Using Risk Profiles To Differentiate Between Offending Trajectories in Childhood Arrestees

This study aims to explain heterogeneity in offending trajectories by examining its association with exposure to combinations of risk (or the lack thereof) across multiple life domains. Drawing on survey data and administrative crime records from the Dutch Childhood Arrestees Study, we examined the relationship between distinct risk profiles and offending trajectories in a sample of 348 children with a first police contact before age 12 (87% male, Mage a first contact = 10.63, SD = 1.48), who were followed from age 12 to 20. Alongside an a priori defined group of non-recidivists (55%), the trajectory analysis yielded four distinct offending patterns: low-rate desisting (14%), low-rate persisting (18%), high-rate desisting (5%), and high-rate persisting (8%). Using latent profile analysis, we constructed three distinct risk profiles based on individual, familial, peer, school, and neighborhood characteristics: low-problem (31%), cognitive- and neighborhood-problem (48%), and multi-problem (21%) profiles. Multinomial regression analyses showed that children with a low-problem profile were the least likely to persist in offending throughout the follow-up period. In comparison to low-problem children, those with a multi-problem profile were more likely to follow the low-rate persistent trajectory, whereas children exposed to cognitive and neighborhood problems were more likely to follow the high-rate persistent trajectory. The findings underscore the value of accounting for risk exposure across multiple life domains to explain variations in longitudinal offending patterns.

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Publication Details

Journal
Journal of Developmental and Life-Course Criminology
Published
2025-12-01
DOI
https://doi.org/10.1007/s40865-025-00283-8
Primary Topic
Crime Patterns and Interventions
Type
article
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article

Using Risk Profiles To Differentiate Between Offending Trajectories in Childhood Arrestees

Arne Popma, Lieke van Domburgh, Babette C. M. van Hazebroek, Hilde Wermink et al.
Journal of Developmental and Life-Course Criminology
Crime Patterns and Interventions
article

Using Risk Profiles To Differentiate Between Offending Trajectories in Childhood Arrestees

Arne Popma, Lieke van Domburgh, Babette C. M. van Hazebroek, Hilde Wermink, Jan W. De Keijser
article en

Abstract

This study aims to explain heterogeneity in offending trajectories by examining its association with exposure to combinations of risk (or the lack thereof) across multiple life domains. Drawing on survey data and administrative crime records from the Dutch Childhood Arrestees Study, we examined the relationship between distinct risk profiles and offending trajectories in a sample of 348 children with a first police contact before age 12 (87% male, Mage a first contact = 10.63, SD = 1.48), who were followed from age 12 to 20. Alongside an a priori defined group of non-recidivists (55%), the trajectory analysis yielded four distinct offending patterns: low-rate desisting (14%), low-rate persisting (18%), high-rate desisting (5%), and high-rate persisting (8%). Using latent profile analysis, we constructed three distinct risk profiles based on individual, familial, peer, school, and neighborhood characteristics: low-problem (31%), cognitive- and neighborhood-problem (48%), and multi-problem (21%) profiles. Multinomial regression analyses showed that children with a low-problem profile were the least likely to persist in offending throughout the follow-up period. In comparison to low-problem children, those with a multi-problem profile were more likely to follow the low-rate persistent trajectory, whereas children exposed to cognitive and neighborhood problems were more likely to follow the high-rate persistent trajectory. The findings underscore the value of accounting for risk exposure across multiple life domains to explain variations in longitudinal offending patterns.

Journal of Developmental and Life-Course CriminologyVol. 11(1-4)
Leiden University (NL), University of Applied Sciences Leiden (NL), Amsterdam University Medical Centers (NL)
Openalex Percentile: Top 52%
Crime Patterns and Interventions
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