQDA, ATLAS.ti, Delve and Dedoose, drawn from each vend
5or's own published terms and prices.</p><ul class="mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 "><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-scale h-[18px] w-[18px]"><path d="m16 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z"></path><path d="m2 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z"></path><path d="M7 21h10"></path><path d="M12 3v18"></path><path d="M3 7h2c2 0 5-1 7-2 2 1 5 2 7 2h2"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/alternatives">The best qualitative data analysis tools, compared</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Evidano, NVivo, MAXQDA, ATLAS.ti, Delve, Dovetail, Dedoose and Taguette compared on published accuracy evidence, codebook support, quote traceability, languages and price â with per-tool alternative guides.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calculator h-[18px] w-[18px]"><rect width="16" height="20" x="4" y="2" rx="2"></rect><line x1="8" x2="16" y1="6" y2="6"></line><line x1="16" x2="16" y1="14" y2="18"></line><path d="M16 10h.01"></path><path d="M12 10h.01"></path><path d="M8 10h.01"></path><path d="M12 14h.01"></path><path d="M8 14h.01"></path><path d="M12 18h.01"></path><path d="M8 18h.01"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/pricing-comparison">Compare qualitative analysis software pricing</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">
5An interactive cost calculator for your own scenario against NVivo, MAXQDA, ATLAS.ti, Delve and Dedoose, using each vendorâs official checkout prices, segmented by student, academic, non-profit and commercial use.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-shield-check h-[18px] w-[18px]"><path d="M20 13c0 5-3.5 7.5-7.66 8.95a1 1 0 0 1-.67-.01C7.5 20.5 4 18 4 13V6a1 1 0 0 1 1-1c2 0 4.5-1.2 6.24-2.72a1.17 1.17 0 0 1 1.52 0C14.51 3.81 17 5 19 5a1 1 0 0 1 1 1z"></path><path d="m9 12 2 2 4-4"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/data-security-comparison">Compare data security across QDA tools</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">A head-to-head security comparison sourced from each vendorâs own terms â subprocessor chains, AI model ownership, human review, training use and encryption posture.</p><div class="mt-auto pt-4"></div></article></li></ul></section><section aria-labelledby="capabilities-heading" class="mt-14"><h2 class="text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl" id="capabilities-heading">Capabilities by data type</h2><ul class="mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3"><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-sparkles h-[18px] w-[18px]"><path d="M9.937 15.5A2 2 0 0 0 8.5 14.063l-6.135-1.582a.5.5 0 0 1 0-.962L8.5 9.936A2 2 0 0 0 9.937 8.5l1.582-6.135a.5.5 0 0 1 .963 0L14.063 8.5A2 2 0 0 0 15.5 9.937l6.135 1.581a.5.5 0 0 1 0 .964L15.5 14.063a2 2 0 0 0-1.437 1.437l-1.582 6.135a.5.5 0 0 1-.963 0z"></path><path d="M20 3v4"></path><path d="M22 5h-4"></path><path d="M4 17v2"></path><path d="M5 18H3"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/thematic-analysis-software">Thematic analysis software</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">AI-native thematic analysis end to end: inductive or codebook-driven coding in 100+ languages, with every theme backed by clickable source quotes.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">
5Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-cpu h-[18px] w-[18px]"><rect width="16" height="16" x="4" y="4" rx="2"></rect><rect width="6" height="6" x="9" y="9" rx="1"></rect><path d="M15 2v2"></path><path d="M15 20v2"></path><path d="M2 15h2"></path><path d="M2 9h2"></path><path d="M20 15h2"></path><path d="M20 9h2"></path><path d="M9 2v2"></path><path d="M9 20v2"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/ai-thematic-analysis">AI thematic analysis: accuracy, methods, and limits</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">What published agreement studies show about AI coding, how AI maps onto Braun and Clarkeâs phases, and a workflow you can defend to reviewers.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-book-open h-[18px] w-[18px]"><path d="M12 7v14"></path><path d="M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/ai-qualitative-coding">AI qualitative coding with your own codebook</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Deductive, codebook-driven coding across a full dataset, with an auditable source quote behind every code application.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-quote h-[18px] w-[18px]"><path d="M16 3a2 2 0 0 0-2 2v6a2 2 0 0 0 2 2 1 1 0 0 1 1 1v1a2 2 0 0 1-2 2 1 1 0 0 0-1 1v2a1 1 0 0 0 1 1 6 6 0 0 0 6-6V5a2 2 0 0 0-2-2z"></path><path d="M5 3a2 2 0 0 0-2 2v6a2 2 0 0 0 2 2 1 1 0 0 1 1 1v1a2 2 0 0 1-2 2 1 1 0 0 0-1 1v2a1 1 0 0 0 1 1 6 6 0 0 0 6-6V5a2 2 0 0 0-2-2z"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/quote-traceability">Source-traceable quotes</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Why hallucinated quotes are the central risk of AI qualitative analysis, and how clickable source-linked evidence makes every theme verifiable.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">
5Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-languages h-[18px] w-[18px]"><path d="m5 8 6 6"></path><path d="m4 14 6-6 2-3"></path><path d="M2 5h12"></path><path d="M7 2h1"></path><path d="m22 22-5-10-5 10"></path><path d="M14 18h6"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/multilingual-qualitative-analysis">Multilingual qualitative analysis</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Analyze interviews and surveys in 100+ languages â code in the original language or translate first, with transcription built into the workflow.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-sparkles h-[18px] w-[18px]"><path d="M9.937 15.5A2 2 0 0 0 8.5 14.063l-6.135-1.582a.5.5 0 0 1 0-.962L8.5 9.936A2 2 0 0 0 9.937 8.5l1.582-6.135a.5.5 0 0 1 .963 0L14.063 8.5A2 2 0 0 0 15.5 9.937l6.135 1.581a.5.5 0 0 1 0 .964L15.5 14.063a2 2 0 0 0-1.437 1.437l-1.582 6.135a.5.5 0 0 1-.963 0z"></path><path d="M20 3v4"></path><path d="M22 5h-4"></path><path d="M4 17v2"></path><path d="M5 18H3"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/features">All Evidano features</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Thematic, content, frequency and cross-segment analysis, AI avatar interviewing, transcription, translation, web and social data collection, and visualization.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-mic h-[18px] w-[18px]"><path d="M12 2a3 3 0 0 0-3 3v7a3 3 0 0 0 6 0V5a3 3 0 0 0-3-3Z"></path><path d="M19 10v2a7 7 0 0 1-14 0v-2"></path><line x1="12" x2="12" y1="19" y2="22"></line></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/speech-to-text">Transcription for research audio and video</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Multi-language transcription with speaker diarization, with a page per supported language.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">
5Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-book-open h-[18px] w-[18px]"><path d="M12 7v14"></path><path d="M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/image-to-text">Image to text for handwriting, manuscripts and scans</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Transcribe photographs, scans and PDFs, with a page of real sample pages for every supported script, hand and document type.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-languages h-[18px] w-[18px]"><path d="m5 8 6 6"></path><path d="m4 14 6-6 2-3"></path><path d="M2 5h12"></path><path d="M7 2h1"></path><path d="m22 22-5-10-5 10"></path><path d="M14 18h6"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/translation">Translation for multilingual research</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Translate PDF, DOCX, XLSX and TXT sources across 100+ languages, with a page per language pair.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-globe h-[18px] w-[18px]"><circle cx="12" cy="12" r="10"></circle><path d="M12 2a14.5 14.5 0 0 0 0 20 14.5 14.5 0 0 0 0-20"></path><path d="M2 12h20"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/getdata">Collect web and social media data</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Turn URLs and bulk lists into structured datasets across 82 platform types, ready for analysis.</p><div class="mt-auto pt-4"></div></article></li><li><article class="group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]"><div class="flex items-start justify-between gap-3"><div class="flex flex-wrap items-center gap-2"><span class="rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]">
5Resource</span></div><span aria-hidden="true" class="inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-book-open h-[18px] w-[18px]"><path d="M12 7v14"></path><path d="M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z"></path></svg></span></div><h3 class="mt-3 font-semibold text-gray-900 text-base"><a class="after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100" href="/guides">Product documentation and tutorials</a></h3><p class="mt-2 text-gray-600 line-clamp-2 text-sm">Step-by-step documentation for using Evidano itself â getting started, workflows, troubleshooting and reference.</p><div class="mt-auto pt-4"></div></article></li></ul></section><section class="mt-16 border-t border-gray-100 pt-10"><h2 class="text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl">Latest articles</h2><p class="mt-2 max-w-3xl text-base leading-relaxed text-gray-600">Commentary connecting newly published studies to reproducible analysis workflows.</p></section><div class="mt-8"><div class="w-full"><form class="relative" role="search" action="/blogs"><label class="sr-only" for="blog-search">Search blog articles</label><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-search pointer-events-none absolute left-4 top-1/2 h-5 w-5 -translate-y-1/2 text-gray-400" aria-hidden="true"><circle cx="11" cy="11" r="8"></circle><path d="m21 21-4.3-4.3"></path></svg><input class="w-full rounded-full border border-gray-200 bg-white py-3.5 pl-12 pr-28 text-base text-gray-800 shadow-[0_2px_12px_rgb(0,0,0,0.04)] transition-colors placeholder:text-gray-400 focus:border-[rgb(31,119,206)] focus:outline-none focus:ring-4 focus:ring-blue-100 [&::-webkit-search-cancel-button]:appearance-none [&::-webkit-search-decoration]:appearance-none" id="blog-search" placeholder="Search articles â e.g. thematic coding, interviews, NVivo" type="search" name="q" value=""/><div class="absolute right-2 top-1/2 flex -translate-y-1/2 items-center gap-1"><button class="rounded-full bg-[rgb(31,119,206)] px-4 py-2 text-sm font-semibold text-white transition-colors hover:bg-[rgb(25,95,165)] focus:outline-none focus:ring-4 focus:ring-blue-100" type="submit">Search</button></div></form></div></div><div class="mt-6 flex flex-col gap-3"><nav aria-label="Filter articles by category" class="flex flex-wrap items-center gap-2"><span class="mr-1 text-xs font-semibold uppercase tracking-wide text-gray-400">Topics</span><a class="rounded-full border px-4 py-1.5 text-sm transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-[rgb(24,100,180)] bg-[rgb(24,100,180)] font-semibold text-white shadow-sm" href="/blogs">All</a><a class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-400 bg-white text-gray-800 shadow-sm hover:border-[rgb(31,119,206)] hover:bg-blue-50 hover:text-[rgb(31,119,206)]" href="/blogs?category=Commentary+on+News">Commentary on News</a><a class="rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-400 bg-white text-gray-800 shadow-sm hover:border-[rgb(31,119,206)] hover:bg-blue-50 hover:text-[rgb(31,119,206)]" href="/blogs?category=Research+Methods">Research Methods</a></nav></div><p class="mb-3 mt-6 text-sm text-gray-500">Showing<!-- --> <span class="font-semibold text-gray-700">10</span> <!-- -->of<!-- --> <span class="font-semibold text-gray-700">1053</span> <!-- -->articles</p><div class="mt-6"><div class="grid auto-rows-[minmax(220px,auto)] grid-cols-1 gap-6 [grid-auto-flow:row_dense] sm:grid-cols-2 lg:grid-cols-3" style="opacity:0"><div class="sm:col-span-2 sm:row-span-2"><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/climate-change-acceptance-definition-undergrads"><div class="relative w-full overflow-hidden h-40 sm:h-52"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #1D4ED8 0%, #60A5FA 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M40 76h80" stroke="rgba(255,255,255,0.42)" stroke-width="2"></path><g fill="rgba(255,255,255,0.92)"><rect height="20" rx="2" width="12" x="48" y="56" opacity="0.55"></rect><rect height="34" rx="2" width="12" x="68" y="42" opacity="0.75"></rect><rect height="46" rx="2" width="12" x="88" y="30"></rect></g><path d="M48 62 L74 48 L94 34 L112 26" fill="none" stroke="rgba(255,255,255,0.92)" stroke-linecap="round" stroke-width="2.5"></path><circle cx="112" cy="26" fill="rgba(255,255,255,0.92)" r="4"></circle></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6 sm:p-8" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2">
5<span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-2xl">Two Definitions: Climate Change Acceptance for Undergrads</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-6">Primary keyword: climate change acceptance definition. According to the PLoS One study (published August 25, 2026), researchers used a mixed-methods Delphi process to produce two consensus definitions of climate change acceptance specifically for undergraduate science students. This post explains the PLoS One findings (scope, sample sizes, dates), translates them for classroom and research decisions, and shows how AI-enabled qualitative research tools accelerate applying those definitions to interviews, open-ended surveys, and existing instruments.</p><div class="mt-1"><p class="mb-2 text-xs font-semibold uppercase tracking-wide text-gray-400">In this article</p><ul class="space-y-1.5"><li class="flex items-start gap-2 text-sm text-gray-600"><span class="mt-1.5 h-1.5 w-1.5 flex-shrink-0 rounded-full bg-[rgb(31,119,206)]"></span><span class="line-clamp-1">Key Takeaways</span></li><li class="flex items-start gap-2 text-sm text-gray-600"><span class="mt-1.5 h-1.5 w-1.5 flex-shrink-0 rounded-full bg-[rgb(31,119,206)]"></span><span class="line-clamp-1">What Happened and How the Delphi Process Worked</span></li><li class="flex items-start gap-2 text-sm text-gray-600"><span class="mt-1.5 h-1.5 w-1.5 flex-shrink-0 rounded-full bg-[rgb(31,119,206)]"></span><span class="line-clamp-1">Findings Snapshot</span></li><li class="flex items-start gap-2 text-sm text-gray-600"><span class="mt-1.5 h-1.5 w-1.5 flex-shrink-0 rounded-full bg-[rgb(31,119,206)]"></span><span class="line-clamp-1">Implications for Postsecondary Science Educators and Researchers</span></li></ul></div><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>8<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/researcher-in-the-loop-ai-ux-research-ce94f8ed"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z" fill="rgba(255,255,255,0.92)"></path><g fill="#2A0F5E" opacity="0.45"><rect height="4" rx="2" width="34" x="58" y="36"></rect><rect height="4" rx="2" width="24" x="58" y="46"></rect></g><path d="M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z" fill="rgba(255,255,255,0.92)"></path></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2">
5<span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">Researcher-in-the-loop: AI-enabled UX research</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">How the researcher-in-the-loop model governs AI-enabled UX research. Learn practical governance, stats from the August 2026 piece, and how Evidano supports this workflow.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>7<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/researcher-in-the-loop"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z" fill="rgba(255,255,255,0.92)"></path><g fill="#2A0F5E" opacity="0.45"><rect height="4" rx="2" width="34" x="58" y="36"></rect><rect height="4" rx="2" width="24" x="58" y="46"></rect></g><path d="M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z" fill="rgba(255,255,255,0.92)"></path></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2"><span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">Researcher-in-the-Loop: Governance for AI UX Research</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">
5Govern AI in qualitative UX research with the researcher-in-the-loop model from Jennifer L. Bowie (Aug 25, 2026): practical rules, risks, and tool mappings.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>6<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/qualitative-analysis-of-larc-uptake-bangladesh"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z" fill="rgba(255,255,255,0.92)"></path><g fill="#2A0F5E" opacity="0.45"><rect height="4" rx="2" width="34" x="58" y="36"></rect><rect height="4" rx="2" width="24" x="58" y="46"></rect></g><path d="M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z" fill="rgba(255,255,255,0.92)"></path></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2"><span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">Why LARC/PM Uptake Is Low: Qualitative Analysis in Bangladesh</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">Actionable guidance for researchers: qualitative analysis of LARC uptake in rural Bangladesh using AI-enabled workflows to code interviews, surface themes, and inform rights-based programs.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>6<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/qualitative-analysis-larc-uptake-bangladesh-d333f5d9-3"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0D3C6E 0%, #1F77CE 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M80 34 L56 62 M80 34 L80 62 M80 34 L104 62" stroke="rgba(255,255,255,0.42)" stroke-width="2"></path><circle cx="80" cy="30" fill="rgba(255,255,255,0.92)" r="9"></circle><circle cx="56" cy="66" fill="rgba(255,255,255,0.42)" r="6"></circle><circle cx="80" cy="66" fill="rgba(255,255,255,0.92)" r="6"></circle><circle cx="104" cy="66" fill="rgba(255,255,255,0.42)" r="6"></circle></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2">
5<span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">AI for Qualitative Analysis: LARC Uptake in Bangladesh</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">How AI-enabled qualitative analysis reveals multilevel barriers to LARC/PM uptake in rural Bangladesh, with practical steps for researchers and program teams. Read actionable methods.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>7<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/climate-change-acceptance-definition-delphi"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #3730A3 0%, #6366F1 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><rect fill="rgba(255,255,255,0.20)" height="60" rx="5" width="56" x="52" y="20"></rect><rect fill="rgba(255,255,255,0.92)" height="7" rx="3.5" width="7" x="60" y="30"></rect><rect fill="rgba(255,255,255,0.42)" height="4" rx="2" width="30" x="72" y="31.5"></rect><rect fill="rgba(255,255,255,0.92)" height="7" rx="3.5" width="7" x="60" y="46"></rect><path d="M61.5 49.5l2 2 3.5-3.5" stroke="#0F2F5C" stroke-linecap="round" stroke-width="1.6"></path><rect fill="rgba(255,255,255,0.92)" height="4" rx="2" width="24" x="72" y="47.5"></rect><rect fill="rgba(255,255,255,0.42)" height="7" rx="3.5" width="7" x="60" y="62"></rect><rect fill="rgba(255,255,255,0.42)" height="4" rx="2" width="34" x="72" y="63.5"></rect></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2">
5<span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">Consensus definitions: climate change acceptance definition</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">PLoS One (Aug 25, 2026) presents two consensus climate change acceptance definitions for undergraduates; see stats and how AI qualitative analysis accelerates survey design.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>7<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/qualitative-analysis-larc-pm-bangladesh"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0D3C6E 0%, #1F77CE 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M80 34 L56 62 M80 34 L80 62 M80 34 L104 62" stroke="rgba(255,255,255,0.42)" stroke-width="2"></path><circle cx="80" cy="30" fill="rgba(255,255,255,0.92)" r="9"></circle><circle cx="56" cy="66" fill="rgba(255,255,255,0.42)" r="6"></circle><circle cx="80" cy="66" fill="rgba(255,255,255,0.92)" r="6"></circle><circle cx="104" cy="66" fill="rgba(255,255,255,0.42)" r="6"></circle></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2"><span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">AI synthesis: qualitative analysis of LARC/PM uptake</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">AI-enabled synthesis of a PLOS ONE qualitative analysis of LARC/PM uptake in rural Bangladesh (Aug 25, 2026). Read methods, key stats, quotes, and AI research workflows.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>7<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/ai-simulation-testing-clinical"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #5B21B6 0%, #8B5CF6 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><text fill="rgba(255,255,255,0.92)" font-family="Georgia, serif" font-size="34" font-weight="700" x="38" y="62">A</text><path d="M72 50h20m0 0l-6-5m6 5l-6 5" stroke="rgba(255,255,255,0.42)" stroke-linecap="round" stroke-width="2.5"></path><text fill="rgba(255,255,255,0.92)" font-family="Georgia, serif" font-size="34" font-weight="700" x="100" y="62">æ</text></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2">
5<span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">Simulation Testing: AI Simulation Testing for Clinical Care</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">How Mayo Clinic uses AI simulation testing to close the clinical AI translation gap; practical steps for qualitative researchers and UX teams plus tools to scale evaluation.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>5<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/qualitative-analysis-contraceptive-uptake-bangladesh-d333f5d9"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z" fill="rgba(255,255,255,0.92)"></path><g fill="#2A0F5E" opacity="0.45"><rect height="4" rx="2" width="34" x="58" y="36"></rect><rect height="4" rx="2" width="24" x="58" y="46"></rect></g><path d="M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z" fill="rgba(255,255,255,0.92)"></path></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2"><span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">AI-ready Guide: qualitative analysis of contraceptive uptake</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">Apply AI-enabled qualitative analysis to LARC/PM uptake in rural Bangladesh: study stats, direct quotes, and practical researcher steps. Learn methods and next steps.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>7<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div><div class=""><div class="h-full" style="transform-style:preserve-3d;opacity:0;transform:translateY(20px)"><a class="group relative flex h-full flex-col overflow-hidden rounded-2xl border border-neutral-200/60 bg-gradient-to-b from-neutral-50/60 via-neutral-50/40 to-neutral-50/30 shadow-[0_4px_20px_rgb(0,0,0,0.04)] backdrop-blur-[4px] transition-all duration-500 ease-out hover:border-blue-200 hover:shadow-[0_8px_30px_rgb(31,119,206,0.12)]" href="/blogs/qualitative-analysis-of-larc-uptake"><div class="relative w-full overflow-hidden h-28"><div aria-hidden="true" class="relative h-full w-full overflow-hidden transition-transform duration-500 ease-out group-hover:scale-105" style="background-image:radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0D3C6E 0%, #1F77CE 100%);background-size:18px 18px, 100% 100%"><svg class="absolute inset-0 h-full w-full" preserveAspectRatio="xMidYMid meet" viewBox="0 0 160 100" xmlns="http://www.w3.org/2000/svg"><g><path d="M80 34 L56 62 M80 34 L80 62 M80 34 L104 62" stroke="rgba(255,255,255,0.42)" stroke-width="2"></path><circle cx="80" cy="30" fill="rgba(255,255,255,0.92)" r="9"></circle><circle cx="56" cy="66" fill="rgba(255,255,255,0.42)" r="6"></circle><circle cx="80" cy="66" fill="rgba(255,255,255,0.92)" r="6"></circle><circle cx="104" cy="66" fill="rgba(255,255,255,0.42)" r="6"></circle></g></svg></div></div><div class="relative z-10 flex flex-1 flex-col gap-3 p-6" style="transform:translateZ(20px)"><div class="flex flex-wrap gap-2">
5<span class="w-fit rounded-full bg-blue-50 px-3 py-1 text-xs font-medium text-[rgb(31,119,206)] ring-1 ring-blue-100">Commentary on News</span></div><div class="flex items-start justify-between gap-3"><h2 class="font-bold text-gray-800 transition-colors duration-300 group-hover:text-[rgb(31,119,206)] text-lg">AI-enabled qualitative analysis of LARC uptake</h2><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-up-right mt-1 h-5 w-5 flex-shrink-0 text-gray-300 transition-colors duration-300 group-hover:text-[rgb(31,119,206)]"><path d="M7 7h10v10"></path><path d="M7 17 17 7"></path></svg></div><p class="text-sm leading-relaxed text-gray-500 line-clamp-3">How AI speeds thematic, cross-segment insight from interviews: an AI-enabled qualitative analysis of LARC uptake in rural Bangladesh, with practical research workflows.</p><div class="mt-auto flex flex-wrap items-center justify-between gap-x-4 gap-y-2 border-t border-gray-100 pt-3"><div class="flex flex-wrap items-center gap-x-3 gap-y-1 text-xs font-medium text-gray-400"><span>Evidano</span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-calendar-days h-3.5 w-3.5" aria-hidden="true"><path d="M8 2v4"></path><path d="M16 2v4"></path><rect width="18" height="18" x="3" y="4" rx="2"></rect><path d="M3 10h18"></path><path d="M8 14h.01"></path><path d="M12 14h.01"></path><path d="M16 14h.01"></path><path d="M8 18h.01"></path><path d="M12 18h.01"></path><path d="M16 18h.01"></path></svg><time dateTime="2026-08-27">Aug 27, 2026</time></span><span class="inline-flex items-center gap-1"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-clock h-3.5 w-3.5" aria-hidden="true"><circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline></svg>6<!-- --> <!-- -->min read</span></div><span class="text-sm font-semibold text-[rgb(31,119,206)] transition-colors duration-300 group-hover:text-[rgb(25,95,165)]">Read More</span></div></div></a></div></div></div><nav aria-label="Blog pagination" class="mt-10 flex flex-col items-center gap-3"><div class="flex items-center justify-center gap-2"><span aria-disabled="true" class="flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 cursor-not-allowed border-gray-200 text-gray-600 opacity-40"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-left h-4 w-4"><path d="m15 18-6-6 6-6"></path></svg></span><a aria-current="page" aria-label="Page 1" class="flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-[rgb(31,119,206)] bg-[rgb(31,119,206)] text-white shadow-md" href="/blogs">1</a><a aria-label="Page 2" class="flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-gray-200 text-gray-600 hover:border-blue-200 hover:text-[rgb(31,119,206)]" href="/blogs?page=2">2</a><span class="px-1 text-gray-400">â¦</span><a aria-label="Page 117" class="flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-gray-200 text-gray-600 hover:border-blue-200 hover:text-[rgb(31,119,206)]" href="/blogs?page=117">117</a><a aria-label="Next page" class="flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-gray-200 text-gray-600 hover:border-blue-200 hover:text-[rgb(31,119,206)]" rel="next" href="/blogs?page=2"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-right h-4 w-4"><path d="m9 18 6-6-6-6"></path></svg></a></div><p class="text-xs text-gray-500">Page<!-- --> <!-- -->1<!-- --> <!-- -->of<!-- --> <!-- -->117</p></nav></div></div></main><!--$--><!--/$--><div class="MuiBox-root css-185zj69"><div class="MuiContainer-root MuiContainer-maxWidthLg app-cm-container css-9wvnva"><div class="MuiGrid-root MuiGrid-container MuiGrid-spacing-xs-4 css-havf2x"><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-6 MuiGrid-grid-sm-6 MuiGrid-grid-md-1.5 css-1qz13as"><h2 class="MuiTypography-root MuiTypography-h6 css-2le0">Company</h2><div class="MuiBox-root css-1c68enq"><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/">Home</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/contact">Contact</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/blogs">Blogs</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/guides">Guides</a></div></div><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-12 MuiGrid-grid-sm-6 MuiGrid-grid-md-4 css-1twzmnh"><h2 class="MuiTypography-root MuiTypography-h6 css-2le0">About</h2><div class="MuiBox-root css-r8jj44"><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/features">Features</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/thematic-analysis-software">Thematic Analysis Software</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/ai-thematic-analysis">AI Thematic Analysis</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/ai-qualitative-coding">AI Qualitative Coding</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/quote-traceability">Quote Traceability</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/multilingual-qualitative-analysis">Multilingual Analysis</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/alternatives">Compare QDA Tools</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/plans">Plans</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/case-studies">Case Studies</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/data-security">Data Security</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/how-we-trained-our-ai-models">How We Trained Our AI Models</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/affiliate-program">Affiliate Program</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/cite-us">How to Cite & Journal AI Policies</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/pricing-comparison">Compare Evidano with Other Solutions</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/certified-trainers">Certified Trainers</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/human-vs-ai">Human vs AI</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/environmental-impact">Environmental Impact</a></div></div><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-6 MuiGrid-grid-sm-6 MuiGrid-grid-md-2.5 css-begwwo"><h2 class="MuiTypography-root MuiTypography-h6 css-2le0">Preview Evidano</h2><div class="MuiBox-root css-1c68enq"><a target="_blank" rel="noopener noreferrer" style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="https://www.evidano.com/view-shared-project/cbbb5b5b-cc09-40db-a689-b3d3c9eb2071?pin=202143">View sample AI docx/pdf analysis</a><a target="_blank" rel="noopener noreferrer" style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="https://www.evidano.com/view-excel-share-project/cHJvamVjdF9pZD0xMzc1NyZ1c2VyX2VtYWlsPWFpbHl6ZSU0MG91dGxvb2suY29t">View sample AI xlsx/csv analysis</a><a target="_blank" rel="noopener noreferrer" style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/preview-ai-transcript">View sample AI audio transcription</a><a target="_blank" rel="noopener noreferrer" style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/ai-avatar-demo">Create/ Speak with demo AI avatar interviewer</a><a target="_blank" rel="noopener noreferrer" style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/ai-chatbot">Preview AI Chatbot</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/ai-detection">AI Detection</a></div></div><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-6 MuiGrid-grid-sm-6 MuiGrid-grid-md-2 css-1jgznv1"><h2 class="MuiTypography-root MuiTypography-h6 css-2le0">Account</h2><div class="MuiBox-root css-1c68enq"><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/login">Login</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="/register">Register for Free Plan (free forever, no expiry)</a><a target="_blank" rel="noopener noreferrer" style="color:#9ca3af;text-decoration:none;font-size:14px;font-weight:500;padding:2px 0;transition:all 0.2s ease;border-radius:4px" href="https://calendly.com/ailyze/meeting?hide_landing_page_details=1&hide_gdpr_banner=1&back=1">Book demo</a></div></div><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-12 MuiGrid-grid-sm-6 MuiGrid-grid-md-2 css-wubtha"><h2 class="MuiTypography-root MuiTypography-h6 css-2le0">Newsletter</h2><p class="MuiTypography-root MuiTypography-body1 css-12zs3lt">Product updates, research, and tips â straight to your inbox.</p><button class="!m-0 inline-flex items-center justify-center font-semibold transition-all duration-300 ease-in-out focus:outline-none focus:ring-2 focus:ring-offset-2 disabled:opacity-50 disabled:cursor-not-allowed cursor-pointer bg-gradient-to-r from-[#176CC7] to-[#64A8EA] hover:from-[#1257A6] hover:to-[#176CC7] text-white shadow-lg hover:shadow-xl hover:-translate-y-0.5 focus:ring-[#176CC7]/50 active:scale-95 px-4 py-2 text-sm rounded-full min-h-[36px] gap-2 w-full">Sign up for Newsletter</button></div></div><div class="MuiBox-root css-powfqf"><div class="MuiGrid-root MuiGrid-container MuiGrid-spacing-xs-2 css-1cjromv"><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-12 MuiGrid-grid-md-4 css-19egsyp"><p class="MuiTypography-root MuiTypography-body2 css-1hmu0g8">© Evidano, All Rights Reserved.</p></div><div class="MuiGrid-root MuiGrid-item MuiGrid-grid-xs-12 MuiGrid-grid-md-8 css-efwuvd"><div class="MuiStack-root css-12g5ai9"><a style="color:#9ca3af;text-decoration:none;font-size:14px;transition:color 0.2s" href="/privacy-policy">Privacy Policy</a><a style="color:#9ca3af;text-decoration:none;font-size:14px;transition:color 0.2s" href="/terms-service">Terms of Service</a></div></div></div></div></div></div></div></div><div tabindex="-1" role="dialog" aria-modal="false" aria-label="Customer support chat" class="fixed right-6 top-[72px] z-[1400] w-[360px] max-w-[calc(100vw-24px)] rounded-3xl border border-gray-200 bg-white shadow-xl outline-none hidden"><button type="button" aria-label="Close chat" class="absolute -top-2 -right-2 z-[60] flex h-6 w-6 items-center justify-center rounded-full border border-gray-200 bg-[#1864c4] text-gray-600 shadow-md hover:bg-[#1864c4]"><svg class="MuiSvgIcon-root MuiSvgIcon-fontSizeMedium !text-white !text-[16
