Degrees of Difference among Minority Female Juvenile Offenders’Psychological Functioning, Risk Behavior Engagement, and HealthStatus: A Latent Profile Investigation

Barbara J. GuthrieShauna M. CooperCharity BrownIsha Metzger

Journal of Health Care for the Poor and Underserved, Volume 23, Number1, February 2012, pp. 204-225 (Article)

Published by The Johns Hopkins University PressDOI: 10.1353/hpu.2012.0016

For additional information about this article

Access Provided by your local institution at 02/19/13 12:31PM GMT

http://muse.jhu.edu/journals/hpu/summary/v023/23.1.guthrie.html

Part 1: Original PaPer

© Meharry Medical College Journal of Health Care for the Poor and Underserved 23 (2012): 204–225.

Degrees of Difference among Minority Female Juvenile Offenders’ Psychological Functioning, risk Behavior engagement, and Health Status:

a latent Profile investigation

Barbara J. GuthrieShauna M. Cooper

Charity BrownIsha Metzger

Abstract: Given the increase in the number of female youth who come in contact with the juvenile justice system, particularly those from ethnic minority backgrounds, concerns have been raised about the health status of this population. Using a latent profile analysis, we identified health profiles using indicators of psychological well-being, health risk behav-iors, and health status. Participants included 153 minority adolescent females (M15.13, SD1.70) who were currently in a juvenile diversion program. Results indicated that a three-class solution fit the data optimally. Profiles included girls with low to moderate health risks (n35; 22.9%), higher mental health symptoms (n68; 44.4%), and a combi-nation of multiple health risks (n50; 32.7%). Additionally, demographic, contextual and offense-related variation existed across health profiles. Treatment and policy implications are discussed.

Key words: Juvenile offender, female, minority, adolescent, social context.

Within the last 25 years, there has been a steady increase in number of girls who have had contact with the juvenile justice system. Specifically, arrest rates for

males have decreased by 16%, while female arrest rates have increased by 66%. 1 Much like the general population of juvenile offenders,2 a disproportionately high number of female juvenile offenders are from ethnic minority backgrounds,3 and researchers have indicated that African American and Hispanic youth are more likely than their non-Hispanic White counterparts to receive harsher sentences.3,4 Research specific to female populations has found that non-White females, particularly African American and Hispanic females, have an increased likelihood of being arrested and rearrested for offenses and for receiving harsher sentences.5,6 Additionally, the literature suggests that taking into account prior offenses and mental health symptoms, non-White offenders

The lead auThor (BJG) is affiliated with the School of Nursing at Yale University, 100 Church Street South, P.O. Box 9740, New Haven, CT 06536; barbara.guthrie@yale.edu. The oTher auThors (SMC, CB, IM) are affiliated with the Department of Psychology, University of South Carolina.

205Guthrie, Cooper, Brown, and Metzger

are less likely to receive mental health treatment as an alternative to confinement in a juvenile facility7 or to receive adequate mental health care during confinement.8 Taken together, these studies indicate serious sentencing and health inequities among non-White female youth who come in contact with the juvenile justice system.

Although there is some consistency in risk factors for adolescent boys and girls, a number of distinct social contextual influences exist related to non-White adolescent girls’ contact with the juvenile justice system.9,10,11 In particular, studies have found that non-White adolescent female offenders have an increased likelihood of previous trauma (e.g., sexual abuse), problematic self-perceptions (e.g., too high or too low), and more conflictual relationships with parents relative to their non-Hispanic White counterparts.12 Multiple studies also have indicated that many non-White female juvenile offenders have mental health problems that have indirect and direct consequences for them.13,14 Additionally, there is some indication that this same population of females participate in a range of risk-related health behaviors, which in turn increases their likelihood of coming in contact with the juvenile justice system. Such contact has been associated with the exacerbation of existing physical and mental health related issues as a result of lack of or substandard correctional health care.15

However, few documented studies exist that take a comprehensive, contextually-based approach to understanding the experiences of female juvenile offenders. Furthermore, there is a paucity of research that examines the larger social context of female juvenile offenders from ethnic minority groups. Given that interrelations among the wide range of health-related factors appear to be diverse and complex, subgroups of female juvenile offenders who demonstrate distinct patterns or profiles of broader contextual factors are likely present. The identification of subgroups or profiles may be an important unit of analysis. This approach requires both a conceptual and an analytical shift from more commonly used, variable-oriented frameworks in which information related to the individual often gets lost (i.e., submerged in group means).16,17 In contrast, profile-oriented approaches focus on the ways in which multiple variables are configured within individuals and result in the opportunity to identify meaningful patterns.18 The current investigation uses a profile-oriented approach to identify health profiles among a sample of minority (non-White) female juvenile offenders. Specifically, this study classifies profiles using indicators of general health status, engagement in health risk behaviors (e.g., substance use; sexual risk behaviors), and psychological function-ing. Additionally, this study examines whether the identified health profiles differ with respect to contextual factors and explores variation in self-reported offenses among identified health profiles.

Mental health. Previous studies have focused on the mental health status of youth in contact with the juvenile justice system.19–21 In particular, research has demonstrated that the rate of mental disorders is substantially higher among youth involved in the justice system than among youth in the general population.22 Further, studies have demonstrated that girls within the juvenile justice system have greater mental health needs than others.7,19,23–25 More specifically, investigations have indicated higher preva-lence rates of mental health disorders, such as depression and anxiety among them than among girls who are not involved in the justice system.13,14,26,27 Although these patterns mirror those in the general population, there is some indication that mental

206 Minority female juvenile offenders and health

health issues among girls involved with the juvenile justice system are considerably more complex. In fact, studies have suggested that mental health status is interrelated and interconnected with a range of factors, including physical well-being, engagement in risk behaviors, and additional social contextual influences.5,9,28

Still, despite the disproportionate number of ethnic minority girls who have contact with the juvenile justice system, there is a dearth of research exploring intra-group variation in mental health among this subpopulation. Research suggests that, although the greatest prevalence of mental health diagnoses is among non-Hispanic Whites,26 minority youth involved in the juvenile justice system often have undiagnosed psycho-logical symptoms.29 Additionally, minority juvenile offenders with elevated symptom-atology are less likely than non-Hispanic White juvenile offenders to be referred for mental health services.7 Thus, the presence of undiagnosed mental health symptoms in conjunction with current physical well-being and engagement in health risk behaviors (e.g., substance use, sexual risk behaviors) is an important under-explored topic.

