JMIR Publications

ABSTRACT

Background:

Effective pain and opioid management education remains a persistent challenge in health professions training. Static case studies and lecture-based instruction are widely used but may be insufficient to develop the clinical reasoning and communication skills required in practice. Interactive virtual patient simulations, including those powered by artificial intelligence (AI), offer scalable alternatives, but empirical evidence comparing interactive and static case formats in interprofessional learner populations remains limited.

Objective:

This randomized controlled trial examined whether learner knowledge, case discussion quiz performance, and engagement differed when educational case studies were delivered through an interactive AI-powered virtual patient format versus a static written format.

Methods:

Health professional students (N=58 completers) from medicine, nursing, dentistry, pharmacy, and allied health programs at a US academic health sciences university viewed a 12-minute video on pain management and were then randomized to complete either (1) 3 static written case studies or (2) 3 interactive virtual patient case studies using the Figment Learning Labs Virtual Clinic. Case content was identical across conditions. The virtual patient system used an AI-enabled conversational interface (OpenAI GPT-4o) to deliver case material, whereas the text-based condition required reading of static case text. Knowledge was assessed pre- and post-intervention using an 8-item test. Case discussion quiz accuracy and learner engagement were also measured. Analyses included mixed analysis of variance (ANOVA) and independent-samples t tests.

Results:

A significant time (pre-post) × group (interactive vs written) interaction was observed (F₁,₅₆=4.39, P=.041), indicating greater knowledge gains in the interactive condition. Participants in the virtual patient group demonstrated higher case discussion quiz accuracy (mean 0.78, SD 0.15) than those in the written case group (mean 0.65, SD 0.12; t₆₂=4.04, P<.001), and significantly higher engagement on 13 of 17 survey items (P<.05), including items addressing realism, enjoyment, and perceived clinical relevance.

Conclusions:

Exposure to interactive virtual patient cases was associated with higher engagement and higher knowledge test scores compared with written cases. This study cannot isolate the independent contribution of AI or time-on-task from the broader effects of interactivity. Findings highlight the potential value of interactive case-based learning and suggest that AI-enabled systems are feasible and scalable for delivering clinical training. Larger, multi-institutional, and longitudinal studies are needed to determine durability, generalizability, and the unique impact of AI on learning outcomes. Clinical Trial: Not applicable (educational intervention; IRB-approved by the Medical University of South Carolina Institutional Review Board for the Protection of Human Subjects).