Enhancing pediatric asthma management in underdeveloped regions through ChatGPT training for doctors: a randomized controlled trial Article Swipe
Liwen Zhang
,
Guijun Yang
,
J. M. Yuan
,
Shuhua Yuan
,
Jing Zhang
,
Jiande Chen
,
Mingyu Tang
,
Yunqin Zhang
,
Jilei Lin
,
Liebin Zhao
,
Yong Yin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/fped.2025.1519751
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/fped.2025.1519751
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. Methods 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 2-week follow-up, measured the training's impact. Results 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, vs. 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. Conclusion 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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fped.2025.1519751
- https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2025.1519751/pdf
- OA Status
- gold
- Cited By
- 1
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411970658
All OpenAlex metadata
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https://openalex.org/W4411970658Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fped.2025.1519751Digital Object Identifier
- Title
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Enhancing pediatric asthma management in underdeveloped regions through ChatGPT training for doctors: a randomized controlled trialWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-03Full publication date if available
- Authors
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Liwen Zhang, Guijun Yang, J. M. Yuan, Shuhua Yuan, Jing Zhang, Jiande Chen, Mingyu Tang, Yunqin Zhang, Jilei Lin, Liebin Zhao, Yong YinList of authors in order
- Landing page
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https://doi.org/10.3389/fped.2025.1519751Publisher landing page
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https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2025.1519751/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2025.1519751/pdfDirect OA link when available
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Medicine, Randomized controlled trial, Intervention (counseling), Asthma, Physical therapy, Family medicine, Training (meteorology), Nursing, Surgery, Internal medicine, Meteorology, PhysicsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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