Substance use. Studies indicate higher substance abuse prevalence rates among female juvenile offenders than their females counterparts in the general population.30–34 For instance, Fejes-Mendoza and colleagues found that approximately 50% of female juvenile offenders reported previous substance use.30 More current research by Katoaka and colleagues found that more than 80% of female juvenile offenders reported past or current substance abuse.31 In these studies, many female youth reported being under the influence of a substance (e.g., alcohol, marijuana, etc.) while committing an offense.33 Although substance use has been associated with engagement in criminal activity for both males and females, it has been suggested that female offenders are more likely to report more serious substance use, including heroin and cocaine use, while male offenders are more likely to report alcohol use.33,35 Additionally, substance use has been related to increased likelihood of recidivism among juvenile offenders.36 Attention to the past and current substance use patterns of female juvenile offenders may lend additional insight into circumstances leading up to their entry into the juvenile justice system.

Although connections between serious substance use and contact with the juvenile justice system are relatively complex, research related to substance use, particularly among this subpopulation, indicates that substance use often co-occurs with mental health disorders (e.g., depression).32,37–40 Therefore, researchers have suggested that an accurate depiction of female offenders should include attention to their psychological functioning and substance use.33 Several studies suggest that female juvenile offend-ers’ health would be better understood by exploring health within the context of their social experiences.9,10 Using latent profile methodology, Cruise and colleagues found that many female juvenile offenders with mental health issues also experienced prior physical abuse,24 suggesting that substance use among female juvenile offenders may be a self-medicating response to ongoing or prior trauma.20,41,42 Other studies have found similar associations.34,38,39 Optimal treatment of this population should address the co-occurring nature of substance use and mental health disorders as well as prior or ongoing traumatic and stressful events.

Physical health. In addition to mental health and substance use-related issues, minority female juvenile offenders experience disproportionate physical health issues. According to the 2010 census, 44% of the more than 39 million American youth

207Guthrie, Cooper, Brown, and Metzger

between the ages of 10 and 18 were youth of color.42 Compared with their non-Hispanic White counterparts, this growing population of youth disproportionately experience poor health resulting from limited or inconsistent access to health care. Additionally, several studies indicate that these youth have a greater likelihood of residing in under-resourced neighborhoods and communities, which has been associated with increased risk for engaging in behaviors that enhance the likelihood of coming into contact with the juvenile justice system.43–45 These youth are also more likely to enter the juvenile justice system in poorer overall health.46

Because adolescent girls of color are one of the growing subpopulations of youth who are overrepresented within the juvenile justice system, their short-term and long-term health is likely to become increasingly compromised. Studies suggest that female offend-ers may be at an increased risk for health-related problems, with studies indicating that female juvenile offenders have a lower overall health rating.10,47,48 The aforementioned information, coupled with the fact that minority adolescent females are more likely than non-minority adolescent females to become involved with the juvenile justice system, strongly point to a need to better address their health care needs.

Sexual health. Some of the most significant health concerns for minority female offenders relate to sexual health. Female offenders have an increased likelihood of being victims of sexual trauma,11,49 and are disproportionately afflicted by a range of sexual health issues, including sexually transmitted infections (STIs), such as Chlamydia and HIV/AIDS and more general reproductive health issues.49 Voisin and colleagues indi-cated that more than 83% of detained non-White adolescent females reported having one or more sexual risk behaviors (i.e., behaviors that may compromise sexual health), including greater number of sexual partners and infrequent or non-use of contracep-tives.50 Additional studies have demonstrated that, although adolescent females in the general population have increased prevalence rates of STIs, females in contact with the juvenile justice system have increased STI rates.51 Among this population, treatment issues pertaining to sexual health are exacerbated by mental health and substance use problems.50

Socio-contextual correlates of health risk behaviors. Scholars have suggested that social experiences are an important consideration when addressing the health needs of female juvenile offenders.9,52,53 In particular, studies demonstrated that family factors were associated with health-related and delinquent behaviors,12,29 and familial relation-ships were identified as correlates of offenses and health status.9,29,54–57 Additionally, the literature has shown that prior sexual abuse or trauma is more prevalent among female juvenile offenders than among their male counterparts.12,58 Further, there is some indication that prior trauma compromises physical and mental health and serves as an important etiological factor in involvement with the juvenile justice system involve-ment.11,41,59 In addition, neighborhood resources, including perceived social support, have been associated with a range of adolescent health outcomes and associated risk behaviors (e.g., substance use, delinquency, and reduced psychological functioning).5,56,60

Furthermore, investigating self-esteem might provide greater insight into the socially-embedded health needs of female juvenile offenders.9 There is evidence that lower self-esteem is associated with greater participation in risk related behaviors, such as substance use and sex risk behaviors and poorer mental health outcomes among

208 Minority female juvenile offenders and health

minority adolescent females.61 With respect to minority female juvenile offenders, existing studies have been equivocal. These investigations have indicated that lower56,62 and higher self-esteem63 are correlates of juvenile delinquency. The inconclusive nature of this research may suggest important demographic and contextual moderators.64 In spite of these mixed findings, however, self-esteem has been suggested as an important influential factor in treatment of all female juvenile offenders.65

Variation in types of offenses also has been explored in relation to the health needs of female juvenile offenders. In particular, those with a history of substance use and/or mental health tend to have higher recidivism rates,25 and minority youth with mental health or substance use issues are more likely to be confined to the juvenile justice sys-tem than to be referred for mental health treatment.66 Given that fewer minority female offenders are referred for mental health treatment,7 linkages among populations of color are unclear. Studies have asserted the importance of contextual factors in addressing the specific health needs of minority female juvenile offenders.9,53,67 However, to better tailor intervention, prevention, and treatment to meet these needs, there still remains a need to examine how these contextual factors are associated with comprehensive health profiles among this population.

goals of the present study. Although researchers have generated profiles of incarcer-ated female youth across several behavioral and health indicators,11,37,67 recent studies have utilized latent profile methodologies to identify typologies of female juvenile offenders.24,68,69 However, despite the overrepresentation of girls of color in the juvenile justice system, relatively few studies have taken a comprehensive health approach in this population.11,67 This study identifies health profiles among minority girls who were in contact with the juvenile justice system using a profile-oriented approach (e.g., identi-fication of sub-groups),18,34 with special attention to psychological functioning, health risk behaviors, and general health status. Additionally, we examine whether contextual factors (e.g., quality of familial relationships; perceived neighborhood support; self-esteem) varied by health profile. Finally, we investigate variation in self-reported offenses.

