Week 4: discussion 1

E M P I R I C A L R E S E A R C H

Youth Pathways to Placement: The Influence of Gender, Mental Health Need and Trauma on Confinement in the Juvenile Justice System

Erin M. Espinosa • Jon R. Sorensen •

Molly A. Lopez

Received: 9 April 2013 / Accepted: 27 June 2013 / Published online: 4 July 2013

� Springer Science+Business Media New York 2013

Abstract Although the juvenile crime rate has generally

declined, the involvement of girls in the juvenile justice

system has been increasing. Possible explanations for this

gender difference include the impact of exposure to trauma

and mental health needs on developmental pathways and

the resulting influence of youth’s involvement in the justice

system. This study examined the influence of gender,

mental health needs and trauma on the risk of out-of-home

placement for juvenile offenders. The sample included

youth referred to three urban juvenile probation depart-

ments in Texas between January 1, 2007 and December 31,

2008 and who received state-mandated mental health

screening (N = 34,222; 30.1 % female). The analysis

revealed that, for both genders, elevated scores on the

seven factor-analytically derived subscales of a mental

health screening instrument (Alcohol and Drug Use,

Depressed-Anxious, Somatic Complaints, Suicidal Idea-

tion, Thought Disturbance, and Traumatic Experiences),

especially related to past traumatic experiences, influenced

how deeply juveniles penetrated the system. The findings

suggest that additional research is needed to determine the

effectiveness of trauma interventions and the implemen-

tation of trauma informed systems for youth involved with

the juvenile justice system.

Keywords Detention � Incarceration, disposition � Gender disparity � Trauma � Mental health

Introduction

Adolescence is a period of developmental transition char-

acterized by changes in family, school, peers, self-concept,

and general physical development (Bergman and Scott

2001). Although most youth navigate this developmental

period successfully, incidents of rule breaking and behav-

ioral problems are common and can result in involvement

with law enforcement. Some research suggests that inter-

vention by the criminal justice system during the critical

period of adolescence may negatively impact youth out-

comes, including decreasing opportunities for meeting

educational goals and increasing the risk for later

involvement in delinquency and deviance (Sampson and

Laub 2005; pipeline articles). Recent trends have shown a

steady decline in juvenile offending overall, particularly

among violent crimes. However, statistics have also shown

a trend toward increased delinquency in females. For

example, Snyder (2008) reported that between 1994 and

2006, arrests for simple assault declined by 4 % for boys

while the rate increased by 19 % for girls. Given the

gender differences in adolescent development, it seems

critical to examine the pathways that lead to youth

involvement in the juvenile justice system through this

lens.

Research consistently shows gender-related differences

in delinquent behavior. The literature suggests these

E. M. Espinosa (&) � M. A. Lopez Texas Institute for Excellence in Mental Health, Center

for Social Work Research, School of Social Work,

The University of Texas at Austin, 1717 West 6th Street,

Ste. 335, Austin, TX 78703, USA

e-mail: [email protected]

M. A. Lopez

e-mail: [email protected]

J. R. Sorensen

Department of Criminal Justice, East Carolina University,

Rivers Building, Office #245, Mail Stop 505, Greenville,

NC 27858, USA

e-mail: [email protected]

123

J Youth Adolescence (2013) 42:1824–1836

DOI 10.1007/s10964-013-9981-x

differences first emerge early in child development and

become more pervasive in adolescence. Some leaders in

criminology have suggested that gender differences in

delinquent behavior can be attributed to differential

socialization between genders (Bottcher 2001), while oth-

ers have argued that differences are tied to offender status

in a gender-stratified society (Chesney-Lind 2002). How-

ever, a third model emerges when examining both the

developmental criminological and the developmental psy-

chology literature. The developmental psychology litera-

ture has shown that females are more likely to exhibit

internalizing symptoms that may not come to the attention

of the adults in their life (Rosenfield et al. 2005), while

males are more likely to exhibit externalizing behaviors,

which are problematic for other people and society

(Compton et al. 2002; Kazdin 2005). Greater internalizing

results in girls having increased rates of depression, bipo-

lar, anxiety, post-traumatic stress, and other mood disor-

ders. Boys tend to have higher rates of conditions such as

attention-deficit/hyperactivity disorder, oppositional defi-

ant disorder, and conduct disorder. Therefore, one possible

explanation of the gender differences found in the

involvement of youth in the juvenile justice system could

be explained by differences in mental health conditions that

may develop and/or intensify in adolescence.

Gendered Pathways to Delinquency

Pathways toward and through the juvenile justice system

differ between girls and their male counterparts. This may

be related to how boys and girls develop their self-concepts

and identities. Boys’ self-concepts and identities are

developed in relationship to the world, while girls’ and

young women’s self-concepts and identities are developed

through their interactions with others (Gilligan and Brown

1992). Gilligan and Brown contend that female moral

development is based on a personal view and commitment

to others. Although female offenders occasionally engage

in conduct more stereotypical of males, such as aggression

and assaultive behavior, more often they suppress their

aggression and struggle with the difficulty of managing

their emotions, especially those associated with depression

and anxiety (Ford et al. 2006). Delinquent girls have a

higher risk of self-devaluation, suicidality (Wasserman

et al. 2005), and conflict with family and school compared

with their male counterparts (Zoccolillo et al. 1996).

Attachment, interdependence and connectedness are criti-

cal to the foundation of their identity.

Gender Disparity in System Processing

Studies of delinquency and the response of the juvenile

justice system have consistently found both legal and extra-

legal factors contribute to the detention and dispositional

outcomes of youth involved in juvenile offending. How-

ever, findings have been inconsistent regarding the effects

of gender on case outcomes in post-adjudication disposi-

tion decisions (Belknap and Holsinger 2006). Some studies

have revealed girls were the recipients of more severe

sanctions than their male counterparts, especially in

response to status offenses (Chesney-Lind 2002). Other

studies indicated females received more lenient outcomes

for delinquent behavior (class B misdemeanor and higher

offenses) than males. Some research discovered that out-

comes depend on the stage of processing. For instance,

MacDonald and Chesney-Lind (2001) reported no differ-

ence between boys and girls in the decision to petition an

offense. However, during the adjudication stage, ‘‘charge

seriousness’’ was more important for girls than boys with

the reverse trend during the disposition stage. Thus, when

female juvenile offenders were adjudicated delinquent,

they were ‘‘more likely than boys to be given a restrictive

sanction for a less serious offense’’ (p. 187).

It has become common knowledge in criminology that

by engaging in a practice referred to as bootstrapping,

courts detain females through findings of contempt of

court, probation violations, or violations of court orders for

underlying status offenses or minor delinquent behavior

(Sherman 2005). As a result of bootstrapping, early evi-

dence suggests more female juvenile offenders are detained

prior to adjudication for offenses less threatening to the

community than those of their male counterparts. Data

from the Juvenile Detention Alternatives Initiative (JDAI),

launched by the Annie E. Casey Foundation in 1992,

demonstrated the number of juveniles housed in secure

detention nationwide increased by 72 % between 1985 and

1995 (Sherman 2005). While it may be assumed this

increase reflected the need for community safety, less than

one-third of the juvenile offenders detained in 1995 were

charged with a violent offense. Across both genders, more

youth were detained for status offenses than violent

offenses, with violations of court orders accounting for

39.9 % of the detention population. This trend was even

greater for female juvenile offenders, who were more likely

than their male counterparts to be detained for status

offenses and technical violations (Sherman 2005). Similar

findings have been demonstrated in several study replica-

tions (American Bar Association and the National Bar

Association 2001; Sickmund et al. 2004).

For instance, Gavazzi et al. (2006) noted girls were more

likely to be detained for incorrigibility and domestic vio-

lence, and parents were more likely to be the complainants.

Their findings also indicated boys were more likely to be

arrested for property offenses, with complainants more

likely to be community citizens. The authors summarize

the difference between male and female juvenile detention

J Youth Adolescence (2013) 42:1824–1836 1825

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decisions by stating that: ‘‘boys are detained as a response

to public safety issues, whereas girls are detained because

of problems at home’’ (p. 608). By 2003, this trend had

extended to custodial placements other than detention as

well, with females accounting for 40 % of the status

offenders but only 14 % of delinquents held in custody

(Snyder and Sickmund 2006).

Mental Health Disorders and Delinquency

Recent studies suggest a correlation between juvenile jus-

tice system processing and psychiatric disorders, with some

research indicating girls with mental health needs are

funneled deeper into the system for less serious offenses

than their male counterparts. Abram et al. (2003), in a

study of Cook County Juvenile Detention youth, found

females were 1.4 times more likely than males to meet

diagnostic criteria for at least one disorder, and they also

were more likely to have at least one co-morbid disorder.

Davis et al. (2009) discovered females receiving care in the

community mental health system were arrested at younger

ages and more frequently than girls not receiving public

mental health treatment. In addition, for those youth

needing hospitalizations, girls had shorter lengths of stay

than boys (Pavkov et al. 1997). These findings have lead

some researchers to suggest girls are typically undertreated

for their mental health needs and others to suggest this lack

of treatment results in their involvement in the juvenile

justice system (Wasserman et al. 2005).

Youth involved with the juvenile justice system often

have not one, but several co-morbid psychiatric disorders.

Wasserman et al. (2005) found the prevalence of youth

meeting criteria for at least one psychiatric disorder to be

39 %, with 16 % meeting criteria for three or more disor-

ders. In addition to the growing prevalence of youth with

mental health challenges in the juvenile justice system,

studies also indicate mental health disorders are correlated

with delinquent behavior. Several prospective studies

indicate hyperactivity (Lynam et al. 2000), conduct disor-

ders and emotional disorders (Copeland et al. 2007; Boots

2008; Boots and Wareham 2009) serve as key indicators

for involvement with the justice system. Specifically, Co-

peland et al. (2007) found 20.6 % of female juvenile

offending and 15.3 % of male juvenile offending was

attributable to mental health disorders, after controlling for

offense level and poverty. Among specific psychiatric

profiles, the findings indicate co-occurring anxiety and

depressive disorders had the strongest association with

delinquent behavior. Boots and Wareham (2009) extended

these findings further when they demonstrated a moderate

correlation between depression and anxiety (r = .577) and

future offending.

Trauma and Delinquency

Although not all youth who experience trauma engage in

delinquent activity, studies of youth involved with the

juvenile justice system have found high rates of trau-

matic experiences, generally between 70 and 90 %

(McMackin et al. 1998; Steiner et al. 1997). Some

studies have found boys and girls involved with the

juvenile justice system experienced different types of

traumas, with males more likely to have witnessed a

violent event and females more likely to have been the

victim of violence. The Survey of Youth in Residential

Placement, conducted on a sample of over 7,000 incar-

cerated youth, indicated females were almost twice as

likely to report prior physical abuse (42 % of females

versus 22 % of males), and females reported a higher

likelihood (69 % of females versus 40 % of their male

counterparts) of the perpetrator of the physical abuse

being a sibling or mother (Sedlak and McPherson 2010).

Researchers also found girls who reside in violent homes

have heightened risk factors for engaging in delinquent

activity, such as truancy, sexual promiscuity, running

away, and substance abuse (Thornberry et al. 2004). Not

surprisingly, female juveniles arrested for running away

frequently report experiences of family violence and

emotional, physical, and sexual abuse and report these

conditions as their primary motivation for leaving home

(Chesney-Lind 2002). Furthermore, studies indicate

females who have experienced trauma develop mental

health problems as a result of that trauma more often

than their male counterparts (Crimmins et al. 2000).

Some studies found girls who have mood disorders are

more likely to have experienced trauma and are more

likely to have post-traumatic stress disorder (Wasserman

et al. 2005).

Sexual victimization, in particular, is a common form

of trauma experienced by girls involved in the justice

system and is likely a contributing factor to the complex

mental health needs of this population. Although virtually

absent from formal theories of female delinquency, some

studies examined the correlation between sexual abuse

and female juvenile delinquency. In a study of chroni-

cally delinquent offenders, Sherman (2005) found 77 %

of female offenders had a history of sexual abuse in

comparison to only 3 % of the males, suggesting a

potential relationship between trauma and chronic delin-

quency in girls. Furthermore, Goodkind et al. (2006)

found juvenile justice-involved girls who have experi-

enced some form of sexual abuse had poorer mental

health and more substance use, risky sexual behavior, and

delinquent behavior than those who had not experienced

this form of trauma.

1826 J Youth Adolescence (2013) 42:1824–1836

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Hypotheses

Despite the overall decline in the rate of juvenile delin-

quency, the involvement of girls with the juvenile justice

system has increased. In addition, there has been an

enhanced recognition of the disproportionate representation

of youth with mental health needs and trauma histories in

the juvenile justice system. While males typically are

associated with externalizing problems, females dispro-

portionately are identified with internalizing problems and

interpersonal aggression. This changing demographic of

juvenile delinquency poses challenges to the traditional

juvenile justice system accustomed to handling behaviors

associated with externalizing manifestations of delin-

quency. Analyzing the extent to which mental health need,

trauma, and gender influence juvenile justice system pro-

cessing will provide a more comprehensive understanding

of the pathways youth take in the juvenile justice system,

as well as identify potential modifications needed to

address the unique needs of youth accessing the system in

the future.

First, we hypothesized that more girls would be placed

outside of the home for bootstrap level offenses, such as

status offenses and violation of probation, than boys. This

analysis sought to determine whether girls are funneled

deeper into the system for lower level offenses than their

male counterparts. Second, we hypothesized that greater

mental health need, as measured by the mental health

screening instrument, would be associated with a greater

risk of out-of-home placement. Finally, we formed an

exploratory hypothesis aimed toward examining the influ-

ence of the endorsement of prior traumatic experiences, as

measured by the mental health screening instrument, on the

restrictiveness of out-of-home placement decisions. We

were interested in whether a trauma history increased the

likelihood of a juvenile being removed from their home. In

addition to these three primary hypotheses, a secondary

analysis explored the relative importance of these variables

on different types of out-of-home placement.

Method

The study sample included all youth referred to three urban

juvenile probation departments in Texas during the period

of January 1, 2007 through December 31, 2008. Only youth

who received the state-mandated mental health screening,

the Massachusetts Youth Screening Instrument-Second

Version (MAYSI-2) were included (N = 34,222; 30.1 %

female). This secondary dataset included all demographic,

offense, disposition and placement data collected by

trained juvenile probation officers and clinicians within the

departments. Data was obtained with approval from the

Chief Juvenile Probation Officer and the juvenile board and

the protocol was reviewed and approved by the Institu-

tional Review Board at the researchers’ university.

Measures

The main predictor variables considered were referral

offense seriousness, gender, and level of mental health

need. Gender is a dichotomous static variable and was

coded as male (0) or female (1) for analysis. The referral

offense seriousness and level of mental health need vari-

ables could be interpreted with a broad array of values;

therefore, specific operational definitions and categorical

values for these variables were developed prior to con-

ducting analyses.

Offense Seriousness

Youth could have been referred to local juvenile probation

departments for multiple offenses on any one referral

event. Therefore, this study targeted the referral offense

associated with most severe disposition during the sample

period. The categorical coding guidelines identified within

the Texas Juvenile Probation Commission (TJPC) data

codebook were used for establishing operational definitions

and assigning categorical values for offense seriousness.

The TJPC data codebook is used by juvenile probation

officers collecting and entering data into the state’s data

collection system. This coding process categorized the

4,019 types of offenses into a continuous classification

variable ranging from the least serious 1 (status offenses) to

the most severe 8 (capital felony). The classifications

between status offense and capital felony included the

following: 2 = Class B misdemeanor; 3 = Class A mis-

demeanor; 4 = State-jail felony; 5 = Third-degree felony;

6 = Second-degree felony; and 7 = First-degree felony.

In addition to the ordinal offense severity code, two

dichotomous indicator variables were constructed to eval-

uate the potential bootstrapping of juveniles into and

through the juvenile justice system. Bootstrapping has been

defined in the literature as engaging in a practice whereby

courts detain females through findings of contempt of

court, probation violations, or violations of court orders for

underlying status offenses or minor delinquent behavior

(Sherman 2005). A traditional bootstrap variable (Status)

included offenses that have been typically categorized as

status offenses (otherwise known as ‘‘Conduct Indicating

Need for Supervision Offenses’’ or CHINS offenses), Class

C misdemeanors, and contempt of court referrals. These

types of offenses include runaway, truancy, and curfew

violations. Class C misdemeanors are typically violations

of city or county ordinances and are processed in a manner

similar to status offenses. A second bootstrap variable

J Youth Adolescence (2013) 42:1824–1836 1827

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(VOP) included violations of probation or juvenile court

order.

