Observational studyJournal of medical Internet research2025
Generative AI-Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study.
Observational study in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Digital front door technologies to pre-assess people before assessment for NHS Talking Therapies [HTE10055]: early value assessment.Health technology assessment (Winchester, England) · 2026Pooled it
- Artificial Intelligence for Predicting Treatment Response in Patients With Anxiety Disorders After Cognitive Behavioral Therapy: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Generative AI Mental Health Chatbots as Therapeutic Tools: Systematic Review and Meta-Analysis of Their Role in Reducing Mental Health Issues.Journal of medical Internet research · 2025Pooled it
- Large language models in real-world clinical workflows: a systematic review of applications and implementation.Frontiers in digital health · 2025Pooled it
- Bridging primary care with artificial intelligence: toward a global 1.5-Tier Healthcare System.npj health systems · 2026Review
- Engagement, Satisfaction, and Therapeutic Alliance With an AI Conversational Agent for Parents: Quantitative Descriptive Study.JMIR formative research · 2026Article
- Exploring Applications of AI in the Crisis Line Sector: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- Conversational AI should fill the white space in mental health care, not replace humans.NPJ digital medicine · 2026Review
- Artificial Intelligence in Child and Adolescent Psychiatry: A Narrative Review of Recent Clinical Applications and Ethical Considerations.Current psychiatry reports · 2026Review
- User Experience and Early Clinical Outcomes of a Mental Wellness Chatbot for Depression and Anxiety: Pilot Evaluation Mixed Methods Study.JMIR formative research · 2026Article
- Real-World Data From a Group Parent Management Training Program Enhanced Using Artificial Intelligence: Qualitative Study.JMIR formative research · 2026Article
- Six reasons to study emotional support from conversational artificial intelligence.Nature human behaviour · 2026Article
- The present and future of blended care: current research and introduction to the B-FIT framework.NPJ digital medicine · 2026Review
- Increasing engagement with cognitive-behavioral therapy (CBT) using generative AI: a randomized controlled trial (RCT).Communications medicine · 2026Article
- Mapping applications and evaluations of LLM-enabled AI chatbots for health purposes: a scoping review.Frontiers in public health · 2026Article
- Positive psychology 4.0: a science of consequence for a world that can no longer wait.Frontiers in psychology · 2026Article
- Clinical Efficacy, Therapeutic Mechanisms, and Implementation Features of Cognitive Behavioral Therapy-Based Chatbots for Depression and Anxiety: Narrative Review.JMIR mental health · 2025Review
- H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics.International journal of health geographics · 2025Article
- Public Health Risk Management, Policy, and Ethical Imperatives in the Use of AI Tools for Mental Health Therapy.Healthcare (Basel, Switzerland) · 2025Article
- Mentalizing Without a Mind: Psychotherapeutic Potential of Generative AI.Journal of medical Internet research · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCognitive 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.
objectiveThe 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.
methodsWe 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.
resultsPatients 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.
conclusionsOur 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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