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Arely M. Hurtado1,2, Phillip D. Akutsu2, & Deanna L. Stammer1

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Presentation on theme: "Arely M. Hurtado1,2, Phillip D. Akutsu2, & Deanna L. Stammer1"— Presentation transcript:

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) We know that in the recent years, juvenile arrest has been declining. However, research suggest that as many as 70% of youth with juvenile justice contact have a diagnosable mental health problem. We also know that there is no single risk factor. It is a complex issue with multiple contributing factors including Individual, Peer, Family, School and Community. For example, research suggests that males are more likely to report being arrested, however, female arrest rates are rising. Also, Ethnic minority groups and mental health problems, we have found that externalizing mental health problems like aggression are more likely to report being arrested than those with internalizing mental health problems such as depression. Other factors including early exposure to violence, school truancy/absenteeism, negative peer influences with others who have negative contact with police, and community disengagement has been found to be correlated to higher likelihood of arrest.

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 ( ). Variables Percentage Sex – Female 46% Ethnicity African American 19% Asian American 4% Latino 52% White American 26% Age Young Age 49% Middle Age 37% Old Age 14% Living Situation – Permanent 89% Preferred Language – English Arrested 15%

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
Variables M or % SD Psychosocial Variables Externalizing MH Problem 0.93 0.65 Internalizing MH Problem 0.76 0.53 Substance Abuse 0.48 0.73 History of Delinquency 0.20 0.45 Delinquency Influences 0.25 0.57 Violence History 0.14 0.39 Violence Emotional Behavioral Risk 0.19 0.47 Resiliency to Violence 0.61 School Nonattendance 0.72 0.99 Community Involvement 1.87 1.03 Dependent Variable Juvenile Arrest 15% -

7 Predicting Juvenile Arrest
Logistic regression model Significant: χ²(11, N = 1,862) = , p < .001 Cox & Snell pseudo-R² = .25. Variable B S.E. Wald Comparative Group: Young Age Middle Age 1.06*** 0.19 30.07 Old Age 0.74** 0.26 8.48 Living Situation – Permanent -0.71** 0.22 10.48 Preferred Language - English -0.70* 0.35 4.02 Externalizing MH Problem 0.94*** 0.17 29.90 Substance Abuse 0.65*** 0.11 35.84 History of Delinquency 1.09*** 0.23 23.21 School Non-attendance 0.23** 0.78 8.84 Community Involvement -0.37*** 0.09 17.26 * 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! 10


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