System Backgrounds,Psychosocial Characteristics,and Service Access Among Dually Involved Youth: A Los Angeles Case Study

Abstract

Dually involved youth are youth who are concurrently involved in both the child welfare and juvenile justice systems. Dually involved youth require a broader array of services compared to single-system youth though less is known about what types of services youth ultimately access while under the supervision of both systems. The current study examines the juvenile justice and child welfare histories, psychosocial characteristics, and predictors of rearrest among the dually involved population in Los Angeles County (N = 718) as well as the services youth are referred to and utilize among a subsample of dually involved youth tracked postdisposition (n = 152). Findings reveal an increased representation of females and an overrepresentation of African Americans among the sample. In fact, African American youth in Los Angeles County are disproportionately dually involved at a rate almost 6 times their general population numbers (7.4% vs. 43%). Youth histories show significant involvement in both systems with 33% of the sample having been arrested prior to the current referral, and youth having an average of 10.8 referrals to child welfare in their past. Youth exhibited high levels of behavioral health issues, which were associated with rearrest. Youth were referred to a broad range of services, though not all of them were accessed. Placement changes and contact with probation officers were identified as both challenges to and facilitators of service access in unique ways.

Keywords

juvenile justice child welfare service access mental health dually involved youth

Dually involved youth are youth who are concurrently involved in both the child welfare and juvenile justice systems. These multisystem youth often exhibit higher rates of mental health needs, substance use, and education-related challenges, including truancy and academic issues, than youth involved in only one system of care or without system involvement (Herz & Ryan, 2008; Herz, Ryan, & Bilchik, 2010; Leone & Weinberg, 2012). As a higher needs population, dually involved youth arguably require a broader array of services compared to single-system youth, particularly later in life. Recent research among young adults who were system involved as adolescents in Los Angeles and New York City underscores this point (Culhane et al., 2011; New York City Office of the Mayor, Center for Innovation Through Data Intelligence, 2015). These studies reveal significant service utilization (e.g., Medicaid, emergency department visit, inpatient, and jail stay) for dually involved young adults compared to those with a history of juvenile justice or foster care only (Culhane et al., 2011; New York City Office of the Mayor, Center for Innovation Through Data Intelligence, 2015). For instance, in New York City, about 94% of young adults with a history of dual involvement were later involved in at least one service domain (i.e., homeless services, justice services, foster care, financial assistance, and health services), 80% in two or more domains, and 50% in three or more domains. Similar data from Los Angeles County corroborate this trend with almost identical percentages, indicating that multisystem involvement often creates long-term dependency on additional systems and subsequent higher costs (New York City Office of the Mayor, Center for Innovation Through Data Intelligence, 2015). The estimated average cumulative cost of service usage for young adults with a history of dual involvement was estimated at US$65,424 compared to US$47,854 for the justice-only group and US$46,670 for the foster care only group (New York City Office of the Mayor, Center for Innovation Through Data Intelligence, 2015).

Long-term service utilization and high costs continuing into adulthood may be associated with unmet or unaddressed behavioral health needs during childhood or adolescence (i.e., mental health, substance abuse/use, behavior, and crisis intervention). Some researchers suggest a causal association between these early behavioral health needs, and childhood maltreatment and delinquency (Bender, 2010; Kerig & Becker, 2010; Smith & Thornberry, 1995; Thornberry, Ireland, & Smith, 2001). The experiences of maltreatment and trauma during childhood and adolescence can disrupt the brain’s typical development and physical structure, exposing maltreatment victims to a great risk of mental health issues (Teicher, et al., 2003). Additionally, victims may utilize alcohol and drugs as a means of coping with their maltreatment, a practice that often necessitates risky or delinquent behavior (Bender, 2010). Therefore, addressing behavioral health issues through appropriate services may be considered an appropriate intervention in order to disrupt the factors that contribute to dual involvement, delinquency, and/or recidivism.

Studies that show high long-term service costs for dually involved youth also emphasize the need to implement effective and targeted services prior to the transition to adulthood to ensure youth can go on to live healthy, safe, and productive lives. Despite the important role of services in the lives of dually involved youth and the energy expended by multiple systems that fund and administer these services, there is very little research on what type of services are available to, and utilized by, dually involved youth. Previous research, utilizing a subsample from the current study, focused on education-related issues and services which revealed discrepancies between service needs, referrals, and access (Hirsch, Dierkhising, & Herz, 2018). The current study looks more comprehensively at behavioral health needs and service access among the dually involved population in Los Angeles County, CA. Specifically, we examine the behavioral health needs of dually involved youth, the services youth are referred to and utilize, and factors associated with service access.

Behavioral Health Needs Among Dually Involved Youth

The literature clearly illustrates the behavioral health needs of those who are involved in the child welfare and juvenile justice systems independently. For instance, national studies reveal up to 70% of justice-involved youth have been identified as having a mental health diagnosis, with many youth experiencing dual diagnoses (Abram et al., 2013; Schufelt & Cocozza, 2006; Teplin, Abram, McClelland, Dulcan, & Mericle, 2002). Of those identified with a mental health diagnosis, nearly 61% had a co-occurring substance use disorder (Schufelt & Cocozza, 2006). Thus, in many instances, youth are using substances to self-medicate and treat their own disorders, which can lead to further involvement within the systems. Trauma exposure and post-traumatic stress symptoms are common among justice-involved youth (Dierkhising et al., 2013) with as many as 50% of girls meeting criteria for post-traumatic stress disorder (PTSD; Cauffman, Feldman, Waterman, & Steiner, 1998; Kerig & Becker, 2012). In a study of juvenile justice–involved youth who experienced detention, 93% of youth with PTSD diagnoses suffered from at least one comorbid psychiatric disorders, such as anxiety or substance use (Abram et al., 2013).

