Qualitative data related to implementation process and fidelity will be examined using content analysis. Continuous variables will be summarized with descriptive statistics (mean, standard deviation); categorical variables will be described with counts and percentages. Change scores and percent change scores will be calculated across several baseline time points as well as across two years of program implementation. Multilevel modeling will be used to examine changes among Rapid City students compared to students in the comparison community. One data set will be change across time at the individual level and another will be aggregated school-level data with the matched control school data merged in. Descriptive statistics will be conducted to evaluate the distributions of variables, testing for out of range values and outliers, and determining the need for transformation of non-normal distributions. In addition, the investigators will evaluate the measures for their psychometric properties for the current samples using exploratory and confirmatory factor analysis or structural equation modeling. Evaluation will include inspection of factor loadings, error variances, intercorrelations of factors, path coefficients and overall model fit. Additionally, the investigators will test for treatment differences in the total sample on key variables collected on each time point (e.g., gender, income, race/ethnicity, etc.). The investigators will calculate Horvitz-Thompson weights or propensity scores to adjust for bias in the models to compare treatment effects. For the primary outcome, SV rate of victimization and perpetration, the investigators will use mixed effect logistic regression models to estimate the difference of intervention and non-intervention groups (pre-intervention vs. post intervention in single case, multiple baseline design and treatment difference between intervention schools and matched non-intervention schools), adjusting by other background variables including social, demographics, and community-level characteristics. Secondary behavioral, dichotomous outcomes will be analyzed the same way SV perpetration and victimization are analyzed. The model can also be slightly altered to include time as a continuous variable to examine the trajectories of SV rate reduction as well as changes over time in intermediary and secondary outcomes as a function of Youth VIP exposure and engagement.