Sex Offender Recidivism Prediction

• NCJ Number: 166759
• Journal: Forum Volume: 8 Issue: 2 Dated: (May 1996) Pages: 22-24
• Author(s): N Belanger; C Earls
• Date Published: 1996
• Length: 3 pages
• Publication Format: Article
• Publication Type: Test/Measurement
• Language: English
• Country: Canada

Annotation

This article summarizes a preliminary test of the predictive validity of the Sex Offender Risk Appraisal Guide, which has been used in Canada to predict both sexual and non-sexual recidivism offenses.

Abstract

To test the predictive validity of the Guide with sex offenders in the criminal justice system, a sample of 57 male sex offenders was studied. These offenders were released from minimum-security, medium-security, and maximum-security correctional institutions in the Quebec region between January 1, 1991, and January 31, 1993. All of the offenders were released to a half-way house with the specific condition that they participate in a community-based sex offender treatment program. None of the offenders had received institutional treatment. Follow-up was conducted from the moment an inmate was released and continued until his sentence expired. Recidivism was defined as being charged with a new sex offense, being charged with a new non-sex offense, or a conditional release violation serious enough to return the offender to a Federal institution. Of the 57 sex offenders, 43.9 percent were returned to a Federal institution within 40 weeks of release. To further test the validity of the instrument, a computer simulation was used to identify correct and incorrect release decisions for each Sex Offender Risk Appraisal Guide category score. The Guide has nine prediction categories that range from 0.00 to 1.00 probability of violent recidivism. For each prediction category, the simulation calculated the percentage of the sample correctly identified by the instrument, the percentage of false negatives (offenders predicted to succeed who failed), and the percentage of false positive (offenders successful in the community who had been predicted to fail). The accuracy of prediction and types of errors produced by the model varied over the nine prediction categories. A maximum of 75.4 percent of the total sample was correctly identified. Risk prediction must balance the costs of recidivism against the costs of continued incarceration. The best way to reduce the costs of both recidivism and continued incarceration is to provide effective sex offender treatment. 2 tables and 3 footnotes