Artificial intelligence in supporting non-dental workers to integrate oral health into primary care: An integrative review

Artificial intelligence in supporting non-dental workers to integrate oral health into primary care: An integrative review | 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 Systematic Review Artificial intelligence in supporting non-dental workers to integrate oral health into primary care: An integrative review Dr Md Nazmul Huda, Dileep Sharma, Sarbin Ranjitkar, Leonie M. Short, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8222032/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: The World Health Organization advocates for the involvement of non-dental workers in integrating oral health into primary care and improving oral health outcomes. Artificial Intelligence (AI) has the potential to facilitate their involvement in oral care, but existing literature remains fragmented and unsynthesised.This review aimed to examine the use and effectiveness of AI strategies to support non-dental workers inintegrating oral health into primary care. Methods: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and utilised Whittemore and Knafl’s (2005) integrative review framework (Prospero registration number: CRD42024593238). We searched for studies in CINAHL, EMBASE/Ovid, ProQuest, PsycINFO, PubMed, and Google Scholar and included papers published in English between 2015 and 2024 that examined AI strategies used by non-dental workers and their effectiveness. A data extraction form was used to extract information from the included articles, and athematic analysis was conducted to report findings. Results: This review included six studies with quantitative, qualitative, mixed-methods, participatory, and quasi-experimental designs. Findings revealed that various non-dental workers (e.g., frontline healthcare workers, clinic managers, care givers, registered nurses, general practitioners, and allied health staff) used preventive, triage, and oral diagnosis and treatment-focused AI applications in integrated oral health spaces, providing prompt, low-cost digital oral health education, screening, and referral services. These AI applications were reported to be effective in optimising knowledge, awareness, early detection, disease prevention, oral care, and addressing oral health disparities and inequity among diverse populations. Conclusions: AI can increase non-dental workers’ capacity and involvement in oral care within non-dental settings and support integrating oral health into primary care. However, this integration necessitates adequate training, and further research is warranted to clarify its role in optimising oral care. Artificial Intelligence and Machine Learning Health Policy Artificial intelligence Non-dental professionals Barriers Training Outcomes Integration Primary care Full Text Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryFile1Studyriskofbiasassessment.pdf Supplementary File 1_Study risk of bias assessment 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8222032","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":551769941,"identity":"da8410f8-4f68-44f6-9cf9-1a8e6f22693f","order_by":0,"name":"Dr Md Nazmul Huda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYFACHhCygXLYiNeSRrqWwyRo0W3gPSbxpuZ84nb+MwYMH8oOM/DPSMCvxewAX5rknGO3E3fOyDFgnHHuMIPEDYJaeMykedhuJ264wbuBmbcN6ELitPw7l7jh/NkNzH+BWuSJ0sLbdiBxw4HcDcyMQC0GBLUc5jG2nNuXbLzhRv6Hgz3n0nkMzzwgoOV4j+GNN9/sZDecP5b44EeZtZzccQK2MDAjsQ8wgKNpFIyCUTAKRgHFAAAs3EUGLj765gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-7048-1266","institution":"University of New South Wales, Sydney","correspondingAuthor":true,"prefix":"Dr","firstName":"Md","middleName":"Nazmul","lastName":"Huda","suffix":""},{"id":551769942,"identity":"28e24897-dedc-4d26-a86b-8bbb690d83d7","order_by":1,"name":"Dileep Sharma","email":"","orcid":"","institution":"University of Newcastle","correspondingAuthor":false,"prefix":"","firstName":"Dileep","middleName":"","lastName":"Sharma","suffix":""},{"id":551769943,"identity":"7b5fb619-bfd4-46c2-a064-59d1e08210e5","order_by":2,"name":"Sarbin Ranjitkar","email":"","orcid":"","institution":"University of Adelaide","correspondingAuthor":false,"prefix":"","firstName":"Sarbin","middleName":"","lastName":"Ranjitkar","suffix":""},{"id":551769944,"identity":"03674714-d765-48c7-808f-f57b21da6d60","order_by":3,"name":"Leonie M. 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