Mapping Factors Influencing the Psychological Well-Being of Medical Students Interacting with Generative Artificial Intelligence: A Scoping Review v1

Abstract

The rapid integration of generative artificial intelligence (GenAI) tools such as ChatGPT and large language models (LLMs) into medical education has created new opportunities for learning, simulation, and clinical reasoning. However, these technologies also introduce potential challenges affecting students’ psychological well-being, including anxiety about reliability, ethical concerns, and changes in academic engagement. This protocol describes a scoping review designed to map the factors influencing the psychological well-being of medical students in their interactions with GenAI. The review will follow the methodological framework proposed by Arksey and O’Malley and guided by the PRISMA-ScR checklist. Searches will be conducted across international and Persian databases from 2018 onward, using the PCC framework (Population–Concept–Context) to ensure comprehensive coverage. Eligible studies will include empirical and theoretical works addressing medical students’ experiences with GenAI in educational contexts. Data will be extracted using a structured form and synthesized through descriptive mapping and thematic analysis. The expected outcome is a conceptual framework summarizing factors that positively or negatively influence medical students’ psychological well-being when engaging with GenAI. This review will identify knowledge gaps and provide evidence to inform educational policy, research, and the development of a culturally adapted conceptual model based on the METUX framework.

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