Toward a Classification of Juvenile Offenders: Subgroups of Serious Juvenile Offenders and Severity of Recidivism

Abstract

The aim of this study was to identify subgroups of serious juvenile offenders on the basis of their risk profiles, using a data-driven approach. The sample consists of 1,147 of the top 5% most serious juvenile offenders in the Netherlands. A part of the sample, 728 juvenile offenders who had been released from the institution for at least 2 years, was included in analyses on recidivism and the prediction of recidivism. Six subgroups of serious juvenile offenders were identified with cluster analysis on the basis of their scores on 70 static and dynamic risk factors: Cluster 1, antisocial identity; Cluster 2, frequent offenders; Cluster 3, flat profile; Cluster 4, sexual problems and weak social identity; Cluster 5, sexual problems; and Cluster 6, problematic family background. Clusters 4 and 5 are the most serious offenders before treatment, committing mainly sex offences. However, they have significantly lower rates of recidivism than the other four groups. For each of the six clusters, a unique set of risk factors was found to predict severity of recidivism. The results suggest that intervention should aim at different risk factors for each subgroup.

Serious juvenile offenders: classification into subgroups based on static and dynamic charateristics

“…The present study is a replication of the previous study by Mulder and colleagues [ 23 ] and thereby a validation of the earlier described subgroups. Factor analyses on the 70 items of the JFP-list of risk factors demonstrated almost the same nine factors in the present as the previous study on a sample twice as large.…”

“…In line with policy of the Dutch Ministry of Safety and Justice, no information about ethnicity was collected. The study of Mulder and colleagues [ 23 ] included 1107 adolescents, which are also included in the current sample.…”

“…As a result, data on the uniqueness of offender characteristics, other than offense characteristics, for specific subgroups of offenders, is lacking. To overcome these limitations, Mulder, Brand, Bullens, and van Marle identified subgroups of offenders based on a wide variety of risk factors in a nation-wide sample of incarcerated youth [ 23 ]. This study of Mulder and colleagues identified subgroups based on data driven research which provided certain fit values, combined with the face value after the consultation of experts in the forensic field.…”

“…This study of Mulder and colleagues identified subgroups based on data driven research which provided certain fit values, combined with the face value after the consultation of experts in the forensic field. Six subgroups with different risk profiles were found, named: (1) antisocial identity, (2) frequent offenders, (3) flat profile, (4) sexual problems and weak social identity, (5) sexual problems, and (6) problematic family background [ 23 ]. Since the identification of subgroups by algorithms is an exploratory heuristics process that can create as well as reveal structure, replication is critical to establish validity [ 24 ].…”

The Role of Perceived Social Support in the Psychological Well-Being of Young Offenders: from Pretrial Detention to Correctional Camps

“…The prevalence of undiagnosed mental disorders and the disadvantaged social situation of development often overlap with the particularities of adolescence and become a trigger for illegal actions leading to committing crimes of varying severity. In addition, studies in different countries indicate that recidivism and its severity are very high in serious juvenile offenders [4][5][6]. The high level of recidivism in adolescent perpetrators is widespread regardless of the criminal justice system, the severity of the sentencing against minors and the corrective measures employed [7].…”