Mental Health Need

Texas has adopted the MAYSI-2 for mental health

screening within the juvenile justice system (Grisso 2004;

Schwank et al. 2003). The MAYSI-2 is a 52-item, self-

report screening instrument completed by youth between

the ages of 12 and 17 upon intake in the juvenile justice

system. The MAYSI-2 contains seven factor-analytically

derived subscales: Alcohol and Drug Use, Angry-Irritable,

Depressed-Anxious, Somatic Complaints, Suicidal Idea-

tion, Thought Disturbance, and Traumatic Experiences.

Studies have demonstrated good concurrent validity when

comparing MAYSI-2 scales with scores on other mental

health measures (Archer et al. 2004; Grisso and Barnum

2006). Test–retest reliability up to eight days later was

moderate to good, ranging from 0.53 to 0.89 (Grisso and

Barnum 2006). Cut-off scores for the MAYSI-2 subscales

(excluding Traumatic Experiences) were developed to

identify youth scoring greater than 90 % of the normative

sample on each subscale (Grisso and Barnum 2006).

Overall mental health need was defined as the total number

of subscales reaching this ‘‘warning’’ cut-off, ranging from

0 to 6.

The traumatic experiences subscale of the MAYSI-2

does not have established warning cut-offs, and so was kept

in its original reporting format, with a scoring range of 0–5.

Four questions on the subscale are common to both gen-

ders: ‘‘Have you been badly hurt or been in danger of

getting badly hurt or killed?’’, ‘‘Have you ever in your

whole life had something very bad or terrifying happen to

you?’’, ‘‘Have you ever seen someone severely injured or

killed?’’, and ‘‘Have you had a lot of bad thoughts or

dreams about a bad or scary event that happened to you?’’.

For boys, the fifth question is ‘‘Have people talked about

you a lot when you’re not there?’’. For girls, this fifth

question is ‘‘Have you ever been raped or been in danger of

getting raped?’’.

Level of Placement

Level of placement was categorized into a five-point

ordinal variable, with higher scores on the scale repre-

senting more ‘‘severe’’ placements. Categorization reflec-

ted not only the determination of whether the facility was

secure or non-secure, but also consideration of what

intercept point in the juvenile justice system (pre or post

disposition) the juvenile could be placed within the facility.

No placement is reflected by a ‘‘0’’ on the scale and

detention is reflected by a ‘‘1’’. Although often a secure

setting, juvenile detention facilities are the first type of

facility within the juvenile justice system a youth can be

placed and are frequently used to hold juveniles while

awaiting court decisions pre-adjudication. The next three

levels of placement severity within the composite were

non-secure (2), county secure (3), and state correctional

facility (4). Non-secure facilities included facilities

licensed by the state child welfare agency to provide foster

care or treatment services and included residential treat-

ment centers, emergency shelters, substance abuse treat-

ment facilities, therapeutic camps, and foster care. Local

juvenile probation departments contract with non-secure

facilities to care for juveniles who are considered low risk

and in need of some form of treatment or other basic care

needs. County secure facilities included county-operated

secure post-adjudication programs registered with the

state’s juvenile justice department to serve as an interme-

diate placement option for moderate or high-risk juveniles.

These facilities may include juveniles who have been

adjudicated of either misdemeanor or felony offenses. State

correctional facilities included high security facilities

intended for high-risk juveniles with felony adjudications

and represent the state’s youth prison system (Texas

Juvenile Justice Department 2012).

Control Variables

Control variables included age at first referral, age at target

referral, ethnicity, severity of offense history and prior

probation referrals. Ethnicity was reflected by dummy

coding two variables—Hispanic (1) or White (0) and Black

(1) or White (0). Both age at first referral and age at target

referral were also included in the analyses. Almost half of

the juveniles in the sample had a prior record with the

partnering juvenile probation departments (n = 16,077).

Severity of offense history was categorized using the same

procedures as the target referral offense. The seriousness of

offense history ranged from 0, indicating no prior record, to

8, indicating prior referral for a capital murder. Prior pro-

bation referrals were defined as the number of prior dis-

positions to probation supervision.

Procedures

Differences in variables of interest and control variables by

gender were examined through independent t-tests and Chi

square analyses. Multivariate analyses examined level of

placement by gender and mental health need. First, the

analyses sought to establish the general influence of mental

health need and gender on level of placement. The exam-

ination of the general influence of the predictor variables

on level of placement for all facility types utilized an OLS

regression model with gender (0 = male, 1 = female)

included in the equation, along with other predictor

1828 J Youth Adolescence (2013) 42:1824–1836

123

variables, regressed on facility composite (0 = no place-

ment, 1 = detention, 2 = non-secure, 3 = secure, 4 =

corrections). The OLS regression model is presented for

ease of interpretation. Results from ordinal logistic

regression and probit models confirmed the significance,

direction, and relative magnitude of coefficients presented

in the OLS model.

