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

AuthorJamie Newsome,Melissa Lugo,Amber A. Petkus,Christopher J. Sullivan
Published date01 April 2022
Date01 April 2022
Subject MatterArticles
Youth Violence and Juvenile Justice
2022, Vol. 20(2) 139163
© The Author(s) 2021
Article reuse guidelines:
DOI: 10.1177/15412040211061270
The Impact of Risk Assessment
on Juvenile Justice
Decision-Making and New
Adjudication: An Analysis of
Usage and Outcome
Amber A. Petkus
, Christopher J. Sullivan
, Melissa Lugo
, and
Jamie Newsome
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.
Juvenile Justice, Mediation, Risk Assessment, Risk-Needs-Responsivity, Ohio Youth Assessment
System (OYAS), Youth, Delinquency, Disposition, Treatment
School of Criminal Justice, University of Cincinnati, Cincinnati, OH, USA
School of Criminal Justice and Criminology, Texas State University, San Marcos, TX, USA
North Carolina Sentencing and Policy Advisory Commission, Raleigh, NC, USA
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.
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 riskrecidivismstudies 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 riskneedresponsivity (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 individualsrisk of re-
offending. The need principle states that the most effective interventions will address ones
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 RiskRecidivism 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 youthsrecidivism 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)

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