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Assessing ChatGPT’s Competency in Addressing Interdisciplinary Inquiries on Chatbot Uses in Sports Rehabilitation: Simulation Study

Authors :
Joseph C McBee
Daniel Y Han
Li Liu
Leah Ma
Donald A Adjeroh
Dong Xu
Gangqing Hu
Source :
JMIR Medical Education, Vol 10, p e51157 (2024)
Publication Year :
2024
Publisher :
JMIR Publications, 2024.

Abstract

BackgroundChatGPT showcases exceptional conversational capabilities and extensive cross-disciplinary knowledge. In addition, it can perform multiple roles in a single chat session. This unique multirole-playing feature positions ChatGPT as a promising tool for exploring interdisciplinary subjects. ObjectiveThe aim of this study was to evaluate ChatGPT’s competency in addressing interdisciplinary inquiries based on a case study exploring the opportunities and challenges of chatbot uses in sports rehabilitation. MethodsWe developed a model termed PanelGPT to assess ChatGPT’s competency in addressing interdisciplinary topics through simulated panel discussions. Taking chatbot uses in sports rehabilitation as an example of an interdisciplinary topic, we prompted ChatGPT through PanelGPT to role-play a physiotherapist, psychologist, nutritionist, artificial intelligence expert, and athlete in a simulated panel discussion. During the simulation, we posed questions to the panel while ChatGPT acted as both the panelists for responses and the moderator for steering the discussion. We performed the simulation using ChatGPT-4 and evaluated the responses by referring to the literature and our human expertise. ResultsBy tackling questions related to chatbot uses in sports rehabilitation with respect to patient education, physiotherapy, physiology, nutrition, and ethical considerations, responses from the ChatGPT-simulated panel discussion reasonably pointed to various benefits such as 24/7 support, personalized advice, automated tracking, and reminders. ChatGPT also correctly emphasized the importance of patient education, and identified challenges such as limited interaction modes, inaccuracies in emotion-related advice, assurance of data privacy and security, transparency in data handling, and fairness in model training. It also stressed that chatbots are to assist as a copilot, not to replace human health care professionals in the rehabilitation process. ConclusionsChatGPT exhibits strong competency in addressing interdisciplinary inquiry by simulating multiple experts from complementary backgrounds, with significant implications in assisting medical education.

Details

Language :
English
ISSN :
23693762
Volume :
10
Database :
Directory of Open Access Journals
Journal :
JMIR Medical Education
Publication Type :
Academic Journal
Accession number :
edsdoj.75ab61bebe3f4daeb0996d1d8c578cf3
Document Type :
article
Full Text :
https://doi.org/10.2196/51157