Generative AI-Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study.

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2025-03-10 DOI:10.2196/60435
Johanna Habicht, Larisa-Maria Dina, Jessica McFadyen, Mona Stylianou, Ross Harper, Tobias U Hauser, Max Rollwage
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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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生成式人工智能支持治疗工具,改善临床结果和患者参与团体治疗:现实世界观察研究。
背景:认知行为疗法(CBT)是一种非常有效的治疗抑郁症和焦虑症的方法。尽管如此,很大一部分患者对治疗没有反应。缺乏治疗材料和训练,这是CBT的必要组成部分,是治疗失败的关键决定因素。目的:本研究的目的是测试使用生成式人工智能(AI)支持的治疗支持工具,帮助患者在疗程之间参与治疗材料和练习,与通过静态工作簿进行CBT练习的标准交付相比,是否可以提高治疗成功率和患者治疗依从性。方法:我们对244名在英国国家卫生服务谈话治疗服务中接受基于小组的CBT的患者进行了一项现实世界的观察性研究,比较了150名(61.5%)使用人工智能支持治疗工具的患者和94名(38.5%)使用标准交付CBT练习的患者。两组在CBT材料的内容和人类主导的治疗过程方面是相同的;然而,干预组在进行CBT练习时得到了人工智能支持的治疗支持工具的支持。结果:使用人工智能支持治疗工具的患者在治疗过程中表现出更高的出勤率,更少的患者退出治疗。此外,与对照组相比,这些患者表现出更高的可靠改善、恢复和可靠恢复率,这与人工智能支持治疗工具的使用程度有关。此外,我们发现,相对于心理教育材料,参与人工智能支持的CBT干预可以预测更好的治疗依从性和治疗成功率,突出了个性化在干预有效性中的作用。为了进一步研究这些影响的机制,我们在非临床用户样本中进行了单独的定性实验(n=113)。结果表明,用户认为人工智能支持的治疗工具对于讨论他们的问题以获得对他们情况的认识和清晰度以及学习如何在日常生活中应用应对技巧和CBT技术最有用。结论:我们的研究结果表明,人工智能支持的个性化治疗支持工具与人类主导的团体治疗相结合,是提高精神卫生保健疗效和依从性的有希望的途径。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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