GenAI use duration, anxiety, depressive symptoms, and sleep-onset difficulty among medical students in Shanxi, China: a cross-sectional survey

The widespread popularity of generative artificial intelligence (GenAI) has changed the learning and lifestyle of medical students, while its association with mental health status and sleep problems among medical students remains insufficiently. This study aimed to analyze the correlation between GenAI usage, anxiety, depressive symptoms, and sleep-onset difficulty. A cross-sectional survey design was adopted in this study. Participants were medical students recruited from four medical universities in Shanxi, China, and data were collected via an online questionnaire. The usage duration of GenAI, anxiety and depressive symptoms, and sleep-onset difficulty were self-reported. Multiple logistic regression and linear regression analysis were performed to explore the association between GenAI use, anxiety, depressive symptoms, and sleep-onset difficulty. A total of 1,882 valid questionnaires were collected from medical students. After adjusting for all covariates, high-duration GenAI use was associated with increased odds of anxiety symptoms (OR = 2.02, 95%CI:1.48–2.77, P for trend < 0.001), high-duration GenAI use exhibited higher odds of sleep-onset difficulty based on the PSQI sleep latency component (OR = 1.67, 95%CI:1.26–2.24, P for trend < 0.001), compared to low/non-users. High-duration GenAI use was associated with elevated depressive scores (β = 0.66, 95%CI: 0.15–1.17, P for trend < 0.01) but not depressive symptoms. GenAI is widely used among medical students in Shanxi, China, and high-duration of GenAI is associated with anxiety symptoms and sleep-onset difficulty. Future research should deploy longitudinal design to clarify the long-term associations between GenAI use duration, mental health, and sleep problems.