Artificial intelligence ethical awareness and academic integrity among medical students at the University of Khartoum: a cross-sectional study

Abstract

Integration of artificial intelligence in healthcare and medical education implies significant opportunities along with significant ethical challenges. Despite the substantial medical student uptake of artificial intelligence globally, little comprehensive assessments of ethical awareness are being conducted. This study aimed to assess artificial intelligence awareness and academic integrity level among University of Khartoum medical students and to examine relationships between the awareness level, demographic factors, artificial intelligence exposure, and tool use behavior. An institutional cross-sectional descriptive study of Years 3–6 medical students at University of Khartoum Faculty of Medicine in 2025 was conducted. A convenience sampling with quota allocation was used, and 349 students responded. The instrument included demographic variables, artificial intelligence exposure measures, and the 32-item Artificial Intelligence Ethical Awareness and Academic Integrity Scale. Nonparametric tests were applied. Participants were predominantly female (69.3%) with a mean age of 22.85 years. The median total Artificial Intelligence Ethical Awareness and Academic Integrity score was 4.16, indicative of moderate ethical awareness based on sample-derived empirical tertiles. Privacy and Data Protection were highest (median 4.67), with lowest scores in Transparency and Fairness/Non-Discrimination (3.80). Female students were more aware ( P = .01). No year-based differences observed. While 63.9% had minimal formal artificial intelligence exposure, 51.6% had moderate to high informal exposure. ChatGPT usage was prevalent (94.6%), and Google Gemini/Notebook LM usage was strongly associated with higher awareness ( P = .003). Informal exposure was positively correlated with awareness ( P = .01), but formal exposure was not. Multiple regression indicated that gender, informal exposure, and tool accounted for 11.2% of the variance in awareness. University of Khartoum medical students showed moderate-to-high aggregate artificial intelligence, ethical sensitivity, with areas of privacy protection and accountability being of particular strength. Gaps exist for awareness of transparency and fairness. The dominance of informal learning pathways over formal instruction, and gender variability favoring female students are significant findings. Findings highlight the need for institutional policies and conducting longitudinal research to track the evolution of AI ethics throughout medical training.

The authors' abstract, as published at the source. BMC Medical Education, 2026 · DOI ↗