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August 26, 2026Journal of Psychiatric and Mental Health NursingOpen Access

An Umbrella Review of Artificial Intelligence Applications in Mental Health Care

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Authors

JOJonathan OdameGOGabriel Obeng‐GyamfiDHDayeon Heo

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Overview

Umbrella review demonstrates improved early detection and risk stratification for psychiatric conditions across 14 million individuals, suggesting AI is most effective in hybrid care models.

Key Points

  • To synthesize evidence from systematic reviews on the clinical applications, benefits, ethical challenges, and risk-mitigation strategies of artificial intelligence in mental health care.
  • Conducted an umbrella review following PRISMA 2020 guidelines across five databases (Web of Science, Scopus, PubMed, PsycINFO, and CINAHL) for studies published between 2021 and 2025.
  • Evaluated methodological quality of included systematic reviews using the AMSTAR-2 tool and synthesized findings via iterative thematic coding.
  • Included 27 systematic reviews encompassing over 14 million participants, with 27 reviews reaching moderate or high confidence ratings on the AMSTAR-2 tool.
  • Demonstrated robust evidence for AI in early detection and risk stratification of depression, anxiety, stress, PTSD, and suicidal ideation, outpacing its evidence base for sustained therapeutic interventions.
  • Identified critical ethical and methodological fragilities, including algorithmic bias and limited external validity, emphasizing that AI delivers optimal outcomes when embedded in clinician-guided hybrid care.

Cite This Study

Odame et al. (2026) studied this question.

synapsesocial.com/papers/6a8e9b21451774b83f3b39e4https://doi.org/10.1111/jpm.70180
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