Lee Suonaa, Oh Jae Won, Park Kyung Mee, Lee San, Lee Eun
Department of Psychiatry and the Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Department of Psychiatry, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea.
NPJ Digit Med. 2023 Mar 25;6(1):52. doi: 10.1038/s41746-023-00800-3.
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.
尽管针对失眠的数字认知行为疗法(dCBT-I)开展了相关研究,但关于dCBT-I对失眠以及抑郁症和焦虑症等相关临床病症疗效的研究却很有限。我们在PubMed、PsycINFO(Ovid)、Embase和Cochrane数据库中检索了针对成年失眠患者且报告了抑郁或焦虑症状测量结果的随机对照试验(RCT)。去除重复文章后,共识别出2504篇文章,最终纳入荟萃分析的有22项RCT。在治疗后评估中,dCBT-I组在缓解抑郁症状(标准化均数差(SMD)=-0.42;95%可信区间:-0.56,-0.28;p<0.001;k=21)和焦虑症状方面有小到中度的效果(SMD=-0.29;95%可信区间:-0.40,-0.19;p<0.001;k=18),但对睡眠结果测量有较大效果(SMD=-0.76;95%可信区间:-0.95,-0.57;p<0.001;k=22)。在考虑治疗依从性时,高依从性组的治疗效果显示出更显著的结果,在抑郁、焦虑和睡眠结果方面的效应量比低依从性组更大。此外,对使用完全自动化dCBT-I治疗且无人类治疗师支持的研究进行的额外亚组分析显示,在抑郁、焦虑和睡眠结果方面有显著的治疗效果。结果表明,针对失眠的数字干预在缓解抑郁和焦虑症状以及失眠症状方面产生了显著效果。具体而言,该研究表明,在考虑治疗依从性并实施完全自动化dCBT-I时,对上述症状有显著效果。