Evaluating AI Chatbots for Pediatric Contact Lenses: A Study on Accuracy, Readability, and Reliability
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This study evaluated the accuracy, readability, and comprehensiveness of patient-facing responses generated by LLM-based chatbot platforms to pediatric contact lens (CL)–related questions, using expert grading and readability benchmarking. Five platforms (ChatGPT-4o, Gemini 1.5, Perplexity, Copilot, and Claude 3.5 Sonnet) were assessed using 28 curated questions. Two pediatric ophthalmologists graded anonymized outputs using DISCERN and PEMAT-P, 5-point Likert scales for accuracy and comprehensiveness, and multiple automated readability indices. Expert-written responses were included only for readability benchmarking. ChatGPT-4o produced the longest responses (p
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Ophthalmology and Visual Health Research
Health Literacy and Information Accessibility
Publication details
- Journal / source
- Uludağ Üniversitesi Tıp Fakültesi Dergisi
- Volume
- 52
- Pages
- 1780297–1780297
- Publication date
- 16 March 2026
- Language
- EN