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The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review
Xi Wang1, Yujia Zhou2, Guangyu Zhou1
1School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China.
JMIR Mental Health
|June 27, 2025
Summary
Generative artificial intelligence (GenAI) offers promising advancements in mental health care, enhancing diagnosis, therapy, and clinician support. However, ethical considerations and robust safeguards are crucial for responsible implementation.
Area of Science:
- Digital Health
- Artificial Intelligence in Medicine
- Mental Healthcare Technology
Background:
- Mental health disorders impact 1 in 8 individuals globally, facing barriers like accessibility, cost, and stigma.
- Generative artificial intelligence (GenAI) offers real-time language understanding and generation, presenting new avenues for mental health care enhancement.
Purpose of the Study:
- To systematically review current applications of GenAI in mental health.
- Focus on three core domains: diagnosis and assessment, therapeutic tools, and clinician support.
- To identify and synthesize key ethical issues associated with GenAI in mental health.
Main Methods:
- Comprehensive literature search following PRISMA 2020 guidelines.
- Databases searched include PubMed, ACM Digital Library, Scopus, Embase, PsycInfo, and Google Scholar.
- Analysis of 79 peer-reviewed studies published between October 2019 and September 2024.
Main Results:
- Substantial growth in GenAI mental health studies since 2023.
- Diagnosis/assessment (47%) focused on detecting depression and suicidality; therapeutic applications (25%) explored chatbots for support with limited real-world deployment.
- Clinician support (30%) involved decision-making, documentation, and training, with consistent ethical concerns reported across all domains.
- Proposed the GenAI4MH ethical framework for responsible GenAI use in mental health.
Conclusions:
- GenAI holds significant promise for augmenting mental health services, improving diagnostic accuracy, accessibility, and reducing clinician burden.
- Ethical implementation requires comprehensive safeguards, particularly concerning data privacy, algorithmic bias, and user safety.
- GenAI can enhance traditional mental health approaches but necessitates careful governance for effective and responsible integration.
Keywords:
generative AIlarge language modelsmental healthmental health detection and diagnosistherapeutic chatbotsMore Related Videos
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