Objective/Background: Integration of virtual patient (VP) cases has traditionally complemented clinical encounters during medical students clinical placements at Karolinska Institutet (KI). This study aimed to assess the educational value of clinical reasoning (CR) training by comparing two platforms: a novel large language model (LLM)-enhanced social robotic VP platform and a conventional computer-based platform within the context of rheumatology.

Methods/summary of work: A qualitative study involved 23 third-year medical students from KI during clinical placements in rheumatology. Each student completed nine VP cases using two distinct platforms: an LLM-enhanced social robotic platform and a computer-based semi-linear platform. Following each case completion, students participated in seminars with consultant rheumatologists to discuss the clinical cases. In-depth interviews assessed students’ self-perceived acquirement of CR skills using the two platforms following all VP cases and their corresponding seminars. Thematic analysis was employed to identify themes and sub-themes.

Results/Summary of results: Thematic analysis revealed three principal themes: authenticity, VP application, and strengths and limitations. Students perceived the social robotic platform more authentic and engaging, particularly through its capacity for interactive communication and emotional expression, collectively delivering a realistic clinical experience. The platform demonstrated effectiveness in facilitating active learning processes, hypothesis formation, and adaptive thinking skills. However, notable limitations were identified, including the absence of physical examination capabilities and instances of mechanical dialogue patterns.

Conclusion: In our setting of undergraduate medical education placements within rheumatology, an LLM-enhanced social robotic VP platform offered a more authentic and interactive learning experience compared to a conventional computer-based platform. Despite some limitations, the social robotic platform shows promise in training CR skills, communication, and adaptive thinking. AI-enhanced Social robotic VPs may prove useful learning modalities for exposing medical students to diverse, highly interactive patient simulations.