SaludIA: community health worker perceptions and implementation of AI-enabled integrated health-environment screening in rural Colombia

SaludIA: community health worker perceptions and implementation of AI-enabled integrated health-environment screening in rural Colombia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article SaludIA: community health worker perceptions and implementation of AI-enabled integrated health-environment screening in rural Colombia Joseph Javier This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8356820/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Recent advances in Artificial Intelligence (AI) suggest that AI applications could transform healthcare delivery in resource-limited settings. However, little is known about community health workers’ (CHWs) knowledge, perceptions, and concerns regarding AI-enabled health applications when combined with environmental interventions. Objective: To examine CHWs’ knowledge, perceptions, understanding of AI, and anticipated benefits and challenges when integrating AI-enabled health-environment screening in rural Colombia. Methods: Empirical study conducted September-November 2025 with a purposively sampled cohort of 50 community health workers (54% female, mean age 46.8 years, mean experience 11.6 years) in Vereda El Manantial, Guadalajara de Buga, Colombia. Following a systematic two-condition video provocation protocol (positive scenario n=25, negative scenario n=25), participants engaged in semi-structured interviews averaging 45 minutes each, yielding a comprehensive qualitative dataset of 112 hours of audio-recorded material. Transcripts underwent dual-coded thematic analysis generating 156 initial codes synthesized through iterative consensus into 12 major themes. Stratified analysis examined response patterns across video conditions and demographic stratification by gender, age, CHW experience, and smartphone access. Results: Drawing on 112 hours of qualitative interview data from 50 CHWs, analysis reveals the Gender Paradox in technology adoption: male CHWs demonstrated skepticism-then-utopianism (65%→70%), while female CHWs maintained pragmatic gradualism. Key findings: (1) CHWs did not perceive AI as a threat (86%); (2) anticipated benefits—improved efficiency (92%), enhanced community respect (86%), upskilling (80%); (3) trust in AI (80%) alongside concerns about misdiagnosis (74%); (4) diverse data governance perspectives (58% government support); (5) limited privacy concerns (33%) despite vulnerabilities; (6) perceptual stability across scenarios demonstrated structural resilience of technological optimism in low-resource contexts. Conclusions: CHWs view AI-enabled health-environment integration as beneficial. This study contributes: (1) the Gender Paradox framework documenting differentiated adoption pathways with implications for gender-differentiated deployment; (2) structural resilience of technological optimism grounded in rational cost-benefit evaluation under scarcity. Deployment requires: algorithm transparency; gender-differentiated training; sustained technical support; and engagement with diverse values regarding privacy and community benefit. Artificial Intelligence and Machine Learning Artificial Intelligence Community Health Worker Gender Paradox Structural Resilience Health-Environment Integration Global South HCI4D ICTD Full Text Additional Declarations The authors declare no competing interests. Supplementary Files SupplementalDataS1ThematicCodebook.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8356820","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559996330,"identity":"e301344a-6a7d-4358-a47b-ead791df7ca4","order_by":0,"name":"Joseph Javier","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0007-2008-823X","institution":"Corporación Universitaria Minuto de Dios (UNIMINUTO)","correspondingAuthor":true,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Javier","suffix":""}],"badges":[],"createdAt":"2025-12-14 08:47:44","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8356820/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8356820/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98434650,"identity":"3dc31de8-7907-4b57-8234-256fd1ea0968","added_by":"auto","created_at":"2025-12-17 16:52:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":493252,"visible":true,"origin":"","legend":"","description":"","filename":"peerjreviewing130302v0.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8356820/v1_covered_0c99a5ae-01b7-4c85-a3b3-408081158856.pdf"},{"id":98273997,"identity":"cdb5acdb-2260-4bdf-a416-3109945688b4","added_by":"auto","created_at":"2025-12-16 02:57:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":83660,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalDataS1ThematicCodebook.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8356820/v1/14d51121dd769c8b7cc2607e.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eSaludIA: community health worker perceptions and implementation of AI-enabled integrated health-environment screening in rural Colombia\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[{"identity":"fced78ea-463d-4ca7-adb2-1f8247d29cbd","identifier":"10.13039/501100016362","name":"Corporación Universitaria Minuto de Dios","awardNumber":"N/A","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Corporación Universitaria Minuto de Dios","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial Intelligence, Community Health Worker, Gender Paradox, Structural Resilience, Health-Environment Integration, Global South, HCI4D, ICTD","lastPublishedDoi":"10.21203/rs.3.rs-8356820/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8356820/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Recent advances in Artificial Intelligence (AI) suggest that AI applications could transform healthcare delivery in resource-limited settings. However, little is known about community health workers’ (CHWs) knowledge, perceptions, and concerns regarding AI-enabled health applications when combined with environmental interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To examine CHWs’ knowledge, perceptions, understanding of AI, and anticipated benefits and challenges when integrating AI-enabled health-environment screening in rural Colombia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Empirical study conducted September-November 2025 with a purposively sampled cohort of 50 community health workers (54% female, mean age 46.8 years, mean experience 11.6 years) in Vereda El Manantial, Guadalajara de Buga, Colombia. 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Key findings: (1) CHWs did not perceive AI as a threat (86%); (2) anticipated benefits—improved efficiency (92%), enhanced community respect (86%), upskilling (80%); (3) trust in AI (80%) alongside concerns about misdiagnosis (74%); (4) diverse data governance perspectives (58% government support); (5) limited privacy concerns (33%) despite vulnerabilities; (6) perceptual stability across scenarios demonstrated structural resilience of technological optimism in low-resource contexts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e CHWs view AI-enabled health-environment integration as beneficial. This study contributes: (1) the Gender Paradox framework documenting differentiated adoption pathways with implications for gender-differentiated deployment; (2) structural resilience of technological optimism grounded in rational cost-benefit evaluation under scarcity. 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