Additional analyses examined the influence of the pre-

dictor variables by specific facility type and gender at both

the pre-adjudicatory and post-adjudicatory phases, requir-

ing separate female and male models. A dichotomous

outcome variable was created for the pre-adjudicatory

detention decision and coded as either not detained (0) or

detained (1). Binary logistic regression was used to model

the detention decision. Multinomial logistic regression was

used to model post-adjudicatory placement, which includes

separate panels to describe the influence of predictors on

placement in non-secure facilities, county operated secure

facilities, and state correctional facilities. Alternatives to

placement served as the reference category for the multi-

nomial comparisons. Detention was included as a predictor

variable in the post-adjudicatory placement model. Status

offense had to be removed from the post-adjudicatory

placement model. Limited cell size prevented model con-

vergence when status offense was included. Additional

analysis was conducted to test for differences between

regression coefficients of the gendered models. The for-

mula suggested by Brame et al. (1998) was used to test for

differences between the model coefficients:

Z ¼ b1 � b2 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

SEb21 þ SEb22 p

Results

Table 1 presents outcomes, offense seriousness, mental

health need, and control variables by gender. The mean

facility composites show boys are placed deeper in the

system overall. The binary outcomes show males are more

likely to be placed in each type of confinement, with the

exception of non-secure placement, where girls are twice as

likely to be placed. Part of the reason is apparent in the

Table 1 Level of placement, offense seriousness, mental

health need, and control

variables by gender

* p \ .05; ** p \ .01; *** p \ .001

Female

Mean (SD)

Male

Mean (SD)

Test of difference

Level of placement

Facility composite 0.496 (0.748) 1.024 (1.212) t = -49.130***

Detention 0.373 0.531 v2 = 725.656***

Non-secure placement 0.068 0.033 v2 = 213.268***

County secure placement 0.013 0.142 v2 = 1293.434***

State correctional commitment 0.008 0.048 v2 = 332.220***

Offense seriousness

Offense composite 2.091 (1.956) 2.789 (1.641) t = -48.709***

Status offense (Boot1) 0.144 0.068 v2 = 512.619***

VOP (Boot2) 0.089 0.143 v2 = 192.406***

Mental health need

Warnings (total #) 0.284 (0.697) 0.232 (0.688) t = 6.400***

Drug 0.023 0.020 v2 = 4.854*

Angry 0.109 0.068 v2 = 166.115***

Depressed 0.104 0.047 v2 = 385.650***

Somatic 0.065 0.036 v2 = 143.961***

Suicide 0.141 0.059 v2 = 628.816***

Thought 0.164 0.113 v2 = 94.904***

Trauma score 1.1300 (1.470) 1.120 (1.232) t = 11.182***

Control variables

Race–Black 0.363 0.373 v2 = 3.386

Ethnicity–Hispanic 0.390 0.413 v2 = 15.993***

Age at referral 14.900 (1.275) 14.956 (1.387) t = -3.581***

Age of onset 14.383 (1.399) 14.140 (1.560) t = 14.225***

Severity of offense history 0.894 (1.508) 1.691 (2.163) t = -39.075***

Prior probated dispositions 0.208 (0.560) 0.455 (0.830) t = -32.108***

Prior facility composite 0.205 (0.536) 0.521 (0.985) t = -38.208***

J Youth Adolescence (2013) 42:1824–1836 1829

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level of offense, which shows that girls, on average,

commit less serious offenses and are more than twice as

likely as boys to be referred for status offenses. Girls also

had less serious prior records, as evidenced by the control

variables. They also tended to be slightly younger at

referral and older at age of onset than boys.

Consistent with existing literature on prevalence of

mental health disorders and gender, girls had a higher level

of mental health need as evidenced by the total number of

warnings and a greater percentage of girls with need across

all subscales. Trauma scores were also higher for girls than

boys. Girls also tended to be clustered at the higher end of

the scale, with 10.9 % of girls reporting four or more

trauma indicators compared to only 5.2 % of the boys (not

tabled). The percentage of females reporting five or more

trauma indicators was over four times higher (4.1 %) than

their male counterparts (0.9 %).

Analysis of the predictor variables regressed on the level

of placement composite, reported in Table 2, indicated that

all predictor variables were statistically significant. The

Betas from the OLS regression revealed the strongest

predictors of increased severity of out-of-home placement

were higher scores on the MAYSI-2 Trauma scale, offense

severity, age at first referral, and commission of a probation

violation. Gender was negatively related to level of

placement, indicating that being female decreased a juve-

nile’s overall likelihood of being placed at a higher level of

placement. Prior offense and probation history were also

related to increased levels of out-of-home placement, as

was minority status and overall mental health need, while

the commission of a status offense and lower age at target

referral were related to lower levels of placement.

Detention Decision

The logistic regression analysis presented in Table 3 indi-

cates gender differences among predictor variables when

regressed on the variable reflecting whether or not a

juvenile was detained. As the age at target referral for a

male juvenile offenders increased, the odds of being

detained increased. However, for girls, as their age at target

referral increased, their odds of being detained decreased.

Commission of status offenses was negatively related to a

detention decision for both genders, although boys were

slightly less likely to be detained than girls for status

Table 2 Predictor variables regressed on level of placement composite

B SE Beta

Severity of offense .195 .003 .269***

Gender–female -.152 .010 -.062***

Status offense (Boot1) -.229 .017 -.059***

VOP (Boot2) .709 .018 .211***

Mental health need .043 .007 .067***

Trauma score .039 .004 .275***

Race–Black .181 .012 .078***

Ethnicity–Hispanic .145 .012 .064***

Age at target referral -.056 .006 -.068***

Age at first referral .049 .005 .248***

Prior offense history .137 .004 .046***

Prior probation history .401 .009 .026***

Constant -.087 .056

Model R 2

= .425***

* p \ .05; ** p \ .01; *** p \ .001

Table 3 Predictor variables regressed on detention decision by gender

Female Male Test of difference

e b

(seb) e b

(seb)

