人工智能在心理健康領域的多學科研究重點：行動呼籲 Multidisciplinary research priorities for artificial intelligence in mental health: a call to action ——《柳葉刀-精神病學》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）的應用有望變革心理健康照護。然而，該領域研究的飛速發展已超前於協調性框架的建立，導致研究工作碎片化、標準不統一，且在安全與倫理保障方面嚴重缺失。本立場文件概述了一份協調一致的路線圖，旨在指導心理健康領域AI的負責任評估與實施；該路線圖圍繞四大優先領域構建，明確了近期行動與長期戰略目標。領域1（強化安全與證據標準）針對臨床證據和安全監管方面的不足，強調開展穩健的比較試驗、實施標準化安全測試以及建立適應性監管框架的必要性。領域2（以倫理、公平及患者聲音為核心）側重於通過透明報告、在AI全生命周期中融入患者視角，以及構建具有代表性的數據集和公平的治理結構，使AI開發與現實照護環境相契合。領域3（演進臨床醫務人員的角色）探討臨床整合過程中的挑戰，包括界定核心勝任力、明確臨床監管與問責機制，以及構想並試點新型人力資源模式。領域4（促進可持續實施與系統整合）聚焦於現實應用中的障礙，強調與臨床基礎設施的互操作性，以及建立可持續的資金籌措與實施路徑的重要性。該路線圖旨在支持各利益相關方開展協調行動，確保基於AI的心理健康系統的開發與實施遵循安全、公平、循證及臨床問責的原則。 [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. 論文原文：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 （翻譯兼責任編輯：MARY） （需要英文原文的朋友，請聯繫微信：millerdeng95或iacmsp）
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