Objective To investigate the views, usage patterns, and attitudes towards potential impact of resident physicians toward artificial intelligence (AI) tools. Methods This study used a questionnaire survey method to investigate 168 residents′ perception and attitudes towards AI in the 2024 residency training program at the First Affiliated Hospital of Sun Yat-sen University, and the survey results were analyzed through descriptive statistics and χ2 test. Results Totally 109 (64.9%) residents expressed willingness to use AI for learning and exam preparation, 70 (41.7%) residents believed that ChatGPT could effectively meet their needs, while 112 (66.7%) believed that AI-generated answers still required further validation. Regarding ethical issues and the development of policies for AI use in medical education, 93(55.4%) residents supported the establishment of relevant guidelines. Additionally, 96(57.1%) residents believed that AI would have a profound impact on their careers in terms of improving patient care quality. Among the 168 residents, there were 74 males and 94 females. Gender difference analysis showed that male respondents were more likely than female respondents to use AI to explore new medical topics or conduct research [37(50.0%) vs. 25(26.6%)] and were more inclined to use AI to assist in writing academic papers [44(59.5%) vs. 37(39.4%)], both P<0.05. Conclusions Medical residents show a positive outlook on AI′s potential to enhance medical education and patient care, though there are concerns regarding its accuracy, ethical implications, and the need for formal guidelines. Gender differences may influence residents′ views on the promotion and application of AI technologies in the medical field. Future research should address these concerns and explore how AI can be effectively integrated into residency training.
Ba Hongjun
,
Chen Jiarui
,
Hu Han
,
Jiang Xiaoyun
,
Li Shujuan
. Survey on residents′ perception and attitudes towards the application of artificial intelligence[J]. Chinese Journal of Medical Education, 2025
, 45(3)
: 194
-197
.
DOI: 10.3760/cma.j.cn115259-20241126-01215
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