BMC Oral Health. 2025 May 7;25(1):689. doi: 10.1186/s12903-025-06069-0.
ABSTRACT
BACKGROUND: Effective patient education is critical in enhancing treatment outcomes and reducing anxiety in dental procedures. This study compares the effectiveness of AI-generated educational materials with traditional methods in improving patient comprehension and reducing anxiety during endodontic and restorative dental treatments.
METHODS: A cross-sectional, comparative study was conducted with 100 participants undergoing restorative or endodontic procedures. Patients were randomized into two groups: those receiving AI-generated instructional materials (via ChatGPT) and those receiving traditional education (verbal explanations and pamphlets). Baseline knowledge and post-intervention knowledge retention were assessed using structured tests. Patient perceptions of clarity, usefulness, comprehensiveness, trust, and anxiety were measured using Likert-scale surveys. Three dental experts evaluated the educational content for accuracy and suitability. Statistical analysis included t-tests and Cohen’s kappa to measure inter-rater reliability.
RESULTS: AI-generated materials significantly outperformed traditional methods in all measured dimensions, including clarity (4.42 vs. 3.25), usefulness (4.63 vs. 3.50), comprehensiveness (4.50 vs. 3.29), trust (4.00 vs. 2.96), and anxiety reduction (mean anxiety score: 2.63 vs. 3.38, p < 0.001). Pre- and post-intervention knowledge assessments revealed substantial knowledge improvement in the AI group. Expert evaluations confirmed the accuracy and suitability of AI-generated materials, with high inter-rater reliability (κ = 0.75, p < 0.001).
CONCLUSIONS: AI-generated educational materials demonstrate superior effectiveness in improving patient comprehension and reducing anxiety compared to traditional methods. Their integration into dental practice could enhance patient satisfaction and streamline the educational process, particularly for complex or anxiety-inducing procedures. Future research should explore their application in diverse dental specialties and assess long-term impacts on patient behavior and clinical outcomes.
PMID:40335999 | DOI:10.1186/s12903-025-06069-0