Methods

Participants. This study was a part of a larger, community-based investigation explor-ing contextual influences on adolescent girls’ health behaviors.67 A self-selected and non-random network sampling technique was used to collect cross-sectional data on adolescent girls between the ages of 12 and 18 who were currently in a juvenile diversion program (e.g., a sentencing alternative to formal court proceedings for offenders). Data were collected from two geographic locations: a large, urban city in the Southeastern region of the United States and a large, urban city in the Mid-Atlantic region of the United States. For the purposes of this secondary analysis, European American/non-Hispanic White girls were excluded from analyses. Participants more than 17 years old were also excluded from final analyses, resulting in a sample of 153 girls. Approximately 77% of the sample was African American, 13% was Latina/Hispanic, 10% was Multi-racial/other, 1.3% was Native American, and 1.3% was Asian American. The mean age was 15.13 (SD1.70), with ages ranging from 12 to 17 years. Additionally, 76% of the sample reported that their household received public financial assistance (e.g., Temporary

209Guthrie, Cooper, Brown, and Metzger

Assistance for Needy Families-TANF), and 68% reported residing in a single-parent household. Demographic characteristics for the full sample are provided in Table 1.

Procedure. Before survey administration, the questionnaire was piloted on a sample of 24 adolescent girls who mirrored the proposed target population in order to determine gender, ethnic, and age appropriateness. The questionnaire was refined on the basis

table 1. DeMOgraPHiC, COnteXtUal anD SelF-rePOrteD OFFenSeS FreQUenCY (%) anD MeanS

Full low/Moderate Compound High Mental Sample Health risk Health risk Health risk (n153) (n35) (n50) (n68)

Demographic Variables Aged (years) 12–13 32 (21.3) 4 (11.4) 6 (12.0) 22 (32.4) 14–15 54 (36.0) 8 (22.8) 24 (48.0) 24 (35.3) 16–17 64 (42.7) 23 (65.7) 20 (40.0) 22 (32.4) Mean Age (SD) 15.13 (1.70) 15.15 (0.23)b 15.93 (0.21)a,b 14.66 (0.22)a

Ethnicityd

African American 117 (76.5) 26 (74.3) 29 (58.0) 62 (91.2) Hispanic/Latino 20 (13.1) 4 (11.4) 13 (26.0) 3 (4.4) Asian/Pacific-Islander 2 (1.3) 1 (2.9) 1 (2.0) 0 (0) Multi-racial/Other 14 (9.1) 4 (11.4) 7 (14.0) 3 (4.4) Received Public Assistanced Yes 113 (74.0) 25 (71.4) 34 (68.0) 54 (79.4) No 40 (26.0) 10 (28.6) 16 (32.0) 14 (20.6)Contextual Variablese

Relationship with Mother 3.45 (0.79) 3.32 (0.11)b 3.16 (0.14)a 3.67 (0.83)a,b

Relationship with Father 3.28 (0.84) 3.31 (0.17) 3.14 (0.15) 3.34 (0.09) Sexual Trauma 0.24 (0.70) 0.31 (0.79) 0.15 (0.36) 0.27 (0.81) Self-Esteem 3.43 (0.97) 2.64 (1.02)a,c 3.18 (0.62)b,c 3.94 (0.75)a,b

Neighborhood Support 3.11 (0.68) 2.97 (0.14)b 2.78 (0.09)a 3.31 (0.07)a.b

Self-Reported Offensese

Theft 1.97 (2.62) 3.03 (0.54)b 3.34 (0.48)a 0.87 (.20)a,b

Vandalism 0.91 (1.32) 1.48 (0.27)b 1.57 (0.24)a 0.36 (0.10)a.b

Violence/Assault 1.01 (1.31) 1.62 (0.26)b 1.66 (0.24)a 0.45 (0.10)a,b

Drugs 1.15 (1.79) 2.00 (0.33)b 2.01 (0.36)a 0.38 (.14)a,b

Sex-Related Crimes 0.02 (0.17) 0.00 (0.00) 0.00 (0.00) 0.03 (0.24)

a,b,cMeans sharing a common superscript are significantly different (p.05)dIndicates frequencies (percentages)eIndicates means and standard errors

210 Minority female juvenile offenders and health

of the pilot study, and a question-by-question running glossary was added to provide clarification for terms that were unknown to or difficult for the target population. This glossary was utilized for the in-person administration of the questionnaire. After obtaining human subjects approval through the University’s Internal Review Board (IRB), fliers and posters were placed in 8 of 18 youth diversion programs to recruit adolescent girls between the ages of 12 and 18. At each data collection site, girls who were interested in participating were given a consent form in order to obtain parental or legal guardian consent for participation.

Once initial written assent and consent were obtained, all participants were instructed on the study’s confidentiality protocol (e.g., assignment of ID numbers to provide anonymity). Furthermore, although no one discontinued participation in this inves-tigation, girls were told that they could withdraw from the study at any time. Survey administration lasted approximately one and one half hours. To circumvent any literacy barriers, all survey questions were read aloud by a female research assistant. Given the sensitive nature of the survey questions (e.g., ethnic identity), all attempts were made to match survey administrators and participants by ethnicity. The senior author, a graduate research assistant, and a research associate participated in survey administration. After completing the survey, adolescents were debriefed on the study goals. Participants were compensated with a $25 gift card after completion of the survey.

Measures. Health profile indicators. Subjective health. A one-item indicator was used to measure girls’ self-perceived health. Participants were asked, “How would you rate your health at the present time?” They provided responses based on a 5-point Likert scale (1 poor; 5 excellent).

Sexual activity. A one-item question was used to measure total number of sexual partners. Participants were asked, “In your lifetime, how many sexual partners have you had?” Higher numbers of course indicated a greater number of sexual partners.