Nationally representative data also reveal that children and youth involved in child welfare have high rates of mental health needs, substance abuse issues, and trauma exposure. For instance, up to 50% of youth involved in child welfare have severe behavioral or emotional problems (Burns et al., 2004; Heneghan et al., 2015). These problems are prevalent among older children as well as very young children with up to one third of toddlers displaying a social–emotional problem on standardized assessments (McCue Horwitz et al., 2012). The developmental trauma framework highlights how severe or chronic trauma exposure among child welfare (and other system) involved children and youth is associated with poor outcomes such as affect dysregulation, behavioral problems, relational problems, and post-traumatic stress symptoms (D’Andrea, Stolbach, Ford, Spinazolla, & Van der Kolk, 2012; Kisiel et al., 2014; van der Kolk, 2005).

Given the extensive documentation of behavioral health needs among single-system youth, it is not surprising that research consistently identifies similarly high rates in the dual system population. A nationally representative study, for example, used data from 92 different counties collected in the National Survey of Child and Adolescent Well-Being. Study results revealed that youth with co-occurring maltreatment and delinquency had the highest rate of substance abuse (79%) and mental health problems (76%) when compared with youth in care of solely child welfare or juvenile justice (Chuang & Wells, 2010). An analysis of case files of 204 dually involved youth in Arizona found 80% had some level of substance use issues while 61% had some level of mental health or emotional issues (Halemba, Siegel, Lord, & Zawacki, 2004). In a similar study in Los Angeles County, 83% of dually involved youth had an identified behavioral health issue with 38% having co-occurring substance abuse and mental health issues (Herz & Ryan, 2008; Herz et al., 2010).

Behavioral Health Needs and Recidivism Among Dually Involved Youth

Substance abuse has been identified as a significant and consistent risk factor for recidivism among dually involved (Herz et al., 2010) and dually adjudicated youth (Baglivio et al., 2016) despite distinct differences in these subpopulations. Herz, Ryan and Bilchik (2010) used a sample of dually involved youth in Los Angeles County (N = 581), and Baglivio et al. (2016) used a sample of deep-end juvenile justice–involved youth completing a postdisposition residential program in Florida (N = 12,955). Among the dually involved youth in Los Angeles, age of first arrest and the presence of substance abuse, truancy, or probation violations were four factors positively associated with recidivism; youth with substance use issues and truant youth being twice as likely to recidivate compared to youth who did not face those issues (Herz et al., 2010). Similarly, for those deep-end dually involved youth, substance abuse, a history of delinquency, and school conduct issues were significant predictors of recidivism, although only among the males in the study (Baglivio et al., 2016). While substance use has been associated with recidivism in the broader literature on juvenile and adult offenders, the existing research is rarely limited to the dually involved population and has produced mixed evidence as to whether or not substance use is an independent predictor of recidivism (e.g., Chassin, 2008; Cottle, Lee, & Heilbrun, 2001; Dowden & Brown, 2002; Putnins, 2003; Stoolmiller & Blechman, 2005).

Several evaluations of behavioral health treatment programs suggest that they may contribute to a reduction in recidivism among system-involved youth, though few studies explicitly examine the subpopulation of youth that are dually involved (e.g., Foster, Qaseem, & Connor, 2004; Hiller, Rosenthal, Bornstein, Berry, & Brunell-Neuleib, 1999; Pullman et al., 2006). Interestingly, few studies that do examine the dually involved population identify a positive correlation between recidivism or delinquency and behavioral health treatment. Herz, Harada, Lecklitner, Rauso and Ryan (2009); Goodkind, Shook, Kim, Pohlig, and Herring (2013); and Jonson-Reid (2002) all show an increased risk of delinquency or recidivism for youth participating in behavioral health treatment. This does not suggest, however, a causal relationship between treatment and delinquency. In some cases, treatment use in a study served to identify youth with behavioral health needs when specific mental health and substance abuse assessment information was not available (Goodkind, Shook, Kim, Pohlig, & Herring, 2013; Jonson-Reid, 2002). Thus, treatment was used as a proxy for another variable (e.g., mental health need). As Goodkind et al. (2013) notes, this positive association between service utilization and delinquency is present across gender and racial demographic only when considering services administered before and after juvenile justice involvement. When limiting the evaluation to services utilized prior to juvenile justice involvement, the positive treatment-delinquency association is only present for White boys (Goodkind et al., 2013). This suggests that many youth have unmet treatment needs prior to their entrance into the juvenile justice system. It is important to note that these studies treat behavioral health treatment as a dichotomous variable and are unable to assess the severity of youth’s mental health symptoms, type of mental health problem, or whether the youth were receiving evidence-based treatments aligned with the youths’ individual risks and needs (Herz, Harada, Lecklitner, Rauso, & Ryan, 2009).

Behavioral Health Services and Dually Involved Youth

Meeting the complex treatment, service, and supervision needs of dually involved youth is important for successful outcomes. Conducting assessments and providing appropriate levels of supervision and treatment to dually involved youth can be particularly challenging because it requires coordination across the dependency and delinquency court systems and their affiliated agencies. The academic literature on best practices with dually involved youth is sparse, but not surprisingly, the growing body of research on dually involved youth underscores the necessity of interagency collaboration to comprehensively understand and appropriately address the risks and needs of dually involved youth (Culhane et al., 2011; Halemba et al., 2004; Herz & Ryan, 2008; Siegel & Lord, 2004; Stewart, Lutz, & Herz, 2010; Wiig & Tuell, 2004). Chuang and Wells (2010) identified the conditions in which interagency collaboration increases access to behavioral health treatment for dually involved youth. Specifically, sharing administrative data and assigning a single agency—either the juvenile justice or the child welfare system—as being accountable for a youth’s treatment increased the likelihood of a youth receiving treatment (Chuang & Wells, 2010). This study, however, did not address whether such treatments were appropriate or effective in addressing the behavioral health needs of dually involved youth.

Coordinating community-based services across juvenile justice, child welfare, and other related systems through a wraparound or system-of-care model may be helpful in improving behavioral health outcomes and reducing recidivism for this population (Herz et al., 2009; Pullmann et al., 2006). Relatedly, one promising practice for dually involved youth is the use of multidisciplinary teams (MDTs) to ensure dually involved youth are receiving comprehensive assessments and case plans through an integrated-system approach (Halemba et al., 2004; Siegel & Lord, 2004; Stewart et al., 2010). To improve the integrated care dually involved youth received, Los Angeles County began implementing an MDT model in 2012.

