Psychopathy Profiles and Personality Assessment Inventory Scores in a Sex Offender Risk Assessment Field Setting

A growing body of research suggests there are identifiable psychopathy subtypes among offenders scored on Hare’s Psychopathy Checklist–Revised (PCL-R; Hare, 2003). We used latent profile analysis to examine the generalizability of these subtype findings to PCL-R scores ( N = 615) assigned in a sex offender risk assessment field setting and to examine how offender subtypes differ on measures of comorbid psychopathology, risk, and treatment amenability from the Personality Assessment Inventory. Consistent with prior research, we identified four subtypes when using PCL-R scores from all offenders: Prototypic psychopathy ( n = 239, 38.9%), callous-conning ( n = 154, 25.0%), sociopathic ( n = 96, 15.6%), and general offenders ( n = 126, 20.5%). Prototypic and sociopathic subtypes exhibited the highest levels of comorbid psychopathology and risk for potential violence. We identified classes consistent with primary ( n = 66, 36.7%) and secondary ( n = 114, 63.3%) psychopathy among offenders with PCL-R total scores ≥ 25, and found higher levels of comorbid psychopathology and potential for violence among those in the secondary psychopathy class. Findings provide support the generalizability of existing PCL-R subtype findings to field scores and show how those with similar PCL-R total scores may differ on scores from commonly used multiscale inventories.

Updating Probability in Sex Offender Risk Assessment

Actuarial scales like the Static-99R are widely used to predict an individual’s risk of sexual recidivism. However, current actuarial scales only provide rates of detected sex offenses over 10-year follow-up and do not account for all recidivism risk factors. Therefore, some forensic evaluators extrapolate, adjust, or override recidivism rates derived from actuarial scales to predict the lifetime risk of committed offenses that accounts for external risk factors, those not addressed by the actuarial scales. However, critics contend that altering rates from actuarial scales degrades their predictive validity. This article makes the case for extrapolating risk for time of exposure and for evidence-based external risk factors. It proposes using odds ratios (ORs) from case-control studies to adjust predictions from follow-up cohort studies. Finally, it shows how evaluators can apply ORs and their margins of error to sex offender risk assessment.

Calculating Probability in Sex Offender Risk Assessment

Risk is the probability of an adverse event or outcome. In a previous article, I compared the Bayesian and Frequentist models of defining probability. This article compares the Bayesian and regression models of quantifying probability. Both approaches are widely used in the biomedical and behavioral sciences even though they yield different results. No consensus has emerged as to which is more appropriate. The choice between them remains controversial. This article concludes that the Bayesian model provides a viable alternative to logistic regression and may be more useful in quantifying the absolute recidivism risk of individual sex offenders. It shows how evaluators can easily calculate Bayesian probabilities and their associated credible intervals from an actuarial data set. Last, the article proposes a forensic practice guideline that evaluators do not conclude that an offender meets an absolute risk threshold unless the subject’s risk exceeds the threshold by a credible margin of error.