Subramanian, C. R., Yang, D. A. & Khanna, R. Enhancing health care communication with large Language models—the role, challenges, and future directions. JAMA Netw. Open. 7e240347 (2024).
Google Scholar
Rahman, A. et al. Comparative analysis based on DeepSeek, ChatGPT, and Google Gemini: Features, techniques, performance, future prospects. Preprint at (2025).
Aggarwal, A., Tam, C. C., Wu, D., Li, X. & Qiao, S. Artificial intelligence–based chatbots for promoting health behavioral changes: systematic review. J. Med. Internet Res. 25e40789 (2023).
Google Scholar
Younis, H. A. et al. A systematic review and meta-analysis of artificial intelligence tools in medicine and healthcare: applications, considerations, limitations, motivation and challenges. Diagnostics 14109 (2024).
Google Scholar
Weyant, R. J. et al. Topical fluoride for caries prevention: executive summary of the updated clinical recommendations and supporting systematic review. J. Am. Dent. Assoc. 1441279–1291 (2013).
Google Scholar
Samaranayake, L., Porntaveetus, T., Tsoi, J. & Tuygunov, N. Facts and fallacies of the fluoride controversy: a contemporary perspective. Int. Dent. J. 75100833 (2025).
Google Scholar
American Academy of Pediatric Dentistry. American academy of pediatric dentistry fluoride therapy. The Reference Manual of Pediatric Dentistry (American Academy of Pediatric Dentistry, 2020).
American Academy of Pediatric Dentistry. American Academy of Pediatric Dentistry Reference Manual (American Academy of Pediatric Dentistry, 2008).
Singh, B. et al. Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours. NPJ Digit. With. 6118 (2023).
Google Scholar
Moult, B., Franck, L. S. & Brady, H. Ensuring quality information for patients: development and preliminary validation of a new instrument to improve the quality of written health care information. Health Expect. 7165–175 (2004).
Google Scholar
Li, H., Zhang, R., Lee, Y. C., Kraut, R. E. & Mohr, D. C. Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being. NPJ Digit. With. 6236 (2023).
Google Scholar
American Academy on Pediatric Dentistry Liaison with Other Groups Committee, & American Academy on Pediatric Dentistry Council on Clinical Affairs. Policy on use of fluoride. Pediatr. Dent. 3034–35 (2008).
Google Scholar
Esmaeilzadeh, F., Movahhed, T., Hasani Yaghooti, M. R., Hoseinzadeh, M. & Babazadeh, S. Content analysis of fluoride-related posts on instagram: prevalence of misinformation. BMC Oral Health. 241179 (2024).
Google Scholar
American Dental Association. Community Water Fluoridation at Optimal Levels is Safe and Effective (Press Release). (2024).
Keleş, Z. H. Is fluoride opposition a marketing tool on social media? Int. Dent. J. 7493 (2024).
Google Scholar
Charnock, D., Shepperd, S., Needham, G. & Gann, R. DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. J. Epidemiol. Community Health. 53105–111 (1999).
Google Scholar
Yeung, A. W. K. Evaluation of content quality of online health information by global quality score: A case study of researchers misnaming it and citing secondary sources. Publications 1323 (2025).
Google Scholar
Laymouna, M. et al. Roles, users, benefits, and limitations of chatbots in health care: rapid review. J. Med. Internet Res. 26e56930 (2024).
Google Scholar
Jindal, P. & MacDermid, J. C. Assessing reading levels of health information: uses and limitations of Flesch formula. Educ. Health. 3084–88 (2017).
Google Scholar
Jin, E., Ryoo, Y., Kim, W. J. & Song, Y. G. Bridging the health literacy gap through AI chatbot design: the impact of gender and Doctor cues on chatbot trust and acceptance. Internet Res. 341299–1329 (2025).
Google Scholar
Diviani, N., van den Putte, B., Giani, S. & van Weert, J. C. Low health literacy and evaluation of online health information: a systematic review of the literature. J. Med. Internet Res. 17e112 (2015).
Google Scholar
Hindelang, M., Sitaru, S. & Zink, A. Transforming health care through chatbots for medical history-taking and future directions: comprehensive systematic review. JMIR Med. Inf. 12e56628 (2024).
Google Scholar
Bhattacharya, B. S. & Pissurlenkar, V. S. Assistive chatbots for healthcare: a succinct review. Preprint at (2023).
Buldur, M. & Sezer, B. Evaluating the accuracy of chat generative pre-trained transformer version 4 (ChatGPT-4) responses to united States food and drug administration (FDA) frequently asked questions about dental amalgam. BMC Oral Health. 24605 (2024).
Google Scholar
Gugnani, N., Pandit, I. K., Gupta, M., Gugnani, S. & Kathuria, S. Parental concerns about oral health of children: is ChatGPT helpful in finding appropriate answers? J. Indian Soc. Pedod. Prev. Dent. 42104–111 (2024).
Google Scholar
Pupong, K., Hunsrisakhun, J., Pithpornchaiyakul, S. & Naorungroj, S. Development of chatbot-based oral health care for young children and evaluation of its effectiveness, usability, and acceptability: mixed methods study. JMIR Pediatr. Parent. 5e62738 (2025).
Google Scholar
Or, A. et al. Enhancing dental students’ history-taking skills with a generative artificial intelligence chatbot. J. Dent. Educ. 1e13952 (2025).
Google Scholar
Maruska, E. E. et al. Comparing dentist and chatbot answers to dental questions for quality and empathy. JADA Found. Sci. 4100044 (2025).
Google Scholar
Collaborative, T. C. Reporting guideline for chatbot health advice studies: the chatbot assessment reporting tool (CHART) statement. BMJ Med. 4e001632 (2025).
Google Scholar
Zhou, Y., Oniani, D., Sreekumar, S., DeAlmeida, R. & Wang, Y. Toward improving health literacy in patient education materials with neural machine translation models. Preprint at (2022).
