DOI 10.1136/bmjhci-2025-101479
Chatbot interventions for improving mental health among people in Asia: a systematic review and meta-analysis of randomised controlled trials.
Аннотация
OBJECTIVES
Chatbot-delivered treatments offer tremendous mental health benefits. This systematic review aimed at examining the effectiveness of using chatbots for improving mental health among people in Asia.
METHODS
Randomised controlled trials (RCTs) on standalone chatbot interventions targeting mental health conditions, ranging from mental well-being to clinically relevant mental health symptoms (eg, depression, anxiety, stress, affect, distress, insomnia and psychological well-being), were included. Four electronic databases (PubMed, CINAHL, PsycINFO and Medline) were searched until 11 December 2024.
RESULTS
A total of eight RCTs (n=921) were included. Our meta-analysis results by random-effects models showed that chatbot interventions reduced the severity of depressive symptoms by 0.46 (95% CI -0.76 to -0.16, p=0.002, I2=73%). In the subgroup analyses, chatbot interventions were effective in reducing depression in clinical populations by 0.54 (95% CI -1.02 to -0.07, p=0.02, I2=73%), among Chinese participants by 0.55 (95% CI -0.92 to -0.17, p=0.004, I2=81%), and when being compared with traditional bibliotherapy (eg, paperback books or e-book) by 0.47 (95% CI -0.76 to -0.18, p=0.001, I2=26%). Meanwhile, chatbot interventions were shown to reduce levels of negative affect by 1.95 (95% CI -3.46 to -0.44, p=0.01, I2=0%) versus no treatment. However, no significant effects were found for other mental health outcomes, including anxiety, positive affect and stress. Other relevant mental health outcomes included insomnia, attention deficit symptoms, panic disorder, social phobia, problem gambling and methamphetamine use disorder. No adverse events were reported.
DISCUSSION AND
CONCLUSION
Chatbot-assisted therapy is a clinically beneficial and safe modality for treating depressive symptoms in the Asian context.
PROSPERO REGISTRATION NUMBER: CRD42024546316.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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