Dually Involved Youth in Los Angeles County

Los Angeles County is home to the largest juvenile justice system in the country. Approximately 135,000 allegations of child abuse or neglect were made in 2014 in Los Angeles County; of those, about 26,000 were substantiated and about 10,000 entered foster care (Webster et al., 2018). Studies completed in Los Angeles County have found that about 100 foster youth are arrested each month, and between 7% and 10% of dependent youth (i.e., in the care and supervision of the child welfare system) who are 7 years or older will eventually cross into the delinquency system (Ryan, Herz, Hernandez, & Marshall, 2007). This percentage increases to 23.5% for youth who are identified as high risk for delinquency (Bogie, Johnson, Ereth, & Scharenbroch, 2011). Similarly, up to 83% of youth exiting a probation placement (group home or correctional placements) have been found to have a history of child welfare contact (i.e., referral; Herz et al., 2015, 2017).

Los Angeles County utilizes the MDT model, a cross-system collaborative approach, in accordance with the California Welfare and Institutes Code 241.1. This code requires child welfare and probation agencies to conduct a joint assessment to assist in determining the best-case plan for a youth who crosses over from the child welfare system to the delinquency system. In 2007, this approach was piloted, and by 2012, the MDT approach was implemented throughout the county. MDTs in Los Angeles County are comprised of a Department of Children and Family Services (DCFS) social worker, a deputy probation officer, a Department of Mental Health (DMH) court services clinician, and an education consultant. Together, each of these representatives collects their information from their respective agencies and works collaboratively to assess the case and provide joint recommendations to the court.

While MDT approaches are used in many other jurisdictions, the Los Angeles 241.1 MDT is unique in several ways. First, it is used for all youth with an open child welfare case who are subsequently petitioned to delinquency court. Typical MDTs may have certain triggering events or can be requested by stakeholders in the case, but they are not typically applied to all dually involved youth by statute. Second, the 241.1 MDT can recommend an array of dispositional options ranging from diversion to dual jurisdiction (i.e., retaining both the child welfare case and becoming a ward of the delinquency court) to delinquency wardship (i.e., the child welfare case is closed). While MDTs can result in recommendations to the court or collaboratively developed case plans, the statutory authority of the 241.1 MDT to weigh in on questions of wardship is unique. Finally, the 241.1 MDT captures referral information from all agencies as well as follow-up data in an online database (see Herz, 2015, for more description of the database), providing data and information not routinely collected.

The current study uses data drawn from the 241.1 MDT online database between October 1, 2013, and July 31, 2014, to inform practice in Los Angeles County as well as jurisdictions across the country on how best to address the service needs of dually involved youth. Specifically, the aims of this study are as follows. First, we aim to describe the characteristics of dually involved youth with a focus on psychosocial characteristics (e.g., mental health, substance abuse, and placements) and their involvement (both previous and current) with child welfare and juvenile justice systems. Second, we aim to identify predictors of rearrest for dually involved youth. Finally, we describe service referrals and service access by dually involved youth and identify factors either aiding or impeding service access.

Method

The current study capitalizes on an initiative in Los Angeles County to enhance practice related to dually involved youth. This initiative included the launch of an online database to capture information collected as part of the 241.1 MDT process by all participating agencies (i.e., Probation, DCFS, DCFS Education Consultants, and DMH). The database includes all youth who receive a 241.1 referral and captures two types of data: (1) referral data (i.e., baseline) and (2) tracking data (i.e., 6-month postdisposition follow-up). Referral data include all information collected by each agency about the youth prior to their arrest as well as some postarrest/precourt appearance indicators, such as rearrest prior to the disposition hearing. Tracking data capture a limited number of outcomes within 6 months after youth received their dispositions. Referral data are captured on all referrals; however, tracking data are only collected on a small subsample of youth (n = 152) who received their court dispositions between October 2013 and July 2014. The tracking component was unfunded and required staff from multiple agencies to enter data on top of their professional responsibilities. Because of this, and the depth of the data, the tracked data are only collected on this small subsample. Researchers from Cal State Los Angeles received deidentified data for analysis. The use of these data for analysis was approved by the first and second authors’ institutional review board and by the Los Angeles County Juvenile Court through a court order.

Referral Data

Referral or baseline data include information collected from both child welfare and juvenile justice files for all youth at the time of their referral to the 241.1 MDT unit. All data are entered using a standard form developed for the 241.1 MDT units based on the agencies role. For the current study, the sample is refined to include only (1) youth who were declared dependent at the time of the referral and were petitioned to the delinquency court and (2) unique referrals for an initial MDT assessment (youth may receive multiple referrals and therefore may be redundant in the data system). This yielded 718 unique youth, who had an open child welfare case, were arrested and referred to the 241.1 MDT unit during the study time frame.

Child welfare characteristics

Child welfare information was provided by DCFS and includes official information related to the youth’s history in the child welfare system. These data include the number of referrals to the child welfare system (regardless of substantiation), the length of stay in the system, number of placements and type of placements, and the youth’s permanency goal at the time of the referral. The permanency goal at the time of referral indicates the long-term plan for the youth at the time of the MDT referral. Permanency goals include guardianship, reunification, legal guardianship, adoption, or permanent planned living arrangement (PPLA). PPLA includes kinship care, foster care, and congregate care. It is important to note that the time of referral may be at different vantage points throughout the DCFS case; thus, the permanency goal may change when tracked. DCFS workers are required to participate in concurrent planning for a youths’ permanency as circumstances change and it is possible that a new safety concern or development may arise throughout the case (Welfare and Institutions Code 16500-16523.1). For the number of placement changes in the youth’s child welfare history, the count of placements in foster care, congregate care (i.e., group home), relative placements, residential treatment facilities, hospitalizations, and an open-ended “other” placement type were summed to create a count variable.

Juvenile justice characteristics

Information related to juvenile justice involvement and history was entered by the Probation Department. These data include official information related to arrest history; type of current charge; preadjudication detention decision, where the arrest occurred; the MDT’s recommendation to court; and the court’s disposition.