5px] !font-bold css-q7mezt" focusable="false" aria-hidden="true" viewBox="0 0 24 24" data-testid="CloseIcon"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"></path></svg></button><div class="relative h-[540px] w-full overflow-hidden rounded-3xl border border-gray-200 bg-white"><div class="absolute inset-0 flex items-center justify-center text-sm text-gray-500">Loading chat...</div><div id="tawk_657ffbd107843602b8032487" class="h-full w-full invisible"></div></div></div><!--$--><!--$?--><template id="B:0"></template><!--/$--><!--/$-->
5<script>requestAnimationFrame(function(){$RT=performance.now()});</script>
5<script src="/_next/static/chunks/0tmid5v1qi6nw.js" id="_R_" async=""></script>
5<div hidden id="S:0"><style> 6#nprogress { 7 pointer-events: none; 8} 9 10#nprogress .bar { 11 background: #1F77CF; 12 13 position: fixed; 14 z-index: 99999; 15 top: 0; 16 left: 0; 17 18 width: 100%; 19 height: 3px; 20} 21 22/* Fancy blur effect */ 23#nprogress .peg { 24 display: block; 25 position: absolute; 26 right: 0px; 27 width: 100px; 28 height: 100%; 29 box-shadow: 0 0 10px #1F77CF, 0 0 5px #1F77CF; 30 opacity: 1.0; 31 32 -webkit-transform: rotate(3deg) translate(0px, -4px); 33 -ms-transform: rotate(3deg) translate(0px, -4px); 34 transform: rotate(3deg) translate(0px, -4px); 35} 36 37/* Remove these to get rid of the spinner */ 38#nprogress .spinner { 39 display: block; 40 position: fixed; 41 z-index: 1031; 42 top: 15px; 43 bottom: auto; 44 right: 15px; 45 left: auto; 46} 47 48#nprogress .spinner-icon { 49 width: 18px; 50 height: 18px; 51 box-sizing: border-box; 52 53 border: solid 2px transparent; 54 border-top-color: #1F77CF; 55 border-left-color: #1F77CF; 56 border-radius: 50%; 57 58 -webkit-animation: nprogress-spinner 400ms linear infinite; 59 animation: nprogress-spinner 400ms linear infinite; 60} 61 62.nprogress-custom-parent { 63 overflow: hidden; 64 position: relative; 65} 66 67.nprogress-custom-parent #nprogress .spinner, 68.nprogress-custom-parent #nprogress .bar { 69 position: absolute; 70} 71 72@-webkit-keyframes nprogress-spinner { 73 0% { -webkit-transform: rotate(0deg); } 74 100% { -webkit-transform: rotate(360deg); } 75} 76@keyframes nprogress-spinner { 77 0% { transform: rotate(0deg); } 78 100% { transform: rotate(360deg); } 79} 80</style></div>
80<script>$RB=[];$RV=function(a){$RT=performance.now();for(var b=0;b<a.length;b+=2){var c=a[b],e=a[b+1];null!==e.parentNode&&e.parentNode.removeChild(e);var f=c.parentNode;if(f){var g=c.previousSibling,h=0;do{if(c&&8===c.nodeType){var d=c.data;if("/$"===d||"/&"===d)if(0===h)break;else h--;else"$"!==d&&"$?"!==d&&"$~"!==d&&"$!"!==d&&"&"!==d||h++}d=c.nextSibling;f.removeChild(c);c=d}while(c);for(;e.firstChild;)f.insertBefore(e.firstChild,c);g.data="$";g._reactRetry&&requestAnimationFrame(g._reactRetry)}}a.length=0}; 81$RC=function(a,b){if(b=document.getElementById(b))(a=document.getElementById(a))?(a.previousSibling.data="$~",$RB.push(a,b),2===$RB.length&&("number"!==typeof $RT?requestAnimationFrame($RV.bind(null,$RB)):(a=performance.now(),setTimeout($RV.bind(null,$RB),2300>a&&2E3<a?2300-a:$RT+300-a)))):b.parentNode.removeChild(b)};$RC("B:0","S:0")</script>
81<script>(self.__next_f=self.__next_f||[]).push([0])</script>
81<script>self.__next_f.push([1,"1:\"$Sreact.fragment\"\n3:I[339756,[\"/_next/static/chunks/0jyvuu-rh3tqf.js\",\"/_next/static/chunks/0x9hbt.2lqqoh.js\"],\"default\"]\n4:I[837457,[\"/_next/static/chunks/0jyvuu-rh3tqf.js\",\"/_next/static/chunks/0x9hbt.2lqqoh.js\"],\"default\"]\n6:I[897367,[\"/_next/static/chunks/0jyvuu-rh3tqf.js\",\"/_next/static/chunks/0x9hbt.2lqqoh.js\"],\"OutletBoundary\"]\n7:\"$Sreact.suspense\"\na:I[897367,[\"/_next/static/chunks/0jyvuu-rh3tqf.js\",\"/_next/static/chunks/0x9hbt.2lqqoh.js\"],\"ViewportBoundary\"]\nc:I[897367,[\"/_next/static/chunks/0jyvuu-rh3tqf.js\",\"/_next/static/chunks/0x9hbt.2lqqoh.js\"],\"MetadataBoundary\"]\ne:I[563491,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/15tbim000cf6s.js\"],\"default\"]\n10:I[556864,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"OpenAIPixelProvider\"]\n11:I[845191,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"GoogleAdsProvider\"]\n12:I[545493,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\","])</script>
81<script>self.__next_f.push([1,"\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"default\"]\n13:I[427595,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"AuthProvider\"]\n14:I[834338,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"AdAttributionCleanup\"]\n15:I[447012,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"WebVitalsReporter\"]\n16:I[899330,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/"])</script>
81<script>self.__next_f.push([1,"static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"SentryUserIdentifier\"]\n17:I[375392,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"PostHogUserIdentifier\"]\n18:I[334735,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"default\"]\n19:I[177105,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/"])</script>
81<script>self.__next_f.push([1,"_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"default\"]\n1a:I[501654,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"ThemeProvider\"]\n1b:I[162406,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"default\"]\n1c:I[663141,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"PostHogProvider\"]\n1d:I[766584,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12"])</script>
81<script>self.__next_f.push([1,"coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"default\"]\n1e:I[758298,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/0ivt8q6yvg__5.js\"],\"default\"]\n1f:I[329306,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/08z1r-elw.3u4.js\"],\"default\"]\n20:I[443880,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\"],\"Analytics\"]\n21:I[27201,[\"/_next/static/chunks/0jyvuu-rh3tqf.js\",\"/_next/static/chunks/0x9hbt.2lqqoh.js\"],\"IconMark\"]\n:HL[\"/_next/static/chunks/14alqosszpf9s.css\",\"style\"]\n"])</script>
81<script>self.__next_f.push([1,"0:{\"P\":null,\"c\":[\"\",\"blogs\"],\"q\":\"\",\"i\":false,\"f\":[[[\"\",{\"children\":[\"blogs\",{\"children\":[\"__PAGE__\",{}]}]},\"$undefined\",\"$undefined\",16],[[\"$\",\"$1\",\"c\",{\"children\":[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/_next/static/chunks/14alqosszpf9s.css\",\"precedence\":\"next\",\"crossOrigin\":\"$undefined\",\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-0\",{\"src\":\"/_next/static/chunks/15tev3v-k6ykn.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-1\",{\"src\":\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-2\",{\"src\":\"/_next/static/chunks/014.cojmeu8r7.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-3\",{\"src\":\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-4\",{\"src\":\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-5\",{\"src\":\"/_next/static/chunks/06a45a7j5k-js.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-6\",{\"src\":\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-7\",{\"src\":\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-8\",{\"src\":\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-9\",{\"src\":\"/_next/static/chunks/09220hua3xdwb.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-10\",{\"src\":\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-11\",{\"src\":\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-12\",{\"src\":\"/_next/static/chunks/06uysyk4dsnp..js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-13\",{\"src\":\"/_next/static/chunks/0ieejselqt4sb.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-14\",{\"src\":\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-15\",{\"src\":\"/_next/static/chunks/0uy~38govsi.j.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-16\",{\"src\":\"/_next/static/chunks/102.xx_c910ig.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-17\",{\"src\":\"/_next/static/chunks/0qia6hd26k~vx.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-18\",{\"src\":\"/_next/static/chunks/12coqwet6qxr0.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-19\",{\"src\":\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-20\",{\"src\":\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-21\",{\"src\":\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-22\",{\"src\":\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-23\",{\"src\":\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-24\",{\"src\":\"/_next/static/chunks/0sk9j1giok5~z.js\",\"async\":true,\"nonce\":\"$undefined\"}],[\"$\",\"script\",\"script-25\",{\"src\":\"/_next/static/chunks/06mb6yniv~mh_.js\",\"async\":true,\"nonce\":\"$undefined\"}]],\"$L2\"]}],{\"children\":[[\"$\",\"$1\",\"c\",{\"children\":[null,[\"$\",\"$L3\",null,{\"parallelRouterKey\":\"children\",\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L4\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":\"$undefined\",\"forbidden\":\"$undefined\",\"unauthorized\":\"$undefined\"}]]}],{\"children\":[[\"$\",\"$1\",\"c\",{\"children\":[\"$L5\",[[\"$\",\"script\",\"script-0\",{\"src\":\"/_next/static/chunks/0wpt7ub5rom57.js\",\"async\":true,\"nonce\":\"$undefined\"}]],[\"$\",\"$L6\",null,{\"children\":[\"$\",\"$7\",null,{\"name\":\"Next.MetadataOutlet\",\"children\":\"$@8\"}]}]]}],{},null,false,null]},null,false,\"$@9\"]},null,false,null],[\"$\",\"$1\",\"h\",{\"children\":[null,[\"$\",\"$La\",null,{\"children\":\"$Lb\"}],[\"$\",\"div\",null,{\"hidden\":true,\"children\":[\"$\",\"$Lc\",null,{\"children\":[\"$\",\"$7\",null,{\"name\":\"Next.Metadata\",\"children\":\"$Ld\"}]}]}],null]}],false]],\"m\":\"$undefined\",\"G\":[\"$e\",[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/_next/static/chunks/14alqosszpf9s.css\",\"precedence\":\"next\",\"crossOrigin\":\"$undefined\",\"nonce\":\"$undefined\"}]]],\"S\":false,\"h\":null,\"s\":\"$undefined\",\"l\":\"$undefined\",\"p\":\"$undefined\",\"d\":\"$undefined\",\"b\":\"B2gJsQ_CB5nUD4Bl4SKaY\"}\n"])</script>
81<script>self.__next_f.push([1,"f:[]\n9:\"$Wf\"\n"])</script>
81<script>self.__next_f.push([1,"2:[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[[\"$\",\"head\",null,{\"children\":[[\"$\",\"script\",null,{\"async\":true,\"src\":\"https://www.googletagmanager.com/gtag/js?id=AW-18384924145\"}],[\"$\",\"script\",null,{\"id\":\"google-ads-gtag-bootstrap\",\"dangerouslySetInnerHTML\":{\"__html\":\"window.dataLayer = window.dataLayer || [];\\nfunction gtag(){dataLayer.push(arguments);}\\nwindow.gtag = window.gtag || gtag;\\ngtag('js', new Date());\\ngtag('config', \\\"AW-18384924145\\\");\"}}]]}],[\"$\",\"body\",null,{\"suppressHydrationWarning\":true,\"children\":[[[\"$\",\"link\",\"https://ai.ailyze.com\",{\"rel\":\"preconnect\",\"href\":\"https://ai.ailyze.com\",\"crossOrigin\":\"anonymous\"}]],[\"$\",\"link\",null,{\"rel\":\"preconnect\",\"href\":\"https://bzrcdn.openai.com\",\"crossOrigin\":\"anonymous\"}],[\"$\",\"link\",null,{\"rel\":\"dns-prefetch\",\"href\":\"https://ipapi.co\"}],[\"$\",\"link\",null,{\"rel\":\"dns-prefetch\",\"href\":\"https://api.frankfurter.dev\"}],[\"$\",\"$L10\",null,{}],[\"$\",\"$L11\",null,{}],[\"$\",\"$L12\",null,{\"options\":{\"key\":\"css\",\"prepend\":true},\"children\":[\"$\",\"$L13\",null,{\"children\":[[\"$\",\"$L14\",null,{}],[\"$\",\"$L15\",null,{}],[\"$\",\"$L16\",null,{}],[\"$\",\"$L17\",null,{}],[\"$\",\"$L18\",null,{\"children\":[\"$\",\"$L19\",null,{\"children\":[\"$\",\"$L1a\",null,{\"children\":[[\"$\",\"$L1b\",null,{}],[\"$\",\"$L1c\",null,{\"children\":[\"$\",\"$L1d\",null,{\"children\":[[\"$\",\"$L3\",null,{\"parallelRouterKey\":\"children\",\"error\":\"$1e\",\"errorStyles\":[],\"errorScripts\":[[\"$\",\"script\",\"script-0\",{\"src\":\"/_next/static/chunks/0ivt8q6yvg__5.js\",\"async\":true}]],\"template\":[\"$\",\"$L4\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"$L1f\",null,{}],[]],\"forbidden\":\"$undefined\",\"unauthorized\":\"$undefined\"}],[\"$\",\"$L20\",null,{}]]}]}]]}]}]}]]}]}]]}]]}]\n"])</script>
81<script>self.__next_f.push([1,"b:[[\"$\",\"meta\",\"0\",{\"charSet\":\"utf-8\"}],[\"$\",\"meta\",\"1\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}]]\n8:null\n"])</script>
81<script>self.__next_f.push([1,"d:[[\"$\",\"title\",\"0\",{\"children\":\"AI Qualitative Research Blog | Evidano\"}],[\"$\",\"meta\",\"1\",{\"name\":\"description\",\"content\":\"Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano.\"}],[\"$\",\"meta\",\"2\",{\"name\":\"application-name\",\"content\":\"Evidano\"}],[\"$\",\"meta\",\"3\",{\"name\":\"author\",\"content\":\"Evidano\"}],[\"$\",\"link\",\"4\",{\"rel\":\"manifest\",\"href\":\"/manifest.webmanifest\",\"crossOrigin\":\"$undefined\"}],[\"$\",\"meta\",\"5\",{\"name\":\"robots\",\"content\":\"index, follow\"}],[\"$\",\"link\",\"6\",{\"rel\":\"canonical\",\"href\":\"https://www.evidano.com/blogs\"}],[\"$\",\"link\",\"7\",{\"rel\":\"alternate\",\"type\":\"application/rss+xml\",\"href\":\"https://www.evidano.com/blogs/rss.xml\",\"title\":\"Evidano Blog RSS Feed\"}],[\"$\",\"meta\",\"8\",{\"property\":\"og:title\",\"content\":\"AI Qualitative Research Blog | Evidano\"}],[\"$\",\"meta\",\"9\",{\"property\":\"og:description\",\"content\":\"Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano.\"}],[\"$\",\"meta\",\"10\",{\"property\":\"og:url\",\"content\":\"https://www.evidano.com/blogs\"}],[\"$\",\"meta\",\"11\",{\"property\":\"og:type\",\"content\":\"website\"}],[\"$\",\"meta\",\"12\",{\"name\":\"twitter:card\",\"content\":\"summary_large_image\"}],[\"$\",\"meta\",\"13\",{\"name\":\"twitter:title\",\"content\":\"AI Qualitative Research Blog | Evidano\"}],[\"$\",\"meta\",\"14\",{\"name\":\"twitter:description\",\"content\":\"Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano.\"}],[\"$\",\"link\",\"15\",{\"rel\":\"icon\",\"href\":\"/favicon.ico?favicon.0oz7g567qe3_2.ico\",\"sizes\":\"48x48\",\"type\":\"image/x-icon\"}],[\"$\",\"link\",\"16\",{\"rel\":\"apple-touch-icon\",\"href\":\"/apple-icon.png?apple-icon.15j4gpa5nlhmt.png\",\"sizes\":\"180x180\",\"type\":\"image/png\"}],[\"$\",\"$L21\",\"17\",{}]]\n"])</script>
81<script>self.__next_f.push([1,"22:T1e15,"])</script>
81<script>self.__next_f.push([1,"{\"@context\":\"https://schema.org\",\"@graph\":[{\"@type\":\"Blog\",\"@id\":\"https://www.evidano.com/blogs\",\"name\":\"Evidano AI Qualitative Research Blog\",\"description\":\"Practical guides and commentary on qualitative research, thematic analysis, AI-assisted coding, interviews and transcription â from the team behind Evidano.\",\"url\":\"https://www.evidano.com/blogs\",\"inLanguage\":\"en\",\"publisher\":{\"@type\":\"Organization\",\"name\":\"Evidano\",\"url\":\"https://www.evidano.com\"},\"blogPost\":[{\"@type\":\"BlogPosting\",\"headline\":\"Two Definitions: Climate Change Acceptance for Undergrads\",\"description\":\"How a PLoS One Delphi study (Aug 25, 2026) defined climate change acceptance for undergraduate science students, and how AI-enabled qualitative analysis applies it.\",\"url\":\"https://www.evidano.com/blogs/climate-change-acceptance-definition-undergrads\",\"image\":\"https://www.evidano.com/blogs/climate-change-acceptance-definition-undergrads/opengraph-image\",\"datePublished\":\"2026-08-27T02:32:23.121788Z\",\"keywords\":\"climate change acceptance definition, climate change acceptance undergraduate, Delphi study climate acceptance, qualitative analysis climate education\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"Researcher-in-the-loop: AI-enabled UX research\",\"description\":\"How the researcher-in-the-loop model governs AI-enabled UX research. Learn practical governance, stats from the August 2026 piece, and how Evidano supports this workflow.\",\"url\":\"https://www.evidano.com/blogs/researcher-in-the-loop-ai-ux-research-ce94f8ed\",\"image\":\"https://www.evidano.com/blogs/researcher-in-the-loop-ai-ux-research-ce94f8ed/opengraph-image\",\"datePublished\":\"2026-08-27T02:31:27.618383Z\",\"keywords\":\"researcher-in-the-loop, AI-enabled UX research, governed research AI, research governance AI\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"Researcher-in-the-Loop: Governance for AI UX Research\",\"description\":\"Govern AI in qualitative UX research with the researcher-in-the-loop model from Jennifer L. Bowie (Aug 25, 2026): practical rules, risks, and tool mappings.\",\"url\":\"https://www.evidano.com/blogs/researcher-in-the-loop\",\"image\":\"https://www.evidano.com/blogs/researcher-in-the-loop/opengraph-image\",\"datePublished\":\"2026-08-27T02:30:35.794981Z\",\"keywords\":\"researcher-in-the-loop, AI-enabled qualitative research, AI governance for UX research\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"Why LARC/PM Uptake Is Low: Qualitative Analysis in Bangladesh\",\"description\":\"Actionable guidance for researchers: qualitative analysis of LARC uptake in rural Bangladesh using AI-enabled workflows to code interviews, surface themes, and inform rights-based programs.\",\"url\":\"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake-bangladesh\",\"image\":\"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake-bangladesh/opengraph-image\",\"datePublished\":\"2026-08-27T02:30:14.783359Z\",\"keywords\":\"qualitative analysis of LARC uptake, LARC uptake Bangladesh qualitative, AI-enabled qualitative research, long-acting contraception qualitative\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"AI for Qualitative Analysis: LARC Uptake in Bangladesh\",\"description\":\"How AI-enabled qualitative analysis reveals multilevel barriers to
81LARC/PM uptake in rural Bangladesh, with practical steps for researchers and program teams. Read actionable methods.\",\"url\":\"https://www.evidano.com/blogs/qualitative-analysis-larc-uptake-bangladesh-d333f5d9-3\",\"image\":\"https://www.evidano.com/blogs/qualitative-analysis-larc-uptake-bangladesh-d333f5d9-3/opengraph-image\",\"datePublished\":\"2026-08-27T02:29:22.936258Z\",\"keywords\":\"qualitative analysis of LARC uptake, LARC PM uptake Bangladesh, AI-enabled qualitative research, thematic analysis family planning\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"Consensus definitions: climate change acceptance definition\",\"description\":\"PLoS One (Aug 25, 2026) presents two consensus climate change acceptance definitions for undergraduates; see stats and how AI qualitative analysis accelerates survey design.\",\"url\":\"https://www.evidano.com/blogs/climate-change-acceptance-definition-delphi\",\"image\":\"https://www.evidano.com/blogs/climate-change-acceptance-definition-delphi/opengraph-image\",\"datePublished\":\"2026-08-27T02:28:29.626300Z\",\"keywords\":\"climate change acceptance definition, Delphi climate acceptance undergraduates, climate acceptance definitions PLoS One, AI qualitative analysis for survey design\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"AI synthesis: qualitative analysis of LARC/PM uptake\",\"description\":\"AI-enabled synthesis of a PLOS ONE qualitative analysis of LARC/PM uptake in rural Bangladesh (Aug 25, 2026). Read methods, key stats, quotes, and AI research workflows.\",\"url\":\"https://www.evidano.com/blogs/qualitative-analysis-larc-pm-bangladesh\",\"image\":\"https://www.evidano.com/blogs/qualitative-analysis-larc-pm-bangladesh/opengraph-image\",\"datePublished\":\"2026-08-27T02:27:53.966224Z\",\"keywords\":\"qualitative analysis of LARC/PM uptake, LARC uptake Bangladesh qualitative, AI-enabled qualitative research, thematic analysis family planning\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"Simulation Testing: AI Simulation Testing for Clinical Care\",\"description\":\"How Mayo Clinic uses AI simulation testing to close the clinical AI translation gap; practical steps for qualitative researchers and UX teams plus tools to scale evaluation.\",\"url\":\"https://www.evidano.com/blogs/ai-simulation-testing-clinical\",\"image\":\"https://www.evidano.com/blogs/ai-simulation-testing-clinical/opengraph-image\",\"datePublished\":\"2026-08-27T02:26:52.908224Z\",\"keywords\":\"AI simulation testing, clinical AI evaluation, simulation-based AI testing, AI translation gap, qualitative AI testing\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"AI-ready Guide: qualitative analysis of contraceptive uptake\",\"description\":\"Apply AI-enabled qualitative analysis to LARC/PM uptake in rural Bangladesh: study stats, direct quotes, and practical researcher steps. Learn methods and next steps.\",\"url\":\"https://www.evidano.com/blogs/qualitative-analysis-contraceptive-uptake-bangladesh-d333f5d9\",\"image\":\"https://www.evidano.com/blogs/qualitative-analysis-contraceptive-uptake-bangladesh-d333f5d9/opengraph-image\",\"datePublished\":\"2026-08-27T02:26:42.453403Z\",\"keywords\":\"qualitative analysis of contraceptive uptake, LARC uptake Bangladesh qualitative, AI-enabled qualitative research, family planning qualitative methods\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}},{\"@type\":\"BlogPosting\",\"headline\":\"AI-enabled qualitative analysis of LARC uptake\",\"description\":\"How AI speeds thematic, cross-segment insight from interviews: an AI-enabled qualitative analysis of LARC uptake in rural Bangladesh, with practical research workflows.\",\"url\":\"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake\",\"image\":\"https://www.evidano.com/blogs/qualitative-analysis-of-larc-uptake/opengraph-image\",\"datePublished\":\"2026-08-27T02:25:28.418465Z\",\"keywords\":\"qualitative analysis of LARC uptake, AI qualitative research, LARC uptake Bangladesh, thematic analysis interviews\",\"author\":{\"@type\":\"Organization\",\"name\":\"Evidano\"}}]}
81,{\"@type\":\"BreadcrumbList\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https://www.evidano.com\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Blog\",\"item\":\"https://www.evidano.com/blogs\"}]}]}"])</script>
81<script>self.__next_f.push([1,"5:[\"$\",\"main\",null,{\"className\":\"min-h-screen bg-white pb-20 pt-[84px]\",\"children\":[[\"$\",\"script\",null,{\"type\":\"application/ld+json\",\"dangerouslySetInnerHTML\":{\"__html\":\"$22\"}}],\"$L23\"]}]\n"])</script>
81<script>self.__next_f.push([1,"24:I[522016,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/0wpt7ub5rom57.js\"],\"\"]\n25:I[689484,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/0wpt7ub5rom57.js\"],\"default\"]\n26:I[183607,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/0wpt7ub5rom57.js\"],\"default\"]\n"])</script>
81<script>self.__next_f.push([1,"23:[\"$\",\"div\",null,{\"className\":\"mx-auto max-w-7xl px-5 sm:px-8\",\"children\":[[\"$\",\"header\",null,{\"className\":\"pb-8 pt-10\",\"children\":[[\"$\",\"nav\",null,{\"aria-label\":\"Breadcrumb\",\"className\":\"mb-4 text-sm text-gray-500\",\"children\":[[\"$\",\"$L24\",null,{\"className\":\"transition-colors hover:text-[rgb(31,119,206)]\",\"href\":\"/\",\"children\":\"Home\"}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"mx-2 text-gray-300\",\"children\":\"/\"}],[\"$\",\"span\",null,{\"className\":\"text-gray-700\",\"children\":\"Blog\"}]]}],[\"$\",\"h1\",null,{\"className\":\"max-w-4xl text-3xl font-black tracking-tight text-gray-900 text-balance sm:text-4xl md:text-5xl\",\"children\":\"AI \u0026 Qualitative Research Blog\"}],[\"$\",\"p\",null,{\"className\":\"mt-5 max-w-3xl text-sm text-gray-500\",\"children\":[\"New to Evidano? Start with the\",\" \",[\"$\",\"$L24\",null,{\"className\":\"font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700\",\"href\":\"/features\",\"children\":\"feature overview\"}],\", \",[\"$\",\"$L24\",null,{\"className\":\"font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700\",\"href\":\"/case-studies\",\"children\":\"published case studies\"}],\", or \",[\"$\",\"$L24\",null,{\"className\":\"font-medium text-[rgb(31,119,206)] underline underline-offset-2 hover:text-blue-700\",\"href\":\"/blogs/rss.xml\",\"children\":\"subscribe via RSS\"}],\".\"]}]]}],[[\"$\",\"$L25\",null,{}],[\"$\",\"$L26\",null,{\"methodTags\":[{\"id\":\"thematic-analysis\",\"group\":\"method\",\"label\":\"Thematic analysis\",\"shortLabel\":\"Thematic\",\"description\":\"Reflexive, semantic and latent coding of patterns across a corpus.\",\"match\":[\"thematic\",\"theme\",\"reflexive\",\"semantic coding\",\"latent coding\"]},{\"id\":\"evidence-synthesis\",\"group\":\"method\",\"label\":\"Evidence synthesis\",\"shortLabel\":\"Synthesis\",\"description\":\"Systematic, scoping, rapid and integrative reviews; meta-synthesis and meta-ethnography.\",\"match\":[\"systematic review\",\"scoping review\",\"rapid review\",\"integrative review\",\"meta-synthesis\",\"meta-ethnograph\",\"literature review\",\"evidence synthesis\",\"narrative synthesis\"]},{\"id\":\"grounded-theory\",\"group\":\"method\",\"label\":\"Grounded theory\",\"shortLabel\":\"Grounded theory\",\"description\":\"Glaserian, Straussian and constructivist grounded theory; constant comparison; the Gioia method.\",\"match\":[\"grounded theory\",\"constant comparative\",\"gioia\",\"dimensional analysis\",\"situational analysis\"]},{\"id\":\"phenomenology\",\"group\":\"method\",\"label\":\"Phenomenology\",\"shortLabel\":\"Phenomenology\",\"description\":\"IPA plus descriptive, hermeneutic, transcendental and existential phenomenology.\",\"match\":[\"phenomenolog\",\"interpretative phenomenological\",\"ipa\",\"lived experience\",\"husserl\",\"heidegger\",\"moustakas\"]},{\"id\":\"ethnography\",\"group\":\"method\",\"label\":\"Ethnography and observation\",\"shortLabel\":\"Ethnography\",\"description\":\"Classical, focused, institutional and digital ethnography; participant observation; shadowing.\",\"match\":[\"ethnograph\",\"netnograph\",\"participant observation\",\"shadowing\",\"go-along\",\"fieldwork\"]},{\"id\":\"narrative-discourse\",\"group\":\"method\",\"label\":\"Narrative and discourse\",\"shortLabel\":\"Narrative\",\"description\":\"Narrative inquiry and analysis, discourse and critical discourse analysis, conversation analysis.\",\"match\":[\"narrative inquiry\",\"narrative analysis\",\"discourse\",\"conversation analysis\",\"rhetorical\",\"genre analysis\"]},{\"id\":\"content-framework\",\"group\":\"method\",\"label\":\"Content and framework analysis\",\"shortLabel\":\"Content analysis\",\"description\":\"Conventional, directed and summative content analysis; framework and template analysis; document analysis.\",\"match\":[\"content analysis\",\"framework analysis\",\"template analysis\",\"document analysis\",\"textual analysis\",\"ritchie\",\"codebook\",\"coding frame\"]},{\"id\":\"theory-based-evaluation\",\"group\":\"method\",\"label\":\"Theory-based evaluation\",\"shortLabel\":\"Theory of change\",\"description\":\"Theory of change, logic models, logframes, results chains and impact pathways.\",\"match\":[\"theory of change\",\"logic model\",\"logframe\",\"logical framework\",\"results chain\",\"impact pathway\",\"program theory\"]},{\"id\":\"realist-causal\",\"group\":\"method\",\"label\":\"Realist and causal analysis\",\"shortLabel\":\"Realist\",\"description\":\"Realist evaluation and synthesis, contribution analysis, c
81ontribution and process tracing.\",\"match\":[\"realist\",\"context-mechanism\",\"contribution analysis\",\"contribution tracing\",\"process tracing\",\"cmo\"]},{\"id\":\"participatory\",\"group\":\"method\",\"label\":\"Participatory and collaborative\",\"shortLabel\":\"Participatory\",\"description\":\"Participatory and empowerment evaluation, CBPR, most significant change, photovoice.\",\"match\":[\"participatory\",\"empowerment evaluation\",\"community-based\",\"cbpr\",\"most significant change\",\"photovoice\",\"collaborative evaluation\"]},{\"id\":\"outcome-impact\",\"group\":\"method\",\"label\":\"Outcome and impact assessment\",\"shortLabel\":\"Outcomes\",\"description\":\"Outcome harvesting and mapping, QCA, case-based impact evaluation, ripple effects mapping.\",\"match\":[\"outcome harvesting\",\"outcome mapping\",\"qualitative comparative\",\"qca\",\"ripple effect\",\"success case\",\"impact evaluation\"]},{\"id\":\"implementation\",\"group\":\"method\",\"label\":\"Implementation and process evaluation\",\"shortLabel\":\"Implementation\",\"description\":\"Process and implementation evaluation, fidelity assessment, CFIR and RE-AIM, normalization process theory.\",\"match\":[\"implementation\",\"process evaluation\",\"fidelity\",\"cfir\",\"re-aim\",\"normalization process\"]},{\"id\":\"developmental-evaluation\",\"group\":\"method\",\"label\":\"Developmental and utilization-focused\",\"shortLabel\":\"Developmental\",\"description\":\"Developmental, utilization-focused, formative, rapid-cycle and embedded evaluation.\",\"match\":[\"developmental evaluation\",\"utilization-focused\",\"formative evaluation\",\"rapid-cycle\",\"embedded evaluation\",\"lean evaluation\"]},{\"id\":\"contextual-inquiry\",\"group\":\"method\",\"label\":\"Exploratory and contextual inquiry\",\"shortLabel\":\"Contextual\",\"description\":\"In-depth interviews, focus groups, contextual inquiry, diary studies, intercepts and ride-alongs.\",\"match\":[\"in-depth interview\",\"contextual inquiry\",\"diary study\",\"experience sampling\",\"intercept interview\",\"ride-along\"]},{\"id\":\"ux-research\",\"group\":\"method\",\"label\":\"UX and human-centered design\",\"shortLabel\":\"UX research\",\"description\":\"Usability testing, heuristic evaluation, cognitive walkthroughs, card sorting, journey mapping.\",\"match\":[\"usability\",\"heuristic evaluation\",\"cognitive walkthrough\",\"card sorting\",\"tree testing\",\"think-aloud\",\"journey mapping\",\"service blueprint\"]},{\"id\":\"jobs-to-be-done\",\"group\":\"method\",\"label\":\"Needs and jobs-to-be-done\",\"shortLabel\":\"JTBD\",\"description\":\"JTBD interviews, outcome-driven innovation, Kano exploration, value proposition mapping.\",\"match\":[\"jobs-to-be-done\",\"jtbd\",\"outcome-driven innovation\",\"kano\",\"opportunity solution\",\"value proposition\"]},{\"id\":\"concept-testing\",\"group\":\"method\",\"label\":\"Concept and message testing\",\"shortLabel\":\"Concept testing\",\"description\":\"Concept testing, prototype co-creation, message and claims testing, naming and packaging research.\",\"match\":[\"concept testing\",\"prototype\",\"claims testing\",\"message testing\",\"naming and positioning\",\"packaging\"]},{\"id\":\"voice-of-customer\",\"group\":\"method\",\"label\":\"Customer experience and VoC\",\"shortLabel\":\"Voice of customer\",\"description\":\"Customer journey deep dives, advisory boards, VoC interviews, call-log and review mining.\",\"match\":[\"voice-of-customer\",\"customer journey\",\"advisory board\",\"call log\",\"chat log\",\"feedback mining\",\"review mining\"]},{\"id\":\"social-cultural\",\"group\":\"method\",\"label\":\"Social and cultural insights\",\"shortLabel\":\"Social insights\",\"description\":\"Online community analysis, social listening, UGC analysis, semiotics, category code mapping.\",\"match\":[\"social listening\",\"online community\",\"user-generated content\",\"semiotic\",\"category code\",\"influencer\"]}],\"resources\":[{\"id\":\"evidence:oxford-melbourne-ai-interview-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/oxford-melbourne-ai-interview-analysis\",\"t
