ChatGPT in medical education: a cross-sectional analysis of usage, attitudes, perceptions, and practices among Saudi medical students

Background: Generative artificial intelligence (AI) platforms such as ChatGPT are rapidly reshaping higher education, particularly in medical learning environments. Although several researches have examined students' perceptions and attitudes toward ChatGPT in Saudi Arabia, context-specific evidence focusing on medical students and their practical engagement with ChatGPT remained limited. Objectives: This study aimed to describe patterns of ChatGPT usage, students' perceptions, attitudes, and practices among medical students and to explore their associations with demographic and academic characteristics. Methods: < 0.05. Parametric assumptions were tested, and multiple regression analysis was conducted to identify independent predictors. Results: < 0.05), with academic year, age, GPA, and gender being the most consistent predictors. Younger students (<21 years), early-year students, those with higher GPAs (>4.5), and students from higher-income families exhibited more favorable responses. Conclusion: The findings highlight strong awareness, frequent use, and positive perception toward ChatGPT among medical students at King Faisal University, viewed as an accessible and effective academic aid. Nevertheless, apprehension remain regarding reliability, ethical use, and risk of overdependence. Institutional frameworks incorporating AI literacy, critical appraisal training, and ethical guidelines are essential to ensure effective integration of ChatGPT in medical education.