Web-Based AI-Driven Virtual Patient Simulator Versus Actor-Based Simulation for Teaching Consultation Skills: Multicenter Randomized Crossover Study
Background: There is a need to increase healthcare professional training capacity to meet global needs by 2030. Effective communication is essential for delivering safe and effective patient care. artificial intelligence (#AI) (AI) technologies may provide a solution. However, evidence for high-fidelity virtual patient simulators using unrestricted two-way verbal conversation for communication skills training is lacking. Objective: To compare a fully automated AI-driven voice recognition-based Virtual Patient Simulator with traditional actor-based consultation skills simulated training in undergraduate medical students for differences in developing self-rated communication skills, student satisfaction scores and direct cost-comparison. Methods: Using an open-label randomised crossover design, a single web-based AI-driven communication skills training session (AI-CST) was compared with a single face-to-face actor-based consultation skills training session (AB-CST) in undergraduates at two UK medical schools. Offline total cohort recruitment was used, with an opt-out option. Pre-post intervention surveys using 10-point linear scales were used to derive outcomes. The primary outcome was the difference in self-reported attainment of communication skills between interventions. Secondary outcomes were differences in student satisfaction and cost-comparison of delivering both interventions. Results: Of 396 students, 378 (95%) completed at least one survey. Both modalities significantly increased self-reported communication skills attainment (AI-CST: mean 1.14 points (95%CI 0.53-0.175); AB-CST: mean 1.50 points (95%CI 0.9-2.10); both P