81itle\":\"Volda and Melbourne researchers used AI interview analysis to triangulate manual coding\",\"summary\":\"Two researchers coded 11 interviews by hand with over 90% agreement, then ran the anonymised transcripts through Evidano and compared the results for triangulation and validation.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"open-ended-survey\",\"second-coder\"],\"year\":2026,\"provenance\":\"Educational Psychology 46(1): 27â51 (Routledge / Taylor \u0026 Francis), open access\",\"organizations\":[\"Volda University College\",\"University of Melbourne\",\"University of Oslo\"],\"stat\":{\"value\":\"209\",\"label\":\"survey participants, a 97% response rate\"},\"sourceUrl\":\"https://doi.org/10.1080/01443410.2025.2528663\",\"doi\":\"10.1080/01443410.2025.2528663\",\"logo\":{\"src\":\"/images/publications/melbourne.png\",\"alt\":\"University of Melbourne logo\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-gamlem-2025\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/preservice-teachers-generative-ai\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:stanford-uc-davis-ai-cross-check-coding\",\"kind\":\"evidence\",\"href\":\"/case-studies/stanford-uc-davis-ai-cross-check-coding\",\"title\":\"Stanford and UC Davis researchers used AI to cross-check their qualitative coding\",\"summary\":\"A published mixed-methods study uploaded deidentified transcripts into Evidano to cross-check its themes. Every AI code was reviewed by the researcher.\",\"tags\":[\"academia\",\"content-framework\",\"interviews\"],\"year\":2026,\"provenance\":\"Getting Down to Facts III technical report (Stanford Graduate School of Education / SCALE Initiative), May 2026\",\"organizations\":[\"Stanford Graduate School of Education (SCALE Initiative)\",\"University of California, Davis\"],\"stat\":{\"value\":\"9\",\"label\":\"interviews analyzed\"},\"sourceUrl\":\"https://gettingdowntofacts.com/reports/mandatory-regionalization-and-its-limits-how-california-districts-experience-and-navigate\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/stanford.png\",\"alt\":\"Stanford University logo\"},\"art\":\"coding\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:education-sciences-2026-ai-qualitative-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/education-sciences-2026-ai-qualitative-analysis\",\"title\":\"UNC Wilmington: AI-assisted qualitative coding of student evaluations across 22 courses\",\"summary\":\"A peer-reviewed 2026 Education Sciences study used Evidano (previously AILYZE) as a thought partner after three rounds of human coding, surfacing a gender pattern the team had missed.\",\"tags\":[\"academia\",\"content-framework\",\"open-ended-survey\",\"thought-partner\",\"second-coder\",\"synthesis\",\"global-development\"],\"year\":2026,\"provenance\":\"Education Sciences (MDPI), 16(3), 448, open access\",\"organizations\":[\"University of North Carolina Wilmington\",\"Watson College of Education, Department of Educational Leadership\"],\"stat\":{\"value\":\"22\",\"label\":\"coursesâ open-ended student evaluation comments analyzed\"},\"sourceUrl\":\"https://doi.org/10.3390/educsci16030448\",\"doi\":\"10.3390/educsci16030448\",\"logo\":{\"src\":\"/images/publications/education_science.png\",\"alt\":\"Education Sciences journal logo\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-parker-savage-2026\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/gendered-language-student-evaluations\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:cambridge-prisms-bioplastics-focus-groups\",\"kind\":\"evidence\",\"href\":\"/case-studies/cambridge-prisms-bioplastics-focus-groups\",\"title\":\"South East Technological University: AI focus group thematic analysis of bioplastics\",\"summary\":\"Peer-reviewed, open-access research from Ireland used Evidano (previously AILYZE) to support focus group thematic analysis and help mitigate unintentional bias.\",\"tags\":[\"academia\",\"thematic-analysis\",\"focus-groups\"],\"year\":2026,\"provenance\":\"Cambridge Prisms: Plastics (Cambridge University Press), 4, e7, open access with open peer review\",\"organizations\":[\"South East Technological University (SETU
81), Carlow, Ireland\",\"UK Centre for Ecology \u0026 Hydrology\"],\"stat\":{\"value\":\"9\",\"label\":\"themes from the focus group thematic analysis\"},\"sourceUrl\":\"https://doi.org/10.1017/plc.2026.10045\",\"doi\":\"10.1017/plc.2026.10045\",\"logo\":{\"src\":\"/case-study-logos/cambridge-university-press.png\",\"alt\":\"Cambridge University Press logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/bioplastic-public-acceptance\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:frontiers-education-braun-clarke-thematic-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/frontiers-education-braun-clarke-thematic-analysis\",\"title\":\"Sharjah Education Academy: AI thematic analysis of 9 teacher interviews, human-verified\",\"summary\":\"Published in Frontiers in Education (2026): encrypted data, human-verified themes, and a transparent AI coding workflow across English and Arabic interviews.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"second-coder\",\"initial-coding\",\"synthesis\"],\"year\":2026,\"provenance\":\"Frontiers in Education, 11:1690181 (Frontiers Media, 2026), open access\",\"organizations\":[\"Sharjah Education Academy\",\"Sharjah City for Humanitarian Services\"],\"stat\":{\"value\":\"9\",\"label\":\"Teachers interviewed\"},\"sourceUrl\":\"https://doi.org/10.3389/feduc.2026.1690181\",\"doi\":\"10.3389/feduc.2026.1690181\",\"logo\":{\"src\":\"/case-study-logos/frontiers.png\",\"alt\":\"Frontiers logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-meda-2026\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/early-intervention-special-educational-needs\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:lut-michigan-global-survey-triangulation\",\"kind\":\"evidence\",\"href\":\"/case-studies/lut-michigan-global-survey-triangulation\",\"title\":\"LUT University \u0026 University of Michigan: AI triangulation of a 490-response global survey\",\"summary\":\"A research team at LUT University (Finland) and the University of Michigan (USA) used Evidano (previously AILYZE) alongside manual coding to analyze a global survey, published by Springer in 2026.\",\"tags\":[\"academia\",\"thematic-analysis\",\"open-ended-survey\"],\"year\":2026,\"provenance\":\"Lecture Notes in Business Information Processing vol. 574 (Springer), ICSOB 2025 proceedings, pp. 394â410, open access\",\"organizations\":[\"LUT University\",\"University of Michigan\"],\"stat\":{\"value\":\"490\",\"label\":\"end-user responses analyzed\"},\"sourceUrl\":\"https://doi.org/10.1007/978-3-032-14518-5_30\",\"doi\":\"10.1007/978-3-032-14518-5_30\",\"logo\":{\"src\":\"/case-study-logos/lut.png\",\"alt\":\"LUT University logo\"},\"art\":\"surveys\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:glasgow-springer-xp-triangulation\",\"kind\":\"evidence\",\"href\":\"/case-studies/glasgow-springer-xp-triangulation\",\"title\":\"University of Glasgow used AI triangulation on a 16-interview thematic analysis\",\"summary\":\"Inside a Springer-published University of Glasgow study that used Evidano to generate an independent thematic overview and triangulate its six themes.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\"],\"year\":2026,\"provenance\":\"Agile Processes in Software Engineering and Extreme Programming, XP 2026, Springer LNB
81IP 578, pp. 3â19, open access\",\"organizations\":[\"University of Glasgow\",\"The Open University\"],\"stat\":{\"value\":\"16\",\"label\":\"semi-structured interviews, about 60 minutes each\"},\"sourceUrl\":\"https://doi.org/10.1007/978-3-032-22375-3_1\",\"doi\":\"10.1007/978-3-032-22375-3_1\",\"logo\":{\"src\":\"/case-study-logos/glasgow.png\",\"alt\":\"University of Glasgow arms\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/sustaining-agile-change-after-coaching\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:ucla-dissertation-holistic-wellbeing-ai-coding\",\"kind\":\"evidence\",\"href\":\"/case-studies/ucla-dissertation-holistic-wellbeing-ai-coding\",\"title\":\"UCLA dissertation used AI-assisted qualitative coding on student journals and interviews\",\"summary\":\"A UCLA doctoral dissertation ran three separate Evidano analyses across 18 studentsâ journals and interview transcripts, then reviewed and refined every code by hand.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"documents-policy\",\"thought-partner\",\"initial-coding\",\"synthesis\"],\"year\":2026,\"provenance\":\"UCLA Electronic Theses and Dissertations, eScholarship (University of California), 2026\",\"organizations\":[\"University of California, Los Angeles (UCLA)\",\"UCLA School of Education \u0026 Information Studies\"],\"stat\":{\"value\":\"18\",\"label\":\"students in the qualitative sample\"},\"sourceUrl\":\"https://escholarship.org/uc/item/12t387vp\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/ucla.png\",\"alt\":\"UCLA logo\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-yang-2026\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/holistic-student-wellbeing-yoga-higher-education\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:university-split-transgender-media-representation\",\"kind\":\"evidence\",\"href\":\"/case-studies/university-split-transgender-media-representation\",\"title\":\"University of Split thesis used AI-triangulated thematic coding on 8 interviews\",\"summary\":\"Initial thematic coding of 8 in-depth interviews was processed through Evidano to support analytic triangulation, then reviewed and verified by the authors.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"second-coder\",\"initial-coding\"],\"year\":2026,\"provenance\":\"Bachelorâs thesis, University of Split, Repository of the Faculty of Humanities and Social Sciences (2026)\",\"organizations\":[\"University of Split, Faculty of Humanities and Social Sciences\",\"Department of Psychology, University of Split\"],\"stat\":{\"value\":\"8\",\"label\":\"in-depth interviews with transgender women\"},\"sourceUrl\":\"https://urn.nsk.hr/urn:nbn:hr:172:545777\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/university-split.png\",\"alt\":\"University of Split arms\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-stanicic-2026\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:rcis-grounded-theory-social-media-identity\",\"kind\":\"evidence\",\"href\":\"/case-studies/rcis-grounded-theory-social-media-identity\",\"title\":\"Five Ukrainian universities used AI-assisted grounded theory on 51 literature sources\",\"summary\":\"A peer-reviewed, Scopus-indexed grounded theory study processed 51 literature sources through Evidano to formulate the categories that fed its constructed theory.\",\"tags\":[\"academia\",\"grounded-theory\",\"documents-policy\",\"initial-coding\",\"synthesis\",\"narrative-discourse\",\"thematic-analysis\"],\"year\":2026,\"provenance\":\"Revista de Cercetare si Interventie Sociala, Vol. 93 (2026), pp. 43â66, peer-reviewed and Scopus-indexed\",\"organizations\":[\"National University of Ostroh Academy\",\"Taras Shevchenko National University of Kyiv\",\"State University of Trade and Economics\"],\"stat\":{\"value\":\"51\",\"label\":\"literature sources processed\"},\"sourceUrl\":\"https://doi.org/10.33788/rcis.93.3\",\"doi\":\"10.33788/rcis.93.3\",\"logo\":{\"src\":\"/case-study-logos/kyiv.png\",\"alt\":\"Taras Shevchenko National University of Kyiv logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-maslova-2026\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/fragmented-digital-identity-soft-power\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:university-san-carlos-colugo-ecotourism-lgu-interviews\",\"kind\":\"evidence\",\"href\":\"/case-studies/university-san-carlos-colugo-ecotourism-lgu-interviews\",\"title\":\"University of San Carlos study used AI interview anal
81ysis on 15 government officials\",\"summary\":\"In-depth interviews with 15 local government officials were analysed thematically in Evidano, using valence coding to classify responses across three Philippine municipalities.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"initial-coding\",\"synthesis\",\"participatory\"],\"year\":2026,\"provenance\":\"Preprints.org, posted 16 June 2026 (preprint, not peer-reviewed; CC BY 4.0)\",\"organizations\":[\"University of San Carlos\",\"Kahibalo Foundation\"],\"stat\":{\"value\":\"15\",\"label\":\"local government officials interviewed, 58 minutes on average\"},\"sourceUrl\":\"https://doi.org/10.20944/preprints202606.1186.v1\",\"doi\":\"10.20944/preprints202606.1186.v1\",\"logo\":{\"src\":\"/case-study-logos/university-san-carlos.png\",\"alt\":\"University of San Carlos logo\"},\"art\":\"interviews\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-nudalo-2026\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:utar-ai-literacy-employment-prospects-triangulation\",\"kind\":\"evidence\",\"href\":\"/case-studies/utar-ai-literacy-employment-prospects-triangulation\",\"title\":\"Universiti Tunku Abdul Rahman: AI thematic analysis in an IEEE mixed-methods pilot\",\"summary\":\"Interview data was entered into Evidano and interpreted thematically, then used as triangulation to add richness to the quantitative findings of an IEEE conference paper.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\"],\"year\":2026,\"provenance\":\"2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), IEEE\",\"organizations\":[\"Universiti Tunku Abdul Rahman\",\"Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman\"],\"stat\":{\"value\":\"3\",\"label\":\"constructs modelled: AI literacy, attitude toward AI, employment prospects\"},\"sourceUrl\":\"https://doi.org/10.1109/ACDSA67686.2026.11468141\",\"doi\":\"10.1109/acdsa67686.2026.11468141\",\"logo\":{\"src\":\"/case-study-logos/utar.jpg\",\"alt\":\"Universiti Tunku Abdul Rahman logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/ai-literacy-employment-prospects\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:ai-coding-39788-federal-survey-comments\",\"kind\":\"evidence\",\"href\":\"/case-studies/ai-coding-39788-federal-survey-comments\",\"title\":\"ENAP and UBC used AI-assisted qualitative coding on 39,788 federal survey comments\",\"summary\":\"A peer-reviewed, open-access study coded 39,788 open-ended comments against a predefined thematic grid, then manually verified a random 15% sample.\",\"tags\":[\"government\",\"content-framework\",\"open-ended-survey\",\"thought-partner\",\"synthesis\",\"thematic-analysis\"],\"year\":2026,\"provenance\":\"Public Personnel Management (SAGE), 2026, open access\",\"organizations\":[\"Ãcole nationale dâadministration publique (ENAP)\",\"University of British Columbia\",\"Vermont Law and Graduate School\"],\"stat\":{\"value\":\"39,788\",\"label\":\"open-ended comments coded\"},\"sourceUrl\":\"https://doi.org/10.1177/00910260261444414\",\"doi\":\"10.1177/00910260261444414\",\"logo\":{\"src\":\"/case-study-logos/sage.png\",\"alt\":\"Sage Publishing logo\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-morin-2026\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/return-to-office-mandates-federal-employee-wellbeing\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:federal-worker-comments-ai-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/federal-worker-comments-ai-analysis\",\"title\":\"ENAP and CUNY used AI-assisted qualitative analysis on 5,211 federal-worker comments\",\"summary\":\"A 2026 study coded 5,211 federal-worker comments against a seven-mechanism framework with AI, then reviewed every result by hand.\",\"tags\":[\"government\",\"content-framework\",\"open-ended-survey\"],\"year\":2026,\"provenance\":\"Administrative Theory \u0026 Praxis (Routledge / Taylor \u0026 Francis), 2026\",\"organizations\":[\"Ãcole nationale dâadministration publique (ENAP)\",\"CUNY College of Staten Island\",\"Vermont Law and Graduate School\"],\"stat\":{\"value\":\"5,211\",\"label\":\"survey comments analyzed\"},\"sourceUrl\":\"https://doi.org/10.1080/10841806.2025.2605601\",\"doi\":\"10.1080/10841806.2025.2605601\",\"logo\":{\"src\":\"/case-study-logos/taylor-francis.png\",\"alt\":\"Taylor \u0026 Francis Group logo\"},\"art\":\"ai-chat\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:experimental-criminology-police-leadership-triangulation\",\"kind\":\"evidence\",\"href\":\"/case-studies/experimental-criminology-police-leadership-triangulation\",\"title\":\"UT Austin and Wichita State used AI thematic analysis to triangulate 224 survey responses\",\"summary\":\"A peer-reviewed criminology study analysed its open-ended responses by hand, then used Evidano to triangulate the findings: 8 of 9 human themes were confirmed.\",\"tags\":[\"government\",\"thematic-analysis\",\"open-ended-survey\",\"thought-partner\",\"second-coder\",\"synthesis\",\"academia\"],\"year\":2026,\"provenance\":\"Journal of Experimental Criminology (Springer Nature), 2026, open access\",\"organizations\":[\"University of Texas at Austin (LBJ School of Public Affairs)\",\"Wichita State University (Hugo Wall School of Public Affairs)\"],\"stat\":{\"value\":\"303\",\"label\":\"respondents in the conjoint survey\"},\"sourceUrl\":\"https://doi.org/10.1007/s11292-026-09770-4\",\"doi\":\"10.1007/s11292-026-09770-4\",\"logo\":{\"src\":\"/case-study-logos/ut-austin.png\",\"alt\":\"University of Texas at Austin logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-abner-mee-2026\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/public-preferences-police-chief-leadership\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:clinical-research-informed-consent-ai-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/clinical-research-informed-consent-ai-analysis\",\"t
81itle\":\"Yenepoya Centre for Ethics ran AI content analysis of 30 AI-drafted consent documents\",\"summary\":\"Evidano ran the qualitative content analysis behind a 2026 peer-reviewed comparison of five generative AI toolsâ informed consent documents.\",\"tags\":[\"health\",\"content-framework\",\"documents-policy\"],\"year\":2026,\"provenance\":\"Perspectives in Clinical Research 17(2): 96â104 (Wolters Kluwer, Medknow), open access\",\"organizations\":[\"Centre for Ethics, Yenepoya (Deemed to be University)\"],\"stat\":{\"value\":\"5\",\"label\":\"generative AI tools compared\"},\"sourceUrl\":\"https://doi.org/10.4103/picr.picr_376_25\",\"doi\":\"10.4103/picr.picr_376_25\",\"logo\":{\"src\":\"/case-study-logos/yenepoya.png\",\"alt\":\"Yenepoya University logo\"},\"art\":\"themes\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:annals-medicine-ai-thematic-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/annals-medicine-ai-thematic-analysis\",\"title\":\"UP Manila medical education study: AI thematic analysis produced an 11-theme codebook\",\"summary\":\"How Evidano produced a complementary codebook and 11 granular themes to strengthen the dependability of a 2026 reflexive thematic analysis.\",\"tags\":[\"health\",\"thematic-analysis\",\"interviews\",\"documents-policy\",\"academia\",\"content-framework\"],\"year\":2026,\"provenance\":\"Annals of Medicine and Medical Sciences (AMMS) Vol. 05, 2026, pp. 161â166, open access\",\"organizations\":[\"National Teachers Training Center for Health Professions, University of the Philippines Manila\"],\"stat\":{\"value\":\"11\",\"label\":\"granular themes from the Evidano codebook\"},\"sourceUrl\":\"https://ammspub.com/index.php/amms/article/view/469\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/up-manila.png\",\"alt\":\"University of the Philippines seal\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/master-health-professions-education-medical-educators\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:costa-rica-national-evaluation-agenda\",\"kind\":\"evidence\",\"href\":\"/research-spotlights/costa-rica-national-evaluation-agenda\",\"title\":\"Casos de estudio sobre el proceso OCDE â Costa Rica: una guÃa académica para docentes y estudiantes de Administración Pública\",\"summary\":\"For a book chapter meta-evaluating Costa Ricaâs National Evaluation Agenda, Dr. Mora-MartÃnez used Evidano to apply a single evaluation framework across ten reports spanning employment, education, health, culture, and the environment, acting as evaluator while Evidano analyzed the documents.\",\"tags\":[\"academia\",\"global-development\",\"health\"],\"year\":2026,\"provenance\":\"Esteban O. Mora-MartÃnez · University of Costa Rica\",\"organizations\":[\"University of Costa Rica\"],\"sourceUrl\":\"https://cicap.ucr.ac.cr/casos-de-estudio-sobre-el-proceso-ocde-costa-rica-una-guia-academica-para-docentes-y-estudiantes-de-administracion-publica/\",\"doi\":\"$undefined\",\"art\":\"findings\",\"facets\":[\"spotlight\"]},{\"id\":\"evidence:neurodivergent-workplace-inclusion-belonging\",\"kind\":\"evidence\",\"href\":\"/research-spotlights/neurodivergent-workplace-inclusion-belonging\",\"title\":\"Through Their Eyes: Neurodivergent Perspectives on Workplace Inclusion and Belonging Initiatives\",\"summary\":\"For a descriptive phenomenological dissertation on how neurodivergent adults experience workplace inclusion and belonging initiatives, Dr. Leanos used Evidano to apply the Moustakas method to ten interview transcripts and generate initial codes and theme concepts, then cross-referenced the codebook against the transcripts and revised the meaning units by hand.\",\"tags\":[\"phenomenology\",\"thematic-analysis\",\"interviews\",\"academia\",\"content-framework\"],\"year\":2026,\"provenance\":\"Allison Leanos · University of La Verne\",\"organizations\":[\"University of La Verne\"],\"sourceUrl\":\"https://researchworks.laverne.edu/esploro/outputs/doctoral/Through-Their-Eyes-Neurodivergent-Perspectives-on/991004382102406311\",\"doi\":\"$undefined\",\"art\":\"findings\",\"facets\":[\"spotlight\"]},{\"id\":\"evidence:actualized-leadership-profile-leadership-theories\",\"kind\":\"evidence\",\"href\":\"/research-spotlights/actualized-leadership-profile-leadership-theories\",\"title\":\"The Intersection of the Actualized Leadership Profile (ALP) and Transformational, Adaptive, Connective, and Servant Leadership Theories\",\"summary\":\"For a theory-based dissertation, Racha Zeitoun mapped the Actualized Leadership Profile against transformational, adaptive, connective, and servant leadership through a qualitative comparative analysis of the foundational literature â the kind of document-heavy conceptual work Evidano is built to supp
81ort.\",\"tags\":[\"content-framework\",\"evidence-synthesis\",\"documents-policy\",\"academia\",\"outcome-impact\"],\"year\":2026,\"provenance\":\"Racha Zeitoun · University of La Verne\",\"organizations\":[\"University of La Verne\"],\"sourceUrl\":\"https://researchworks.laverne.edu/esploro/outputs/doctoral/The-Intersection-of-the-Actualized-Leadership/991004388702406311\",\"doi\":\"$undefined\",\"art\":\"findings\",\"facets\":[\"spotlight\"]},{\"id\":\"evidence:undp-evaluation-ai-coding-interviews\",\"kind\":\"evidence\",\"href\":\"/case-studies/undp-evaluation-ai-coding-interviews\",\"title\":\"UNDPâs Latin America and Caribbean evaluation used AI-assisted qualitative coding\",\"summary\":\"Inside a 2025 UN Development Programme evaluation: transparent, human-reviewed AI qualitative analysis of 70+ interviews, survey responses, and documents.\",\"tags\":[\"global-development\",\"content-framework\",\"interviews\"],\"year\":2025,\"provenance\":\"Final Evaluation of the UNDP Regional Programme for Latin America and the Caribbean 2022â2025, UNDP Evaluation Resource Centre (October 2025)\",\"organizations\":[\"UNDP Regional Bureau for Latin America and the Caribbean (RBLAC)\",\"UNDP Evaluation Resource Centre\"],\"stat\":{\"value\":\"103\",\"label\":\"informants engaged\"},\"sourceUrl\":\"https://erc.undp.org/evaluation/evaluations/detail/13886\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/logo_govt/8.png\",\"alt\":\"UNDP logo\"},\"art\":\"coding\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:unesco-synthesis-evaluations-ai-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/unesco-synthesis-evaluations-ai-analysis\",\"title\":\"UNESCO IOS synthesis of 50 evaluations triangulated with AI thematic analysis\",\"summary\":\"Evidano (previously AILYZE) supported and triangulated the analysis behind UNESCOâs 2025 Synthesis of Evaluations, the largest since the series began in 2017.\",\"tags\":[\"global-development\",\"evidence-synthesis\",\"documents-policy\",\"second-coder\",\"synthesis\"],\"year\":2025,\"provenance\":\"2025 Synthesis of UNESCO Evaluations, IOS/EVS/PI 229, UNESCO IOS Evaluation Office (June 2025)\",\"organizations\":[\"UNESCO Internal Oversight Services (IOS) Evaluation Office\",\"Buddhi Consultancy Limited\"],\"stat\":{\"value\":\"50\",\"label\":\"evaluation reports analysed, the most since the synthesis began in 2017\"},\"sourceUrl\":\"https://unesdoc.unesco.org/ark:/48223/pf0000395374\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/logo_govt/10.png\",\"alt\":\"UNESCO logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-unesco-2025\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:unesco-museums-programme-evaluation-ai\",\"kind\":\"evidence\",\"href\":\"/case-studies/unesco-museums-programme-evaluation-ai\",\"title\":\"UNESCOâs Museums Programme evaluation used AI-assisted coding of 163 project reports\",\"summary\":\"A UN evaluation office used Evidano to screen 582 projects and code 163 reports against its own schema, validating a sample analysis before scaling up.\",\"tags\":[\"global-development\",\"content-framework\",\"documents-policy\"],\"year\":2025,\"provenance\":\"Evaluation of UNESCOâs Museums Programme, IOS/EVS/PI 228, UNESCO IOS Evaluation Office (August 2025)\",\"organizations\":[\"UNESCO Internal Oversight Services (IOS) Evaluation Office\",\"UNESCO Culture Sector\"],\"stat\":{\"value\":\"582 â 230\",\"label\":\"candidate projects screened down to museum-related records with Evidano\"},\"sourceUrl\":\"https://unesdoc.unesco.org/ark:/48223/pf0000395199\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/logo_govt/10.png\",\"alt\":\"UNESCO logo\"},\"art\":\"coding\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:wfp-mali-resilience-evaluation-ai\",\"kind\":\"evidence\",\"href\":\"/case-studies/wfp-mali-resilience-evaluation-ai\",\"title\":\"WFP Mali evaluation: AI-assisted qualitative analysis of 47 interviews and 22 focus groups\",\"summary\":\"A published United Nations World Food Programme evaluation disclosed Evidano (previously AILYZE) in its data analysis methods, alongside a researcher-built codebook.\",\"tags\":[\"global-development\",\"content-framework\",\"interviews\"],\"year\":2025,\"provenance\":\"WFP decentralized evaluation DE/MLCO/2019/020, final report, December 2025 (French)\",\"organizations\":[\"World Food Programme (WFP) Mali Country Office\",\"International Advisory, Products and Systems (i-APS)\"],\"stat\":{\"value\":\"47\",\"label\":\"Key informant interviews\"},\"sourceUrl\":\"https://www.wfp.org/publications/mali-decentralized-evaluation-integrated-resilience-package-20-priority-communes-2018\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/logo_govt/2.png\",\"alt\":\"World Food Programme logo\"},\"art\":\"interviews\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:african-development-bank-evaluation-ai\",\"kind\":\"evidence\",\"href\":\"/case-studies/african-development-bank-evaluation-ai\",\"title\":\"African Development Bank evaluation: AI-assisted evidence coding, validated with Evidano\",\"summary\":\"Named as the validation tool in the AI-assisted methodology of an African Development Bank evaluation, within a human-supervised workflow.\",\"tags\":[\"global-development\",\"content-framework\",\"documents-policy\"],\"year\":2025,\"provenance\":\"IDEV Inception Report, Evaluation of the Implementation of the AfDBâs Selectivity Framework (2013â2024), prepared by SEO Amsterdam Economics, April 2025\",\"organizations\":[\"Independent Development Evaluation (IDEV), African Development Bank Group\",\"SEO Amsterdam Economics\"],\"stat\":{\"value\":\"2,500+\",\"label\":\"operations in the portfolio under evaluation\"},\"sourceUrl\":\"https://idev.afdb.org/en/document/evaluation-implementation-afdbs-selectivity-framework-0\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/afdb.png\",\"alt\":\"African Development Bank Group logo\"},\"art\":\"findings\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:sparc-fcdo-farmer-herder-conflict-research\",\"kind\":\"evidence\",\"href\":\"/case-studies/sparc-fcdo-farmer-herder-conflict-research\",\"title\":\"SPARC policy brief: AI-assisted qualitative synthesis of farmerâherder conflict research\",\"summary\":\"UK aid-funded research across three countries, synthesised with AI support and reviewed by named peer reviewers, including from the UN mediation support unit.\",\"tags\":[\"global-development\",\"content-framework\",\"documents-policy\",\"interviews\"],\"year\":2025,\"provenance\":\"SPARC Knowledge policy brief, London, November 2025 (ISSN 2977-9650)\",\"organizations\":[\"SPARC (Supporting Pastoralism and Agriculture in Recurrent and Protracted Crises)\",\"International Livestock Research Institute (ILRI)\",\"ODI Global\"],\"stat\":{\"value\":\"3\",\"label\":\"countries studied (Sudan, Nigeria, Mali)\"},\"sourceUrl\":\"https://doi.org/10.61755/SQIM9261\",\"doi\":\"10.61755/sqim9261\",\"logo\":{\"src\":\"/case-study-logos/sparc.png\",\"alt\":\"SPARC logo\"},\"art\":\"documents\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:fao-zambia-plos-ai-sentiment-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/fao-zambia-plos-ai-sentiment-analysis\",\"t