Type of charge was coded as either a felony, misdemeanor, or 707(b) offense. According to California’s Welfare and Institutions Codes, 707(b) offenses are considered the more serious offenses and span a broad range of offenses such as murder, rape, robbery, and assault with a deadly weapon, these offenses can be considered for transfer to adult court (Welfare and Institutions Code section 675-714). For the regression and correlational analyses, the offenses were ranked from misdemeanor to 707(b).

Rearrest in this study was measured by whether the youth had a new arrest or a new status offense between the original referral arrest and the preplea court date for all referrals. It is important to note that the time frame between these two points varies across youth due to various factors that influence the scheduling of court hearings for any particular case. However, rearrests occurred within a 6-month time frame following the referral arrest. Additionally, it was possible for a youth to have multiple arrests during this time, but for this study, rearrest was dichotomized to capture whether a youth received at least one new arrest or a new status offense (or both) during the designated time frame (new arrest = 1). This information was taken from the baseline data and is a measure of rapid rearrest rather than recidivism, given that it occurs prior to a hearing on the original/referral arrest.

Behavioral health needs and psychosocial characteristics

Psychosocial information was entered by DMH and education liaisons housed in DCFS. For the current study, we focused on the DMH information, for an overview of the education data, see Hirsch et al. (2018). DMH information includes whether the youth was receiving mental health services at the time of arrest, whether the youth has a history of substance abuse, whether the youth has a mental health diagnosis, and whether the youth was prescribed (and taking) psychotropic medications (no = 0, yes = 1, for all behavioral health and psychosocial variables).

Tracked Data

Tracked data were collected for a period of 6 months post the disposition by all involved agencies and include a list of services that the youth was referred to and the status of service access. The three domains of services are mental health services, education services, and substance abuse services. Within each domain of service, there are a variety of different types of services a youth may be referred to or access (see Table 1, for a description of these services). A service was coded as being “accessed” (accessed = 1) if a youth had completed the service or was attending the service. If it was indicated that the youth was not attending, was referred only, waitlisted, or terminated the service, the service was coded as “not accessed” (not accessed = 0).

Table 1.

Service Referrals and Access for the Tracked Dually Involved Youth.

Services	Referred (%)	Accessed (%)	Unknown/Missing (%)
Mental health services
Individual therapy	73.7	54.6	0.7
Group therapy	34.9	23.7	0.7
Medication monitoring	32.9	15.1	2
Family therapy	28.9	17.1	0.7
Wraparound	25.0	17.1	—
Other mental health service	7.2	3.9	0.7
Therapeutic behavioral services	3.9	2	—
Cognitive-behavioral therapy	3.9	2.6	—
Full service partnership	0.7	0.7	—
Functional family therapy	2.0	—	—
Trauma-informed care	1.3	0.7	—
Substance abuse/use interventions
Alcohol/drug education	29.6	16.4	2.6
Other substance abuse service	26.3	21.7	0.7
Alcohol/drug outpatient	17.1	9.9	0
Alcohol/drug inpatient	14.5	8.6	2
Education services
Tutoring	43.4	17.1	—
Youth enrolled in school	30.3	24.3	1.3
Daily attendance monitoring	33.6	22.4	2.6
Credit recovery program	27.6	13.8	0.7
Appointment with school counselor	21.1	8.6	—
Individualized Education Plan team meeting	21.1	7.9	1.3
California High School Exit Exam preperation	21.1	5.9	0.7
AB 167 appropriate	20.4	9.9	1.3
Weekly attendance monitoring	14.5	6.6	0.7
Graduation status check	13.2	7.2	—
Career survey	10.5	2	2
Behavioral support services	9.9	3.3	0.7
Student support team	7.9	—	—
Adult responsible for education rights	7.2	2.6	—
Educationally related mental health service	5.9	0.7	0.7
317 e-Referral	4.6	0.7	—
Other education service	4.6	0.7	0.7
Regional center referral	2.6	—	—
Functional behavioral analysis	2.0	—	—
Functional analysis assessment	1.3	—	0.7
Monthly attendance monitoring	0.7	—	—

Note. Percent accessed and unknown are of those who were referred not of the total sample.

Results

Both the referral data (i.e., all dually involved youth) and the tracked youth (i.e., the subsample followed over time) are described below. For comparison purposes, we separate the subsample of tracked youth when describing their demographics, backgrounds, and characteristics. In addition, we include whether there were significant differences between the tracked sample and the full sample. However, it is important to recall that the tracked youth are also counted among the full sample.

Demographic Information

Of the youth with an open dependency case who were criminally charged (i.e., dually involved youth) and referred to the 241.1 MDT units (N = 718), nearly 40% were female (39.6% all youth, 37.5% tracked youth) and 15.8 years old on average (see Table 2). Referred youth were mostly Latino (46.8% all youth, 41.9% tracked youth) and African American (42.6% all youth, 44.2% tracked youth); with 9.3% of all youth Caucasian (10.1% tracked youth) and 1.2% Other for all youth (3.9% tracked youth). The most common living situation for youth at time of arrest was at a group home (38.2% all youth, 39.5% tracked youth). Many youth were absent without leave (AWOL) at time of arrest (19.6% all youth, 15.8% tracked youth).

Table 2.

Demographic Information.

Demographic Variables	All Dually Involved Youth (N = 718)	Tracked Youth (N = 152)
Gender
Female	39.6%	37.5%
Male	60.4%	62.5%
Race/ethnicity
African American	42.6%	44.2%
Latino/Hispanic	46.8%	41.9%
Caucasian	9.3%	10.1%
Other	1.2%	3.9%
Average age at time of referral	15.82	15.82
Living situation at time of referral
Group home	38.2%	39.5%
Home	23.7%	23.0%
Relative (includes legal guardian)	19.0%	23.6%
Foster care or legal guardian	15.4%	12.5%
Other/missing	3.8%	1.3%
AWOL at time of arrest	19.6%	15.8%

Note. AWOL = absent without leave.

