Evidence map›Paper›PMID 41317168›Full record

ArticleBehavioral sciences & the law

Irreversible Effects of Affiliation With Delinquent Peers on Cyberbullying Perpetration Among Adolescents in Hong Kong: Moderating Effect of Student-Teacher Relationships.

Yang Han, Ji-Kang Chen

Abstract read
In one paragraph

Article in Behavioral sciences & the law. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Yang HanDepartment of Social Work, The Chinese University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0002-8486-5508
Ji-Kang ChenDepartment of Social Work, The Chinese University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0001-7762-3888

Funding

General Research Fund, The Research Grants Council, Government of the Hong Kong Special Administrative Region 14619123International Research Collaboration Fund granted by the Department of Social Work, The Chinese University of Hong Kong 19231105
6 · The paper itself

Abstract

Adolescent affiliation with delinquent peers can lead to offline delinquent behaviors; however, less is known about its effect on online delinquent behaviors, particularly cyberbullying perpetration. Furthermore, it is unclear whether the delinquent peer effect on cyberbullying perpetration can be reversed by reducing affiliation with delinquent peers. Using novel asymmetric fixed-effects regression with two-wave follow-up data from Hong Kong (N = 356) to control for observed time-variant and observed and unobserved time-invariant confounders, we found that increased affiliation with delinquent peers was associated with increased cyberbullying perpetration, whereas decreased affiliation with delinquent peers was not associated with cyberbullying perpetration. Additionally, improving student-teacher relationships mitigated the effect of increased affiliation with delinquent peers on cyberbullying perpetration. Therefore, the effect of affiliation with delinquent peers on cyberbullying perpetration may be irreversible. Nevertheless, interventions and policies can aim to enhance student-teacher relationships to alleviate the delinquent peer effect on cyberbullying perpetration.

Indexed as

Adolescent BehaviorCyberbullyingInterpersonal RelationsJuvenile DelinquencyPeer GroupSchool TeachersStudentsAdolescentFemaleHong KongHumansMaleadolescentsaffiliation with delinquent peersasymmetric fixed‐effects regressioncyberbullying perpetrationirreversible effectsstudent–teacher relationships

Identifiers

PMID41317168
PMCPMC12865677

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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.