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Med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. Twelve databases were searched for experimental studies of AI-based CAs\u2019 effects on mental illnesses and psychological well-being published before May 26, 2023. Out of 7834 records, 35 eligible studies were identified for systematic review, out of which 15 randomized controlled trials were included for meta-analysis. The meta-analysis revealed that AI-based CAs significantly reduce symptoms of depression (Hedge\u2019s g 0.64 [95% CI 0.17\u20131.12]) and distress (Hedge\u2019s g 0.7 [95% CI 0.18\u20131.22]). These effects were more pronounced in CAs that are multimodal, generative AI-based, integrated with mobile\/instant messaging apps, and targeting clinical\/subclinical and elderly populations. However, CA-based interventions showed no significant improvement in overall psychological well-being (Hedge\u2019s g 0.32 [95% CI \u20130.13 to 0.78]). User experience with AI-based CAs was largely shaped by the quality of human-AI therapeutic relationships, content engagement, and effective communication. These findings underscore the potential of AI-based CAs in addressing mental health issues. Future research should investigate the underlying mechanisms of their effectiveness, assess long-term effects across various mental health outcomes, and evaluate the safe integration of large language models (LLMs) in mental health care.<\/jats:p>","DOI":"10.1038\/s41746-023-00979-5","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T19:02:35Z","timestamp":1703012555000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":400,"title":["Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being"],"prefix":"10.1038","volume":"6","author":[{"given":"Han","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7636-9598","authenticated-orcid":false,"given":"Renwen","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yi-Chieh","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Robert E.","family":"Kraut","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5443-7596","authenticated-orcid":false,"given":"David C.","family":"Mohr","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,19]]},"reference":[{"key":"979_CR1","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1055\/s-0041-1726510","volume":"30","author":"T Dingler","year":"2021","unstructured":"Dingler, T., Kwasnicka, D., Wei, J., Gong, E. & Oldenburg, B. 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