Protocol of a systematic review and network meta-analysis for the prevention and treatment of perinatal depression

Author:

Smith Robert David,Hung Sze Chai,Goh Joyce,Ip Hoi Lam,Fong Daniel Yee TakORCID,Ali Shehzad,Wilson Claire AnnaORCID,Lok Kris Yuet-WanORCID

Abstract

IntroductionPerinatal depression is common and can often lead to adverse health outcomes for mother and child. Multiple pharmacological and non-pharmacological treatments have been evaluated against usual care or placebo controls in meta-analyses for preventing and treating perinatal depression compared. It is not yet established which of these candidate treatments might be the optimal approach for prevention or treatment.Methods and analysisA systematic review and Bayesian network meta-analyses will be conducted. Eight electronic databases shall be searched for randomised controlled trials that have evaluated the effectiveness of treatments for prevention and/or treatment of perinatal depression. Screening of articles shall be conducted by two reviewers independently. One network meta-analysis shall evaluate the effectiveness of interventions in preventing depression during the perinatal period. A second network meta-analysis shall compare the effectiveness of treatments for depression symptoms in women with perinatal depression. Bayesian 95% credible intervals shall be used to estimate the pooled mean effect size of each treatment, and surface under cumulative ranking area will be used to rank the treatments’ effectiveness.Ethics and disseminationWe shall report our findings so that healthcare providers can make informed decisions on what might be the optimal approach for addressing perinatal depression to prevent cases and improve outcomes in those suffering from depression through knowledge exchange workshops, international conference presentations and journal article publications.PROSPERO registration numberCRD42020200081.

Funder

University of Hong Kong

Publisher

BMJ

Subject

General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3