A Validation Study of the Child Pornography Offender Risk Tool (CPORT)

Sexual Abuse ◽  
2018 ◽  
Vol 31 (4) ◽  
pp. 456-476 ◽  
Author(s):  
Angela W. Eke ◽  
L. Maaike Helmus ◽  
Michael C. Seto
Keyword(s):  
Statistical Power ◽  
Predictive Accuracy ◽  
Sexual Offending ◽  
Child Pornography ◽  
Area Under The Curve ◽  
Risk Assessments ◽  
Sexual Offense ◽  
Sexual Recidivism ◽  
Development And Validation

The Child Pornography Offender Risk Tool (CPORT) is a seven-item structured tool to assess the likelihood of future sexual offending over a 5-year fixed follow-up. The current study examined 5-year fixed follow-up data (15% any new sexual offense, 9% any new child pornography offense) for a validation sample of 80 men convicted of child pornography offense(s). Although statistical power was low, results were comparable with the development sample: The CPORT had slightly lower predictive accuracy for sexual recidivism for the overall group (area under the curve [AUC] = .70 vs. .74), but these values were not significantly different. Combining the development and validation samples, the CPORT predicted any sexual recidivism (AUC = .72) and child pornography recidivism specifically (AUC = .74), with similar accuracies. CPORT was also significantly predictive of these outcomes for the child pornography offenders with no known contact offenses. Strengths and weaknesses of incorporating CPORT into applied risk assessments are discussed.

The Predictive Validity of the Static-99, Static-99R, and Static-2002/R: Which One to Use?

Sexual Abuse ◽  
2017 ◽  
Vol 30 (8) ◽  
pp. 887-907 ◽  
Author(s):  
Sophie G. Reeves ◽  
James R. P. Ogloff ◽  
Melanie Simmons
Keyword(s):  
Decision Making ◽  
Predictive Validity ◽  
Sexual Offenders ◽  
Predictive Accuracy ◽  
Risk Measures ◽  
Sexual Offending ◽  
Area Under The Curve ◽  
Sexual Recidivism ◽  
Sexual Offenses ◽  
Risk Categories

The use of Static tools (Static-99, Static-99R, Static-2002, and Static-2002R) in risk decision making involving sexual offenders is widespread internationally. This study compared the predictive accuracy and incremental validity of four Static risk measures in a sample of 621 Australian sexual offenders. Results indicated that approximately 45% of the sample recidivated (with 18.8% committing sexual offenses). All of the Static measures investigated yielded moderate predictive validity for sexual recidivism, which was comparable with other Australian and overseas studies. Area under the curve (AUC) values for the four measures across the 5-, 10-, and 15-year intervals ranged from .67 to .69. All of the Static measures discriminated quite well between low-risk and high-risk sexual offenders but less well for the moderate risk categories. When pitted together, none of the tools accounted for additional variance in sexual recidivism, above and beyond what the other measures accounted for. The overall results provide support for the use of Static measures as a component of risk assessment and decision making with Australian sexual offending populations. The limitations of this study and recommendations for further research are also discussed.

A Preliminary Analysis of Sexual Recidivism and Predictive Validity of the Static-99R in Men Discharged From State Hospitals Pursuant to California’s Sexually Violent Predator Act

Sexual Abuse ◽  
2021 ◽  
pp. 107906322110197
Author(s):  
Allen Azizian ◽  
Mark E. Olver ◽  
James Rokop ◽  
Deirdre M. D’Orazio
Keyword(s):  
Predictive Validity ◽  
Area Under The Curve ◽  
Sexual Offense ◽  
Sexual Recidivism ◽  
Recidivism Rates ◽  
Sexually Violent Predator ◽  
State Hospitals ◽  
Sexually Violent ◽  
General Recidivism

We examined the recidivism rates and the predictive validity of the Static-99R in 335 men who were detained or civilly committed and released from California State Hospitals pursuant to the Sexually Violent Predator (SVP) Act, and followed up for approximately 21 years from date of hospital admission. In all, 8.7% were arrested or convicted for a new sexual offense during the total follow-up ( N = 335) and 7.8% over a fixed 5-year follow-up ( n = 205). The Static-99R demonstrated small in magnitude discrimination for sexual, violent, and general recidivism (area under the curve [AUC]/C = .56 to .63). Calibration analyses, conducted through expected/observed (E/O) index, demonstrated that the Static-99R overpredicted sexual recidivism, irrespective of whether the Routine or High Risk/Need norms were used. Observed recidivism rates were lower than predicted by Static-99R scores and may be the result of the sample’s older age at release, lengthy hospitalization, or other factors.

