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

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.

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.

A cross-sectional study was carried out between August to October 2025 involving 328 undergraduate medical students in King Faisal University, Saudi Arabia. Data were obtained using a validated 44-item instrument measuring students' perceptions, attitudes, and practices toward ChatGPT. Descriptive and inferential statistics were performed using Statistical Package for Social Science (SPSS, Version, 27), with statistical significant set at p < 0.05. Parametric assumptions were tested, and multiple regression analysis was conducted to identify independent predictors.

An exceptional high proportion of students (97.6%) reported prior use of ChatGPT, indicating widespread familiarity with the tool. In terms of usage pattern, the majority (60.1%) indicated frequent use, followed by 26.8% who used it always, 11.3% sometimes, and only 1.08% who had never used it. Overall perception (M = 3.90 ± 0.69), attitude (M = 3.71 ± 0.62), and practice (M = 3.68 ± 0.73) scores reflected generally positive views. A large majority (81.7%) found ChatGPT helpful or extremely helpful in understanding medical concepts, and 73.8% believed it useful for summarizing research articles. Nonetheless, concerns persisted, with 65.2% expressed apprehension about over-reliance on ChatGPT potentially affecting originality and critical thinking. Multiple regression analyses indicated that gender, age, academic year, family status, family income, type of stay, and GPA were significant predictors of perception, attitude, and practice scores (R ² = 0.11-0.15, p < 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.

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.