Methods: Latent profile analysis (LPA) was used to identify clusters of juvenile offenders based on clinically relevant measures of psychiatric symptoms (including past traumatic experiences), lifetime substance use, and drug and alcohol related problems stemming from the use of psychoactive substances in a statewide population (n = 723). Next, additional covariates were employed to fully delineate identified clusters. Final cluster solutions were based on maximum likelihood estimation using the Bayesian Information Criterion (BIC) and other fit indices such as class error, number of parameters, and entropy. Finally, bootstrapping methods were used to compare model fit of final clusters.
Results: Findings revealed that a 4-class solution fit the data optimally. The four classes identified represented a severity-based gradient of symptom and substance use endorsement ranging from a mild subgroup (n = 195; 27.0%), to moderately low (n = 250; 34.6%) and high (n = 197; 27.2%) subgroups and finally a severely distressed subgroup (n=81; 11.2%).
Implications: Overall, findings suggest that juvenile offenders exhibit considerable variation in severity and persistence of mental health and substance use problems. Accordingly, interventions in the juvenile justice system should be designed to address treatment needs along a continuum of problem behavior. It is equally important to note that many youth may not require mental health services; thus, additional resources can be redirected toward providing more intensive treatment to those juvenile offenders who are severely distressed. Study findings also have juvenile justice policy implications. For example, we identified a large class (n =195, 26.9% of total) that possibly could have been diverted at the adjudication stage from state-level residential placement. Relative to their counterparts, this class possessed fewer cumulative risk factors. This finding is troubling given that contact with the criminal justice system can interrupt adolescent development and psychological adjustment (Steinberg, Chung, & Little, 2004). Findings here are relevant to risk-need-responsivity principles based on treatment of moderate- and high-risk cases and the importance of addressing criminogenic needs and employing empirically based social-learning techniques (Andrews, 2006).