Comparing Artificial Intelligence–Generated and Clinician-Created Personalized Self-Management Guidance for Patients With Knee Osteoarthritis: Blinded Observational Study
GPT-4 could generate personalized self-management guidance for knee osteoarthritis with greater efficiency, accuracy, personalization, comprehensiveness, and safety than clinician-generated content, as assessed using standardized, guideline-aligned evaluation frameworks. These findings underscore the potential of large language models to support scalable, high-quality patient education in chronic disease management. The observed lexical complexity suggests the need to refine outputs for populations with limited health literacy. As an exploratory, single-center study, these results warrant confirmation in larger, multicenter cohorts with diverse demographic profiles. Future implementation should be guided by ethical and operational safeguards, including data privacy, transparency, and the delineation of clinical responsibility. Hybrid models integrating artificial intelligence-generated content with clinician oversight may offer a pragmatic path forward.
Authors
- Wei-Shuai Du
- Qi Zuo (ORCID: https://orcid.org/0000-0002-8491-4090)
- Chenyu Zhang (ORCID: https://orcid.org/0000-0002-6739-4724)
- Ping Chen (ORCID: https://orcid.org/0000-0003-0295-0846)
- Shu-Ming Li (ORCID: https://orcid.org/0000-0002-7460-1349)
- Ao Li (ORCID: https://orcid.org/0009-0009-7888-0478)
- Ren Guo
- Kai Du (ORCID: https://orcid.org/0009-0004-8375-869X)
Institutions
- Beijing University of Chinese Medicine (CN)
- Beijing Hospital of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-03-31
- DOI
- https://doi.org/10.2196/67830
- Citations
- 10
- Primary Topic
- Osteoarthritis Treatment and Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 16.68