A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Aggression and delinquent behavior in a large representative sample of high school students: Cannabis use and victimization as key discriminating factors. | LitMetric

Aggression and delinquent behavior in a large representative sample of high school students: Cannabis use and victimization as key discriminating factors.

Psychiatry Res

Centre de recherche de l'Institut Universitaire en Santé Mentale de Montréal; Montreal, Canada; Department of Psychiatry and Addictology, Faculty of medicine, University of Montreal; Montreal, Canada; Institut national de psychiatrie légale Philippe-Pinel; Montreal, Canada. Electronic address:

Published: February 2021

Purpose: Since conduct problems (CP) vary distinctly across youths, better subtyping CP may be an important vehicle to study specific risk factors associated to differential patterns of CP. In a sample of 63,196 adolescents, we employed a two-step method to the identify such CP patterns and to help classify youths based on several sociodemographic and psychopathological risk factors associated with CP.

Methods: K-means clustering methods were first used to reduce the heterogeneity of CP by analyzing patterns of aggressive (AGG) and rule-breaking (RB) behaviors. A multi-class Classification and Regression Tree approach was further employed to examine the hierarchical interactions between risk factors specific to the emergence of different CP patterns.

Results: Results revealed a three-cluster solution: (i) Low AGG-RB, (ii) High AGG and low RB, and (iii) High AGG-RB. The frequency of cannabis use, level of victimization and hyperactivity symptoms were the three factors best discriminating youths' membership to distinct patterns of CP. The model displayed a moderate to strong discriminatory capacity.

Conclusion: Although this study provides evidence of key factors that may increase the risk of youths following specific patterns of disruptive behavior, additional research is necessary to clarify the etiology, longitudinal trajectories and outcomes related to these patterns.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.psychres.2020.113640DOI Listing

Publication Analysis

Top Keywords

risk factors
12
factors associated
8
factors
6
patterns
6
aggression delinquent
4
delinquent behavior
4
behavior large
4
large representative
4
representative sample
4
sample high
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!