The home-field advantage and the perils of professional judgment: Evaluating the performance of the Static-99R and the MnSOST-3 in predicting sexual recidivism

Betting Against the Odds: The Mysterious Case of the Clinical Override in Risk Assessment of Adult Convicted Offenders

Various tools were designed to guide practitioners in the risk assessment of offenders, including the Level of Service and Case Management Inventory (LS/CMI). This instrument is based on risk assessment principles prioritizing the actuarial approach to clinical judgment. However, the tool's architects allowed subjective judgment from the practitioners-referred to as clinical override-to modify an offender's risk category under certain circumstances. Few studies, however, have examined these circumstances. Therefore, the current study used decision tree analyses among a quasi-population of Quebec offenders (n = 15,744) to identify whether there are offenders more likely to be subjected to this discretion based on their characteristics. The results suggest that, although the override is rare, it occurred under few specific combinations of circumstances. More precisely, these findings propose that the utilization of the clinical override stems from a perceived discrepancy between risk prediction and management.

Forensic application of static and dynamic risk factors: Is it the right time?

It is common, accepted clinical practice to conduct risk assessments of individuals who commit sexual offenses using the combination of sexual violence risk actuarial measures and dynamic risk factors. This assessment approach has utility when identifying treatment targets, assessing progress in sexual offender treatment, and forming risk management plans. Little research has examined this method in forensic contexts such as deciding whether individuals who suffer from mental disorders are likely to engage in sexually dangerous behavior as defined by sexually violent predator or persons (“SVP”) involuntary civil confinement laws in the USA. In particular, it is uncertain whether the combination of sexual violence risk actuarial measures and dynamic risk factors (DRF) produces sufficiently reliable, relevant, and probative evidence for the trier of fact to properly evaluate the SVP legally defined likelihood of sexual dangerousness. This article explores the efficacy of combining actuarial measures of sexual violence risk and dynamic risk factors as applied in SVP risk assessments based on some commonly observed forensic practices among evaluators. Based on the analysis, recommendations for forensic practice and future research are offered.

Testing the Static-99R as a Global Screen for Risk of Sex Crime Recidivism in a Norwegian Routine Sample

The Static-99R has been recommended for use as a first global screen for sorting out sex-convicted persons who are in need of further risk assessment. This study investigated the Static-99R's predictive validity based on a nonselected Norwegian sample (n = 858) of persons released from prison after having served a sex crime sentence. After a mean observation period of 2,183 days, 3.4% (n = 29) had recidivated to a new sex offense. A higher number of recidivists were found among those with higher Static-99R total scores. The predictive contribution from each of the ten Static-99R risk items was investigated using standard logistic regression, proportional hazard regression, and random forest classification algorithm. The overall results indicate that the Static-99R is relevant as a risk screen in a Norwegian context, providing similar results concerning predictive accuracy as previous studies.

Estimating the probability of sexual recidivism among men charged or convicted of sexual offences: Evidence-based guidance for applied evaluators

Risk assessment is routinely applied in forensic decision-making. Although relative risk information from risk scales is robust across diverse samples and settings, estimates of the absolute probability of sexual recidivism are not. Nonetheless, absolute recidivism estimates are still necessary in some evaluations. This paper summarizes research and offers guidance on evidence-based practices for assessing the probability of recidivism, organized largely around questions commonly asked in court. Overall, estimating the probability of sexual recidivism is difficult and should be undertaken with humility and circumspection. That being said, research favours empirical-actuarial risk tools for this task, more structured scales, and the use of multiple scales. Professional overrides of risk scale results should not be used under any circumstances. Paradoxically, however, professional judgement is still required in some circumstances. Risk scales do not consider all relevant risk factors, but the added value of external risk factors reaches a point of diminishing returns and may or may not be incremental (or worse, can degrade accuracy). There are reasons actuarial risk scales may both underestimate recidivism (e.g., undetected offending, short follow-ups) and overestimate recidivism (e.g., inclusion of sex offences not of interest in some referral questions, data on declining crime and recidivism rates, newer studies demonstrating overestimation of recidivism). Given all these considerations and the need for humility, in the absence of exceptional circumstances, I would not deviate too far from empirical estimates.

Illuminating the dark figure of sexual recidivism

Detected or reported ("observed") rates of sexual reoffending have long been recognized as underestimating the occurrence of actual sexual recidivism. Past attempts to bridge the gap between the two rates have been unsuccessful. Scurich and John try to reverse this course by presenting a simulation model to estimate the predicted actual sexual recidivism rates among individuals convicted of sexual offenses based on three parameters; they also apply these data to calibrate the sexual recidivism rates from four sexual recidivism studies. The accuracy of the predicted actual sexual recidivism rates is wholly dependent upon the reliability of the inputs to the model. This analysis relies upon scientific studies and literature to delve into the precision of the parameters of Scurich and John in relation to the accuracy of their predicted actual sexual recidivism rates and the validity of the calibration process. The results reveal that some of the assumptions by Scurich and John about the parameters are supported empirically, while others are not. Overall, the simulation model parameters suffer from significant deficiencies that likely produce inaccurate predicted actual sexual recidivism rates. Moreover, the methodologies of the comparison studies used in the calibration process do not actually meet the requirements of the analytic strategy of Scurich and John, which effectively invalidates their findings. Until computational strategies are employed that account for linear and nonlinear effects of model parameters, closing the gap between observed and actual sexual recidivism rates will remain elusive.

Risk assessment tool floundering? Let's ask the client to self-predict

Self-prediction by criminal justice involved clients has not been typically implemented in risk assessment procedures, yet clients have unique self-knowledge that may add to the assessment of risk. The Transition Inventory is an eight scale self-prediction measure that addresses areas that are a precursor to antisocial and criminal activity (e.g., "Drugs or alcohol will be a problem for me"). The Transition Inventory was administered to 131 paroled clients (primary drug-related offenses), 104 of whom were of minority/ethnic status. Predictive validity was demonstrated by the Transition Inventory incrementally predicting supervision failure. Individual scale construct validity was demonstrated by predicting later assessed corresponding measures, with the Leisure scale having the most robust predictive relationship. Self-prediction may promote greater predictability and stronger client engagement in the assessment process.