Shaping the future of medical education: A cross-sectional study on ChatGPT attitude and usage among medical students in Sudan - Weam Mohamed Meargni Ahmed; Malaz M. Abdalmotalib; Mohamed H. Elbadawi; Galia Tajelsir Fadulelmula Mohammed; Waad Mohamed Ibrahim Mohamed; Fatima Salih Babiker Mohammed; Hajar Saad Salih; Hiba Omer Yousif Mohamed (PLoS ONE, 2025)
Background Artificial intelligence (AI) is revolutionizing education globally, yet its adoption in medical education remains inadequately understood. ChatGPT, a generative AI tool, offers promising yet doubtful potential for enhancing academic and clinical training. Methods This study employed an analytical cross-sectional design, involving 1,443 Sudanese medical students who participated through an online, structured questionnaire. The questionnaire was designed to assess ChatGPT awareness, usage, and associated factors. Statistical analysis was performed using SPSS software to identify key determinants influencing ChatGPT awareness and usage among the participants. Objective This study investigates the levels of awareness, attitude, and usage of ChatGPT among Sudanese medical students, identifying key socio-demographic, economic, and institutional factors influencing its adoption. Results Among the participants, 65.8% were aware of ChatGPT, yet only 41.9% reported using it. Gender differences were statistically significant, with males demonstrating higher usage rates (p < 0.001). Single and unemployed students were more likely to use ChatGPT compared to their counterparts. Students residing in private accommodations and those with higher family incomes (>300,000 SDGs) showed significantly greater usage (p < 0.001). Factors such as residency type, internet quality, and institutional orientation were identified as key influences on ChatGPT adoption, highlighting a substantial digital influence. Additionally, inadequate infrastructure and reliance on traditional curricula were significant barriers to wider usage. Conclusions The findings underscore the urgent need for targeted interventions, including curriculum reform to integrate AI literacy, enhanced digital infrastructure, and gender-equity initiatives. Addressing these systemic gaps will scale up AI adoption in medical education. This study provides actionable insights for educators and policymakers, emphasizing the urgency of bridging socio-economic and institutional inequities to foster equitable access to AI tools in medical training.