Description of original award (Fiscal Year 2018, $249,425)
Teen dating violence (TDV) is an increasing criminal justice and public health issue. Risk algorithms have been recommended for violence screening but do not exist for TDV perpetration. The primary aims of the study are to determine (1) Whether risk algorithms based on a collection of modifiable risk/protective factors can estimate TDV-perpetration above and beyond past traumatic events; (2) If prediction models vary as a function of race/ethnicity and sex; and (3) Whether the risk algorithm generalizes across adolescent settings (school vs. juvenile justice) and other violent behaviors (e.g., physical fights, carrying a weapon).
The sample will include 400 high school students in Texas, and 200 adolescents participating in a juvenile diversion program in Illinois. They will complete online surveys at baseline, 6-months, and 12-months. Participants ages range between 13-17, and the sample is balanced with regard to sex and race (White, African-American, and Hispanic).
The surveys measure TDV- perpetration and other violent behavior, childhood adversities, individual risk factors for TDV-perpetration, and interpersonal and culturally-relevant protective factors. A novel analytic plan using latent growth curve modeling, receiver operating characteristic (ROC) and reclassification analyses will properly contextualize each risk factors relation to TDV-perpetration, and then translate these findings into an empirically-based decision making tool.
"Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14).
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