Severity of offense 1.975*** (.022) 1.553*** (.010) 10.000***

Status offense (Boot1) 0.389*** (.082) 0.286*** (.073) 2.793**

VOP (Boot2) 6.177*** (.112) 3.967*** (.056) 3.544***

Mental health need 1.005 (.035) 1.163*** (.024) -3.476***

Trauma score 1.257*** (.017) 1.063*** (.013) 8.000***

Race–Black 2.004*** (.063) 2.052*** (.040) -0.320

Ethnicity–Hispanic 1.557*** (.064) 1.822*** (.039) -2.090*

Age at target referral 0.935* (.034) 1.065*** (.018) -3.421***

Age of first referral 1.009 (.032) 0.954** (.016) 1.528

Prior offense history 1.261*** (.025) 1.171*** (.011) 2.741**

Prior probation referrals 1.159* (.065) 1.083** (.027) 0.971

Constant 0.103*** (.296) 0.088*** (.172) 0.480

Model Pseudo R 2

.243*** .203***

* p \ .05; ** p \ .01; *** p \ .001

1830 J Youth Adolescence (2013) 42:1824–1836

123

offenses. The exponentiated logistic regression coefficients

indicated for a violation of probation, a girl’s chance of

being detained almost doubled (e b

= 6.177) that of a boy’s

(e b

= 3.967). Current offense severity and prior offense

history increased a girl’s odds of being detained slightly

more than a boy’s. Scoring in the warning cutoffs on the

MAYSI-2 was not found to be statistically significant in

predicting detention for girls. For boys, however, higher

mental health need increased the odds of being detained.

Elevations on the traumatic experience scale increased the

likelihood of detention more for girls than for boys.

Non-secure Placement

Analysis of the predictor variables on non-secure place-

ment, presented in the first panel of Table 4, indicates age

Table 4 Multinomial logistic regression model predicting post-adjudication placement by gender

Female Male Test of difference

e b

(seb) e b

(seb)

Non-secure placement

Severity of offense 1.118** (.037) 1.446*** (.028) -5.539***

VOP (Boot2) 3.167*** (.136) 7.990*** (.122) -5.003***

Mental health need 1.144** (.051) 1.097 (.055) 0.547

Trauma score 1.193*** (.030) 1.033 (.035) 3.130**

Race–Black 0.972 (.121) 0.865 (.110) 0.716

Ethnicity–Hispanic 0.806 (.127) 0.926 (.109) -0.832

Age at target referral 0.918 (.052) 0.837*** (.038) 1.444

Age of first referral 0.966 (.048) 0.995 (.034) -0.493

Prior offense history 1.243*** (.032) 1.386*** (.022) -2.809**

Prior probation referrals 1.595*** (.078) 1.103 (.069) 3.548***

Detention 19.408*** (.173) 5.665*** (.124) 5.789***

County operated secure placement

Offense composite 1.601*** (.087) 1.178*** (.015) 3.447***

VOP (Boot2) 17.108*** (.311) 2.439*** (.064) 6.135***

Warnings 0.585*** (.184) 1.092** (.033) -3.342***

Trauma score 1.286*** (.057) 1.026 (.020) 3.742***

Race–Black 1.549 (.300) 1.009 (.064) 1.397

Ethnicity–Hispanic 1.453 (.304) 1.044 (.064) 1.064

Age at referral 1.040 (.096) 0.823*** (.025) 2.354**

Age of onset 0.809* (.086) 1.193*** (.021) -4.384***

Prior offense history 1.276*** (.059) 1.253*** (.013) 0.315

Prior probated dispositions 1.554** (.133) 2.669*** (.033) -3.949***

Detention 12.988*** (.432) 5.505*** (.059) 1.986*

State correctional commitment

Offense composite 2.174*** (.108) 2.136*** (.030) 0.161

VOP (Boot2) 11.990*** (.419) 12.452*** (.124) -0.087

Warnings 0.962 (.138) 1.267*** (.046) -1.897

Trauma score 1.399*** (.074) 1.110** (.031) 2.875**

Race–Black 0.868 (.351) 1.216 (.111) -0.918

Ethnicity–Hispanic 1.056 (.346) 1.222 (.111) -0.402

Age at referral 1.120 (.126) 0.934 (.037) 1.382

Age of onset 0.746** (.105) 1.060 (.029) -3.229***

Prior offense history 1.696*** (.072) 1.664*** (.021) 0.253

Prior probation referrals 2.397*** (.134) 2.936*** (.043) -1.440

Detention 4.337*** (.393) 2.097*** (.089) 1.801

Model Pseudo R 2

.435*** .456***

* p \ .05; ** p \ .01; *** p \ .001

J Youth Adolescence (2013) 42:1824–1836 1831

123

at target referral was negatively related to confinement for

males. Greater offense severity and offense history

increased the likelihood of a non-secure placement for both

genders, although these variables were less important for

girls than boys. A violation of probation increased the odds

of non-secure placement for boys (e b

= 7.990) at about

2� times that of girls (eb = 3.167). The only legal variable that increased a girl’s odds of incarceration in a non-secure

facility relative to a boy’s was prior probation history.

Neither mental health need nor trauma score was found to

be a statistically significant predictor of placement in a

non-secure facility for boys. For girls, however, elevations

on either mental health need or trauma increased the odds

of placement in a non-secure facility. Detention, an out-

come found to be strongly related to trauma and VOP for

girls, when inserted into the current model was shown to

influence non-secure confinement for both genders. How-

ever, the influence of detention was uneven in the multi-

nomial model, increasing the odds of a girl’s confinement

by 3� times that of a boy’s. With an odds multiplier of nearly 20, detention was by far the strongest predictor of a

girl’s non-secure confinement.

