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Article

Treatment Services in the Juvenile Justice System: Examining the Use and Funding of Services by Youth on Probation

Clair White 1

Abstract Youth enter the juvenile justice system with a variety of service needs, particularly for mental health problems. Research has examined the extent to which youth have mental health disorders, primarily among detained youth, and factors associated with treatment referrals, but little research has examined youth on probation and the actual use of services. Using data obtained from the Maricopa County Juvenile Probation Department from July 2012 through August 2014 (N ¼ 3,779), the current study examines (1) the factors associated with receiving treatment services while on probation and (2) the factors associated with receiving treatment services through different funding streams. Findings reveal that only about 25% of the sample of youth on probation received treatment services, suggesting the underservicing of youth. Consistent with prior research, there were also racial and ethnic disparities concerning treatment use, with Blacks and Latinos less likely to receive services. Additionally, certain characteristics of youth and their background influenced the funding source for treatment services. Implications for policy and research are discussed in light of these findings.

Keywords probation, treatment services, service use, juvenile justice, racial/ethnic disparities

The juvenile justice system has multiple responsibilities often serving conflicting goals of punitive

sanctions and rehabilitative treatment (Bishop, 2006; Lipsey, Howell, Kelly, Chapman, & Carver,

2010). The system must not only address the current delinquent behavior but also, in many cases,

consider the health and well-being of the youth. Youth come into the juvenile justice system with

more complex problems and greater needs for mental and behavioral health services, which has

resulted in more attention on efforts to rehabilitate and address youth’s mental and behavioral

1 Center for Evidence-Based Crime Policy, Criminology, Law and Society, George Mason University, Fairfax, VA, USA

Corresponding Author:

Clair White, Center for Evidence-Based Crime Policy, Criminology, Law and Society, George Mason University, 4400

University Dr., MS 6D12, Fairfax, VA 22030, USA.

Email: [email protected]

Youth Violence and Juvenile Justice 2019, Vol. 17(1) 62-87 ª The Author(s) 2017 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/1541204017728997 journals.sagepub.com/home/yvj

service needs (Myers & Farrell, 2008). Research has examined a number of issues related to mental

health and behavioral health problems of youth in the juvenile justice system, particularly identify-

ing the rates of mental health problems and service needs among youth and factors associated with

treatment referrals of youth in different systems of care (i.e., juvenile justice system and mental

health system).

Research on mental health problems in justice-involved youth has primarily focused on the

service needs of youth and where they have been referred to meet these needs and not on whether

they actually received those services. Additionally, much of the work examines youth in detention or

compares youth sentenced to community versus correctional supervision rather than youth on

probation which is the predominate sentence in the juvenile justice system. The current study uses

juvenile probation data from a large, urban jurisdiction in Arizona to examine these issues. More

specifically, legal and extralegal factors associated with the use of treatment services among youth

on probation supervision are examined. Furthermore, the extent to which services are funded by the

juvenile justice system has not been empirically examined, therefore, whether these services are

funded by the juvenile justice system or external funding sources such as Medicaid or private

insurance is also examined.

Unmet Service Needs and Treatment Referrals

Youth involved in the juvenile justice system often experience multiple adversities or risk factors,

such as economic disadvantage, experiences of abuse and neglect, unstable family environments,

exposure to drugs and alcohol, and mental illness (Esbensen, Peterson, & Taylor, 2010; Huizinga,

Loeber, Thornberry, & Cothern, 2000; Loeber & Farrington, 1998). Research has generally found

that 65–70% of youth in juvenile justice facilities, primarily detention centers and correctional facilities, suffer from at least one mental health disorder (Shufelt & Cocozza, 2006; Teplin, Abram,

McClelland, Dulcan, & Mericle, 2002; Wasserman, McReynolds, Lucas, Fisher, & Santos, 2002),

while rates among youth on probation are approximately 50% (Wasserman, McReynolds, Ko, Katz, & Carpenter, 2005).

Additionally, comorbidity, or the presence of more than one mental or behavioral disorder, is

particularly high among youth in juvenile justice settings (Abram, Teplin, McClelland, & Dulcan,

2003; Kessler et al., 1996; Teplin et al., 2002). Shufelt and Cocozza (2006) found that roughly 79% of those who met criteria for at least one mental health disorder had two or more diagnoses.

Unfortunately, many of these mental and behavioral service needs are not met in the community

(Flisher et al., 1997; Jensen et al., 2011; Kataoka, Zhang, & Wells, 2002; Ringel & Sturm, 2001). As

a result, the coexistence of multiple disorders in addition to other criminogenic risk factors makes

prioritizing mental and behavioral service needs more challenging for the juvenile justice system

(Grisso, 2004).

Research has examined factors related to unmet service needs and the avenues through which

youths’ mental health needs are met through various service sectors, such as the mental health

system and juvenile justice system (Burns et al., 2004; Stahmer et al., 2005; Thompson, 2005).

Among the general population, children and adolescents with mental and behavioral health problems

are gravely undertreated with high rates of unmet service needs (Angold et al., 1998; Flisher et al.,

1997; Horwitz, Gary, Briggs-Gowan, & Carter, 2003). Studies have examined characteristics of

children with unmet mental health needs and their families using various samples to identify key

predictors of treatment service use and unmet service needs.

Among the primary factors associated with unmet service needs are elements related to economic

disadvantage such as living on public assistance, lack of health insurance, and transportation prob-

lems (Chow, Jaffee, & Snowden, 2003; Cornelius, Pringle, Jernigan, Kirisci, & Clark, 2001; Haines,

McMunn, Nazroo, & Kelly, 2002). Race and ethnicity are also strong predictors of unmet service

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needs with Whites being more likely to receive mental health services compared to minorities

(Angold et al., 2002; Garland et al., 2005; Kataoka et al., 2002; Thompson, 2005; Yeh, McCabe,

Hough, Dupuis, & Hazen, 2003). Studies have also found that minorities have limited opportunities

to access mental health services (Arcia, Keyes, Gallagher, & Herrick, 1993), and once they start

treatment they are less likely to complete treatment (Kazdin, Stolar, & Marciano, 1995).

Research has also found involvement in the mental health system increases the likelihood of

being referred to the juvenile justice system (Cohen et al., 1990; Evens & Stoep, 1997; Rosenblatt,

Rosenblatt, & Biggs, 2000). In addition, younger adolescents, females, and White youths are more

likely to be referred to the mental health system, while minorities, males, and youths with more

serious and disruptive mental health disorders are more likely to be referred to the juvenile justice

system (Atkins et al., 1999; Cohen et al., 1990; Dembo, Turner, Borden, & Schmeidler, 1994; Evens

& Stoep, 1997). In general, service needs of disadvantaged and minority youth are often not

recognized until their contact with the juvenile justice system (Golzari, Hunt, & Anoshiravani,

2006; Rawal, Romansky, Jenuwine, & Lyons, 2004; Rogers, Pumariega, Atkins, & Cuffe, 2006).

Upon entering the juvenile justice system, service needs often continue to go unmet even after

identification of need for treatment (Rogers, Zima, Powell, & Pumariega, 2001; Shelton, 2005).

Shelton (2005) found that only 23% of youth diagnosed with mental health disorders received treatment and that having a mental disorder was not a significant predictor of receiving services.

