Despite the high prevalence of traumatic brain injuries (TBI), there are few rapid and straightforward tests to improve its assessment. To this end, we developed a tablet-based software battery ("BrainCheck") for concussion detection that is well suited to sports, emergency department, and clinical settings. This article is a study of the diagnostic accuracy of BrainCheck. We administered BrainCheck to 30 TBI patients and 30 pain-matched controls at a hospital Emergency Department (ED), and 538 healthy individuals at 10 control test sites. We compared the results of the tablet-based assessment against physician diagnoses derived from brain scans, clinical examination, and the SCAT3 test, a traditional measure of TBI. We found consistent distributions of normative data and high test-retest reliability. Based on these assessments, we defined a composite score that distinguishes TBI from non-TBI individuals with high sensitivity (83%) and specificity (87%). We conclude that our testing application provides a rapid, portable testing method for TBI.

This study analyzes the law enforcement response to prostitution in Houston, Texas, between 1977 and 2010 to examine whether the traditional approach to policing prostitution disproportionately penalizes women. Data included the disposition and sentencing information for 22,916 first-time prostitution arrests in Harris County. Using bivariate and multivariate analyses, we explored gender differences in the likelihood of receiving punishment, the type(s) of punishment received, and the amount of punishment for first-time prostitution offenses. We find that women were disproportionately arrested for prostitution and that women were more likely to receive a jail sentence for involvement in prostitution than men were. In contrast, male arrestees for prostitution were more likely to receive probation sentences and/or fines. This study adds to a robust body of literature suggesting that gender impacts sentencing in the criminal justice system. Yet, it is unclear whether the role of the arrestee—as either a buyer or seller—moderates the effect of gender. This quandary demonstrates the need for more comprehensive data collection about the role of the arrestee in the commercial sexual exchange.

We seek to address current limitations of forensic risk assessments by introducing the first mobile, self-scoring, risk assessment software that relies on neurocognitive testing to predict reoffense. This assessment, run entirely on a tablet, measures decision-making via a suite of neurocognitive tests in less than 30 minutes. The software measures several cognitive and decision-making traits of the user, including impulsivity, empathy, aggression, and several other traits linked to reoffending. Our analysis measured whether this assessment successfully predicted recidivism by testing probationers in a large urban city (Houston, TX, United States) from 2017 to 2019. To determine predictive validity, we used machine learning to yield cross-validated receiveroperator characteristics. Results gave a recidivism prediction value of 0.70, making it comparable to commonly used risk assessments. This novel approach diverges from traditional self-reporting, interview-based, and criminal-records-based approaches, and can also add a protective layer against bias, while strengthening model accuracy in predicting reoffense. In addition, subjectivity is eliminated and time-consuming administrative efforts are reduced. With continued data collection, this approach opens the possibility of identifying different levels of recidivism risk, by crime type, for any age, or gender, and seeks to steer individuals appropriately toward rehabilitative programs. Suggestions for future research directions are provided.

Risk assessment has become a prominent part of the criminal justice system in many jurisdictions, typically relying on structured questions and an interview. This approach, however, may not accurately assess certain psychological concepts correlated with reoffense, such as executive functioning, ability to plan, impulse control, risk-taking, aggression, and empathy. We hypothesized that using rapid-tablet-based neurocognitive tests would pay off in terms of objectivity, precision, and scalability when added to the existing risk assessment structure. We analyzed 240 observations from adult felony offenders from a large urban county in the South assessed by the Texas version of the Ohio Risk Assessment System (ORAS) risk tool. We identified significant differences in impulse control, planning, and reactive aggression between offenders and reoffenders. By combining these variables with the Texas Risk Assessment System (TRAS), we yielded significant improvements in risk prediction. We hope this will provide new inroads for actuarial assessments of reoffense risk that incorporate direct measurements of individual decision making.

According to conservative estimates, the country spends a minimum of $25,500-$26,000 per year on each person incarcerated [1]. Incarceration also has long-term costs for both offenders and society. For example, a young person with a prison record may be precluded from becoming a citizen who votes, participates in community-building, and contributes to the community. Someone's re-offending (i.e., in the case of recidivism, defined broadly as re-offending with any jailable offense) means social resources were squandered without rehabilitating the offender (i.e., without resulting in future behavior for which one could be arrested). Unfortunately, the United States has high rates of recidivism: two separate Bureau of Justice Statistics studies have found that more than 62 percent of offenders released from prison are rearrested within three years [2, 3]. Society thus achieves minimal rewards in return for its costly expenses, because nearly two-thirds of convicts reoffend and return to the criminal justice system.