Clinical Overrides With the YLS/CMI: Predictive Validity and Associated Factors

• Author: Geneviève Parent,Marie-Pier Bilodeau,Catherine Laurier,Jean-Pierre Guay
• DOI: http://doi.org/10.1177/00938548221131958
• Published date: 01 January 2023
• Date: 01 January 2023
• Subject Matter: Original Articles

CRIMINAL JUSTICE AND BEHAVIOR, 2023, Vol. 50, No. 1, January 2023, 101 –117.

DOI: https://doi.org/10.1177/00938548221131958

Article reuse guidelines: sagepub.com/journals-permissions

© 2022 International Association for Correctional and Forensic Psychology

101

CLINICAL OVERRIDES WITH THE YLS/CMI

Predictive Validity and Associated Factors

GENEVIÈVE PARENT

University of Québec in Outaouais

Montreal Youth in Difficulty Institute

MARIE-PIER BILODEAU

University of Sherbrooke

Youth in Difficulty Institute

CATHERINE LAURIER

University of Sherbrooke

Montreal Youth in Difficulty Institute

JEAN-PIERRE GUAY

Universiy of Montreal

Philippe-Pinel National Institute of Forensic Psychiatry

International Center for Comparative Criminology

This study explores the use of clinical override with the Youth Level of Service/Case Management Inventory (YLS/CMI), includ-

ing implications for predictive validity as well as the factors associated with this practice. The sample included 597 justice-

involved youth from a metropolitan region in Québec, Canada. The clinical override was used in 32.5% of cases, usually to

increase risk levels (30.3% of cases). As found in previous studies, clinical override did not increase the predictive validity of the

YLS/CMI. Upward and downward clinical overrides were differently linked to the sociodemographic characteristics and criminal

history of the youths in the sample. Criminal History, Peer Relations, Personality/Behavior, and Attitudes/Orientation risk/need

domains were positively associated with upward override while Family Circumstances/Parenting, Personality/Behavior, and

Attitudes/Orientation risk/need domains were negatively associated with downward override. These results are discussed in rela-

tion to the impact clinical override can have on the case management and interventions provided to justice-involved youth.

Keywords: YLS/CMI; clinical override; recidivism; predictive validity

Many clinicians working with youth involved with the justice system use the Youth

Level of Service/Case Management Inventory (YLS/CMI; Hoge & Andrews, 2006,

2011), a standardized instrument whose psychometric properties for estimating the risk of

AUTHORS’ NOTE: We have no known conflict of interest to disclose. We received funding from Grant 430-

2016-00313 from the Social Sciences and Humanities Research Council of Canada. The authors would also like

to acknowledge the financial support of the Montreal Youth in Difficulty Institute in the writing of this article.

Correspondence concerning this article should be addressed to Geneviève Parent, Department of

Psychoeducation and Psychology, University of Québec in Outaouais, 283 boulevard Alexandre-Taché, C.P.

1250 succursale Hull, Gatineau, Québec, Canada J8X 3X7; e-mail: genevieve.parent@uqo.ca.

1131958CJBXXX10.1177/00938548221131958Criminal Justice and BehaviorParent et al. / CLINICAL OVERRIDES WITH THE YLS/CMI

research-article2022

102 CRIMINAL JUSTICE AND BEHAVIOR

recidivism have been confirmed in several studies (e.g., Olver et al., 2009; Schmidt et al.,

2005). In exceptional cases, clinicians can use their clinical judgment to override a YLS/

CMI risk classification and put an individual in a higher or lower risk category, a practice

known as clinical override. However, studies have shown that clinical override decreases

the predictive value of the instrument (e.g., Chappell et al., 2013; Guay & Parent, 2018).

Deciding how best to combine standardized assessment and clinical judgment in day-to-

day practice requires understanding the factors that can play a role in this decision-making

process.

EVOLUTION OF RISK ASSESSMENT

Methods of assessing recidivism risk have evolved significantly over the last 50 years,

through four generations of assessment (Bonta & Andrews, 2017). In the first generation,

clinicians relied on a dynamic understanding of an individual based on unstructured inter-

views and clinical judgment (“gut feelings”; Latessa & Lovins, 2010). The second genera-

tion involved attempts to standardize risk assessment through the creation of actuarial

instruments based on a specific number of static or historical risk factors, such as age or

criminal history, statistically associated with recidivism in studies of normative samples

(e.g., Hoffman, 1994) or in meta-analyses (e.g., Hanson & Thornton, 2000). The aggrega-

tion of ratings of all risk factors is used to establish risk levels. While numerous meta-

analyses have shown that structured assessments have higher predictive validity than

clinical judgment alone (e.g., Ægisdóttir et al., 2006; Grove & Meehl, 1996), they are atheo-

retical and provide no information about intervention targets or changes in risk over time

(Olver & Wong, 2019).

In the third generation, dynamic risk factors (factors that can be modified through inter-

ventions aimed at reducing recidivism risk), such as problems with substance use or antiso-

cial attitudes, were added to second-generation risk assessment instruments. Meta-analyses

have demonstrated that dynamic risk factors are as effective as static risk factors in predict-

ing recidivism (Campbell et al., 2009; Gendreau et al., 1996). Third-generation instruments

also have a slight advantage over second-generation instruments in statistically significant

predictions (Campbell et al., 2009; Schwalbe, 2007; Yang et al., 2010). Finally, fourth-

generation measures make it possible to assess static risk factors (e.g., criminal history),

criminogenic needs (i.e., dynamic risk factors associated with recidivism), and responsivity

factors as well as providing indications for case management, including changes in the level

of risk until case closure (Campbell et al., 2009; Latessa & Lovins, 2010; Olver & Wong,

2019). A meta-analysis by Campbell et al. (2009) based on five effect sizes found that

fourth-generation measures are more effective than their predecessors.

THE YLS/CMI

The YLS/CMI is a fourth-generation instrument used with youth between 12 and 18

years of age who have been convicted of a crime. It is one of the most widely used struc-

tured risk and need assessment instrument in many jurisdictions, such as Canada (Catchpole

& Gretton, 2003; Schmidt et al., 2005, 2016; Viljoen et al., 2014), the United States

(Campbell et al., 2014; Chappell et al., 2013; Guy et al., 2014), Singapore (Chu et al.,

2014), and the United Kingdom (Vaswani & Merone, 2014). While there is no clear guid-

ance about reassessment frequency when using the YLS/CMI (Hoge & Andrews, 2006,