A Bayesian Analysis of a Cognitive-Behavioral Therapy Intervention for High-Risk People on Probation.

This analysis employs a Bayesian framework to estimate the impact of a Cognitive-Behavioral Therapy (CBT) intervention on the recidivism of high-risk people under community supervision. The study relies on the reanalysis of experimental datal using a Bayesian logistic regression model. In doing so, new estimates of programmatic impact were produced using weakly informative Cauchy priors and the Hamiltonian Monte Carlo method. The Bayesian analysis indicated that CBT reduced the prevalence of new charges for total, non-violent, property, and drug crimes. However, the effectiveness of the CBT program varied meaningfully depending on the participant's age. The probability of the successful reduction of drug offenses was high only for younger individuals (<26 years old), while there was an impact on property offenses only for older individuals (>26 years old). In general, the probability of the successful reduction of new charges was higher for the older group of people on probation. Generally, this study demonstrates that Bayesian analysis can complement the more commonplace Null Hypothesis Significance Test (NHST) analysis in experimental research by providing practically useful probability information. Additionally, the specific findings of the reestimation support the principles of risk-needs responsivity and risk-stratified community supervision and align with related findings, though important differences emerge. In this case, the Bayesian estimations suggest that the effect of the intervention may vary for different types of crime depending on the age of the participants. This is informative for the development of evidence-based correctional policy and effective community supervision programming.

Finding blood in the dark: A comparison of infrared imaging devices for the detection of bloodstains on dark fabrics based on their resolution.

The use of infrared (IR) light to locate bloodstains on dark fabric is a search technique that is employed in forensic examinations in a number of organisations worldwide. IR is used to complement existing, established visual white light search techniques. There exist a variety of commercially available products that can be purchased for this purpose as well as the option of using IR-converted standard DSLR (Digital Single Lens Reflex) cameras. In this study, a number of IR systems with contrasting resolutions were explored and their performance was assessed on a variety of bloodstain types and fabrics in comparison with white light. The systems ranged from low-budget, low resolution options, such as portable webcams, to vision-industry standard, high resolution, purpose-built cameras for more detailed blood searching of suitable items in the laboratory. Blood spatter, transfer bloodstains, dilute bloodstains, blood mixed with other body fluids and environmental contaminants were among the samples tested on eight different dark fabric types under IR conditions to assess the impact of the resolution differences. All IR systems were able to locate bloodstains, with significantly more bloodstains being found with IR compared to white light. The higher resolution systems were able to locate significantly more bloodstains than the systems with the lower resolution. The webcams were able to locate many of the larger areas of bloodstaining but performed less well in terms of locating smaller bloodstains and dilute blood. False positives such as mud, make-up and brown sauce were detected under IR but were readily discriminated under white light and with presumptive chemical tests. The balance between the ability to locate bloodstains based on system resolution and practicality and possible efficiency gains is discussed.

Breath tests in Western Australia: Examining the economic dividends and effectiveness of general deterrence.

In this paper, we examine the relationship between traffic enforcement (in the form of roadside breath testing for alcohol) and traffic outcomes (alcohol-related traffic crashes) to identify an optimal point of traffic enforcement. In Western Australia (WA), Police are authorised to stop any driver and measure their blood alcohol concentration via a sample of their breath. Using a metric employed by Ferris et al. (2013) and a methodology analogous to that utilised by Cameron (2013), we model the relationship between alcohol related traffic crashes and the saturation of breath testing in WA from January 2008 to April 2018. Our analysis suggests that given the saturation of breath testing in 2018 (1.2 tests per licenced driver), a 10 % increase in breath testing would be associated with a decline of 0.34 alcohol related traffic crashes (ARTC) per 100,000 drivers per month, equating to six fewer crashes per month, state-wide. In addition, using 'willingness to pay' and human capital cost metrics to approximate the social costs of ARTC, we employ a cost-benefit analysis to estimate the point at which the social costs of ARTC equal the economic costs of breath tests. Our analysis suggests that an increase in the number of tests to 143 % of all licensed WA drivers (an increase of 450,000 breath tests from the 2017/18 financial year) would be anticipated to save the state AUD$13.3 million annually in the human capital costs of ARTC. Our findings suggest that a further increase in breath tests to 154% of all licensed WA drivers (an increase of 650,000 breath tests from 2017/18) may save the state AUD$31.0 million annually in willingness to pay costs. The analytics below present a novel combination of methods to approximate the relative economic merits of increases in traffic enforcement. Furthermore, the findings outlined here have practical applications for operational policing, while providing an analytical perspective for policy makers faced with making recommendations regarding the volume and saturation of breath tests.

The impact of residential change and housing stability on recidivism: pilot results from the Maryland Opportunities through Vouchers Experiment (MOVE).

OBJECTIVES: This article provides a description and preliminary assessment of the Maryland Opportunities through Vouchers Experiment (MOVE), a randomized housing mobility program for former prisoners designed to test whether residential relocation far away from former neighborhoods, incentivized through the provision of a housing subsidy, can yield reductions in recidivism. METHODS: The MOVE program was implemented as a randomized controlled trial. Participants were recruited from four different Maryland prisons and randomly assigned to experimental groups. In the first iteration of the experiment, treatment group participants received 6 months of free housing away from their home jurisdiction and control group participants received free housing back in their home jurisdiction. In the second iteration of the experiment, the treatment group remained the same and the control condition was redesigned to represent the status quo and did not receive free housing. Analyses were conducted of one-year rearrest rates. RESULTS: With respect to reductions in recidivism, pilot results suggest that there is some benefit to moving and a benefit to receiving free housing. Rearrest was lower among the treatment group of movers than the non-movers, and was also lower for non-movers who received free housing versus non-movers who did not receive housing. CONCLUSIONS: To the extent that pilot results can be validated and replicated in a full-scale implementation of the MOVE program, policies that provide greater access to housing assistance for formerly incarcerated individuals may yield substantial public safety benefits, particularly housing opportunities located far away from former neighborhoods.