81itle\":\"University of Zambia and FAO: AI-assisted focus group analysis published in PLOS NTDs\",\"summary\":\"Sentiment analysis on focus group transcripts in three local languages, with every theme cross-referenced against verbatim quotes by the researchers.\",\"tags\":[\"global-development\",\"content-framework\",\"focus-groups\",\"thematic-analysis\",\"academia\"],\"year\":2025,\"provenance\":\"PLOS Neglected Tropical Diseases 19(5): e0012852 (2025), open access\",\"organizations\":[\"University of Zambia, School of Veterinary Medicine\",\"FAO Emergency Centre for Transboundary Animal Diseases (ECTAD)\",\"Lilongwe University of Agriculture and Natural Resources\"],\"stat\":{\"value\":\"6\",\"label\":\"Focus group discussions\"},\"sourceUrl\":\"https://doi.org/10.1371/journal.pntd.0012852\",\"doi\":\"10.1371/journal.pntd.0012852\",\"logo\":{\"src\":\"/images/publications/plos.png\",\"alt\":\"PLOS logo\"},\"art\":\"interviews\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/anthrax-risk-farming-communities-zambia\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:arizona-state-thematic-analysis-education-sciences\",\"kind\":\"evidence\",\"href\":\"/case-studies/arizona-state-thematic-analysis-education-sciences\",\"title\":\"Arizona State Universityâs AI thematic analysis of therapy-dog handler interviews\",\"summary\":\"Disclosed in the methods, validated by the researcher, and rerun to confirm quote alignment, in a peer-reviewed Education Sciences study (2025).\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"thought-partner\",\"second-coder\",\"initial-coding\",\"health\"],\"year\":2025,\"provenance\":\"Education Sciences (MDPI), 15(7), 929, open access\",\"organizations\":[\"Arizona State University\",\"Mary Lou Fulton College for Teaching and Learning Innovation\"],\"stat\":{\"value\":\"7\",\"label\":\"handler interviews analyzed, 45 to 60 minutes each\"},\"sourceUrl\":\"https://doi.org/10.3390/educsci15070929\",\"doi\":\"10.3390/educsci15070929\",\"logo\":{\"src\":\"/case-study-logos/asu.png\",\"alt\":\"Arizona State University logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-farrand-jung-2025\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:university-trieste-teacher-responses-themes\",\"kind\":\"evidence\",\"href\":\"/case-studies/university-trieste-teacher-responses-themes\",\"title\":\"University of Trieste: AI thematic analysis of 54 science teachersâ survey responses\",\"summary\":\"A 2025 mixed-methods education study cited Evidano (previously AILYZE) in its methods to identify themes across science teachersâ open-ended responses.\",\"tags\":[\"academia\",\"thematic-analysis\",\"open-ended-survey\",\"initial-coding\",\"synthesis\",\"global-development\"],\"year\":2025,\"provenance\":\"Education and New Developments 2025, Vol. I (inScience Press), pp. 321â325\",\"organizations\":[\"University of Trieste\"],\"stat\":{\"value\":\"75\",\"label\":\"teachers in the training program\"},\"sourceUrl\":\"https://doi.org/10.36315/2025v1end074\",\"doi\":\"10.36315/2025v1end074\",\"logo\":{\"src\":\"/case-study-logos/university-trieste.png\",\"alt\":\"University of Trieste logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-bologna-bembich-2025\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:peking-university-ai-assisted-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/peking-university-ai-assisted-analysis\",\"title\":\"Peking University \u0026 University of Zambia: AI-assisted qualitative coding of 34 interviews\",\"summary\":\"A peer-reviewed Elsevier study paired manual coding with AI-assisted analysis across 34 interviews, two focus groups, documents, and social media data.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"focus-groups\",\"content-framework\",\"documents-policy\",\"web-social\"],\"year\":2025,\"provenance\":\"Social Sciences \u0026 Humanities Open, 11:101465 (Elsevier, 2025), open access\",\"organizations\":[\"Peking University, Graduate School of Education\",\"University of Zambia\"],\"stat\":{\"value\":\"34\",\"label\":\"in-depth interviews\"},\"sourceUrl\":\"https://doi.org/10.1016/j.ssaho.2025.101465\",\"doi\":\"10.1016/j.ssaho.2025.101465\",\"logo\":{\"src\":\"/images/publications/peking.png\",\"alt\":\"Peking University logo\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/open-educational-resources-zambian-community-schools\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:oida-grounded-theory-content-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/oida-grounded-theory-content-analysis\",\"t
81itle\":\"NUBiP of Ukraine: AI-assisted grounded theory categorisation across 35 literature sources\",\"summary\":\"An international journal article used Evidano for grounded theory categorisation of its literature sample, then applied content and discourse analysis by hand.\",\"tags\":[\"academia\",\"grounded-theory\",\"content-framework\",\"narrative-discourse\",\"documents-policy\"],\"year\":2025,\"provenance\":\"OIDA International Journal of Sustainable Development, 18(11): 321â330 (2025)\",\"organizations\":[\"National University of Life and Environmental Sciences of Ukraine\",\"Sumy State Pedagogical University\",\"Igor Sikorsky Kyiv Polytechnic Institute\"],\"stat\":{\"value\":\"35\",\"label\":\"literature sources analysed\"},\"sourceUrl\":\"https://oidaijsd.com/wp-content/uploads/2025/09/18-11-27-23-18-IJSD-UR-3-25-SK.pdf\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/oida.jpg\",\"alt\":\"OIDA International logo\"},\"art\":\"themes\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:chengchi-university-interview-codebook\",\"kind\":\"evidence\",\"href\":\"/case-studies/chengchi-university-interview-codebook\",\"title\":\"National Chengchi University published an AI interview analysis case study of Evidano\",\"summary\":\"A university research team demonstrated Evidano end to end on eight interview transcripts, from codebook and themes to quotes and frequency charts, in a methods article.\",\"tags\":[\"academia\",\"content-framework\",\"interviews\",\"thematic-analysis\"],\"year\":2025,\"provenance\":\"Journal of Education Research (æè²ç ç©¶æå), No. 375, pp. 128â145 (July 2025)\",\"organizations\":[\"National Chengchi University, College of Education\"],\"stat\":{\"value\":\"8\",\"label\":\"interview transcripts analyzed\"},\"sourceUrl\":\"https://doi.org/10.53106/168063602025070375009\",\"doi\":\"10.53106/168063602025070375009\",\"logo\":{\"src\":\"/case-study-logos/chengchi.png\",\"alt\":\"National Chengchi University logo\"},\"art\":\"interviews\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/ai-qualitative-interview-analysis\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:glasgow-erasmus-thesis-ai-coding\",\"kind\":\"evidence\",\"href\":\"/case-studies/glasgow-erasmus-thesis-ai-coding\",\"title\":\"University of GlasgowâErasmus thesis: AI-assisted qualitative coding of 13 interviews\",\"summary\":\"An AI tool was named in the data analysis section of a 2025 University of Glasgow and Erasmus University Rotterdam thesis. Here is what it supported.\",\"tags\":[\"academia\",\"content-framework\",\"interviews\",\"transcripts-av\"],\"year\":2025,\"provenance\":\"Masterâs thesis, MA Managing Art and Cultural Heritage in Global Markets (Erasmus Mundus), University of Glasgow and Erasmus University Rotterdam, 2025\",\"organizations\":[\"University of Glasgow\",\"Erasmus University Rotterdam\"],\"stat\":{\"value\":\"13\",\"label\":\"semi-structured interviews\"},\"sourceUrl\":\"https://thesis.eur.nl/pub/76844\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/glasgow.png\",\"alt\":\"University of Glasgow arms\"},\"art\":\"coding\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:ethnographic-thinking-ai-pattern-refinement\",\"kind\":\"evidence\",\"href\":\"/case-studies/ethnographic-thinking-ai-pattern-refinement\",\"title\":\"Antropoloogia Keskus: AI-assisted pattern refinement across 31 ethnographic interviews\",\"summary\":\"An ethnographic thinking framework and thematic analysis of a girlsâ technology programme, with AI used to check and refine patterns on pseudonymised texts.\",\"tags\":[\"academia\",\"ethnography\",\"thematic-analysis\",\"interviews\"],\"year\":2025,\"provenance\":\"Antropoloogia Keskus research report for HK Unicorn Squad (commissioned by Proud Engineers), 2025\",\"organizations\":[\"Antropoloogia Keskus\",\"HK Unicorn Squad\"],\"stat\":{\"value\":\"31\",\"label\":\"in-depth interviews across four respondent groups\"},\"sourceUrl\":\"https://unicornsquad.ee/wp-content/uploads/2026/03/HK-Unicorn-Squadi-programmi-kogemuse-ja-moju-uuring.pdf\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/estonian-anthropology.png\",\"alt\":\"Antropoloogia Keskus logo\"},\"art\":\"interviews\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:illinois-consortium-62-institutions-ai-themes\",\"kind\":\"evidence\",\"href\":\"/case-studies/illinois-consortium-62-institutions-ai-themes\",\"title\":\"Illinois Board of Higher Education \u0026 ICCB: AI theme analysis across 62 institutions\",\"summary\":\"Evidano surfaced themes across six quarters of data from a 62-institution consortium, with report staff re-reading all raw data to validate every finding.\",\"tags\":[\"government\",\"thematic-analysis\",\"documents-policy\",\"second-coder\",\"synthesis\"],\"year\":2025,\"provenance\":\"Second Annual Report of the Early Childhood Access Consortium for Equity (IBHE \u0026 ICCB, 2025)\",\"organizations\":[\"Illinois Board of Higher Education\",\"Illinois Community College Board\",\"Afton Partners\"],\"stat\":{\"value\":\"62\",\"label\":\"institutions whose data was analyzed: 41 community colleges, 11 public and 10 private universities\"},\"sourceUrl\":\"https://archive.ibhe.org/ECACE/assets/documents/2025/ECACE_2nd_Annual_Report_2.5.25.pdf\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/iccb.png\",\"alt\":\"Illinois Community College Board logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-ibhe-2024\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:hungarian-sign-language-learners-ai-themes\",\"kind\":\"evidence\",\"href\":\"/case-studies/hungarian-sign-language-learners-ai-themes\",\"title\":\"IBS Budapest study: AI thematic analysis of Hungarian sign language learner responses\",\"summary\":\"Evidano surfaced five themes from open-ended responses, in Hungarian, and converged with the researcherâs own analysis on the central role of video materials.\",\"tags\":[\"academia\",\"thematic-analysis\",\"open-ended-survey\",\"grounded-theory\"],\"year\":2025,\"provenance\":\"TESOL-Hungary Conference Selections: Three TESOL Treats (TESOL-Hungary, Budapest, 2025), pp. 25â55\",\"organizations\":[\"International Business Sc
81hool Budapest\",\"TESOL-Hungary\"],\"stat\":{\"value\":\"31\",\"label\":\"sign language learners surveyed\"},\"sourceUrl\":\"https://tesol-hungary.org/wp-content/uploads/2025/09/Three-TESOL-Treats.pdf\",\"doi\":\"$undefined\",\"logo\":\"$undefined\",\"art\":\"themes\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/hungarian-sign-language-learners\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:glasgow-ceeres-thesis-ai-initial-codes\",\"kind\":\"evidence\",\"href\":\"/case-studies/glasgow-ceeres-thesis-ai-initial-codes\",\"title\":\"CEERES thesis (Glasgow, Tartu, Ilia State) used AI-assisted coding on 12 expert interviews\",\"summary\":\"A researcher generated initial codes with AI, then reviewed every one against the research question. Transparent, disclosed, human-led.\",\"tags\":[\"academia\",\"content-framework\",\"interviews\"],\"year\":2025,\"provenance\":\"CEERES Masterâs thesis, Ilia State University, University of Glasgow and University of Tartu (University of Tartu DSpace, 2025)\",\"organizations\":[\"University of Glasgow\",\"Ilia State University\",\"University of Tartu\"],\"stat\":{\"value\":\"12\",\"label\":\"expert interviews: 4 academia, 4 international organisations, 4 civil society\"},\"sourceUrl\":\"https://hdl.handle.net/10062/117271\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/glasgow.png\",\"alt\":\"University of Glasgow arms\"},\"art\":\"coding\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:naval-postgraduate-school-thesis-ai-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/naval-postgraduate-school-thesis-ai-analysis\",\"title\":\"Naval Postgraduate School thesis: AI-assisted Gioia analysis of 25 Marine Corps interviews\",\"summary\":\"A Naval Postgraduate School thesis surfaced 62 first-order concepts from 799 interview excerpts with Evidano, then refined them by hand into a six-theme Gioia model.\",\"tags\":[\"government\",\"content-framework\",\"interviews\"],\"year\":2025,\"provenance\":\"Acquisition Research Program Sponsored Report Series, NPS-HR-26-046 (Naval Postgraduate School), June 2025\",\"organizations\":[\"Naval Postgraduate School\",\"Department of Defense Management, Naval Postgraduate School\",\"U.S. Marine Corps\"],\"stat\":{\"value\":\"25\",\"label\":\"in-depth interviews, 71 minutes on average\"},\"sourceUrl\":\"https://hdl.handle.net/10945/74187\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/naval-postgraduate-school.png\",\"alt\":\"Naval Postgraduate School seal\"},\"art\":\"interviews\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:southern-african-parliaments-digital-leadership\",\"kind\":\"evidence\",\"href\":\"/case-studies/southern-african-parliaments-digital-leadership\",\"title\":\"University of Zambia study of 13 SADC parliaments used AI thematic analysis\",\"summary\":\"A 2025 study of digital leadership across Southern African parliaments disclosed Evidano for thematic analysis of its focus group and open-ended survey data.\",\"tags\":[\"government\",\"thematic-analysis\",\"focus-groups\"],\"year\":2025,\"provenance\":\"International Journal of Research and Innovation in Social Science (IJRISS), Vol. IX Issue IV, 2025, open access\",\"organizations\":[\"University of Zambia\",\"Southern African Development Community (SADC) parliaments\"],\"stat\":{\"value\":\"23\",\"label\":\"digital leaders in the study sample\"},\"sourceUrl\":\"https://doi.org/10.47772/IJRISS.2025.90400385\",\"doi\":\"10.47772/ijriss.2025.90400385\",\"logo\":{\"src\":\"/case-study-logos/ijriss.png\",\"alt\":\"RSIS International logo\"},\"art\":\"themes\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:policing-journal-ai-scoping-review\",\"kind\":\"evidence\",\"href\":\"/case-studies/policing-journal-ai-scoping-review\",\"title\":\"ENAP researchers ran an AI-assisted scoping review of 60 policing studies\",\"summary\":\"Used to structure data extraction from 60 peer-reviewed studies in Policing: An International Journal, with researcher oversight throughout.\",\"tags\":[\"government\",\"evidence-synthesis\",\"documents-policy\",\"academia\"],\"year\":2025,\"provenance\":\"Policing: An International Journal, Vol. 48 No. 6, pp. 1391â1411 (Emerald Publishing), 2025\",\"organizations\":[\"Ãcole nationale dâadministration publique (ENAP)\",\"University of Technology Sydney\",\"Université du Québec à Trois-Rivières\"],\"stat\":{\"value\":\"60\",\"label\":\"peer-reviewed studies analyzed\"},\"sourceUrl\":\"https://doi.org/10.1108/PIJPSM-05-2025-0077\",\"doi\":\"10.1108/pijpsm-05-2025-0077\",\"logo\":{\"src\":\"/case-study-logos/emerald.png\",\"alt\":\"Emerald Publishing logo\"},\"art\":\"ai-chat\",\"facets\":[\"case-study\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/research-spotlights/civilian-personnel-modern-policing\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:indonesia-ministry-finance-ai-literature-review\",\"kind\":\"evidence\",\"href\":\"/case-studies/indonesia-ministry-finance-ai-literature-review\",\"title\":\"Indonesian Ministry of Finance researcher used AI thematic analysis for a coaching review\",\"summary\":\"A transparent, AI-assisted systematic literature review that surfaced five themes from about 20 papers, with the researcherâs manual review of 15 more alongside.\",\"tags\":[\"government\",\"evidence-synthesis\",\"thematic-analysis\",\"documents-policy\"],\"year\":2025,\"provenance\":\"Prosiding PITNAS Widyaiswara (Ikatan Widyaiswara Indonesia), Vol. 1 No. 1, 2025, pp. 411â427, open access\",\"organizations\":[\"Pusdiklat Kepemimpinan dan Manajerial, BPPK (Ministry of Finance of the Republic of Indonesia)\"],\"stat\":{\"value\":\"30\",\"label\":\"Scopus-indexed articles reviewed\"},\"sourceUrl\":\"https://www.ejournal.iwi.or.id/ojs/index.php/pitnas2024/article/view/366\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/indonesia-mof.png\",\"alt\":\"Indonesian Ministry of Finance seal\"},\"art\":\"themes\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:nutrition-clinical-practice-thematic-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/nutrition-clinical-practice-thematic-analysis\",\"t
81itle\":\"Bowling Green State University triangulated dietitian interviews with AI thematic analysis\",\"summary\":\"Researchers ran two independent Evidano analyses, one AI-coded and one using their own codebook, and compared both against their manual reflexive thematic analysis.\",\"tags\":[\"health\",\"thematic-analysis\",\"interviews\",\"second-coder\",\"initial-coding\",\"implementation\"],\"year\":2025,\"provenance\":\"Nutrition in Clinical Practice 40(6): 1465â1482 (Wiley, for ASPEN), open access\",\"organizations\":[\"Bowling Green State University\",\"Academy of Nutrition and Dietetics\",\"University of New Mexico\"],\"stat\":{\"value\":\"10\",\"label\":\"dietitians interviewed\"},\"sourceUrl\":\"https://doi.org/10.1002/ncp.70043\",\"doi\":\"10.1002/ncp.70043\",\"logo\":{\"src\":\"/case-study-logos/aspen-nutrition.png\",\"alt\":\"American Society for Parenteral and Enteral Nutrition logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-knippen-2025\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:who-backed-philippines-adr-thematic-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/who-backed-philippines-adr-thematic-analysis\",\"title\":\"Philippine FDAâs WHO/TDR-funded pharmacovigilance study used AI thematic analysis\",\"summary\":\"A TDR-funded mixed-methods study on adverse drug reaction reporting used Evidano on its focus group transcripts, with outputs cross-checked by two independent coders.\",\"tags\":[\"health\",\"thematic-analysis\",\"interviews\",\"second-coder\",\"synthesis\"],\"year\":2025,\"provenance\":\"Drugs â Real World Outcomes 12(3): 367â381 (Adis / Springer Nature), open access\",\"organizations\":[\"Philippine Food and Drug Administration (National Pharmacovigilance Center)\",\"Philippine Womenâs University, School of Pharmacy\"],\"stat\":{\"value\":\"4,364\",\"label\":\"healthcare professionals surveyed in the quantitative strand\"},\"sourceUrl\":\"https://doi.org/10.1007/s40801-025-00492-z\",\"doi\":\"10.1007/s40801-025-00492-z\",\"logo\":{\"src\":\"/case-study-logos/springer.png\",\"alt\":\"Springer Nature logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-lirasan-2025\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:rillero-2025\",\"kind\":\"evidence\",\"href\":\"/cite-us#pub-rillero-2025\",\"title\":\"Unraveling the Fictionalized Ideal: The Rise of âTheâ Scientific Method in the 19th Century\",\"summary\":\"The researchers assembled passages concerning historical definitions and representations of the scientific method. Evidano supported the theme-based analysis by identifying, categorizing, and refining candidate themes across the text. The authors reviewed the generated themes, revised their language, and moved through explicit stages of initial coding, theme development, refinement, and validation before finalizing the findings.\",\"tags\":[\"initial-coding\",\"content-framework\",\"open-ended-survey\",\"academia\"],\"year\":2025,\"provenance\":\"Science \u0026 Education · History \u0026 philosophy of science\",\"sourceUrl\":\"https://doi.org/10.1007/s11191-025-00690-9\",\"doi\":\"10.1007/s11191-025-00690-9\",\"logo\":{\"src\":\"/case-study-logos/springer.png\",\"alt\":\"Springer Nature logo\"},\"art\":\"interviews\",\"facets\":[\"publication\"]},{\"id\":\"evidence:autism-communication-parents-emotional-wellbeing\",\"kind\":\"evidence\",\"href\":\"/research-spotlights/autism-communication-parents-emotional-wellbeing\",\"title\":\"Insights into Communication Differences of ASD Children and their Parentsâ Emotional State\",\"summary\":\"For a qualitative study of parents of autistic children in Gujranwala, Pakistan, Mehak Afzalâs team coded in-depth interviews in ATLAS.ti and used Evidano for theme extraction, then reviewed the generated themes themselves â merging duplicates and clarifying the ones that needed further interpretation.\",\"tags\":[\"thematic-analysis\",\"interviews\",\"health\",\"contextual-inquiry\",\"academia\"],\"year\":2025,\"provenance\":\"Mehak Afzal · GIFT University, Pakistan\",\"organizations\":[\"GIFT University, Pakistan\"],\"sourceUrl\":\"https://doi.org/10.55966/assaj.2025.4.1.091\",\"doi\":\"10.55966/assaj.2025.4.1.091\",\"art\":\"findings\",\"facets\":[\"spotlight\"]},{\"id\":\"evidence:cop29-climate-leadership-rhetoric-azerbaijan\",\"kind\":\"evidence\",\"href\":\"/research-spotlights/cop29-climate-leadership-rhetoric-azerbaijan\",\"title\":\"A Thematic Analysis of the Azerbaijani Governmentâs Use of COP29 in Constructing an International Image of Climate Leadership and Legitimizing Its Regime\",\"summary\":\"For a thematic analysis of President Ilham Aliyevâs COP29 speeches, Chau Pham used Evidano to visualize recurring patterns in the language â including the prominence of words such as gas, energy, green, and oil â while the coding, theme development, and interpretation stayed with the researcher.\",\"tags\":[\"thematic-analysis\",\"narrative-discourse\",\"documents-policy\",\"government\",\"global-development\"],\"year\":2025,\"provenance\":\"Chau Pham · Vietnam\",\"organizations\":[\"Vietnam\"],\"sourceUrl\":\"https://doi.org/10.2139/ssrn.5389361\",\"doi\":\"10.2139/ssrn.5389361\",\"art\":\"findings\",\"facets\":[\"spotlight\"]},{\"id\":\"evidence:unicef-ai-assisted-analysis-vs-manual-coding\",\"kind\":\"evidence\",\"href\":\"/case-studies/unicef-ai-assisted-analysis-vs-manual-coding\",\"title\":\"UNICEF tested AI-assisted qualitative coding against manual coding on 160 evaluations\",\"summary\":\"Same 160 management responses, AI and manual coding side by side. See where Evidano matched human analysts, where humans stayed essential, and what each approach cost.\",\"tags\":[\"global-development\",\"content-framework\",\"open-ended-survey\",\"documents-policy\",\"thought-partner\",\"second-coder\",\"synthesis\"],\"year\":2024,\"provenance\":\"UNICEF Office of Emergency Programmes review report, New York, November 2024\",\"organizations\":[\"UNICEF Office of Emergency Programmes (EMOPS)\",\"UNICEF Evaluation Office\"],\"stat\":{\"value\":\"160\",\"label\":\"management responses\"},\"sourceUrl\":\"https://www.evalcommunity.com/wp-content/uploads/2026/04/teams-DAPM-Knowledge-DocumentLibrary1-Rev-of-Mgmt-Responses-to-Humanitarian-Evaluations-2017%E2%80%932024-11Oct2024-2.0.pdf\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/images/publications/unicef.png\",\"alt\":\"UNICEF logo\"},\"art\":\"coding\",\"facets\":[\"case-study\",\"publication\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-unicef-2024\",\"label\":\"See how it was cited\"}]},{\"id\":\"evidence:william-mary-mensa-open-ended-responses\",\"kind\":\"evidence\",\"href\":\"/case-studies/william-mary-mensa-open-ended-responses\",\"title\":\"William \u0026 Maryâs AI thematic analysis of 19,000+ open-ended responses from 3,443 adults\",\"summary\":\"AI-assisted thematic analysis of 12 open-ended questions in batches of 150 responses, each run three times and verified quote by quote by a human researcher.\",\"tags\":[\"academia\",\"thematic-analysis\",\"open-ended-survey\",\"second-coder\",\"initial-coding\",\"synthesis\"],\"year\":2024,\"provenance\":\"Research report by the William \u0026 Mary Center for Gifted Education for the Mensa Foundation, May 2024 (W\u0026M ScholarWorks)\",\"organizations\":[\"William \u0026 Mary Center for Gifted Education\",\"Mensa Foundation\"],\"stat\":{\"value\":\"3,443\",\"label\":\"participants in the study\"},\"sourceUrl\":\"https://scholarworks.wm.edu/cgereports/7/\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/william-mary.png\",\"alt\":\"William \u0026 Mary logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-cross-2024\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/unmet-needs-highly-intelligent-adults\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:elsevier-ssho-ai-theme-identification\",\"kind\":\"evidence\",\"href\":\"/case-studies/elsevier-ssho-ai-theme-identification\",\"title\":\"Petra Christian University: AI theme identification from English teachersâ interviews\",\"summary\":\"A published, open-access qualitative study disclose
81s how AI-assisted theme identification sat inside a human-reviewed workflow.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\"],\"year\":2024,\"provenance\":\"Social Sciences \u0026 Humanities Open, 9:100846 (Elsevier, 2024), open access\",\"organizations\":[\"Petra Christian University\",\"Universitas Negeri Malang\",\"National Institute of Education, Nanyang Technological University\"],\"stat\":{\"value\":\"10\",\"label\":\"in-depth, semi-structured interviews\"},\"sourceUrl\":\"https://doi.org/10.1016/j.ssaho.2024.100846\",\"doi\":\"10.1016/j.ssaho.2024.100846\",\"logo\":{\"src\":\"/case-study-logos/elsevier.png\",\"alt\":\"Elsevier logo\"},\"art\":\"themes\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:studies-educational-evaluation-ai-thematic-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/studies-educational-evaluation-ai-thematic-analysis\",\"title\":\"Monash University study trialled AI thematic analysis to cross-check its themes\",\"summary\":\"See how doctoral education researchers trialled Evidano for thematic analysis, with human researchers leading every interpretation.\",\"tags\":[\"academia\",\"thematic-analysis\",\"interviews\",\"thought-partner\",\"second-coder\",\"global-development\",\"open-ended-survey\"],\"year\":2024,\"provenance\":\"Studies in Educational Evaluation, vol. 83, 101379 (Elsevier, 2024), open access\",\"organizations\":[\"Monash University, Faculty of Education\",\"American University of the Middle East\"],\"stat\":{\"value\":\"23\",\"label\":\"doctoral writersâ responses analysed, from 29 recruited\"},\"sourceUrl\":\"https://doi.org/10.1016/j.stueduc.2024.101379\",\"doi\":\"10.1016/j.stueduc.2024.101379\",\"logo\":{\"src\":\"/logo_universities/Studies in Educational Evaluation.png\",\"alt\":\"Studies in Educational Evaluation journal logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-cahusac-pretorius-2024\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/doctoral-writing-groups-peer-feedback\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:unitar-evaluation-ai-theme-analysis\",\"kind\":\"evidence\",\"href\":\"/case-studies/unitar-evaluation-ai-theme-analysis\",\"title\":\"UNITARâs Tanzania peacekeeping training evaluation used AI theme analysis of 45 informants\",\"summary\":\"A UN training institute used Evidano (previously AILYZE) for exploratory theme analysis of interview and focus group transcripts, with full evaluator oversight.\",\"tags\":[\"global-development\",\"thematic-analysis\",\"interviews\"],\"year\":2023,\"provenance\":\"Independent Evaluation of the Reinforcement of the Tanzania Peacekeeping Training Center Project, UNITAR PPME, December 2023\",\"organizations\":[\"United Nations Institute for Training and Research (UNITAR)\",\"UNITAR Planning, Performance Monitoring and Evaluation Unit\",\"Tanzania Peacekeeping Training Centre\"],\"stat\":{\"value\":\"45\",\"label\":\"informants interviewed (13 female, 32 male)\"},\"sourceUrl\":\"https://unitar.org/results-evidence-learning/evaluation/independent-evaluation-reinforcement-tanzania-peacekeeping-training-center-project\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/unitar.png\",\"alt\":\"UNITAR logo\"},\"art\":\"themes\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:jet-education-outcome-harvesting-ai\",\"kind\":\"evidence\",\"href\":\"/case-studies/jet-education-outcome-harvesting-ai\",\"title\":\"JET Education Services used AI-assisted qualitative analysis in a 200-outcome harvest\",\"summary\":\"A monitoring and evaluation team analysed 12 years of reports with researchers and Evidano, one of five evidence sources behind 200+ harvested outcomes.\",\"tags\":[\"global-development\",\"outcome-impact\",\"documents-policy\"],\"year\":2023,\"provenance\":\"JET Education Services Annual Report 2023, \\\"Working Towards Impact\\\" (published June 2024)\",\"organizations\":[\"JET Education Services\"],\"stat\":{\"value\":\"12 yrs\",\"label\":\"of reports (2011 to 2022) analysed with Evidano\"},\"sourceUrl\":\"https://www.jet.org.za/news/news/2023-jet-annual-report\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/jet-education.png\",\"alt\":\"JET Education Services logo\"},\"art\":\"findings\",\"facets\":[\"case-study\"]},{\"id\":\"evidence:cornell-ai-thematic-analysis-aaace\",\"kind\":\"evidence\",\"href\":\"/case-studies/cornell-ai-thematic-analysis-aaace\",\"title\":\"Cornellâs CLASP used AI thematic analysis on its program film. Adult educators concurred.\",\"summary\":\"A published Cornell study used Evidano (previously AILYZE) for thematic analysis of its program film, then compared the AIâs reading with expert educatorsâ reactions at AAACE 2023.\",\"tags\":[\"academia\",\"thematic-analysis\",\"transcripts-av\",\"thought-partner\",\"synthesis\"],\"year\":2023,\"provenance\":\"AAACE 2023 Conference Proceedings, pp. 118â124 (ERIC ED649311)\",\"organizations\":[\"Cornell University\",\"Community Learning and Service Partnership (CLASP), Cornell\"],\"stat\":{\"value\":\"8\",\"label\":\"themes identified in the thematic analysis\"},\"sourceUrl\":\"https://eric.ed.gov/?id=ED649311\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/cornell.png\",\"alt\":\"Cornell University logo\"},\"art\":\"themes\",\"facets\":[\"case-study\",\"publication\",\"spotlight\"],\"icon\":\"$undefined\",\"alsoAt\":[{\"href\":\"/cite-us#pub-raymer-nelson-2023\",\"label\":\"See how it was cited\"},{\"href\":\"/research-spotlights/cornell-clasp-adult-learning\",\"label\":\"Read the researcher spotlight\"}]},{\"id\":\"evidence:ufmg-migration-research-ai-vs-atlas-ti\",\"kind\":\"evidence\",\"href\":\"/case-studies/ufmg-migration-research-ai-vs-atlas-ti\",\"title\":\"UFMG: AI qualitative coding vs manual coding vs Atlas.ti on Pataxó migration interviews\",\"summary\":\"A study at the Federal University of Minas Gerais (UFMG) compared Evidano (previously AILYZE) with manual coding and Atlas.ti on the same real interview transcript.\",\"tags\":[\"academia\",\"content-framework\",\"interviews\"],\"year\":2023,\"provenance\":\"Anais do XIII Encontro Nacional sobre Migrações (ABEP / NEPO-UNICAMP), Campinas, November 2023, published 2024, pp. 177â184\",\"organizations\":[\"Federal University of Minas Gerais (UFMG)\",\"Department of Sociology, FAFICH/UFMG\"],\"stat\":{\"value\":\"Under 1 min\",\"label\":\"Evidano analysis time\"},\"sourceUrl\":\"https://www.nepo.unicamp.br/encontro2023-gts-abep/anais/anais-encontro-2023.pdf\",\"doi\":\"$undefined\",\"logo\":{\"src\":\"/case-study-logos/ufmg.png\",\"alt\":\"Federal University of Minas Gerais (UFMG) logo\"},\"art\":\"coding\",\"facets\":[\"case-study\"]}],\"sectorTags\":[{\"id\":\"academia\",\"group\":\"sector\",\"label\":\"Academic research\",\"shortLabel\":\"Academia\",\"description\":\"Dissertations, faculty research, peer-reviewed studies and methodological transparency.\",\"match\":[\"universit\",\"academic\",\"dissertation\",\"thesis\",\"doctoral\",\"faculty\",\"peer-review\",\"scholar\"]},{\"id\":\"global-development\",\"group\":\"sector\",\"label\":\"Program evaluation and global development\",\"shortLabel\":\"Evaluation\",\"description\":\"UN and donor evaluations, monitoring and evaluation, multi-country programmes.\",\"match\":[\"unicef\",\"undp\",\"unesco\",\"unfpa\",\"unitar\",\"wfp\",\"evaluation\",\"humanitarian\",\"donor\",\"development\"]},{\"id\":\"government\",\"group\":\"sector\",\"label\":\"Government and public sector\",\"shortLabel\":\"Government\",\"description\":\"Public consultations, citizen comments, policy evaluation and departmental research.\",\"match\":[\"government\",\"federal\",\"ministry\",\"parliament\",\"public sector\",\"policy\",\"civil service\",\"policing\"]},{\"id\":\"health\",\"group\":\"sector\",\"label\":\"Healthcare research\",\"shortLabel\":\"Healthcare\",\"description\":\"Patient and clinician research, implementation science, service evaluation, public health.\",\"match\":[\"health\",\"clinical\",\"patient\",\"clinician\",\"nursing\",\"medical\",\"pharmacovigilance\",\"dietit\",\"nutrition\"]},{\"id\":\"market-research\",\"group\":\"sector\",\"label\":\"Market research\",\"shortLabel\":\"Market\",\"description\":\"Customer interviews, concept testing, brand and product feedback research.\",\"match\":[\"market research\",\"consumer\",\"brand\",\"customer\",\"shopper\",\"commercial\"]},{\"id\":\"ux-product\",\"group\":\"sector\",\"label\":\"UX and product research\",\"shortLabel\":\"UX\",\"description\":\"User interviews, usability studies, product feedback synthesis and research repositories.\",\"match\":[\"ux\",\"user experience\",\"product research\",\"usability\",\"user interview\"]}]}],\"$L27\",\"$L28\",\"$L29\",\"$L2a\",\"$L2b\"],\"$L2c\",\"$L2d\",\"$L2e\",\"$L2f\"]}]\n"])</script>
81<script>self.__next_f.push([1,"54:I[133695,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/0wpt7ub5rom57.js\"],\"default\"]\n55:I[552257,[\"/_next/static/chunks/15tev3v-k6ykn.js\",\"/_next/static/chunks/0j6zc1fd6nfww.js\",\"/_next/static/chunks/014.cojmeu8r7.js\",\"/_next/static/chunks/0rkt4vczk~qc7.js\",\"/_next/static/chunks/0b_bz3qblxdp-.js\",\"/_next/static/chunks/06a45a7j5k-js.js\",\"/_next/static/chunks/08n_t7-3qaqxt.js\",\"/_next/static/chunks/14fu6zf9vwf4c.js\",\"/_next/static/chunks/0mtxwrtj1pimg.js\",\"/_next/static/chunks/09220hua3xdwb.js\",\"/_next/static/chunks/0wx.~0vo7c8j-.js\",\"/_next/static/chunks/0~p_uee4sxnt6.js\",\"/_next/static/chunks/06uysyk4dsnp..js\",\"/_next/static/chunks/0ieejselqt4sb.js\",\"/_next/static/chunks/0p-k.~tfn1t4o.js\",\"/_next/static/chunks/0uy~38govsi.j.js\",\"/_next/static/chunks/102.xx_c910ig.js\",\"/_next/static/chunks/0qia6hd26k~vx.js\",\"/_next/static/chunks/12coqwet6qxr0.js\",\"/_next/static/chunks/0.xr3l.uor6_o.js\",\"/_next/static/chunks/07xu0f7a_b-vv.js\",\"/_next/static/chunks/120.i~vx9g2x~.
