Exploring Students' Perspectives on Using Al Tools to Improve an Interprofessional Education [IPE] Patient Safety Course Across Health Professions Education Programs

This quantitative cross-sectional study evaluated the integration of artificial intelligence (AI) tools in an Interprofessional Education (IPE) Patient Safety course among clinical-year undergraduate students (Medicine, Nursing, Pharmacy; N = 312) at a health sciences college in Jeddah, Saudi Arabia. Data collected via four validated instruments (SCEQ, Inter-professional Course Evaluation Scale, H-PEPSS, and TAM) demonstrated high baseline AI Acceptance ( M = 4.52 ± 0.72) and perceived Patient Safety Competency ( M = 4.47 ± 0.75). Female students exhibited significantly higher safety competency ( p = 0.021) and AI acceptance ( p = 0.047). Higher academic performance (GPA 4.50–5.0) and older age (≥ 24 years) were significantly associated with greater engagement and competency ( p < 0.001), whereas no significant variance was observed across clinical disciplines. Multiple linear regression revealed that the model explained 76.4% of the variance in patient safety competency ( R2 = 0.764, p < 0.001). AI Acceptance emerged as the strongest independent predictor (β = 0.505, p 0.001), followed by IPE Course Evaluation (β = 0.307, p 0.001) and Student Engagement (β = 0.143, p = 0.002). Strategic AI integration within team-based learning enhances perceived patient safety competencies across health professions. Technological readiness serves as a primary driver of safety competency, reinforcing the necessity for longitudinal AI frameworks in undergraduate medical curricula.