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Predicting Juvenile Arrest Among Culturally Diverse Youth in Mental Health Treatment

This study explores predictors of juvenile arrest among culturally diverse youth in mental health treatment, including demographics, psychosocial issues, and risk factors. Findings suggest age, substance abuse, and delinquency history influence arrest likelihood.

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Predicting Juvenile Arrest Among Culturally Diverse Youth in Mental Health Treatment

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  1. Predicting Juvenile Arrest Among Culturally Diverse Youth Referred for Mental Health Treatment Arely M. Hurtado1,2, Phillip D. Akutsu2, & Deanna L. Stammer1 Uplift Family Services1& California State University, Sacramento2

  2. INTRODUCTION • Up to 70% in juvenile justice have a mental health (MH) problem • Mental health services are often inadequate or unavailable (U.S. Department of Justice, 2011) • Incarcerated youth continue to have problems throughout their life (Health Policy Institute, 2019) • Risk factors include: • Individual (e.g., gender, race/ethnicity) • Peer (e.g., delinquent or aggressive peers) • Family (e.g., parental criminality) • School (e.g., attendance) • Community (e.g., instability)

  3. Hypotheses • Positive Predictors • Demographics • Males • Ethnic Minorities • Middle Age • Older Age • Living Situation: Temporary • Psychosocial Issues • Externalizing MH Problems • Substance Abuse • History of Delinquency • Delinquency Influences • Violence History • School Non-attendance • Negative Predictors • Demographics • Younger Age • Living Situation: Permanent • Psychosocial Issues • Internalizing MH Problems • Resiliency to Violence

  4. Method: Participants • Participants (N = 1862) • First-time youth (12-19 y/o) referred to a single mental health network in California (2012-2017).

  5. meTHOD: mEASUREs • Child and Adolescent Needs and Strengths (CANS) scale • 4-point scale • Range: 0 = No Problem to 3 = Severe Problem • Community Life • Higher scores: Greater community involvement • Assessment: First month • Juvenile Arrest: Yes/No • Self-Report

  6. Results: Descriptive statistics

  7. Predicting Juvenile Arrest • Logistic regression model • Significant: χ²(11, N = 1,862) = 530.01, p < .001 • Cox & Snell pseudo-R²= .25. * p < .05, ** p < .01, *** p < .001 Note: Different asterisks denotes level of significance.

  8. DISCUSSION • Hypotheses: Partially supported • Strongest predictors • Substance Abuse • Middle age • Externalizing MH problems • History of Delinquency • Limitations • Low levels of arrest: 15% • Self-Report • Correlational, not causal relationship • Type of arrest?

  9. RECOMMENDATIONS • Age effects • Tailor treatment plans to specific age groups • Higher arrest, higher recidivism • Significance of living situation • Higher client monitoring: ↓ Juvenile arrest • Externalizing MH problems • Co-occurring externalizing MH problems and substance abuse

  10. THANK YOU!

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