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Evaluating the application of ChatGPT in China’s residency training education

An exploratory study

Bibliographic Data

ID21447660
AuthorsLuxiang Shang (Department of Cardiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital), Rui Li (0000-0001-9744-7965, Shandong Provincial Center for Disease Control and Prevention), Mingyue Xue (0000-0001-9582-0930, Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital), Qilong Guo (0000-0003-3357-5970, Department of Cardiology, The Affiliated Hospital of Qingdao University (Pingdu)), Yinglong Hou (0000-0001-5495-6233, Department of Cardiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, corresponding author)
Year2025
Volume47
Issue5
Pages858-864
Publication date2025-05-04
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Teacher (JOURNAL)
Journal identifiersISSN: 0142-159X • E-ISSN: 1466-187X
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0142159x.2024.2377808
PMID38994848
OpenAlexW4400586618
LanguageEN
Citations received1
References cited37

OBJECTIVE: The purpose of this study was to assess the utility of information generated by ChatGPT for residency education in China. METHODS: We designed a three-step survey to evaluate the performance of ChatGPT in China's residency training education including residency final examination questions, patient cases, and resident satisfaction scores. First, 204 questions from the residency final exam were input into ChatGPT's interface to obtain the percentage of correct answers. Next, ChatGPT was asked to generate 20 clinical cases, which were subsequently evaluated by three instructors using a pre-designed Likert scale with 5 points. The quality of the cases was assessed based on criteria including clarity, relevance, logicality, credibility, and comprehensiveness. Finally, interaction sessions between 31 third-year residents and ChatGPT were conducted. Residents' perceptions of ChatGPT's feedback were assessed using a Likert scale, focusing on aspects such as ease of use, accuracy and completeness of responses, and its effectiveness in enhancing understanding of medical knowledge. RESULTS: Our results showed ChatGPT-3.5 correctly answered 45.1% of exam questions. In the virtual patient cases, ChatGPT received mean ratings of 4.57 ± 0.50, 4.68 ± 0.47, 4.77 ± 0.46, 4.60 ± 0.53, and 3.95 ± 0.59 points for clarity, relevance, logicality, credibility, and comprehensiveness from clinical instructors, respectively. Among training residents, ChatGPT scored 4.48 ± 0.70, 4.00 ± 0.82 and 4.61 ± 0.50 points for ease of use, accuracy and completeness, and usefulness, respectively. CONCLUSION: Our findings demonstrate ChatGPT's immense potential for personalized Chinese medical education

China · Continuing education · Exploratory research · Medical education · Political science · Residency training · Sociology · Artificial Intelligence in Healthcare and Education · Digital Mental Health Interventions · Medicine · Misinformation and Its Impacts · Psychology

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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