Trust in Artificial Intelligence-Generated Oral Health Information and Its Influence on Patient Decision-Making: A Cross-Sectional Study


Emir B. U., KARA B., Behkar S., Ozcan E.

ORAL HEALTH & PREVENTIVE DENTISTRY, cilt.24, sa.1, ss.759-766, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 1
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3290/j.ohpd.c_2805
  • Dergi Adı: ORAL HEALTH & PREVENTIVE DENTISTRY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals
  • Sayfa Sayıları: ss.759-766
  • Lokman Hekim Üniversitesi Adresli: Hayır

Özet

Purpose: Artificial intelligence (Al)-assisted applications are increasingly used to obtain health-related information; however, concerns remain regarding the reliability of AI-generated responses and their influence on patient attitudes and decision-making. This study aimed to evaluate the use of AI-assisted applications among patients, their trust in AI-generated information, and the influence of these applications on oral-health-related decision-making. Methods and Materials: This cross-sectional questionnaire-based study included 430 patients attending the Department of Periodontology. Participants completed a structured questionnaire evaluating Al-assisted application use, trust in Al-generated oral health information, and the effects of AI on oral-health-related attitudes. Categorical variables were presented as frequencies (n) and percentages (%). Associations between categorical variables were analysed using the chi-square test. Effect sizes were evaluated using Cramer's V coefficient. Statistical significance was set at p < 0.05. Results: A total of 430 participants completed the questionnaire, including 300 AI users. Al usage rates were generally similar across reasons for admission, although the highest usage was observed among individuals attending routine check-ups (18/19; 94.7%). In treatment-related decisions, most participants preferred dentists' opinions over AI-generated recommendations (80.8%; p < 0.01). Trust was significantly associated with Al usage frequency (p < 0.01), whereas education level was significantly associated with Al usage (p < 0.001). Education level was also associated with willingness to consult AI-assisted programmes regarding dentist-created treatment plans (p = 0.033). Conclusion: AI-assisted applications have become an important part of health information-seeking behaviour, particularly among younger and more educated individuals. However, patients remain cautious about the reliability of AI-generated information and continue to prioritise professional dental expertise in treatment-related decisions.