Child Welfare Characteristics

On average, youth were referred to child welfare 10 times (10.8 referrals all youth, 9.8 referrals tracked youth) with a range from 0 to 58 times for all youth and 0 to 52 times for tracked youth (see Table 3). Youth spent just over 5 years, on average, in DCFS care, either consecutive or nonconsecutive time. The most common permanency goal was PPLAs. Many youth had a history of placement instability in the child welfare system with an average of about eight placement changes; however, there is significant variation in this variable (SD = 11.6, range = 0–114 all youth; M = 6.00, SD = 9.35, range = 0–61 tracked youth) and those who were tracked had significantly less placement changes compared to the full sample, F(1, 716) = 5.70, p < .05.

Table 3.

Child Welfare Characteristics.

Child Welfare Variables	All Dually Involved Youth (N = 718)	Tracked Youth (N = 152)
Average number of referrals for youth’s family	10.8 (SD = 7.8)	9.9 (SD = 8.4)
Average number of years in the system	5.3 (SD = 4.6)	5.4 (SD = 6.4)
Percentage of time that was consecutive while in the system	57.1%	59.2%
Percentage with prior 241.1 referral	14.8%	11.2%
Permanency goal at time of referral
Permanent planned living arrangements	41.1%	35.5%
Reunification	25.6%	28.9%
Remain at home	22.4%	21.1%
Guardianship	6.8%	9.9%
Other	2.7%	3.3%
Missing	1.4%	—
Number of placement changes in child welfare ever^a	8.14 (SD = 11.6)	6.00 (SD = 9.35)

^a Significant difference between tracked and nontracked youth (p < .05).

Juvenile Justice Characteristics

As shown in Table 4, the most common referral offense was for a violent offense (42.2% all youth, 44.7% tracked youth), of which about two thirds were assault related (66.7% all youth, 70.6% tracked youth), followed by property offenses (27.2% all youth, 29.6% tracked youth) and other (30.1% all youth, 25.7% tracked youth; e.g., trespassing, criminal threats, and vandalism). Of all these charges, nearly one third were related to the youth’s living situation (27.7% all youth, 30.9% tracked youth). About one third of youth had been arrested prior to the referral arrest (32.9% all youth, 27% tracked youth), with about one quarter having a prior status offense (25.2% all youth, 20.4% tracked youth). Many youth were detained at the time of arrest, though the tracked youth were detained at arrest significantly less compared to the full sample (χ² = 9.10, p < .05).

Table 4.

Juvenile Justice Characteristics.

Juvenile Justice Variables	All Dually Involved Youth (N = 718)	Tracked Youth (N = 152)
Detained at time of arrest^a	38.3%	27.0%
Most serious current charge
Violent offense	42.2%	44.7%
Percentage of violent offenses involving an assault	66.7%	70.6%
Property offense	27.2%	29.6%
Other offense	30.1%	25.7%
Type of charge
Felony	51.9%	47.4%
707b Offense	9.1%	8.6%
Misdemeanor	38.7%	44.1%
Current offense related to
Living situation	27.7%	30.9%
School	17.7%	19.1%
Missing data	5.3%	4.6%
Prevalence of prior offenses
Criminal charges	32.9%	27.6%
Status offenses	25.2%	20.4%
Missing data	5.3%	—
Average number of prior offenses
Criminal charges	1.7 (SD = 1.3)	1.6 (SD = 1.3)
Status offenses	3.1 (SD = 4.7)	3.0 (SD = 3.7)

Note. Youth may have multiple charges across offense categories; thus, the offense categories do not add up to 100%.

^a Significant difference between tracked and nontracked youth (p < .05).

Psychosocial Characteristics

Regarding mental health information, the majority of youth had a diagnosed mental health problem at the time of arrest (74.5% all youth, 78.9% tracked youth). Approximately half of youth were receiving mental health services at the time of the referral (44% all youth, 53.3% tracked youth) and approximately one quarter were prescribed psychotropic medications (26.4% all youth, 27% tracked youth). Of those who were prescribed psychotropic medications, about half (55% all youth, 53.7% tracked youth) reported actually taking the prescribed medication. Finally, most youth (58.7% all youth, 62.5% tracked youth) had some sort of substance abuse problem or pattern of substance use (see Table 5). The full sample had a significantly higher rate of substance abuse problems compared to the tracked sample (χ² = 4.41, p < .05).

Table 5.

Mental Health and Substance Use/Abuse Characteristics.

Mental Health and Substance Use/Abuse Variables	All 300 Youth With Pending Delinquency (N = 718; %)	Tracked Youth (N = 152; %)
Mental health history
Ever placed in psychiatric hospital	30.9	31.0
Experienced suicidal ideation	21.3	24.4
Ever attempted suicide	9.2	12.5
Prescribed psychotropic medication	26.3	27.0
Taking prescribed psychotropic medication	55.0	53.7
Has a mental health diagnosis	73.8	77.5
Receiving mental health services at time of arrest	44	53.3
Substance use/abuse^a
No substance abuse problem	21.9	30.9
Misuse/pattern of use	24.3	27.0
Abuse/dependency	34.4	35.5
Missing data	13.5	4.6

^a Significant difference between tracked and non-tracked youth (p < .05).

Factors Associated With Rearrest Prior to Court Appearance

Of the full sample, 10.6% were rearrested with a new criminal charge prior to the youth’s initial court appearance (e.g., preplea, predisposition) for the arrest that instigated the 241.1 referral, 3.3% had a new status offense, and, when combined, 12.3% were either rearrested or had a new status offense. To evaluate factors that increase or decrease the odds of rearrest prior to the youth’s initial court appearance, we ran a stepwise logistic regression model. In this model, all dually involved youth were included (i.e., the full sample) which represents baseline data only. Rearrest was a dichotomous variable combining both a new status offense and a new charge compared to having neither. In the first step, we controlled for gender and race/ethnicity, the second step included juvenile justice characteristics (i.e., severity of charge, number of prior arrests, and whether or not they were detained at arrest), and the third step included child welfare characteristics (i.e., number of referrals to child welfare and number of placement changes ever in child welfare). Finally, we included psychosocial risk and protective factors; specifically, whether the youth had a substance use or mental health issue and whether the youth was receiving mental health services at time of arrest. As shown in Table 6, there are four factors that predicted rearrest: a higher number of prior arrests (odds ratio [OR] = 1.248), the number of placement changes ever experienced in child welfare (OR = 1.03), having a substance abuse issue (OR = 3.465), and receiving mental health services at time of arrest (OR = 1.952).

