Delinquent Development in Dutch Childhood Arrestees: Developmental Trajectories, Risk Factors and Co-morbidity with Adverse Outcomes during Adolescence
Abstract:Heterogeneity of re-offending patterns was studied in a group of 287 male early onset offenders who were first arrested before age 12. By combining data on the frequency and severity of offending as registered by the police over a 5-year follow-up period, three delinquent trajectories were identified; low, escalating, and high level re-offenders. Predicting group membership by individual and environmental characteristics known to the police at the time of the first arrest proved difficult. Compared to low leve… Show more
“…The four clinical subsamples were selected to capture the entire adolescent aggression range and differed with respect to the mean study aggression level: 131 participants from a special school for children with disruptive behavioral problems, 199 participants from a residential facility for treatment of conduct problems, 154 adolescents with a history of being arrested by the police before the age of 12 (Cohn et al 2015; Domburgh et al 2009), and 103 participants from a Dutch diversion program for delinquent youth (Popma et al 2007). Participants of the first two studies were asked to fill in questionnaires at the start of their treatment within the school program or within the residential facility.…”
This study was designed to examine whether proactive and reactive aggression are meaningful distinctions at the variable-and person-based level, and to determine their associated behavioral profiles. Data from 587 adolescents (mean age 15.6; 71.6 % male) from clinical samples of four different sites with differing levels of aggression problems were analyzed. A multi-level Latent Class Analysis (LCA) was conducted to identify classes of individuals (personbased) with similar aggression profiles based on factor scores (variable-based) of the Reactive Proactive Questionnaire (RPQ) scored by self-report. Associations were examined between aggression factors and classes, and externalizing and internalizing problem behavior scales by parent report (CBCL) and self-report (YSR). Factor-analyses yielded a three factor solution: 1) proactive aggression, 2) reactive aggression due to internal frustration, and 3) reactive aggression due to external provocation. All three factors showed moderate to high correlations. Four classes were detected that mainly differed quantitatively (no 'proactive-only' class present), yet also qualitatively when age was taken into account, with reactive aggression becoming more severe with age in the highest affected class yet diminishing with age in the other classes. Findings were robust across the four samples. Multiple regression analyses showed that 'reactive aggression due to internal frustration' was the strongest predictor of YSR and CBCL internalizing problems. However, results showed moderate to high overlap between all three factors. Aggressive behavior can be distinguished psychometrically into three factors in a clinical sample, with some differential associations. However, the clinical relevance of these findings is challenged by the person-based analysis showing proactive and reactive aggression are mainly driven by aggression severity.
“…The four clinical subsamples were selected to capture the entire adolescent aggression range and differed with respect to the mean study aggression level: 131 participants from a special school for children with disruptive behavioral problems, 199 participants from a residential facility for treatment of conduct problems, 154 adolescents with a history of being arrested by the police before the age of 12 (Cohn et al 2015; Domburgh et al 2009), and 103 participants from a Dutch diversion program for delinquent youth (Popma et al 2007). Participants of the first two studies were asked to fill in questionnaires at the start of their treatment within the school program or within the residential facility.…”
This study was designed to examine whether proactive and reactive aggression are meaningful distinctions at the variable-and person-based level, and to determine their associated behavioral profiles. Data from 587 adolescents (mean age 15.6; 71.6 % male) from clinical samples of four different sites with differing levels of aggression problems were analyzed. A multi-level Latent Class Analysis (LCA) was conducted to identify classes of individuals (personbased) with similar aggression profiles based on factor scores (variable-based) of the Reactive Proactive Questionnaire (RPQ) scored by self-report. Associations were examined between aggression factors and classes, and externalizing and internalizing problem behavior scales by parent report (CBCL) and self-report (YSR). Factor-analyses yielded a three factor solution: 1) proactive aggression, 2) reactive aggression due to internal frustration, and 3) reactive aggression due to external provocation. All three factors showed moderate to high correlations. Four classes were detected that mainly differed quantitatively (no 'proactive-only' class present), yet also qualitatively when age was taken into account, with reactive aggression becoming more severe with age in the highest affected class yet diminishing with age in the other classes. Findings were robust across the four samples. Multiple regression analyses showed that 'reactive aggression due to internal frustration' was the strongest predictor of YSR and CBCL internalizing problems. However, results showed moderate to high overlap between all three factors. Aggressive behavior can be distinguished psychometrically into three factors in a clinical sample, with some differential associations. However, the clinical relevance of these findings is challenged by the person-based analysis showing proactive and reactive aggression are mainly driven by aggression severity.
“…A greater challenge has been identifying covariates that help explain these trajectories (Blokland, Nagin, & Nieuwbeerta, 2005;Day et al, 2010;Fergusson, Horwood, & Nagin, 2000;Landsheer & Dijkum, 2005;Nagin, Farrington, & Moffitt, 2005;Odgers et al, 2008;van der Geest, Blokland, & Bijleveld, 2009;van Domburgh, Vermeiren, Blokland, & Doreleijers, 2009;Ward et al, 2010). The related major theme of this article is that symptoms of psychopathy can be employed to account for some of these offending trajectories (see also Corrado et al, 2015;McCuish et al, 2014McCuish et al, , 2015.…”
Section: Psychopathy and Its Intended Scope In Explanations Of Offendingmentioning
“…petty theft, arson, vandalism, trespassing, burglary, assault, sexual abuse and robbery), excluding status offences. Thus far, they have been assessed in four waves: mean age at study entrance 10.8 (SD 1.5) years and mean age at wave three 12.9 (SD 1.5) years (van Domburgh et al, 2009). Wave four included a neuroimaging protocol in which DTI data were acquired.…”
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