JMIR Publications

ABSTRACT

Background:

Virtual patients (VPs) are computer-based simulations of clinical scenarios used in health professions education to address various learning outcomes, including clinical reasoning (CR). CR is a crucial skill for healthcare practitioners, and its inadequacy can compromise patient safety. Recent advancements in large language models (LLMs) and social robots have introduced new possibilities for enhancing VP interactivity and realism. However, their application in VP simulations has been limited, and no studies have investigated the effectiveness of combining LLMs with social robots for CR skills acquisition.

Objective:

To explore the potential added value of a social robotic VP platform combined with an LLM compared to a conventional computer-based VP modality for the acquirement of CR skills by medical students.

Methods:

A Swedish explorative proof-of-concept study was conducted between May and July 2023, combining quantitative and qualitative methodology. Fifteen medical students from Karolinska Institutet completed a VP case in a social robot and a computer-based semi-linear platform. Students’ self-perceived acquirement of CR skills was assessed using validated indices, and paired t-test was used to compare mean scores (scales from 1 to 5) between the platforms. Moreover, in-depth interviews were conducted with eight medical students.

Results:

The social robotic platform was perceived as more authentic (4.4±0.2 versus 3.9±0.0; p=0.027) and provided a superior overall learning effect (4.4±0.0 versus 4.1±0.1; p=0.009) compared with the computer-based platform. Qualitative analysis revealed four themes wherein students experienced the social robot as superior to the computer-based platform in training CR, communication, and emotional skills. Limitations related to technical and user-related aspects were identified, and suggestions for improvements included enhanced facial expressions and VP cases simulating multiple personalities.

Conclusions:

A social robotic platform enhanced by an LLM can provide an authentic and engaging learning experience for medical students in the context of VP simulations for training CR. Beyond its limitations, several aspects of potential improvement were identified for the robotic platform, lending promise for this technology as a means towards attainment of learning outcomes within medical education curricula.