Substance use behaviors. Substance use behaviors was assessed with two individual one-item questions measuring alcohol and marijuana use: “During the past month, how much alcohol have you had in one sitting, 0 none; 5 more than four cans/glasses)?” and “How many times have you used marijuana in your lifetime, 0 no; 3 more than 10 times?” Numerous studies have supported the validity of one-item indicators in the assessment of youth substance use.70

Depressive symptoms. Level of depressive symptomatology was measured with the Center for Epidemiologic Studies Depression Scale (CES-D).71 Participants responded on a 4-point scale (1 rarely/none of the time; 4 most/all of the time) how true each statement was during the past week (e.g., “I feel that everything I did was an effort.”; “I feel like crying.”). Reliability for this 20-item scale was .90. Higher scores indicated greater depressive symptomatology. Studies have indicated that the CES-D is reliable and valid for use with adolescent populations,72 including investigations with African American adolescent females.73

Anxiety symptoms. The State-Trait Anxiety Inventory (STAI)74 was used to mea-sure anxiety-related symptoms. The STAI is composed of two subscales: state-anxiety (20 items) and trait-anxiety (20 items). The trait subscale, which measures relatively stable anxiety symptoms (e.g., “I am worried,” “I am preoccupied by disappointment”), was utilized for this investigation. Based on previous investigations,75,76 this scale is

211Guthrie, Cooper, Brown, and Metzger

appropriate for use with adolescent and ethnic populations. Responses were coded on a 4-point scale (1 almost never; 4 very often). Reliability for the trait-anxiety subscale was .89. Higher scores indicated more anxiety-related symptoms.

Adolescent daily hassles. Forty-one items were utilized from the Daily Hassles Ques-tionnaire (DHQ77,78). The DHQ, which is a self-report inventory of day-to-day concerns of children and adolescents, was modeled after the original Daily Hassle Scale com-monly used for adults. Respondents were asked to rate on a four-point scale (0 not at all a hassle; 3 a very big hassle) the extent to which each item was a hassle during the past week. Sample items included the following: “trying to get good grades,” “hav-ing to take care of brother/sister,” and “not being part of the popular group.” Previous studies have demonstrated that the Daily Hassles for Adolescents Scale is reliable with ethnically diverse populations.10,79 Reliability for the current study was .92.

Demographic and contextual variables. Demographic indicators. Age and ethnicity of participants were used as demographic variables in this investigation. Additionally, a one-item, dichotomous (0 no; 1 yes) indicator of socio-economic status was utilized: “Does your family receive public financial assistance (e.g., TANF)?

Parent-adolescent relationship. A five-item scale was used to assess the adolescent’s perception of her relationship with her mother and father.80 Separate scales were computed for mother-adolescent (α.87) and father-adolescent (α.84) relationship. Higher scores indicated greater closeness with each parent. Sample items included “My mother/father is always there when I need her/him” and “I can talk to my mother/father about anything.”

Neighborhood resources. A 20-item scale81 measuring adolescents’ perception of their neighborhood (1 strongly agree; 5 strongly disagree). All items were coded such that higher scores indicated greater neighborhood resources. Sample items included “My neighborhood is like one big happy family” and “It’s hard to stay out of trouble in my neighborhood” (reverse scored). Reliability for this scale was .83. Existing stud-ies have utilized this scale with minority youth and demonstrated good reliability.82,83

Global self-esteem. Ten items from the Rosenberg Self-Esteem Scale (RSES)84 were used to assess participants’ global self-esteem. Sample items include: “I take a positive attitude toward myself ” and “I feel I am a person of worth, at least on an equal basis with others.” The scale ranged from 1 (strongly disagree) to 5 (strongly agree). In the present study, reliability for this scale was adequate (α.74). The RSES has been used previously with African American adolescent female populations and demonstrated good reliability.85

Prior sexual trauma. Four items were used to measure participants’ prior sexual trauma. Specifically, respondents were asked if they consented to sexual intercourse under any of the following circumstances: under pressure; due to authority of transgres-sor; due to physical force; and under threat of violence. The response scale for these questions was dichotomous (0 no; 1 yes). A mean score was computed using these items, and reliability for this scale was .73.

Self-reported offenses. Additionally, participants responded to a 19-item index assessing their self-reported offenses within the last 12 months. A cumulative index, which was adapted from the National Longitudinal Study of Adolescent Health,86 was computed for five dimensions: 1) theft (e.g., stolen something under $50; stolen

212 Minority female juvenile offenders and health

something over $50); 2) vandalism/personal property (e.g., damaged school property; damaged work property); 3) violence/assault (e.g., used knife/gun; fought with friend against gang); 4) drugs (e.g., sold drugs, runner for drugs); and 5) sex-related crimes (e.g., having sex for money; having sex for drugs). Higher scores indicated more self-reported offenses. Previous studies have used similar measures to capture self-reported offenses among African American adolescents.87

results

latent profile analysis. A latent profile analysis (LPA) was utilized to identify health profiles among study participants. Using Mplus software,88 LPA was employed to determine the viability of 1-, 2-, 3-, and 4-class solutions. Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) based on the previous literature89 were used to determine the best fitting model. Previous studies have suggested that AIC and BIC scores should be interpreted relative to one another, and that lower scores (e.g., closer to 0) are indicative of a more optimal model fit.90 In addition to AIC and BIC values, entropy scores were used to determine which class-solution was most accurate. Entropy values closer to 1.0 indicate a better fitting model. Finally, the Lo-Mendell-Rubin Adjusted Ratio Likelihood Test (LMRT) was used to determine the best model fit.91 Specifically, class solutions with a p-value less than .05 indicate that that solution is a better fit than the next lowest class (e.g., 4-class solution is a better fit than the 3-class solution) while class solutions with a LMRT p-value greater than .05 suggest that the higher class solution is not a better fit than the lower class solution. Fit indices (e.g., AIC, BIC, Entropy, LMRT) for each potential class solution are shown in Table 2.

