Preventing Delinquency and Later Criminal Offending

2021 ◽  
pp. 627-642
Author(s):  
Brandon C. Welsh ◽  
David P. Farrington ◽  
Alexis Yohros
Keyword(s):  
2008 ◽  
Author(s):  
Christopher M. Weaver ◽  
Rachel Kimerling ◽  
Dara R. Goldberg ◽  
Jason Jacobs-Lentz ◽  
Jodie Trafton

Author(s):  
Brandon C. Welsh ◽  
Steven N. Zane

This chapter reviews the leading family-based programs for preventing delinquency and later offending, focusing on the highest quality research studies as well as the most rigorous reviews of research that include only high-quality studies. It argues that by focusing on families we can go a long way toward improving the effectiveness of programs and policies to prevent delinquency and later criminal offending. As such, this chapter provides some background on family risk factors and family-based prevention programs. It then examines the research evidence on the leading family-based programs for preventing delinquency and later offending: parent education, parent management training, and family programs for system-involved youth. Finally, this chapter discusses some implications for research and policy.


2017 ◽  
Vol 52 (6) ◽  
pp. 530-541 ◽  
Author(s):  
Melissa J Green ◽  
Stacy Tzoumakis ◽  
Kristin R Laurens ◽  
Kimberlie Dean ◽  
Maina Kariuki ◽  
...  

Objective: Detecting the early emergence of childhood risk for adult mental disorders may lead to interventions for reducing subsequent burden of these disorders. We set out to determine classes of children who may be at risk for later mental disorder on the basis of early patterns of development in a population cohort, and associated exposures gleaned from linked administrative records obtained within the New South Wales Child Development Study. Methods: Intergenerational records from government departments of health, education, justice and child protection were linked with the Australian Early Development Census for a state population cohort of 67,353 children approximately 5 years of age. We used binary data from 16 subdomains of the Australian Early Development Census to determine classes of children with shared patterns of Australian Early Development Census–defined vulnerability using latent class analysis. Covariates, which included demographic features (sex, socioeconomic status) and exposure to child maltreatment, parental mental illness, parental criminal offending and perinatal adversities (i.e. birth complications, smoking during pregnancy, low birth weight), were examined hierarchically within latent class analysis models. Results: Four classes were identified, reflecting putative risk states for mental disorders: (1) disrespectful and aggressive/hyperactive behaviour, labelled ‘misconduct risk’ ( N = 4368; 6.5%); (2) ‘pervasive risk’ ( N = 2668; 4.0%); (3) ‘mild generalised risk’ ( N = 7822; 11.6%); and (4) ‘no risk’ ( N = 52,495; 77.9%). The odds of membership in putative risk groups (relative to the no risk group) were greater among children from backgrounds of child maltreatment, parental history of mental illness, parental history of criminal offending, socioeconomic disadvantage and perinatal adversities, with distinguishable patterns of association for some covariates. Conclusion: Patterns of early childhood developmental vulnerabilities may provide useful indicators for particular mental disorder outcomes in later life, although their predictive utility in this respect remains to be established in longitudinal follow-up of the cohort.


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