Table 6.

Stepwise Logistic Regression Results for Demographics, Psychosocial, Child Welfare, and Juvenile Justice Characteristics Predicting Rearrest.

Predictor Variables	Model 1		Model 2		Model 3		Model 4
Predictor Variables	OR	Standard Error	OR	Standard Error	OR	Standard Error	OR	Standard Error
Demographics
Gender	1.288	0.27	1.188	0.276	1.286	0.282	1.283	0.287
Race/ethnicity	1.13	0.182	1.123	0.186	1.124	0.188	1.032	0.191
Juvenile justice characteristics
Severity of current charge			1.185	0.214	1.18	0.216	1.281	0.287
Number of prior arrests			1.32**	0.097	1.269*	0.101	1.248*	0.191
Detained at arrest			0.672	0.289	0.619	0.297	0.566	0.308
Child welfare characteristics
Number of child welfare referrals					0.996	0.019	0.999	0.019
Number of child welfare placements ever					1.03*	0.013	1.03*	0.013
Psychosocial characteristics
Substance abuse issue							3.465**	0.406
Mental health issue							1.07	0.392
Receiving mental health services							1.952*	0.279
Constant	0.091***	0.483	0.068***	0.616	0.057***	0.66	0.014***	0.814

Note. Males are the reference category in gender.

*p < .05. **p < .01. ***p < .001.

Service Referrals and Utilization

Tracking data capture the types of services youth were referred to and whether they accessed that service. It is important to note that 30 of the probation cases closed during the tracking time frame reducing the sample size in this analysis. These services fall into three categories: education-related services, mental health services, and substance abuse services. On average, youth were referred to 2.56 services in the mental health domain (SD = 1.19, range = 0–5), 3.55 in the education domain (SD = 2.59, range = 0–11), and 0.93 services in the substance abuse/use domain (SD = 1.01, range = 0–4). Overall 59.2% of youth accessed education-related services, 64.5% accessed mental health services, and 38.2% accessed substance abuse-/use-related services. Table 1 displays the breakdown of referrals and service access for each type of service within each domain. For a detailed overview of education-related services and education issues with this sample, see Hirsch et al. (2018).

From our previous work, we know that service access is not associated with recidivism during the tracking period for these youth (17 tracked youth were rearrested during the tracking period); however, service access, compared to referral rates, is low (Hirsch et al., 2018). Thus, in the current study, we evaluated factors that may impede (i.e., placement changes) or aid in service access (i.e., contacts with probation officer). Almost half of the tracked sample (42.7%) experienced a placement change during the tracking period. Results of one-way analyses of variance, with placement change as the factor and access to each service domain as the dependent variables, revealed a significant difference in service access for youth who experienced placement changes (see Table 7). For those who experienced a placement change, they were less likely to access education or mental health services. Conversely, youth who experienced a placement change were more likely to access substance abuse services. Additionally, correlation analyses revealed a positive significant association between face-to-face contact with a probation officer and accessing substance abuse services (r = .243, p < .01; n = 124) but no association between face-to-face contact and accessing mental health- or education-related services. There were no significant associations between service access (in any domain) and phone contacts with a probation officer.

Table 7.

Access to Services Based on Whether a Placement Change Occurred During the Tracking Period.

Service domain	Placement Change	No Placement Change	F	p	n
Service domain	M (SD)	M (SD)	F	p	n

Mental health services access	1.02 (1.17)	1.56 (1.37)	5.42	.02	123
Substance abuse services access	0.66 (0.85)	0.35 (0.64)	5.32	.02	123
Education services access	0.91 (1.61)	1.66 (1.49)	7.29	.008	123

Discussion

Given the unique nature of the Los Angeles 241.1 MDT process, the data collected through this partnership offer a significant opportunity to address gaps in the literature and offer insight into how systems can improve practice to address the service needs and access challenges of dually involved youth. Results reveal that dually involved youth in Los Angeles County are in need of a high level of service provision including significant mental health, substance abuse, and education services.

Similar to previous research (Herz et al., 2010), females were represented at a higher rate in the dually involved population compared to the juvenile justice population generally. For example, in 2014, females were involved in 28% of the delinquency cases processed by juvenile courts across the country (Hockenberry & Puzzanchera, 2017) compared to 39.6% of the dually involved cases in Los Angeles County. It is not known why females represent a larger proportion of the dually involved population compared to the general delinquency population but scholars and advocates point to justice-involved girls’ trauma histories, including family conflict and sexual abuse histories, as a significant contributor to their system involvement (Kerig & Ford, 2014; Saar, Epstein, Rosenthal, & Vafa, 2015).

African American youth were also strikingly overrepresented in this population. About 43% of the dually involved youth in the sample were African American which is highly disproportionate to the population generally in Los Angeles County as well as in the child welfare and juvenile justice systems singularly. In 2016, African American youth accounted for only 7.4% of the child population in Los Angeles County, about 13% of the child abuse and neglect reports, and 29% of the foster care population (Webster et al., 2018). Thus, African American youth in Los Angeles County are disproportionately dually involved at a rate almost 6 times their general population numbers (7.4% vs. 43%). Disproportionality among African American children and families in juvenile justice and child welfare in the United States has been documented for decades. More recently, scholars have looked toward the child welfare system as a pathway to overrepresentation in juvenile justice for African American youth (Ryan, Chiu, & Williams, 2011). Indeed, studies have shown that there is a child welfare bias when it comes to case processing (Ryan et al., 2011) and placement decisions (Ryan et al., 2007) in juvenile justice; since African American youth are more likely to be in child welfare, this bias also contributes to disparities in juvenile justice. Our findings highlight this trajectory as well.

Youth histories reveal significant involvement in both systems. One third of youth had prior arrests with an average of 1.7 prior criminal charges and three status offenses. Youth also had spent over 5 years in the child welfare system and averaged about 10 referrals to the system. Youth also had significant mental health and substance abuse needs. The majority, approximately 75%, of youth had a diagnosed mental health problem and about half were receiving mental health services at the time of arrest. One quarter of youth were prescribed psychotropic medication; though only half of them were taking their medication.

