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Juvenile Offending Trajectories

Juvenile Offending Trajectories. A Queensland Study. Presentation. Background Current study Results Limitations and future research Conclusions. Criminal Careers. Based on longitudinal cohort studies Exploring initiation, frequency, duration, specialisation, escalation and desistance

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Juvenile Offending Trajectories

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  1. Juvenile Offending Trajectories A Queensland Study 1

  2. Presentation • Background • Current study • Results • Limitations and future research • Conclusions 2

  3. Criminal Careers • Based on longitudinal cohort studies • Exploring initiation, frequency, duration, specialisation, escalation and desistance • Focus on identifying offender sub-populations 3

  4. Criminal Careers • E.g. Wolfgang et. al. (1975) • Chronics = >5 offences • Farrington et. al. (1987) • ‘Frequents’ and ‘Occasionals’ • Moffitt et. al. (1993) • ‘Life course persistent’ and ‘adolescent-limited’ offenders 4

  5. Offending Trajectories 5

  6. Offending Trajectories 6

  7. Trajectory models • Land and Nagin (1993) developed Semiparametric Group Based Method (SPGM) • Group together ‘similar’ trajectories of offending • Identify offender subgroups from the data rather than imposing ex ante definitions 7

  8. Current study • Develop a trajectory model of juvenile offending • Explore correlates of trajectory membership • Assess predictive validity of trajectories 8

  9. Cohort • People born in 1983 or 1984 with one or more finalised court appearances in Queensland • Offending (cautioning and court) modelled between the ages of 10 and 16 9

  10. Trajectory model 10

  11. Late Onset Group • Included more than two-thirds of the cohort • Average of 2.3 offences as juveniles • Responsible for 40% of the entire cohort’s offending 11

  12. Adolescent Limited Group • Included 20% of the cohort • Committed 23% of the offences committed by the whole cohort • Early onset with offending peaking at age 14. 12

  13. Chronic group • Included just over one-tenth of the cohort • Responsible for 33% of the entire cohort’s offending • Average of 10.5 juvenile offences each 13

  14. Factors associated with trajectories • Six factors explored: • Sex • Indigenous status • Remoteness of residence • Socio-economic disadvantage (of area of residence) • Child protection history • First court outcome 14

  15. Factors associated with trajectories • Multivariate analysis: • Little difference between adolescent-limited and adolescent-onset groups • Males more than twice as likely as females to follow ‘chronic’ trajectory • Indigenous offenders between 3 and 5 times as likely as non-Indigenous to follow ‘chronic’ trajectory 15

  16. Factors associated with trajectories • Multivariate analysis: • Young people with child protection substantiations were 2 – 4 times more likely to follow ‘chronic’ trajectory • Young people with a supervised order at the first court appearance were around 1.5 times more likely to follow ‘chronic’ trajectory 16

  17. Predictive validity of trajectories • Relationship between juvenile offending trajectory and adult offending • For this study, adult offending was based on adult court appearances and was simply coded as a yes/no variable 17

  18. Predictive validity of trajectories 18

  19. Predictive validity of trajectories • When sex, Indigenous status, remoteness and SED, child protection and first court outcome were controlled for in a logistic regression model: • Chronics were 2.7 times more likely to progress than late onset offenders • Chronics were 3.3 times more likely to progress than adolescent limited offenders 19

  20. Findings • Trajectory model similar to U.S., U.K. and New Zealand models • Consistency of results adding evidence to a model of offending that includes two or more subpopulations of offenders 20

  21. International comparisons 21

  22. Findings • Expected differences between males and females; Indigenous and non-Indigenous offenders • Some evidence that some females do follow a chronic offending trajectory 22

  23. Findings • Child protection history strongly related to offending trajectory • Offending trajectories strongly predict future offending at an aggregate levels • Similarities between late-onset and adolescent-limited groups need further examination 23

  24. Limitations of study • Short time frame • Limited range of factors available • Sample attrition • Use of official data for offending 24

  25. Future research • Extend study into adult offending • Explore distinct trajectory models based on sex and Indigenous status • Studies of how interventions/social changes (such as marriage, employment etc) affect trajectory group membership 25

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