The Relationship Between Changes in Dynamic Risk Factors and the Predictive Validity of Risk Assessments Among Youth Offenders

• Author: Maggie C. Clarke,Tracey A. Skilling,Michele Peterson-Badali
• DOI: 10.1177/0093854817719915
• Published date: 01 October 2017
• Date: 01 October 2017
• Published By: Sage Publications, Inc.

https://doi.org/10.1177/0093854817719915

CRIMINAL JUSTICE AND BEHAVIOR, 2017, Vol. 44, No. 10, October 2017, 1340 –1355.

DOI: 10.1177/0093854817719915

© 2017 International Association for Correctional and Forensic Psychology

1340

THE RELATIONSHIP BETWEEN CHANGES IN

DYNAMIC RISK FACTORS AND THE

PREDICTIVE VALIDITY OF RISK ASSESSMENTS

AMONG YOUTH OFFENDERS

MAGGIE C. CLARKE

Waterloo Region District School Board

MICHELE PETERSON-BADALI

TRACEY A. SKILLING

University of Toronto

The Youth Level of Service/Case Management Inventory (YLS/CMI) is a widely used risk assessment tool for youth offend-

ers. It is intended to be administered regularly to capture changes in criminogenic needs and thus inform case management

during a youth’s sentence. However, there is a dearth of research examining whether updated assessments are more predictive

of recidivism than initial assessments. We examined whether including dynamic risk factors increased the predictive validity

of the YLS/CMI and whether changes in dynamic risk scores improved the prediction of recidivism. Two hundred youth

offenders were tracked from their first risk assessment conducted at probation to their most recent risk assessment completed

prior to first reoffense or study end date. Inclusion of dynamic risk scores improved predictive accuracy above static risk and

updated dynamic risk scores improved accuracy over those obtained from the initial assessment, supporting the utility of the

YLS/CMI as a reassessment tool.

Keywords: dynamic risk factors; Risk-Need-Responsivity; YLS/CMI; changes in risk; recidivism; predictive validity;

youth offenders; probation

INTRODUCTION

Given the detrimental social and economic costs of youth crime, its prevention and

reduction has been a priority for many jurisdictions in North America, the United Kingdom,

Europe, Australia, and New Zealand. Based on a general personality and cognitive social

learning theory of criminal conduct (Andrews & Bonta, 2010a), the Risk-Need-Responsivity

AUTHORS’ NOTE: This article is based on Maggie Clarke’s doctoral dissertation. The research was con-

ducted at the Ontario Institute for Studies in Education, University of Toronto. Maggie Clarke is currently work-

ing for the Waterloo Region District School Board. This research was supported by Grant number 410101516

from the Social Sciences and Humanities Council of Canada to the second and third authors. The authors would

like to express their deep appreciation to Kathy Underhill of the Program Effectiveness, Statistics and Applied

Research Unit of the Ontario Ministry of Community Safety and Correctional Services and Mr. Justice Brian

Weagant of the Ontario Court of Justice for their contributions to this study. Correspondence concerning this

article should be addressed to Michele Peterson-Badali, Department of Applied Psychology & Human

Development, Ontario Institute for Studies in Education, University of Toronto, 252 Bloor Street West, 12th floor,

Toronto, Ontario, Canada M5S 1V6; e-mail: m.petersonbadali@utoronto.ca.

719915CJBXXX10.1177/0093854817719915Criminal Justice and BehaviorClarke et al. / Dynamic Risk Factors Changes and Youth Recidivism

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Clarke et al. / DYNAMIC RISK FACTORS CHANGES AND YOUTH RECIDIVISM 1341

(RNR) framework is considered one of the most prominent models used in the assessment

and treatment of youth offenders. It forms the basis for correctional and community (e.g.,

probation) youth justice practice in many jurisdictions throughout the world. This theoreti-

cal framework encompasses a systematic empirical examination of risk factors associated

with criminal behavior and focuses on individual differences within a corrections model

while simultaneously incorporating community factors (Andrews & Bonta, 2010a). Both

individual studies (Luong & Wormith, 2011; Vieira, Skilling, & Peterson-Badali, 2009) and

meta-analytic research (Andrews et al., 1990; Lipsey, 2009) have consistently shown

reduced recidivism rates for community and correctional interventions and programs that

adhere to the RNR model, with reductions in offender recidivism by up to 35% (Andrews

& Bonta, 2010a).

According to the risk principle, the intensity of supervision and services provided in the

context of sentencing should be matched to an offender’s identified level of risk to reoffend.

That is, more intensive supervision, restrictive placements, and treatment services should

be reserved for high-risk youth, and fewer resources should be allocated to low-risk offend-

ers who require less monitoring and case management (Andrews & Bonta, 2010a, 2010b;

Andrews & Dowden, 2006; Andrews et al., 1990; Loeber & Ahonen, 2014). Studies have

shown that higher risk offenders benefit the most when treatment is of adequate intensity

(Bourgon & Armstrong, 2005; Kroner & Takahashi, 2012) and that treatment services pro-

vided to low-risk offenders may in fact increase the likelihood of poor outcomes (Andrews

& Dowden, 2006; Lowenkamp & Latessa, 2004; Lowenkamp, Latessa, & Holsinger, 2006).

In the youth literature, there is strong evidence to support that high-risk youth benefit the

most from targeted intervention (Lipsey, 2009; Luong & Wormith, 2011) when compared

with low-risk youth (skilling, Vieira et al., 2009). Adhering to this principle requires assess-

ment of factors that strongly and directly predict recidivism, which in the RNR framework

are termed “criminogenic needs.” In addition to criminal history, seven criminogenic need

domains have been identified as strong predictors of reoffending, including Procriminal

Attitudes (thoughts, values, and sentiments supportive of criminal behavior), Antisocial

Personality (low self-control, hostility, adventurous pleasure seeking, disregard for others,

callousness), Procriminal Associates, Social Achievement (education, employment),

Family/Marital (marital instability, poor parenting skills, criminality), Substance Abuse,

and Leisure/Recreation (lack of prosocial pursuits; Andrews & Bonta, 2010a).

The need principle describes “what should be treated” and points to the critical impor-

tance of focusing intervention on criminogenic needs rather than factors empirically shown

to be noncriminogenic (i.e., variables with weak or indirect relationships to reoffending;

Andrews & Bonta, 2010b). Furthermore, in contrast to risk classification (and the risk prin-

ciple), which incorporates both static and dynamic risk factors (Andrews & Bonta, 2010b),

the focus of the need principle is on the latter group of variables. While there are a number

of static risk factors that are strong, direct predictors of criminal behavior (e.g., age, gender,

history of criminal offending), such variables cannot be modified with treatment and are

therefore not appropriate targets of intervention. Dynamic risk factors comprise variables

that are directly related to offending and are amenable to change through intervention. Thus,

according to the need principle, intervention should focus on dynamic risk factors if the

goal is to decrease a youth’s risk to reoffend (Andrews & Bonta, 2010a, 2010b). Several

studies of justice-involved youth have supported the adherence to the need principle, find-

ing that addressing youths’ individually assessed criminogenic needs with appropriate