Digital cognitive behavioral therapy for insomnia on depression and anxiety: a systematic review and meta-analysis

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Suonaa Lee
Jae Won Oh
Kyung Mee Park
San Lee
Eun Lee
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[1] Yonsei University College of Medicine,Department of Psychiatry and the Institute of Behavioral Science in Medicine
[2] Yongin Severance Hospital,Department of Psychiatry
[3] Yonsei University College of Medicine,Institute for Innovation in Digital Healthcare
[4] Yonsei University,undefined
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Despite research into the development of digital cognitive behavioral therapy for insomnia (dCBT-I), research into the outcomes of dCBT-I on insomnia and the associated clinical conditions of depression and anxiety have been limited. The PubMed, PsycINFO (Ovid), Embase, and Cochrane databases were searched for randomized controlled trials (RCTs) on adult patients with insomnia also having reported measures of depressive or anxiety symptoms. In total, 2504 articles were identified after duplicate removal, and 22 RCTs were included in the final meta-analysis. At the post-treatment assessment, the dCBT-I group had a small to moderate effect in alleviating depressive (standardized mean difference (SMD) = −0.42; 95% CI: −0.56, −0.28; p < 0.001; k = 21) and anxiety symptoms (SMD = −0.29; 95% CI: −0.40, −0.19; p < 0.001; k = 18), but had a large effect on sleep outcome measures (SMD = −0.76; 95% CI: −0.95, −0.57; p < 0.001; k = 22). When considering treatment adherence, the treatment effects of those in the high adherent groups identified a more robust outcome, showing greater effect sizes than those in the low adherent groups for depression, anxiety, and sleep outcomes. Furthermore, additional subgroup analysis on studies that have used the fully automated dCBT-I treatment without the support of human therapists reported significant treatment effects for depression, anxiety, and sleep outcomes. The results demonstrated that digital intervention for insomnia yielded significant effects on alleviating depressive and anxiety symptoms as well as insomnia symptoms. Specifically, the study demonstrated significant effects on the above symptoms when considering treatment adherence and implementing fully automated dCBT-I.
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