%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 27
%N 
%P e60435
%T Generative AI–Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study
%A Habicht,Johanna
%A Dina,Larisa-Maria
%A McFadyen,Jessica
%A Stylianou,Mona
%A Harper,Ross
%A Hauser,Tobias U
%A Rollwage,Max
%+ Limbic Ltd, Kemp House, 128 City Road, London, EC1V 2NX, United Kingdom, 44 020 3818 3240, max@limbic.ai
%K artificial intelligence
%K National Health Service
%K NHS Talking Therapies
%K mental health
%K therapy support tool
%K cognitive behavioral therapy
%K CBT
%K chatbot
%K conversational agent
%K clinical
%K patient engagement
%K therapist
%K treatment
%K medication
%K depression
%K anxiety disorder
%K exercise
%K observational study
%K control group
%K patient adherence
%D 2025
%7 10.3.2025
%9 Original Paper
%J J Med Internet Res
%G English
%X 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. 
%M 40063074
%R 10.2196/60435
%U https://www.jmir.org/2025/1/e60435
%U https://doi.org/10.2196/60435
%U http://www.ncbi.nlm.nih.gov/pubmed/40063074