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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.07623 |
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| _version_ | 1866911199733481472 |
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| author | Lawrence, Hannah R. Stirman, Shannon Wiltsey Dorison, Samuel Yun, Taedong Bell, Megan Jones |
| author_facet | Lawrence, Hannah R. Stirman, Shannon Wiltsey Dorison, Samuel Yun, Taedong Bell, Megan Jones |
| contents | Generative artificial intelligence (Generative AI) is transforming healthcare. With this evolution comes optimism regarding the impact it will have on mental health, as well as concern regarding the risks that come with generative AI operating in the mental health domain. Much of the investment in, and academic and public discourse about, AI-powered solutions for mental health has focused on therapist chatbots. Despite the common assumption that chatbots will be the most impactful application of GenAI to mental health, we make the case here for a lower-risk, high impact use case: leveraging generative AI to enhance and scale training in mental health service provision. We highlight key benefits of using generative AI to help train people to provide mental health services and present a real-world case study in which generative AI improved the training of veterans to support one another's mental health. With numerous potential applications of generative AI in mental health, we illustrate why we should invest in using generative AI to support training people in mental health service provision. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07623 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Case for Leveraging Generative AI to Expand and Enhance Training in the Provision of Mental Health Services Lawrence, Hannah R. Stirman, Shannon Wiltsey Dorison, Samuel Yun, Taedong Bell, Megan Jones Artificial Intelligence Generative artificial intelligence (Generative AI) is transforming healthcare. With this evolution comes optimism regarding the impact it will have on mental health, as well as concern regarding the risks that come with generative AI operating in the mental health domain. Much of the investment in, and academic and public discourse about, AI-powered solutions for mental health has focused on therapist chatbots. Despite the common assumption that chatbots will be the most impactful application of GenAI to mental health, we make the case here for a lower-risk, high impact use case: leveraging generative AI to enhance and scale training in mental health service provision. We highlight key benefits of using generative AI to help train people to provide mental health services and present a real-world case study in which generative AI improved the training of veterans to support one another's mental health. With numerous potential applications of generative AI in mental health, we illustrate why we should invest in using generative AI to support training people in mental health service provision. |
| title | A Case for Leveraging Generative AI to Expand and Enhance Training in the Provision of Mental Health Services |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2510.07623 |