A recent study conducted by Hoeve, McReynolds, and Wasserman (2014) found that youth with

externalizing disorders and substance use disorders were more likely to receive referrals, while only

40% of youth with internalizing disorders referred to service. Consistent with the findings from the general public, Whites are more likely to be referred to services compared to Black youth in the

justice system (Dalton, Evans, Cruise, Feinstein, & Kendrick, 2009; Lopez-Williams, Stoep, Kuro,

& Stewart, 2006; Maschi, Hatcher, Schwalbe, & Rosato, 2008; Rogers et al., 2006), but there are

some mixed findings (Breda, 2003; Hoeve et al., 2014). Shelton (2005) concluded that

while the total responsibility for the well-being of children does not lie solely with the juvenile justice

system, the decision not to provide treatment services to youth in need and under their care implies

neglect . . . it implies a perception that these youth will go away, be treated elsewhere, or grow out of their

problems. (p. 110)

These prior studies do not provide a clear set of predictors for service referrals and many studies

were not able to control for offense severity and criminal history (Dalton et al., 2009; Lopez-

Williams et al., 2006; Rawal et al., 2004), which are likely to influence referrals for services.

Regardless, there were discrepancies in service referrals in the juvenile justice system. Receipt of

service referrals was not found to be dependent entirely on the need for services but may be

influenced by other factors that create disparities in the health of youth. Furthermore, these studies

did not take into account access (i.e., availability, health insurance, etc.) to referred services or

whether youth were actually using the services.

Many of the studies previously discussed use referrals for treatment services as the outcome of

interest, but little research has examined the actual receipt or use of treatment services by youth

(Teplin, Abram, McClelland, Washburn, & Pikus, 2005). Teplin, Abram, McClelland, Washburn,

and Pikus (2005) found that roughly 16% of youth who had been identified as needing mental health services during detention received services within 6 months from detention or by disposition.

Additionally, 11% of youths received services but did not meet the definition of need. Johnson et al. (2004) examined substance abuse treatment need and use among youth entering juvenile

corrections and found that nearly half of youth with need for substance abuse treatment received

services. Rawal, Romansky, Jenuwine, and Lyons (2004) examined racial differences in mental

health needs and service use among incarcerated youth. The authors found that Blacks had the

64 Youth Violence and Juvenile Justice 17(1)

greatest level of mental health needs, but the lowest level of prior and current service use. In general,

these studies emphasize how few individuals actually receive services for their mental and beha-

vioral service needs as well as the “benign neglect” of the juvenile justice system in addressing

mental and behavioral service needs (Herz, 2001).

Lastly, receiving referrals for treatment or participating in certain programs and treatment does

not necessarily translate into needs being met (Grisso, 2004). The justice system has the difficult task

of distinguishing youths’ need for specific programs that target criminogenic risk factors from the

need for treatment services that address their overall mental well-being. Given limited training and

resources, some needs are often prioritized over others, leaving other needs unaddressed (Haqanee,

Peterson-Badali, & Skilling, 2015). Responsivity is a key component of the risk-needs-responsivity

(RNR) model in offender treatment, emphasizing matching program and treatment plans to meet the

unique reoffending risks and risk factors (i.e., criminogenic needs) of offenders through evidence-

based rehabilitative programs that are tailored to an individual’s strengths and capacities (Andrews

& Bonta, 2010; Andrews, Bonta, & Hoge, 1990; Hoge & Andrews, 1996). Rather than general

mental health (GMH) care, the RNR model is focused on reducing future delinquency and recidi-

vism but has been criticized for not addressing more basic, noncriminogenic, human needs, such as

mental health (T. Ward & Stewart, 2003; T. Ward, Yates, & Willis, 2012). Additionally, treating

mental health and substance abuse disorders may or may not address other criminogenic risk factors

and prevent future delinquency (see Wibbelink, Hoeve, Stams, & Oort, 2017) but may have impli-

cations for youths’ responsiveness to treatment goals and success in addressing criminogenic needs

(Haqanee et al., 2015). Nevertheless, programs that adhere to the principles of RNR have been

successful in reducing recidivism (Andrews & Bonta, 2010).

One of the primary RNR assessment tools, the Youth Level of Service/Case Management Inven-

tory (YLS/CMI), has been validated for its ability to predict recidivism among youth (Catchpole &

Gretton, 2003; Jung & Rawana, 1999; Onifade et al., 2008; Vieira, Skilling, & Peterson-Badali,

2009). However, agencies and practitioners face many challenges to develop clear treatment plans

and effectively implement services despite identifying risks and needs through assessment (Flores,

Travis, & Latessa, 2004; Latessa, Cullen, & Gendreau, 2002; Sutherland, 2009), resulting in many

youths’ needs left unaddressed (Vieira et al., 2009). This “implementation gap” is often the result in

the availability of quality, evidence-based programming, such as cognitive behavioral therapy

(Haqanee et al., 2015). For example, Flores, Travis, and Latessa (2004) found in one state jurisdic-

tion that the RNR tool (YLS/CMI) was widely used, but when it came to services in the treatment

plans, they rarely targeted the needs identified in the assessment. In sum, there have been great

strides in recognizing and measuring criminogenic risks and needs that when addressed can improve

outcomes for youth. Mental illness, however, is often not considered one of those criminogenic

needs (Haqanee et al., 2015), so practitioners may continue to use their clinical judgment and

experience over the use of risk assessment tools (C. Schwalbe, 2004), and services received may

not target the needs/risks identified.

Funding Treatment Services

While the juvenile justice system has a legal mandate to provide treatment services, it does not have

to be the one to administer that care (Grisso, 2004). When a youth is required to receive court-

ordered treatment services as a condition of probation supervision, there are multiple avenues or

sources of funding that can pay for these services. If the youth has no means (i.e., health insurance)

to pay for treatment services ordered by the court, the juvenile justice system has a financial

responsibility to fund the treatment services it is requiring.

The juvenile justice system has used outside agencies and external funds to reduce the burden of

providing treatment services—they typically contract out to private providers or other government

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agencies such as public mental health service providers. Similarly, the treatment services can be

funded through different sources such as private insurance or public health care, but if those avenues

are not available, the juvenile justice system is responsible to fund the treatment services. Families

of youth in the juvenile justice system often have limited knowledge and resources to navigate the

health-care system; therefore, youth often are more likely to be uninsured and their mental and

behavioral conditions are not addressed. Furthermore, services provided through Medicaid are often

restricted to children with the most severe mental disorders due to lack of funding (Kerker & Dore,

2006). As a result, children with less serious problems are often ineligible for services and those who

do qualify receive inconsistent and fragmented care. Finally, studies have found that lack of health

insurance is a major impediment to obtaining mental and behavioral health services (Farmer, Stangl,

Burns, Costello, & Angold, 1999; Flisher et al., 1997; Kataoka et al., 2002).

In light of the health-care debate, the current research also speaks to the issue of funding and

resources for mental health care and substance use disorder services that are often subject to social,

political, and economic influence. The coverage for mental health and substance use disorders by

insurance companies and the availability and eligibility of Medicaid will likely have implications for

practices in the juvenile justice system and the extent to which treatment services are court-funded.

If youth have alternative sources to pay for treatment services, such as private insurance or Med-

icaid, the juvenile justice system will be relieved of that responsibility. While the current research

does not empirically evaluate health-care reform on funding treatment services in the juvenile justice

system, findings should be considered in the context of these broader changes.

