Predicting and Preventing Failure: Developing an Assessment for Technical Violations

• In Event: Programs and Issues Influencing Probation Outcomes

Abstract

Technical violators have long been a considerable portion of prison admissions. As focus in correctional practice and policy has shifted from the age of mass incarceration to one of mass supervision, the issue of how best to deal with violators has become all the more pertinent. With this focus comes a clear need to identify evidence-based predictors of technical violations. Extant literature however, often presents the violator group as being synonymous with those who commit new crime while on supervision. Subsequently, research on the prediction of technical violations has fallen short of separating out the differences between noncriminal violations and new crime predictors. To fill this gap in the literature and meet the need of community corrections operations, the current study presents a risk and needs assessment for technical violations. Using bootstrap item selection and logistic regression analyses of Washington state offenders on supervision this study offers the predictive validity of the Static Risk Offender Needs Guide (STRONG) models for technical violators. Findings and implications of this assessment regarding its use in community corrections practice are discussed.

Authors

• Zachary K. Hamilton, Washington State University

• Christopher M. Campbell, Washington State University

• Alex Kigerl, Washington State University