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

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 ne...

Full description

Saved in:  
Bibliographic Details
Main Author: Campbell, Christina A. (Author)
Contributors: Anderson, Valerie R. ; Barnes, Ashlee ; D’amato, Christopher ; Moses, Natasha ; Papp, Jordan
Format: Electronic Article
Language:English
Published: 2020
In: Criminal justice and behavior
Year: 2020, Volume: 47, Issue: 9, Pages: 1079-1096
Online Access: Volltext (lizenzpflichtig)
Journals Online & Print:
Drawer...
Check availability: HBZ Gateway
Keywords:
Youth Level of Service/Case Management Inventory (YLS/CMI)
adjudicated youth
Hazard modeling
Juvenile recidivism
Neighborhood disadvantage
Risk assessment
Description
Summary: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.
ISSN:1552-3594
DOI:10.1177/0093854820924834