JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI)-powered chatbots delivering cognitive behavioral therapy (CBT) are increasingly recognized as scalable solutions for addressing mental health concerns such as depression and anxiety. These fully automated interventions offer novel pathways for psychological support, particularly for individuals with limited access to traditional therapy.

Objective:

This narrative review aims to examine the clinical efficacy, therapeutic mechanisms, and technological features of CBT-based AI chatbots used to alleviate symptoms of depression and anxiety.

Methods:

Twelve peer-reviewed studies published between 2015 and 2025 were included based on predefined inclusion criteria. The studies were analyzed to extract information on intervention structure, therapeutic components, outcomes, and implementation characteristics.

Results:

Evidence from the included studies suggests that CBT chatbot interventions consistently result in significant short-term reductions in depressive and anxiety symptoms, particularly within 4 to 8 weeks. Moderate effect sizes were observed for depression. Common therapeutic features included cognitive restructuring, behavioral activation, and mindfulness strategies. Technological components such as self-monitoring, real-time feedback, and goal tracking were also associated with enhanced user engagement and adherence.

Conclusions:

CBT-based chatbots represent a promising, scalable modality for delivering psychological support. However, heterogeneity in study design and the limited availability of long-term outcome data present challenges for generalizability. Future research should emphasize personalized interventions, long-term effectiveness, cross-cultural adaptability, and ethical considerations for real-world clinical integration.