Protective Factors for Reducing Juvenile Reoffending: An Examination of Incremental and Differential Predictive Validity
| Author | Christina A. Campbell,Ashlee R. Barnes-Lee |
| DOI | 10.1177/0093854820952115 |
| Published date | 01 November 2020 |
| Date | 01 November 2020 |
| Subject Matter | Articles |
research-article2020
Protective Factors For reducing
Juvenile reoFFending
an examination of incremental and
differential Predictive validity
ASHLEE R. BARNES-LEE
Michigan State University
CHRISTINA A. CAMPBELL
University of Cincinnati
Juvenile court practitioners and researchers have recently gained interest in evaluating internal and external strengths, or
protective factors. Some scholars assert that incorporating measures of strengths into the risk assessment process can increase
the accuracy of identifying odds of recidivating. Relatively few juvenile risk assessment validation studies have evaluated
the predictive validity of strengths. This study employed a diverse sample (N = 278) of juveniles under supervision in a
Midwestern court. The Protective Factors for Reducing Juvenile Reoffending (PFRJR) significantly predicted recidivism for
the total sample, males, and White youth. There was no evidence of differential predictive validity across gender; however,
strengths predicted differently across race/ethnicity. Strengths did not increase the amount of variance explained in recidivism
after accounting for the variance explained by risk factor scores. Findings contribute to the paucity of validation studies that
investigated the differential and incremental predictive validity of strengths.
Keywords: juvenile risk assessment; protective factors; strengths; desistance; YLS/CMI
introduction
Research on the role of strengths in correctional rehabilitation is on the rise, yet pales in
comparison with the body of literature that focuses on risk factors (Walker et al., 2013), as
relatively few studies have explored the predictive validity of protective factors. It is safe to
surmise that most research focuses on risk factors because the Risk-Need-Responsivity
(RNR) model prioritizes the assessment and targeting of deficits (Andrews et al., 2006),
leading to the development of RNR-based tools that are exclusively comprising risk factors.
Notwithstanding, there are instruments that have risk and strength factors, yet investiga-
tions of the relationship between risks, strengths, recidivism, and desistance remain scarce.
A major shortcoming of understanding the role of strengths in recidivism prediction models
is that few studies have reported the predictive validity of strengths—in cases in which they
autHors’ note: We have no conflicts of interests to disclose. Correspondence concerning this article
should be addressed to Ashlee R. Barnes-Lee, School of Social Work, Michigan State University, 655
Auditorium Road, #254, East Lansing, MI 48824; e-mail: barnes75@msu.edu.
CRIMINAL JUSTICE AND BEHAVIOR, 2020, Vol. 47, No. 11, November 2020, 1390 –1408.
DOI: 10.1177/0093854820952115
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Barnes-Lee, Campbell / PROTECTIVE FACTORS FOR REDUCINg JUVENILE REOFFENDINg 1391
are included in the measure (Loeber & Farrington, 2012). Moreover, the empirical examina-
tion of the theoretical assumption that protective factors can be included in recidivism mod-
els to improve them has not been adequately investigated (Barnes-Lee, this issue; Wanamaker
et al., 2018).
For example, Barnes (2017) conducted a systematic review of peer-reviewed published
research between 1990 and 2016 and identified 608 studies that examined the predictive
validity of risk assessment with juveniles who engaged in general offending. Of the 608
validation studies, 31 examined the relationship between strengths and recidivism. Similarly,
Wanamaker and colleagues (2018) identified 48 validation studies that evaluated strengths
with juvenile and adult populations. Scholars have asserted that including an evaluation of
strengths could mitigate rater pessimism and stigma in the risk assessment process,
strengthen the ability to assess risk of recidivism, and may aid in successful rehabilitation
(de Vogel et al., 2011; Miller, 2006; Rogers, 2000). It is likely that criticisms of the deficits-
focused RNR model (Ward et al., 2012) have led researchers and practitioners to pay closer
attention to strengths.
