Background: The majority of studies on youth violence have focused on factors that increase the risk for youth violence. Purpose: To assess whether determinants of violence operate as risk factors, direct protective factors, or both during adolescence and young adulthood. Methods: Data from participants in the National Longitudinal Study of Adolescent Health, aged 13 years at Wave 1, were analyzed. Individual, family, school, peer, and community factors during adolescence (Wave 1 ; age 13 years) were examined as predictors of violence involvement during adolescence (Wave 2 ; age 14 years) and in young adulthood (Wave 3 [2001-2002]; ages 18-20 years). Results: Twelve percent of participants aged 14 years and 8% of participants aged 18-20 years reported serious violence involvement during the past 12 months. Bivariate analyses revealed risk and direct protective factors for violence at both time points. Risk for violence at age 14 years was increased by earlier attention-deficit hyperactivity disorder (ADHD) symptoms, low school connectedness, low grade-point average, and high peer delinquency. Direct protective factors for youth violence at age 14 years included low ADHD symptoms, low emotional distress, high educational aspirations, and high grade-point averages. Bivariate analyses showed a lower risk of violence among youth aged 18-20 years who reported low peer delinquency at age 13 years. Multiple logistic regression analyses predicting violence involvement showed direct protective effects for low ADHD symptoms and low emotional distress at age 14 years, and a direct protective effect for low peer delinquency at ages 18-20 years, after controlling for demographic characteristics. Conclusions: Findings suggest that violence involvement remains difficult to predict but indicate the importance of assessing both risk and direct protective factors for understanding violent behavior.
Bibliographical noteFunding Information:
Publication of this article was supported by Cooperative Agreement award # CIP-08-001 from the CDC to the Association for Prevention Teaching and Research (APTR).
This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development , with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website ( www.cpc.unc.edu/addhealth ).