Screening and Assessment: An Evidence-Based Process for the Management and Care of Adult Drug-Involved Offenders

Hiller, Matthew L.; Belenko, Steven; Welsh, Wayne N.; Zajac, Gary; Peters, Roger H.

doi:10.1007/978-1-4419-9470-7_4

Cited by 11 publications

(10 citation statements)

References 76 publications

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“…Although static factors are not directly amenable to change, criminogenic needs are. An application of this finding may be that assessment of risks and needs should continue, as indicated by the R-N-R model, from prison to community (see Hiller, Belenko, Welsh, Zajac, & Peters, 2011). Information from these assessments could be used to adjust reentry plans to emphasize the particular criminogenic needs evident for the individual.…”

Section: Discussionmentioning

confidence: 99%

Predicting Recidivism for Released State Prison Offenders

Stahler

Mennis

Belenko

et al. 2013

Criminal Justice and Behavior

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We examined the influence of individual and neighborhood characteristics and spatial contagion in predicting reincarceration on a sample of 5,354 released Pennsylvania state prisoners. Independent variables included demographic characteristics, offense type, drug involvement, various neighborhood variables (e.g., concentrated disadvantage, residential mobility), and spatial contagion (i.e., proximity to others who become reincarcerated). Using geographic information systems (GIS) and logistic regression modeling, our results showed that the likelihood of reincarceration was increased with male gender, drug involvement, offense type, and living in areas with high rates of recidivism. Older offenders and those convicted of violent or drug offenses were less likely to be reincarcerated. For violent offenders, drug involvement, age, and spatial contagion were particular risk factors for reincarceration. None of the neighborhood environment variables were associated with increased risk of reincarceration. Reentry programs need to particularly address substance abuse issues of ex-offenders as well as take into consideration their residential locations.

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Section: Discussionmentioning

confidence: 99%

Predicting Recidivism for Released State Prison Offenders

Stahler

Mennis

Belenko

et al. 2013

Criminal Justice and Behavior

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“…The interview records, among others, the parole candidate’s self-assessed mental health history. Additionally, the PBPP conducted an official assessment of risk for reoffending using the Level of Service Inventory-Revised (LSI-R) [73], a well-known, validated actuarial risk tool widely used in U.S. corrections and in many other western countries [74]. It is a 54-item interview that measures both criminogenic and non-criminogenic needs.…”

Section: Introductionmentioning

confidence: 99%

Mental Health Risk Factors and Parole Decisions: Does Inmate Mental Health Status Affect Who Gets Released

Houser

Vîlcică

Saum

et al. 2019

IJERPH

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Parole decision—the decision to release an incarcerated individual from prison conditionally—is one of the most critical decisions across justice systems around the world. The decision carries with it significant consequences: for the freedom of the individual awaiting release (the parolee); for the safety of the community in which they will return; and for the correctional system overall, especially its organizational capacity. The current study attempts to add to the parole decision-making literature by specifically analyzing the role that mental health factors may play in explaining parole decisions. Research to date is inconclusive on whether or not mental illness is a risk factor for criminal behavior; despite this, individuals with mental health problems generally fare worse on risk assessment tools employed in justice decisions. The study relies on a 1000+ representative sample of parole-eligible individuals in Pennsylvania, United States. To increase reliability, the analyses test for several mental health factors based on information from different sources (i.e., self-reported mental health history; risk assessment tool employed by the Parole Board; and risk assessment tool employed by the Department of Corrections). To address validity concerns, the study controls for other potential correlates of parole decisions. Although the multivariate models explained a considerable amount of variance in parole decisions, the inclusion of mental health variables added relatively little to model fit. The results provide insights into an understudied area of justice decision making, suggesting that despite the stigmatization of mental illness among criminal justice populations, parole board members in Pennsylvania, United States, appear to follow official guidelines rather than to consider more subjective notions that poor mental health should negate parole release.

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“…Measures that could be aggregated to the group level include those that directly measure the participant’s responses to treatment. Whether it is the REST, as used in this study and others (Hiller, Belenko, Welsh, Zajac, & Peters, 2011; Welsh, 2010), or other instruments that measure the individual’s experiences in treatment, the critical factor required to enable the study of group dynamics is that the compositional measures come from the treatment participants themselves. These are the measures best suited to quantitatively describe treatment group functioning and to use as level-2 predictors of individual behavior.…”

Section: Discussionmentioning

confidence: 99%

The Treatment Group and Recidivism: A Multilevel Analysis of Prison-Based Substance Abuse Treatment

2019

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This study contributes to the substance abuse treatment literature by examining recidivism across treatment groups, the level of aggregation between the individual and the program. The sample consisted of 618 drug-involved offenders who participated in 12 different treatment groups within a single prison. Reincarceration significantly varied across groups, controlling for time at risk and treatment modality. This between-unit variation was explained by individual level treatment response measures and control variables. Results demonstrated that treatment effectiveness is impacted by the group in which the individual participates. These findings have substantial implications for correctional treatment theory, research, and policy.

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Screening and Assessment: An Evidence-Based Process for the Management and Care of Adult Drug-Involved Offenders

Cited by 11 publications

References 76 publications

Predicting Recidivism for Released State Prison Offenders

Predicting Recidivism for Released State Prison Offenders

Mental Health Risk Factors and Parole Decisions: Does Inmate Mental Health Status Affect Who Gets Released

The Treatment Group and Recidivism: A Multilevel Analysis of Prison-Based Substance Abuse Treatment

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