The role of generative artificial intelligence in psychiatric education: a scooping review (Preprint)

Abstract

<sec> <title>BACKGROUND</title> The increasing prevalence of mental health conditions, exacerbated by the COVID-19 pandemic, underscores the urgent need for improved psychiatric education. This study investigates the potential role of generative artificial intelligence (GenAI) in psychiatric education. </sec> <sec> <title>OBJECTIVE</title> While GenAI has shown promising outcomes in medical education, its application in psychiatric training remains underexplored. In this study, we hope to highlight the potential roles of GenAI in psychiatric education. </sec> <sec> <title>METHODS</title> We conducted a scoping review to identify the role of GenAI in psychiatric education based on the educational framework of the Canadian Medical Education Directives for Specialists (CanMEDS). </sec> <sec> <title>RESULTS</title> Of the 6412 papers identified, 5 studies met the inclusion criteria, revealing key roles for GenAI in case-based learning, simulation, content synthesis, and assessments. Despite these promising applications, limitations such as content accuracy, biases, and concerns regarding security and privacy were highlighted. </sec> <sec> <title>CONCLUSIONS</title> Despite these promising applications, limitations such as content accuracy, biases, and concerns regarding security and privacy were highlighted. This study contributes to the understanding of how GenAI can enhance psychiatric education and suggests future research directions to refine its use in training medical students and primary care physicians. GenAI holds significant potential to address the growing demand for mental health professionals, provided its limitations are carefully managed. </sec>

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