Based upon the LMRT value (197.30, p.02), the 2-class solution was a better fit than the 1-class solution. Additionally, the 3-class solution was deemed a better fit than the 2-class solution (136.30, p.03). However, the LMRT values did not indicate that the

table 2.latent PrOFile analYSiS MODel Fit inDiCeS FOr ClaSS (PrOFile) SOlUtiOnS

Model Fit indices

Model aiC BiC entropy lMrt

1 Class 2951.88 2994.30 — —2 Class 2765.67 2832.34 0.86 197.30, p.143 Class 2641.98 2732.90 0.95 136.30, p.034 Class 2586.87 2702.03 0.95 69.39, p.43

AIC Akaike Information CriterionBIC Bayesian Information CriterionLMRT Lo-Mendell-Rubin Test

213Guthrie, Cooper, Brown, and Metzger

4-class solution was a better fit than the 3-class solution (69.39, p.43). Although the 4-class solution had lower AIC and BIC values, the 3-class solution was considered the best fitting model due to a significant LMRT value. Thus, three distinct classes were identified. Class 1 included 35 participants (22.9%), Class 2 included 68 participants (44.4%), and Class 3 included 50 participants (32.7%). Average latent class probabilities for most likely latent class membership indicated probabilities of 95.3% (Class 1), 97.8% (Class 2), and 100% (Class 3).

Both the overall sample means and class means were used to interpret the pattern of each identified profile (See Table 3). Class 1 was identified as the Low to Moderate Health Risk (N41) profile due to reduced risk behaviors (e.g., moderate number of lifetime sexual partners, less alcohol and lifetime marijuana use, lower mental health symptoms, slightly elevated daily hassles, and a higher subjective health rating). Class 2 (N68) included participants with moderate health risk behaviors, elevated depressive and anxiety symptoms, lower subjective health rating, and fewer daily hassles. Therefore, this class was defined as the High Mental Health Risk profile. In Class 3 (N50), the Compound Health Risk profile, participants had elevated risk behaviors (higher number of lifetime sexual partners and substance use) and higher levels of daily hassles. Addi-tionally, individuals in this class reported mental health symptoms similar to that of the overall sample mean. However, they also indicated a slightly higher (in comparison to the overall sample mean) subjective health rating. Means, standard deviations and comparisons of health profile indicators (e.g., psychological functioning, risk behaviors, health status) are shown in Table 3.

Comparison of health profiles by demographic variables. Equality of means tests across profiles and pairwise comparisons revealed no profile differences in whether girls’ socio-economic status. However, analyses did indicate profile differences in age and ethnicity. Girls in the Compound Health Risk profile were older than girls in the High Mental Health Risk (χ2(1, 152) 17.19, p.001) and Low/Moderate Health Risk profiles (χ2(1, 152) 6.37, p.05). A chi-squared analysis was conducted to explore differences between health profile groups and ethnic group membership. Results suggested that there was a significant relationship between ethnicity and profile membership (χ218.88; df4, p.001). Due to smaller numbers of Asian/Pacific Islander girls in our sample (n2), they were omitted from ethnic group comparisons. Thus, the chi-squared analysis explored an ethnicity (African American; Hispanic; Multiracial/Other) by profile inter-action (Low/Moderate Health Risk; High Mental Health Risk; Compound Health Risk). Exploration of cell counts and residuals indicated that African American girls were in the high Mental Health Risk cluster at a rate higher than anticipated (residual 10.0). However, Hispanic and Multiracial/Other girls were in the High Mental Health Risk cluster at a lower rate than expected (residual [Hispanic]  5.9; residual [Multiracial/Other] 4.1). Conversely, both Hispanic (residual 6.5) and Multiracial/Other (residual 2.8) girls were in the Compound Health Risk profile at a higher rate than expected, while African American girls (residual 9.2) were included in the profile at a lower rate than expected. Projections for inclusion in the Low/Moderate Health Risk profile were in line with the expected counts for African American (residual .8), Hispanic (residual .6), and Multiracial/Other (residual  1.3) girls.

Comparison of profiles by contextual variables. As depicted in Table 1, a significant

214 Minority female juvenile offenders and health

mean difference was found for mother-daughter relationship quality. Girls in the High Mental Health Risk profile reported greater maternal support and warmth than those in the Low/Moderate Health Risk (χ2(1, 152) 5.81, p.05) and Compound Health Risk profile (χ2(1, 152) 9.33, p.01). Also, girls in the High Mental Health Risk profile reported greater neighborhood support than those in the Low/Moderate Health Risk (χ2(1, 152) 5.20, p.05) and Compound Health Risk profile (χ2(1, 152)  22.34, p.001). A significant mean difference in self-esteem was found with girls in the Mental Health Risk profile reporting higher self-esteem than those in both the Compound Health (χ2(1, 152) 16.54, p.001) and Low/Moderate Health Risk profiles (χ2(1, 152)  62.03, p.001). Also, girls in the Low/Moderate Health Risk profile reported lower self-esteem than those in the Compound Health Risk profile (χ2(1, 152) 7.05, p.01). There was no significant mean difference in experiences of sexual trauma across the three profiles.

Mean differences in number of arrests and self-reported crimes. Analyses indicated a significant mean difference across multiple domains of self-reported offenses (e.g., thefts, vandalism, drugs, violence/assaults). Girls in the High Mental Health Risk pro-file reported committing fewer thefts (Compound: χ2(1, 152) 22.37, p.001; Low/Moderate: (χ2(1, 152) 13.75, p.001)), violent (Compound: χ2(1, 152) 21.00, p.001; (Low/Moderate: χ2(1, 152) 16.99, p.001)), vandalism (Compound: χ2(1, 152) 21.56, p.001; Low/Moderate: (χ2(1, 152) 14.47, p.001)), and drug-related (Compound: χ2(1, 152) 20.82, p.001; Low/Moderate: (χ2(1, 152) 17.32, p.001)) crimes than those in both the Compound Health Risk and Low/Moderate Health Risk

table 3. OVerall SaMPle anD HealtH PrOFile inDiCatOr MeanS (StanDarD DeViatiOnS)

Overall low/Moderate Compound High Mental Sample Health risk Health risk Health risk Profile indicators (n35) (n153) (n50) (n68)

Health Rating 2.80 3.98a,b 2.71b,c 1.97a,c

Number of Sex Partners 3.21 3.20 4.76a 2.11a

Depressive Symptoms 2.61 1.84a,c 2.67b,c 3.12a,b

Anxiety Symptoms 2.60 1.96a,b 2.70b,c 2.98a,c

Alcohol Use 1.22 0.48a 3.89a,b 0.38b

Lifetime Marijuana Use 0.76 1.06a 1.37b 0.24a,b

Daily Hassles 0.27 0.32 0.35 0.18

a,b,cMeans sharing a common superscript are significantly different (p.05). Health Rating was coded 1 (poor) to 5 (excellent). Number of Sex Partners was a continuous variable. Depressive Symptoms was coded 1 (rarely/none of the time); 4 (almost every day). Anxiety Symptoms was coded 1 (almost never); 4 (very often). Alcohol Use was coded 0 (none); 5 (more than 4 can/glasses). Lifetime Marijuana Use was coded 0 (never); 3 (more than 10 times). Daily Hassles was coded 0 (not at all a hassle); 3 (a very big hassle).

