Generative AI–Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study
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Abstract
Background: Cognitive behavioral therapy (CBT) is a highly effective treatment for depression and anxiety disorders. Nonetheless, a substantial proportion of patients do not respond to treatment. The lack of engagement with therapeutic materials and exercises between sessions, a necessary component of CBT, is a key determinant of unsuccessful treatment. Objective: The objective of this study was to test whether the deployment of a generative artificial intelligence (AI)–enabled therapy support tool, which helps patients to engage with therapeutic materials and exercises in between sessions, leads to improved treatment success and patient treatment adherence compared with the standard delivery of CBT exercises through static workbooks. Methods: We conducted a real-world observational study of 244 patients receiving group-based CBT in 5 of the United Kingdom’s National Health Service Talking Therapies services, comparing 150 (61.5%) patients who used the AI-enabled therapy support tool to 94 (38.5%) patients who used the standard delivery of CBT exercises. The groups were equivalent with respect to the content of the CBT materials and the human-led therapy sessions; however, the intervention group received support from the AI-enabled therapy support tool in conducting CBT exercises. Results: Patients using the AI-enabled therapy support tool exhibited greater attendance at therapy sessions and fewer dropouts from treatment. Furthermore, these patients demonstrated higher reliable improvement, recovery, and reliable recovery rates when compared to the control group, which was related to the degree of use of the AI-enabled therapy support tool. Moreover, we found that engagement with AI-supported CBT interventions, relative to psychoeducational materials, predicted better treatment adherence and treatment success, highlighting the role of personalization in the intervention’s effectiveness. To investigate the mechanisms of these effects further, we conducted a separate qualitative experiment in a nonclinical sample of users (n=113). Results indicated that users perceived the AI-enabled therapy support tool as most useful for discussing their problems to gain awareness and clarity of their situation as well as learning how to apply coping skills and CBT techniques in their daily lives. Conclusions: Our results show that an AI-enabled, personalized therapy support tool in combination with human-led group therapy is a promising avenue to improve the efficacy of and adherence to mental health care.
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One study found that the GenAI support system significantly improved patient attendance and treatment outcomes.
“one study found that the GenAI support system significantly improved patient attendance and treatment outcomes [68].”
From Generative AI Mental Health Chatbots as Therapeutic Tools: Systematic Review and Meta-Analysis of Their Role in Reducing Mental Health Issues (2025) · cites this paper as [68]
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- Authors
- Habicht, J., Dina, L.-M., McFadyen, J., Stylianou, M., Harper, R., Hauser, T. U., & Rollwage, M.
- Affiliations
- University College London (GB)
- Corresponding author
- Rollwage, Max
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2025-03-10
- Volume
- 27
- Pages
- e60435
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC11933774
- OpenAlex
- W4408290602
- Cited by
- 52
- References
- 42
- Citations by year
- 2026: 36 · 2025: 16
- FWCI
- 41.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- generative AI, cognitive behavioral therapy, group therapy, medication adherence, patient engagement, depression, anxiety disorders, treatment discontinuation, personalized interventions, coping strategies, mental health services
- MeSH terms
- Adult, Anxiety Disorders, Artificial Intelligence, Female, United Kingdom, Humans, Male, Middle Aged, Patient Participation, Psychotherapy, Group, Cognitive Behavioral Therapy, Treatment Outcome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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