Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: A Systematic Review (Preprint)

心理干预 心理信息 奇纳 系统回顾 随机对照试验 医学 梅德林 社会心理的 认知行为疗法 精神科 家庭医学 政治学 外科 法学
作者
Wan Md Zin Wan Yunus,Hanna-Maria Matinolli,Otto Waris,Subina Upadhyaya,Miika Vuori,Tarja Korpilahti-Leino,Terja Ristkari,Tarja Koffert,Andre Sourander
出处
期刊:Journal of Medical Internet Research [JMIR Publications]
卷期号:24 (2): e33337-e33337 被引量:1
标识
DOI:10.2196/33337
摘要

Background Studies have shown a high prevalence of depression during pregnancy, and there is also evidence that cognitive behavioral therapy (CBT) is one of the most effective psychosocial interventions. Emerging evidence from randomized controlled trials (RCTs) has shown that technology has been successfully harnessed to provide CBT interventions for other populations. However, very few studies have focused on their use during pregnancy. This approach has become increasingly important in many clinical areas due to the COVID-19 pandemic, and our study aimed to expand the knowledge in this particular clinical area. Objective Our systematic review aimed to bring together the available research-based evidence on digitalized CBT interventions for depression symptoms during pregnancy. Methods A systematic review of the Web of Science, Cochrane Central Register of Controlled Trials, CINAHL, MEDLINE, Embase, PsycINFO, Scopus, ClinicalTrials.gov, and EBSCO Open Dissertations databases was carried out from the earliest available evidence to October 27, 2021. Only RCT studies published in English were considered. The PRISMA (Preferred Reporting Items of Systematic Reviews and Meta-analyses) guidelines were followed, and the protocol was registered on the Prospective Register of Systematic Reviews. The risk of bias was assessed using the revised Cochrane risk-of-bias tool for randomized trials. Results The review identified 7 studies from 5 countries (the United States, China, Australia, Norway, and Sweden) published from 2015 to 2021. The sample sizes ranged from 25 to 1342 participants. The interventions used various technological elements, including text, images, videos, games, interactive features, and peer group discussions. They comprised 2 guided and 5 unguided approaches. Using digitalized CBT interventions for depression during pregnancy showed promising efficacy, with guided intervention showing higher effect sizes (Hedges g=1.21) than the unguided interventions (Hedges g=0.14-0.99). The acceptability of the digitalized CBT interventions was highly encouraging, based on user feedback. Attrition rates were low for the guided intervention (4.5%) but high for the unguided interventions (22.1%-46.5%). A high overall risk of bias was present for 6 of the 7 studies. Conclusions Our search only identified a small number of digitalized CBT interventions for pregnant women, despite the potential of this approach. These showed promising evidence when it came to efficacy and positive outcomes for depression symptoms, and user feedback was positive. However, the overall risk of bias suggests that the efficacy of the interventions needs to be interpreted with caution. Future studies need to consider how to mitigate these sources of biases. Digitalized CBT interventions can provide prompt, effective, evidence-based interventions for pregnant women. This review increases our understanding of the importance of digitalized interventions during pregnancy, including during the COVID-19 pandemic. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42020216159; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216159

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
斯文海豚发布了新的文献求助20
2秒前
jiangshanshan完成签到,获得积分20
3秒前
wxy完成签到,获得积分10
5秒前
神勇难胜完成签到,获得积分10
7秒前
三石完成签到,获得积分10
8秒前
沉默的涔发布了新的文献求助10
9秒前
牛曙东完成签到,获得积分10
10秒前
14秒前
Tom完成签到,获得积分0
15秒前
小杜完成签到,获得积分10
16秒前
zln完成签到,获得积分10
18秒前
斯文海豚完成签到,获得积分20
19秒前
Vivian完成签到 ,获得积分10
19秒前
牧青发布了新的文献求助50
19秒前
19秒前
19秒前
19秒前
20秒前
哈基米应助科研通管家采纳,获得10
20秒前
哈基米应助科研通管家采纳,获得10
20秒前
领导范儿应助科研通管家采纳,获得10
20秒前
所爱皆在完成签到 ,获得积分10
22秒前
23秒前
大肥猫完成签到,获得积分10
26秒前
今后应助momo采纳,获得10
26秒前
cyw发布了新的文献求助10
31秒前
小鱼完成签到 ,获得积分10
32秒前
孙同学完成签到 ,获得积分10
34秒前
35秒前
35秒前
Patience完成签到,获得积分10
36秒前
开着飞机骑拖拉机完成签到,获得积分10
37秒前
38秒前
39秒前
Brave发布了新的文献求助10
40秒前
小破仁完成签到,获得积分10
41秒前
41秒前
岁月旧曾谙完成签到,获得积分10
43秒前
momo发布了新的文献求助10
44秒前
老实的黑米完成签到 ,获得积分10
45秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359014
求助须知:如何正确求助?哪些是违规求助? 8172981
关于积分的说明 17211866
捐赠科研通 5413996
什么是DOI,文献DOI怎么找? 2865331
邀请新用户注册赠送积分活动 1842737
关于科研通互助平台的介绍 1690836