County Operated Secure Placement

The second panel of Table 4 presents results from the

multinomial logistic regression analysis of the predictor

variables on secure out-of-home placement by gender.

Current offense severity and prior offense history increased

the odds of secure placement for both genders, but current

offense increased the likelihood of placement by a greater

margin for girls than boys. The analysis also revealed age

at first referral was a negative predictor of secure place-

ment for girls, yet for boys it had a positive relationship.

While a violation of probation (VOP) increased the odds of

secure placement for boys (e b

= 2.439), girls with a VOP

experienced about 7 times greater risk of secure out-of-

home placement than boys (e b

= 17.108). Overall mental

health need was a statistically significant predictor of

secure placement for boys; yet for girls, higher mental

health need resulted in decreased odds of secure placement.

However, elevated trauma scores increased the risk of

placement in a county-operated secure post-adjudication

facility for girls. Detention was again more strongly related

to the placement decision for girls than for boys.

State Correctional Commitment

The third panel of Table 4 presents the influence of the

predictor variables on state correctional commitment. The

models indicate that severity of the offense and prior

offense history were highly predictive of state commitment

for both genders. Severity of offense and offense history

resulted in virtually the same odds of commitment by

gender, as did a current violation of probation and prior

probation. Age at first referral was not significant for boys.

However, for girls it was negatively related, indicating

earlier starts to offending by girls were more likely to

evoke the most severe sanction available. Both mental

health need and trauma scores were significant for boys,

with only the trauma scale being significant for girls. Girls

had a higher risk of commitment based on reports of

trauma in comparison to boys. While detention was a

significant predictor of state commitment for both genders,

it appears to be twice as influential for girls. It should be

noted that although not statistically significant in a two-

tailed Z-test, the coefficients would have been significant if

a one-tailed test had been employed. Because the pattern

matches the results from the other types of confinement,

the relative size of the test coefficients suggests the dif-

ferences between genders are reliable.

Discussion

The overarching purpose of this study was to evaluate the

influence of gender and mental health need on out-of-home

placement for youth involved with the juvenile justice

system. Previous research suggested a relationship between

female delinquency and mental health need. It initially was

hypothesized that female juvenile offenders were ordered

to out-of-home placement at a higher rate for lesser

offenses than males with similar mental health needs.

Contrary to this hypothesis, the combined OLS model

regressed on the level of placement variable indicated that,

overall, being male increased a juvenile’s likelihood of

being placed in more restrictive placements. Interestingly,

mental health need was a significant, but relatively small,

predictor of placement severity, while trauma indicators,

age at first referral and violation of probation were the most

significant predictors.

Although results supported the hypothesis that mental

health need had an influence on out-of-home placement

and placement severity, it was clear a history of traumatic

experiences was a more influential factor in placement

decisions regardless of gender. However, when the analysis

included the influence of status offenses and violations of

probation, the influence of past traumatic experiences

appeared to be especially influential for girls. Other

research studies, as well as findings from this study, sug-

gest several possible explanations for this relationship.

Research has shown adolescents and adults who have

experienced childhood trauma are at an increased risk for a

variety of mental health problems, as well as many

behaviors leading to familial and legal difficulties, such as

substance abuse, promiscuity, teen pregnancy, running

1832 J Youth Adolescence (2013) 42:1824–1836

123

away, and aggression (Felitti et al. 1998). This relationship

has been shown to be dose dependent, meaning the greater

the cumulative number of traumatic experiences, the

greater the risk, which mirrors the dose response found in

the current study.

Research has shown offenders with mental health dis-

orders are much less successful under supervision in the

community than those without mental health disorders

(Monahan et al. 2005; Skeem et al. 2006; Solomon et al.

2002). This seems to be particularly true for girls, who

have been found to have higher rates of mental health

needs than their male counterparts and respond less posi-

tively to involvement in the system (Teplin et al. 2002;

Wasserman et al. 2005). The findings of this study extend

this previous research, suggesting that through the use of

violation of probation, girls and youth of both genders with

documented mental health needs are funneled deeper into

both county and state operated out-of-home placements

than boys and those without a mental health needs. These

effects also appear to be cumulative, with pre-adjudicatory

decisions influencing post-adjudicatory outcomes. Factors

influencing detention decision for girls, expressly traumatic

experiences and bootstrapping, continue to indirectly

influence post-adjudicatory decisions.

The trend identified for trauma experiences to increase

the risk for youth to be placed in more restrictive settings

may be counter-productive. Some researchers postulate

traumatic stress symptoms may be worsened as a result of

being involved in the juvenile justice system. Youth being

placed out of the home, especially in more secure settings,

may be further traumatized by separation from familiar

adults, exposure to aggressive or threatening peers, and by

feelings of threat and lack of safety. The characteristics of

the environment, including traditional confrontational

methods of maintaining order, may backfire for girls with

traumatic stress symptoms (Griffin 2002; Hennessey et al.

2004). Seclusion and restraints have been cited as an

example of a practice in institutions that can be especially

re-traumatizing (Huckshorn 2006). Prescott (1997) indi-

cated the cycle of staff interventions, especially during

times of crisis, led to increased self-injury in response to

the use of physical and mechanical restraints. Due to their

high rates of traumatic stress and the possibility of re-

traumatization through incarceration, girls may be espe-

cially susceptible to worsened traumatic stress sympto-

mology (Hennessey et al. 2004).

