Evaluating artificial intelligence chatbots regarding Saudi patients’ gums disease questions: a qualitative cross-sectional study
Periodontal diseases, including gingivitis and periodontitis, represent a major global oral health burden and are associated with systemic health conditions. With the increasing use of artificial intelligence (AI) chatbots for health information, patients frequently seek oral health advice from digital platforms. However, the reliability and accuracy of AI-generated periodontal health information remain uncertain. This study aimed to evaluate the quality and accuracy of responses generated by AI chatbots to questions regarding periodontal diseases. A qualitative evaluation cross-sectional study assessed the responses of four AI chatbots to ten frequently asked questions about gums diseases. Questions were submitted to the chatbots, and two periodontists evaluated the responses using an referenced-based scoring system focusing on accuracy, completeness, and clinical relevance. Overall, the AI four chatbots generated largely acceptable responses. The chatbots consistently identified plaque accumulation as the primary cause of gingivitis and highlighted common symptoms. However, variations were observed in the depth and structure of responses. All chatbots recommended professional dental consultation for diagnosis and management. The two periodontists agreed in the evaluation of most of the four chatbots’ responses, with a slight variation. AI chatbots demonstrated an overall acceptable level of accuracy in providing information on gingivitis and periodontal diseases. Although these tools may support oral health education and improve patients’ access to information, variability in response completeness highlights the need for cautious use.
Authors
- Nada M Suliman (ORCID: https://orcid.org/0000-0003-1731-8472)
- Elwalid Fadul Nasir (ORCID: https://orcid.org/0000-0001-5909-7423)
Institutions
- King Faisal University (SA)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2026-08-27
- DOI
- https://doi.org/10.1186/s12903-026-09744-y
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00