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Systematic review: The integration of artificial intelligence-powered cognitive-behavioural therapy for autonomous

Li-Ting Chen¹, Li-Ching Yang¹, Fang-Yi Lin²

¹Department of Nursing, College of Nursing, Fooyin University, Kaohsiung, Taiwan, ROC.

Archives of Psychiatric Nursing

|August 15, 2025

Abstract

Background:

Depression is a widespread mental health disorder that affects quality of life, with traditional treatments often resource-intensive. Studies have demonstrated the effectiveness of CBT-based AI in alleviating depressive symptoms through autonomous mental health management.

Purpose:

To evaluate the effect and the integration level of Cognitive-Behavioural Therapy-based artificial intelligence (AI) on autonomous health management in depressive symptoms care.

Methods:

This systematic review used the PRISMA methodology and a mixed-methods appraisal tool. Studies included randomized controlled trials using artificial intelligence interventions for depression, analysing theoretical frameworks, intervention designs, and outcomes. Reviews and protocols were excluded. Data sources were searched in the Cochrane Library, CINAHL Plus with Full Text, and PubMed for articles published between October 2019 and October 2024.

Results:

Five studies demonstrated that artificial intelligence designs incorporating the Cognitive-Behavioural Therapy guidance framework specifically indicated short-term intervention effectiveness. Of these AI interventions, only partial integration of 54 % implemented a theoretical framework in AI design. Nevertheless, findings revealed a significant 60 % decrease in depressive symptoms among participants who engaged with the AI-based autonomous mental health management, particularly those with moderate-to-severe depression, when grounded in a strong theoretical foundation.

Conclusion:

Cognitive-Behavioural Therapy-based artificial intelligence interventions have demonstrated effectiveness in decrease depressive symptoms through patient self-management platforms. The theory-driven approach not only guides the development of AI applications but also facilitates the implementation of automated mental health interventions, thereby reducing the workload of nursing staff. This integration of CBT-guided AI technology empowers patients with self-management tools while optimizing nursing resources in mental health settings.

Keywords:

Artificial intelligence College students Depressive symptoms Systematic review Young adults

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