Sleep & breathing = Schlaf & Atmung · 2026
Efficacy of fully automated digital cognitive behavioral therapy for insomnia in adults: a systematic review and meta-analysis.
СтатьяСистематический обзорМетаанализНазвание и аннотация: Перевод в очереди
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Gao Kaige, Zhao Yanjie, Zhang Xuehong, Su Kanbao, Jia Jia, Xu Yuezhen
Аннотация
OBJECTIVE: Fully automated digital cognitive behavioral therapy for insomnia (dCBT-I) is increasingly used as a scalable intervention for adults with insomnia. Although recent reviews have supported its overall efficacy, uncertainty remains regarding the interpretation of platform-related differences across trials. We aimed to evaluate the efficacy of fully automated dCBT-I in adults and to explore whether apparent differences by delivery platform may be related to study-level characteristics.
METHODS: We conducted a systematic review and random-effects meta-analysis of randomized controlled trials in general adult populations. Standardized mean differences (SMDs) were pooled using restricted maximum likelihood estimation with truncated Knapp-Hartung adjustment. Subgroup analyses and exploratory meta-regression examined delivery platform and publication year as potential moderators.
RESULTS: Fifteen trials (N = 3,507) were included. Fully automated dCBT-I was associated with substantial reductions in insomnia severity (SMD = - 0.82) and consistent improvements in sleep initiation and sleep efficiency, with smaller but significant improvements in sleep quality. In exploratory multivariable meta-regression, the association between delivery platform and treatment effect was attenuated after adjustment for study-level characteristics, including publication year. More recent trials tended to yield smaller effect estimates. Given the limited number of app-based studies, these findings should be interpreted cautiously. Residual heterogeneity was low.
CONCLUSIONS: Fully automated dCBT-I appears to be an effective intervention for adults with insomnia. Platform-related differences were not robust in exploratory analyses and may reflect broader temporal or design-related differences across studies rather than inherent advantages or limitations of a specific delivery format. Further trials, particularly app-based studies, are needed to clarify whether platform-specific effects exist.
METHODS: We conducted a systematic review and random-effects meta-analysis of randomized controlled trials in general adult populations. Standardized mean differences (SMDs) were pooled using restricted maximum likelihood estimation with truncated Knapp-Hartung adjustment. Subgroup analyses and exploratory meta-regression examined delivery platform and publication year as potential moderators.
RESULTS: Fifteen trials (N = 3,507) were included. Fully automated dCBT-I was associated with substantial reductions in insomnia severity (SMD = - 0.82) and consistent improvements in sleep initiation and sleep efficiency, with smaller but significant improvements in sleep quality. In exploratory multivariable meta-regression, the association between delivery platform and treatment effect was attenuated after adjustment for study-level characteristics, including publication year. More recent trials tended to yield smaller effect estimates. Given the limited number of app-based studies, these findings should be interpreted cautiously. Residual heterogeneity was low.
CONCLUSIONS: Fully automated dCBT-I appears to be an effective intervention for adults with insomnia. Platform-related differences were not robust in exploratory analyses and may reflect broader temporal or design-related differences across studies rather than inherent advantages or limitations of a specific delivery format. Further trials, particularly app-based studies, are needed to clarify whether platform-specific effects exist.