Evidence map›Paper›PMID 41102803›Full record

ArticleBMC psychology2025

Cyberbullying and cybervictimization patterns among left-behind and non-left-behind adolescents in China: a latent profile analysis.

Lei Liu, Bixia Zhang, Meilin Song, Yanxiang Fan, Min Mo, Biao Peng

Abstract read
In one paragraph

Article in BMC psychology, 2025. 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

6 authors.

Lei Liu *Public Administration School, Guangzhou University, Guangzhou, China.
Bixia Zhang *College of Music, Hunan Normal University, Changsha, China.
Meilin SongSchool of Public Administration, Hunan Normal University, Changsha, China.
Yanxiang FanThe Party School of the Yiyang Municipal Committee of the CPC, Yiyang, China.
Min MoHunan Industry Polytechnic, Changsha, China. 523846690@qq.com.
Biao PengSchool of Marxism, Changsha Institute of Technology, Changsha, China. pengbiao220@qq.com.

Funding

Hunan Provincial Natural Science Foundation of China No.2022JJ60003
6 · The paper itself

Abstract

backgroundLeft-behind adolescents in China may face heightened risks of involvement in cyberbullying due to their psychological vulnerability and complex social circumstances. Considering the potential heterogeneity within this population, this study aimed to identify distinct patterns of cyberbullying and cybervictimization among left-behind adolescents and to explore how reactive anger, left-behind patterns, gender, and grade level predict membership in these subgroups.

methodsA total of 1,351 junior high school students (752 left-behind, 599 non-left-behind) were recruited from five schools. Latent profile analysis (LPA) was used to identify distinct patterns, and multinomial logistic regression was used to examine the relationships between predictors and various profiles.

results(1) Three distinct profiles of cyberbullying and cybervictimization were identified among left-behind adolescents. (2) Left-behind adolescents were more likely to experience cybervictimization compared to their non-left-behind peers. (3) Reactive anger, left-behind patterns, gender, and grade level significantly predicted subgroup membership.

conclusionThese findings underscore the importance of developing targeted interventions and considering the specific psychosocial vulnerabilities of left-behind youth.

Indexed as

Adolescent BehaviorCyberbullyingAdolescentAngerChinaFemaleHumansMaleStudentsCyberbullyingCybervictimizationLatent profile analysisLeft-behind students

Identifiers

PMID41102803
PMCPMC12532435

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.