215Guthrie, Cooper, Brown, and Metzger

profiles. No profile differences, however, were found in the number of sex-related crimes (e.g., having sex for money).

Discussion

Recent statistics indicate that juvenile court cases involving female youth have increased in the last 25 years. Moreover, research has suggested that there are distinct risk factors for female juvenile offenders.28 However, despite being disproportionately represented in the juvenile justice system,5,92 there are few studies that examine social contextual correlates (e.g., familial relationships; neighborhood characteristics; intrapersonal factors) of ethnically-diverse female juvenile offenders’ comprehensive health status. This investigation had several findings that contribute to the extant literature. First, we identified three distinct health profiles among a sample of minority female juve-nile offenders. Second, we provided evidence that these health profiles differed across multiple demographic and contextual dimensions. Third, our findings indicated that self-reported offenses varied by health profiles.

Health profiles among minority female juvenile offenders. This investigation revealed that psychological functioning, health status, and risk behavior engagement are important considerations among females of color who are juvenile offenders. Specifically, our latent class analysis identified 3 distinct profiles among this sample— 1) Low/Moderate Health Risk; 2) High Mental Health Risk; and 3) Compound Health Risk. Girls in the low to moderate health risk profile (22.8% of the total sample) represented low to moderate health hazards, including higher health ratings, fewer depression and anxiety symptoms, low to moderate substance use. Thus, based upon relation to other profiles, females in this profile were classified as having a lower health risk. The high mental health risk profile, however, was composed of female youth reporting increased mental health symptoms and fewer reported health risk behaviors (e.g., alcohol use, lifetime marijuana use). In accordance with numerous studies that have pointed to dis-proportionate psychological issues among female juvenile offenders,14,23,25 the majority of the sample (n68; 44.4%) were in the mental health risk profile. Thus, similar to patterns indicated in the larger literature, our investigation suggested that depressive and anxiety symptoms were present among a sizeable majority of females in our sample.

Additionally, our analyses indicated a distinct group of girls who possessed a com-bination of mental and physical health risks. In particular, the compound health risk profile (n50; 32.7%) reported greater engagement in multiple health risk behaviors (e.g., substance use and greater number of sex partners) and moderate mental health symptoms (e.g., depressive and anxiety symptoms). Previous studies have indicated that the duality of physical and mental health is an important consideration in under-standing the experiences of female adult and juvenile offenders.10,51,46,49 Overall, our results suggest that there is variation in the health status of minority female juvenile offenders. Furthermore, these findings indicate that these distinct profiles may have important implications for short- and long-term physical and mental treatment among this subpopulation. For example, girls with compound health risk issues should have short-term and long-term treatments that take a comprehensive approach to physical and mental health issues. In addition, girls with elevated psychological symptoms (as

216 Minority female juvenile offenders and health

identified in the mental health risk profile) should have treatment plans that address mental health issues, including attention to underlying factors (e.g., prior trauma). Moreover, attention to these health issues should be in tandem with understanding the behaviors associated with their juvenile justice system engagement. Importantly, the identification of distinct health risk profiles among girls of color negates the perspec-tive that all girls have the same health issues and provides beginning evidence of the significance of differentiating the mental and health needs of this population.

Demographic variation among health profiles. Our analyses indicated that girls classified as having a Compound Health Risk were older than girls in the High Mental Health and Low/Moderate Risk profiles. These findings may signify a developmental pattern, in which female youth who do not receive adequate treatment may eventu-ally progress to more serious health risks. Research has suggested that health issues among offenders often have earlier origins that compound throughout the lifespan.93 Although this study did not explore developmental pathways or trajectories, they are in line with various investigations suggesting that risk does accumulate over time.94,95 Additionally, given that girls in the Mental Health risk profile were younger, our find-ings are bolstered by indications that girls with more serious mental health issues are likely to enter the Juvenile Justice System at younger ages. Overall, this finding further substantiates the importance of addressing mental and physical health-related factors among female juvenile offenders and suggests that there may be developmental patterns.

Furthermore, our analyses indicated difference by ethnic group among profiles. Spe-cifically, the number of African American girls in the High Mental Health Risk profile was higher than expected. Our investigation suggests that African American female youth report disproportionately higher mental health-related symptoms and this finding further substantiates that African American, in comparison to the general population have an increased mental health risk.96 Additionally, our analyses provided evidence that Hispanic and Multiracial/Other girls have a greater likelihood of being in the Compound Health Risk profile. Due to the smaller number of Non-African American girls in this study, however, prospective studies, preferably ones utilizing nationally-representative data, are needed to further explore these associations.

Contextual variation among health profiles. Regarding contextual variation, this study suggested that the identified health profiles differed across several dimensions. Surprisingly, girls in the Mental Health Risk profile reported a more positive mother-daughter relationship and greater neighborhood support than the other profiles. Our findings were not in line with several studies pointing to associations between several domains of social support and greater psychological functioning.97 The directionality of our results suggests that there may be some important underlying factors. For instance, studies have shown that social capital (e.g., positive familial relationships; community support) may not always be associated with positive mental health outcomes.97 Further, this research suggests that decreased psychological functioning may occur when indi-viduals do not conform to expected behaviors and rules of their social networks, which could be an important consideration for girls who are engaging in problem behaviors. Thus, these associations suggest that individual and contextual factors interact to influ-ence girls’ outcomes. Still, further studies are needed to better understand the nuances of this relationship, including the identification of moderators.

