Using Risk Profiles To Differentiate Between Offending Trajectories in Childhood Arrestees

Journal of Developmental and Life-Course Criminology, vol. 11, pp. 294–322

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, M age 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.

Authors 5

1. Babette C. M. van Hazebroek corresponding Aachen Department of Criminology, Leiden University

   Leiden University

   Affiliation as printed

   Department of Criminology, Leiden University, Steenschuur 25, Leiden, 2311 ES, The Netherlands

2. Lieke van Domburgh

   Amsterdam University Medical Centers · iHub

   Affiliation as printed

   Amsterdam University Medical Centers, Amsterdam, The Netherlands

   iHUB, Rotterdam, The Netherlands

3. Jan W. De Keijser Aachen Department of Criminology, Leiden University

   Leiden University

   Affiliation as printed

   Department of Criminology, Leiden University, Steenschuur 25, Leiden, 2311 ES, The Netherlands

4. Arne Popma

   Amsterdam University Medical Centers

   Affiliation as printed

   Amsterdam University Medical Centers, Amsterdam, The Netherlands

5. Hilde T. Wermink Aachen Department of Criminology, Leiden University

   Leiden University

   Affiliation as printed

   Department of Criminology, Leiden University, Steenschuur 25, Leiden, 2311 ES, The Netherlands