Although this study is an important step in better

understanding the influence of gender and mental health

need on juvenile justice placement decisions, several lim-

itations to the methodology should be noted. One important

limitation to note is the study was limited to three urban

juvenile probation departments in one state. Additional

studies should be undertaken to replicate the findings in

other states and jurisdictions to determine its generaliz-

ability. Similarly, differences between jurisdictions were

not identified in the analyses conducted and should be

explored in future research. In addition, the study was

limited to the variables available within the county

administrative systems. This did not allow for the inclusion

of other measures of mental health need or trauma that may

have been more sensitive than a screening measure. It also

did not allow for the inclusion of extralegal variables that

may influence a court’s decision to put a juvenile in out-of-

home placement, such as home environment, community-

based resources, or other process-oriented measures.

Although the study design had some limitations, there

are also many strengths that result in this study contributing

to the literature. One strength of the study is the relatively

large sample size and the longitudinal nature of the data

collected. The data set analyzed included demographic as

well as lifetime arrest, disposition and mental health data

collected on over 30,000 individual youth who were

referred to the participating juvenile probation departments

during the 2 year sample period. Combined, the partici-

pating juvenile probation departments account for over

51 % of the state’s total juvenile population each year.

Another strength of this study was the use of multiple

probation departments. All three departments resided in

urban settings, but differed in geographic location and

ethnic composition. One department was located in north

Texas with a primary minority population of African

American youth. Another was located in south Texas with

a primary minority population of Hispanic youth. The final

department was located in central Texas with comparable

representation of African American and Hispanic youth. In

addition, well-delineated variable definitions and the

inclusion of many relevant predictor variables further

strengthened the study. This was evidenced by the rela-

tively large amount of variance predicted in the tested

models.

Conclusion

The above findings suggest the importance of trauma

informed care, both to better address the impact of trauma

on criminogenic risk and improve the success rate of youth

with mental health needs on supervision. One important step

in the last decade is a focus on trauma-informed systems,

including juvenile justice systems. The National Child

Traumatic Stress Network defines a trauma-informed child

and adolescent service system as one in which all programs

and agencies ‘‘infuse and sustain trauma awareness,

knowledge, and skills into their organizational cultures,

practices, and policies’’ (National Child Traumatic Stress

Network 2012). In a trauma informed juvenile justice

J Youth Adolescence (2013) 42:1824–1836 1833

123

system, judges and probation officers are knowledgeable

about the impact of trauma and respond to youth with this

context in mind. All youth are screened routinely for

exposure to trauma and evidence-based trauma treatments

are available. Behaviors that may be attempts to cope with

current or past traumatic experiences, such as substance

abuse, interpersonal aggression, risky sexual behavior, self-

injury, gang affiliation, and running away, are recognized as

a symptom of mental health difficulties and addressed with a

trauma lens, rather than strictly a legal one.

Although, this study replicated the findings of several

other prevalence studies that youth in out-of-home juvenile

justice placements have higher rates of mental health need

than those remaining in the community, it also highlighted

the need for juvenile justice systems to enhance their

awareness of the role of trauma in juvenile delinquency and

transform the system to address and support youth who

have experienced significant trauma in their childhood.

Additional research is needed to determine the effective-

ness of trauma interventions for youth in the various

components of the juvenile justice system (e.g., prevention

programs, community-based supervision, detention, non-

secure and secure facilities, parole). For some youth, their

trauma history coupled with their involvement in the

juvenile justice system can lead to the development of post-

traumatic stress disorder (PTSD), depressive disorders, and

anxiety disorders. Without effective treatment and/or

involvement in a trauma informed system, these disorders

are likely to continue to cause impairment and may result

in negative long-term outcomes. The reality is juvenile

justice systems have public safety, and not mental health

treatment, as their primary goal and significant organiza-

tional change will be needed to embrace the goal of

becoming a trauma-informed system.

Acknowledgments The authors would like to acknowledge the local juvenile probation departments for their support and collabo-

ration during the data collection and study design efforts conducted

for this study.

Author contributions Each author contributed to the development of the study and the resulting article submission. EE was the primary

researcher and conceived the study and performed the initial analysis

and the initial implications of the study. JJ assisted with the initial

analysis and conducted additional analysis to examine the exploratory

hypothesis. ML contributed to the interpretation of the analysis and

the impacts of trauma and trauma informed care. All three authors

helped to write the article and approved the manuscript’s content.

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Author Biographies

Erin M. Espinosa is a research associate in the Texas Institute for Excellence in Mental Health at the Center for Social Work Research

at the University of Texas in Austin. She received her doctorate in

juvenile justice from Prairie View A&M University. Her primary

areas of interest and research are mental health and juvenile justice,

trauma based recovery and special populations, juvenile competency,

developmental perspectives for juvenile justice, and implementation

of Evidence Based Practices (EBPs) in criminal justice.

Jon R. Sorensen is a Professor of Criminal Justice at East Carolina University. He received his doctorate in criminal justice from Sam

Houston State University. His major research interests include prison

violence, capital punishment, and racial disparity in the justice

system. He has published articles on prison violence, capital

J Youth Adolescence (2013) 42:1824–1836 1835

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punishment, and racial disparity in the criminal justice system. He is

coauthor of Lethal Injection: Capital Punishment in Texas During the

Modern Era (2006, University of Texas Press).

Molly A Lopez is the Director of the Texas Institute for Excellence in Mental Health, a licensed clinical psychologist and a Research

Associate Professor at the University of Texas at Austin, School of

Social Work. She received her doctorate in clinical psychology

from Texas A&M University. Her research interests include mental

health services, child and adolescent service systems, the imple-

mentation of evidence-based practices, and cognitive behavioral

therapies.

1836 J Youth Adolescence (2013) 42:1824–1836

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