Given the psychosocial characteristics of the youth, it is not surprising that they also received high levels of service referrals. The most common referrals were for individual therapy (74%), tutoring (43%), and group therapy (35%). However, the largest discrepancies between referrals and access of services were for individual therapy (74% referred, 55% accessed), medication monitoring (33% referred, 15% accessed), and, the largest discrepancy, for tutoring (43% referred, 17% accessed). Conversely, the most commonly accessed services were individual therapy (55%), ensuring the youth was enrolled in school (24%), and group therapy (24%).

In considering factors that impede or facilitate service access, we found that placement changes impeded access to mental health and education services but facilitated access to substance use services. It is likely that placement changes disturb mental health and education services because they lead to disruptions in school enrollment and movements between community-based mental health providers. Conversely, in Los Angeles, some substance abuse services, especially alcohol/drug education which was a common service in this domain, are provided at the group homes. Thus, the placement changes may have had less impact on this type of service. Nevertheless, research consistently shows that placement changes are harmful for youth’s behavioral health outcomes (Rubin, Reilly, Luan, & Localio, 2007; Ryan & Testa, 2005), even prospectively linking placement instability to criminality later in adulthood (DeGue & Widom, 2009). Our study adds to these findings by highlighting how placement instability can also impede access to mental health- and education-related services.

Face-to-face contact with a youth’s probation officer increased access to substance abuse services but had no association with mental health or educational service access. It is possible that this was the case because substance abuse services are often a condition of probation and that may be what the officer is more focused on when interacting with a client. Additionally, it is possible that the officers are having face-to-face contact with the youth because the officer is drug testing the youth. Indeed, drug testing, in the current study, fell under the “Other” category of substance abuse services. More generally, this finding could underscore the importance of relationships and accountability. Youth, for example, may be more invested in accessing services if (1) they believe their actions are truly being monitored and (2) they believe someone is invested in seeing them do better. This latter principle is central to the idea of multidisciplinary teams and coordinated case management. Relatedly, we were unable to assess the amount of contact youth may have had with their social worker from DCFS. These findings highlight the need for coordinated case planning and management between both agencies to ensure a holistic and multidisciplinary approach to better service youth involved in multiple systems. A coordinated approach, ideally with an integrated case plan, should also include both agencies involved in tracking youth progress.

When evaluating rearrest, number of prior arrests, placement changes, a substance abuse issue, and receiving mental health services were all significant predictors of rearrest prior to disposition. It seems counterintuitive that mental health service receipt would be a predictor of rearrest; however, this finding is consistent with previous research (Goodkind et al., 2013; Jonson- Reid, 2002) where scholars have used mental health service receipt as a proxy or indicator of a mental health problem rather than a potential protective factor. It is likely that, in the current study, mental health service receipt prior to arrest is also a proxy variable, though not for a mental health problem since we also included a mental health diagnosis in the regression model which did not predict rearrest. The service receipt variable may, in the current study, be an indicator of their dependency system involvement; since they have an open child welfare case, they were likely already referred to mental health treatment as part of their prior system involvement. However, it may simply (and more importantly) be the case that the services youth are receiving are not having the desired effect or are not appropriately matched to the type and level of service need. This would align with our previous work, using the same sample in this study, that revealed that service access was not a protective factor for recidivism (Hirsch et al., 2018). It is imperative that the child welfare and juvenile justice systems ensure they are appropriately assessing youth for service needs and then referring youth to quality, evidence-based services matched to the specific needs of each youth. As highlighted in the current study, youth were referred to several services which may indicate a tendency to overrefer youth rather than focus on the primary issue that brought them to the attention of the system(s). There is an unfortunate lack of research on the type and quality of services system-involved youth actually receive. Future research must shed light on this issue and, ideally, include the lessons learned from the field of implementation science (Aarons & Palinkas, 2007; Mihalic, 2004; Mihalic & Irwin, 2003).

The strongest and most notable predictor of rearrest was substance abuse; for youth with a substance abuse issue, they were 3.5 times more likely to be rearrested prior to disposition compared to those without a substance abuse issue, when controlling for demographics, and juvenile justice and child welfare characteristics. Dually involved youth are more likely to experience substance abuse problems compared to their single-system peers, and this factor has a significant and strong influence on their rate of rearrest and ultimately penetration into the system. It is probable that the high rates of substance use among dually involved youth are associated with their trauma histories. Juvenile justice–involved youth have high rates of polyvictimization (Ford, Grasso, Hawke, & Chapman, 2013), and polyvictimized youth have 3–5 times the rate of diagnosable substance use disorders compared youth not exposed to trauma (Ford, Elhai, Connor, & Frueh, 2010). Although this hasn’t been formally evaluated yet, we would expect the prevalence of polyvictims among dually involved youth to be even higher than justice-only youth, given their child welfare history. For example, youth in our sample had spent over 5 years in the dependency system and had over 10 child welfare referrals, on average. These findings reveal the necessity to identify dually involved youth and address their substance use and abuse issues from a trauma-informed perspective. It also highlights the need to ensure a continuum of quality substance abuse treatment services are available to meet the various needs of youth. It is clear from the referral characteristics that dually involved youth enter the juvenile justice system with high levels of substance use/abuse. Without prompt and appropriate intervention, the instability caused by this use arguably leads to future involvement in delinquency both in the short term and long term.

Finally, the lack of race and gender effects is an important finding and is consistent with previous research on dually involved youth (Herz et al., 2010). It seems that the race and gender effects that are most often found among child welfare and juvenile justice populations, essentially, disappear among the dually involved population. By the time, youth penetrate the deeper ends of both systems their risk factors and behavioral health challenges are strikingly similar. What we know less about, however, are their trajectories of system involvement. For instance, emerging research points to dually involved girls as being at a higher risk for sexual exploitation and that girls experience a sexual abuse to prison pipeline (Saar et al., 2015). Questions remain, as well, regarding how often youth touch these systems before (and after) they become dually involved and the reasons for their system contact. Future research should examine the varying trajectories to dual involvement and, potentially, whether the overall dual system population exhibits more heterogeneity than we are aware of so far.

