Prégent Julien, Chung Van-Han-Alex, El Adib Inès, Désilets Marie, Hudon Alexandre
Department of Psychiatry and Addictology, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada.
Faculty of Medicine, McGill University, Montreal, QC, Canada.
JMIR Med Educ. 2025 Jul 28;11:e75238. doi: 10.2196/75238.
Artificial intelligence (AI) is increasingly integrated into health care, including psychiatry and psychology. In educational contexts, AI offers new possibilities for enhancing clinical reasoning, personalizing content delivery, and supporting professional development. Despite this emerging interest, a comprehensive understanding of how AI is currently used in mental health education, and the challenges associated with its adoption, remains limited.
This scoping review aimed to identify and characterize current applications of AI in the teaching and learning of psychiatry and psychology. It also sought to document reported facilitators of and barriers to the integration of AI within educational contexts.
A systematic search was conducted across 6 electronic databases (MEDLINE, PubMed, Embase, PsycINFO, EBM Reviews, and Google Scholar) from inception to October 2024. The review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. Studies were included if they focused on psychiatry or psychology, described the use of an AI tool, and discussed at least 1 facilitator of or barrier to its use in education. Data were extracted on study characteristics, population, AI application, educational outcomes, facilitators, and barriers. Study quality was appraised using several design-appropriate tools.
From 6219 records, 10 (0.2%) studies met the inclusion criteria. Eight categories of AI applications were identified: clinical decision support, educational content creation, therapeutic tools and mental health monitoring, administrative and research assistance, natural language processing (NLP), program/policy development, students' study aid, and professional development. Key facilitators included the availability of AI tools, positive learner attitudes, digital infrastructure, and time-saving features. Barriers included limited AI training, ethical concerns, lack of digital literacy, algorithmic opacity, and insufficient curricular integration. The overall methodological quality of included studies was moderate to high.
AI is being used across a range of educational functions in psychiatry and psychology, from clinical training to assessment and administrative support. Although the potential for enhancing learning outcomes is clear, its successful integration requires addressing ethical, technical, and pedagogical barriers. Future efforts should focus on AI literacy, faculty development, and institutional policies to guide responsible and effective use. This review underscores the importance of interdisciplinary collaboration to ensure the safe, equitable, and meaningful adoption of AI in mental health education.
人工智能（AI）正越来越多地融入医疗保健领域，包括精神病学和心理学。在教育环境中，人工智能为增强临床推理、个性化内容交付以及支持专业发展提供了新的可能性。尽管人们对此兴趣渐浓，但对于人工智能目前在心理健康教育中的应用方式以及采用过程中所面临的挑战，全面的了解仍然有限。
本范围综述旨在识别和描述人工智能在精神病学和心理学教学与学习中的当前应用。它还试图记录在教育环境中报道的人工智能整合的促进因素和障碍。
从数据库建立至2024年10月，在6个电子数据库（MEDLINE、PubMed、Embase、PsycINFO、循证医学评论和谷歌学术）中进行了系统检索。该综述遵循系统评价和Meta分析扩展的范围综述首选报告项目（PRISMA-ScR）指南。如果研究聚焦于精神病学或心理学，描述了人工智能工具的使用，并讨论了其在教育中使用的至少一个促进因素或障碍，则纳入研究。提取了关于研究特征、人群、人工智能应用、教育成果、促进因素和障碍的数据。使用几种适合设计的工具对研究质量进行了评估。
从6219条记录中，有10项（0.2%）研究符合纳入标准。确定了八类人工智能应用：临床决策支持、教育内容创建、治疗工具和心理健康监测、行政和研究协助、自然语言处理（NLP）、项目/政策制定、学生学习辅助工具和专业发展。关键促进因素包括人工智能工具的可用性、学习者的积极态度、数字基础设施以及节省时间的功能。障碍包括人工智能培训有限、伦理问题、数字素养不足、算法不透明以及课程整合不足。纳入研究的总体方法质量为中等至高。
人工智能正被应用于精神病学和心理学的一系列教育功能中，从临床培训到评估和行政支持。虽然提高学习成果的潜力显而易见，但其成功整合需要克服伦理、技术和教学方面的障碍。未来的努力应集中在人工智能素养、教师发展和机构政策上，以指导负责任和有效的使用。本综述强调了跨学科合作对于确保在心理健康教育中安全、公平和有意义地采用人工智能的重要性。