The funding of treatment services in the juvenile justice system has not been examined as a key

variable of interest. While the source of funding for treatment services is often determined by the

youth’s health care coverage, the court also considers the need for services, prioritizing those with

greatest need. However, as was demonstrated with literature on unmet service needs, need does

not necessarily result in the expected outcomes (i.e., services). Following this line of thought,

there may be other factors that could influence the court’s decision to fund treatment services.

Furthermore, the quality of services and degree of investment the court has when it is funding the

treatment services may differ, which may have implications for the future delinquent behavior and

overall health of the youth.

Current Focus

Building on previous research on service needs and use among youth with mental and behavioral

problems, this research examined treatment services received by youth involved in the Maricopa

County Juvenile Probation Department (MCJPD). The court serves youth by requiring treatment

services for mental and behavioral problems but providing resources to pay for treatment services

adds an additional level of intervention and investment in these youth’s lives. The current research

examined characteristics of youth who received treatment services as well as funding sources for

services. More specifically, two research questions are examined:

Research Question 1: What are the predictors (e.g., gender, race, delinquent background,

etc.) associated with receiving treatment services under probation supervision?

Research Question 2: Among youth receiving treatment services, what are the predictors

associated with the source of funding for treatment services; specifically, what are the pre-

dictors of receiving treatment services via external funding sources relative to court-based

funding?

Research on mental and behavioral service needs and service referrals has generally focused on

treatment for mental health and substance use disorders, but youth can have other service needs. The

66 Youth Violence and Juvenile Justice 17(1)

current research is not restricted to mental health and substance use treatment services and is

more inclusive of other treatment services provided by the juvenile justice system, such as

behavior-specific education, mentoring programs, and evidence-based programs. Based on previous

research, we expect race/ethnicity to be a strong predictor of service use as well as prior history of

mental health problems and involvement in the juvenile justice system.

This research will also shed light on which types of services are typically funded by the court. The

ever-changing financial climate and the health-care debate provide a broader context that can help

inform the importance of understanding the sources of funding for treatment services. There is

growing concern for addressing service needs, particularly for mental health and substance use

disorders, but with limited resources, the funding sources of treatment services deserves empirical

attention. Given the limited attention on the issue of funding, this question is more exploratory in

nature. The implications of this research will help to inform broader issues of the juvenile justice

system’s obligation to provide treatment.

Method

Data and Sample

The MCJPD and the Treatment Services Division were sources for data regarding youth receiving

treatment services. The time frame for the data spanned a 25-month period beginning July 1, 2012, to

August 31, 2014, during which a total of 4,244 youth were placed on probation, 60 of whom had

multiple probations during the time frame. 1

The data were compiled onsite with the assistance from

the Research and Planning Division of the MCJPD. A data sharing agreement was obtained with

institutional review board approval to receive deidentified youth information through electronic

databases. With the exception of certain files, such as psychological case notes, 2

MCJPD uses the

integrated court information system to manage youths’ records, and Microsoft ®

Access was used to

query databases associated with youth who were placed under probation supervision during the

specified time frame. 3

For purposes of this analysis, the unit of analysis was the individual youth. Eight different databases

were used to measure the legal and extralegal characteristics of the youth and their case. The databases

were cleaned as separate files and merged based on each youth’s unique identifier. The data required

recoding variables and MCJPD advised to ensure the recoded variables accurately measured the

correct information. For example, the complaint data set contained all referrals (or complaints) the

youth has received in Maricopa County. The unit of analysis in this data set was referrals, and there

were 17,784 referrals for the 4,244 youth analyzed in the current research. This data set, in particular,

took an extensive amount of cleaning and management because it was used to (1) identify which

referral was associated with the disposition that placed the youth on probation and the severity of that

offense, and (2) determine the number of referrals and adjudications that occurred before the current

probation to measure prior offending behavior.

The final sample of youths on probation was 3,779 after those with short probation periods (less

than 10 days) and cases with missing data were removed. 4

Descriptive statistics of the sample of

youth are presented in Table 1. Similar to other research on juvenile justice populations, a majority

of the sample was male (81.2%), roughly 37% of the sample were White, 15% Black, and 41% Hispanic, and the mean age was 16.1 years old. A majority of the youth came from single parent

living situations (60.8%) and a quarter were not enrolled in school. In regard to the youths’ offense and juvenile justice history, property felonies were the most common (25.1%), followed by personal felonies (19.1%), 40.5% were detained prior to adjudication, 67.1% had a prior referral, and 12.9% had a prior adjudication. Additionally, 37.5% of youth received a psychological evaluation

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associated with the current offense, 18.3% had prior treatment services, and in regard to risk level, 20.4% were low, 24.6% were moderate, and 55% were high risk.

The current research focused on youth who received treatment services in the community and

residential facilities while on probation, thus services received while on diversion will not be

examined, but will be captured as prior services. In 2012, MCJPD began the Service Authorization

Table 1. Descriptive Statistics of Dependent and Independent Variables.

Variables

Youth on Probation (N ¼ 3,779)

% n

Outcome variables Receiving treatment services 25.0 944 Funding source (n ¼ 861)

Court-based 72.2 622 External 27.8 239

Independent variables Gender

Female (reference) 18.8 712 Male 81.2 3,067

Race/ethnicity White (reference) 37.4 1,414 Black 15.3 580 Latino 41.4 1,564 Native American 4.3 161 Other 1.6 60

Age (mean) 16.1 (1.3) 3,779 Living situation

Single parent (reference) 60.8 2,299 Two parents 19.6 741 Grandparents or other relatives 8.3 313 DCS and other 11.3 198

School status Enrolled (reference) 75.1 2,839 Not enrolled 24.9 940

Offense severity Property felony (reference) 25.1 948 Personal felony 19.1 720 Property misdemeanor 12.6 477 Personal misdemeanor 8.0 304 Drugs 18.8 710 Public peace 14.8 559 Other 1.6 61

Preadjudication detention 40.5 1,530 Prior referral 67.1 2,537 Prior adjudication 12.9 486 Psychological evaluation 37.5 1,416 Prior treatment services 18.3 692 Risk level

Low (reference) 20.4 770 Moderate 24.6 929 High 55.0 2,080

Note. DCS ¼ Department of Child Services.

68 Youth Violence and Juvenile Justice 17(1)

Form Automation Project to electronically track the treatment services ordered by the court and

progress of youth receiving services as part of their probation. Based on the recommendation by

Research and Planning Division, services that started 90 days prior to the start of probation will also

be considered prior services. Treatment services evaluated in the current study include GMH

services, sex offender services, substance abuse services, mentoring or life skills programs,

behavior-specific education, evidence-based programs, and drug court services. 5

Treatment services

that are not included in the current research include mandatory drug testing, detention alternative

programs, physical health services such as acute care or hospitalization, polygraph examinations,

and assessments. These services were not included because they are not therapeutic in nature and

generally not used to address mental and behavioral service needs. Among the 3,779 youth on

probation included in the analysis, 944 (25%) received the services of interest.

Measures

There are a number of legal and extralegal factors that have been examined in relation to various

outcomes in the juvenile justice system and whether youth end up in mental health system versus

juvenile justice system (Cohen et al., 1990; Evens & Stoep, 1997; Lyons, Baerger, Quigley, Erlich,

& Griffin, 2001; Thomas & Stubbe, 1996). The current study focused on the referral that placed the

youth on the current probation and treatment services, but characteristics of prior behavior are

captured. The independent variables that were used in the analyses include gender, race, ethnicity,

age, living situation, school status, offense severity, preadjudication detention, prior referrals, prior

adjudications, whether the youth received a psychological evaluation, prior treatment service use,

and risk assessment level.