81js\",\"/_next/static/chunks/0ghr.qsuu5a8s.js\",\"/_next/static/chunks/0ticqhfaxqa9m.js\",\"/_next/static/chunks/0sk9j1giok5~z.js\",\"/_next/static/chunks/06mb6yniv~mh_.js\",\"/_next/static/chunks/0wpt7ub5rom57.js\"],\"default\"]\n"])</script>
81<script>self.__next_f.push([1,"27:[\"$\",\"section\",null,{\"aria-labelledby\":\"methods-heading\",\"className\":\"mt-14\",\"children\":[[\"$\",\"h2\",null,{\"className\":\"text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl\",\"id\":\"methods-heading\",\"children\":\"Research methods, explained\"}],[\"$\",\"ul\",null,{\"className\":\"mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3\",\"children\":[[\"$\",\"li\",\"social-listening\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"h-24 w-full\",\"children\":[\"$\",\"div\",null,{\"aria-hidden\":true,\"aria-label\":\"$undefined\",\"className\":\"relative h-full w-full overflow-hidden\",\"role\":\"$undefined\",\"style\":{\"backgroundImage\":\"radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #1E3A8A 0%, #3B82F6 100%)\",\"backgroundSize\":\"18px 18px, 100% 100%\"},\"children\":[\"$\",\"svg\",null,{\"className\":\"absolute inset-0 h-full w-full\",\"preserveAspectRatio\":\"xMidYMid meet\",\"viewBox\":\"0 0 160 100\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"children\":[\"$\",\"g\",null,{\"children\":[[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.20)\",\"height\":\"52\",\"rx\":\"4\",\"transform\":\"rotate(-8 62 52)\",\"width\":\"40\",\"x\":\"42\",\"y\":\"26\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.42)\",\"height\":\"52\",\"rx\":\"4\",\"transform\":\"rotate(-3 74 50)\",\"width\":\"40\",\"x\":\"54\",\"y\":\"24\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.92)\",\"height\":\"54\",\"rx\":\"4\",\"width\":\"42\",\"x\":\"72\",\"y\":\"23\"}],[\"$\",\"g\",null,{\"fill\":\"#0F2F5C\",\"opacity\":\"0.35\",\"children\":[[\"$\",\"rect\",null,{\"height\":\"3\",\"rx\":\"1.5\",\"width\":\"26\",\"x\":\"80\",\"y\":\"33\"}],[\"$\",\"rect\",null,{\"height\":\"3\",\"rx\":\"1.5\",\"width\":\"20\",\"x\":\"80\",\"y\":\"42\"}],[\"$\",\"rect\",null,{\"height\":\"3\",\"rx\":\"1.5\",\"width\":\"24\",\"x\":\"80\",\"y\":\"51\"}],[\"$\",\"rect\",null,{\"height\":\"3\",\"rx\":\"1.5\",\"width\":\"14\",\"x\":\"80\",\"y\":\"60\"}]]}]]}]}]}]}],[\"$\",\"div\",null,{\"className\":\"flex flex-1 flex-col p-5\",\"children\":[[\"$\",\"span\",null,{\"className\":\"w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Social and Cultural Insights\"}],[\"$\",\"h3\",null,{\"className\":\"mt-3 text-base font-semibold leading-snug text-gray-900\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/blogs/social-listening\",\"children\":\"Social Listening: qualitative analysis of public digital talk\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600\",\"children\":\"Beyond dashboards: designing queries, cleaning and sampling social data, reading conversations in context, and the representativeness caveats that keep findings honest.\"}]]}]]}]}],[\"$\",\"li\",\"voice-of-customer-interviews\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"h-24 w-full\",\"children\":[\"$\",\"div\",null,{\"aria-hidden\":true,\"aria-label\":\"$undefined\",\"className\":\"relative h-full w-full overflow-hidden\",\"role\":\"$undefined\",\"style\":{\"backgroundImage\":\"radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%)\",\"backgroundSize\":\"18px 18px, 100% 100%\"},\"children\":[\"$\",\"svg\",null,{\"className\":\"absolute inset-0 h-full w-full\",\"preserveAspectRatio\":\"xMidYMid meet\",\"viewBox\":\"0 0 160 100\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"children\":[\"$\",\"g\",null,{\"children\":[[\"$\",\"path\",null,{\"d\":\"M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z\",\"fill\":\"rgba(255,255,255,0.92)\"}],[\"$\",\"g\",null,{\"fill\":\"#2A0F5E\",\"opacity\":\"0.45\",\"children\":[[\"$\",\"rect\",null,{\"height\"
81:\"4\",\"rx\":\"2\",\"width\":\"34\",\"x\":\"58\",\"y\":\"36\"}],[\"$\",\"rect\",null,{\"height\":\"4\",\"rx\":\"2\",\"width\":\"24\",\"x\":\"58\",\"y\":\"46\"}]]}],[\"$\",\"path\",null,{\"d\":\"M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z\",\"fill\":\"rgba(255,255,255,0.92)\"}]]}]}]}]}],[\"$\",\"div\",null,{\"className\":\"flex flex-1 flex-col p-5\",\"children\":[\"$L30\",\"$L31\",\"$L32\"]}]]}]}],\"$L33\",\"$L34\",\"$L35\",\"$L36\"]}],\"$L37\"]}]\n"])</script>
81<script>self.__next_f.push([1,"28:[\"$\",\"section\",null,{\"aria-labelledby\":\"trust-heading\",\"className\":\"mt-14\",\"children\":[[\"$\",\"h2\",null,{\"className\":\"text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl\",\"id\":\"trust-heading\",\"children\":\"Research, accuracy and responsible AI\"}],[\"$\",\"p\",null,{\"className\":\"mt-2 max-w-3xl text-base leading-relaxed text-gray-600\",\"children\":\"How Evidano's output has been evaluated, how its models were built, how your data is handled, and how to disclose or cite it in your own work.\"}],[\"$\",\"ul\",null,{\"className\":\"mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3\",\"children\":[[\"$\",\"li\",\"page:human-vs-ai\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-scale h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"7g6ntu\",{\"d\":\"m16 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z\"}],[\"$\",\"path\",\"ijws7r\",{\"d\":\"m2 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z\"}],[\"$\",\"path\",\"1b0cd5\",{\"d\":\"M7 21h10\"}],[\"$\",\"path\",\"108xh3\",{\"d\":\"M12 3v18\"}],[\"$\",\"path\",\"3gwbw2\",{\"d\":\"M3 7h2c2 0 5-1 7-2 2 1 5 2 7 2h2\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/human-vs-ai\",\"children\":\"Human vs AI: validated accuracy benchmarks\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Three head-to-head comparisons against expert human analysis â 371 interview transcripts with Arizona State and Penn State, 298 evaluation reports for a UN evaluation group, and UNICEFâs manual-coding review.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}],[\"$\",\"li\",\"page:how-we-trained-our-ai-models\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-cpu h-[18px] w-[18px]\",\"children\":[[\"$\",\"rect\",\"14l7u7\",{\"width\":\"16\",\"height\"
81:\"16\",\"x\":\"4\",\"y\":\"4\",\"rx\":\"2\"}],[\"$\",\"rect\",\"5aljv4\",{\"width\":\"6\",\"height\":\"6\",\"x\":\"9\",\"y\":\"9\",\"rx\":\"1\"}],[\"$\",\"path\",\"13l42r\",{\"d\":\"M15 2v2\"}],[\"$\",\"path\",\"15mkzm\",{\"d\":\"M15 20v2\"}],[\"$\",\"path\",\"1gxd5l\",{\"d\":\"M2 15h2\"}],[\"$\",\"path\",\"1bbxkp\",{\"d\":\"M2 9h2\"}],[\"$\",\"path\",\"19e6y8\",{\"d\":\"M20 15h2\"}],\"$L38\",\"$L39\",\"$L3a\",\"$undefined\"]}]}]]}],\"$L3b\",\"$L3c\",\"$undefined\",\"$L3d\"]}]}],\"$L3e\",\"$L3f\",\"$L40\"]}]]}]\n"])</script>
81<script>self.__next_f.push([1,"29:[\"$\",\"section\",null,{\"aria-labelledby\":\"comparisons-heading\",\"className\":\"mt-14\",\"children\":[[\"$\",\"h2\",null,{\"className\":\"text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl\",\"id\":\"comparisons-heading\",\"children\":\"Compare qualitative analysis software\"}],[\"$\",\"p\",null,{\"className\":\"mt-2 max-w-3xl text-base leading-relaxed text-gray-600\",\"children\":\"Evidence-based comparisons against NVivo, MAXQDA, ATLAS.ti, Delve and Dedoose, drawn from each vendor's own published terms and prices.\"}],[\"$\",\"ul\",null,{\"className\":\"mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 \",\"children\":[[\"$\",\"li\",\"page:alternatives\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-scale h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"7g6ntu\",{\"d\":\"m16 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z\"}],[\"$\",\"path\",\"ijws7r\",{\"d\":\"m2 16 3-8 3 8c-.87.65-1.92 1-3 1s-2.13-.35-3-1Z\"}],[\"$\",\"path\",\"1b0cd5\",{\"d\":\"M7 21h10\"}],[\"$\",\"path\",\"108xh3\",{\"d\":\"M12 3v18\"}],[\"$\",\"path\",\"3gwbw2\",{\"d\":\"M3 7h2c2 0 5-1 7-2 2 1 5 2 7 2h2\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/alternatives\",\"children\":\"The best qualitative data analysis tools, compared\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Evidano, NVivo, MAXQDA, ATLAS.ti, Delve, Dovetail, Dedoose and Taguette compared on published accuracy evidence, codebook support, quote traceability, languages and price â with per-tool alternative guides.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}],[\"$\",\"li\",\"page:pricing-comparison\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-calculator h-[18px] w-[18px]\",\"children\":[[\"$\",\"rect\",\"1nb95v\",{\"width\":\"16\",\"height\"
81:\"20\",\"x\":\"4\",\"y\":\"2\",\"rx\":\"2\"}],[\"$\",\"line\",\"x4nwl0\",{\"x1\":\"8\",\"x2\":\"16\",\"y1\":\"6\",\"y2\":\"6\"}],[\"$\",\"line\",\"wjye3r\",{\"x1\":\"16\",\"x2\":\"16\",\"y1\":\"14\",\"y2\":\"18\"}],[\"$\",\"path\",\"1m94wz\",{\"d\":\"M16 10h.01\"}],[\"$\",\"path\",\"1nrarc\",{\"d\":\"M12 10h.01\"}],[\"$\",\"path\",\"19clt8\",{\"d\":\"M8 10h.01\"}],[\"$\",\"path\",\"1etili\",{\"d\":\"M12 14h.01\"}],\"$L41\",\"$L42\",\"$L43\",\"$undefined\"]}]}]]}],\"$L44\",\"$L45\",\"$undefined\",\"$L46\"]}]}],\"$L47\"]}]]}]\n"])</script>
81<script>self.__next_f.push([1,"2a:[\"$\",\"section\",null,{\"aria-labelledby\":\"capabilities-heading\",\"className\":\"mt-14\",\"children\":[[\"$\",\"h2\",null,{\"className\":\"text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl\",\"id\":\"capabilities-heading\",\"children\":\"Capabilities by data type\"}],\"$undefined\",[\"$\",\"ul\",null,{\"className\":\"mt-6 grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3\",\"children\":[[\"$\",\"li\",\"page:thematic-analysis-software\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-sparkles h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"4pj2yx\",{\"d\":\"M9.937 15.5A2 2 0 0 0 8.5 14.063l-6.135-1.582a.5.5 0 0 1 0-.962L8.5 9.936A2 2 0 0 0 9.937 8.5l1.582-6.135a.5.5 0 0 1 .963 0L14.063 8.5A2 2 0 0 0 15.5 9.937l6.135 1.581a.5.5 0 0 1 0 .964L15.5 14.063a2 2 0 0 0-1.437 1.437l-1.582 6.135a.5.5 0 0 1-.963 0z\"}],[\"$\",\"path\",\"1olli1\",{\"d\":\"M20 3v4\"}],[\"$\",\"path\",\"1gvqau\",{\"d\":\"M22 5h-4\"}],[\"$\",\"path\",\"vumght\",{\"d\":\"M4 17v2\"}],[\"$\",\"path\",\"zchphs\",{\"d\":\"M5 18H3\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/thematic-analysis-software\",\"children\":\"Thematic analysis software\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"AI-native thematic analysis end to end: inductive or codebook-driven coding in 100+ languages, with every theme backed by clickable source quotes.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}],[\"$\",\"li\",\"page:ai-thematic-analysis\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-cpu h-[18px] w-[18px]\",\"children\":[[\"$\",\"rect\",\"14l7u7\",{\"width\":\"16\",\"height\"
81:\"16\",\"x\":\"4\",\"y\":\"4\",\"rx\":\"2\"}],[\"$\",\"rect\",\"5aljv4\",{\"width\":\"6\",\"height\":\"6\",\"x\":\"9\",\"y\":\"9\",\"rx\":\"1\"}],[\"$\",\"path\",\"13l42r\",{\"d\":\"M15 2v2\"}],[\"$\",\"path\",\"15mkzm\",{\"d\":\"M15 20v2\"}],[\"$\",\"path\",\"1gxd5l\",{\"d\":\"M2 15h2\"}],[\"$\",\"path\",\"1bbxkp\",{\"d\":\"M2 9h2\"}],[\"$\",\"path\",\"19e6y8\",{\"d\":\"M20 15h2\"}],[\"$\",\"path\",\"19tzq7\",{\"d\":\"M20 9h2\"}],[\"$\",\"path\",\"165o2o\",{\"d\":\"M9 2v2\"}],[\"$\",\"path\",\"i2bqo8\",{\"d\":\"M9 20v2\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":\"$L48\"}],\"$L49\",\"$undefined\",\"$L4a\"]}]}],\"$L4b\",\"$L4c\",\"$L4d\",\"$L4e\",\"$L4f\",\"$L50\",\"$L51\",\"$L52\",\"$L53\"]}]]}]\n"])</script>
81<script>self.__next_f.push([1,"2b:[\"$\",\"section\",null,{\"className\":\"mt-16 border-t border-gray-100 pt-10\",\"children\":[[\"$\",\"h2\",null,{\"className\":\"text-2xl font-bold tracking-tight text-gray-900 sm:text-3xl\",\"children\":\"Latest articles\"}],[\"$\",\"p\",null,{\"className\":\"mt-2 max-w-3xl text-base leading-relaxed text-gray-600\",\"children\":\"Commentary connecting newly published studies to reproducible analysis workflows.\"}]]}]\n2c:[\"$\",\"div\",null,{\"className\":\"mt-8\",\"children\":[\"$\",\"$L54\",null,{\"category\":\"\",\"query\":\"\",\"resultCount\":1053,\"subcategory\":\"\"}]}]\n2d:[\"$\",\"div\",null,{\"className\":\"mt-6 flex flex-col gap-3\",\"children\":[[\"$\",\"nav\",null,{\"aria-label\":\"Filter articles by category\",\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"mr-1 text-xs font-semibold uppercase tracking-wide text-gray-400\",\"children\":\"Topics\"}],[\"$\",\"$L24\",null,{\"className\":\"rounded-full border px-4 py-1.5 text-sm transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-[rgb(24,100,180)] bg-[rgb(24,100,180)] font-semibold text-white shadow-sm\",\"href\":\"/blogs\",\"children\":\"All\"}],[[\"$\",\"$L24\",\"Commentary on News\",{\"className\":\"rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-400 bg-white text-gray-800 shadow-sm hover:border-[rgb(31,119,206)] hover:bg-blue-50 hover:text-[rgb(31,119,206)]\",\"href\":\"/blogs?category=Commentary+on+News\",\"children\":\"Commentary on News\"}],[\"$\",\"$L24\",\"Research Methods\",{\"className\":\"rounded-full border px-4 py-1.5 text-sm font-medium transition-colors focus:outline-none focus:ring-4 focus:ring-blue-100 border-gray-400 bg-white text-gray-800 shadow-sm hover:border-[rgb(31,119,206)] hover:bg-blue-50 hover:text-[rgb(31,119,206)]\",\"href\":\"/blogs?category=Research+Methods\",\"children\":\"Research Methods\"}]]]}],false,false]}]\n2e:[\"$\",\"p\",null,{\"className\":\"mb-3 mt-6 text-sm text-gray-500\",\"children\":[\"Showing\",\" \",[\"$\",\"span\",null,{\"className\":\"font-semibold text-gray-700\",\"children\":10}],\" \",\"of\",\" \",[\"$\",\"span\",null,{\"className\":\"font-semibold text-gray-700\",\"children\":1053}],\" \",\"articles\"]}]\n56:T42a,The researcher-in-the-loop model makes governance the primary control for AI-enabled UX research, answering the question: who keeps democratized research honest? Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to [Uxdesign.cc](https://uxdesign.cc/researcher-in-the-loop-18a8ffddf48e), Jennifer L. Bowie, Ph.D. published her model on 25 August 2026 describing mandatory sourcing, confidence ratings, and escalation triggers as core governance mechanisms. The model responds to concrete failure modes: Bowie reports that in one study 75% of users could not complete a flagship AI feature, and Bowie cites a review of 182 peer-reviewed studies when arguing for more nuanced human-with-the-loop partnerships. This post refracts Bowieâs August 2026 article through the lens of AI-enabled qualitative research and explains how teams can operationalize governance, measure risk and confidence, and use tools like Evidano to automate safe, auditable self-service research."])</script>
81<script>self.__next_f.push([1,"2f:[\"$\",\"div\",null,{\"className\":\"mt-6\",\"children\":[[\"$\",\"$L55\",null,{\"posts\":[{\"slug\":\"climate-change-acceptance-definition-undergrads\",\"title\":\"Two Definitions: Climate Change Acceptance for Undergrads\",\"author\":\"Evidano\",\"content\":{\"title\":\"Two Definitions from a Delphi Study: Climate Change Acceptance for Undergraduate Science Students\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to the PLoS One study (published August 25, 2026), researchers used a Delphi method and four rounds of data collection to derive two defensible definitions of climate change acceptance for undergraduate science students ([PLoS One](https://journals.plos.org/plosone/article? id=10.1371%2Fjournal.pone.0356374)).\",{\"points\":[\"The Delphi team conducted a scoping review between October 2023 and February 2024 that screened 523 articles and extracted 3, 089 item-level measures, of which 2, 402 were unique (PLoS One, 2026).\",\"The Delphi recruitment ran from April 2024 through July 2025 and included iterative panels: 58 participants in Round 2 (December 2024), 26 respondents in Round 3 (February 2025), and 111 participants at a July 2025 conference (PLoS One, 2026).\",\"Across four rounds, experts split between two definitions: the Anthropogenic + Mechanistic Definition (e.g., âtemperatures and greenhouse gases are increasing and humans are causing itâ) and the simpler Anthropogenic Definition (e.g., âclimate change is happening and human behaviors are causing itâ), with each achieving majority support in different rounds (PLoS One, 2026).\",\"Practical implication: educators can choose the simpler definition for baseline acceptance measures or the mechanistic definition as a higher-level target for advanced students, per the Delphi authors (PLoS One, 2026).\"]}]},{\"type\":\"text\",\"title\":\"What Happened and How the Delphi Process Worked\",\"content\":[\"Answer: The PLoS One Delphi study synthesized 14 constructs from a prior scoping review, triangulated student pilot data, and then iteratively surveyed and interviewed educators to reach stable, consensus definitions (PLoS One, published August 25, 2026).\",\"According to the PLoS One paper, the team first performed a scoping review between October 2023 and February 2024 that identified 523 relevant articles and extracted 3, 089 items measuring aspects of climate change acceptance, which informed a preliminary codebook of 14 constructs (PLoS One, 2026).\",\"According to the PLoS One methods section, researchers then ran four rounds of educator interviews and surveys from April 2024 to July 2025, using frequency counts and thematic coding to move from 15 tentative definitions to two final, stable definitions (PLoS One, 2026).\",\"The PLoS One results show quantitative shifts: in Round 2 (December 2024) 50.9% (n = 29) chose the detailed definition, in Round 3 (February 2025) 69% (n = 18) favored the detailed version, and in Round 4 (July 2025) 64% (n = 70) selected the simpler anthropogenic definition, revealing a bipolarity of expert opinion (PLoS One, 2026).\",\"The authors report that this bipartite outcome led them to publish two complementary definitions appropriate for different educational contexts: the Anthropogenic Definition and the Anthropogenic + Mechanistic Definition (PLoS One, 2026).\"]},{\"rows\":[[\"Oct 2023âFeb 2024\",\"Scoping review: articles screened\",\"523 articles; 3, 089 item-level measures; 2, 402 unique items\",\"Provided the preliminary 14-construct framework used to draft candidate definitions (PLoS One, 2026).\"],[\"Dec 2024 (Round 2)\",\"Educator respondents\",\"58 participants; 50.9% (n = 29) chose detailed definition\",\"Early majority favored the mechanistic definition, prompting refinement (PLoS One, 2026).\"],[\"Feb 2025 (Round 3)\",\"Round 3 respondents\",\"26 agreed; 69% (n = 18) selected Anthropogenic + Mechanistic\",\"Mechanistic wording revised for clarity after qualitative feedback (PLoS One, 2026).\"],[\"July 2025 (Round 4)\",\"Final round respondents\",\"111 participants at a conference; 64% (n = 70) preferred the simpler Anthropogenic Definition\",\"Stability and bipolarity justified publishing two definitions for different educational levels (PLoS One, 2026).\"],[\"Aug 25, 2026\",\"Publication\",\"PLoS One open-access article\",\"Formal dissemination of two consensus definitions and guidance for educators and researchers (PLoS One, 2026).\"]],\"type\":\"table\",\"title\":\"Findings Snapshot\",\"headers\":[\"Date\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for Postsecondary Scie
81nce Educators and Researchers\",\"content\":[\"Answer: Educators should align the chosen definition of climate change acceptance with course goals and student level, using the simpler Anthropogenic Definition for baseline measurement and the Anthropogenic + Mechanistic Definition for advanced outcomes (PLoS One, 2026).\",\"The PLoS One authors explicitly recommend that instructors who expect students to master mechanistic knowledge (greenhouse gases and temperature trends) use the Anthropogenic + Mechanistic Definition as their working construct when selecting or designing instruments (PLoS One, 2026).\",\"The PLoS One study cautions that existing public-facing instruments developed before a consensus definition may measure different constructs and therefore are not directly comparable without revalidation (PLoS One, 2026).\",\"For researchers, the PLoS One team emphasizes content validity: the scoping review and Delphi coding produced a defensible content framework that should anchor future instrument development and cross-study synthesis (PLoS One, 2026).\",\"Ethics note: These definitions are research and curriculum tools, not clinical or diagnostic measures; researchers should follow institutional review and data-protection standards when collecting student responses (PLoS One, 2026).\"]},{\"type\":\"subsections\",\"title\":\"How Evidano Helps\",\"subsections\":[{\"title\":\"Evidano: platform definition\",\"content\":[\"Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"Problem: Large, unstandardized item pools (3, 089 items and 2, 402 unique items in the PLoS One scoping review) make instrument alignment and construct mapping time consuming (PLoS One, 2026).\",\"Solution: Evidano automates thematic extraction and content-frequency mapping so teams can map existing survey items to the new consensus constructs quickly.\",\"Learn more about core capabilities on the Evidano features page: [Evidano features](https://www.evidano.com/features).\"]},{\"title\":\"Problem: Mixed definitions across instruments â Feature: Thematic + cross-segment analysis\",\"content\":[\"Answer: When instruments disagree on what they measure, Evidanoâs thematic and cross-segment analyses reveal which items map to the Anthropogenic or Anthropogenic + Mechanistic constructs.\",\"Supporting detail: Researchers can upload instrument item banks and use automated code suggestion, then validate or adjust codes with human-in-the-loop review to produce reproducible mappings.\"]},{\"title\":\"Problem: Interview and open-text justification analysis â Feature: AI chat and transcript processing\",\"content\":[\"Answer: For qualitative rationale like the educator quotes in PLoS One, Evidano transcribes audio, redacts PII, and extracts representative quotes so you can quantify thematic support for each definition.\",\"Supporting detail: Use Evidanoâs transcription pipeline and AI chat over documents to surface quotes such as an educator saying, \\\"I chose this definition because it is the most comprehensive\\\" for transparent coding decisions (PLoS One, 2026).\",\"Explore speech tools: [Evidano speech-to-text](https://www.evidano.com/speech-to-text).\"]},{\"title\":\"Problem: Revalidating existing scales â Feature: Frequency, co-occurrence, and hierarchical coding\",\"content\":[\"Answer: Evidano computes frequency counts and co-occurrence networks that replicate the Delphiâs mixed-methods evidence approach, supporting content validity and instrument revision.\",\"Supporting detail: Teams can generate tables that mirror the PLoS One snapshot approach, test how items load on the two definitions, and prepare psychometric follow-ups.\"]}]},{\"type\":\"subsections\",\"title\":\"FAQ: climate change acceptance definition\",\"subsections\":[{\"title\":\"What are the two definitions of climate change acceptance the Delphi produced?\",\"content\":[\"Answer: The Delphi produced two definitions: the Anthropogenic Definition and the Anthropogenic + Mechanistic Definition (PLoS One, Aug 25, 2026).\",\"Supporting detail: The Anthropogenic Definition states that 'climate change is happening and human behaviors are causing it, ' while the Anthropogenic + Mechanistic Definition adds that 'average temperatures and greenhouse gases are increasing globally' to the definition, per the PLoS One article (2026).\"]},{\"title\":\"How should an educator choose which definition to use in a course?\",\"content\":[\"Answer: Choose the simpler Anthropogenic Definition for baseline or incoming-student assessments and the Anthropogenic + Mechanistic Definition for advanced students or courses that require mechanistic understanding (PLoS One, 2026).\",\"Supporting detail: The PLoS One Delphi team reports that some educators favored simplicity for clarity, while others favored inclusion of mechanisms for scientific precision, and both choices are defensible depending on learning goals (PLoS One, 2026).\"]},{\"title\":\"Can existing survey instruments be revalidated to these definitions?\",\"content\":[\"Answer: Yes, researchers should map existing items to the two consensus definitions and then revalidate instruments for content validity as recommended by the PLoS One authors (PLoS One, 2026).\",\"Supporting detail: The PLoS One paper warns that previously published instruments lack a unifying definition, so revalidation, including thematic mapping and psychometric testing, is necessary before cross-study synthesis (PLoS One, 2026).\"]},{\"title\":\"Can AI-enabled qualitative platforms like Evidano speed up applying these definitions?\",\"content\":[\"Answer: Yes, AI-enabled qualitative platforms accelerate mapping, quote extraction, and frequency analysis so researchers reach defensible construct alignments faster.\",\"Supporting detail: Evidano supports transcription, thematic extraction, cross-segment analysis, and AI chat over documents to operationalize the Delphi constructs and provide reproducible outputs for instrument development.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"Answer: The PLoS One Delphi study (published August 25, 2026) produces two operational definitions of climate change acceptance for undergraduate science students, choose the version that matches your educational or research target (PLoS One, 2026).\",\"Researchers should map and revalidate existing instruments against these definitions before pooling or comparing results, as the PLoS One authors recommend (PLoS One, 2026).\",\"If you need to operationalize either definition across interviews, open-text surveys, or item banks, AI-enabled qualitative analysis can cut weeks of coding work into days and produce transparent, citable outputs.\",\"Get started and map your data to the new consensus definitions today: [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"Primary keyword: climate change acceptance definition. According to the PLoS One study (published August 25, 2026), researchers used a mixed-methods Delphi process to produce two consensus definitions of climate change acceptance specifically for undergraduate science students. This post explains the PLoS One findings (scope, sample sizes, dates), translates them for classroom and research decisions, and shows how AI-enabled qualitative research tools accelerate applying those definitions to interviews, open-ended surveys, and existing instruments.\"},\"category\":\"Commentary on News\",\"keywords\":[\"climate change acceptance definition\",\"climate change acceptance undergraduate\",\"Delphi study climate acceptance\",\"qualitative analysis climate education\"],\"description\":\"How a PLoS One Delphi study (Aug 25, 2026) defined climate change acceptance for undergraduate science students, and how AI-enabled qualitative analysis applies it.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1198,\"publishedAt\":\"2026-08-27T02:32:23.121788Z\"},{\"slug\":\"researcher-in-the-loop-ai-ux-research-ce94f8ed\",\"title\":\"Researcher-in-the-loop: AI-enabled UX research\",\"author\":\"Evidano\",\"content\":{\"title\":\"Researcher-in-the-loop: practical governance for AI-enabled UX research\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"The researcher-in-the-loop model from [Uxdesign.cc](https://uxdesign.cc/researcher-in-the-loop-18a8ffddf48e) makes the researcher the governor of AI-driven research artifacts rather than the safety net that checks AI outputs after the fact.\",{\"points\":[\"Jennifer L. Bowie, Ph.D. published the researcher-in-the-loop model on 25 August 2026 and argues governance must be engineered into tools, not assumed as a manual step.\",\"Bowie reports that in one internal study 75% of users could not complete a flagship AI feature, a failure that a researcher caught in March 2026 before release.\",\"Bowie cites a review of 182 peer-reviewed studies (Konstantinos Lazaros et al.) when recommending a shift from \\\"human-in-the-loop\\\" to more flexible human-with-the-loop partnerships on 25 August 2026.\",\"The model prescribes three technical constraints: mandatory s
81ourcing for every insight, confidence ratings tied to evidence, and automatic escalation to researchers for high-risk or low-confidence answers.\"]}]},{\"type\":\"text\",\"title\":\"What happened and how the researcher-in-the-loop works\",\"content\":[\"Answer: Jennifer L. Bowie, Ph.D. described a governance-first model in an August 25, 2026 article on [Uxdesign.cc](https://uxdesign.cc/researcher-in-the-loop-18a8ffddf48e) that flips the usual human-in-the-loop assumption so researchers design, govern, and own escalation rules.\",\"Bowie explains the model by combining three prior ideas: research democratization (Nielsen Norman Group guidance), ResearchOps as infrastructure, and atomic research units that keep evidence traceable. Bowie frames two governed AI artifacts, the AI Librarian and AI Personas, as the safe, self-serve front door that must point back to human researchers when risk or uncertainty is high.\",\"Bowie supplies concrete governance mechanisms: mandatory sourcing for every answer, confidence and trust ratings connected to the underlying evidence, and escalation triggers that automatically route ambiguous or high-risk items to human researchers.\"]},{\"rows\":[[\"25 Aug 2026\",\"Publication\",\"[Uxdesign.cc](https://uxdesign.cc/researcher-in-the-loop-18a8ffddf48e)\",\"Primary source describing the researcher-in-the-loop governance model\"],[\"March 2026\",\"Feature failure rate found in internal study\",\"75% of users could not complete core task\",\"Example where a researcher prevented a harmful release in a high-trust domain\"],[\"2025\",\"Industry guidance cited\",\"Figma 2025 AI report quoted\",\"Supports the need for best practices and governance for AI in design and research\"],[\"2025-04\",\"Literature review referenced\",\"182 peer-reviewed studies (Konstantinos Lazaros et al.)\",\"Evidence base for shifting to nuanced human-with-the-loop partnerships\"]],\"type\":\"table\",\"title\":\"Findings snapshot\",\"headers\":[\"Date\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for UX researchers and research teams\",\"content\":[\"Answer: The researcher-in-the-loop model raises the strategic value of researchers from execution to governance, meaning researchers must set rules, audit artifacts, and run the high-stakes studies only humans can do.\",\"Researchers must design classification rules so the system cannot trust its own confidence scores, because Bowie warns that models and users both overstate certainty. Bowie writes, \\\"Ungoverned AI is dangerous. It is even more dangerous in high-trust domains, \\\" attributing the line to her experience in regulated B2B work.\",\"Teams should treat low-confidence answers as the research backlog, because Bowie argues that every escalated question that becomes a study increases the artifact's confidence ceiling and compounds research value over time.\",\"Product managers and designers should expect faster, directional answers from governed AI artifacts for low-risk questions while reserving researcher time for discovery, sensitive groups, and policy-level decisions.\"]},{\"type\":\"subsections\",\"title\":\"How Evidano helps implement researcher-in-the-loop governance\",\"subsections\":[{\"title\":\"Problem: Fragmented evidence and unverifiable insights â Solution: Atomic sourcing and traceability\",\"content\":[\"Answer: Evidano centralizes documents, transcripts, and surveys and produces evidence-traceable themes so every insight can link to the original source.\",\"Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. Use Evidano to build an auditable \\\"library\\\" the AI Librarian can query, and enforce mandatory sourcing on every automated insight via traceable code and evidence links.\",\"Relevant feature: thematic and content analysis with source linking, see [Evidano features](https://www.evidano.com/features).\"]},{\"title\":\"Problem: No confidence signal or opaque confidence â Solution: Evidence-based confidence scoring\",\"content\":[\"Answer: Evidano computes frequency and cross-segment signals from raw data so confidence can be tied to counts and recency rather than model tone.\",\"Evidano provides thematic frequency counts, cross-segment splits, and time-stamped source metadata so confidence ratings are grounded in the actual evidence Bowie prescribes, reducing the risk that a model \\\"sounds\\\" confident without the data to back it up.\"]},{\"title\":\"Problem: Manual escalation is inconsistent â Solution: Rule-based escalation and researcher alerts\",\"content\":[\"Answer: Evidano supports configurable escalation rules that notify researchers when queries fall into high-risk or low-evidence bands.\",\"Evidano supports AI chat over your documents and automated alerts to route low-confidence or sensitive-topic queries to a researcher for intervention, matching Bowieâs prescription that escalation be a reflex not a courtesy.\",\"Relevant integrations: transcription with PII redaction for regulated domains, see [speech-to-text](https://www.evidano.com/speech-to-text).\"]}]}
81,{\"type\":\"subsections\",\"title\":\"FAQ: researcher-in-the-loop\",\"subsections\":[{\"title\":\"What is the researcher-in-the-loop model and why does it matter?\",\"content\":[\"Answer: The researcher-in-the-loop model makes the researcher the designer and governor of AI research artifacts rather than a post-hoc safety net.\",\"Jennifer L. Bowie, Ph.D. defines the model on [Uxdesign.cc](https://uxdesign.cc/researcher-in-the-loop-18a8ffddf48e) on 25 August 2026 and frames governance as mandatory sourcing, confidence ratings, and automatic escalation to protect high-trust domains from ungoverned AI.\",\"This matters because Bowie documents a concrete failure where a researcher caught a 75% task-completion failure in March 2026 that would have harmed user trust if released.\"]},{\"title\":\"When should teams escalate a question to a human researcher?\",\"content\":[\"Answer: Escalate whenever the classification matrix shows high risk or low evidence, or when the outcome touches protected data, regulated decisions, or unclear ethical boundaries.\",\"Bowie recommends rightsizing oversight based on two axes: risk and confidence, so escalation should be automatic when the AI artifactâs evidence-based confidence falls below preconfigured thresholds tied to research rules set by a researcher.\",\"To implement this, Bowie suggests the system must compute confidence from the underlying research corpus, not from the modelâs self-reported certainty.\"]},{\"title\":\"Can AI replace researchers under this model?\",\"content\":[\"Answer: No, Bowie argues AI can replace specific low-risk research tasks but not the role of the researcher as governor and quality authority.\",\"Bowie writes that AI can \\\"replace some early research, not researchers, \\\" and emphasizes that researchers shift from moderating routine sessions to setting standards, auditing rigor, and conducting high-impact studies.\",\"This role elevation aligns researchers with ResearchOps practices and makes their work more strategic rather than purely operational.\"]},{\"title\":\"How do you prevent automation bias and false precision?\",\"content\":[\"Answer: Prevention requires engineering safeguards: confidence derived from evidence, mandatory sourcing, and external audit rather than relying on training alone.\",\"Bowie references research showing humans over-trust automated outputs and warns that confidence numbers can create a false objectivity; her remedy is traceable ratings and researcher-defined thresholds that move judgment upstream.\",\"Teams should schedule periodic exploratory studies forced by researchers to test areas where the system is most confident, because Bowie warns that the loop can confirm itself if left unchecked.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"The researcher-in-the-loop model from [Uxdesign.cc](https://uxdesign.cc/researcher-in-the-loop-18a8ffddf48e) reframes researchers as governors who design escalation rules, require mandatory sourcing, and tie confidence to evidence.\",\"Teams can operationalize Bowieâs model by building an auditable research library, computing evidence-based confidence, and automating escalation to researchers for high-risk questions.\",\"Evidano can help you implement these controls with source-linked thematic analysis, configurable escalation, and transcription with PII redaction. For a hands-on trial of governance-first qualitative workflows, [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"$56\"},\"category\":\"Commentary on News\",\"keywords\":[\"researcher-in-the-loop\",\"AI-enabled UX research\",\"governed research AI\",\"research governance AI\"],\"description\":\"How the researcher-in-the-loop model governs AI-enabled UX research. Learn practical governance, stats from the August 2026 piece, and how Evidano supports this workflow.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1197,\"publishedAt\":\"2026-08-27T02:31:27.618383Z\"},{\"slug\":\"researcher-in-the-loop\",\"title\":\"Researcher-in-the-Loop: Governance for AI UX Research\",\"author\":\"Evidano\",\"content\":{\"title\":\"Researcher-in-the-Loop: Applying Bowieâs Model to AI-Enabled Qualitative Research\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to Uxdesign.cc, in the article published on August 25, 2026, Jennifer L. Bowie argues that the appropriate response to AI-driven democratization of research is not prohibition but a governed model she calls âresearcher-in-the-loop.â\",{\"points\":[\"Jennifer L. Bowie reported on August 25, 2026 that an internal study she described showed a 75% failure rate for a flagship AI-assisted feature, and that researcher judgement stopped a harmful release.\",\"Konstantinos Lazaros et al., in an April 2025 review cited by Bowie, examined 182 peer-reviewed studies that motivate more nuanced human-with-the-loop partnerships.\",\"Bowieâs model centers three governance mechanisms: mandatory s
81ourcing, confidence ratings, and automatic escalation to researchers when risk or uncertainty is high.\",\"Bowie warns on August 25, 2026 that automation bias and false precision are persistent risks the governance layer must manage, not eliminate.\"]},\"âWhat if, instead of thinking of automation as the removal of human involvement from a task, we imagined it as the selective inclusion of human participation? â; Stanford University HAI, quoted in Uxdesign.cc.\"]},{\"type\":\"text\",\"title\":\"What Happened and How the Model Works\",\"content\":[\"Answer-first: Jennifer L. Bowie described the researcher-in-the-loop model on Uxdesign.cc (Aug 25, 2026) as a governance-first inversion of human-in-the-loop AI where researchers design, set rules, and receive escalations from AI artifacts.\",\"According to Uxdesign.cc (Aug 25, 2026), Bowie frames two primary AI artifacts: the AI Librarian, which pulls cited evidence across studies and flags âWe donât have enough research to answer that, â and AI Personas, which are living, sourced user representations that report confidence and cite their sources.\",\"According to Bowie on Uxdesign.cc (Aug 25, 2026), the model routes questions into a 2x2 matrix of risk and confidence so that low-risk, high-confidence queries are self-serve while high-risk, low-confidence queries automatically escalate to researchers.\",\"Bowie calls for three engineered constraints in the tools: mandatory sourcing for traceability, confidence/trust ratings attached to answers, and escalation triggers that route ambiguous or high-risk outputs to a human researcher.\"]},{\"rows\":[[\"April 2025\",\"Studies reviewed by Lazaros et al.\",\"182 peer-reviewed studies\",\"Supports more sophisticated human-with-the-loop partnership designs, cited by Bowie on Aug 25, 2026.\"],[\"August 25, 2026\",\"Featured failure rate in Bowie case study\",\"75% of users could not complete the featureâs core task\",\"Demonstrates how research oversight changed product direction in a high-trust B2B domain according to Uxdesign.cc.\"],[\"2000\",\"Jakob Nielsen's classic guidance\",\"Testing advice often summarised as '5 users'\",\"Context for rightsizing research effort cited by Bowie on Aug 25, 2026; helps decide when to escalate.\"]],\"type\":\"table\",\"title\":\"Findings Snapshot\",\"headers\":[\"Date\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for UX Research Teams and Product Leaders\",\"content\":[\"Answer-first: Research teams must move from being a bottleneck to being governors, according to Jennifer L. Bowie on Uxdesign.cc (Aug 25, 2026).\",\"According to Uxdesign.cc (Aug 25, 2026), research leaders should codify risk thresholds and confidence rules upstream so that non-researchers cannot under-rate risk to get fast answers.\",\"According to Bowie on Uxdesign.cc (Aug 25, 2026), organizations should treat the AI Librarian as a prioritized backlog generator: the systemâs low-confidence cells become the human research queue, so product and research budgets compound in value rather than depreciate.\"]},{\"type\":\"subsections\",\"title\":\"How Evidano Helps\",\"subsections\":[{\"title\":\"Problem: Scattered evidence and unverifiable answers\",\"content\":[\"Solution: Evidano ingests transcripts, reports, and open-ended survey responses and produces thematic, content, and cross-segment analyses that are traceable to sources, addressing Bowieâs mandatory-sourcing requirement.\",\"According to Bowie on Uxdesign.cc (Aug 25, 2026), mandatory sourcing is non-negotiable; using [Evidano features](https://www.evidano.com/features) teams can build source-linked summaries that the AI Librarian pattern requires.\"]},{\"title\":\"Problem: Overtrust and automation bias\",\"content\":[\"Solution: Evidanoâs AI chat over documents and confidence-calibrated outputs let teams display supporting quotes and origin transcripts alongside summaries, matching Bowieâs confidence-and-escalation design.\",\"According to Jennifer L. Bowie on Uxdesign.cc (Aug 25, 2026), automatic escalation is essential; Evidano supports routing low-confidence findings into researcher review workflows so humans govern edge cases.\"]},{\"title\":\"Problem: Operationalizing atomic research\",\"content\":[\"Solution: Evidanoâs structured tagging and visualization tools (word clouds, co-occurrence networks, hierarchical codes) support the atomic research workflow Bowie cites, making evidence units findable and reusable.\",\"Evidano also offers transcription with custom dictionaries and PII redaction, which helps regulated teams capture source material ethically and in compliance with governance needs cited by Bowie on Aug 25, 2026.\"]}]}
81,{\"type\":\"subsections\",\"title\":\"FAQ: researcher-in-the-loop\",\"subsections\":[{\"title\":\"What exactly is researcher-in-the-loop?\",\"content\":[\"Answer: Researcher-in-the-loop is a governance model where researchers design rules, escalate high-risk outputs, and conduct the high-stakes studies that AI artifacts cannot safely answer, as described by Jennifer L. Bowie in Uxdesign.cc (Aug 25, 2026).\",\"Bowie frames researcher-in-the-loop as an inversion of human-in-the-loop: the researcher is the governor and the AI is a governed servant for routine queries.\"]},{\"title\":\"When should a question escalate to a human researcher?\",\"content\":[\"Answer: Escalation is required when the question sits in the high-risk, low-confidence cell of a risk-by-confidence matrix, a rule recommended by Bowie on Uxdesign.cc (Aug 25, 2026).\",\"Bowie warns that high-trust domains (for example, healthcare, legal, or finance) are likely to produce more high-risk flags and therefore more automatic escalations.\"]},{\"title\":\"How do you reduce automation bias in self-serve AI research?\",\"content\":[\"Answer: You reduce automation bias by engineering confidence signals, mandatory sourcing, and automatic escalation into the tools, according to Bowie on Uxdesign.cc (Aug 25, 2026).\",\"Bowie cites research (Parasuraman and Manzey, and Mosier et al.) showing humans over-trust automation, so a governance layer must make trust and uncertainty explicit rather than optional.\"]},{\"title\":\"Will AI replace user researchers?\",\"content\":[\"Answer: No; AI can replace specific low-risk research tasks but, according to Bowie on Uxdesign.cc (Aug 25, 2026), researchers gain value as governors who design rules, audit confidence, and run high-stakes studies.\",\"Bowieâs case study where a researcher blocked a feature with a 75% failure signal illustrates that human judgement remains essential in high-trust product contexts.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"Summary-first: Jennifer L. Bowieâs researcher-in-the-loop model (Uxdesign.cc, Aug 25, 2026) is a practical governance stance: build mandatory sourcing, confidence ratings, and automatic escalation into AI research tools rather than rely on ad hoc human checks.\",\"For teams building governed AI artifacts, Bowieâs model turns low-confidence AI outputs into a prioritized research backlog and protects high-stakes decisions with human oversight.\",\"If you want to pilot a governed front door for qualitative research, start by collecting atomic, source-linked evidence and wiring confidence-and-escalation rules into your workflow.\",\"To map those rules to tools and try a source-traced, confidence-aware research workflow, [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"The researcher-in-the-loop model reframes governance: Jennifer L. Bowie argues in Uxdesign.cc (published August 25, 2026) that researchers must design and govern AI artifacts rather than act as late-stage safety nets. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. This post translates Bowieâs August 25, 2026 proposal into practical, AI-enabled qualitative research steps for research leaders and product teams, with concrete tools and a mapped workflow you can start using today.\"},\"category\":\"Commentary on News\",\"keywords\":[\"researcher-in-the-loop\",\"AI-enabled qualitative research\",\"AI governance for UX research\"],\"description\":\"Govern AI in qualitative UX research with the researcher-in-the-loop model from Jennifer L. Bowie (Aug 25, 2026): practical rules, risks, and tool mappings.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1196,\"publishedAt\":\"2026-08-27T02:30:35.794981Z\"},{\"slug\":\"qualitative-analysis-of-larc-uptake-bangladesh\",\"title\":\"Why LARC/PM Uptake Is Low: Qualitative Analysis in Bangladesh\",\"author\":\"Evidano\",\"content\":{\"title\":\"AI-enabled qualitative analysis of LARC/PM uptake in rural Bangladesh\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to the [PLOS One](https://journals.plos.org/plosone/article? id=10.1371%2Fjournal.pone.0356493) study published on August 25, 2026, multilevel barr
81iers, knowledge gaps, embodied side-effect experiences, gendered decision-making, stigma, religious beliefs, provider bias, and health-system shortages, explain persistently low LARC/PM uptake in rural Cumilla, Bangladesh.\",{\"points\":[\"The PLOS One study collected 28 in-depth interviews with married women and men and 9 key informant interviews between January 21 and February 20, 2023.\",\"According to the PLOS One authors, Cumilla reported 13.6% LARC/PM use in 2022 while Chattogram Division showed 6.1% LARC/PM uptake as of 2022, and national LARC/PM share declined to 8% in 2022 from 12.1% in 1991.\",\"The PLOS One study documented widespread method misperceptions and tangible embodied fears, illustrated by quotes such as, \\\"Look, sister, we are uneducated people. We donât know or understand these methods\\\" (participant W 02, PLOS One).\",\"The PLOS One findings highlight institutional harms including brief counselling, privacy deficits, coercive practices, and workforce shortages that undermine informed choice.\"]}]},{\"type\":\"text\",\"title\":\"What Happened and how the study was done\",\"content\":[\"The PLOS One study conducted a one-time qualitative inquiry in Cumilla to identify why LARC/PM uptake is low and how barriers interact across levels.\",\"According to the PLOS One article (Shoma and Barden-OâFallon, published August 25, 2026), researchers purposively sampled two Upazilas and used 28 in-depth interviews (22 women, 6 men) plus 9 key informant interviews with providers and one religious leader to reach thematic saturation between January 21 and February 20, 2023.\",\"The PLOS One team analyzed Bengali transcripts using Braun and Clarkeâs thematic analysis framed by the socio-ecological model, coding iteratively with a hybrid inductive-deductive approach and cross-checking English translations for fidelity.\"]},{\"rows\":[[\"Data collection (PLOS One)\",\"Interviews completed\",\"28 IDIs (22 women, 6 men) and 9 KIIs\",\"Sufficient depth to map individual to health-system barriers\"],[\"Published (PLOS One)\",\"Publication date\",\"25 August 2026\",\"Recent qualitative evidence for program design\"],[\"DGFP / PLOS One citation\",\"Local LARC/PM coverage (2022)\",\"Cumilla 13.6%; Chattogram Division 6.1%; National LARC/PM share 8% in 2022\",\"Confirms program-level low uptake and geographic disparity\"],[\"Sample demographics (PLOS One)\",\"Women with 3â5 children\",\"17 of 28 participants reported 3â5 children\",\"High parity common; male child preference and parity norms relevant\"],[\"Service delivery (PLOS One)\",\"Reported provider practices\",\"Brief counselling (often \u003c5 minutes), irregular field visits, workforce shortages\",\"Quality-of-care gaps and rights violations require system fixes\"]],\"type\":\"table\",\"title\":\"Findings snapshot\",\"headers\":[\"Date / Source\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for qualitative researchers and program teams\",\"content\":[\"The PLOS One study implies that qualitative researchers must design interviews and coding schemes to capture embodied experiences, rumor networks, and institutional abuses rather than only knowledge scores.\",\"According to the PLOS One findings, researchers should sample beyond women to include husbands, mothers-in-law, religious leaders, and frontline providers to trace how social norms and provider behavior propagate misperceptions.\",\"According to the PLOS One authors, methodologists should treat LARC and PM as analytically distinct where reversibility, consent, and stigma differ, and code for both anticipated and vicarious side-effect narratives.\",\"According to the PLOS One study, research ethics in family planning require careful consent, privacy, and post-interview referral protocols because interviewees reported coercive or non-consensual service experiences.\"]},{\"type\":\"subsections\",\"title\":\"How Evidano helps: mapping the study's analytic needs to AI-enabled features\",\"subsections\":[{\"title\":\"Problem: Long, untranslated transcripts and multilingual coding\",\"content\":[\"Evidano is an AI-powered qualitative data analysis platform that helps researchers anal
81yze interviews, open-ended surveys, and documents.\",\"Solution: Evidano offers secure transcription with custom dictionaries and translation support to convert Bengali audio into searchable English and Bengali transcripts, which matches the PLOS One workflow that required careful translation and cross-checking.\"]},{\"title\":\"Problem: Capturing embodied side-effect narratives and rumor co-occurrence\",\"content\":[\"Solution: Evidanoâs thematic and co-occurrence network visualizations let teams tag 'embodied experience', 'rumor', and 'provider dismissal' codes and then surface which narratives cluster with gender, age, or migration status.\",\"According to the PLOS One themes, tagging narratives like \\\"excessive bleeding\\\" or \\\"device migration\\\" enables rapid extraction of high-impact quotes and frequency counts for program briefs.\"]},{\"title\":\"Problem: Rapid synthesis for rights-based program design\",\"content\":[\"Solution: Evidano supports thematic summaries, cross-segment comparisons (for example women vs. men, or households with migrants vs. non-migrants), and exportable analytic tables that map barriers to levels of the socio-ecological model.\",\"You can learn more about these capabilities on the Evidano [features page](https://www.evidano.com/features).\"]},{\"title\":\"Problem: Protecting participant privacy and reproducibility\",\"content\":[\"Solution: Evidano provides PII redaction, encrypted storage, and an auditable coding history that supports ethical reporting and reproducibility when analyzing sensitive family planning interviews as documented in the PLOS One study.\",\"Solution: Evidanoâs AI chat over your documents helps non-technical stakeholders query evidence (quotes, counts, coded segments) while preserving source traceability.\"]}]},{\"type\":\"subsections\",\"title\":\"FAQ: qualitative analysis of LARC uptake\",\"subsections\":[{\"title\":\"How can AI help analyze qualitative interviews about contraceptive uptake?\",\"content\":[\"Answer: AI accelerates coding, summarization, and cross-segment comparison while preserving researcher oversight.\",\"Supporting detail: According to the PLOS One study, interviews include embodied and rumor-based narratives that benefit from human-in-the-loop AI workflows which surface candidate themes and extract verbatim quotes for researcher validation.\"]},{\"title\":\"What sample and data details did the PLOS One study use that I should emulate?\",\"content\":[\"Answer: The PLOS One study used 28 IDIs and 9 KIIs collected between January 21 and February 20, 2023, with purposive sampling across two Upazilas.\",\"Supporting detail: According to PLOS One, include variation in parity, migration status, and provider type to enable cross-segment analysis of norms, service barriers, and rights violations.\"]},{\"title\":\"How do I code for 'embodied' versus 'misinformation' narratives ethically?\",\"content\":[\"Answer: Code embodied experiences (reported bleeding, pain, weakness) as distinct from circulating misinformation (device migration, organ removal) and preserve contextual notes on source credibility.\",\"Supporting detail: According to the PLOS One findings, participants often anchored beliefs in personal or vicarious bodily experience, so coding must preserve whether a claim was lived experience, vicarious report, or rumor to avoid dismissing legitimate concerns.\"]},{\"title\":\"How should researchers respond when interviews reveal coercive provider practices?\",\"content\":[\"Answer: Prioritize participant safety, document the account with verbatim quotes and timestamps, and follow pre-specified referral and reporting protocols.\",\"Supporting detail: The PLOS One article reported instances of non-consensual insertions and refusals to remove methods, so ethical protocols and institutional review plans must include pathways for participant support and anonymized reporting.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"The PLOS One study (published August 25, 2026) shows that low LARC/PM uptake in rural Bangladesh is produced by entwined sociocultural, institutional, and system-level factors, not by knowledge gaps alone.\",\"For qualitative teams, the analytic priority is to preserve context: tag embodied effects, map rumor networks, and cross-segment responses by gender and migration status.\",\"Evidano helps teams operationalize these priorities with secure transcription, translation, thematic and cross-segment analytics, and auditable coding exports for program design and rights-based advocacy.\",\"To try an AI-enabled qualitative workflow on your data, [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"This post explains how to do a rigorous qualitative analysis of LARC uptake using the PLOS One study as a worked example, aimed at qualitative researchers and program teams. The primary keyword \\\"qualitative analysis of LARC uptake\\\" guides the methods and recommendations below. According to the PLOS One study published on August 25, 2026, researchers used 28 in-depth interviews and 9 key informant interviews in Cumilla district to map multilevel barr
81iers to long-acting reversible and permanent contraceptive methods (LARC/PM). The payoff is practical: how to structure transcripts, code for embodied concerns and provider bias, and use AI-enabled tools to accelerate thematic synthesis while protecting participant rights.\"},\"category\":\"Commentary on News\",\"keywords\":[\"qualitative analysis of LARC uptake\",\"LARC uptake Bangladesh qualitative\",\"AI-enabled qualitative research\",\"long-acting contraception qualitative\"],\"description\":\"Actionable guidance for researchers: qualitative analysis of LARC uptake in rural Bangladesh using AI-enabled workflows to code interviews, surface themes, and inform rights-based programs.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1195,\"publishedAt\":\"2026-08-27T02:30:14.783359Z\"},{\"slug\":\"qualitative-analysis-larc-uptake-bangladesh-d333f5d9-3\",\"title\":\"AI for Qualitative Analysis: LARC Uptake in Bangladesh\",\"author\":\"Evidano\",\"content\":{\"title\":\"AI-enabled qualitative analysis of LARC/PM uptake in rural Bangladesh\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to the PLOS One study (Shoma \u0026 Barden-OâFallon, 25 August 2026), low LARC/PM uptake in rural Cumilla is driven by interacting individual fears and community- and system-level constraints, not by lack of efficacy of the methods themselves. The PLOS One study combined 28 in-depth interviews and 9 key informant interviews to map multilevel barriers. PLOS One documents concrete statistics and lived quotations that are extractable for program design.\",{\"points\":[\"28 in-depth interviews (22 women, 6 men) and 9 key informant interviews were conducted between 21 January and 20 February 2023, according to PLOS One (published 25 August 2026).\",\"PLOS One reports that Cumilla had 13.6% LARC/PM use based on 2022 Directorate General of Family Planning data, and that national LARC/PM share declined from 12.1% in 1991 to 8% in 2022.\",\"PLOS One quotes participants directly, for example: \\\"Look, sister, we are uneducated people. We donât know or understand these methods\\\" (W 02), and a provider: \\\"Most women who come for IUD removal complain of bleeding problems\\\" (P 04).\",\"PLOS One identifies five socio-ecological levels (individual, interpersonal, community, institutional, health-system) that together explain low uptake and point to multi-pronged interventions.\"]}]},{\"type\":\"text\",\"title\":\"What Happened: Methods and core findings from the PLOS One study\",\"content\":[\"Answer: The PLOS One study used purposive qualitative sampling and thematic analysis to identify multilevel barriers to
81LARC/PM uptake in Cumilla, Bangladesh.\",\"According to the PLOS One article (Shoma \u0026 Barden-OâFallon, 25 August 2026), researchers conducted 28 in-depth interviews with married people and 9 key informant interviews with service providers and one religious leader during 21 Januaryâ20 February 2023 to reach thematic saturation.\",\"According to PLOS One, the study applied Braun and Clarkeâs thematic analysis and a socio-ecological model to code transcripts that were transcribed in Bengali and translated to English to preserve quotations and context.\",\"According to PLOS One, core findings included: (1) individual-level knowledge gaps and embodied side-effect experiences, (2) interpersonal male-dominated decision-making and mother-in-law gatekeeping, (3) community-level stigma, son preference, migration effects and religious objections, (4) institutional problems such as brief counselling, provider bias and privacy deficits, and (5) health-system shortages and low provider incentives.\"]},{\"rows\":[[\"1991 â 2022\",\"Share of LARC/PM nationally\",\"Declined from 12.1% (1991) to 8% (2022)\",\"Program reversal suggests supply and demand shifts; requires system-level review (PLOS One, 25 Aug 2026).\"],[\"2022\",\"Cumilla LARC/PM use\",\"13.6% (DGFP data cited in PLOS One)\",\"Study site selected for persistently low uptake within Chattogram Division (PLOS One, 25 Aug 2026).\"],[\"21 Janâ20 Feb 2023\",\"Qualitative sample\",\"28 IDIs (22 women, 6 men) + 9 KIIs\",\"Sufficient to reach saturation for women and providers according to the authors (PLOS One, 25 Aug 2026).\"],[\"2022\",\"Contraceptive prevalence\",\"National coverage rose from 7.7% (1975) to 64% (2022) (cited in PLOS One)\",\"High overall coverage masks method-mix gaps favoring short-acting methods (PLOS One, 25 Aug 2026).\"]],\"type\":\"table\",\"title\":\"Findings Snapshot\",\"headers\":[\"Date / Period\",\"Metric\",\"Value (from PLOS One)\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for researchers and program teams\",\"content\":[\"Answer: Researchers should design mixed-methods studies that link thematic drivers to measurable outcomes and programs should combine rights-based counselling with community engagement.\",\"According to PLOS One, individual-level fears such as beliefs that implants \\\"move around the body\\\" or that ligation \\\"causes infertility\\\" are prevalent and are grounded in vicarious embodied experiences rather than abstract misinformation, so qualitative nuance matters for messaging.\",\"According to PLOS One, interpersonal influences (15 of 22 women reported husbands had final say) and community-level norms (son preference, religious objections, stigma) indicate that single-focus demand-generation campaigns will be inadequate without male engagement and faith-leader involvement.\",\"According to PLOS One, institutional failures (brief counselling sessions under 5 minutes, privacy deficits, and provider coercion) require system-level remedies that include provider training, supervision, and grievance mechanisms tied to service delivery targets.\"]},{\"type\":\"subsections\",\"title\":\"How Evidano Helps: AI tools mapped to PLOS One problems\",\"subsections\":[{\"title\":\"Problem: Rich qualitative transcripts but slow synthesis\",\"content\":[\"Solution: Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"Evidano feature mapping: import the 28 IDI and 9 KII transcripts, run automated thematic coding, surface frequency counts for fears (e.g., infertility, device migration), and export quota-based codebooks for program briefs.\",\"Why it matters: According to PLOS One, fear-driven themes are anchored in specific quotations and frequencies; Evidano preserves quotations and links them to codes so teams can quote sources like PLOS One accurately in proposals.\"]},{\"title\":\"Problem: Need to compare subgroups (women vs men vs providers)\",\"content\":[\"Solution: Evidano offers cross-segment analysis and co-occurrence networks to show which fears cluster with which demographics.\",\"Evidano feature mapping: run co-occurrence of codes (e.g., \\\"fear of infertility\\\" co-occurring with \\\"mother-in-law influence\\\") to prioritize interventions by audience.\",\"Why it matters: PLOS One documents divergent knowledge levels (implant known by 20/22 women, IUD by 9/22); Evidano makes such counts reproducible and transparent for funders and implementers.\"]},{\"title\":\"Problem: Rights violations and consent issues need documentation\",\"content\":[\"Solution: Evidano supports secure storage, PII redaction, and tagged excerpts for ethical audit trails.\",\"Evidano feature mapping: tag statements of non-consensual insertion or refusal to remove methods and generate an extractable report for policy teams while preserving participant anonymity.\",\"Why it matters: PLOS One reports cases of coerced insertion and refusal to remove implants; Evidano helps programs document and act on these incidents without compromising confidentiality.\"]},{\"title\":\"Problem: Rapid knowledge translation for local stakeholders\",\"content\":[\"Solution: Evidano auto-generates summaries, visualizations (word clouds, hierarchical code trees), and downloadable excerpts for community meetings.\",\"Evidano feature mapping: create one-page evidence briefs that include verbatim quotes (attributed, anonymized) such as \\\"Most women who come for IUD removal complain of bleeding problems\\\" (P 04) to anchor discussions with religious leaders and field staff.\",\"Why it matters: PLOS One emphasizes the need to engage faith leaders and husbands; succinct, evidence-based briefs reduce misinterpretation and enable targeted dialogue.\"]},{\"title\":\"Further resources\",\"content\":[\"Learn more about how these capabilities work in practice on the Evidano [features page](https://www.evidano.com/features).\",\"For secure transcription and PII redaction concerns raised by fieldwork, see Evidanoâs [speech-to-text](https://www.evidano.com/speech-to-text) and [data security](https://www.evidano.com/data-security) pages.\"]}]}
81,{\"type\":\"subsections\",\"title\":\"FAQ: qualitative analysis of LARC uptake\",\"subsections\":[{\"title\":\"How many interviews did the PLOS One study use and when were they conducted?\",\"content\":[\"Answer: The PLOS One study conducted 28 in-depth interviews and 9 key informant interviews between 21 January and 20 February 2023, as reported in PLOS One (25 August 2026).\",\"Supporting detail: The 28 in-depth interview sample included 22 married women and 6 married men, and the KIIs included family planning providers and one Imam, which the authors say reached thematic saturation for women and providers.\"]},{\"title\":\"What are the top three qualitative themes that programs should prioritize?\",\"content\":[\"Answer: According to PLOS One, prioritize (1) addressing embodied fear and side-effect management, (2) engaging male decision-makers and mothers-in-law, and (3) fixing institutional counselling and consent practices.\",\"Supporting detail: PLOS One reports method-specific fears (e.g., implant bleeding, IUD discharge), male-dominated decision-making (15 of 22 women noted husbands decide), and provider issues such as brief counselling under 5 minutes.\"]},{\"title\":\"Can AI help convert qualitative quotes into program metrics?\",\"content\":[\"Answer: Yes, AI-enabled qualitative research platforms can convert coded quotations into frequency metrics and segment comparisons while preserving context.\",\"Supporting detail: The PLOS One study demonstrates the value of counting method familiarity (implant known by 20 of 22 women); Evidano and similar tools generate these counts automatically and link them back to verbatim quotes for transparency.\"]},{\"title\":\"Is the PLOS One study nationally representative?\",\"content\":[\"Answer: No, the PLOS One study is a purposive qualitative study focused on Cumilla and is not nationally representative.\",\"Supporting detail: The authors explicitly note that findings are context-specific to Cumilla district and that transferability should be considered in similar rural contexts; quantitative DHS data are needed to generalize.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"Answer: Multilevel barriers documented in the PLOS One study require combined qualitative insight and scalable analysis to guide rights-based program change.\",\"According to the PLOS One article (Shoma \u0026 Barden-OâFallon, PLOS One, 25 August 2026), interventions should couple couple-centered engagement, faith-leader dialogue, targeted counselling that addresses embodied side effects, and accountability mechanisms for providers.\",\"Next steps for research teams: replicate the studyâs coding framework on larger samples, use cross-segment frequency analysis to prioritize interventions, and document rights-violations for remedial action.\",\"If you want to convert interview transcripts and field notes into actionable priorities as the PLOS One authors recommend, [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"Primary keyword: qualitative analysis of LARC uptake. Researchers and program teams seeking to understand why long-acting reversible and permanent contraceptive methods (LARC/PM) remain underused in rural Bangladesh need contextual, multilevel evidence and scalable ways to synthesize it. According to the PLOS One article by Shoma and Barden-OâFallon (published 25 August 2026), qualitative interviews in Cumilla district revealed knowledge gaps, fear-driven embodied experiences, patriarchal gatekeeping, religious stigma, and health-system failures as core drivers. This post refracts those PLOS One findings through an AI-enabled qualitative research lens and shows how thematic, cross-segment, and frequency analyses can turn 28 in-depth interviews and 9 key informant narratives into program-ready insights.\"},\"category\":\"Commentary on News\",\"keywords\":[\"qualitative analysis of LARC uptake\",\"LARC PM uptake Bangladesh\",\"AI-enabled qualitative research\",\"thematic analysis family planning\"],\"description\":\"How AI-enabled qualitative analysis reveals multilevel barr
81iers to LARC/PM uptake in rural Bangladesh, with practical steps for researchers and program teams. Read actionable methods.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1194,\"publishedAt\":\"2026-08-27T02:29:22.936258Z\"},{\"slug\":\"climate-change-acceptance-definition-delphi\",\"title\":\"Consensus definitions: climate change acceptance definition\",\"author\":\"Evidano\",\"content\":{\"title\":\"Consensus definitions from a Delphi study: climate change acceptance definition\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to Duke and Holt in [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374) (published August 25, 2026), a mixed-methods Delphi process produced two valid, context-sensitive definitions of climate change acceptance for undergraduate science students.\",{\"points\":[\"In a scoping review conducted between October 2023 and February 2024, Duke and Holt identified 523 relevant articles and extracted 3, 089 measurement items, 2, 402 of which were unique.\",\"Duke and Holt recruited educators and stakeholders across four Delphi rounds between May 2024 and July 2025, with Round 2 totaling 58 participants, Round 3 totaling 26 participants, and Round 4 totaling 111 participants; final consensus favored two definitions rather than a single definition.\",\"By August 25, 2026, Duke and Holt reported two definitions: the concise âAnthropogenic Definitionâ and the more detailed âAnthropogenic + Mechanistic Definitionâ, reflecting a bipolarity of expert opinion that may depend on educational context.\"]}]},{\"type\":\"text\",\"title\":\"What happened and how the Delphi process worked\",\"content\":[\"What happened: Duke and Holt used a mixed-methods Delphi design to derive definitions tailored to undergraduate science students, combining a scoping review, a pilot student survey, and four rounds of educator interviews and surveys.\",\"How it worked: According to Duke and Holt in [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374), the team performed a scoping review (Oct 2023âFeb 2024) to generate 14 preliminary constructs, piloted questions with 15 students in April 2024, and ran iterative Delphi rounds from May 2024 to July 2025 with educators in biology, chemistry, and earth and atmospheric science.\",\"How consensus was measured: Duke and Holt reported percent agreement and thematic stability across rounds, citing von der Gracht (recommended practice) and using frequency counts plus qualitative coding to assess stability of responses.\",\"Constraints: Duke and Holt noted demographic homogeneity among expert participants and that the corpus was U.S.-centered, which limits immediate generalizability beyond U.S. undergraduate science populations.\"]},{\"rows\":[[\"Oct 2023âFeb 2024\",\"Articles screened in scoping review\",\"523 articles\",\"Provided item pool and 14 preliminary constructs used to draft candidate definitions\"],[\"Scoping review result\",\"Extracted measurement items\",\"3, 089 items (2, 402 unique)\",\"Demonstrates high instrument heterogeneity in existing literature\"],[\"Apr 2024\",\"Pilot student participants\",\"15 undergraduate students\",\"Tested interview protocol readability and triangulated student perspectives\"],[\"May 2024âJuly 2025\",\"Delphi participants across rounds\",\"Round 2: 58; Round 3: 26; Round 4: 111\",\"Achieved stability and convergence that supported two working definitions\"],[\"Round 2 (Dec 2024)\",\"Top choice (Anthropogenic + Mechanistic)\",\"50.9% (n = 29)\",\"Majority initially preferred the detailed definition\"],[\"Round 3 (Feb 2025)\",\"Top choice shift (Anthropogenic + Mechanistic)\",\"69% (n = 18)\",\"Higher preference for including mechanism (temperature \u0026 greenhouse gases)\"],[\"Round 4 (July 2025 conference)\",\"Final preference (Anthropogenic)\",\"64% (n = 70)\",\"Final sample favored the simpler Anthropogenic definition; outcome: two valid definitions\"]],\"type\":\"table\",\"title\":\"Findings snapshot\",\"headers\":[\"Date / Range\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for undergraduate educators and researchers\",\"content\":[\"What this means for instructors: Duke and Holt in [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374) (Aug 25, 2026) show that choice of definition should map to course goals and student level: use the concise Anthropogenic Definition for baseline acceptance checks and the Anthropogenic + Mechanistic Definition for advanced courses where mechanistic knowledge is expected.\",\"What this means for researchers: Duke and Holt recommend that measurement instruments be aligned to an explicit definition; researchers should not assume interchangeable measures because the scoping review (Oct 2023âFeb 2024) found 2, 402 unique items across 523 articles.\",\"Practical decision rule: According to Duke and Holt, if you measure incoming students or general acceptance, select the Anthropogenic Definition; if you measure disciplinary understanding or post-course outcomes, select the Anthropogenic + Mechanistic Definition.\"]}
