The Impact of Risk Assessment on Juvenile Justice Decision-Making and New Adjudication: An Analysis of Usage and Outcome

• Author: Jamie Newsome,Melissa Lugo,Amber A. Petkus,Christopher J. Sullivan
• Published date: 01 April 2022
• DOI: 10.1177/15412040211061270
• Date: 01 April 2022
• Subject Matter: Articles

Article

Youth Violence and Juvenile Justice

2022, Vol. 20(2) 139–163

© The Author(s) 2021

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DOI: 10.1177/15412040211061270

journals.sagepub.com/home/yvj

The Impact of Risk Assessment

on Juvenile Justice

Decision-Making and New

Adjudication: An Analysis of

Usage and Outcome

Amber A. Petkus

1

, Christopher J. Sullivan

2

, Melissa Lugo

3

, and

Jamie Newsome

4

Abstract

Juvenile risk and needs assessments (JRNAs) have been the focus of extensive research in the

academic literature. Prior studies have primarily focused on the risk-recidivism relationship and

establishing predictive validity with juvenile populations. Less investigated is the use of risk and

need assessment in practice, including how such tools are used to inform decision-makin g. This

study uses record data encompassing 3,034 youth from a multi-state study to examine dispo-

sitional and treatment decisions associated with the Ohio Youth Assessment System (OYAS).

Specif‌ically, mediation analyses were conducted to evaluate how current practices align with

underlying logic and theory regarding the role of assessments in juvenile justice. Findings reveal

varied and complex relationships between assessment scores, case decisions, and recidivism.

While risk was generally associated with recidivism, our results suggest juvenile risk and need

assessments are inconsistently used to inform case management and placement decisions. Im-

plications for practice and future research are also discussed.

Keywords

Juvenile Justice, Mediation, Risk Assessment, Risk-Needs-Responsivity, Ohio Youth Assessment

System (OYAS), Youth, Delinquency, Disposition, Treatment

1

School of Criminal Justice, University of Cincinnati, Cincinnati, OH, USA

2

School of Criminal Justice and Criminology, Texas State University, San Marcos, TX, USA

3

North Carolina Sentencing and Policy Advisory Commission, Raleigh, NC, USA

4

University of Cincinnati Corrections Institute, Cincinnati, OH, USA

Corresponding Author:

Amber Petkus, School of Criminal Justice, University of Cincinnati, 660F Teachers-Dyer Complex, 2610 McMicken Circle,

Cincinnati, OH 45221, USA.

Email: petkusam@ucmail.uc.edu

Every year, close to one million youths are processed through the contemporary juvenile justice

system (Sickmund et al., 2019), and likely encounter some type of structured risk assessment

(Wachter,2015). Juvenile risk and needs assessments (JRNAs) are intended to classify individuals

into groups based on the likelihood that they will reoffend (e.g., low, moderate, and high risk) and

identify needs to target in treatment to reduce individual risk of continued delinquency (Bonta &

Andrews, 2017). The success of this strategy hinges on both the validity of the assessment tools

used and the integration of assessment information into case management. Prior studies suggest

that when implemented correctly, risk assessment tools can increase practitioner ability to ac-

curately anticipate recidivism outcomes in comparison to clinical judgments (Andrews et al.,

2006;Hilterman et al., 2014;Olver et al., 2009).

Researchinvolving juveniles indicatesthat modern risk assessmentsare capable of differentiating

between those who will reoffend and those who will not (Duwe & Rocque, 2017). However, the

extent to which information collected in JRNAs is used to guide case decision-making remains an

understudiedarea of research. Assessments can be viewed as the f‌irst stepin an appropriatejuvenile

justice response with subsequent steps involving the use of JRNA information to better inform

decisions about placement and supervision levels in the disposition process and route youths to

appropriatetreatment. While the breadthof existing risk–recidivismstudies suggest that assessments

are regularlycompleted, there is a shortage ofstudies that investigate their impactas theorized. That

theory suggests that disposition and service receipt should serve as a conduit for the relationship

between risk and needs assessment scores and recidivism. In this study, we utilize data from two

states, including more than 40 agencies and 3000 individual cases, to consider the degree to which

JRNAs are integrated in the juvenile justice process.

Literature Review

Aligning routine operations in juvenile justice agencies with evidence-based practices has pri-

marily involved implementing the risk–need–responsivity (RNR) model (Bonta & Andrews,

2017). The model includes three principles that, when fully adhered to in practice, results in the

greatest reductions in recidivism (Smith et al., 2009). These are risk, need, and responsivity.

The risk principle directs that those services should be based on the individuals’risk of re-

offending. The need principle states that the most effective interventions will address one’s

criminogenic needs or factors, that have been empirically linked with criminal and delinquent

behavior. The responsivity principle stresses that intervention and treatment strategies should be

delivered using cognitive behavioral and social learning methods to maximize their effectiveness

and tailored to individual traits and barriers (specif‌ic responsivity) (Bonta & Andrews, 2017).

Research suggeststhat classifying and assigningoffenders to programming followingthe principles

outlined in the RNR model can reduce the risk of recidivism (Andrews & Bonta, 2010;Bonta &

Andrews, 2017;Latessa et al., 2014); however, the RNR approach cannot be put into practice

without the abilityto determine risk and needs in a validand reliable way (Andrews & Bonta, 2010;

Duwe & Rocque, 2017). JRNAs are meant to serve this role in juvenile justice practice.

Predictive Validity and Variability in the Risk–Recidivism Relationship

As JRNAs have been more widely adopted, studies have investigated the strength of their

predictive validity. In his meta-analysis of 42 predictive validity studies including 28 risk as-

sessments, Schwalbe (2007) indicated that validated JRNAs predict youths’recidivism signif-

icantly better than chance (AUC = 0.64) and have a moderate effect size (r=.25) similar to those

found with meta-analyses of adult risk assessments (e.g., Gendreau et al., 1996). Though estimates

of JRNA effectiveness can vary across different risk assessment tools, as well as across studies

140 Youth Violence and Juvenile Justice 20(2)