Gender was coded as 1 for males and 0 for females, and race and ethnicity are measured by

several dummy variables: Blacks, Latino/Latina, and other race/ethnicity, with White as the refer-

ence category. Age is measured as the age of the youth at the time of the referral that received a

disposition of treatment services and is measured continuously. The living situation of the youth

captured who the youth lived with when they were placed on probation. The categories included

single parent, two parents, grandparents or other relative, and Department of Child Safety or other,

with single parent serving as the reference category. School status was measured on the basis of

whether or not the youth was enrolled in school during the time of the current referral. Offense

severity captured the most severe offense associated with the referral. Consistent with sentencing

research on juveniles, if the youth was charged with multiple offenses, the most serious offense was

measured. There are seven categories of offense severity—property felony, personal felony, prop-

erty misdemeanor, personal misdemeanor, drugs, public peace, and other offenses that included

obstructions of justice and status offenses. Property felony serves as the reference category because

it had the highest frequency. Preadjudication detention captured whether the youth was detained

prior to adjudication for the current offense and probation. Prior referrals and prior adjudications

are measured dichotomously, with “yes/no” outcomes. Prior service use was also a binary variable,

measuring whether the youth has received treatment services through the court from either diversion

or prior probations.

Every youth who reaches adjudication and disposition is considered for a psychological evalua-

tion, but these are predominately conducted only when there is a history of mental illness and service

need, and the court would benefit from clinical assistance. Therefore, having a psychological

assessment is a strong proxy for history of mental health problems in the current study. In addition

to the psychological evaluation, every youth completes the Arizona risk/needs assessment (ARNA)

and receives a risk level—low, moderate, or high. ARNA is an empirically validated instrument

predominately used to predict risk of future offending, but it also helps in identifying needs of youth

(see Krysik & LeCroy, 2002; C. S. Schwalbe, 2009). Following the youth’s initial intake assessment

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that includes an interview with the youth and a review of records, the risk assessment items are

completed by two probation officers. The risk scale consists of a number of dimensions such as

alcohol and drug use, family relationship, assaultive behavior, extensive absenteeism or truancy at

school, peer delinquency, and emotional/behavioral problems.

The type of treatment service was also included as an independent variable for examining the

second dependent variable (source of funding) to control for services that are typically provided and

therefore funded by the court. As previously mentioned, the services youth could receive were:

GMH—residential and outpatient, sex offender—residential and outpatient, and substance abuse—

residential or outpatient, as well as mentoring and life skills, behavior-specific education, evidence-

based programs, and drug court services (see Appendix A). The most common type of treatment

service used was GMH outpatient services (29.9%) followed by residential GMH services (19.9%). Mentoring services, behavior-specific education, evidence-based programs, and drug court services

were combined into one category because of their low frequency and they were predominately

funded and administered through MCJPD. Additionally, 247 youth received multiple services, so

these were divided into youth who received two services and youth who received three or more

services. The reference category for type of service was youth who exclusively received GMH

outpatient services.

Dependent Variables

There are two primary dependent variables that were examined in the current analysis: (1) whether

the youth received treatment services and (2) the type of funding source for treatment services. First,

to examine predictors of receiving treatment services, the dependent variable was a dichotomous

outcome of whether the youth received court-ordered treatment services (coded as 1) or not (coded

as 0). Much of the prior research examines referrals for treatment services, which can often act as a

proxy for receiving services, but since this study can identify referrals that result in the use of

treatment service, referrals for that were denied were coded as zero.

Second, to examine the next research question pertaining to the funding source for treatment

sources, the source of funding was coded as a dichotomous outcome. Given limited resources,

every youth is screened for behavioral health coverage through the state Medicaid fund, Ari-

zona Health Care Cost Containment System (AHCCCS) or Regional Behavioral Health Author-

ities (RBHA), and/or private insurance (Superior Court of Maricopa County, Juvenile Probation

Department, 2015). If the youth does not receive benefits from the private or public insurance,

the youth’s treatment services are funded by the court through the Juvenile Probation Services

Fund. Only seven youth in the sample received treatment services through private insurance, so

this category was not large enough to analyze separately. Additionally, 16 youth received

treatment services through tribal health coverage, 90 through RBHA, and 86 through AHCCCS.

These funding sources were combined into one category of external funding source (coded as

1), which is compared to court-based funding as the reference category (coded as 0) for the

multivariate analysis. 6

Analytic Strategy

The analysis will proceed in two stages. First, bivariate statistics will be estimated to identify

differences between groups using independent sample t tests and w2 to test for significance. The second stage of the analysis involves multivariate regression models. A logistic regression model

was used to examine whether the youth received treatment services, and a two-stage full information

maximum likelihood (FIML) probit model was estimated to control for selection bias when

70 Youth Violence and Juvenile Justice 17(1)

examining the funding source dependent variable. 7

Significant variables are reported in odds ratio

(OR) for easier interpretation.

Results

Use of Services

Beginning with the first question of interest, examining factors associated with the receipt of

treatment services, the bivariate statistics describing the relationship between the independent vari-

ables and whether the youth received treatment services are presented in Table 2. As indicated by

Table 2, there was not a significant relationship between gender and receiving treatment services,

but there was a significant difference for race/ethnicity, with Latino youth were slightly under-

represented in treatment services compared to the other groups and Native Americans more repre-

sented in treatment services.

While the mean age of the youth also was statistically different across treatment service use, with

youth who received treatment services being slightly younger, the difference has little substantive or

practical meaning. There were also significant differences between youths’ living situation, and

offense severity, preadjudication detention, prior adjudication, psychological evaluation, prior treat-

ment service use, and risk level. Youth who lived with parents, particularly two parents, were least

likely to receive treatment services. Importantly, 46.5% of youth who received a psychological evaluation received treatment services, and 12.1% of youth who did not receive a psychological evaluation received services. This finding suggests a disconnect between need and use; while youth

with a psychological evaluation were more likely to get treatment services, there were many youth

who did not receive services. On the other end, a small number of youth received services without

having a psychological evaluation.

The results from a multivariate logistic regression are presented in Table 3. The significant

demographics included age, being Black or Latino, living with grandparents or relatives, and living

with the state (Department of Child Services [DCS]) or other living arrangements. More specifically,

the effect of age is negative, meaning that as age increases the likelihood of receiving treatment

services decreases. In regard to race and ethnicity, Blacks and Latinos are less likely to receive

treatment services than their White counterparts, 33.4% (OR ¼ .666) and 21.9% (OR ¼ .781), respectively. In terms of the youth’s living situation, youth who live with grandparents or relatives

or DCS were more likely to receive treatment services than youth living with single parents.

Specifically, youth under DCS care were more than 2 times (OR ¼ 2.032) more likely to receive treatment services. There was no significant difference between youth who lived with two parents

versus youth who lived with a single parent on the likelihood of receiving services.

Other significant variables included preadjudication detention, prior adjudication psychological

evaluation, and risk level. Both the effect of being detained and having a prior adjudication reduced

the likelihood of receiving treatment services, 23% (OR ¼ .770) and 39% (OR ¼ .610), respectively. Finally, youth who had a psychological evaluation were more than 5 times more likely (OR ¼ 5.189) to receive treatment services, and high risk youth were 3.6% (OR ¼ 1.036) more likely to receive treatment services. Many of these findings are in expected directions and consistent with prior

research, which will be explored in greater depth in the discussion.

