Multidisciplinary research priorities for artificial intelligence in mental health: a call to action

Le résumé fourni par la source

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.

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