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Systematic review and meta

泰然健康网
2025-08-21 03:33

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’ 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’s g 0.64 [95% CI 0.17–1.12]) and distress (Hedge’s g 0.7 [95% CI 0.18–1.22]). 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’s g 0.32 [95% CI –0.13 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.

中文翻译：

基于 AI 的对话代理促进心理健康和福祉的系统评价和荟萃分析

对话式人工智能（AI），尤其是基于 AI 的对话式代理（CA），在心理健康护理领域越来越受欢迎。尽管它们的使用越来越多，但缺乏对其对心理健康和福祉影响的全面评估。本系统评价和荟萃分析旨在通过综合有关基于 AI 的 CA 在改善心理健康方面的有效性以及影响其有效性和用户体验的因素的证据来填补这一空白。搜索了 12 个数据库，以查找 2023 年 5 月 26 日之前发表的基于 AI 的 CA 对精神疾病和心理健康影响的实验研究。在 7834 条记录中，确定了 35 项符合条件的研究进行系统评价，其中 15 项随机对照试验被纳入进行荟萃分析。荟萃分析显示，基于 AI 的 CA 显着减轻了抑郁（Hedge's g 0.64 [95% CI 0.17–1.12]）和痛苦（Hedge's g 0.7 [95% CI 0.18–1.22]）的症状。这些影响在多模式、基于生成式 AI、与移动/即时消息应用程序集成并针对临床/亚临床和老年人群的 CA 中更为明显。然而，基于 CA 的干预措施显示整体心理健康没有显着改善（Hedge's g 0.32 [95% CI -0.13 至 0.78]）。基于 AI 的 CA 的用户体验在很大程度上取决于人机 AI 治疗关系的质量、内容参与和有效沟通。这些发现强调了基于 AI 的 CA 在解决心理健康问题方面的潜力。未来的研究应调查其有效性的潜在机制，评估各种心理健康结果的长期影响，并评估大型语言模型（LLMs）在心理健康护理中的安全整合。