NCJ Number
251886
Journal
Journal of Quantitative Criminology Volume: 33 Issue: 1 Dated: March 2017 Pages: 131-155
Date Published
March 2017
Length
25 pages
Annotation
Recognizing the inherent variability of drug-related behaviors, this study developed an empirically-driven and holistic model of drug-related behavior during adolescence, using factor analysis to simultaneously model multiple drug behaviors.
Abstract
The factor analytic model uncovered latent dimensions of drug-related behaviors, rather than patterns of individuals. These latent dimensions were treated as empirical typologies, which were then used to predict an individual's number of arrests accrued at multiple phases of the life course. The data were sufficiently robust to simultaneously capture drug behavior measures typically considered in isolation in the literature, and to allow for behavior to change and evolve over the period of adolescence. Results indicate that factor analysis is capable of developing highly descriptive patterns of drug offending, and that these patterns have great utility in predicting arrests. Results further demonstrate that although drug behavior patterns were predictive of arrests at the end of adolescence for both males and females, the impacts on arrests were longer lasting for females. The researchers note that various facets of drug behaviors have been a long-time concern of criminological research; however, the ability to model multiple behaviors simultaneously is often constrained by data that do not measure the constructs fully. In the current study. Factor analysis is shown to be a useful technique for modeling adolescent drug involvement patterns in a way that accounts for the multitude and variability of possible behaviors, and in predicting future negative life outcomes, such as arrests. (Publisher abstract modified)