An empirical study on resident physicians'perceptions of artificial intelligence

Du Junjie; Shao Yongfeng; Jiang Yefan; Luo Yu; Ge Minjing; Chen Liling; Huang Hua; Ding Qiang

doi:10.3969/j.issn.2096-4293.2026.03.008

Abstract：Objective To evaluate the impact of artificial intelligence(AI)technology on clinical education from the perspective of resident physicians,analyze perceptual differences across specialties,and propose optimization pathways for educational strategies.Methods A cross-sectional study was conducted using a questionnaire survey administered to 378 resident physicians at Jiangsu Provincial People's Hospital.Attitudes toward AI's role in enhancing clinical reasoning,practical skills,and research capabilities were assessed via a 5-point Likert scale.K-modes cluster analysis was employed to identify key subgroups.Results A total of 317 valid questionnaires were collected(response rate:83.86%).85.80%of respondents acknowledged the overall positive impact of AI on clinical education.Yet skepticism was expressed about its role in cultivating core competencies:only 48.90%supported its enhancement for clinical reasoning,and 41.96%recognized its improvement for procedural skills.98.11%of residents advocated enhanced AI training,but 66.88%criticized current curricula as insufficient.Significant heterogeneity in AI perceptions was observed across departments:the department of auxillary diagnosis exhibited the highest optimism(76.92%),while emergency medicine department showed notable resistance(9.38%).Conclusion AI reshapes clinical education through efficiency gains,yet its empowerment of core competencies remains contentious,with divergent specialty-specific demands.Future residency training systems should establish a dual-track"technology-humanities"framework,design hierarchical curricula tailored to specialty characteristics,and strengthen human-machine collaborative training to balance efficiency optimization and competency development.