More engagement, more improvement: a dose-response study of 100,000 Ash users
A 2026 study of 102,684 Ash users found five engagement patterns and a dose-response link between engagement and improvement in depression, anxiety, and social support.
arXiv
Observational study (engagement phenotyping)
New York University, University of Virginia
Engagement and dose-response in 102,684 Ash users
Key Finding
Across 102,684 Ash users, engagement fell into five distinct patterns, and greater engagement tracked with larger improvements in depression — a dose-response gradient — alongside significant gains in anxiety and social support.
Summary
A 2026 arXiv preprint characterized engagement among 102,684 users of Ash and linked it to clinical outcomes. Five engagement phenotypes emerged, and a dose-response gradient was observed for depression improvement and replicated in a larger model-predicted sample. Significant pre-post improvements appeared for depression (d=-0.51), anxiety (d=-0.57), and social support (d=0.22), and a stronger working alliance predicted greater improvement.
The Full Picture
Two-thirds of users (66.9%) had at least one overnight session, and the authors caution against treating raw session counts as the primary engagement metric — different outcomes responded to different dimensions of use.
The pre-post design is observational rather than controlled. The work is offered as naturalistic evidence for the clinical value of purpose-built conversational AI.
Researchers
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Wolfe, E. C., Su, T., Tieleman, O., Hull, T. D., Malgaroli, M., & Stamatis, C. A. (2026). Engagement Phenotypes for a Sample of 102,684 AI Mental Health Chatbot Users and Dose-Response Associations with Clinical Outcomes [Preprint]. arXiv. https://arxiv.org/abs/2605.00275

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