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Debate and Dilemmas Regarding Generative AI in Mental Health Care: Scoping Review
Xuechang Xian1,2, Angela Chang1,3, Yu-Tao Xiang4
1Department of Communication, Faculty of Social Sciences, University of Macau, Macau SAR, China.
Interactive Journal of Medical Research
|August 12, 2024
Summary
Generative artificial intelligence (GAI) shows promise in mental health care, with key applications in detection, counseling, and therapy. However, GAI should supplement, not replace, human professionals, requiring ethical integration.
Area of Science:
- Digital Health
- Artificial Intelligence in Medicine
- Mental Healthcare Technology
Background:
- Mental disorders are a leading global health burden.
- Generative artificial intelligence (GAI) offers innovative potential for mental health care.
- Research on GAI applications in mental health is currently limited.
Purpose of the Study:
- To review the current state of knowledge on Generative Artificial Intelligence (GAI).
- To identify and categorize the key applications of GAI in the mental health domain.
- To consolidate and analyze relevant scientific literature.
Main Methods:
- Searched 8 major databases (e.g., PubMed, Web of Science) from 2013-2023.
- Included empirical research in English or Chinese focusing on GAI for mental health benefits.
- Synthesized data from 144 articles, with 44 meeting inclusion criteria for detailed analysis.
Main Results:
- Identified six key advanced GAI uses: disorder detection, counseling, therapy, training, decision support, and optimization.
- Therapeutic applications (43%) and counseling support (30%) were the most common uses.
- Limited research exists for specific conditions; ChatGPT's efficacy in detection is insufficient.
Conclusions:
- GAI offers a valuable supplementary tool for mental health care, enhancing services.
- Ethical and conscientious integration is crucial to maximize benefits and mitigate risks.
- This review guides future research, practice, and policy development in GAI for mental health.
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