Adoption of generative AI chatbots among medical postgraduates at two universities in China: patterns, attitudes, and concerns

Abstract

Generative artificial intelligence (AI) chatbots are gaining attention in medical education globally for their potential to support academic writing, clinical reasoning, and personalized learning. However, little is known about their adoption, benefits, and concerns among Chinese postgraduate medical students, particularly across distinct clinical- and academic-track programs that characterize China’s unique medical education system. A cross-sectional survey was conducted among 340 postgraduate medical students from two universities in Chengdu, China. A structured questionnaire assessed AI awareness, usage patterns, perceived benefits, attitudes, and concerns. Descriptive statistics, subgroup analyses, and Pearson correlation analyses were applied to examine differences by gender and degree type. Most students (82.9%) reported strong AI awareness, with DeepSeek (90.9%) and ChatGPT (55.2%) most frequently used. Common applications included literature review (61.5%), exam preparation (55.0%), and clinical case analysis (48.5%). Reported benefits encompassed faster information retrieval (70.8%) and improved writing precision (64.3%). Overall satisfaction was high (mean 4.4/5), and 84.0% supported curriculum integration. Female students use AI more frequently but expressed greater concerns, clinical-track students demonstrated higher awareness than academic-track students. Awareness, usage, and attitudes showed positive correlations, while concerns about accuracy and ethics remained independent of prior exposure. This study at two universities in Chengdu demonstrates widespread adoption and favorable perceptions of generative AI chatbots among postgraduate medical students. Findings suggest that structured curricular integration, accompanied by ethical safeguards addressing China-specific challenges, may maximize benefits while mitigating risks. Multi-center studies are needed to validate these regional patterns nationally.

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