GPT-4 outperforms junior expert physical therapists in sports medicine rehabilitation: an evaluation of AI response quality and adaptiveness

Artikel i vetenskaplig tidskrift, 2026

Background: Artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT, has demonstrated potential in healthcare applications, but its effectiveness in clinical rehabilitation contexts remains underexplored. This study investigated whether GPT-4 (accessed through its online interface ChatGPT) can deliver high-quality, adaptive responses in sports physical therapy comparable to or surpassing those of human professionals. Methods: Fifty-three sports physical therapy questions were developed by senior experts and answered by GPT-4 and three junior expert physical therapists (JEPs). Responses were tailored for different target audiences: patients, physical therapists, and expert physical therapists. GPT-4 was prompted using structured engineering techniques. A blinded panel of three senior physical therapists/researchers assessed responses for quality and adaptiveness, and identified which responses were superior. Results: Across all target audiences, GPT-4 outperformed JEPs in both quality and adaptiveness of responses (p < 0.001). For responses aimed at patients, GPT-4 was rated best in 26 (55%) questions. For responses aimed at physical therapists, GPT-4 was rated best in 34 (64%) questions. Performance varied by topic, but GPT-4 consistently provided more expert-adapted and contextually appropriate information. GPT-4's responses were especially superior in areas like pain, osteoarthritis, and anterior cruciate ligament rehabilitation. Conclusion: This study demonstrated that GPT-4 is capable to generate high-quality, adaptive responses in the field of orthopedic sports physical therapy, which can surpass the performance of JEPs in a controlled setting.