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

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Dinc D., Kocaaydın S., Ilisulu S. C.

BMC ORAL HEALTH, cilt.26, ss.1-10, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1186/s12903-026-08502-4
  • Dergi Adı: BMC ORAL HEALTH
  • Derginin Tarandığı İndeksler: Natural Science Collection (ProQuest), Biological Science Database (ProQuest), Biomedical Reference Collection: Corporate Edition (EBSCO), Health Research Premium Collection (ProQuest), Scopus, Science Citation Index Expanded (SCI-EXPANDED), CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1-10
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • İstanbul Kent Üniversitesi Adresli: Evet

Özet

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.

Keywords Accuracy, Artificial intelligence, Chatbots, Fluoride, Pediatric dentistry