Eliciting Responsivity: Exploring Programming Interests of Federal Inmates as a Function of Security Classification.

Research supports the effectiveness of the Risk-Needs-Responsivity model for reducing criminal recidivism. Yet programming interests of inmates--one facet of responsivity--remain an understudied phenomenon. In the present study, we explored the programming interests of 753 federal inmates housed across three levels of security. Results suggest that inmates, as a group, prefer specific programs over others, and that some of their interests may differ by security level. We discuss possible implications of these findings.

Sexually violent predators: toward reasonable estimates of recidivism base rates.

The sexual recidivism rate of sex offenders is a controversial issue. Perhaps as controversial is the sexual recidivism rate of the select group of sex offenders who are examined pursuant to sexually violent predator (SVP) statutes. At present, reliable estimates of SVP recidivism are unavailable. We propose that reasonable estimates of SVP recidivism can be reached by considering three available pieces of data: (i) a likely recidivism rate of the general population of sex offenders; (ii) procedures typically followed by jurisdictions that civilly commit sex offenders; and (iii) classification accuracy of procedures. Although sexual recidivism rates vary across jurisdictions, the results of our analyses suggest sex offenders referred for examination pursuant to SVP statutes recidivate at substantially higher rates than typical sex offenders. Our results further suggest that sex offenders recommended for commitment as SVPs recidivate at even greater rates than SVP respondents who are not recommended for commitment. We discuss practice and policy implications of these findings.

Classification accuracy of actuarial risk assessment instruments.

Users of commonly employed actuarial risk assessment instruments (ARAIs) hope to generate numerical probability statements about risk; however, ARAI manuals often do not explicitly report data that are essential for understanding the classification accuracy of the instruments. In addition, ARAI manuals often contain data that have the potential for misinterpretation. The authors of the present article address the accurate generation of probability statements. First, they illustrate how the reporting of numerical probability statements based on proportions rather than predictive values can mislead users of ARAIs. Next, they report essential test characteristics that, to date, have gone largely unreported in ARAI manuals. Then they discuss a graphing method that can enhance the practice of clinicians who communicate risk via numerical probability statements. After the authors review several strategies for selecting optimal cut-off scores, they show how the graphing method can be used to estimate positive predictive values for each cut-off score of commonly used ARAIs, across all possible base rates. They also show how the graphing method can be used to estimate base rates of violent recidivism in local samples.

The relationship between trauma and violence in a jail inmate sample.

Research suggests there is a link between trauma and violence, although the nature of the relationship is rather equivocal. This study explored this relationship by examining self-reported trauma as a predictor of self-reported violence in 93 jail inmates. Ninety-six percent of the sample reported experiencing a traumatic event, and 67% reported having been violent during the year preceding incarceration. Inmates reporting trauma were more than twice as likely to report having been violent than nonviolent. Stepwise multiple regression analyses suggested traumatic events, as a combined model, significantly contributed to violence perpetration. In addition, witnessing serious violence predicted perpetration of violence. Implications and limitations of the present study are discussed.