Are chatbots reliable sources of information regarding fluoride in pediatric dentistry?

Abstract

Aim To evaluate the accuracy and consistency of responses generated by artificial intelligence (AI) chatbots in pediatric dentistry, specifically concerning fluoride usage. Study design Descriptive cross-sectional study. Methods Four AI chatbots (ChatGPT, Gemini, Claude, Copilot) and four groups of dental professionals (pediatric dentists, general dentists, pediatric dentistry PhD students, and fifth-year dental students) answered 23 true–false questions based on IAPD, AAPD and EAPD guidelines. Each chatbot was tested 28 times per question in separate sessions. Accuracy was analyzed across four categories: Individual Topical Fluoride Applications, Professional Topical Fluoride Applications, Systemic Fluoride Applications, and Fluorosis. All groups were statistically compared with each other to evaluate differences in response accuracy across AI chatbots and human participant categories. Results Significant differences were observed in the accuracy of chatbot responses across fluoride application categories (p < 0.05). Claude achieved perfect accuracy in Systemic Fluoride Applications (100%), while the other AI models performed lower—with ChatGPT scoring the lowest (94.3%)—and Gemini showed the highest accuracy in Fluorosis-related questions (76.8%). Among professionals, pediatric dentists (82.3%) consistently had the highest accuracy. Statistics Chi-square and Fisher’s Exact tests were used to assess differences in response accuracy between groups. A p-value < 0.05 was considered statistically significant. Conclusions Claude and Gemini demonstrated greater reliability in fluoride-related questions than ChatGPT and Copilot. However, expert oversight remains crucial in pediatric dental care.