Literature DB >> 31686291

Profiles of Antisocial Behavior in School-Based and At-Risk Adolescents in Singapore: A Latent Class Analysis.

Rebecca P Ang1, Xiang Li2, Vivien S Huan3, Gregory Arief D Liem3, Trivina Kang4, Qinyuen Wong3, Jeanette Y P Yeo3.   

Abstract

This study used latent class analysis to examine whether multiple subgroups can be identified based on rule-breaking and aggressive behavior in school-based and at-risk adolescent samples. These groups were tested for differences in behavioral, emotional, personality and interpersonal correlates. Rule breaking and aggressive behavior co-occurred across all classes. School-based adolescents were classified as having minimal, minor or moderate antisocial problems. At-risk adolescents were classified as having mild, medium or severe antisocial problems. Generally, at-risk adolescents had higher levels of antisocial behavior, and greater severity of antisocial behavior was associated with more problems in various domains. Results differed however, for the school-based and at-risk samples with respect to emotional problems, sensation-seeking and peer conformity pressure. There is a need to jointly consider both non-aggressive rule-breaking behavior and aggressive behavior in prevention and intervention work, as it is insufficient to address isolated symptoms and problems in children and adolescents.

Entities:  

Keywords:  Aggressive behavior; At-risk adolescents; Latent class analysis; Rule-breaking behavior; School-based adolescents

Year:  2020        PMID: 31686291     DOI: 10.1007/s10578-019-00941-1

Source DB:  PubMed          Journal:  Child Psychiatry Hum Dev        ISSN: 0009-398X


  1 in total

1.  Predicting How Well Adolescents Get Along with Peers and Teachers: A Machine Learning Approach.

Authors:  Farhan Ali; Rebecca P Ang
Journal:  J Youth Adolesc       Date:  2022-04-04
  1 in total

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