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.

scholarly journals Development and Validation of a Simplified Risk Score for the Prediction of Critical COVID-19 Illness in Newly Diagnosed Patients

2021 ◽  
Author(s):  
Stanislas Werfel ◽  
Carolin E. M. Jakob ◽  
Stefan Borgmann ◽  
Jochen Schneider ◽  
Christoph Spinner ◽  
...  
Keyword(s):  
Critical Illness ◽  
Clinical Decision Making ◽  
Validation Cohort ◽  
Predictive Accuracy ◽  
Clinical Decision ◽  
Increased Risk ◽  
Risk Of Progression ◽  
Risk Of Disease ◽  
Development And Validation

AbstractScores for identifying patients at high risk of progression of the coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), are discussed as key instruments for clinical decision-making and patient management during the current pandemic.Here we used the patient data from the multicenter Lean European Open Survey on SARS-CoV-2 - Infected Patients (LEOSS) and applied a technique of variable selection in order to develop a simplified score to identify patients at increased risk of critical illness or death.A total of 1,946 patients, who were tested positive for SARS-CoV-2 were included in the initial analysis. They were split into a derivation and a validation cohort (n=1,297 and 649, respectively). A stability selection among a total of 105 baseline predictors for the combined endpoint of progression to critical phase or COVID-19-related death allowed us to develop a simplified score consisting of five predictors: CRP, Age, clinical disease phase (uncomplicated vs. complicated), serum urea and D-dimer (abbreviated as CAPS-D score). This score showed an AUC of 0.81 (CI95%: 0.77-0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (CI95%: 0.77-0.85) during the full follow-up. Finally, we used an additional prospective cohort of 682 patients, who were diagnosed largely after the “first wave” of the pandemic to validate predictive accuracy of the score, observing similar results (AUC for an event within 7 days: 0.83, CI95%, 0.78-0.87; for full follow-up: 0.82, CI95%, 0.78-0.86).We thus successfully establish and validate an easily applicable score to calculate the risk of disease progression of COVID-19 to critical illness or death.

Comparing Predictive Validity of JSORRAT-II and MEGA♪ With Sexually Abusive Youth in Long-Term Residential Custody

2017 ◽  
Vol 62 (10) ◽  
pp. 2937-2953 ◽  
Author(s):  
Lucinda A. Lee Rasmussen
Keyword(s):  
Risk Assessment ◽  
Area Under The Curve ◽  
Assessment Tools ◽  
Sexual Recidivism ◽  
Residential Treatment Facility ◽  
Sexually Abusive ◽  
Risk Assessment Tools ◽  
Representative Samples

This 6-year prospective study is the first to compare two psychometrically sound risk assessment tools for sexually abusive youth: JSORRAT-II and MEGA♪. Cross-validated on representative samples of over 500 youth, these measures have cutoff scores, allowing for a more exact assessment of risk. Study sample consisted of 129 male adjudicated adolescents housed in a secured residential treatment facility for sexually abusive youth. Receiver operating characteristic (ROC) analysis showed that MEGA♪ Risk Scale was mildly predictive of sexual recidivism over a 6-year period (mean follow-up = 15.6 months)—area under the curve (AUC) = .67; 95% confidence interval [CI] = [0.52, 0.82]; p < .015. JSORRAT-II was not predictive (AUC = .57; 95% CI = [0.42, 0.72]; p < .297). The study contributes to scant literature on the most contemporary, statistically robust risk assessment tools for sexually abusive youth.

scholarly journals Development and validation of the Beliefs about Revenge Pornography Questionnaire

2020 ◽  
Author(s):  
Craig A. Harper ◽  
Lorraine Smith ◽  
Jessie Leach ◽  
Neil Daruwala ◽  
Dean Fido
Keyword(s):  
Concurrent Validity ◽  
Sexual Offending ◽  
Community Sample ◽  
Psychological Research ◽  
Rape Myth ◽  
Sexual Offense ◽  
Just World ◽  
Future Directions ◽  
Sexual Crime ◽  
Development And Validation

Revenge pornography has become an increasingly prominent topic in social and legislative discussions about sexual crime, but has received relatively little attention within psychological research. Here, we leveraged existing theorizing in the area of sexual offending proclivity to systematically develop and validate of a measure of beliefs about revenge pornography. Using a large international community sample (N = 511) we found our ‘Beliefs about Revenge Pornography Questionnaire (BRPQ)’ to be comprised of three underpinning domains: ‘Victims as Responsible’, ‘Sociological Explanations’, and ‘Revenge Pornography as a Sexual Offense’. Concurrent validity is demonstrated through relationships with trait empathy, belief in a just world, dark personality traits, and rape myth acceptance. Randomly dividing the sample, we also show that the BRPQ predicts both revenge pornography proclivity (n = 227) and social judgements of this type of offending (n = 233). Implications and future directions are discussed.

scholarly journals A cluster analytic examination and validation of adult victim sexual offending subtypes in two Canadian samples

2021 ◽  
Vol 16 ◽  
Author(s):  
John-Etienne Myburgh ◽  
Mark E. Olver
Keyword(s):  
Sexual Offending ◽  
External Validation ◽  
Cluster Solution ◽  
Sexual Offense ◽  
Violence Risk ◽  
Case Formulation ◽  
Two Samples ◽  
High Base ◽  
Cluster Analytic ◽  
Development And Validation