Juvenile courts use risk assessment tools to evaluate risk of reoffending and identify
areas of criminogenic need to support case management and decisions on the appropriate
sanctions. Past research indicates that risk assessment tools have strong reliability and are
able to predict risk of recidivism with about 70% accuracy (Latessa & Lovins, 2010)—
significant improvement over past predictions based on clinical judgment. Nevertheless,
there is considerable room for improvement as risk assessment accounts for minimal varia-
tion in recidivism predictions. Researchers have also suggested that narrowly focusing on
criminogenic risk factors while neglecting protective factors may contribute to erroneous
projections of violent reoffending (de Vogel et al., 2011; Miller, 2006; Rogers, 2000).
Deficits-focused assessment may also leave a gap in understanding the strengths or resil-
ience factors that could reduce risk and promote positive development. Furthermore, given
the multiple disparities that pervade the juvenile justice system, it is important that research-
ers understand whether the relationship between strengths and recidivism varies for certain
youth as past research findings have indicated inconsistencies in the predictive validity of
risk assessment tools for racial minority and female juveniles (Shepherd et al., 2013).
The goal of this research was to examine the predictive validity of a recently developed
measure, Protective Factors for Reducing Juvenile Reoffending (PFRJR; Barnes-Lee, this
issue). The PFRJR was designed to complement traditional risk assessment measures by
assessing internal and external strengths of justice system-involved juveniles. Barnes-Lee
(this issue) discussed the development, factor structure, and reliability of the instrument.
The current study builds on the previous research by evaluating the tool’s predictive validity
and highlights the empirical and practical value of strengths in an applied setting—a topic
deserving more attention.
literature review
Protective Factors and Juvenile recidivism
Protective factors are defined as “aspects of an individual and their situation that contrib-
ute to a decreased likelihood of criminal behavior by having a direct effect on problem
behaviors or by moderating the relationship between risk factors and criminal behavior”
(Fougere & Daffern, 2011, p. 245). A youth’s “situation” can be interpreted as including
every level of their social environment from family dynamics and peer relationships to
1392 CRIMINAL JUSTICE AND BEHAVIOR
neighborhood safety. Following the lead of resilience pioneers, scholars have defined, under-
stood, and measured protective factors by grouping them into ecologically relevant domains:
individual, family, school, and community (Fergus & Zimmerman, 2005; garmezy, 1985).
The theoretical and empirical value of individual, family, school, and community protec-
tive factors has been extensively investigated with adolescents who did not formally make
contact with the juvenile justice system, yet rarely with youth who did, a major limitation of
the research in this area. Collectively, findings suggest that the predictive validity of protec-
tive factors in the individual domain are prosocial attitudes (Jones et al., 2016; Lodewijks
et al., 2008, 2010; Shepherd et al., 2016), impulse control (Williams et al., 2014), social skills
(Jones et al., 2016), and resilient personality (Dolan & Rennie, 2008).
Research also suggests the predictive validity of protective factors within the family
domain include parental supervision (Williams et al., 2014), discipline (Jimerson et al.,
2004), social support (Lodewijks et al., 2008, 2010), and strong attachment and bonds
(Lodewijks et al., 2008, 2010). Moreover, scholars have found protective factors within the
school domain to be associated with recidivism including positive peers (Jimerson et al.,
2004), commitment to education (Lodewijks et al., 2008, 2010; Shepherd et al., 2016), and
progress toward graduation (Jimerson et al., 2004). Finally, community-level protective
factors such as low neighborhood crime (Jimerson et al., 2004) and prosocial involvement
(Shepherd et al., 2016) have also been found to decrease the odds of reoffending. Overall,
the literature most strongly supports the predictive validity of prosocial attitudes, social
support, positive peers, and commitment to education. It is critical to explore and under-
stand which single protective factors are predictive among juveniles and the role they play
in developing pathways to desistance.
Predictive validity and incremental validity oF Protective Factors
Predictive validity
Researchers who examined the predictive validity of protective factor scores found they
were significant predictors of recidivism, indicating that evaluating protective factors shows
promise in effectively reducing odds of reoffending (e.g., Hilterman et al., 2016). Significant
findings were consistent across multiple recidivism outcomes and samples including violent
reoffending (Rennie & Dolan, 2010; Shepherd et al., 2016), juveniles in detention (Rennie &
Dolan, 2010; Vincent et al., 2011), and juveniles on...
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