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Therapeutic Interaction Features of AI Chatbots in Depression Interventions: Systematic Review and Meta-Analysis.
Ting Huang1, Shuangyu Li2, Yanzhong Wang3
1Department of Engineering, King's College London, S2.20, Strand Building, Strand Campus, Strand, London, WC2R 2LS, United Kingdom, 44 20 7836 5454.
Journal of Medical Internet Research
|June 30, 2026
Summary
This systematic review found that while AI chatbots did not significantly reduce depression symptoms overall, specific interaction features like emotional responsiveness and frequent interaction boosted user adherence. Designing engaging chatbots is key for digital mental health interventions.
Area of Science:
- Digital Mental Health
- Artificial Intelligence in Healthcare
- Clinical Psychology
Background:
- Depression is a leading global cause of disability, necessitating scalable interventions.
- AI-driven chatbots offer accessible digital solutions for depression management.
- Limited research exists on how chatbot features impact adherence and outcomes.
Conclusions:
- While not statistically significant overall, AI chatbot interaction design is crucial for adherence in digital mental health.
- Emotional responsiveness and interaction frequency are key features for improving adherence.
- Further research is needed due to study limitations, including small RCT numbers and heterogeneity.
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