Dataset Information

Assessing Risk Among Correctional Community Probation Populations: Predicting Reoffense With Mobile Neurocognitive Assessment Software.

ABSTRACT: 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 receiver-operator 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.

SUBMITTER: Haarsma G

PROVIDER: S-EPMC6992536 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Assessing Risk Among Correctional Community Probation Populations: Predicting Reoffense With Mobile Neurocognitive Assessment Software.

Haarsma Gabe G Davenport Sasha S White Devonte C DC Ormachea Pablo A PA Sheena Erin E Eagleman David M DM

Frontiers in psychology 20200124

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. ...[more]

PMID: 32038355

Similar Datasets

Project description:BackgroundVisuospatial dysfunction and cognitive impairment are common in Parkinson's disease (PD), which draw increasing attention in the current literature. But clinicians still lack rapid, effective and unified cognitive battery for visuospatial assessment.ObjectiveA new approach was studied to explore the feasibility of using mobile application software (APP) to evaluate visuospatial dysfunction in patients with PD and compared with traditional assessment tools. We aimed to verify the threshold score of the APP for early diagnosis.Materials and methodsA total of 41 patients with PD underwent assessments using several test modules including Digit Symbol Test (DST), Visual Organization Test (VOT), Facial Recognition Test (FRT), Vocabulary Memory Test (VMT) of this APP, as well as Clock Drawing Test (CDT), Cube Copying Test (CCT) and the Mini-Mental State Examination (MMSE) for comparison. Among the 41 PD patients, 30 individuals were found to have visuospatial dysfunction based on CDT score < 5 and CCT score of<18 while the remaining 11 patients served as control.ResultsThere were statistically significant differences in DST, VOT, and FRT scores (all p ≤ 0.001 for group comparisons). DST, VOT, and FRT-1 were significantly correlated with MMSE, CDT and CCT and the correlations were moderate or fairly strong. For visuospatial dysfunction diagnosis, all the areas under curves (AUC) of DST, VOT, and FRT-1 were statistically significant (p < 0.0001, p = 0.0002, and p = 0.0002, respectively). The estimates and 95% confidence intervals of AUC were 0.8303 (0.6868, 0.9739), 0.8045 (0.6423, 0.9668), and 0.7833 (0.6344, 0.9322), respectively. Their cut-off points for visuospatial dysfunction were 26, 17, and 19, respectively. After dichotomization by the cut-off points, DST had high sensitivity of 96.67% while VOT and FRT-1 had high specificity of 81.82 and 90.91%.ConclusionThis study demonstrated that visuospatial disorders was highly prevalent in PD patients, and the APP used in study could be a practical clinical screening tool for visuospatial ability assessment with high sensitivity and specificity.

Project description:ImportanceProbation is a cornerstone of efforts to reduce mass incarceration. Although it is understudied, specialty probation could improve outcomes for the overrepresented group of people with mental illness.ObjectiveTo test whether specialty probation yields better public safety outcomes than traditional probation.Design, setting, and participantsA longitudinal observational study with group matching on age, sex, race/ethnicity, probation time, and offense at 2 urban agencies that exemplify specialty and traditional probation. Enrollment began October 19, 2005; follow-up data were complete January 26, 2013. Participants were 359 diverse probationers with serious mental health problems and functional impairment. Probationers and officers were assessed 3 times (for probationers, 6-month retention, 315 of 359 [88%]; 12-month retention 304 of 359 [85%]) and follow-up records were obtained. Machine learning algorithms were combined with a targeted maximum likelihood estimation, a double robust estimator that accounts for associations between confounders and both treatment assignment and outcomes. Statistical analysis was conducted from January 1, 2016 to May 5, 2017.InterventionsSpecialty probationers were assigned to small, homogeneous caseloads supervised by experts. Prior data indicate that specialty officers had better relationships with probationers, participated more in probationers' treatment, and relied more on positive compliance strategies than traditional officers.Main outcomes and measuresViolence during 1 year, determined by probationer report, officer report, and records, and rearrest during a period of 2 to 5 years, according to Federal Bureau of Investigation records.ResultsParticipants were 183 specialty (73.8% of 248 eligible) and 176 traditional (56.6% of 311 eligible) probationers (205 men and 154 women; mean [SD] age, 36.9 [10.6]). Although specialty probation had no significant effect on violence (odds ratio, 0.97; 95% CI, 0.69-1.36), the odds of rearrest were 2.68 times higher for traditional probationers than for specialty probationers (95% CI, 1.86-3.84; P?<?.001). At 2 years, estimated probabilities of rearrest were 28.6% for specialty probationers and 51.8% for traditional probationers. Survival analyses indicate that arrest effects endured up to 5 years.Conclusions and relevanceAlthough it did not specifically reduce violence, well-implemented specialty probation appears to be effective in reducing general recidivism. Reform efforts for people with mental illness could leverage probation-a ubiquitous and revitalized node of the justice system.

Dataset Information

Assessing Risk Among Correctional Community Probation Populations: Predicting Reoffense With Mobile Neurocognitive Assessment Software.

Publications

Assessing Risk Among Correctional Community Probation Populations: Predicting Reoffense With Mobile Neurocognitive Assessment Software.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets