Psychopathology and offense types in detained male juveniles
Introduction
Juveniles commit a substantial proportion of severe criminal acts, and juvenile delinquency is a challenge for policy makers and communities in most modern societies (Snyder, 2006, Siegel and Welsh, 2009). There is general consensus that juvenile detainees are often affected by psychiatric morbidity, with overall high rates of psychiatric disorders and co-morbidities (Vermeiren et al., 2006, Fazel et al., 2008). Moreover, psychiatric disorders in incarcerated juvenile offenders have been found to affect behavioral aspects such as suicidal behavior (Penn et al., 2003, Ruchkin et al., 2003, Plattner et al., 2007), sexual risk-taking behavior (Elkington et al., 2008), aggressive behavior (Hamerlynck et al., 2008) and criminological aspects such as general criminal recidivism (Vermeiren et al., 2002, Plattner et al., 2009).
However, a core aspect, namely the relation between psychiatric disorders and offense types, is not yet clear in juvenile detainees, with few recent studies addressing this research question and producing conflicting results: Some studies found no difference between psychiatric disorders in violent versus non-violent juvenile offenders (Kemph et al., 1998, Gosden et al., 2006) concluding that in detained adolescents psychopathology might not yet have developed in severity and number to be significantly associated with violent offending (Gosden et al., 2006). In contrast, other studies found such associations but yielded diverging results. For instance, substance use disorders (SUD) were found to be negatively associated (Vreugdenhil et al., 2003, Vreugdenhil et al., 2004, Colins et al., 2009) as well as positively associated (Haapasalo and Hamalainen, 1996) with violent offending. In terms of disruptive behavior disorders (DBD), none of the studies found a positive association with violent offending, whereas one study even found a significant negative association between severe violent offending and DBD (Vreugdenhil et al., 2004). Furthermore, posttraumatic stress disorder (PTSD) in detained juveniles could not be linked to offending characteristics, even though early studies found high rates of experienced child abuse and neglect in violent offenders and offenders convicted of homicide (Lewis et al., 1988, Widom, 1989). However, one recent study found that juveniles who committed violent offenses showed a tendency to have suffered from more extreme physical abuse than property offenders (Haapasalo and Hamalainen, 1996).
The major shared limitations in these studies are the extremely heterogeneous subgroups of offenders: For example, the violent subgroups included individuals that committed robbery, homicide, manslaughter, bodily harm and even juvenile sexual offenders (JSO). The latter have been found to be an extremely heterogeneous group per se (Aebi et al., 2012). Similarly the non-violent subgroups included individuals that committed vandalism, theft and burglary, drug offenses, bodily harm by negligence, unlawful threat, possessions of weapons and resistance against an officer. Moreover, as a further limitation, most offenders categorized as violent also had a history of a non-violent crime.
A most recent study of 245 detained juveniles addressed this specific limitation by introducing a subgroup of versatile offenders (Colins et al., 2009). By adding the third grouping variable, the understanding of detained property offenders presenting them as psychiatric multi-morbid antisocial juveniles was substantially expanded. Versatile offenders showed less mood disorders than property offenders. The only prediction for violent offender group membership by psychiatric disorder was a reduced likelihood to endorse any marijuana use. Even in this methodologically sound study, the violent group was still very heterogeneous including index crimes such as robbery, homicide, manslaughter and sexual crimes, and possible relations to psychopathological mechanisms may have been concealed. Therefore, the question of psychopathological correlates of violent offending in juveniles remains open.
In order to address the limitations mentioned above, we refrained from the common strategy of forming subgroups of offenders and chose a pure offense-oriented approach. By use of this analytic strategy, the bias of heterogeneous offender subgroups will be ruled out. Furthermore, approaching the topic from a criminological point of view might add to the understanding of behavioral outcomes of psychopathology in juveniles.
Section snippets
Participants
The study was performed at the Vienna County jail (Justizanstalt Josefstadt) which is the sole detention facility for juveniles awaiting trial in Vienna, Austria. Juveniles who were admitted to this specific correctional facility between March 2003 and January 2005 showing sufficient command of the German language were included in the present study. Exclusion criteria were significant medical conditions (e.g. acute state of human immunodeficiency virus, hepatitis, or other infectious diseases)
Descriptive findings
The sample consisted of 275 male juvenile offenders between 14 and 20 years old, with a mean age of 16.45 years (S.D. = 1.27 years). For 133 juveniles (48.4%), the actual incarceration was their first detention. The remaining 142 juveniles (51.6%) had already been one (n = 91, 33.1%) or several times (n = 51, 18.5%) in detention before. The mean age at first detention was 16.00 years (S.D. = 1.32 years).
Most commonly the juveniles in the samples were detained for robberies (n = 156, 56.7%) and/or property
Discussion
The aim of this study was to analyze the association between psychopathology and distinct criminal behavior from a crime-category approach in a large sample of detained juveniles. Sociodemographic data such as age, SES and country of origin were included in the analyses. Interestingly, age at detention was found to be associated with crime characteristics, as younger age was found to be linked to robbery, and older age to drug-related and violent crimes. In terms of psychopathology the abuse of
Acknowledgements
Financial support for data collection and data management was received through a grant to Dr. Plattner by the Medizinisch-wissenschaftlicher Fonds des Bürgermeisters der Bundeshauptstadt Wien (Grant Nr: 2236), Vienna, Austria. The authors are grateful to Dr. Mark Brink from Public and Organizational Health, ETH Zurich for his practical advice and helpful suggestions regarding logit curve calculations.
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