Extending the UTAUT Model: The Role of Trust and Anthropomorphism in Shaping AI Acceptance in Medical Education in Iran

Despite the widespread application of artificial intelligence (AI) in medical education, limited research has been conducted on the acceptance of this technology from medical students' perspectives. Therefore, this study aims to highlight the factors influencing AI's acceptance in medical education from students' perspectives by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model with the components of trust and anthropomorphism. The developed model was validated based on data collected from 139 students in Tehran, Iran, over a three-month period from September to November 2024 using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The study's results revealed that performance expectancy, effort expectancy, social influence, and trust are directly related to the behavioral intention to accept AI. In contrast, facilitating conditions and anthropomorphism did not show a direct significant relationship with behavioral intention. Importantly, the findings supported the mediating role of trust in the relationship between both anthropomorphism and social influence with behavioral intention, emphasizing the central role of trust in students' decision-making about AI use in medical education. Additionally, the study's findings validated the direct relationship between facilitating conditions and behavioral intention with the acceptance of AI applications in medical education.