Source of Funding

The second dependent variable examined was the source of funding for the treatment services

youth on probation received, particularly whether certain characteristics of youth influence

whether they receive treatment services through external funding, exclusively, compared to

court-based funding. The bivariate results comparing the three funding sources are presented

White 71

Table 2. Bivariate Statistics—Youth Receiving Treatment Services.

Variables No Treatment Services Treatment Services

% %

Gender Female (reference) 76.1 23.9 Male 74.8 25.2

Race/ethnicity* White (reference) 73.2 26.8 Black 73.6 26.4 Latino 77.4 22.6 Native American 71.4 28.6 Other 80.0 20.0

Age (mean, SD)*** 16.2 (0.02) 15.6 (0.04) Living situation***

Single parent (reference) 78.2 21.8 Two parents 80.0 20.0 Grandparent or other family 69.3 30.7 Other-DCS 53.5 46.5

School enrollmenty

Enrolled in school (reference) 74.3 25.7 Not enrolled in school 77.2 22.8

Offense severity*** Property felony (reference) 78.0 22.0 Personal felony 59.7 40.3 Property misdemeanor 82.2 17.8 Personal misdemeanor 73.7 26.3 Drugs 78.7 21.3 Public peace 78.9 21.1 Other 82.0 18.0

Preadjudication detention*** Not detained (reference) 77.0 23.0 Detained 72.2 27.8

Prior referral No prior referrals (reference) 74.1 25.9 Prior referral 74.5 24.5

Prior adjudication*** No prior adjudications (reference) 73.9 26.1 Prior adjudications 82.5 17.5

Psychological evaluation*** No psychological evaluation (reference) 87.9 12.1 Psychological evaluation 53.5 46.5

Prior treatment service** No prior treatment services (reference) 75.8 24.2 Prior treatment services 71.5 28.5

Risk level*** Low (reference) 78.4 21.6 Moderate 77.3 22.7 High 72.7 27.3

N 2,835 944

Note. N ¼ 3,779. Continuous measures were examined using a t-test and categorical variables were examined using a w2 test. SD ¼ standard deviation; DCS ¼ Department of Child Services. *p � .05. **p � .01.***p � .001. yp � .1.

72 Youth Violence and Juvenile Justice 17(1)

in Table 4. Regarding statistically significant differences across court-based and external funding,

race/ethnicity, living situation, offense severity, preadjudication detention, psychological evalua-

tion, risk level, and the type of treatment service had a statistically significant relationship with the

source of funding for the treatment services. In regard to race and ethnicity, Native Americans in

particular were more likely to get external funding (70%), whereas the other groups were more similar in the use of external funding.

One of the most notable differences between the two sources of funding was the youth’s living

situation. Roughly 75% of youth who lived with grandparents or other family, over 80% of youth who live with two parents, and almost 90% of youth living with one parent received funding through the court, whereas 67% of youth who lived in other living situations such as State were funded externally. Regarding preadjudication detention, youth who were detained were more likely to

receive treatment services through external funding rather than court based. Youth who had a

psychological evaluation were more likely to receive treatment services via external funding,

whereas youth who did not have a psychological evaluation were more likely to have their treatment

services funded by the court. Low risk youth were also more likely to receive court-based funding

for treatment services.

Table 3. Logistic Regression Predicting Youth Receiving Treatment Services.

Variables b SE Exp(b)

Male 0.106 .109 — Age �0.226*** .033 0.797 Race/ethnicity

Black �0.407** .130 0.666 Latino(a) �0.247** .097 0.781 Native American �0.088 .207 — Other �0.299 .367 —

Living situation Two parents 0.029 .114 — Grandparents or relatives 0.296* .147 1.345 DCS and other 0.709*** .126 2.032 Not enrolled in school

y �0.129 .105 — Offense severity

Felony person 0.601*** .125 1.824 Misdemeanor property �0.289 .162 — Misdemeanor person 0.014 .172 — Drugs 0.042 .137 — Public peace 0.175 .145 — Other �0.116 .363 —

Preadjudication detention �0.261** .095 0.770 Prior referral �0.121 .121 — Prior adjudication �0.494*** .144 0.610 Psychological evaluation 1.647*** .092 5.189 Prior treatment service 0.131 .111 — Risk level

Moderate 0.035 .137 — High 0.351* .149 1.036 Constant 1.585** .543 —

Log-likelihood �1,754.29 Pseudo R2 .1748

Note. N ¼ 3,779. DCS ¼ Department of Child Services; SE ¼ standard error. *p � .05. **p � .01.***p � .001. yp � .1.

White 73

Table 4. Bivariate Statistics—Source of Funding for Treatment Services.

Variables Court Based

% External

%

Gender y

Female 66.4 33.6 Male 73.5 26.5

Race/ethnicity*** White (reference) 76.3 23.7 Black 68.8 31.2 Latino 75.2 24.8 Native American 30.0 70.0 Other 54.5 45.5

Age—mean (SD) 15.7 (0.05) 15.3 (0.09) Living with***

Two parents (reference) 80.8 19.2 Single parent 89.9 10.1 Grandparent or other family 74.7 25.3 Other-DCS 33.1 66.9

School enrollment Enrolled in school (reference) 71.4 28.6 Not enrolled in school 74.9 25.1

Offense severity*** Property felony(reference) 73.0 27.0 Personal felony 70.9 29.1 Property misdemeanor 58.2 41.8 Personal misdemeanor 58.7 41.3 Drugs 78.1 21.9 Public peace 86.3 13.7 Other 80.0 20.0

Preadjudication detention** Not detained (reference) 76.4 23.6 Detained 67.1 32.9

Prior referraly No prior referrals (reference) 76.2 23.8 Prior referral 70.2 29.8

Prior adjudication No prior adjudications (reference) 72.3 27.7 Prior adjudications 71.4 28.6

Psychological evaluation** No psychological evaluation (reference) 79.1 20.9 Psychological evaluation 69.0 31.0

Prior treatment servicey

No prior treatment services (reference) 73.6 26.4 Prior treatment services 67.2 32.8

Risk level*** Low (reference) 86.3 13.7 Moderate 68.2 31.8 High 69.6 30.4

Exclusive type of treatment service*** GMH outpatient (reference) 65.1 34.9 GMH residential 19.6 80.4 Sex offender outpatient 85.4 14.6

(continued)

74 Youth Violence and Juvenile Justice 17(1)

Finally, there were differences across the type of treatment service the youth received and the

funding source for those treatment services. In general, outpatient treatment services were more

likely to be funded by the court, while residential services (GMH, sex offender, and substance abuse)

were more likely to be funded by external sources. These findings indicate that both characteristics

of the youth and the type of treatment service required by the court are related to the source of

funding used to pay for treatment services.

The results from a two-stage FIML probit model predicting external funding compared to court-

based funding are presented in Table 5. 8

The results from the analysis show that Native Americans

are 76.5% (OR ¼ 1.765) more likely to receive treatment services through external funding, which is likely due to their tribal health care. Youth who were living in state care, such as DCS, were over 2

times (OR ¼ 2.07) more likely to receive treatment services through external funding sources. Youth who committed personal felonies and public peace offenses were 32.4% (OR ¼ .676) and 46.3% (OR ¼ .537), respectively, less likely to receive treatment services through external funding. Pre- adjudication detention and moderate-risk level had a positive significant effect, indicating that youth

who were detained prior to adjudication and youth who were moderate-risk level are more likely to

receive treatment services via external funding. In regard to psychological evaluation, youth who

received a psychological evaluation were less likely to receive services through external funding.

