Effectiveness of AI and rule-based conversational agents for depression, anxiety and stress: A meta-analysis
Saeed Mokhtari Masoumi Alamdarloo, Ali Mirzakhani, Mohamad Azhdarloo, Elaheh Haghani-Samani, Abouzar Nazari · 2026
Read Effectiveness of AI and rule-based conversational agents for depression, anxiety and stress: A meta-analysis by Saeed Mokhtari Masoumi Alamdarloo, Ali Mirzakhani, Mohamad Azhdarloo, Elaheh Haghani-Samani, Abouzar Nazari (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13503911.txt.
Description
Saeed Mokhtari Masoumi Alamdarloo and others meta-analyze conversational agents for low mood, anxiety, and stress. In 2026, the review synthesizes forty-eight randomized controlled trials covering 28,071 people, spanning both artificial-intelligence and rule-based agents, using robust variance estimation to handle within-study dependencies. Restricted access leaves many people without timely mental health care.
Effects were small to modest but clear: same-form mean gaps of minus 0.27 for low mood, minus 0.20 for anxiety, and minus 0.26 for stress, with larger gains in medical groups and shorter programs. Risk of bias was largely low and publication bias negligible. Chat-based agents emerge as scalable support, though long-term effectiveness and integration remain open.
Catalog record
| CREATOR | Saeed Mokhtari Masoumi Alamdarloo, Ali Mirzakhani, Mohamad Azhdarloo, Elaheh Haghani-Samani, Abouzar Nazari |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 66 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |