Evidence map›Paper›PMID 36591046›Full record

ArticleFrontiers in psychology2022

School bullying among migrant children in China: A cross-sectional study.

Zhengmin Yang, Ying Tu, Zaihua Qin, Xiaoqun Liu, Dali Lu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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.

Zhengmin YangDepartment of Maternal and Child Health, Xiangya School of Public Health, Central South University, Changsha, China.
Ying TuDepartment of Maternal and Child Health, Xiangya School of Public Health, Central South University, Changsha, China.
Zaihua QinDepartment of Student Affairs, Hunan University of Finance and Economics, Changsha, China.
Xiaoqun LiuDepartment of Maternal and Child Health, Xiangya School of Public Health, Central South University, Changsha, China.
Dali LuDepartment of Pediatric Psychology, Shenzhen Longhua Maternity and Child Healthcare Hospital, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bullying is a serious public health concern affecting the physical and mental health of children. Migrant children are at higher risk of developing health problems. We conducted this study to investigate the prevalence of school bullying and its possible influencing factors of migrant children. Methods: A cross-sectional study was carried out in Hunan Province, China from April to July 2018. Multi-stage cluster sampling was adopted to achieve a representative sample covering both urban and rural areas. Migrant children are defined as those who migrate with one or both parents to other places and who do not have a hukou in their city of residence. The Chinese version of Olweus Bully/Victim Questionnaire was applied to measure children's involvement in school bullying. Results: A total of 7,607 students were surveyed, including 995 migrant children and 6,612 non-migrant children. The prevalence of school bullying was significantly higher in migrant children than in non-migrant children ( Conclusion: Migrant children showed a higher prevalence of school bullying than non-migrant children. Gender, grade, frequency of playing violent games, number of social friends and being beaten by parents or caregivers were associated with school bullying in migrant children.

Indexed as

Chinainfluencing factorsmigrant childrenprevalenceschool bullying

Identifiers

PMID36591046
PMCPMC9795197

What OpenQuestion holds

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Registered trials

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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.