Suppr超能文献

数字干预措施治疗抑郁症的元分析综述。

Digital interventions for the treatment of depression: A meta-analytic review.

机构信息

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki.

Department of Research Methods, Institute of Psychology and Education, Ulm University.

出版信息

Psychol Bull. 2021 Aug;147(8):749-786. doi: 10.1037/bul0000334.

Abstract

The high global prevalence of depression, together with the recent acceleration of remote care owing to the COVID-19 pandemic, has prompted increased interest in the efficacy of digital interventions for the treatment of depression. We provide a summary of the latest evidence base for digital interventions in the treatment of depression based on the largest study sample to date. A systematic literature search identified 83 studies (N = 15,530) that randomly allocated participants to a digital intervention for depression versus an active or inactive control condition. Overall heterogeneity was very high (I2 = 84%). Using a random-effects multilevel metaregression model, we found a significant medium overall effect size of digital interventions compared with all control conditions (g = .52). Subgroup analyses revealed significant differences between interventions and different control conditions (WLC: g = .70; attention: g = .36; TAU: g = .31), significantly higher effect sizes in interventions that involved human therapeutic guidance (g = .63) compared with self-help interventions (g = .34), and significantly lower effect sizes for effectiveness trials (g = .30) compared with efficacy trials (g = .59). We found no significant difference in outcomes between smartphone-based apps and computer- and Internet-based interventions and no significant difference between human-guided digital interventions and face-to-face psychotherapy for depression, although the number of studies in both comparisons was low. Findings from the current meta-analysis provide evidence for the efficacy and effectiveness of digital interventions for the treatment of depression for a variety of populations. However, reported effect sizes may be exaggerated because of publication bias, and compliance with digital interventions outside of highly controlled settings remains a significant challenge. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

摘要

全球范围内抑郁症的高患病率,加上最近由于 COVID-19 大流行加速了远程护理,促使人们对数字干预治疗抑郁症的疗效产生了更大的兴趣。我们根据迄今为止最大的研究样本,总结了数字干预治疗抑郁症的最新证据基础。系统文献检索确定了 83 项研究(N = 15530),这些研究将参与者随机分配到数字干预组治疗抑郁症,与积极或不活动的对照组进行比较。总体异质性非常高(I2 = 84%)。使用随机效应多层荟萃回归模型,我们发现与所有对照组相比,数字干预的总体效果大小具有显著的中等效应(g =.52)。亚组分析显示,干预措施与不同的对照组之间存在显著差异(WLC:g =.70;注意:g =.36;TAU:g =.31),涉及人类治疗指导的干预措施(g =.63)比自助干预措施(g =.34)的效果显著更高,有效性试验(g =.30)的效果显著低于疗效试验(g =.59)。我们发现基于智能手机的应用程序和基于计算机和互联网的干预措施之间的结果没有显著差异,以及人类指导的数字干预措施与面对面的心理治疗之间也没有显著差异,尽管这两种比较的研究数量都很少。当前荟萃分析的结果为各种人群的数字干预治疗抑郁症的疗效和有效性提供了证据。然而,由于发表偏倚,报告的效果大小可能被夸大,并且在高度受控的环境之外,数字干预的依从性仍然是一个重大挑战。(PsycInfo 数据库记录(c)2021 APA,保留所有权利)。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验