217Guthrie, Cooper, Brown, and Metzger

We found a similar pattern with respect to self-esteem. Previous studies have docu-mented the important role of self-esteem in the development of female youth and our findings indicated self-esteem differences by profile. Our analyses indicated that girls in the Compound Health Risk profile reported lower self-esteem. Existing investigations suggesting that self-esteem is associated with risk behavior engagement and decreased psychological functioning among adolescent girls provide additional support for our findings.98 Additionally, our analyses indicated that girls in the High Mental Health Risk profiles reported higher self-esteem. While this may seem counterintuitive, several recent investigations have asserted that high self-esteem, in some situations, is associ-ated with less positive outcomes.99,100 For instance, Kernis and colleagues demonstrated that individuals with fragile high self-esteem are more vulnerable to external influ-ences on their self-worth (e.g., peers, parents). Moreover, this increased vulnerability can adversely influence psychological functioning.101 Another possible explanatory factor is the multidimensional nature of self-esteem (e.g., academic; personal, peer-related).101,102,103 Recent investigations have supported this assertion with suggestions that low self-esteem in some domains (e.g., family; school) and that high self-esteem in other domains (e.g., peer relationships) are both associated with negative outcomes.104

Self-reported offenses. This investigation suggested differences among health profiles regarding self-reported offenses. In particular, we found a consistent pattern that girls in the Mental Health Risk profile reported fewer non-violent (e.g., thefts) and violent (e.g., assaults) self-reported offenses than those in the other profiles. It is possible that girls with an increased mental health risk are committing less serious offenses. In fact, there is some indication in the literature that female offenders who have used mental health services are more likely to be arrested for nonviolent offenses.93 This is compli-cated further by studies indicating that African American female youth who come in contact with the Juvenile Justice System are less likely to receive mental health treatment than their White counterparts.1,5,7 Our finding is of particular importance given the disproportionate number of African American female youth who were in this profile and suggests that mental health status among female juvenile offenders, particularly among African American female youth, remains an important consideration. Moreover, these findings underscore the significance of mental health treatment services among this population.

limitations and future directions. Despite contributions of this investigation, it is not without limitations. First, this investigation was based upon self-reported data. Although the self-reported perspectives and perceptions of female youth were impor-tant, information from additional sources (e.g., juvenile justice system reported arrest and offense data) could have provided greater insight into the examined relationships and address any issues with bias. Moreover, the cross-sectional nature of this investi-gation makes it difficult to ascertain directionality of the explored relationships. For instance, although studies have demonstrated that less positive family and neighbor-hood factors affect health outcomes,60 it is also probable that girls in poorer health (e.g., mental health) may influence their social relationships, and their perceptions of these relationships may be affected.

Additionally, the girls in this investigation were a self-selected sample in a juvenile diversion program. Thus, these findings cannot be generalized to the entire population

218 Minority female juvenile offenders and health

of non-White females who are currently in diversion programs or the general popula-tion of girls in the juvenile justice system. Future studies should explore health profiles using a more representative sample of minority female juvenile offenders. Also, although we sought to identify profiles using adolescent girls from various ethnic groups, this study did not have sufficient sample sizes among all ethnic groups to make these com-parisons. Another limitation of this investigation was that the scales utilized may not adequately describe all facets of health and social experiences. In particular, we were not able to explore additional aspects of sexual trauma, including frequency, duration and transgressor. Prospective studies should include additional scales that provide insight into minority female juvenile offenders’ physical and mental health status and socio-contextual correlates (e.g., multiple self-esteem domains). Still, our investigation contributes further to the development and refinement of a comprehensive health profile, encompassing health status, psychological functioning, and risk behavior engagement among this population.

implications. Despite these limitations, this investigation further contributes to the extant literature on the health of ethnic minority female juvenile offenders. Specifically, this study provides additional evidence that psychological functioning, risk behavior engagement, and health status collectively, should be taken into account when assess-ing the health needs of female juvenile offenders. Our investigation suggests that the examined health indicators do not occur in isolation from one another and a multi-pronged health care approach may lead to more optimal health outcomes. Further, the overarching findings of this investigation implicitly support the notion that health is not an isolated idea but is contextually-embedded. Williams105 suggested that in order to better understand and provide responsive health care, health is best understood, examined, and cared for within the individual or group’s relational and social contexts. Addressing health disparities is one of the overarching goals of Healthy People 2020.106 Hence, to better address the specific health needs of youth who are within the juvenile justice system, particularly ethnically-diverse youth, the detention health care systems must be cognizant of the fact that the “one size fits all” approach to adolescent female health care will not meet the challenges of the 21st century or achieve the Healthy People 2020 goal of health equity for all.

Of equal importance is the further development of evidence-based practices and treatments that are based upon integrative, multidimensional, and ecological frame-works. For instance, health risk behaviors, mental health and offending behaviors are inextricably bound and only addressing the offending behaviors might impede rehabilitation.9 In order to meet the unique physical and mental health needs of girls of color, the correctional health care system must move toward instituting gender-responsive and restorative correctional health care model that includes understanding the variation of health profiles among this population of girls. Guthrie107 posits that the intent of a restorative health care model is to address and treat the existing physical and mental health inequities that females of color experience. The two critical assump-tions that provide the underpinnings of this model are as follows: “health and access to health care are not privileges but rights that should be afforded to all human beings irrespective or race, ethnicity, age, sexual orientation, educational level and behavior (criminal or not) and female’s health is relational and is best understood and examined

219Guthrie, Cooper, Brown, and Metzger

within the socially embedded health-related processes.”[p.5] Moreover, research suggests that a wide range of factors should be considered, including educational assets, abuse, neighborhood safety, mental and physical health, social relationships and community support.108 The information generated from this detailed information will provide a better understanding of how to develop a comprehensive physical and mental health action plan that is multilevel and tailored toward ethnically diverse female’s distinct health risk profiles.

With that said, our investigation also has important implications related to address-ing the timely physical and mental access to and quality of services available within the community and the juvenile justice system. As multiple sources have indicated, ethnic minority youth are more likely than other youth to experience health inequities prior to and within the juvenile justice system, their pre-existing disparate physical and mental health issues may become even more exacerbated during confinement.48 Further, several studies have indicated that juvenile justice systems are ill-equipped to address the overall health of youth and even more ill-equipped to adequately address the complex mental and physical health issues of females, particularly those from various ethnic and racial backgrounds.109,110 Thus, another important step toward improving the effectiveness of juvenile justice health care services is to train professionals to become more aware of the unique gender-related experiences of female juvenile offenders as well as under-standing that there is tremendous across and within ethnic group variation in these experiences. In addition, our study suggests the importance of collaboration across multiple systems and health care settings. For instance, juvenile justice systems should partner with community-based agencies and health professionals (e.g., physicians and nurse practitioners) to develop health action plans for all youth.

notes 1. Office of Juvenile Justice and Delinquency Prevention. Youth characteristics and

background. Washington, DC: Office of Juvenile Justice and Delinquency Prevention, 2010.

