VERA-MH: Validation of Ethical and Responsible AI in Mental Health
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866913146042580992 |
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| author | Belli, Luca Bentley, Kate H. Gieringer, Josh Van Ark, Emily Zhao, Nilu Thachile, Pradip Hawrilenko, Matt Brown, Millard Chekroud, Adam M. |
| author_facet | Belli, Luca Bentley, Kate H. Gieringer, Josh Van Ark, Emily Zhao, Nilu Thachile, Pradip Hawrilenko, Matt Brown, Millard Chekroud, Adam M. |
| contents | Chatbot usage has increased, including in fields for which they were never developed for--notably mental health support. To that end, we introduce Validations of Ethical and Responsible AI in Mental Health (VERA-MH), a novel clinically-validated evaluation for safety of chatbots in the context of mental health support. The first iteration of VERA-MH focuses on Suicidal Ideation (SI) risks, by assessing how well chatbots can responds to users that might be in crisis.
VERA-MH is comprised of three steps: conversation simulation, conversation judging and model rating. First, to simulate conversations with the chatbot under evaluation, another chatbot is tasked with role-playing users based on specific personas. Such user personas have been developed under clinical guidance, to make sure that, among others, multiple risk factors, demographic characteristics and disclosure factors were represented. In the judging step, a second support model is used as an LLM-as-a-Judge, together with a clinically-developed rubric. The rubric is structured as a flow, with a single Yes/No question asked each time, to improve answers' consistency and highlight models' failure modes. In the last stage, results of each conversation are aggregated to present the final evaluation of the chatbot. Together with the framework, we present the result of the evaluations for four leading LLM providers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_13318 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | VERA-MH: Validation of Ethical and Responsible AI in Mental Health Belli, Luca Bentley, Kate H. Gieringer, Josh Van Ark, Emily Zhao, Nilu Thachile, Pradip Hawrilenko, Matt Brown, Millard Chekroud, Adam M. Artificial Intelligence Emerging Technologies Chatbot usage has increased, including in fields for which they were never developed for--notably mental health support. To that end, we introduce Validations of Ethical and Responsible AI in Mental Health (VERA-MH), a novel clinically-validated evaluation for safety of chatbots in the context of mental health support. The first iteration of VERA-MH focuses on Suicidal Ideation (SI) risks, by assessing how well chatbots can responds to users that might be in crisis. VERA-MH is comprised of three steps: conversation simulation, conversation judging and model rating. First, to simulate conversations with the chatbot under evaluation, another chatbot is tasked with role-playing users based on specific personas. Such user personas have been developed under clinical guidance, to make sure that, among others, multiple risk factors, demographic characteristics and disclosure factors were represented. In the judging step, a second support model is used as an LLM-as-a-Judge, together with a clinically-developed rubric. The rubric is structured as a flow, with a single Yes/No question asked each time, to improve answers' consistency and highlight models' failure modes. In the last stage, results of each conversation are aggregated to present the final evaluation of the chatbot. Together with the framework, we present the result of the evaluations for four leading LLM providers. |
| title | VERA-MH: Validation of Ethical and Responsible AI in Mental Health |
| topic | Artificial Intelligence Emerging Technologies |
| url | https://arxiv.org/abs/2605.13318 |