81,{\"type\":\"subsections\",\"title\":\"How Evidano helps researchers apply these consensus definitions\",\"subsections\":[{\"title\":\"What Evidano is\",\"content\":[\"Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"How this maps to the PLoS One study: Duke and Holtâs process required rapid thematic coding of interviews, frequency counts of definition choices, and cross-round stability checks, tasks that AI-enabled qualitative tools can accelerate without sacrificing methodological rigor.\"]},{\"title\":\"Problem: 2, 402 unique items and inconsistent constructs â Solution: content mapping at scale\",\"content\":[\"Problem: The scoping review reported 2, 402 unique items (Oct 2023âFeb 2024), making manual mapping slow and error-prone; Duke and Holt triangulated constructs across sources to create their codebook.\",\"Solution: Evidano automates ingestion of item banks and interview transcripts, performs thematic clustering and co-occurrence analysis, and produces codeâsubcode hierarchies that let teams quickly compare candidate items to the two consensus definitions, see [Evidano features](https://www.evidano.com/features) for capabilities.\"]},{\"title\":\"Problem: iterative Delphi rounds need stable tracking â Solution: reproducible audit trails\",\"content\":[\"Problem: Delphi processes require tracking percent agreement and qualitative rationales across rounds, as Duke and Holt did across Rounds 2â4.\",\"Solution: Evidano creates versioned analyses and exportable frequency counts so researchers can reproduce percent-agreement tables and attach coded rationales to items for review by panels.\"]},{\"title\":\"Problem: instrument development and validation â Solution: definition-driven item selection and synthesis\",\"content\":[\"Problem: Duke and Holt caution that instruments developed before defining acceptance may underrepresent the construct.\",\"Solution: Evidanoâs AI chat over your documents plus thematic and frequency analyses helps you shortlist candidate items that map to either the Anthropogenic Definition or the Anthropogenic + Mechanistic Definition, accelerating pilot testing and construct validation.\"]}]},{\"type\":\"subsections\",\"title\":\"FAQ: climate change acceptance definition\",\"subsections\":[{\"title\":\"What are the two consensus definitions of climate change acceptance from the PLoS One Delphi study?\",\"content\":[\"Direct answer: Duke and Holt present two definitions labeled the Anthropogenic Definition and the Anthropogenic + Mechanistic Definition.\",\"Supporting detail: According to Duke and Holt in [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374) (Aug 25, 2026), the Anthropogenic Definition reads \\\"Climate change is happening and human behaviors are causing it, \\\" while the Anthropogenic + Mechanistic Definition reads \\\"Climate change is happening, average temperatures and greenhouse gases are increasing globally, and human behaviors are causing it.\\\"\"]},{\"title\":\"Which definition should I use for a first-year undergraduate survey?\",\"content\":[\"Direct answer: Use the Anthropogenic Definition for first-year or baseline surveys.\",\"Supporting detail: Duke and Holt report that educators favored the concise Anthropogenic Definition as a baseline because it does not require prior mechanistic knowledge and was selected for simplicity by 64% of Round 4 participants (n = 70) according to [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374).\"]},{\"title\":\"Does the Delphi study show mechanistic knowledge increases acceptance?\",\"content\":[\"Direct answer: The study does not claim a causal effect but reports that many educators consider mechanistic knowledge relevant to deeper forms of acceptance.\",\"Supporting detail: Duke and Holt note that some experts conflated knowledge and acceptance and that Round 3 participants (n = 26) preferred the mechanistic definition because it explicitly links greenhouse gases and temperature with human causation.\"]},{\"title\":\"Can I use existing instruments after these definitions were published?\",\"content\":[\"Direct answer: You can use existing instruments, but you should align them to your chosen definition and reassess content validity.\",\"Supporting detail: Duke and Holt warn that many published instruments were developed without a universal definition and that researchers must critically evaluate whether an instrument maps to either the Anthropogenic or Anthropogenic + Mechanistic Definition before interpreting results.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"Duke and Holtâs Delphi study in [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374) (published August 25, 2026) produces two rigorously derived definitions of climate change acceptance for undergraduate science students, giving educators and researchers explicit targets for measurement.\",\"Researchers should map existing items to one of the two consensus definitions, pilot for content validity, and report the chosen definition when publishing results, as Duke and Holt recommend.\",\"If you want to accelerate that mapping and produce reproducible thematic and frequency analyses across interview transcripts and item banks, use AI-enabled qualitative research tools that preserve audit trails.\",\"Ready to align your instruments to a consensus definition and speed analysis with AI? [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"This post explains the two consensus definitions of \\\"climate change acceptance\\\" developed for undergraduate science students and shows how AI-enabled qualitative research tools can accelerate definition-driven instrument design. The primary keyword \\\"climate change acceptance definition\\\" refers to the pair of definitions that Jessica R. Duke and Emily A. Holt published in PLoS One on August 25, 2026: the shorter \\\"Anthropogenic Definition\\\" and the longer \\\"Anthropogenic + Mechanistic Definition\\\". According to Duke and Holt in [PLoS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0356374) (Aug 25, 2026), the two definitions emerged after a scoping review, a pilot student survey, and four Delphi rounds with educator experts.\"},\"category\":\"Commentary on News\",\"keywords\":[\"climate change acceptance definition\",\"Delphi climate acceptance undergraduates\",\"climate acceptance definitions PLoS One\",\"AI qualitative analysis for survey design\"],\"description\":\"PLoS One (Aug 25, 2026) presents two consensus climate change acceptance definitions for undergraduates; see stats and how AI qualitative analysis accelerates survey design.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1193,\"publishedAt\":\"2026-08-27T02:28:29.626300Z\"},{\"slug\":\"qualitative-analysis-larc-pm-bangladesh\",\"title\":\"AI synthesis: qualitative analysis of LARC/PM uptake\",\"author\":\"Evidano\",\"content\":{\"title\":\"AI synthesis of a PLOS ONE qualitative analysis of LARC/PM uptake\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to the PLOS ONE study by Shoma and Barden-OâFallon (published Aug 25, 2026) [PLOS ONE](https://journals.plos.org/plosone/article? id=10.1371%2Fjournal.pone.0356493), low LARC/PM uptake in rural Cumilla is driven by intertwined individual fears, family and community norms, provider practices, and health system constraints.\",{\"points\":[\"The study conducted 28 in-depth interviews and 9 key informant interviews between Jan 21 and Feb 20, 2023, with 37 participants consenting out of 46 approached (9 refusals), as reported in PLOS ONE on Aug 25, 2026.\",\"According to PLOS ONE, Cumilla district had LARC/PM use of 13.6% in 2022 and national LARC/PM share declined to 8% by 2022, underscoring a programmatic gap.\",\"The PLOS ONE results identify recurrent themes: (1) knowledge gaps and embodied fear of side effects, (2) male-dominated decision-making and mother-in-law gate
81keeping, and (3) provider bias, brief counselling, privacy deficits, and workforce shortages.\",\"The PLOS ONE study documents direct experience-based quotes such as: \\\"Look, sister, we are uneducated people. We donât know or understand these methods\\\" (W 02), and a provider reflection, \\\"Most women who come for IUD removal complain of bleeding problems\\\" (P 04), which anchor the qualitative claims in participantsâ voices.\"]}]},{\"type\":\"text\",\"title\":\"What happened and how the study was done\",\"content\":[\"Answer: The PLOS ONE study used purposive sampling and thematic analysis to map multi-level barriers to LARC/PM uptake in Cumilla, Bangladesh.\",\"According to the PLOS ONE article (published Aug 25, 2026), the authors carried out 28 in-depth interviews with married women and men plus 9 key informant interviews with family planning providers and an Imam, collecting data between Jan 21 and Feb 20, 2023.\",\"According to PLOS ONE, transcripts were transcribed in Bengali, translated to English, and analyzed using Braun and Clarkeâs thematic analysis guided by McLeroy et al.âs socio-ecological model, using a hybrid inductive-deductive coding approach.\",\"According to PLOS ONE, the analytic sample included 22 women, 6 men, 8 family planning service providers and 1 religious leader, and the team assessed saturation iteratively during fieldwork.\"]},{\"rows\":[[\"Aug 25, 2026\",\"Publication\",\"[PLOS ONE](https://journals.plos.org/plosone/article? id=10.1371%2Fjournal.pone.0356493)\",\"Peer-reviewed qualitative evidence available for program design\"],[\"Jan 21âFeb 20, 2023\",\"Data collection window\",\"28 IDIs + 9 KIIs\",\"In-depth perspectives from demand and supply sides\"],[\"2022\",\"LARC/PM prevalence in Cumilla\",\"13.6%\",\"Locally low uptake within Chattogram Division\"],[\"1991â2022\",\"Trend in LARC/PM share\",\"Declined from 12.1% (1991) to 8% (2022)\",\"Program delivery and method mix shifts require investigation\"],[\"Sample consent\",\"Approached vs consented\",\"46 approached, 37 consented, 9 refusals\",\"Refusals concentrated among men, indicating recruitment constraints\"]],\"type\":\"table\",\"title\":\"Findings snapshot\",\"headers\":[\"Date\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for qualitative researchers and program evaluators\",\"content\":[\"Answer: The PLOS ONE study shows that qualitative methods must capture multilevel context, embodied experiences, and power relations when evaluating contraceptive uptake.\",\"According to PLOS ONE, researchers should design interview guides that probe embodied side effects, family power dynamics, and religious meaning because participants cited lived bodily experiences and community narratives as decisive.\",\"According to PLOS ONE, program evaluators should pair qualitative findings with facility readiness data (for example, workforce shortages and counselling quality) to avoid blaming clients for system failures.\",\"Practical research decisions informed by the PLOS ONE study include oversampling male partners and influencers where possible, scheduling longer interviews for women to elicit embodied narratives, and triangulating provider accounts with client quotations to detect provider bias.\"]},{\"type\":\"subsections\",\"title\":\"How Evidano helps: AI tools mapped to the studyâs barriers\",\"subsections\":[{\"title\":\"Problem: Large interview corpus, slow manual synthesis â Solution: Rapid thematic coding\",\"content\":[\"Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"Evidano can ingest transcriptions (including custom dictionaries and PII redaction) and auto-suggest inductive themes so teams replicate Braun and Clarke workflows at scale; this directly accelerates tasks performed in the PLOS ONE study such as hybrid inductive-deductive coding.\",\"See the platform features page for relevant capabilities: [Evidano features](https://www.evidano.com/features).\"]},{\"title\":\"Problem: Cross-cutting socio-ecological themes are hard to compare â Solution: cross-segment analysis\",\"content\":[\"Evidano supports cross-segment analyses that compare themes by participant type (for example, women vs providers vs religious leader) so researchers can quantify how frequently an issue like \\\"fear of infertility\\\" appears across groups and dates.\",\"This mirrors the PLOS ONE need to show how knowledge gaps and stigma vary across individual, interpersonal, community, and system levels.\"]},{\"title\":\"Problem: Quotes and evidence need traceability â Solution: searchable transcripts + AI chat\",\"content\":[\"Evidano preserves verbatim quotations and links them to source timestamps and participant meta-data, enabling transparent citation of participant voices such as \\\"Look, sister, we are uneducated people\\\" (W 02) as reported in PLOS ONE.\",\"Evidanoâs AI chat over your project data helps produce extractable evidence summaries for reports, grant applications, or policy briefs while maintaining an audit trail.\"]},{\"title\":\"Problem: Iterative probing and translator checks â Solution: integrated transcription and translation\",\"content\":[\"Evidano offers transcription and translation with custom dictionaries, which helps teams that, like the PLOS ONE authors, transcribe in Bengali and translate to English while preserving technical terms and local phrasing.\",\"Accurate translation keeps quotations defensible and reduces meaning loss during cross-language analysis.\"]}]}
81,{\"type\":\"subsections\",\"title\":\"FAQ: qualitative analysis of LARC/PM uptake\",\"subsections\":[{\"title\":\"What were the main barriers to LARC/PM uptake identified by the PLOS ONE study?\",\"content\":[\"Answer: The PLOS ONE study found barriers at individual, interpersonal, community, institutional, and health-system levels.\",\"According to PLOS ONE, individual barriers included knowledge gaps and fear of side effects; interpersonal barriers included male-dominated decision making and mother-in-law influence; community barriers included son preference, stigma, and religious interpretations; institutional barriers included provider bias, brief counselling, and privacy deficits; health-system barriers included workforce shortages and low incentives.\"]},{\"title\":\"How was data collected and analyzed in the PLOS ONE study?\",\"content\":[\"Answer: The PLOS ONE study used purposive sampling, in-depth semi-structured interviews, and thematic analysis.\",\"According to PLOS ONE, interviews were conducted from Jan 21âFeb 20, 2023 (28 IDIs and 9 KIIs), transcribed in Bengali, translated into English, and coded using a hybrid inductive-deductive approach with Braun and Clarkeâs framework and the socio-ecological model as an organizing lens.\"]},{\"title\":\"Can AI tools change interpretation or bias in such qualitative studies?\",\"content\":[\"Answer: AI tools can accelerate coding and surface patterns but must be used with careful human oversight to avoid reinforcing bias.\",\"According to best practices and the PLOS ONE emphasis on reflexivity, researchers should use AI to propose codes and frequencies, while retaining human review for context-sensitive interpretation, verbatim quote selection, and ethical judgment.\"]},{\"title\":\"Are the PLOS ONE findings generalizable beyond Cumilla district?\",\"content\":[\"Answer: The PLOS ONE authors state the findings are context-specific and analytically transferable rather than statistically generalizable.\",\"According to PLOS ONE, the purposive sample and qualitative design aimed for depth in Cumilla, and the authors caution about regional variation, limited male sample size, and predominance of Muslim participants when applying the findings elsewhere.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"Recap: The PLOS ONE qualitative analysis (published Aug 25, 2026) documents how fear, social norms, provider practices, and health-system constraints combine to suppress LARC/PM uptake in rural Bangladesh; the reportsâ 28 IDIs and 9 KIIs provide concrete, attributable evidence.\",\"Next steps for researchers include pairing these qualitative insights with facility readiness metrics and designing migration- and gender-sensitive interventions that address embodied concerns and provider accountability, as recommended by PLOS ONE.\",\"If you want to accelerate transparent, auditable thematic synthesis of interviews like those used in the PLOS ONE study, try an AI-first workflow: [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. This post applies an AI-enabled qualitative research lens to the PLOS ONE study \\\"Understanding the low uptake of long-acting reversible and permanent contraceptive methods in rural Bangladesh\\\" by Shoma and Barden-OâFallon, with the primary keyword qualitative analysis of LARC/PM uptake. According to the PLOS ONE article (published Aug 25, 2026), the authors used a socio-ecological framework and in-depth interviews to explain why LARC/PM use remains low in rural Cumilla, Bangladesh. This write-up highlights the study's methods, concrete numbers and quotes, practical implications for qualitative researchers, and how AI tools accelerate trustworthy thematic synthesis.\"},\"category\":\"Commentary on News\",\"keywords\":[\"qualitative analysis of LARC/PM uptake\",\"LARC uptake Bangladesh qualitative\",\"AI-enabled qualitative research\",\"thematic analysis family planning\"],\"de
81scription\":\"AI-enabled synthesis of a PLOS ONE qualitative analysis of LARC/PM uptake in rural Bangladesh (Aug 25, 2026). Read methods, key stats, quotes, and AI research workflows.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1192,\"publishedAt\":\"2026-08-27T02:27:53.966224Z\"},{\"slug\":\"ai-simulation-testing-clinical\",\"title\":\"Simulation Testing: AI Simulation Testing for Clinical Care\",\"author\":\"Evidano\",\"content\":{\"title\":\"Simulation Testing: AI Simulation Testing for Clinical Care\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to HealthsystemCIO, Mayo Clinic is using its simulation center to test clinical AI, surfacing workflow variation and clinician acceptance issues before deployment ([HealthsystemCIO](https://healthsystemcio.com/2026/08/24/ai-simulation-testing-mayo/)).\",{\"points\":[\"As of August 24, 2026, HealthsystemCIO reports Mayoâs simulation program leverages a simulation center staffed with more than 100 standardized patients to create realistic clinical encounters.\",\"According to HealthsystemCIO on August 24, 2026, Mayoâs landscape analysis spans five years of translational work begun in 2021 and has produced an enterprise advisory board and a testing catalog.\",\"According to HealthsystemCIO on August 24, 2026, clinician time is the single largest operational constraint for simulation testing, and Mayo is piloting a clinician AI testing core plus remote and after-hours options to grow sample sizes.\"]}]},{\"type\":\"text\",\"title\":\"What Happened: Mayo Clinicâs Simulation-Based Evaluation\",\"content\":[\"Answer: According to HealthsystemCIO, Mayo Clinic moved AI evaluation into its existing simulation center to test tools in realistic workflows before clinical deployment.\",\"According to HealthsystemCIO on August 24, 2026, Shauna Overgaard, PhD, described that Mayoâs team inherited simulation design expertise and standardized patient rosters from decades of medical education work.\",\"According to HealthsystemCIO on August 24, 2026, the program began after a five-year translational science effort (since 2021) that produced an enterprise advisory board, an evaluation framework, and a catalog of testing methods.\",\"According to HealthsystemCIO on August 24, 2026, simulation studies combine human factors observation, workflow shadowing by implementation scientists, and mathematical fairness testing (for example using the HOUSES index) to reveal performance gaps across populations.\",\"According to HealthsystemCIO on August 24, 2026, Mayo is adapting logistics to clinician constraints by offering remote standardized-patient sessions via Teams and after-hours observation and by piloting a clinician AI testing core.\"]},{\"rows\":[[\"August 24, 2026\",\"Article reporting Mayo strategy\",\"HealthsystemCIO feature article\",\"Documents simulation approach and operational barriers\"],[\"August 24, 2026\",\"Standardized patient capacity\",\"More than 100 standardized patients\",\"Enables many realistic scenarios but requires clinician time to staff\"],[\"2021 to 2026\",\"Translational program length\",\"5 years\",\"Produced framework, advisory board, and testing catalog\"]],\"type\":\"table\",\"title\":\"Findings Snapshot\",\"headers\":[\"Date\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for Clinical Researchers and UX Teams\",\"content\":[\"Answer: According to HealthsystemCIO, simulation testing makes clinical workflows visible and gives clinicians evidence they expect before adoption.\",\"According to HealthsystemCIO on August 24, 2026, researchers should embed an implementation scientist to shadow real workflows before any advisory review to identify insertion points and baseline metrics.\",\"According to HealthsystemCIO on August 24, 2026, UX teams must plan for clinician availability as a project constraint and budget clinician time explicitly through protected research time, publication credit, or compensation models.\",\"According to HealthsystemCIO on August 24, 2026, teams must pair human factors testing with mathematical subgroup checks, for example Mayoâs use of the HOUSES index to detect socioeconomic performance gaps and then design interface cues that surface model reliability.\"]}
81,{\"type\":\"subsections\",\"title\":\"How Evidano Helps\",\"subsections\":[{\"title\":\"Problem: Shadowing and qualitative synthesis are slow\",\"content\":[\"Solution: Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"Evidano feature mapping: Use thematic coding and cross-segment analysis to turn implementation scientist field notes and standardized-patient transcripts into prioritized barriers and insertion points; see the platform capabilities at [Evidano Features](https://www.evidano.com/features).\",\"Evidano benefit: Average synthesis time drops because Evidano extracts code frequencies, co-occurrence networks, and illustrative quotes so teams can present evidence to advisory boards faster.\"]},{\"title\":\"Problem: Limited clinician time reduces sample sizes\",\"content\":[\"Solution: Evidano supports rapid transcription, redaction, and translation for remote video and phone sessions so simulation testing can run asynchronously.\",\"Evidano feature mapping: Use [Evidano Speech-to-Text](https://www.evidano.com/speech-to-text) for accurate transcripts with custom dictionaries, then run thematic frequency and segment comparisons to evaluate differential responses across clinician subgroups.\"]},{\"title\":\"Problem: Need to track model equity and interface cues\",\"content\":[\"Solution: Evidanoâs cross-segment analysis connects qualitative clinician reasoning with quantitative subgroup performance so teams can design and test patient-context reliability cues.\",\"Evidano workflow: Ingest model output, clinician notes, and standardized-patient transcripts, then generate content and frequency analyses that support iterative simulation design and post-deployment monitoring.\"]}]},{\"type\":\"subsections\",\"title\":\"FAQ: AI simulation testing\",\"subsections\":[{\"title\":\"What is AI simulation testing and why use it?\",\"content\":[\"Answer: AI simulation testing is evaluating clinical AI in realistic, controlled clinical scenarios to surface workflow and safety risks before deployment.\",\"According to HealthsystemCIO on August 24, 2026, Mayo Clinic uses its simulation center and standardized patients to recreate clinical encounters so clinicians can test the tool in context and generate evidence that builds trust.\"]},{\"title\":\"How do you measure success in a simulation study?\",\"content\":[\"Answer: Success is measured by predefined workflow metrics, clinician task time, safety signals, and clinician acceptance rates.\",\"According to HealthsystemCIO on August 24, 2026, Mayo teams start with baseline metrics collected by implementation scientists and then test whether the AI improves or degrades those metrics during simulated encounters.\"]},{\"title\":\"How do you recruit clinicians without overloading them?\",\"content\":[\"Answer: Offer flexible remote sessions, publication credit, formalized testing roles, and appropriate compensation to protect clinician time.\",\"According to HealthsystemCIO on August 24, 2026, Mayo is piloting a clinician AI testing core and experimenting with after-hours remote sessions and academic credit as incentives.\"]},{\"title\":\"Can qualitative tools scale simulation findings into policy?\",\"content\":[\"Answer: Yes, rigorous qualitative synthesis translates simulation observations into actionable policy recommendations.\",\"According to HealthsystemCIO on August 24, 2026, Mayoâs advisory board relies on implementation-scientist reports and simulation evidence to create policies that assign clinical champions and product owners for each AI tool.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"According to HealthsystemCIO on August 24, 2026, Mayo Clinicâs use of simulation shows that realistic, human-centered testing reduces the translation gap between AI research and clinical practice.\",\"Researchers and product teams should start with workflow shadowing, formalize clinician roles, and pair human factors simulation with quantitative subgroup checks to surface equity gaps.\",\"If your team runs standardized-patient sessions, use an analysis platform that ingests transcripts, codes themes, and compares segments to accelerate evidence for advisory review; explore [Evidano Features](https://www.evidano.com/features) for relevant capabilities.\",\"Try [Try Evidano for free](https://www.evidano.com/register) to pilot thematic and cross-segment analyses on your simulation transcripts and turn qualitative evidence into implementation decisions.\"]}],\"introduction\":\"AI simulation testing is the practice of evaluating clinical AI in lifelike, controlled settings before deployment. HealthsystemCIO reported on August 24, 2026 that Mayo Clinic runs selected AI tools through its simulation center to reveal workflow, usability, and safety risks before live care. This post translates Mayo Clinicâs approach into actionable guidance for qualitative researchers, UX teams, and clinical implementation leaders who need reproducible, human-centered evaluation methods.\"},\"category\":\"Commentary on News\",\"keywords\":[\"AI simulation testing\",\"clinical AI evaluation\",\"simulation-based AI testing\",\"AI translation gap\",\"qualitative AI testing\"],\"de
81scription\":\"How Mayo Clinic uses AI simulation testing to close the clinical AI translation gap; practical steps for qualitative researchers and UX teams plus tools to scale evaluation.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1191,\"publishedAt\":\"2026-08-27T02:26:52.908224Z\"},{\"slug\":\"qualitative-analysis-contraceptive-uptake-bangladesh-d333f5d9\",\"title\":\"AI-ready Guide: qualitative analysis of contraceptive uptake\",\"author\":\"Evidano\",\"content\":{\"title\":\"AI-enabled qualitative analysis of contraceptive uptake in rural Bangladesh\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to the PLOS One study, published August 25, 2026, multilevel socio-ecological barriers explain persistently low long-acting reversible and permanent contraception (LARC/PM) uptake in rural Cumilla, Bangladesh, despite national family planning goals. The PLOS One study collected data from January 21 to February 20, 2023, using 28 in-depth interviews and 9 key informant interviews (37 total participants).\",{\"points\":[\"The PLOS One study found that 22 of the in-depth interview participants were women and 6 were men; data collection occurred between 21 January and 20 February 2023.\",\"The PLOS One article reports that national LARC/PM share declined from 12.1% in 1991 to 8% in 2022, and that Cumilla had 13.6% LARC/PM use in 2022, showing a gap versus program targets.\",\"The PLOS One authors identified five analytic levels (individual, interpersonal, community, institutional, and health-system) with concrete barriers including fears of infertility, provider coercion, male-dominated decision-making, religious stigma, and workforce shortages.\",\"The PLOS One study documents rights violations: respondents reported coerced insertions and refusals to remove devices, which the authors link to incentive structures and weak accountability mechanisms.\",\"Direct respondent evidence in PLOS One includes: âWe donât know or understand these methodsâ (W 02) and âMen donât want to undergo (vasectomy)â¦they fear they will have sexual problemsâ (P 02).\"]}]},{\"type\":\"text\",\"title\":\"What Happened: qualitative analysis of contraceptive uptake in Cumilla\",\"content\":[\"Answer-first: The PLOS One study used a socio-ecological qualitative approach to explain why LARC/PM uptake remains low in rural Cumilla, Bangladesh.\",\"The PLOS One article (published August 25, 2026) reports purposive sampling that produced 28 in-depth interviews with married women and men and 9 key informant interviews with providers and one religious leader, with interviews lasting 7â55 minutes between 21 January and 20 February 2023.\",\"The PLOS One authors analyzed transcribed Bengali interviews translated into English using Braun and Clarkeâs thematic analysis with a hybrid inductive-deductive codebook organized by the socio-ecological model.\",\"The PLOS One findings document method-specific fears (for example IUDs linked to infection, implants to heavy bleeding), interpersonal gatekeeping (15 of 22 interviewed women reported husbands had decision power), community norms (male-child preference and religious narratives), and system failures (short counselling, workforce shortages).\"]},{\"rows\":[[\"PLOS One (published Aug 25, 2026)\",\"Qualitative interviews collected\",\"28 IDIs + 9 KIIs (37 total) between 21 Janâ20 Feb 2023\",\"Rich multi-stakeholder perspectives across socio-ecological levels\"],[\"PLOS One (citing DGFP 2022)\",\"LARC/PM national share\",\"8% in 2022 (declined from 12.1% in 1991)\",\"Programmatic retreat from long-acting methods; service gaps\"],[\"PLOS One (citing DGFP 2022)\",\"Cumilla LARC/PM use\",\"13.6% in 2022\",\"Site selection rationale: persistently low uptake regionally\"],[\"PLOS One (respondent quotes)\",\"Common individual concerns\",\"Fears: infertility, device migration, organ removal, impotence\",\"Information and counselling must address embodied and vicarious experiences\"],[\"PLOS One (providers)\",\"Rights and service delivery problems\",\"Reports of non-consensual insertions and refusal to remove\",\"Need for accountability, grievance mechanisms, and provider oversight\"]],\"type\":\"table\",\"title\":\"Findings Snapshot\",\"headers\":[\"Date / Source\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for qualitative researchers and program evaluators\",\"content\":[\"Answer-first: For researchers, the PLOS One findings mean study design, coding, and reporting must preserve context, quote-level provenance, and traceability to support ethical recommendations.\",\"The PLOS One study highlights how participant networks and embodied narratives (for example, neighborhood stories about infertility after implant removal) function as evidence in communities; qualitative researchers must code for source type (personal experience vs. hearsay) and map influence pathways.\",\"The PLOS One authors show that combining demand- and supply-side interviews (37 total participants across 28 IDIs and 9 KIIs) produced insights that single-source surveys miss; researchers should therefore plan mixed stakeholder recruitment and saturation checks similar to the PLOS One approach.\",\"The PLOS One evidence underlines the need to quantify qualitative themes for program decision-making: researchers should produce counts, timelines, and cross-segment comparisons (for example, method familiarity by gender) as the PLOS One authors did when reporting that 20 of 22 women recognized implants while only 9 knew about IUDs.\",\"Ethics note: The PLOS One study documents rights violations; researchers using similar qualitative methods must maintain confidentiality, obtain informed consent, and avoid facilitating coercion while collecting and disseminating findings.\"]}
81,{\"type\":\"subsections\",\"title\":\"How Evidano Helps: mapping PLOS One problems to AI-enabled solutions\",\"subsections\":[{\"title\":\"Problem: Fragmented transcripts, lost provenance\",\"content\":[\"Solution: Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"Evidano features automated transcription with a custom dictionary and PII redaction, which preserves verbatim quotes and speaker labels from interviews like the PLOS One study and speeds the stage of creating verifiable transcripts.\"]},{\"title\":\"Problem: Manual thematic coding and slow cross-segment synthesis\",\"content\":[\"Solution: Evidanoâs thematic and cross-segment analysis automates code suggestion, frequency tallies, and co-occurrence networks so researchers can reproduce counts such as \\\"20 of 22 women knew implants\\\" and quickly validate inter-rater consistency.\",\"Researchers can use Evidanoâs hierarchical code â subcode visualizations to mirror the PLOS One socio-ecological model and export counts anchored to source excerpts for transparent reporting.\"]},{\"title\":\"Problem: Handling multilingual data and translation fidelity\",\"content\":[\"Solution: Evidano supports translation with a custom dictionary so teams can preserve key terms and respondent meanings when translating interviews from Bengali into English, aligning with the PLOS One method of cross-checking translations.\",\"Use Evidanoâs AI chat over your documents to ask targeted questions like, âShow me all quotes about implant bleeding between Jan and Feb 2023, â and retrieve source-attributed excerpts instantly.\"]},{\"title\":\"Problem: Demonstrating rights-based service failures and generating accountability-ready reports\",\"content\":[\"Solution: Evidano produces audit-trailed exports (quote-level, timestamps, coder decisions) that can be attached to policy briefs or shared with oversight bodies while preserving participant anonymity.\",\"For operational teams, Evidanoâs visualizations and frequency metrics make systemic problems (for example, reports of non-consensual insertions) visible and actionable for program redesign.\"]},{\"title\":\"Learn more about relevant features\",\"content\":[\"See how automatic transcription works in practice on the Evidano [Speech-to-Text](https://www.evidano.com/speech-to-text) page.\",\"See product capabilities and workflows on the Evidano [Features](https://www.evidano.com/features) page.\"]}