The development and validation of sexual offense perpetrator typologies remains a useful endeavor with implications for theory and correctional/clinical practice. Most such typologies—which rely on factors such as the individual’s motivation for offending—have not been validated empirically. The current study utilized a validated sexual violence risk-needs instrument, the Violence Risk Scale—Sexual Offense version (VRS-SO; Wong, Olver, Nicholaichuk, & Gordon [2003, 2017], Regional Psychiatric Centre and University of Saskatchewan, Saskatoon, Canada), to develop and validate an empirically-derived adult victim sexual offense (AVSO) typology through model-based cluster analysis of dynamic risk-need domains. The study featured two treated samples of men (n = 283 and 169) convicted for contact sexual offenses against adult victims. A three-cluster solution was identified and replicated across the two samples: high antisociality high deviance (HA-HD), high antisociality low deviance (HA-LD), and low antisociality low deviance (LA-LD). External validation analyses demonstrated that HA-HD men had more dense sexual offense histories, were more likely to be diagnosed with a paraphilia, and had the highest rates of sexual recidivism (Sample 2 only). By contrast, the HA-LD men had greater concerns on indexes of nonsexual criminality, particularly high base rates of antisocial personality and substance use disorders, and high rates of general violent recidivism (particularly Sample 1). The findings suggest that the VRS-SO factors may have utility in discriminating between AVSO types to inform sexual offending theory, case formulation, and risk management.

STABLE-2007 Demonstrates Predictive and Incremental Validity in Assessing Risk-Relevant Propensities for Sexual Offending: A Meta-Analysis

Sexual Abuse ◽  
2019 ◽  
pp. 107906321987157 ◽  
Author(s):  
Andrew E. Brankley ◽  
Kelly M. Babchishin ◽  
R. Karl Hanson
Keyword(s):  
Risk Assessment ◽  
Sexual Offending ◽  
Meta Analysis ◽  
Incremental Validity ◽  
Sexual Offense ◽  
Adult Males ◽  
Sexual Recidivism ◽  
Assessment Practice

STABLE-2007 is a measure of risk-relevant propensities for adult males convicted of a sexual offense. This meta-analysis evaluated the ability of STABLE-2007 and its items to discriminate between recidivists and nonrecidivists, and the extent to which STABLE-2007 improves prediction over and above Static-99R. Based on 21 studies (12 unique samples, N = 6,955), we found that STABLE-2007 was significantly and incrementally related to sexual recidivism, violent (nonsexual) recidivism, violent (including sexual) recidivism, and any crime. Scores on STABLE-2007 items and the three STABLE-2000 attitude items also discriminated between individuals who sexually reoffended and those who did not sexually reoffend. These findings support the use of STABLE-2007 in applied risk assessment practice and the interpretation of STABLE-2007 items as indicators of treatment and supervision targets.

Predicting Sexual Recidivism

Sexual Abuse ◽  
2019 ◽  
Vol 32 (4) ◽  
pp. 375-399 ◽  
Author(s):  
Turgut Ozkan ◽  
Stephen J. Clipper ◽  
Alex R. Piquero ◽  
Michael Baglivio ◽  
Kevin Wolff
Keyword(s):  
Risk Assessment ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Sexual Recidivism ◽  
Florida Department ◽  
Forest Models ◽  
Random Forest Models ◽  
Sex Offense ◽  
Official Records

The current study focuses on adolescents with sex offense histories and examines sexual reoffending patterns within 2 years of a prior sex offense. We employed inductive statistical models using archival official records maintained by the Florida Department of Juvenile Justice (FDJJ), which provides social, offense, placement, and risk assessment history data for all youth referred for delinquent behavior. The predictive accuracy of the random forest models is tested using receiver operator characteristic (ROC) curves, the area under the curve (AUC), and precision/recall plots. The strongest predictor of sexual recidivism was the number of prior felony and misdemeanor sex offenses. The AUC values range between 0.71 and 0.65, suggesting modest predictive accuracy of the models presented. These results parallel the existing literature on sexual recidivism and highlight the challenges associated with predicting sex offense recidivism. Furthermore, results inform risk assessment literature by testing various factors recorded by an official institution.

Predictive Power of Dynamic (vs. Static) Risk Factors in the Finnish Risk and Needs Assessment Form

2019 ◽  
Vol 46 (7) ◽  
pp. 939-960 ◽  
Author(s):  
Benny Salo ◽  
Toni Laaksonen ◽  
Pekka Santtila
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Needs Assessment ◽  
Predictive Power ◽  
Area Under The Curve ◽  
Risk Assessments ◽  
Machine Learning Methods ◽  
Violent Recidivism ◽  
Static Risk

We estimated the predictive power of the dynamic items in the Finnish Risk and Needs Assessment Form ( Riski- ja tarvearvio [RITA]), assessed by caseworkers, for predicting recidivism. These 52 items were compared to static predictors including crime(s) committed, prison history, and age. We used two machine learning methods (elastic net and random forest) for this purpose and compared them with logistic regression. Participants were 746 men who had and 746 who had not reoffended during matched follow-up periods from 0.5 to 5.8 years. Both RITA items and static predictors predicted general and violent recidivism well (area under the curve [AUC] = .74-.78), but to combine them increased discrimination only slightly over static predictors alone (ΔAUC = .01-.03). Calibration was good for all models. We argue that the results show strong potential for the RITA items, but that development is best focused on improving usability for identifying treatment targets and for updating risk assessments.

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