Limitations

The current findings must be considered in light of the methodological strengths and weaknesses of the study. The data collected through the MDT process were not intended for use in traditional research or evaluation. Rather they were meant to inform case management and service recommendations among youth who qualified for the 241.1 protocol and data were inputted by nonresearchers. This means that there were several areas of missing data, given that there was no additional support for the, somewhat burdensome, data entry process; data entry was done in addition to caseworkers and probation officers’ regular duties. Since the data were not intended for research purposes, there were no standardized measures used; only information related to case management and the youth’s behavioral health needs. This also meant that only a small group of youth could be tracked which makes our hypothesis testing less sensitive, increasing the chance of Type II errors. In addition, while the longitudinal nature of the tracked sample was a strength, the time between time points was short (i.e., 6 months). If agencies intend to truly change practice for dual system youth, resources must be directed to data collection and entry so that complete and more comprehensive longitudinal data can be obtained and used in decision-making as well as for research or evaluation.

The study is also geographically limited which constricts our ability to generalize to the broader dually involved population. Unfortunately, the majority of dual system youth research is plagued by this issue. Future research among nationally representative samples are needed. Nevertheless, Los Angeles County is the nation’s largest juvenile justice system and, thus, provides a robust example of dually involved youth’s needs and characteristics. The data limitations in cross-systems work (e.g., data sharing constraints) and the fact that many jurisdictions do not even identify whether their youth are dually involved highlight the importance of the current study despite these limitations.

In addition, there were some key differences between the tracked and full dually involved samples which indicated that the full sample exhibited a significantly higher rate of certain risk factors (i.e., greater likelihood to be detained at arrest, have a substance use history, and have more child welfare placement changes). These differences should be considered in context, given the broad range and high severity of risk factors overall.

Practice and Policy Implications

The results of this study help to inform the growing research on dually involved youth, particularly as it relates to their service needs and service utilization once involved with both the child welfare and juvenile justice systems. In particular, it provides unique insight into what factors are related to continued instability following the arrest that brought them into the delinquency court and factors related to service utilization. Understanding these needs and experiences of dually involved youth is critical to building and improving integrated systems work to improve outcomes for youth and families caught between and within systems; yet, this level of information is rarely available for analysis because agencies do not collect such detailed information on clients in a consistent and standardized way. In many ways, the implementation of the 241.1 MDT in Los Angeles County and the data it has produced over the years illustrate the significance and potential of action research.

The Los Angeles County 241.1 MDT in Los Angeles County represents a culmination of cross-systems work since the 1990s to address the needs of dually involved youth through a practice and policy approach. This work initially began under the direction of the Los Angeles County Juvenile Court Presiding Court Judge, Michael Nash, and an interagency workgroup. This group developed a protocol outlining the roles and responsibilities of the child welfare and probation systems, once a child welfare-involved youth was referred to juvenile delinquency court per Welfare and Institutions Code 241.1 (CA WIC 241.1). The protocol addressed concerns over how youth caught between systems were handled (i.e., more youth retained their child welfare case status instead of moving into the delinquency system), but there was little to no attention placed on assessing the needs of these youth and connecting them to appropriate services. Consequently, many youth were rereferred for additional offenses within a fairly short time frame. In 2005, the interagency workgroup partnered with researchers to produce data related to dually involved youth and used the data to drive the creation of an MDT to (1) conduct a comprehensive review of the histories of youth referred for a 241.1 hearing, (2) identify their treatment/service needs, and (3) develop a plan to implement following the court’s disposition decision. The county participated in the Center for Juvenile Justice Reform’s (CJJR) Crossover Youth Practice Model during this time and enhanced its data collection; consequently, the Los Angeles County MDT approach was often used by CJJR as an example of a promising practice for dually involved youth.

The use of data for the 241.1 MDT approach in Los Angeles County also resulted in additional funding from the Los Angeles County Board of Supervisors to fund the use of psychiatric social workers as part of the team across the county in 2012. Despite its progress, though, the data collected from the 241.1 MDT also showed shortcomings in the area of coordinated case management and access to services as shown in the current study. Most recently, the Board of Supervisors passed a Crossover Youth Motion to create a workgroup tasked with making detailed recommendations on how to improve access to services, coordinated case management, and ongoing data collection for dually involved youth. The results of this study and other related studies will, once again, be used by key stakeholders to inform the policy recommendations made back to the Board of Supervisors on how to improve practice for this population.

Los Angeles County is only one example in which data collected locally can impact system reform in significant ways. Since 2010, the Center for Juvenile Justice Reform has worked with over 100 jurisdictions to implement promising practices and/or best practices across child welfare and juvenile justice systems. This work has produced a number of positive outcomes and resulted in the development of a variety of integrated system approaches across the nation. To date, however, there is no national review of integrated system practices and no identification of evidence-based practices or programs for dually involved or dual system youth (youth who have either concurrent or nonconcurrent contact with both the child welfare and juvenile justice systems).

The work represented in the current study is a starting point for more fully understanding the needs of dual system youth. To this end, the Office of Juvenile Justice and Delinquency Prevention (OJJDP) funded a dual systems youth design study in 2015 in an effort to identify methodologies to estimate a nationally representative incidence rate of dual systems youth and to document characteristics of effective integrated system approaches. The main barrier or challenge in answering the questions put forth by OJJDP and local efforts is the lack of data integration between systems. The effort by OJJDP and the objective of this research are to illuminate our understanding of this population and what practices are effectively meeting youth’s needs in order to prevent youth from crossing over or penetrating deeper into service systems in adulthood (e.g., New York City Office of the Mayor, Center for Innovation Through Data Intelligence, 2015). Ultimately, this type of work is imperative to guide integrated system approaches to improve outcomes for dual system youth as adolescents and into young adulthood.

Footnotes

Authors’ Note

The opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect those of the Department of Justice.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported in part by Grant #OJJD-2015-4126 awarded by the Office of Juvenile Justice and Delinquency Prevention, Office of Justice Programs, U.S. Department of Justice to the first two authors.

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