Evidence map›Paper›PMID 34065853›Full record

ArticleInternational journal of environmental research and public health2021

Association of Child Mental Health with Child and Family Characteristics in Rural China: A Cross-Sectional Analysis.

Huan Wang, Cody Abbey, Xinshu She, Scott Rozelle, Xiaochen Ma

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 17 citations in OpenAlex.

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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

5 authors at 2 institutions in 2 countries.

Huan WangStanford Center on China's Economy and Institutions, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-3219-7226
Cody AbbeyStanford Center on China's Economy and Institutions, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-1281-5472
Xinshu SheStanford School of Medicine, Stanford University, Stanford, CA 94305, USA.
Scott RozelleStanford Center on China's Economy and Institutions, Stanford University, Stanford, CA 94305, USA.
Xiaochen MaChina Center for Health Development Studies, Peking University, Beijing 100871, China.
Stanford University · USPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessing the mental health problems encountered by school children and understanding the contributing factors are crucial to inform strategies aimed at improving mental health in low-resource contexts. However, few studies have investigated the mental health problems among disadvantaged children in poorer countries. This study examines the prevalence of mental health problems in rural China and their association with child and family characteristics. The study uses survey data from 9696 children in 120 rural primary schools and measures child mental health using the Strengths and Difficulties Questionnaire (SDQ). Overall, 17.9% of the sample children were found to be in the abnormal range of the SDQ total difficulties scores. The mean score was 12.93 (SD = 4.94). Abnormal scores were associated with child and family characteristics, including older child age (Odds Ratio, OR = 0.704, 95% CI: 0.611, 0.810;

Indexed as

Mental HealthRural PopulationAdolescentChildChinaCross-Sectional StudiesFamily CharacteristicsHumansSurveys and QuestionnairesChinamental healthrural school childrenstrengths and difficulties questionnaire

Identifiers

PMID34065853
PMCPMC8150989
OpenAlexW3160339852

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.