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.
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.
Recidivism places a significant burden on society and efforts aimed at reducing cyclical criminal justice involvement are needed. This prospective study tested the utility of psychopathic traits in predicting general, felony, and substance-related rearrest in women following release from a correctional facility. The extent to which psychopathic traits offered incremental utility in predicting outcomes, above and beyond other established risk factors, including substance use disorder, was examined. Participants included 327 incarcerated adult women who completed comprehensive clinical and psychiatric assessments prior to release from correctional facilities. Psychopathic traits and lifetime substance use disorder were measured using the Hare Psychopathy Checklist-Revised (PCL-R) and Structured Clinical Interview for DSM-IV-TR Axis I Disorders, respectively. Results showed that general, felony, and substance-related rearrest following institutional release were associated with higher PCL-R Factor 2 scores, assessing lifestyle/behavioral and antisocial/developmental psychopathic traits. Additionally, when controlling for other risk factors associated with recidivism, including age at release, number of prior adult prison terms, and substance use disorder, higher PCL-R Factor 2 scores remained significantly associated with rearrest outcomes in women. Findings inform risk prediction and treatment efforts aimed at reducing recidivism in justice-involved women.
I Braathen LR, Botten (i, Bjerkedal. I'soriatics in Norway: a questiolnniaire study on health statits, contact with paramedical professions, and alcohol and tobacco consutnption. Acta Dernt l'eereol (Stockh) 1989;suppl 142: 9-12. 2 Chaput J-C, Poynard 'T, Naveau S, Pettso 1), I)urrmever 0. Suplissotn 1). Psoriasis, alcotiol, attd liter disease. BrMcd 7 1985;291:25. 3-indegard B. Diseases associated with psoriasis itt a general population of 159200 middle-aged, urbain, native Swedes. 1)ertnatologica 1986;172: 298-304.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.