Evaluation of ChatGPT as a Source of Patient-Oriented Information on Gingival Recession

Background: Gingival recession is a common periodontal condition. With the increasing use of artificial intelligence (AI)-based chatbots, patients frequently seek online health information. However, the reliability, accuracy, and readability of AI-generated patient-oriented information on gingival recession remain unclear. Objective: To evaluate the quality, accuracy, and readability of ChatGPT-generated responses to patient-oriented questions related to gingival recession. Methods: A total of 288 patient-oriented questions were developed by an expert panel and categorized into fourteen thematic domains. Responses generated by ChatGPT (version 3.5) were independently evaluated by five oral health professionals using a modified Brief DISCERN instrument, an accuracy scoring system, and the Global Quality Score (GQS). Readability was assessed using the Flesch Reading Ease and Flesch–Kincaid Grade Level indices. Results: Significant differences were observed among thematic categories for DISCERN, accuracy, GQS, and readability scores (all p < 0.01). The highest modified Brief DISCERN, accuracy, and GQS scores were recorded for the Information Sources/AI Reliability category (DISCERN: 19.60 ± 2.29; accuracy: 4.67 ± 0.49; GQS: 4.33 ± 0.49), whereas the lowest scores were observed for the What Happens If Left Untreated? category (DISCERN: 14.27 ± 1.75; accuracy: 3.23 ± 0.43). Strong positive correlations were identified between DISCERN and accuracy (r = 0.784, p < 0.001) and between accuracy and GQS (r = 0.868, p < 0.001). Readability indices were not significantly correlated with accuracy or quality measures. Conclusions: ChatGPT provided patient-oriented information on gingival recession with variable performance across thematic domains; however, readability remained a limitation. AI-generated content should therefore be considered a supplementary resource rather than a substitute for clinician-guided patient communication.