Predicting Teen Dating Violence Perpetration

• NCJ Number: 253165
• Journal: Pediatrics Volume: 141 Issue: 4 Dated: 2018
• Author(s): J. R. Cohen; R.C. Shorey; S.V. Menon; J.R. Temple
• Date Published: 2018
• Length: 8 pages
• Grant Number(s): 2012-WG-BX-0005; 2016-R2-CX-0035
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description

Annotation

The objectives of this study were (1) to understand what factors uniquely conferred risk for physical and sexual forms of teen dating violence (TDV) perpetration and (2) to create a screening algorithm to quantify perpetration risk on the basis of these factors.

Abstract

A total of 1,031 diverse public high school students living in Southeast Texas participated in the study (56 percent female; 29 percent African-American, 28 percent White, and 31 percent Hispanic). Self-report measures concerning TDV and associated risk factors were completed annually for 6 years. The findings suggest that family violence (domestic violence exposure, maltreatment) together with deficits in conflict resolution incrementally improved researchers' forecasts above and beyond lifetime history of physical TDV perpetration (net reclassification improvement = 0.44; 95 percent confidence interval [CI] = 0.30-0.59). Meanwhile, a violent dating history (TDV sexual perpetration, sexual victimization, and emotional perpetration) and acceptance of TDV incrementally improved researchers' models for forecasting sexual forms of perpetration (net reclassification improvement = 0.41; 95 percent CI = 0.24-0.58). These models adequately discriminated between future perpetrators and nonoffenders (area under the curve statistic >0.70; 95 percent CI: 0.69-0.74). Overall, adolescents with positive test results on the algorithms were over twice as likely to perpetrate dating violence over the course of 6 years. This study is one of the first applications of reclassification analyses to psychosocial research in a pediatric population. The result is a theoretically informed, empirically based algorithm that can adequately estimate the likelihood of physical and sexual TDV perpetration during vulnerable developmental periods. These findings can immediately aid emerging preventive initiatives for this increasing public health concern. (publisher abstract modified)