Factors associated with attitudes towards artificial intelligence among medical students: roles of digital literacy, emotional intelligence, and AI-related perceptions.
BACKGROUND Artificial intelligence is increasingly used in health care and medical education. This study aimed to identify factors associated with medical students' attitudes towards artificial intelligence, with particular attention to digital literacy, emotional intelligence and artificial intelligence-related perceptions. METHODS This cross-sectional study was conducted between November 2025 and January 2026 among 358 medical students. Data were collected using an online questionnaire including sociodemographic items, the Trait Emotional Intelligence Scale-Short Form, the Digital Literacy Scale and the General Attitude Towards Artificial Intelligence Scale. Group comparisons, correlation analyses, hierarchical linear regression and exploratory indirect-effect analysis were performed. RESULTS Most students had previously used artificial intelligence (88.5%), while 59.5% reported ethical or legal concerns and 41.1% believed that artificial intelligence could reduce clinical reasoning. Digital literacy was positively correlated with attitudes towards artificial intelligence (r = 0.319, p < 0.001). In the final hierarchical regression model, digital literacy was the strongest independent factor associated with attitudes towards artificial intelligence (B = 0.242, β = 0.320, p< 0.001). Clinical educational stage, ethical or legal concerns, and perceptions regarding the impact of artificial intelligence on clinical reasoning were also independently associated with attitude scores. Previous artificial intelligence use and emotional intelligence were not independently associated with attitudes after adjustment. CONCLUSIONS Medical students' attitudes towards artificial intelligence were associated more strongly with digital literacy and artificial intelligence-related perceptions than with previous use alone. Undergraduate medical education should integrate digital literacy, ethical awareness and reflective discussion on clinical reasoning into artificial intelligence-related teaching.