81]},{\"type\":\"subsections\",\"title\":\"FAQ: qualitative analysis of contraceptive uptake\",\"subsections\":[{\"title\":\"How did the PLOS One study collect and analyze qualitative data?\",\"content\":[\"Answer: The PLOS One study conducted 28 in-depth interviews and 9 key informant interviews between 21 January and 20 February 2023 and analyzed transcripts using Braun and Clarkeâs thematic analysis with a hybrid inductive-deductive codebook guided by the socio-ecological model.\",\"Supporting detail: The PLOS One authors transcribed interviews in Bengali, translated them to English, used manual coding in Microsoft Excel, and iteratively refined themes until saturation.\"]},{\"title\":\"Which concrete statistics from the PLOS One study are most useful for program design?\",\"content\":[\"Answer: Useful statistics include the sample composition (22 women, 6 men among the 28 IDIs), the regional LARC/PM prevalence (Cumilla 13.6% in 2022), and national trends (LARC/PM share 8% in 2022, down from 12.1% in 1991) as reported in PLOS One.\",\"Supporting detail: These numbers can prioritize regions for intervention and benchmark program targets against documented method awareness and provider issues.\"]},{\"title\":\"Can AI tools preserve the ethical constraints of qualitative research?\",\"content\":[\"Answer: Yes, when configured with PII redaction, encrypted storage, and access controls, AI tools can speed analysis while preserving ethical safeguards.\",\"Supporting detail: The PLOS One study raises rights concerns (coercion, refusal to remove devices), so AI workflows must include anonymization, secure participant metadata handling, and human oversight for interpretation.\"]},{\"title\":\"How do I convert PLOS One-style qualitative findings into program actions?\",\"content\":[\"Answer: Translate themes into measurable indicators (for example, percent of women reporting counselling \u003e5 minutes, frequency of provider coercion reports) and design interventions that map to each SEM level described in PLOS One.\",\"Supporting detail: Use mixed-methods pilots that track both qualitative changes (attitudes, stigma) and service metrics (LARC/PM uptake rates) with pre-registered analysis plans and audit trails.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"Recap: The PLOS One qualitative study (published August 25, 2026) shows that low LARC/PM uptake in rural Bangladesh results from layered socio-ecological barriers, including embodied side-effect experiences, male-dominated decision-making, religious and cultural stigma, and service-delivery failures.\",\"Next steps for researchers: replicate multi-stakeholder interviews, code with provenance, produce counts and segment comparisons, and surface rights-related incidents with documentation suitable for program change.\",\"Operational next steps: use AI-assisted transcription and thematic analysis to compress synthesis time while preserving quotes and audit trails; for feature details see Evidano [Features](https://www.evidano.com/features).\",\"Ready to try an AI-first qualitative workflow? [Try Evidano for free](https://www.evidano.com/register).\"]}],\"introduction\":\"This post explains how AI-enabled qualitative research can turn the PLOS One qualitative study on LARC/PM uptake in rural Bangladesh into actionable evidence for researchers and program designers. The primary keyword for this article is qualitative analysis of contraceptive uptake and the audience is qualitative researchers, program evaluators, and UX teams working on reproductive health. The PLOS One study used 28 in-depth interviews and 9 key informant interviews, and the payoff here is a step-by-step mapping from study findings to reproducible analytic workflows and tooling choices that speed synthesis, maintain audit trails, and support rights-based recommendations.\"},\"category\":\"Commentary on News\",\"keywords\":[\"qualitative analysis of contraceptive uptake\",\"LARC uptake Bangladesh qualitative\",\"AI-enabled qualitative research\",\"family planning qualitative methods\"],\"description\":\"Apply AI-enabled qualitative analysis to LARC/PM uptake in rural Bangladesh: study stats, direct quotes, and practical researcher steps. Learn methods and next steps.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1190,\"publishedAt\":\"2026-08-27T02:26:42.453403Z\"},{\"slug\":\"qualitative-analysis-of-larc-uptake\",\"title\":\"AI-enabled qualitative analysis of LARC uptake\",\"author\":\"Evidano\",\"content\":{\"title\":\"AI-enabled qualitative analysis of LARC uptake\",\"sections\":[{\"type\":\"text\",\"title\":\"Key Takeaways\",\"content\":[\"According to the PLOS One study published August 25, 2026, low LARC/PM uptake in rural Cumilla, Bangladesh is driven by knowledge gaps, embodied side-effect fears, patriarchal decision-making, religious and cultural stigma, provider bias, and health-system constraints ([PLOS One](https://journals.plos.org/plosone/article? id=10.1371%2Fjournal.pone.0356493)).\",{\"points\":[\"The study conducted 28 in-depth interviews (22 women, 6 men) and nine key informant interviews between 21 January and 20 February 2023, as reported in PLOS One (published August 25, 2026).\",\"PLOS One reports that LARC/PM share in Bangladesh declined from 12.1% in 1991 to 8.0% in 2022, and that Cumilla district recorded 13.6% LARC/PM use in 2022, underscoring a persistent program gap.\",\"PLOS One found concrete service failures in 2023: brief counselling, provider bias, privacy deficits, and reports of non-consensual insertions, all of which undermine voluntary, rights-based uptake.\",\"PLOS One documents method-specific misperceptions present in JanuaryâFebruary 2023 interviews, for example fears that implants \\\"move around the body\\\" and that ligation is only available after caesarean delivery.\"]}]},{\"type\":\"text\",\"title\":\"What happened: study design and core findings\",\"content\":[\"Answer: The PLOS One study used a socio-ecological qual
81itative design to identify multilevel barriers to LARC/PM uptake in rural Cumilla, Bangladesh.\",\"The PLOS One study published August 25, 2026, conducted purposive sampling with 28 in-depth interviews (22 women, 6 men) and nine key informant interviews with providers and one religious leader, and analyzed transcripts using Braun and Clarkeâs thematic analysis approach.\",\"The PLOS One findings (Aug 25, 2026) organize barriers across five SEM levels: individual (knowledge gaps, fear of side effects), interpersonal (male-dominated decision-making, mother-in-law gatekeeping), community (religious norms, son preference, stigma), institutional (provider bias, brief counselling, privacy deficits), and health-system (staff shortages, weak incentives).\",\"Direct evidence from participants in PLOS One (JanâFeb 2023) includes method-specific lived-experience quotes such as a woman saying, \\\"Look, sister, we are uneducated people. We donât know or understand these methods.\\\" (participant W02, quoted in PLOS One).\"]},{\"rows\":[[\"2022, PLOS One citing DGFP\",\"National LARC/PM share\",\"8.0% in 2022 (declined from 12.1% in 1991)\",\"Program targets unmet; supply and demand gaps persist\"],[\"2022, PLOS One citing DGFP\",\"Cumilla district LARC/PM use\",\"13.6% in 2022\",\"Site selection justified for low-uptake qualitative enquiry\"],[\"21 Janâ20 Feb 2023, PLOS One primary data\",\"In-depth interviews\",\"28 IDIs (22 women, 6 men) and 9 KIIs\",\"Enables rich, multi-stakeholder thematic analysis\"],[\"Aug 25, 2026, PLOS One\",\"Reported program failures in counselling\",\"Many counselling sessions \u003c 5 minutes; frequent privacy deficits\",\"Counselling quality is a modifiable supply-side barrier\"]],\"type\":\"table\",\"title\":\"Findings snapshot\",\"headers\":[\"Date / Source\",\"Metric\",\"Value\",\"Implication\"]},{\"type\":\"text\",\"title\":\"Implications for qualitative researchers and program teams\",\"content\":[\"Answer: The PLOS One findings require mixed-level interventions and rigorous qualitative analysis that links narratives to service metrics.\",\"Researchers should treat reported fears and embodied experiences as legitimate data, not merely \\\"misinformation, \\\" because PLOS One (Aug 25, 2026) shows these fears are grounded in vicarious or direct bodily experiences and shape decision-making.\",\"Program designers should combine community-engaged dialogue (including religious leaders) with strengthened rights-based counselling because PLOS One (Aug 25, 2026) documents both religious objections and provider coercion as drivers of distrust.\",\"Research teams should prioritize interview segmentation and cross-tabulation (for example, migrant-household status, parity, and method history) because PLOS One (2026) links spouse migration and son preference norms to method choices.\"]},{\"type\":\"subsections\",\"title\":\"How Evidano helps: AI workflows mapped to PLOS One findings\",\"subsections\":[{\"title\":\"Problem: Large interview corpus, slow synthesis â Feature: Thematic + cross-segment analysis\",\"content\":[\"Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.\",\"For a dataset like PLOS Oneâs (28 IDIs, 9 KIIs collected JanâFeb 2023), Evidano automates verbatim transcript ingestion, supports manual and AI-assisted coding, and generates hierarchical themes and co-occurrence networks to reveal how fears, stigma, and provider practices cluster across respondent subgroups.\",\"Use case: tag all quotes about \\\"infertility\\\" and run cross-segment frequency counts by parity and household migration status to surface which groups hold which misperceptions most strongly.\"]},{\"title\":\"Problem: Transcription and translation errors obscure meaning â Feature: Transcription + translation\",\"content\":[\"Evidano integrates transcription features including custom dictionaries and PII redaction to preserve accuracy for interviews like those conducted in Bengali in PLOS One (JanâFeb 2023).\",\"Evidanoâs translation with custom glossaries helps maintain culturally specific terms (for example, \\\"pet katuni\\\") so thematic codes preserve local meaning rather than being flattened by literal translation.\"]},{\"title\":\"Problem: Rapid stakeholder reporting needed â Feature: AI chat over documents and visualizations\",\"content\":[\"Evidano provides AI chat over uploaded transcripts and visual dashboards (word clouds, co-occurrence networks, hierarchical codesâsubcodes) to produce stakeholder-ready, extractable quotes and recommendations tied to source IDs (e.g., W02, P03 as in PLOS One).\",\"Researchers can export a reproducible audit trail matching quotes to codes and timestamps, addressing rights-based concerns about consent and traceability noted
81in PLOS One (Aug 25, 2026).\",\"Learn more about relevant capabilities on Evidanoâs features page: [Evidano features](https://www.evidano.com/features).\"]},{\"title\":\"Problem: Audio quality and manual effort â Feature: Speech-to-text\",\"content\":[\"Evidanoâs speech-to-text pipeline handles noisy field recordings and supports speaker labels, which is useful for multi-speaker IDIs like those in PLOS One (JanâFeb 2023).\",\"See technical details at [Evidano speech-to-text](https://www.evidano.com/speech-to-text).\"]}]},{\"type\":\"subsections\",\"title\":\"FAQ: qualitative analysis of LARC uptake\",\"subsections\":[{\"title\":\"How do I structure a qualitative codebook for LARC uptake interviews?\",\"content\":[\"Answer: Start with a socio-ecological codebook and iteratively add inductive subcodes.\",\"Use the Socio-Ecological Model layers (individual, interpersonal, community, institutional, health-system) as top-level codes, as in the PLOS One analysis (Aug 25, 2026), and then derive inductive subcodes (for example, \\\"implant bleeding\\\" or \\\"mother-in-law gate
81keeping\\\") from early transcripts.\"]},{\"title\":\"Can AI help distinguish lived side-effect experiences from circulating rumors?\",\"content\":[\"Answer: Yes, AI-assisted thematic analysis can surface linguistic markers and co-occurrence that distinguish first-person embodied reports from hearsay.\",\"Operationally, tag language patterns such as first-person past tense and body-symptom terms to isolate embodied experiences, and compare their co-occurrence with network nodes like \\\"neighbour\\\" or \\\"heard from\\\" to identify vicarious narratives, a distinction emphasized in PLOS One (Aug 25, 2026).\"]},{\"title\":\"How should researchers present sensitive quotes while protecting participants?\",\"content\":[\"Answer: Use de-identified speaker IDs and paraphrase where necessary, keeping original wording in a secure, access-controlled dataset.\",\"PLOS One (Aug 25, 2026) used anonymized IDs such as W02 and P03; mirror that practice and keep verbatim transcripts encrypted and access-limited as part of ethical data governance.\"]},{\"title\":\"What metrics help program teams act on qualitative findings about LARC uptake?\",\"content\":[\"Answer: Combine qualitative frequency counts (theme prevalence by subgroup), time-to-service metrics, and reported counselling length as actionable indicators.\",\"For example, PLOS One (Aug 25, 2026) reports counselling often lasted under five minutes; measuring counselling duration and mapping it to subsequent uptake can indicate program improvements.\"]}]},{\"type\":\"text\",\"title\":\"Conclusion \u0026 Next Steps\",\"content\":[\"The PLOS One study (published August 25, 2026) shows that low LARC/PM uptake in rural Bangladesh is a multilevel problem that requires rights-based counselling, community engagement, and health-system reforms, all anchored in rigorous qualitative evidence.\",\"AI-enabled qualitative research workflows accelerate credible synthesis of interviews like those collected in JanâFeb 2023, while preserving audit trails and contextual nuance.\",\"If you want to prototype an analysis that mirrors the PLOS One approach, ingest transcripts, run thematic and cross-segment analyses, and produce stakeholder-ready recommendations, get started with Evidano.\",\"Try Evidano for free: [Try Evidano for free](https://www.evidano.com/register)\"]}],\"introduction\":\"According to the PLOS One study published August 25, 2026, persistent low uptake of long-acting reversible and permanent contraceptive methods (LARC/PM) in rural Bangladesh is shaped by multilevel social, institutional, and health-system barriers. This post is written for qualitative researchers, program managers, and UX teams who want a reproducible, AI-enabled approach to analyze interview and provider data on contraceptive uptake. The primary keyword for this post is \\\"qualitative analysis of LARC uptake\\\" and the payoff is a concise, reproducible workflow that maps the PLOS One findings onto AI-assisted coding, thematic synthesis, and rights-based program recommendations.\"},\"category\":\"Commentary on News\",\"keywords\":[\"qualitative analysis of LARC uptake\",\"AI qualitative research\",\"LARC uptake Bangladesh\",\"thematic analysis interviews\"],\"description\":\"How AI speeds thematic, cross-segment insight from interviews: an AI-enabled qualitative analysis of LARC uptake in rural Bangladesh, with practical research workflows.\",\"geo_version\":2,\"subcategory\":\"Commentary on News\",\"id\":1189,\"publishedAt\":\"2026-08-27T02:25:28.418465Z\"}]}],\"$L57\"]}]\n"])</script>
81<script>self.__next_f.push([1,"30:[\"$\",\"span\",null,{\"className\":\"w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Customer Experience and Voice-of-Customer Research\"}]\n31:[\"$\",\"h3\",null,{\"className\":\"mt-3 text-base font-semibold leading-snug text-gray-900\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/blogs/voice-of-customer-interviews\",\"children\":\"Voice-of-Customer Interviews: from customer words to design requirements\"}]}]\n32:[\"$\",\"p\",null,{\"className\":\"mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600\",\"children\":\"The VoC discipline: eliciting needs in customersâ own language, structuring them without losing the voice â Griffin and Hauserâs empirical findings.\"}]\n"])</script>
81<script>self.__next_f.push([1,"33:[\"$\",\"li\",\"think-aloud-protocol\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"h-24 w-full\",\"children\":[\"$\",\"div\",null,{\"aria-hidden\":true,\"aria-label\":\"$undefined\",\"className\":\"relative h-full w-full overflow-hidden\",\"role\":\"$undefined\",\"style\":{\"backgroundImage\":\"radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #3730A3 0%, #6366F1 100%)\",\"backgroundSize\":\"18px 18px, 100% 100%\"},\"children\":[\"$\",\"svg\",null,{\"className\":\"absolute inset-0 h-full w-full\",\"preserveAspectRatio\":\"xMidYMid meet\",\"viewBox\":\"0 0 160 100\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"children\":[\"$\",\"g\",null,{\"children\":[[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.20)\",\"height\":\"60\",\"rx\":\"5\",\"width\":\"56\",\"x\":\"52\",\"y\":\"20\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.92)\",\"height\":\"7\",\"rx\":\"3.5\",\"width\":\"7\",\"x\":\"60\",\"y\":\"30\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.42)\",\"height\":\"4\",\"rx\":\"2\",\"width\":\"30\",\"x\":\"72\",\"y\":\"31.5\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.92)\",\"height\":\"7\",\"rx\":\"3.5\",\"width\":\"7\",\"x\":\"60\",\"y\":\"46\"}],[\"$\",\"path\",null,{\"d\":\"M61.5 49.5l2 2 3.5-3.5\",\"stroke\":\"#0F2F5C\",\"strokeLinecap\":\"round\",\"strokeWidth\":\"1.6\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.92)\",\"height\":\"4\",\"rx\":\"2\",\"width\":\"24\",\"x\":\"72\",\"y\":\"47.5\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.42)\",\"height\":\"7\",\"rx\":\"3.5\",\"width\":\"7\",\"x\":\"60\",\"y\":\"62\"}],[\"$\",\"rect\",null,{\"fill\":\"rgba(255,255,255,0.42)\",\"height\":\"4\",\"rx\":\"2\",\"width\":\"34\",\"x\":\"72\",\"y\":\"63.5\"}]]}]}]}]}],[\"$\",\"div\",null,{\"className\":\"flex flex-1 flex-col p-5\",\"children\":[[\"$\",\"span\",null,{\"className\":\"w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"User Experience and Human-Centered Design\"}],[\"$\",\"h3\",null,{\"className\":\"mt-3 text-base font-semibold leading-snug text-gray-900\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/blogs/think-aloud-protocol\",\"children\":\"Think-Aloud Protocol: hearing reasoning as it happens\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600\",\"children\":\"Concurrent and retrospective think-aloud: the EricssonâSimon rules that keep verbal reports valid, running sessions without leading, and analysing the streams.\"}]]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"34:[\"$\",\"li\",\"diary-studies-or-experience-sampling\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"h-24 w-full\",\"children\":[\"$\",\"div\",null,{\"aria-hidden\":true,\"aria-label\":\"$undefined\",\"className\":\"relative h-full w-full overflow-hidden\",\"role\":\"$undefined\",\"style\":{\"backgroundImage\":\"radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0E7490 0%, #22B8D4 100%)\",\"backgroundSize\":\"18px 18px, 100% 100%\"},\"children\":[\"$\",\"svg\",null,{\"className\":\"absolute inset-0 h-full w-full\",\"preserveAspectRatio\":\"xMidYMid meet\",\"viewBox\":\"0 0 160 100\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"children\":[\"$\",\"g\",null,{\"children\":[[\"$\",\"path\",null,{\"d\":\"M42 26h44a6 6 0 0 1 6 6v20a6 6 0 0 1-6 6H60l-12 9V58h-6a6 6 0 0 1-6-6V32a6 6 0 0 1 6-6z\",\"fill\":\"rgba(255,255,255,0.92)\"}],[\"$\",\"path\",null,{\"d\":\"M100 44h18a6 6 0 0 1 6 6v16a6 6 0 0 1-6 6h-4v8l-10-8h-4a6 6 0 0 1-6-6V50a6 6 0 0 1 6-6z\",\"fill\":\"rgba(255,255,255,0.42)\"}]]}]}]}]}],[\"$\",\"div\",null,{\"className\":\"flex flex-1 flex-col p-5\",\"children\":[[\"$\",\"span\",null,{\"className\":\"w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Exploratory and Contextual Inquiry\"}],[\"$\",\"h3\",null,{\"className\":\"mt-3 text-base font-semibold leading-snug text-gray-900\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/blogs/diary-studies-or-experience-sampling\",\"children\":\"Diary Studies and Experience Sampling: research across time\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600\",\"children\":\"Capturing life as it is lived: interval, signal, and event-based designs, protocol and burden decisions, compliance, and analysing within-person change.\"}]]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"35:[\"$\",\"li\",\"empowerment-evaluation\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"h-24 w-full\",\"children\":[\"$\",\"div\",null,{\"aria-hidden\":true,\"aria-label\":\"$undefined\",\"className\":\"relative h-full w-full overflow-hidden\",\"role\":\"$undefined\",\"style\":{\"backgroundImage\":\"radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #0E7490 0%, #22B8D4 100%)\",\"backgroundSize\":\"18px 18px, 100% 100%\"},\"children\":[\"$\",\"svg\",null,{\"className\":\"absolute inset-0 h-full w-full\",\"preserveAspectRatio\":\"xMidYMid meet\",\"viewBox\":\"0 0 160 100\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"children\":[\"$\",\"g\",null,{\"children\":[[\"$\",\"path\",null,{\"d\":\"M42 26h44a6 6 0 0 1 6 6v20a6 6 0 0 1-6 6H60l-12 9V58h-6a6 6 0 0 1-6-6V32a6 6 0 0 1 6-6z\",\"fill\":\"rgba(255,255,255,0.92)\"}],[\"$\",\"path\",null,{\"d\":\"M100 44h18a6 6 0 0 1 6 6v16a6 6 0 0 1-6 6h-4v8l-10-8h-4a6 6 0 0 1-6-6V50a6 6 0 0 1 6-6z\",\"fill\":\"rgba(255,255,255,0.42)\"}]]}]}]}]}],[\"$\",\"div\",null,{\"className\":\"flex flex-1 flex-col p-5\",\"children\":[[\"$\",\"span\",null,{\"className\":\"w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Participatory and Collaborative Approaches\"}],[\"$\",\"h3\",null,{\"className\":\"mt-3 text-base font-semibold leading-snug text-gray-900\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/blogs/empowerment-evaluation\",\"children\":\"Empowerment Evaluation: building a programmeâs capacity to evaluate itself\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600\",\"children\":\"Fettermanâs approach: communities assess their own programmes with an evaluator as coach â the three steps, ten principles, a worked case, and the independence debate.\"}]]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"36:[\"$\",\"li\",\"utilization-focused-evaluation\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 bg-white transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"h-24 w-full\",\"children\":[\"$\",\"div\",null,{\"aria-hidden\":true,\"aria-label\":\"$undefined\",\"className\":\"relative h-full w-full overflow-hidden\",\"role\":\"$undefined\",\"style\":{\"backgroundImage\":\"radial-gradient(circle at 1px 1px, rgba(255,255,255,0.16) 1px, transparent 0), linear-gradient(135deg, #4C1D95 0%, #7C3AED 100%)\",\"backgroundSize\":\"18px 18px, 100% 100%\"},\"children\":[\"$\",\"svg\",null,{\"className\":\"absolute inset-0 h-full w-full\",\"preserveAspectRatio\":\"xMidYMid meet\",\"viewBox\":\"0 0 160 100\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"children\":[\"$\",\"g\",null,{\"children\":[[\"$\",\"path\",null,{\"d\":\"M48 24h56a8 8 0 0 1 8 8v28a8 8 0 0 1-8 8H74l-14 10V68h-12a8 8 0 0 1-8-8V32a8 8 0 0 1 8-8z\",\"fill\":\"rgba(255,255,255,0.92)\"}],[\"$\",\"g\",null,{\"fill\":\"#2A0F5E\",\"opacity\":\"0.45\",\"children\":[[\"$\",\"rect\",null,{\"height\":\"4\",\"rx\":\"2\",\"width\":\"34\",\"x\":\"58\",\"y\":\"36\"}],[\"$\",\"rect\",null,{\"height\":\"4\",\"rx\":\"2\",\"width\":\"24\",\"x\":\"58\",\"y\":\"46\"}]]}],[\"$\",\"path\",null,{\"d\":\"M118 30l2.6 6.4 6.4 2.6-6.4 2.6L118 48l-2.6-6.4-6.4-2.6 6.4-2.6z\",\"fill\":\"rgba(255,255,255,0.92)\"}]]}]}]}]}],[\"$\",\"div\",null,{\"className\":\"flex flex-1 flex-col p-5\",\"children\":[[\"$\",\"span\",null,{\"className\":\"w-fit rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Developmental and Utilization-Focused Evaluation\"}],[\"$\",\"h3\",null,{\"className\":\"mt-3 text-base font-semibold leading-snug text-gray-900\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/blogs/utilization-focused-evaluation\",\"children\":\"Utilization-Focused Evaluation: designing for use from day one\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 line-clamp-3 text-sm leading-relaxed text-gray-600\",\"children\":\"Pattonâs UFE: identify the primary intended users, negotiate intended uses, and make every design decision with them â framework, worked case, and the turnover risk.\"}]]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"37:[\"$\",\"p\",null,{\"className\":\"mt-6 text-sm text-gray-600\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"font-semibold text-[rgb(31,119,206)] hover:text-blue-700\",\"href\":\"/blogs/methods\",\"children\":[\"Browse all\",\" \",116,\" \",\"methodologies in the directory â\"]}]}]\n38:[\"$\",\"path\",\"19tzq7\",{\"d\":\"M20 9h2\"}]\n39:[\"$\",\"path\",\"165o2o\",{\"d\":\"M9 2v2\"}]\n3a:[\"$\",\"path\",\"i2bqo8\",{\"d\":\"M9 20v2\"}]\n3b:[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/how-we-trained-our-ai-models\",\"children\":\"How Evidanoâs models were trained\"}]}]\n3c:[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Model provenance for research-ethics review: a provenance-tiered curated corpus, and customer uploads, prompts and outputs excluded from training entirely.\"}]\n3d:[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]\n"])</script>
81<script>self.__next_f.push([1,"3e:[\"$\",\"li\",\"page:data-security\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-shield-check h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"oel41y\",{\"d\":\"M20 13c0 5-3.5 7.5-7.66 8.95a1 1 0 0 1-.67-.01C7.5 20.5 4 18 4 13V6a1 1 0 0 1 1-1c2 0 4.5-1.2 6.24-2.72a1.17 1.17 0 0 1 1.52 0C14.51 3.81 17 5 19 5a1 1 0 0 1 1 1z\"}],[\"$\",\"path\",\"dzmm74\",{\"d\":\"m9 12 2 2 4-4\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/data-security\",\"children\":\"Data security for qualitative research\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Encryption in transit and at rest, customer-controlled deletion, regional storage, and SOC 2 Type 2, GDPR, HIPAA-ready and CCPA/CPRA compliance.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"3f:[\"$\",\"li\",\"page:cite-us\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-book-open-check h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"gj6g52\",{\"d\":\"M12 21V7\"}],[\"$\",\"path\",\"mdajum\",{\"d\":\"m16 12 2 2 4-4\"}],[\"$\",\"path\",\"8arnkb\",{\"d\":\"M22 6V4a1 1 0 0 0-1-1h-5a4 4 0 0 0-4 4 4 4 0 0 0-4-4H3a1 1 0 0 0-1 1v13a1 1 0 0 0 1 1h6a3 3 0 0 1 3 3 3 3 0 0 1 3-3h6a1 1 0 0 0 1-1v-1.3\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/cite-us\",\"children\":\"How to cite and disclose Evidano\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Citation formats in APA, MLA, Chicago, Harvard and Vancouver, methods-section wording per workflow, and an AI-policy review of 41 journals across 8 disciplines.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"40:[\"$\",\"li\",\"page:environmental-impact\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-leaf h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"nnexq3\",{\"d\":\"M11 20A7 7 0 0 1 9.8 6.1C15.5 5 17 4.48 19 2c1 2 2 4.18 2 8 0 5.5-4.78 10-10 10Z\"}],[\"$\",\"path\",\"mt58a7\",{\"d\":\"M2 21c0-3 1.85-5.36 5.08-6C9.5 14.52 12 13 13 12\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/environmental-impact\",\"children\":\"Environmental impact of an analysis workflow\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Measured energy and water footprint of a typical project, with regional comparisons and mitigation.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"41:[\"$\",\"path\",\"6423bh\",{\"d\":\"M8 14h.01\"}]\n42:[\"$\",\"path\",\"mhygvu\",{\"d\":\"M12 18h.01\"}]\n43:[\"$\",\"path\",\"lrp35t\",{\"d\":\"M8 18h.01\"}]\n44:[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/pricing-comparison\",\"children\":\"Compare qualitative analysis software pricing\"}]}]\n45:[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"An interactive cost calculator for your own scenario against NVivo, MAXQDA, ATLAS.ti, Delve and Dedoose, using each vendorâs official checkout prices, segmented by student, academic, non-profit and commercial use.\"}]\n46:[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]\n"])</script>
81<script>self.__next_f.push([1,"47:[\"$\",\"li\",\"page:data-security-comparison\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-shield-check h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"oel41y\",{\"d\":\"M20 13c0 5-3.5 7.5-7.66 8.95a1 1 0 0 1-.67-.01C7.5 20.5 4 18 4 13V6a1 1 0 0 1 1-1c2 0 4.5-1.2 6.24-2.72a1.17 1.17 0 0 1 1.52 0C14.51 3.81 17 5 19 5a1 1 0 0 1 1 1z\"}],[\"$\",\"path\",\"dzmm74\",{\"d\":\"m9 12 2 2 4-4\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/data-security-comparison\",\"children\":\"Compare data security across QDA tools\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"A head-to-head security comparison sourced from each vendorâs own terms â subprocessor chains, AI model ownership, human review, training use and encryption posture.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"48:[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/ai-thematic-analysis\",\"children\":\"AI thematic analysis: accuracy, methods, and limits\"}]\n49:[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"What published agreement studies show about AI coding, how AI maps onto Braun and Clarkeâs phases, and a workflow you can defend to reviewers.\"}]\n4a:[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]\n"])</script>
81<script>self.__next_f.push([1,"4b:[\"$\",\"li\",\"page:ai-qualitative-coding\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-book-open h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"1akyts\",{\"d\":\"M12 7v14\"}],[\"$\",\"path\",\"ruj8y\",{\"d\":\"M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/ai-qualitative-coding\",\"children\":\"AI qualitative coding with your own codebook\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Deductive, codebook-driven coding across a full dataset, with an auditable source quote behind every code application.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"4c:[\"$\",\"li\",\"page:quote-traceability\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-quote h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"rib7q0\",{\"d\":\"M16 3a2 2 0 0 0-2 2v6a2 2 0 0 0 2 2 1 1 0 0 1 1 1v1a2 2 0 0 1-2 2 1 1 0 0 0-1 1v2a1 1 0 0 0 1 1 6 6 0 0 0 6-6V5a2 2 0 0 0-2-2z\"}],[\"$\",\"path\",\"1ymkrd\",{\"d\":\"M5 3a2 2 0 0 0-2 2v6a2 2 0 0 0 2 2 1 1 0 0 1 1 1v1a2 2 0 0 1-2 2 1 1 0 0 0-1 1v2a1 1 0 0 0 1 1 6 6 0 0 0 6-6V5a2 2 0 0 0-2-2z\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/quote-traceability\",\"children\":\"Source-traceable quotes\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Why hallucinated quotes are the central risk of AI qualitative analysis, and how clickable source-linked evidence makes every theme verifiable.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"4d:[\"$\",\"li\",\"page:multilingual-qualitative-analysis\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-languages h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"1wu5hv\",{\"d\":\"m5 8 6 6\"}],[\"$\",\"path\",\"1k1g8d\",{\"d\":\"m4 14 6-6 2-3\"}],[\"$\",\"path\",\"or177f\",{\"d\":\"M2 5h12\"}],[\"$\",\"path\",\"1t2jsx\",{\"d\":\"M7 2h1\"}],[\"$\",\"path\",\"don7ne\",{\"d\":\"m22 22-5-10-5 10\"}],[\"$\",\"path\",\"1m8k6r\",{\"d\":\"M14 18h6\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/multilingual-qualitative-analysis\",\"children\":\"Multilingual qualitative analysis\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Analyze interviews and surveys in 100+ languages â code in the original language or translate first, with transcription built into the workflow.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"4e:[\"$\",\"li\",\"page:features\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-sparkles h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"4pj2yx\",{\"d\":\"M9.937 15.5A2 2 0 0 0 8.5 14.063l-6.135-1.582a.5.5 0 0 1 0-.962L8.5 9.936A2 2 0 0 0 9.937 8.5l1.582-6.135a.5.5 0 0 1 .963 0L14.063 8.5A2 2 0 0 0 15.5 9.937l6.135 1.581a.5.5 0 0 1 0 .964L15.5 14.063a2 2 0 0 0-1.437 1.437l-1.582 6.135a.5.5 0 0 1-.963 0z\"}],[\"$\",\"path\",\"1olli1\",{\"d\":\"M20 3v4\"}],[\"$\",\"path\",\"1gvqau\",{\"d\":\"M22 5h-4\"}],[\"$\",\"path\",\"vumght\",{\"d\":\"M4 17v2\"}],[\"$\",\"path\",\"zchphs\",{\"d\":\"M5 18H3\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/features\",\"children\":\"All Evidano features\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Thematic, content, frequency and cross-segment analysis, AI avatar interviewing, transcription, translation, web and social data collection, and visualization.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"4f:[\"$\",\"li\",\"page:speech-to-text\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-mic h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"131961\",{\"d\":\"M12 2a3 3 0 0 0-3 3v7a3 3 0 0 0 6 0V5a3 3 0 0 0-3-3Z\"}],[\"$\",\"path\",\"1vc78b\",{\"d\":\"M19 10v2a7 7 0 0 1-14 0v-2\"}],[\"$\",\"line\",\"x3vr5v\",{\"x1\":\"12\",\"x2\":\"12\",\"y1\":\"19\",\"y2\":\"22\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/speech-to-text\",\"children\":\"Transcription for research audio and video\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Multi-language transcription with speaker diarization, with a page per supported language.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"50:[\"$\",\"li\",\"page:image-to-text\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-book-open h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"1akyts\",{\"d\":\"M12 7v14\"}],[\"$\",\"path\",\"ruj8y\",{\"d\":\"M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/image-to-text\",\"children\":\"Image to text for handwriting, manuscripts and scans\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Transcribe photographs, scans and PDFs, with a page of real sample pages for every supported script, hand and document type.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"51:[\"$\",\"li\",\"page:translation\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-languages h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"1wu5hv\",{\"d\":\"m5 8 6 6\"}],[\"$\",\"path\",\"1k1g8d\",{\"d\":\"m4 14 6-6 2-3\"}],[\"$\",\"path\",\"or177f\",{\"d\":\"M2 5h12\"}],[\"$\",\"path\",\"1t2jsx\",{\"d\":\"M7 2h1\"}],[\"$\",\"path\",\"don7ne\",{\"d\":\"m22 22-5-10-5 10\"}],[\"$\",\"path\",\"1m8k6r\",{\"d\":\"M14 18h6\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/translation\",\"children\":\"Translation for multilingual research\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Translate PDF, DOCX, XLSX and TXT sources across 100+ languages, with a page per language pair.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"52:[\"$\",\"li\",\"page:getdata\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-globe h-[18px] w-[18px]\",\"children\":[[\"$\",\"circle\",\"1mglay\",{\"cx\":\"12\",\"cy\":\"12\",\"r\":\"10\"}],[\"$\",\"path\",\"13o1zl\",{\"d\":\"M12 2a14.5 14.5 0 0 0 0 20 14.5 14.5 0 0 0 0-20\"}],[\"$\",\"path\",\"9i4pu4\",{\"d\":\"M2 12h20\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/getdata\",\"children\":\"Collect web and social media data\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Turn URLs and bulk lists into structured datasets across 82 platform types, ready for analysis.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"53:[\"$\",\"li\",\"page:guides\",{\"children\":[\"$\",\"article\",null,{\"className\":\"group relative flex h-full flex-col rounded-2xl border border-gray-200 bg-white p-5 transition-all duration-300 hover:border-[rgb(31,119,206)]/40 hover:shadow-[0_8px_24px_rgb(31,119,206,0.10)]\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-start justify-between gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap items-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"className\":\"rounded-full bg-blue-50 px-2.5 py-1 text-[11px] font-semibold uppercase tracking-wide text-[rgb(31,119,206)]\",\"children\":\"Resource\"}],\"$undefined\"]}],[\"$\",\"span\",null,{\"aria-hidden\":true,\"className\":\"inline-flex h-9 w-9 items-center justify-center rounded-xl bg-[rgb(31,119,206)]/10 text-[rgb(31,119,206)] flex-shrink-0\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-book-open h-[18px] w-[18px]\",\"children\":[[\"$\",\"path\",\"1akyts\",{\"d\":\"M12 7v14\"}],[\"$\",\"path\",\"ruj8y\",{\"d\":\"M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z\"}],\"$undefined\"]}]}]]}],[\"$\",\"h3\",null,{\"className\":\"mt-3 font-semibold text-gray-900 text-base\",\"children\":[\"$\",\"$L24\",null,{\"className\":\"after:absolute after:inset-0 focus:outline-none focus-visible:ring-4 focus-visible:ring-blue-100\",\"href\":\"/guides\",\"children\":\"Product documentation and tutorials\"}]}],[\"$\",\"p\",null,{\"className\":\"mt-2 text-gray-600 line-clamp-2 text-sm\",\"children\":\"Step-by-step documentation for using Evidano itself â getting started, workflows, troubleshooting and reference.\"}],\"$undefined\",[\"$\",\"div\",null,{\"className\":\"mt-auto pt-4\",\"children\":[\"$undefined\",\"$undefined\"]}]]}]}]\n"])</script>
81<script>self.__next_f.push([1,"57:[\"$\",\"nav\",null,{\"aria-label\":\"Blog pagination\",\"className\":\"mt-10 flex flex-col items-center gap-3\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex items-center justify-center gap-2\",\"children\":[[\"$\",\"span\",null,{\"aria-disabled\":true,\"className\":\"flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 cursor-not-allowed border-gray-200 text-gray-600 opacity-40\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-chevron-left h-4 w-4\",\"children\":[[\"$\",\"path\",\"1wnfg3\",{\"d\":\"m15 18-6-6 6-6\"}],\"$undefined\"]}]}],[[\"$\",\"$L24\",\"1\",{\"aria-current\":\"page\",\"aria-label\":\"Page 1\",\"className\":\"flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-[rgb(31,119,206)] bg-[rgb(31,119,206)] text-white shadow-md\",\"href\":\"/blogs\",\"children\":1}],[\"$\",\"$L24\",\"2\",{\"aria-current\":\"$undefined\",\"aria-label\":\"Page 2\",\"className\":\"flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-gray-200 text-gray-600 hover:border-blue-200 hover:text-[rgb(31,119,206)]\",\"href\":\"/blogs?page=2\",\"children\":2}],[\"$\",\"span\",\"ellipsis-right\",{\"className\":\"px-1 text-gray-400\",\"children\":\"â¦\"}],[\"$\",\"$L24\",\"117\",{\"aria-current\":\"$undefined\",\"aria-label\":\"Page 117\",\"className\":\"flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-gray-200 text-gray-600 hover:border-blue-200 hover:text-[rgb(31,119,206)]\",\"href\":\"/blogs?page=117\",\"children\":117}]],[\"$\",\"$L24\",null,{\"aria-label\":\"Next page\",\"className\":\"flex h-9 min-w-9 items-center justify-center rounded-lg border px-3 text-sm font-medium transition-all duration-200 border-gray-200 text-gray-600 hover:border-blue-200 hover:text-[rgb(31,119,206)]\",\"href\":\"/blogs?page=2\",\"rel\":\"next\",\"children\":[\"$\",\"svg\",null,{\"ref\":\"$undefined\",\"xmlns\":\"http://www.w3.org/2000/svg\",\"width\":24,\"height\":24,\"viewBox\":\"0 0 24 24\",\"fill\":\"none\",\"stroke\":\"currentColor\",\"strokeWidth\":2,\"strokeLinecap\":\"round\",\"strokeLinejoin\":\"round\",\"className\":\"lucide lucide-chevron-right h-4 w-4\",\"children\":[[\"$\",\"path\",\"mthhwq\",{\"d\":\"m9 18 6-6-6-6\"}],\"$undefined\"]}]}]]}],[\"$\",\"p\",null,{\"className\":\"text-xs text-gray-500\",\"children\":[\"Page\",\" \",1,\" \",\"of\",\" \",117]}]]}]\n"])</script>
81</body></html>
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.