Finally, to address the second part of the research question—certain treatment services were more

likely to be funded by external sources, while other services were less likely, after controlling for

individual covariates. Specifically, GMH and substance abuse residential services were more likely to

be funded by external funding sources, whereas behavior-specific education, evidence-based, and drug

court services were more likely to be funded by the court. Lastly, youth who received two services or

three or more services were less likely to receive their services through external funding sources.

Discussion

The current study examined the receipt and funding of treatment services for mental and behavioral

problems among a sample of youth under probation supervision. Over the last two decades, research-

ers and practitioners have started to examine mental and behavioral service needs of youth and gain a

better understanding of the complexities of providing treatment services in the juvenile justice

system. Given this context, the current study contributes to the larger body of research on juvenile

justice and treatment services by (1) examining the actual receipt or use of treatment services by

youth under probation supervision, rather than referrals for services, and (2) examining the source of

funding for treatment services. In light of the significant findings presented in the previous section,

there are a number of key findings: (1) Few youth overall receive treatment services while on

Table 4. (continued)

Variables Court Based

% External

%

Sex offender residential 45.1 54.9 Substance abuse outpatient 85.3 14.7 Substance abuse residential 9.1 90.9 Other services 97.9 2.1 Two services 86.7 13.3 Three or more services 92.5 7.5

Note. n ¼ 861. Continuous measures were examined using a t test and categorical variables were examined using a w2 test. MH ¼ general mental health; SD ¼ standard deviation; DCS ¼ Department of Child Services. *p � .05. **p � .01. ***p � .001. yp � .1.

White 75

probation, (2) there are racial disparities in the receipt of treatment services, and (3) a disconnect

exists between receiving treatment services and the willingness or capability of external funding

sources to fund these services. These findings deserve further elaboration in the broader context of

research and implications for practice and policy.

Table 5. Stage-Two FIML Probit Model Predicting External Funding for Treatment Services.a

Variables b SE Exp(b)

Male 0.239 .161 — Age �0.084 .069 — Race/ethnicity

Black 0.076 .151 — Latino(a) 0.141 .111 — Native American 0.568* .264 1.765 Other 0.299 .438 —

Living situation Two parents �0.285y .171 — Grandparents or relatives 0.121 .184 — DCS and other 0.727** .265 2.069 Not enrolled in school 0.097 .121 —

Offense severity Felony person �0.391** .148 0.676 Misdemeanor property 0.294 .181 — Misdemeanor person �0.100 .193 — Drugs �0.097 .159 — Public peace �0.621** .230 0.537 Other �0.553 .532 —

Preadjudication detention 0.247** .105 1.280 Prior referral �0.054 .139 — Prior adjudication �0.009 .204 — Psychological evaluation �0.559*** .184 0.572 Prior treatment service 0.165 .145 — Risk level

Moderate 0.442* .199 1.556 High 0.356 .238 —

Exclusive type of treatment serviceb

GMH residential 0.929*** .221 2.532 Sex offender outpatient �0.155 .199 — Sex offender residential �0.293 .234 — Substance abuse outpatient �0.251 .174 — Substance abuse residential 1.235** .397 3.438 Other service �0.822* .325 0.440 Two services �0.599** .208 0.549 Three or more services �0.896** .342 0.408

Constant 1.648* .726 — Log likelihood �1,983.15 Rho w2 0.98 Model w2 156.5***

Note. N ¼ 861. GMH ¼ general mental health; FIML ¼ full information maximum likelihood; DCS ¼ Department of Child Services; SE ¼ standard error. aStage-one FIML probit model predicted youth receiving any treatment services. bMentoring/life skills services omitted due to perfect prediction into court-based funding. *p � .05. **p � .01. ***p � .001. yp � .1.

76 Youth Violence and Juvenile Justice 17(1)

Use of Treatment Services

The first main finding of the current study is that approximately 25% of youth on probation received treatment services. Estimates of mental health disorders among youth in the juvenile justice system

are as high as 60–70% (Garland et al., 2001; Shufelt & Cocozza, 2006; Teplin et al., 2002), and roughly half of which also suffer from substance use disorders (Teplin et al., 2002). Given that

almost 40% of the youth received a psychological evaluation (a proxy for mental health problems) in the current study, it was expected that more youth would receive treatment services. This finding is

consistent with other research that has found a relatively small proportion of youth receive services

in the juvenile justice system despite high prevalence rates (Rogers et al., 2006; Wasserman et al.,

2008), providing additional support that youth with mental and behavioral problems are an under-

served segment of the juvenile justice population.

Unlike much of the prior research, there were no gender differences in service use, but the living

situation did influence the use of treatment services as well as a number of variables related to

offending history and involvement in the juvenile justice system. Particularly youth who lived

without their parents, either with grandparents or other family and especially those is DCS or State

care, were more likely to receive services. Parents and caregivers play an important role in recog-

nizing mental health problems and accessing services to meet service needs (Harrison, McKay, &

Bannon, 2004); therefore, youth not living with parents and entering the juvenile justice system may

have greater unmet service needs that were not being addressed previously. In comparison, youth

living with parents may have more opportunity for support from parents, have fewer service needs,

or may already be receiving services. Additionally, youth under the care of their grandparents or

other relative may have been previously connected to social services agencies and professionals who

may have facilitated services beyond those initiated by correctional service agencies. An alternative

argument is that parents may pose certain obstacles to youth receiving services, such as lack of

involvement (Broeking & Peterson-Badali, 2010; Davies & Davidson, 2001; Peterson-Badali &

Broeking, 2010) or hesitation due to cultural or views about parenting, subsequently affecting

youth’s responsivity to treatment (Haqanee et al., 2015). As a result, courts may be more likely

to refer youth to services when they live with grandparents, other family, or some other care.

Youth convicted of a personal felony and high risk youth were also more likely to receive

treatment services, while youth who were detained or had prior adjudication were less likely to

receive services. In some ways, these are conflicting results; on one hand, it reflects that youth with

more need (not living with parents, felony, and high risk) are getting services, but those previously

detained or adjudicated are not as likely to receive services. This finding may reflect the court

focusing services on youth with high need and limited involvement in the juvenile justice system,

while the court may be more apprehensive to provide treatment services to repeat offenders because

it is viewed as not effective or a good use of resources.

Importantly, a psychological evaluation was a strong predictor of receiving treatment, but

there were still many youth who had an evaluation but did not receive services. Returning to the

RNR model and the importance of identifying risk and needs, and matching services to those

needs, this finding is consistent with research that has found identified needs are not always met

with the appropriate services, often due to lack of resources and programming (Gebo, Stracuzzi,

& Hurst, 2006; Shook & Sarri, 2007), experience with RNR assessments (C. Schwalbe, 2004), or

prioritizing other needs that may not qualify as a risk/need according to assessment tools (Bonta,

Rugge, Scott, Bourgon, & Yessine, 2008; Haqanee et al., 2015; Young, Moline, Farrell, & Bierie,

2006). In the current study, a small percentage (6.6% of youth receiving services) received evidence-based programs, which is a fraction of all the youth on probation, despite a large

number of youth classified as high risk, suggesting a disconnect between risk/needs and use of

evidence-based programming.

