Resource type
Date created
2007
Authors/Contributors
Author: Odgers, C.
Author: Moretti, M. M.
Author: Burnette, M.
Author: Chauhan, P.
Author: Waite, D.
Author: Repucci, D.
Abstract
Females have recently become an important population in research related to serious and violent juvenile offending. Although a small body of research exists on girls in the deep end of the system, very few studies have examined the degree of heterogeneity within high-risk female samples. This study applied latent class analysis (LCA) to identify subgroups of female juvenile offenders based on their self-report of offending profiles (N=133). Results supported a three-class solution with subgroups characterized by patterns of 'violent and delinquent', 'delinquency only', and 'low' offending patterns. The LCA solution was replicated in an independent sample of high-risk females. The 'violent and delinquent' class was characterized by significantly higher rates of DSM-IV diagnoses for internalizing disorders, affect dysregulation, exposure to violence (within the home, school and neighborhood), and familial histories of criminality. Implications for future research, policy and clinical practice are discussed.
Document
Published as
This is the accepted version of the following article: Odgers, C. L., Moretti, M. M., Burnette, M. L., Chauhan, P., Waite, D., & Reppucci, N. D. (2007). A latent variable modeling approach to identifying subtypes of serious and violent female juvenile offenders. Aggressive Behavior, 33(4), 339-352. doi:10.1002/ab.20190 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/ab.20190/epdf
Publication details
Publication title
Aggressive Behavior
Document title
A latent variable modeling approach to identifying subtypes of serious and violent female offenders
Publisher
Wiley Online Library
Date
2009
Volume
33
Issue
4
First page
339
Last page
352
Publisher DOI
10.1002/ab.20190
Published article URL
Copyright statement
Copyright is held by the author(s).
Scholarly level
Peer reviewed?
Yes
Funder
Language
English
Member of collection
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