The 2015 Static-99R: Alternative Recidivism Tables for High-Risk Offenders

2016 ◽  
Vol 61 (14) ◽  
pp. 1593-1605 ◽  
Author(s):  
Richard W. Elwood ◽  
Sharon M. Kelley ◽  
James C. Mundt
Keyword(s):  
High Risk ◽  
Sex Offenders ◽  
Confidence Intervals ◽  
Sexual Recidivism ◽  
Viable Option ◽  
Recidivism Rates ◽  
Sexually Violent ◽  
Male Sex ◽  
Sexually Violent Person ◽  
Male Sex Offenders

The Static-99R is an actuarial scale that is commonly used to assess the recidivism risk of male sex offenders. Hanson, Thornton, Helmus, and Babchishin recently revised the Static-99R norms based on revised analyses that excluded the large Bridgewater sample. As a result, the sample size of the high risk/high need (HR/HN) group was reduced substantially, which increased the confidence intervals around the predicted recidivism rates. This study provides alternative 5- and 10-year recidivism rates based on logistic regression analyses of the entire 2009 Static-99R HR/HN group that includes the Bridgewater sample. These rates fit the observed 2009 data well and have smaller confidence intervals. We propose that using alternative sexual recidivism rates from the 2009 HR/HN group is a viable option for assessing sexually violent person (SVP) and other high-risk offenders.

Predictive Validity of the Static-99 and Static-99R in Switzerland

Sexual Abuse ◽  
2019 ◽  
Vol 32 (2) ◽  
pp. 203-219
Author(s):  
Leonel C. Gonçalves ◽  
Juliane Gerth ◽  
Astrid Rossegger ◽  
Thomas Noll ◽  
Jérôme Endrass
Keyword(s):  
Sex Offenders ◽  
Predictive Validity ◽  
Risk Category ◽  
Average Risk ◽  
Sexual Recidivism ◽  
Sexual Offenses ◽  
Cut Score ◽  
Male Sex ◽  
Male Sex Offenders

This study evaluated the validity of the Static-99 and Static-99R in assessing sexual recidivism in Switzerland, based on a sample of 142 male sex offenders. Both tools showed predictive validity, but the Static-99R had better discrimination (OR = 1.82, AUC = .81) and calibration (Brier = .078, P/E = 0.96) than the Static-99. A cut score of four on the Static-99R maximized sensitivity (92.9%) and specificity (60.2%). However, although most offenders (98.7%) with a score < 4 did not commit sexual offenses in the 5-year follow-up period, only one in five (20.3%) offenders with a score ≥ 4 actually recidivated. Furthermore, the predicted number of recidivists in the well above average risk category (Static-99R ≥ 6) was 24% higher than expected in routine samples. The results suggest that the Static-99R may be a useful screening tool to identify low-risk individuals but offenders with scores ≥ 4 should be subjected to a more thorough assessment.

Understanding the Journeys of High-Risk Male Sex Offenders Voluntarily Receiving Medication to Reduce Their Sexual Preoccupation and/or Hypersexuality

2014 ◽  
pp. 342-370 ◽  
Author(s):  
Belinda Winder ◽  
Rebecca Lievesley ◽  
Helen Jane Elliott ◽  
Christine Norman ◽  
Adarsh Kaul
Keyword(s):  
High Risk ◽  
Sex Offenders ◽  
Male Sex ◽  
Male Sex Offenders

The Co-morbidity of Pedophilia and Zoophilia in Male Sex Offenders

2000 ◽  
Author(s):  
Ronna J. Dillinger ◽  
Susan L. Amato ◽  
Kelly Hardy
Keyword(s):  
Sex Offenders ◽  
Co Morbidity ◽  
Male Sex ◽  
Male Sex Offenders

Male Sex Offenders

1990 ◽  
pp. 271-290 ◽  
Author(s):  
Gene G. Abel ◽  
Joanne-L. Rouleau
Keyword(s):  
Sex Offenders ◽  
Male Sex ◽  
Male Sex Offenders

Using Logistic Regression Modeling to Predict Sexual Recidivism

Sexual Abuse ◽  
2012 ◽  
Vol 24 (4) ◽  
pp. 350-377 ◽  
Author(s):  
Grant Duwe ◽  
Pamela J. Freske
Keyword(s):  
Logistic Regression ◽  
Sex Offenders ◽  
Sex Offender ◽  
Assessment Tools ◽  
Sexual Recidivism ◽  
Recidivism Rates ◽  
Contemporary Sample ◽  
Sex Offender Risk Assessment ◽  
Likelihood Model ◽  
High Level

This study presents the results from efforts to revise the Minnesota Sex Offender Screening Tool–Revised (MnSOST-R), one of the most widely used sex offender risk-assessment tools. The updated instrument, the MnSOST-3, contains nine individual items, six of which are new. The population for this study consisted of the cross-validation sample for the MnSOST-R ( N = 220) and a contemporary sample of 2,315 sex offenders released from Minnesota prisons between 2003 and 2006. To score and select items for the MnSOST-3, we used predicted probabilities generated from a multiple logistic regression model. We used bootstrap resampling to not only refine our selection of predictors but also internally validate the model. The results indicate the MnSOST-3 has a relatively high level of predictive discrimination, as evidenced by an apparent AUC of .821 and an optimism-corrected AUC of .796. The findings show the MnSOST-3 is well calibrated with actual recidivism rates for all but the highest risk offenders. Although estimating a penalized maximum likelihood model did not improve the overall calibration, the results suggest the MnSOST-3 may still be useful in helping identify high-risk offenders whose sexual recidivism risk exceeds 50%. Results from an interrater reliability assessment indicate the instrument, which is scored in a Microsoft Excel application, has an adequate degree of consistency across raters (ICC = .83 for both consistency and absolute agreement).

scholarly journals Evaluating Selection for Sexually Violent Predator Commitment: A Comparison of Those Committed, Not Committed, and Nearly Committed

2020 ◽  
Author(s):  
Anthony Perillo ◽  
Cynthia Calkins ◽  
Elizabeth Jeglic
Keyword(s):  
Risk Scores ◽  
Sexual Recidivism ◽  
Multinomial Regression ◽  
Recidivism Rates ◽  
Sexually Violent Predator ◽  
Sexual Offenses ◽  
Empirically Supported ◽  
Historical Factors ◽  
Sexually Violent ◽  
Selection For

We examined state-wide data of persons evaluated for Sexually Violent Predator (SVP) commitment and compared risk-relevant data of three groups: those committed as SVPs ( n = 374), those not recommended for commitment ( n = 2,707), and those nearly committed (recommended for commitment but ultimately not committed; n = 117). Consistent with legal language for SVP commitment, binary and multinomial regression analyses revealed risk scores predicted SVP commitment recommendations in addition to some historical factors (e.g., psychiatric history, never being married, prior sex offenses). For those recommended for commitment, prior sexual offenses predicted ultimate commitment. Those nearly committed had significantly higher sexual recidivism rates than others who were not committed; however, these recidivism rates were still low (11.5%). Findings suggest evaluators’ SVP decisions incorporate risk data and follow empirically supported trends; however, the observed recidivism rates of a subset of those SVP commitment appears to target suggests SVP commitment’s potential for reducing sexual recidivism effectively and efficiently appears to have a low ceiling.

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