Evidence map›Paper›PMID 34635517›Full record

ArticleBMJ open2021

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

Robert David Smith, Sze Chai Hung, Joyce Goh, Hoi Lam Ip, Daniel Yee Tak Fong, Shehzad Ali, Claire Anna Wilson, Kris Yuet-Wan Lok

Abstract read
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Robert David SmithSchool of Nursing, University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong.
Sze Chai HungSchool of Nursing, University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong.
Joyce GohSchool of Nursing, University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong.
Hoi Lam IpSchool of Nursing, University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong.
Daniel Yee Tak FongSchool of Nursing, University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong.ORCID 0000-0001-7365-9146
Shehzad AliEpidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada.
Claire Anna WilsonSection of Women's Mental Health, King's College London, London, UK.ORCID 0000-0003-2169-5115
Kris Yuet-Wan LokSchool of Nursing, University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong krislok@hku.hk.ORCID 0000-0002-3227-0799

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 ANALYSIS: A 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 DISSEMINATION: We 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 NUMBER: CRD42020200081.

Indexed as

DepressionDepressive DisorderBayes TheoremChildFemaleHumansNetwork Meta-Analysis as TopicPregnancySystematic Reviews as TopicTreatment Outcomedepression & mood disordersmaternal medicinemental health

Identifiers

PMID34635517
PMCPMC8506850

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.