Evidence map›Paper›PMID 32076871›Full record

ReviewEuropean child & adolescent psychiatry2021

Effectiveness comparisons of various psychosocial therapies for children and adolescents with depression: a Bayesian network meta-analysis.

Jing-Hong Liang, Jing Li, Rong-Kun Wu, Jia-Yu Li, Sheng Qian, Rui-Xia Jia, Ying-Quan Wang, Yu-Xi Qian, Yong Xu

Abstract readReviewNetwork Meta-Analysis
PubMed Publisher
In one paragraph

Review in European child & adolescent psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 4 pooled it
2.1field-weighted citation impact, top 13% of its field
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

10 citing papers in PubMed, 4 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
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  4. Pooled it
  5. Article
  6. Review
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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

9 authors at 1 institution in 1 country.

Jing-Hong Liang *Department of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China.
Jing Li *Department of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China.
Rong-Kun WuDepartment of Child and Adolescent Health, School of Public Health, Medical College of Soochow University, No. 199 Ren Ai Road, Suzhou, 215123, Jiangsu, People's Republic of China.
Jia-Yu LiDepartment of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China.
Sheng QianDepartment of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China.
Rui-Xia JiaDepartment of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China.
Ying-Quan WangDepartment of Child and Adolescent Health, School of Public Health, Medical College of Soochow University, No. 199 Ren Ai Road, Suzhou, 215123, Jiangsu, People's Republic of China.
Yu-Xi QianDepartment of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China.
Yong XuDepartment of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, 215123, Jiangsu, People's Republic of China. childhealth@suda.edu.cn.
Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The existence of depression among children or adolescents can trigger a sequence of burdens on themselves, their families and even the whole society, which cause both physical and economic impacts. Our network meta-analysis (NMA) was aimed at comparing them with each other for evaluating the optimal psychosocial therapy to help children and adolescents with depression to improve their mental health. Based on several biomedical databases, a system of search strategies was conducted for searching randomized controlled trials (RCTs) which published from their inception on October, 1st 2018 without language restriction. We carried out an expression analysis for comparing the efficacy of various psychosocial therapies using Bayesian NMA. A battery of analyses and assessments, such as conventional meta-analysis and risk of bias, were performed concurrently. Only 32 of RCTs which involved 2677 participants were eventually included in our analyses from the 19,176 of initial citation screening. In addition, in terms of various valid assessment instruments, interpersonal psychotherapy [standard mean difference (SMD) = -1.38, Credible interval (CrI) - 2.5, - 0.20)], computer cognitive-behavioral therapy (SMD = -1.36, CrI - 2.59, - 0.14), cognitive-behavioral therapy (SMD = -1.16, CrI - 2.15, - 0.18), had significantly better effects than the named control group. All together, these results suggest that interpersonal psychotherapy might be the best approach to improve the depressive state among children and adolescents. This study may provide an excellent resource for future endeavors to utilize psychosocial interventions and may also serve as a springboard for creative undertakings as yet unknown.

Indexed as

Psychosocial Support SystemsBayes TheoremDepressionFemaleHumansMalePsychotherapyBayesian network meta-analysisChildren and adolescentsDepressionPsychosocial therapies

Identifiers

PMID32076871
OpenAlexW3008224780

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.