White 77

While support for RNR assessment tools and success in reducing risk of recidivism is evident, the

complexities of youths’ risks and needs create many challenges for implementation in the justice

system, particularly given the inconsistent relationship between mental health and recidivism

(Bonta, Blais, & Wilson, 2014; Wibbelink et al., 2017). If treating mental health problems does

not reduce recidivism, the juvenile justice system may not prioritize it as a need worth addressing.

On the other side, mental health problems are considered in the responsivity principle and problems

that interfere with or limit engagement in criminogenic need-focused intervention are prioritized for

service. For instance, mental health problems may increase an individual’s vulnerability to crimino-

genic needs, such as when a mental health issue interferes with school performance or behavior or

when mental health issues contribute to family conflict. More research is needed to untangle some of

these nuances and complexities to provide clearer goals for the justice system in treating mental health

problems. The current study did not have diagnostic information from youths’ case files, and as a

result, the type of emotional or behavioral problem, the severity of the problem, history of substance

abuse, and comorbidity with other disorders could not be determined, making it difficult to truly assess

the level of service needs of these youth and whether the services are addressing those need.

Another key finding in the current study is the presence of racial and ethnic disparities in the receipt

of treatment services by youth while on probation. Prior research has found that minorities are more

likely to have unmet service needs compared to White youth (Alegria, Carson, Goncalves, & Keefe,

2011; Angold et al., 2002; Garland et al., 2005; Kataoka et al., 2002; Thompson, 2005; Yeh et al.,

2003), and when they do receive treatment services, it is more likely to occur in the juvenile justice

system rather than the mental health system (Atkins et al., 1999; Cohen et al., 1990; Dembo et al.,

1994; Evens & Stoep, 1997; Thomas & Stubbe, 1996). The current study found that among youth on

probation, Blacks and Latinos were less likely to receive treatment services than their White counter-

parts, after controlling for other youth and behavioral characteristics. Therefore, even though the

juvenile justice system may be their best opportunity to receive treatment services (Rawal et al.,

2004), minorities remain less likely to receive treatment services while under probation supervision.

This finding can be understood in the larger context of health disparities and access to health care.

It is well-established that minorities, particularly Blacks, have poorer health which can be attributed

to a number of factors such as low-socioeconomic status and limited access to quality health care

(Center for Disease Control and Prevention, 2013). Additionally, racial and ethnic minorities have

limited access to services, needs are more likely to go unmet, and when services are received they

are of poor quality (Atdjian & Vega, 2005; McGuire & Miranda, 2008; Snowden, 2001; U.S.

Department of Health and Human Services, 2001; Williams, 2005). These disparities have been

attributed to limited access to treatment and health-care providers geographically and financially

(Alegria et al., 2006; Simpson et al., 2005) as well as the mistrust of beneficial services and stigma

associated with receiving mental health services inhibiting minorities in particular from seeking

treatment services (U.S. Department of Health and Humans Services, 2001).

The disparate access to treatment services in the juvenile justice system may stem from multiple

sources, including the identification and diagnosis of mental health and substance abuse disorders

through common psychological evaluations and diagnostic instruments that have been criticized for

their use on youth and minorities (Grisso, 2004). For example, diagnoses are not sensitive to contextual

differences because disorders are identified based on the presence or absence of symptoms but fail to

take into account the developmental relevance to youth or cultural differences (Grisso, 2004; Rogler,

1993; Safran et al., 2009; Smith, Spillane, & Annus, 2006; Wakefield, 1997). As a result, the service

needs of minority youth may not be adequately identified and assessed.

Second, disparities may be the result of stereotyping and biased beliefs about amenability to

treatment. Sentencing research has tested attribution theory (see Albonetti, 1991; Bridges & Steen,

1998) and has found that minorities are treated more harshly in the juvenile justice system because

their behavior is attributed to internal causes or “bad” personality traits, rather than external factors

78 Youth Violence and Juvenile Justice 17(1)

that can be addressed with treatment. These negative stereotypes have also been found in the health

field where doctors believe Blacks are less likely to comply with treatment (McGuire & Miranda,

2008). Similarly, court officials may believe that minority youth are less deserving of treatment

services or that the treatment services will not be as effective or beneficial to minority youth. These

findings support the historical argument that are two juvenile justice systems, one for Whites and

one for Blacks (G. Ward, 2012), where minority youth have a different experience when they enter

the juvenile justice system, characterized by harsh treatment and little access to services. This may

have long-term implications for their involvement in the juvenile and criminal justice systems as

well as perpetuating health differences that continue over the life course (Yazzie, 2011).

Youth with mental and behavioral service needs can be found in multiple “systems of care,”

including the education system, the mental health system, child welfare system, and the juvenile

justice system (Garland et al., 2001; Stroul, 2002; Stroul, Blau, & Sondheimer, 2008). It is essential

that these systems of care collaborate by sharing information and resources to help ensure that

service needs for youth who are vulnerable to mental and behavioral problems are identified as

early as possible and that services are provided. Unmet mental and behavioral service needs in youth

can affect both their success while on probation and their future involvement in the criminal justice

system (Binswanger, Redmond, Steiner, & Hicks, 2012; Kutcher & McDougall, 2009; Yazzie,

2011) as well as other aspects of life like successful employment and healthy relationships.

Funding Sources of Treatment Services

The current research found that a majority (66%) of youth who received treatment services were funded by the court, and most of the youth who receive funding for treatment services through

external funding sources, through AHCCCS or RBHA, as well as tribal health coverage. Very few

youth received treatment services through private insurance, which was not unexpected because

private insurance companies often have a disclaimer that the insurance company is not required to

cover court-ordered services, unless medically necessary. Given the socioeconomic status of youth

in the juvenile justice system, it was expected that more youth would have external funding for

services through public assistance like AHCCCS. It may be that in some instances, the court is

having to fund services of youth with private insurance who are not eligible for public assistance, but

insurance will not cover the services. Unfortunately, the current study was not able to capture

whether the youth had health coverage prior to their involvement in the juvenile justice system,

or the type of health insurance, so it is difficult to assess the role of prior health coverage, and

whether the court still funded the treatment services when a youth had coverage.

These findings are informative for court administrators to better understand the factors related to

youth receiving treatment services through external funding compared to the youth who tend to

receive services via court-based funding, which has implications for the continuity of care. Partic-

ularly, treatment services may be beneficial to youth after their involvement in the juvenile justice

system, but without court-based funding, the services cannot be continued unless the youth is able to

attain other sources to cover the cost of the services. If the youth is eligible for Medicaid to cover

services, there may be a change in service provider and any established rapport with a mental health

professional is disrupted. The process of continuing care after probation has ended may be less

disruptive if the services are funded through external sources from the beginning. Youth may be able

to continue using the same service provider with the same health care coverage. Youth who received

psychological evaluations were more likely to have services funded by the court, which is likely

because psychological evaluations are funded by the court so continuity of services is more likely if

the same service provider and funding source is used by the court.

