Predictors and responses to the growth in physical violence during adolescence
A comparison of students in Washington state and Victoria, Australia
Bibliographic Data
| ID | 9053692 |
|---|---|
| Authors | Todd I Herrenkohl (0000-0002-7001-1544, University of Washington), Sheryl A Hemphill (0000-0001-8342-1561, Australian Catholic University), W Alex Mason (0000-0002-8132-8045, Boys Town), John W Toumbourou (0000-0002-8431-3762, Deakin University), Richard F Catalano (University of Washington) |
| Year | 2012 |
| Volume | 82 |
| Issue | 1 |
| Pages | 41-49 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | American Journal of Orthopsychiatry (JOURNAL) |
| Journal identifiers | ISSN: 0002-9432 • E-ISSN: 1939-0025 |
| Publisher | American Psychological Association (APA) (PUBLISHER) |
| DOI | 10.1111/j.1939-0025.2011.01139.x |
| PMID | 22239392 |
| PMCID | PMC3261578 |
| OpenAlex | W2016299614 |
| Language | EN |
| Citations received | 2 |
| References cited | 23 |
This study investigates patterns in violence over 3 time points in early- to mid-adolescence in 2 statewide representative samples of youth, one in Washington State, USA, and the other in Victoria, Australia. Comparable data collection methods in both states were used to cross-nationally compare patterns of violence, risk factors, and responses to violence (school suspensions and arrests) in 2 policy contexts. Risk factors include early use of alcohol, binge drinking, involvement with antisocial peers, family conflict, poor family management, sensation seeking, and bully victimization. These are modeled as correlates of initial violence and predictors of change in violence over a 3-year period, from ages 12-15, for participating youth. Results suggest that patterns and predictors of violence are mostly similar in the 2 states. Initial levels of violence (age 13) and change over time in violence were associated in both states with more youth school suspensions and more police arrests in Grade 9. Some cross-national differences were also shown. For example, correlations of violence with gender and violence with binge drinking were stronger in Victoria, whereas correlations of violence with early use of alcohol and with antisocial peer involvement were stronger in Washington State. Antisocial peer involvement and family conflict were significant predictors of a gradual increase in violence from Grades 7-9 for youth in Victoria only. Implications are discussed with attention to prevention and intervention efforts
Binge drinking · Domestic violence · Injury prevention · Intervention (counseling) · Medical emergency · Occupational safety and health · Personality · Poison control · Psychiatry · Sensation Seeking · Sociology · Suicide prevention · Bullying, Victimization, and Aggression · Child and Adolescent Psychosocial and Emotional Development · Clinical Psychology · Demography · Gun Ownership and Violence Research · Human Factors and Ergonomics · Medicine · Psychology · Social Psychology
Serious and Violent Juvenile Offenders
Measurement Properties of the Communities That Care Youth Survey Across Demographic Groups
Developmental risk factors for youth violence
A Longitudinal Study of Relational Aggression, Physical Aggression, and Children's Social–Psychological Adjustment
Measuring Risk and Protective Factors for Use, Delinquency, and Other Adolescent Problem Behaviors
Physical Aggression During Early Childhood
Latent Growth Curves within Developmental Structural Equation Models
Testing Structural Equation Models
Risk and protection
Pathways From School Suspension to Adolescent Nonviolent Antisocial Behavior in Students in Victoria, Australia and Washington State, United States
Teasing, rejection, and violence
Development of juvenile aggression and violence
Can test statistics in covariance structure analysis be trusted
Using covariance structure analysis to detect correlates and predictors of individual change over time
Alternative Ways of Assessing Model Fit
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,15 |
| Citation span | 2013 - 2019 (7) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |