Actuarial risk assessment scales and their associated recidivism estimates are generally developed on samples of offenders whose average age is well below 50 years. Criminal behavior of all types declines with age; consequently, actuarial scales tend to overestimate recidivism for older offenders. The current study aimed to develop a revised scoring system for two risk assessment tools (Static-99 and Static-2002) that would more accurately describe older offenders' risk of recidivism. Using data from 8,390 sex offenders derived from 24 separate samples, age was found to add incremental predictive validity to both Static-99 and Static-2002. After creating new age weights, the resulting instruments (Static-99R and Static-2002R) had only slightly higher relative predictive accuracy. The absolute recidivism estimates, however, provided a substantially better fit for older offenders than the recidivism estimates from the original scales. We encourage evaluators to adopt the revised scales with the new age weights.

The current meta-analysis compared the characteristics of online child pornography-only offenders, typical (offline) sex offenders against children, and offenders with both child pornography and contact sex offences against children (mixed). Based on 30 unique samples (comparison ns ranging from 98 to 2,702), the meta-analysis found key differences between groups. Offenders who committed contact sex offences were more likely to have access to children than those with only child pornography offences. In contrast, offenders who used the internet to commit sexual offences had greater access to the internet than those with contact sex offenders. Differences between the groups, however, were not limited to differential opportunities. Sex offenders against children and mixed offenders were found to score higher on indicators of antisociality than online child pornography offenders (CPOs). CPOs were also more likely to have psychological barriers to sexual offending than sex offenders against children and mixed offenders (e.g., greater victim empathy). Mixed offenders were found to be the most pedophilic, even more than CPOs. The findings suggest that offenders who restricted their offending behavior to online child pornography offences were different from mixed offenders and offline sex offenders against children, and that mixed offenders were a particularly high risk group.

Empirical actuarial risk tools are routinely used to assess the recidivism risk of adult sexual offenders. Compared with other forms of risk assessment, one advantage of actuarial risk tools is that they provide recidivism rate estimates. Previous research, however, suggests that there is considerable variability in the recidivism rates associated with the most commonly used sexual offender risk assessment tools (Static-99/R, Static-2002/R). The current study examined the extent to which the variability in the recidivism rates across 21 Static-99R studies (N = 8,805) corresponded to the normative groups proposed by the STATIC development group (routine, treatment, high risk/high need). We found strong evidence that routine (i.e., complete) samples were, on average, less likely to reoffend with a sexual offense than offenders in the high-risk/high-need samples (i.e., those explicitly preselected on risk-relevant variables external to STATIC scales). The differences between routine/complete and high-risk/high-need samples, however, were only consistently observed for offenders with low or moderate scores; for offenders with high STATIC scores, the 5-year sexual recidivism rates for these two groups were not meaningfully different. There was only limited evidence to support treatment samples as a distinct sample type; consequently, the use of separate normative tables for treatment samples is not recommended. The current results reinforce the value of regularly updating the norms for empirical actuarial risk tools. Options are discussed on how STATIC scores could be used to inform recidivism rates estimates in applied assessments.

There is much concern about the likelihood that online sexual offenders (particularly online child pornography offenders) have either committed or will commit offline sexual offenses involving contact with a victim. This study addresses this question in two meta-analyses: the first examined the contact sexual offense histories of online offenders, whereas the second examined the recidivism rates from follow-up studies of online offenders. The first meta-analysis found that approximately 1 in 8 online offenders (12%) have an officially known contact sexual offense history at the time of their index offense (k = 21, N = 4,464). Approximately one in two (55%) online offenders admitted to a contact sexual offense in the six studies that had self-report data (N = 523). The second meta-analysis revealed that 4.6% of online offenders committed a new sexual offense of some kind during a 1.5- to 6-year follow-up (k = 9, N = 2,630); 2.0% committed a contact sexual offense and 3.4% committed a new child pornography offense. The results of these two quantitative reviews suggest that there may be a distinct subgroup of online-only offenders who pose relatively low risk of committing contact sexual offenses in the future.

There is much debate as to whether online offenders are a distinct group of sex offenders or if they are simply typical sex offenders using a new technology. A meta-analysis was conducted to examine the extent to which online and offline offenders differ on demographic and psychological variables. Online offenders were more likely to be Caucasian and were slightly younger than offline offenders. In terms of psychological variables, online offenders had greater victim empathy, greater sexual deviancy, and lower impression management than offline offenders. Both online and offline offenders reported greater rates of childhood physical and sexual abuse than the general population. Additionally, online offenders were more likely to be Caucasian, younger, single, and unemployed compared with the general population. Many of the observed differences can be explained by assuming that online offenders, compared with offline offenders, have greater self-control and more psychological barriers to acting on their deviant interests.

There has been considerable research on relative predictive accuracy (i.e., discrimination) in offender risk assessment (e.g., Are high-risk offenders more likely to reoffend than low-risk offenders?), but virtually no research on the accuracy or stability of absolute recidivism estimates (i.e., calibration). The current study aimed to fill this gap by examining absolute and relative risk estimates for certain Static sex offender assessment tools. Logistic regression coefficients for Static-99R and Static-2002R were combined through meta-analysis (8,106 sex offenders; 23 samples). The sexual recidivism rates for typical sex offenders are lower than the public generally believes. Static-99R and Static-2002R both demonstrated remarkably consistent relative predictive accuracy across studies. For both scales, however, the predicted recidivism rates within each Helmus et al. / ABSOLUTE RECIDIVISM RATES 1149 risk score demonstrated large and significant variability across studies. The authors discuss how the variability in recidivism rates complicates the estimation of recidivism probability in applied assessments.

The pervasiveness of risk assessment in correctional decision-making necessitates a better understanding of the nature of risk scales and the methods used to assess their accuracy. Risk is a continuous dimension, which means that risk assessment is a prognostic task as opposed to a diagnostic task. Risk scales can also be considered criterion-referenced as opposed to norm-referenced. Predictive accuracy can be divided into discrimination and calibration. Area under the curves (AUCs), Cox regression, Harrell’s C, Cohen’s d, and logistic regression are appropriate for analyses of discrimination. There is no consensus on calibration statistics, but both chi-square tests and the Expected/Observed (E/O) index have been used and show promise. Statistics intended for dichotomous diagnostic decisions (e.g., positive predictive accuracy and negative predictive accuracy, number needed to detain, number needed to discharge) are inappropriate for risk scales because of the prognostic nature of risk scales. In many circumstances, diagnostic statistics provide more information about the base rate of recidivism than about the risk scale.

This article describes principles for developing risk category labels for criterion referenced prediction measures, and demonstrates their utility by creating new risk categories for the Static-99R and Static-2002R sexual offender risk assessment tools. Currently, risk assessments in corrections and forensic mental health are typically summarized in 1 of 3 words: low, moderate, or high. Although these risk labels have strong influence on decision makers, they are interpreted differently across settings, even among trained professionals. The current article provides a framework for standardizing risk communication by matching (a) the information contained in risk tools to (b) a broadly applicable classification of "riskiness" that is independent of any particular offender risk scale. We found that the new, common STATIC risk categories not only increase concordance of risk classification (from 51% to 72%)-they also allow evaluators to make the same inferences for offenders in the same category regardless of which instrument was used to assign category membership. More generally, we argue that the risk categories should be linked to the decisions at hand, and that risk communication can be improved by grounding these risk categories in evidence-based definitions. (PsycINFO Database Record