Exploring Health Care Professionals’ Perceptions of Live Actor Avatar and AI Avatar Simulated Patient Interactions

Introduction: The increasing use of simulation in health care and advancing capabilities of virtual technology have increased the use of virtual avatars. Recently, the development of large language models has created an opportunity for virtual reality (VR) simulation through combination of VR and artificial intelligence (AI). This study sought to evaluate the perception of authenticity in prerecorded virtual simulated patient interactions using two different avatar platforms: AI avatar and live actor avatar. Methods: Participants included 41 health professionals with patient care experience, of which 32 completed the post experience survey. Using a repeated measures mixed methods research design allowed the assessment of differences in health professionals’ perception of verbal and nonverbal communication between AI avatar and live actor avatar after viewing two five-minute prerecorded virtual patient simulations. Quantitative scale data were analyzed using descriptive statistics and frequencies. Differences in perception of patient communication were assessed using a paired t-test. Qualitative data were coded for thematic analysis converged with quantitative data for a better understanding of participants’ responses. Results: Quantitative and qualitative analysis suggested participants perceived the live actor avatar as having a higher degree of authenticity in both verbal and nonverbal communication, with the largest effect sizes seen in displaying emotions and nonverbal communication. Discussion: Results demonstrated greater perceived authenticity in live avatar simulation experiences compared to simulation utilizing AI avatars. However, AI avatars offer the advantages of consistent, repeatable learning experiences accessible across diverse educational settings. Educators should consider the complexity of integrating different simulation modalities, weighing authenticity benefits against practical implementation factors such as cost, scalability, and technical requirements.