人工智能在心理健康领域的多学科研究重点：行动呼吁 Multidisciplinary research priorities for artificial intelligence in mental health: a call to action ——《柳叶刀-精神病学》第13卷第9期，2026年9月—— <The Lancet / Psychiatry>, Volume 13, Issue 9, September 2026 【摘要】人工智能（AI）的应用有望变革心理健康照护。然而，该领域研究的飞速发展已超前于协调性框架的建立，导致研究工作碎片化、标准不统一，且在安全与伦理保障方面严重缺失。本立场文件概述了一份协调一致的路线图，旨在指导心理健康领域AI的负责任评估与实施；该路线图围绕四大优先领域构建，明确了近期行动与长期战略目标。领域1（强化安全与证据标准）针对临床证据和安全监管方面的不足，强调开展稳健的比较试验、实施标准化安全测试以及建立适应性监管框架的必要性。领域2（以伦理、公平及患者声音为核心）侧重于通过透明报告、在AI全生命周期中融入患者视角，以及构建具有代表性的数据集和公平的治理结构，使AI开发与现实照护环境相契合。领域3（演进临床医务人员的角色）探讨临床整合过程中的挑战，包括界定核心胜任力、明确临床监管与问责机制，以及构想并试点新型人力资源模式。领域4（促进可持续实施与系统整合）聚焦于现实应用中的障碍，强调与临床基础设施的互操作性，以及建立可持续的资金筹措与实施路径的重要性。该路线图旨在支持各利益相关方开展协调行动，确保基于AI的心理健康系统的开发与实施遵循安全、公平、循证及临床问责的原则。 [Summary] The use of artificial intelligence (AI) is anticipated to transform mental health care. However, the rapid research growth in this field has outpaced coordinated frameworks, leaving research efforts fragmented, standards inconsistent, and safeguards for safety and ethics largely absent. This Position Paper outlines a coordinated roadmap to guide the responsible evaluation and implementation of AI in mental health, structured across four overarching priority domains that define near-term actions and longer-term strategic goals. Domain 1 (Strengthen safety and evidence standards) addresses deficits in clinical evidence and safety oversight, emphasising the need for robust comparative trials, standardised safety testing, and adaptive regulatory frameworks. Domain 2 (Centre ethics, equity, and patient voices) focuses on aligning AI development with real-world care contexts through transparent reporting, integration of patient perspectives throughout the AI lifecycle, and the development of representative datasets and equitable governance structures. Domain 3 (Evolve the role of the clinician) addresses challenges in clinical integration, including defining core competencies, clarifying clinical oversight and accountability, and conceptualising and trialling new workforce models. Domain 4 (Facilitate sustainable implementation and systems integration) targets barriers to real-world adoption, including the importance of interoperability with clinical infrastructure and the development of sustainable financing and implementation pathways. This roadmap should support coordinated action across stakeholders and ensure that AI-based mental health systems are developed and implemented in line with principles of safety, equity, evidence, and clinical accountability. 论文原文：Jake Linardon, Joseph Firth, Andre F Carvalho, et al. (2026). Multidisciplinary research priorities for artificial intelligence in mental health: a call to action. The Lancet / Psychiatry, Volume 13, Issue 9, Pages792-803. September 2026. https://doi.org/10.1016/S2215-0366(26)00127-6 （翻译兼责任编辑：MARY） （需要英文原文的朋友，请联系微信：millerdeng95或iacmsp）
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