School Success Among Youth Serving Probation

Background/Purpose:  This study builds on growing recognition of the importance school success holds for youth involved in the juvenile justice system. We utilize a risk and resilience framework (Jensen & Fraser, 2015) to examine unique and cumulative contributions of theorized risk and protective factors on school success among probation youth. We draw from work establishing the strong correlation between juvenile justice involvement and educational achievement (e.g. Farn et al., 2016; Blomberg et al., 2011). A risk and resilience framework enable assessment of how protective factors counteract relationships between risk factors and school success, offering direction for focusing intervention and support strategies that promote school success for youth serving probation.    

Methods: Data derive from a sample (n=4840) of initial intake assessments of Peirce County, Washington probation youth assessed using the Back On Track, 4^th Generation (BOT4.0) and Positive Achievement Change Tool, 2^nd generation (PACT2.0) instruments.

Three school success outcomes—school disruption, school disengagement, and grades—were employed in a three-step regression model testing the associations between demographic factors, risk factors, and protective factors on school success. Stepping in these three variable blocks (demographic, risk, protective) tested the extent to which each covariates’ unique effect retained significance across an increasingly complex multivariate model; R² changes tracked the cumulative contribution of these factors on school success outcomes. The first step tested associations between demographic covariates (gender and race/ethnicity groups) and school success. The second step added a risk block, which contained five measures: a ten-item index measuring adversity experiences (ACEs); three dichotomous variables measuring if a youth currently was living in a foster care or group home placement, had special education needs, or had gang ties; and, a six-item scale measuring youths’ attitudes regarding empathy, authority, and appropriate behavior. Step three added a protective block, comprised of three mean-based scales measuring youths’ levels of parental support, positive community relationships, and individual-level protective skills. Linear regression was used to test school disruption and school disengagement. Ordered logistic regression was used to test grades.    

Results: Demographically, associations between school disruption and school disengagement were significantly stronger for minority youth. These significant differences were sustained when accounting for both risk and protective factors. School disruption and school disengagement were also significantly positively associated with gang ties and youths’ attitudes, and strongly negatively associated with parental support, positive community relationships, and individual-level protective skills. Youth with gang ties and more adversarial attitudes toward authority and prosocial conventions were significantly more likely to have poorer grades. The three protective measures significantly increased the odds of higher grades. Across the regression model, protective factors contributed the strongest effects on school success.

Conclusions and Implications: These findings indicate that malleable protective factors have potential to counteract many risk factors that pose barriers to school success. We discuss opportunities for concentrating intervention and collaboration strategies between schools and the probation system that promote increased protective resources for probation youth aimed at bolstering their ability to achieve school success and reduce recidivism.