Quality of AI-generated temporomandibular disorder information: A comparative analysis based on Turkish patient queries

Abstract

ObjectiveThis study aims to evaluate the accuracy and quality of responses generated by large language model-based chatbots to frequently asked questions related to temporomandibular disorders (TMD).MethodsTen questions were selected based on the most common inquiries made by patients with TMD to artificial intelligence (AI) chatbots. The responses of four widely used AI chatbots (ChatGPT Pro, ChatGPT 3.5, Deepseek, Grok3.0) were collected. Three expert evaluators assessed each chatbot\"s response using a modified Global Quality Scale (GQS).ResultsA statistically significant difference was observed among the four AI chatbots (p = 0.0097; eta & sup2; = 0.09). ChatGPT Pro and Grok achieved significantly higher GQS scores than DeepSeek (p = 0.037*).ConclusionWhile some AI chatbots show potential in answering TMD-related patient questions, variability in accuracy and reliability currently limits their use in clinical settings. Further training and validation are needed before integration into patient education or clinical decision-support systems.