aceReliability, quality, and readability of large language models in carpal tunnel syndrome: A comparative cross-linguistic, cross-sectional observational study
BackgroundAI-based chatbots are increasingly used for health information, while cross-linguistic studies suggest that response performance may vary by language. Given the high prevalence of carpal tunnel syndrome (CTS), this study evaluated the reliability, quality, patient education suitability, and readability of AI-generated responses to CTS questions in English and Turkish.Materials and methodsSeventeen patient-centered CTS questions were directed to ChatGPT ® (GPT-5 Mini), Gemini ® 3 Flash, and Claude ® 4.5…
None of the three tested chatbots produced carpal tunnel syndrome answers at recommended readability levels in English or Turkish, and quality varied by model and language.
The mDISCERN instrument partly reflects whether references are provided and does not directly assess factual clinical accuracy, so score differences between models should be interpreted cautiously.
Evidence
- Peer-reviewedJournal of Back and Musculoskeletal Rehabilitation2026-10-08
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Truvace Impact Record TRV-2026-1730, v1: “Reliability, quality, and readability of large language models in carpal tunnel syndrome: A comparative cross-linguistic, cross-sectional observational study.” Truvace, 2026-10-17. /record/TRV-2026-1730 (accessed at citation time). sha256 1ffb5329939cf5f9…
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