ORIGINAL RESEARCH article
Front. Pediatr.
Sec. Pediatric Pulmonology
Volume 13 - 2025 | doi: 10.3389/fped.2025.1519751
Enhancing Pediatric Asthma Management in Underdeveloped Regions through ChatGPT Training for Doctors: A Randomized Controlled Trial
Provisionally accepted
Liwen Zhang1
Guijun Yang1
Jiajun Yuan2Shuahua Yuan1
Jing Zhang1
Jiande Chen1
Mingyu Tang1
Jilei Lin1Yunqin Zhang3Liebin Zhao4,5
Yin Yong1,4,5*- 1Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- 2Medical Department of Shanghai Children's Medical Center，Shanghai Jiao Tong University School of Medicine, Shanghai, China
- 3Department of Respiratory Medicine, Linyi Maternal and Child Healthcare Hospital, Linyi Branch of Shanghai Children's Medical Center, Linyi City, Shandong Province, China
- 4Pediatric AI clinical application and research center, Shanghai Children’s Medical Center, Shanghai, China
- 5Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
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Background: Childhood asthma represents a significant challenge globally, especially in underdeveloped regions. Recent advancements in Large Language Models (LLMs), such as ChatGPT, offer promising improvements in medical service quality.This randomized controlled trial assessed the effectiveness of ChatGPT in enhancing physicians' childhood asthma management skills. A total of 192 doctors from varied healthcare environments in China were divided into a control group, receiving traditional medical literature training, and an intervention group, trained in utilizing ChatGPT. Assessments conducted before and after training, and a two-week follow-up, measured the training's impact.The intervention group showed significant improvement, with scores of test questions increasing by approximately 20 out of 100 (improving to 72 ± 8 from a baseline, versus the control group's increase to 50 ± 9). Post-training, ChatGPT's regular usage among the intervention group jumped from 6.3% to 62%, markedly above the control group's 4.3%. Moreover, physicians in the intervention group reported higher levels of familiarity, effectiveness, satisfaction, and intention for future use of ChatGPT. ChatGPT training significantly improves childhood asthma management among physicians in underdeveloped regions. This underscores the utility of LLMs like ChatGPT as effective educational tools in medical training, highlighting the need for further research into their integration and patient outcome impacts.
Keywords: ChatGPT1, pediatric2, Asthma Management3, Large Language Models4, Randomized Controlled Trial5
Received: 30 Oct 2024; Accepted: 23 Jun 2025.
Copyright: © 2025 Zhang, Yang, Yuan, Yuan, Zhang, Chen, Tang, Lin, Zhang, Zhao and Yong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yin Yong, Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.