This article presents the results of a meta-analysis of the existing research literature, in an effort to increase our understanding of the prevalence of domestic violence (DV) among pregnant women, and of risk factors associated with DV during pregnancy. Across 92 independent studies, the average reported prevalence of emotional abuse was 28.4%, physical abuse was 13.8%, and sexual abuse was 8.0%. Composite odds ratio effect sizes were calculated for the demographic, behavioral, and social risk factors identified by 55 independent studies. Both victimization and perpetration risk factors were analyzed. Abuse before pregnancy and lower education level were found to be strong predictors of abuse during pregnancy. Pregnancy being unintended by either the victim or the perpetrator, lower socioeconomic status, and being unmarried were found to be moderate predictors of abuse during pregnancy.

This random assignment study compared female offenders (n = 468) with substance use disorders in a prison therapeutic community program with those in a cognitive-behavioral intervention. The study demonstrates that all women benefitted from gender-sensitive prison treatment, but the therapeutic community was more effective in reducing drug use, criminal activity, and exposure to trauma and increasing mental health functioning and time until reincarceration during the year after prison. In addition, the ability to sustain and even improve behavior change after the women leave prison highlights the importance of providing accessible community-based continuity of mental health and substance abuse services during reentry.

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Each year many offenders are released homeless putting them at great risk of being returned to prison. To reduce the likelihood of recidivism, Washington State implemented the Reentry Housing Pilot Program (RHPP) to provide housing assistance for high risk/high need offenders leaving prison without a viable place to live. This study provides a longitudinal (2008-2011), multisite outcome evaluation that considers how ex-offenders in the RHPP program (n = 208), who were provided housing and wraparound services, compared with similar offenders released with an elevated risk of homelessness while being traditionally supervised (n = 208). Findings show that the RHPP program was successful in significantly reducing new convictions and readmission to prison for new crimes, but had no significant effect on revocations. In addition, results showed that periods of homelessness significantly elevated the risk of recidivism for new convictions, revocations, and readmission to prison. The authors recommend that subsidized housing for high risk offenders become a central part of coordinated responses to reentry.

Objectives The purpose of the present meta-analysis was to answer the question: Can the Andrews principles of risk, needs, and responsivity, originally developed for programs that treat offenders, be extended to programs that treat drug abusers? Methods Drawing from a dataset that included 243 independent comparisons, we conducted random-effects meta-regression and ANOVA-analog meta-analyses to test the Andrews principles by averaging crime and drug use outcomes over a diverse set of programs for drug abuse problems. Results For crime outcomes, in the meta-regressions the point estimates for each of the principles were substantial, consistent with previous studies of the Andrews principles. There was also a substantial point estimate for programs exhibiting a greater number of the principles. However, almost all of the 95% confidence intervals included the zero point. For drug use outcomes, in the meta-regressions the point estimates for each of the principles was approximately zero; however, the point estimate for programs exhibiting a greater number of the principles was somewhat positive. All of the estimates for the drug use principles had confidence intervals that included the zero point. Conclusions This study supports previous findings from primary research studies targeting the Andrews principles that those principles are effective in reducing crime outcomes, here in meta-analytic research focused on drug treatment programs. By contrast, programs that follow the principles appear to have very little effect on drug use outcomes. Primary research studies that experimentally test the Andrews principles in drug treatment programs are recommended.

Objectives Recent evolutions in actuarial research have revealed the potential increased utility of machine learning and data-mining strategies to develop statistical models such as classification/decision-tree analysis and neural networks, which are said to mimic the decision-making of practitioners. The current article compares such actuarial modeling methods with a traditional logistic regression risk-assessment development approach. Methods Utilizing a large purposive sample of Washington State offenders (N= 297,600), the current study examines and compares the predictive validity of the currently used Washington State Static Risk Assessment (SRA) instrument to classification tree analysis/random forest and neural network models. Results Overall findings varied, being dependent on the outcome of interest, with the best model for each method resulting in AUCs ranging from 0.732 to 0.762. Findings reveal some predictive performance improvements with advanced machine-learning methodologies, yet the logistic regression models demonstrate comparable predictive performance.Conclusions The study concluded that while data-mining techniques hold potential for improvements over traditional methods, regression-based models demonstrate comparable, and often improved, prediction performance with noted parsimony and greater interpretability.

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This study examines the relationship between psychiatric symptoms and violent/disruptive behavior among 192 inmates who participated in prison-based substance abuse treatment. Participants came from two sites able to provide narrative reports of disciplinary actions in the Criminal Justice Drug Abuse Treatment Studies' Co-Occurring Disorders Screening Instrument study. In multivariate logistic models, a lifetime history of thought insertion/control ideation (OR, 11.6; 95% CI, 1.8-75.2), antisocial personality disorder (OR, 3.3; 95% CI, 1.2-8.9), and disciplinary action related to possession of controlled substances or contraband (OR, 4.9; 95% CI, 1.9-12.3) were associated with increased risk for violent or disruptive behavior while in prison, whereas lifetime phobic symptoms (OR, 0.2; 95% CI, 0.1-0.54) and high school graduation (OR, 0.4; 95% CI, 0.2-1.0) were associated with a decreased risk of violence and disruptive behavior in general. We conclude that, among inmates in substance abuse treatment, symptoms that increase risk for violence or disruptive behavior include thought control/insertion ideation and disciplinary infractions related to controlled substances, contraband, or failure to participate in assigned programs, as well a history of antisocial personality disorder.