scholarly journals The Study on the Key Factors of Recidivism Rates of Sex Offenders under Electronic Monitoring Program

2016 ◽  
Vol 28 (2) ◽  
pp. 139-165
Author(s):  
조윤오
Keyword(s):  
Sex Offenders ◽  
Electronic Monitoring ◽  
Monitoring Program ◽  
Key Factors ◽  
Recidivism Rates

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.

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).

Comparing the Central Eight Risk Factors: Do They Differ Across Age Groups of Sex Offenders?

2018 ◽  
Vol 62 (13) ◽  
pp. 4278-4294 ◽  
Author(s):  
Julia Wilpert ◽  
Joan E. van Horn ◽  
Cyril Boonmann
Keyword(s):  
Risk Factors ◽  
Sex Offenders ◽  
Behavioral Therapy ◽  
Age Groups ◽  
Recidivism Rates ◽  
Dynamic Risk Factors ◽  
Rnr Model ◽  
Risk Need Responsivity ◽  
Reducing Recidivism ◽  
General Recidivism

Following the risk-need-responsivity (RNR) model, cognitive-behavioral therapy is considered most effective in reducing recidivism when based on dynamic risk factors. As studies have found differences of these factors across age, exploring this seems beneficial. The current study investigates the Central Eight (C8) risk factors across six age groups of outpatient sex offenders ( N = 650). Results showed that recidivism rates and age were inversely related from 19 years and up. Half of the C8 did not predict general recidivism at all, substance abuse, antisocial cognition, antisocial associates, and history of antisocial behavior in only one or several age groups. However, factors differed between age groups, with the youngest group demonstrating the most dysfunction in several areas and the oldest group the least. It is concluded that the C8 risk factors seem to lose significance in the older age groups. Results may benefit targeting treatment goals.

Megan’s Law 20 Years Later: An Empirical Analysis and Policy Review

2018 ◽  
Vol 45 (7) ◽  
pp. 1028-1046 ◽  
Author(s):  
Kristen M. Zgoba ◽  
Wesley G. Jennings ◽  
Laura M. Salerno
Keyword(s):  
Sex Offenders ◽  
Sex Offender ◽  
Risk Group ◽  
High Risk Group ◽  
Regression Equations ◽  
Megan's Law ◽  
Multivariate Logistic Regression ◽  
Recidivism Rates ◽  
Before And After ◽  
General Recidivism

This present study examines the sexual and general recidivism rates of 547 convicted sex offenders released before and after the enactment of Megan’s Law in New Jersey. Presenting the longest Megan’s Law evaluation, participants were followed for an average of 15 years after release (range = 10-29 years). Bivariate and multivariate logistic regression equations were estimated to identify covariates significantly associated with both sexual and general recidivism. Group-based trajectories of general recidivism within the 10 years post–prison release were also estimated and compared according to pre–Megan’s Law and post–Megan’s Law release status. No differences in recidivism rates were noted between the cohorts, but differences emerged in the offending trajectories of the high-risk group of offenders within 10 years of release. These results highlight the lack of impact that sex offender registration and notification (SORN) laws have on sexual and general reoffending rates postrelease.

Similar Predictive Accuracy of the Static-99R Risk Tool for White, Black, and Hispanic Sex Offenders in California

2017 ◽  
Vol 44 (9) ◽  
pp. 1125-1140 ◽  
Author(s):  
Seung C. Lee ◽  
R. Karl Hanson
Keyword(s):  
Sex Offenders ◽  
Ethnic Groups ◽  
Predictive Validity ◽  
Sex Offender ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Cultural Bias ◽  
Recidivism Rates ◽  
Assessment Procedures

Although considerable research has found overall moderate predictive validity of Static-99R, a sex offender risk prediction tool, relatively little research has addressed its potential for cultural bias. This prospective study evaluated the predictive validity of Static-99R across the three major ethnic groups (White, n = 789; Black, n = 466; Hispanic, n = 719) in the state of California. Static-99R was able to discriminate recidivists from nonrecidivists among White, Black, and Hispanic sex offenders (all area under the curve [AUC] values >.70; odds ratios >1.39). Base rates (at a Static-99R score of 2) with a fixed 5-year follow-up across ethnic groups were very similar (2.4%-3.0%) but were significantly lower than the norms (5.6%). The current findings support the use of Static-99R in risk assessment procedures for sex offenders of White, Black, and Hispanic heritage, but it should be used with caution in estimating absolute sexual recidivism rates, particularly for Hispanic sex offenders.

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