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This study investigated the incidence of stressors and psychological resilience among medical students within the framework of AI-assisted (artificial intelligence-assisted) learning, with the objective of informing evidence-based treatments for the enhancement of resilience. A cross-sectional study utilizing random sampling was performed among 994 medical students from three medical colleges in East China in 2025.The data were analyzed utilizing SPSS version 27.0.The findings indicated that the psychological resilience ratings of medical students were markedly inferior to the national youth average. Resilience had a positive correlation with the utilization of AI applications and a negative correlation with various stressors, demonstrating differing magnitudes and directions of influence. The academic year, academic ranking, family income, only-child status, and gender significantly influenced the outcomes. Path analysis indicated that stress perception partially moderated the association between AI-assisted learning and resilience. These findings offer new empirical data regarding the pathways connecting AI-assisted learning experiences to psychological resilience and underscore the varying impacts of different stressors and individual backgrounds. The study provides practical insights for creating stress-categorization management systems and enhancing intelligent technology applications to promote mental health in medical education.
Xu et al. (Mon,) studied this question.
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