Understanding the Role of Neighborhood Typology and Sociodemographic Characteristics on Time to Recidivism Among Adjudicated Youth

Abstract

This study examined the effect of neighborhood disadvantage and criminogenic risk on juvenile recidivism. The sample included 893 youths involved in the delinquency/formal probation division of one Midwestern county juvenile court between 2004 and 2010. Juveniles were classified into one of three neighborhood typologies (i.e., Distressed/Disadvantage, Resilient/Mixed, Benchmark/Advantaged) based on the socioeconomic conditions in their neighborhoods. Survival models revealed that when examining the effect of neighborhood type, youth who lived in Resilient/Mixed neighborhoods, characterized by having the most transient residents, yet high graduation rates, were at greatest risk of recidivism. However, neighborhood effects disappeared after controlling for sociodemographic characteristics and criminogenic risk. Although there was no significant interaction between neighborhood and risk group classification, there was a significant interaction between risk group, age, and gender. These findings suggest the need for advanced statistical models that can disentangle the conflated effects of socioeconomic conditions and sociodemographic characteristics.

Profile Analysis and Risk Assessment: Identifying Distinct Patterns of Risks and Needs

“…This indicates that despite their overall low risk, many youths come into contact with the juvenile justice system on a relatively consistent basis. One potential explanation is unmeasured ecological factors that may influence the likelihood of contact with the system (Campbell et al, 2020; Onifade et al, 2011). For example, youth within this domain may often come from disadvantaged neighborhoods, which may increase the chance that individuals come into contact with the justice system.…”

Examining Whether Practical Measures of Neighborhood Characteristics Improve Correctional Risk Assessment Tools

“…Some studies suggest that certain macro-level factors influence recidivism (Kirk, 2009; Kubrin & Stewart, 2006). Others have found contrary evidence thus warranting further investigation of the topic (Campbell, 2012; Stahler et al, 2013).…”

“…Although decisions have traditionally been made via the professional judgment of practitioners, actuarial risk assessment tools have been adopted to aid in this process (Dawes et al, 1989). Many empirical studies have shown that these instruments improve the accuracy and consistency of correctional evaluations such as individuals’ progress in treatment and their risk of recidivism (Bonta, 2002; Bonta & Andrews, 2007; Campbell, 2012).…”

“…The only study that has been conducted specifically with neighborhood-level factors in juvenile correctional risk assessments did not find support that their inclusion improved prediction (Campbell, 2012). Instead, it is only the more general, nonrisk assessment-based recidivism studies of similar macro-level constructs among adults that have shown significant effects (Grunwald et al, 2010; Kirk, 2009; Kubrin & Stewart, 2006).…”

“…Apart from Campbell’s (2012) study, no one has examined whether using neighborhood-level measures that could be realistically estimated by correctional officers provide additional predictive power to risk assessment tools. Moreover, Campbell’s (2012) study examined juveniles. We know of no study conducted on an adult sample.…”