If more youth become insured and behavioral health services covered to a greater extent as a result

of health-care reform (Cockburn, Heller, & Sayegh, 2013; Council of State Governments Justice

White 79

Center, 2013), we may see more services in the juvenile and criminal justice system covered through

external funding sources such as Medicaid or private insurance. Expanding mental health coverage and

Medicaid may shift the burden of funding treatment services off the juvenile justice system and into

the health-care system, allowing the juvenile justice system to focus on the delinquency of youth. This

is consistent with Feld’s (1999) argument that the juvenile justice system should be responsible for

responding to delinquent and criminal behavior and other systems of care should be responsible for the

care and welfare of youth. This reform would require the collaboration of agencies to work together

and share information regarding the service needs of youth to help them be successful while involved

in the juvenile justice system and ensure treatment services are provided (Clark & Gehshan, 2006).

There also needs to be clarity in the roles of different systems of care or agencies and implicit

guidelines for responding to delinquency and youth experiencing emotional and behavioral problems.

Limitations

This study had the benefits of a large, representative sample of youth on probation, capturing the actual

use of treatment service, and included a number of variables on prior delinquency and involvement in the

juvenile justice system. But the study is not without its limitations. The sample is limited to one county in

the Southwest, so it is not appropriate to generate findings to juvenile justice systems in other jurisdic-

tions. In addition, the data are used for tracking youth and managing files, not for research purposes, so

other measures particularly related to family/home and school/peer life that may impact service decisions

were not captured. Perhaps most importantly, information from psychological evaluations such as mental

health disorder diagnoses was not measured because information in the youth’s case file is typically not

transferred into an electronic form. Without mental health diagnoses, it is difficult to directly measure

service needs. In particular, the type and severity of emotional and behavioral disorders, as well as

the comorbidity of disorders, has important implications for the receipt of treatment services.

Conclusion

There is growing recognition that youth suffer from mental and behavioral problems which affect

multiple aspects of their lives and may put them at risk for delinquency and involvement in the juvenile

justice system. Ideally, the juvenile justice system should be used as a last resort to address these

adversities, but that is not typically the case. Instead, youth enter the juvenile justice system often due

to the absence of viable, community-based alternatives to address the hardships in their lives (Myers &

Farrell, 2008). The overlap in responsibilities for seriously delinquent youth and seriously mentally ill

youth is often labeled as “not ours” (Grisso, 2004), demonstrating the difficultly of serving youth and the

failure of different systems and agencies to take responsibility. The result can be a lifetime of involve-

ment in the criminal justice system (Cocozza & Skowyra, 2000; Davis, Banks, Fisher, & Grudzinskas,

2004; Elliott, Huizinga, & Menard, 1989; Graves, Frabutt, & Shelton, 2007; Pullmann, 2010), which has

been an ongoing struggle for the juvenile justice system and other systems of care (Grisso, 2004, 2008;

Skowyra & Cocozza, 2007). Lipsey, Howell, Kelly, Chapman, and Carver (2010) argued that

the two most progressive policy reforms of recent years are the drive for evidence-based practice, which

focuses on effective treatments, services, and supports for children and families, and the effort to

establish systems of care to address the infrastructure of funding and linkages between services and

programs. (p. 9)

Identifying service needs and providing services matched to those needs is not an easy process, but

the consequences of ignoring the problems can have long-term negative effects both for the indi-

vidual youth and for the larger community.

80 Youth Violence and Juvenile Justice 17(1)

Appendix A

Author’s Note

This study was approved by institutional review board. This article does not contain any studies with human or

animal subjects. Data was de-identified and informed consent was not applicable.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or pub-

lication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

1. For youth with multiple probations, the first probation is included and only the treatment services received

during the probation supervision of interest.

2. Since psychological records were not managed electronically, this limited access to mental health records

and diagnoses.

3. Most often the effective date of treatment services was the start date of probation (mode), but the average time

between probation starting and the start of treatment services was 114 days and the median was 50 days. Therefore,

by including youth that started probation toward the end of my time frame, these youth may not have had an

opportunity to receive treatment services while on probation and would be not captured in my data. As a limitation,

the number of youth receiving treatment services while on probation is likely underestimated to some degree.

4. The amount missing on each variable did not exceed 5% of the entire sample, and the total missing cases was

less than 10% of the sample, listwise deletion was used to deal with the missing data problem in the current

analysis (see Bennett, 2001; Schafer, 1999).

5. Behavior-specific education includes a variety of programs and classes targeted at specific behaviors, such

as anger management, conflict resolution, or shoplifting. Mentoring services involve pairing youth with an

Youth Receiving Treatment Services.

Type of treatment service

All Youth Receiving Service

Youth Receiving Service Exclusively

Duration of Treatment Servicea (days)

n % n % Mean SD Median Range

GMH outpatient 282 29.9 173 18.3 133.7 99.07 92.0 1–591 GMH residential 188 19.9 103 10.9 156.1 108.8 130.5 1–668 Sex offender outpatient 140 14.8 101 10.7 244.5 167.0 202.0 10–804 Sex offender residential 97 10.3 55 5.8 253.2 167.6 206.0 4–718 Substance abuse outpatient 196 20.8 95 10.1 134.8 93.1 90.0 4–633 Substance abuse residential 44 4.7 23 2.4 102.8 58.5 91.5 11–278 Mentoring and life skills 179 19.0 95 10.1 102.6 55.1 90.0 3–391 Behavior specific education 6 0.6 4 0.4 103.3 72.8 90.0 18–238 Evidence-based programs 62 6.6 31 3.3 141.9 80.4 131.0 4–430 Drug court 70 7.4 16 1.7 144.7 88.8 143.0 3–373 Two services — — 188 20.0 — — — — Three or more services — — 59 6.3 — — — — Total — — 944 100.0 186.4 141.1 147.0 1–850

Note. n ¼ 944. Mode duration is 90 days for all types of services. GMH ¼ general mental health; SD ¼ standard deviation. aType of treatment services are not mutually exclusive.

White 81

adult role model improve prosocial development and also include life skills development and comprehensive

youth programs. The evidenced-based programs include Brief Strategic Family Therapy (BSFT), Functional

Family Therapy (FFT), Multi-Systemic Therapy (MST), and Multi-Systemic Therapy for Problem Sexual

Behavior (MST-PSB). For GMH services, sex offender services, and substance abuse services, youth can

receive out-of-home or residential treatment or outpatient care in the community. In addition, youth in the

residential treatment setting can receive these services in the Level I Residential Unlocked unit, the Level I

Residential Locked unit, the Level II Residential unit, and in Department of Economic Security licensed

group homes. Outpatient services include individual counseling, family counseling, group counseling,

home-based counseling, and multifamily group counseling, and therapeutic days.

6. Youth can also receive funding for services from the court and external sources (n ¼ 83), but this group is not included in the current analysis.

7. Receiving treatment services is not a random process and factors that influence whether a youth receives

treatment services might also influence the type of funding source for treatment services, which constitutes

selection bias. When there is selection bias, the standard errors of the selection model (receiving treatment

services) can be correlated with the standard errors of the primary dependent variable (funding source)

effecting the statistical significance of independent variables on the outcome. The full information maxi-

mum likelihood probit model predicts selection into treatment service to control for selection bias, which is

followed by analyzing the dependent variable of interest in the second stage of the model (Berk, 1983).

8. Stage one predicting treatment services are not presented but are similar to the logistic regression results

presented in Table 3.

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Author Biography

Clair White completed her PhD student at Arizona State University in the School of Criminology

and Criminal Justice in 2015. She is a research assistant professor at the Center for Evidence-Based

Crime Policy at George Mason University. Her research interests include mental health and the

criminal justice system, service use, crime and place, and the illicit use of prescription drugs.

White 87