Although individuals with a history of sexual crime are often viewed as a lifelong risk, recent research has drawn attention to consistent declines in recidivism risk for those who remain offense free in the community. Because these declines are predictable, this article demonstrates how evaluators can use the amount of time individuals have remained offense free to (a) extrapolate to lifetime recidivism rates from rates observed for shorter time periods, (b) estimate the risk of sexual recidivism for individuals whose current offense is nonsexual but who have a history of sexual offending, and (c) calculate yearly reductions in risk for individuals who remain offense free in the community. In addition to their practical utility for case-specific decision making, these estimates also provide researchers an objective, empirical method of quantifying the extent to which individuals have desisted from sexual crime.

Undetected sexual offending creates challenges for risk assessment since estimated sexual recidivism rates are based on documented charges or convictions. Courts and other stakeholders may be primarily interested in the true risk for sexual reoffense and not simply risk for detected sexual offenses. Attempts to study and quantify the rate of undetected sexual offending have resulted in a wide variety of estimates. In this study, we explore whether sanctions imposed for detected sexual offenses increase the detection rate of subsequent offenses, and thereby suppress undetected sexual offending in an exceptionally high-risk sample who were ultimately committed as Sexually Violent Persons. Results indicate the detection rate of sexual offenses increased following an initial sanction, subsequently decreasing the proportion of undetected to detected offending. This effect only occurred after the first sanction. Overall, the sample had a high detection rate and spent little time in the community before subsequent arrests. These results differ from other reports that high rates of sexual offenses go undetected.

The present study features the development of new risk categories and recidivism estimates for the Violence Risk Scale (VRS), a violence risk assessment and treatment planning tool. We employed a combined North American multisite sample (k = 6, N = 1,338) of adult mostly male offenders, many with violent criminal histories, from correctional or forensic mental health settings that had complete VRS scores from archival or field ratings and outcome data from police records (N = 1,100). There were two key objectives: (a) to identify the rates of violent recidivism associated with VRS scores and (b) to generate updated evidence-based VRS violence risk categories with external validation. To achieve the first objective, logistic regression was applied using VRS pretreatment and change scores on treated samples with a minimum 5-year follow-up (k = 5, N = 472) to model 2-, 3-, and 5-year violent and general recidivism estimates, with the resulting logistic regression algorithms retained to generate a VRS recidivism rates calculator. To achieve the second objective, the Council of State Governments' guidelines were applied to generate five risk levels using the common language framework using percentiles, risk ratios (from Cox regression), and absolute violent and general recidivism estimates (from logistic regression). Construct validity of the five risk levels was examined through group comparisons on measures of risk, need, protection, and psychopathy obtained from the constituent samples. VRS applications to enhance risk communication, treatment planning, and violence prevention in light of the updated recidivism estimates and risk categories are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Vitamin D status may be important for stress resilience. This study investigated the effects of vitamin D supplements during winter on biological markers of stress resilience such as psychophysiological activity, serotonin, and cortisol in a placebo-controlled, randomized clinical trial. Eighty-six participants were randomly assigned to the Intervention (vitamin D) or Control (placebo) groups. Before and after the intervention participants were exposed to an experimental stress procedure. Psychophysiological activity was measured during three main conditions: baseline, stress, and recovery. Fasting blood samples were taken in the morning and saliva samples were collected at seven different time points across 24 h. Prior to intervention both groups had normal/sufficient vitamin D levels. Both groups showed a normal pattern of psychophysiological responses to the experimental stress procedure (i.e., increased psychophysiological responses from resting baseline to stress-condition, and decreased psychophysiological responses from stress-condition to recovery; all p < 0.009). Post-intervention, the Intervention group showed increased vitamin D levels (p < 0.001) and normal psychophysiological responses to the experimental stress procedure (p < 0.001). Importantly, the Control group demonstrated a classic nadir in vitamin D status post-intervention (spring) (p < 0.001) and did not show normal psychophysiological responses. Thus, physiologically the Control group showed a sustained stress response. No significant effects of vitamin D were found on serotonin and cortisol.

This study aimed to gain deeper knowledge about the relationship between vitamin D and physical activity in a sample of forensic inpatients. Sixty-seven male forensic inpatients participated. Participants were randomly assigned into an Intervention group (vitamin D) or a Control group (placebo). The Physical Activity–Rating (PA-R) questionnaire was used to measure physical activity from January to May. Vitamin D status was measured as 25-hydroxy vitamin D (25-OHD) pre- and post-intervention. The results revealed that vitamin D status at post-test was positively correlated with physical activity, but there was no effect of vitamin D supplementation looking at the two randomized groups. However, controlling for body mass index (BMI), the results showed an effect of BMI and a main effect of groups with a higher level of physical activity in the Intervention group. No interaction effects were found. Participants were also assigned into High and Low vitamin D groups based on the vitamin D status at post-test; i.e., the upper (75.1 nmol/L) and lower quartile (46.7 nmol/L). T-tests revealed that participants with a vitamin D status above 75 nmol/L showed significantly higher levels of physical activity than participants with a vitamin D status below 46.7 nmol/L. Thus, a vitamin D status above 75 nmol/L seems to be an optimal level.