Profiles of behavioral health service utilization among youth involved in the juvenile legal system.

Abstract

Background: Juvenile legal-involved youth (JLIY) experience behavioral health conditions at more than twice the rate of their peers yet face significant barriers to accessing care. These barriers span predisposing (demographic and social), enabling (logistical and resource-related), and need-based (clinical) factors. To better understand how JLIY navigate the fragmented behavioral healthcare system, we examined their use of services across eight different sectors, including formal treatment settings, non-specialized systems (e.g., schools and courts), and informal community supports.

Methods: We surveyed 100 caregiver-youth dyads enrolled in a juvenile court diversion program, all of whom had youth with documented behavioral health needs. We collected information on caregiver and youth demographics, behavioral health symptoms, treatment barriers, motivation for treatment, and service utilization. Latent Class Analysis (LCA) was used to identify distinct patterns of youth behavioral health service utilization across eight care sectors. Multinomial logistic regression was then conducted to examine how predisposing, enabling, and need-based factors, guided by the Andersen Behavioral Model of Health Services Use, predicted class membership.

Results: On average, youth accessed services in 4 of the 8 behavioral health care sectors. Service sectors utilized by JLIY included school-based support (86%), outpatient care (67%), community network supports (61%), crisis services (59%), general healthcare (58%), juvenile legal services (32%), inpatient care (26%), and residential treatment (11%). Latent Class Analysis revealed three distinct service use profiles: (1) low-intensity, school-centric users; (2) high-intensity, multi-sectoral users; and (3) moderate-intensity, community-based users. Class membership was significantly associated with child welfare involvement, court-mandated treatment, caregiver trauma exposure, caregiver motivation for youth treatment, and youth symptom severity.

Conclusion: JLIY navigate a wide range of behavioral health services, often in fragmented or reactive ways. While individual need was a strong predictor of service use, enabling factors such as caregiver influences and system mandates also played a critical role. The reliance on school-based services suggests systemic gaps, and extensive multi-sector involvement may reflect lack of integration across systems. Findings have implications for policy, including the need to strengthen cross-system coordination among juvenile legal, school and behavioral health systems; expanded family-centered service navigation; and improved access to community-based care before needs escalate.