Examining the Role of Responsivity Factors in Juvenile Probation Outcomes

Anthony J Fortuna, Fordham University


According to the Risk-Needs-Responsivity (RNR) model for offender rehabilitation, treatment plans designed to decrease recidivism are most effective when an individual’s risk level matches dosage of services, dynamic (i.e., changeable) criminogenic needs are targeted, and treatment is modified to address individual responsivity factors that impact treatment delivery (Andrews, Bonta, & Hoge, 1990; Bonta & Andrews, 2017). Converging evidence supports higher needs case plan match (i.e., better matching of services delivered to needs assessment results) predicts better recidivism outcomes (Kapoor, et al., 2018; McCormick, et al., 2017; Peterson-Badali et al., 2015). Unlike the risk and need components of the RNR model, minimal research has addressed the impact of responsivity factors on recidivism. One recent study produced novel results suggesting that the total number of responsivity factors endorsed was a significant predictor of recidivism outcomes (Kapoor et al., 2018). Given the heterogenous nature of responsivity factors (e.g., mental health concerns, financial issues, living in a high crime neighborhood, etc.), it is also important to parse out which of these factors are especially impactful in terms of recidivism risk reduction. The present study tested the impact of responsivity factors on recidivism outcomes, utilizing data from a sample of 165 adolescents in two juvenile probation counties in a large northeastern state. This study utilized the Youth Level of Service/Case Management Inventory (YLS/CMI) risk/needs assessment, the Massachusetts Youth Screening Inventory – 2nd Edition (MAYSI-2; mental health screener for juvenile justice settings), and 12-month recidivism outcomes. It was hypothesized that: (1) higher score on the YLS/CMI would predict 12 month recidivism outcomes, (2) higher needs case plan match would be significantly associated with lower recidivism rate at 12 months post-probation intake, and (3) total count of responsivity factors endorsed, grouped into youth-specific responsivity factors, family-specific responsivity factors, and mental health specific responsivity factors, would be positively associated with recidivism at 12 months post-probation intake. Logistic regression analyses were conducted providing support for total score on the YLS/CMI as a significant predictor of the 12 month recidivism outcome, and did not provide support for the needs case plan match nor the total responsivity factor composites as significant predictors of 12 month recidivism outcomes. Results from this study do not support a reconceptualization of the impact of responsivity factors, but further research is needed to continue refining the vastly under-researched responsivity principle of the RNR model.

Subject Area

Clinical psychology|Developmental psychology|Criminology

Recommended Citation

Fortuna, Anthony J, "Examining the Role of Responsivity Factors in Juvenile Probation Outcomes" (2021). ETD Collection for Fordham University. AAI28715220.