2. Mullis RL, Rathge R, Mullis AK. Predictors of academic performance during early adolescence: a contextual view. Int J Behav Develop. 2003 Nov;27(6):541–8.

3. Barnett M, Simmons EL. Justice by gender: the lack of appropriate prevention, diversion and treatment alternatives for girls in the justice system. Washington, DC: American Bar Association, 2001.

4. Poe-Yamagata E, Jones MA. And justice for some: differential treatment of minority youth in the justice system. Washington, DC: National Institute of Correction, 2000.

5. Chauhan P, Reppucci ND, Burnette M, et al. Race, neighborhood disadvantage, and antisocial behavior among female juvenile offenders. Journal of Community Psychol-ogy. 2010;38(4):532–40.

6. Moore LD, Padavic I. Racial and ethnic disparities in girls’ sentencing in the juvenile justice system. Feminist Criminology. 2010 Jul;5(3):263–85.

7. Lopez-Williams A, Stoep AV, Kuo E, et al. Predictors of mental health service enroll-ment among juvenile offenders. Youth Violence and Juvenile Justice. 2006 Jul;4(3): 266–80.

8. Gallagher CA, Dobrin A, Douds AS. A national overview of reproductive health care

220 Minority female juvenile offenders and health

services for girls in juvenile justice residential facilities. Women’s Health Issues. 2007 Jul–Aug;17(4):217–26.

9. Cauffman EE. Understanding the female offender. The future of children. 2008 Fall; 18(2):119–42.

10. Guthrie BJ, Young AM, Boyd CJ, et al. Ebb and flow when navigating adolescence: predictors of daily hassles among African-American adolescent girls. Journal for Specialists in Pediatric Nursing. 2002 Oct 1;7(4):143–52.

11. Martin D, Martin M, Dell R, et al. Profile of incarcerated juveniles: comparison of male and female offenders. Adolescence. 2008 Fall;43(171):607–22.

12. Petrocelli JV, Calhoun GB, Glaser BA. The role of general family functioning in the quality of the mother-daughter relationship of female African American juvenile offenders. Journal of Black Psychology. 2003 Nov;29(4):378–92.

13. Cauffman E, Piquero AR, Broidy L, et al. Heterogeneity in the association between social-emotional adjustment profiles and deviant behavior among male and female serious juvenile offenders. Int J Offender Therapy and Comparative Criminology. 2004 Apr;48(2):235–52.

14. Graves KN, Frabutt JM, Shelton TL. Factors associated with mental health and juve-nile justice involvement among children with severe emotional disturbance. Youth Violence and Juvenile Justice. 2007 Apr;5(2):147–67.

15. Braithwaite RL, Treadwell HM, Arriola KR. Health disparities and incarcerated women: a population ignored. Am J Public Health. 2008 Sep;98(9 Suppl):S173–5.

16. Bergman LR, Trost K. The person-oriented versus the variable-oriented approach: are they complementary, opposites, or exploring different worlds?. Journal of Devel-opmental Psychology. 2006 Jul;52(3):601–32.

17. Magnusson D, Stattin H. Person-context interaction theories. In: Damon W, Lerner RM, eds. Handbook of child psychology: theoretical models of human development (5th ed.). New York, NY: Wiley, 1998.

18. Bogat GA, Levendosky AA, von Eye A. The future of research on intimate partner violence: person-oriented and variable-oriented perspectives. Am J Community Psychol. 2005 Sep;36(1–2):49–70.

19. Dembo R, Williams L, Schmeidler J. Gender differences in mental health service needs among youths entering a juvenile detention center. Journal of Prison and Jail Health. 1993;12(2):73–101.

20. McCarty CA, Stoep AV, Kuo ES, et al. Depressive symptoms among delinquent youth: testing models of association with stress and support. J Psychopathol Behav Assess. 2006 Jun;28(2):85–93.

21. Timmons-Mitchell J, Brown C, Schulz SC, et al. Comparing the mental health needs of female and male incarcerated juvenile delinquents. Behav Sci Law. 1997 Spring;15(2):195–202.

22. Wasserman GA, McReynolds LS, Ko SJ et al. Gender differences in psychiatric dis-orders at juvenile probation intake. Am J Public Health. 2005 Jan;95(1):131–7.

23. Cook NE, Barese TH, Dicataldo F. The confluence of mental health and psycho-pathic traits in adolescent female offenders. Criminal Justice and Behavior. 2010 Jan; 37(1):119–35.

24. Cruise KR, Marsee MA, Dandreaux DM, et al. Mental health screening of female juvenile offenders: replication of a subtyping strategy. Journal of Child and Family Studies. 2007 Oct;16(5):615–25.

221Guthrie, Cooper, Brown, and Metzger

25. Kataoka SH, Zima BT, Dupre DA, et al. Mental health problems and service use among female juvenile offenders: their relationship to criminal history. J Am Acad Child Adolesc Psychiatry. 2001 May;40(5):549–55.

26. Teplin L, Abram K, McClelland G, et al. Psychiatric disorders in youth in juvenile detention. Arch Gen Psychiatry. 2002 Dec;59(12):1133–43.

27. Ritakallio M, Kaltiala-Heino R, Kivivuori J, et al. Delinquency and the profile of offenses among depressed and non-depressed adolescents. Crim Behav Ment Health. 2006;16(2):100–10.

28. Quinn MM, Poirier JM, Garfinkel L. Girls with mental health needs in the juvenile justice system: challenges and inequities confronting a vulnerable population. Excep-tionality. 2005;13(2):125–39.

29. Holsinger K, Holsinger AM. Differential pathways to violence and self-injurious behavior: African American and White girls in the juvenile justice system. Journal of Research in Crime and Delinquency. 2005 May;42(2):211–42.

30. Fejes-Mendoza K, Miller D, Eppler R. Portraits of dysfunction: criminal, educational, and family profiles of juvenile female offenders. Education & Treatment of Children. 1995 Aug;18(3):309–21.

31. Kataoka SH, Zima BT, Dupre DA, et al. Mental health problems and service use among female juvenile offenders: their relationship to criminal history. J Am Acad Child Adolesc Psychiatry. 2001 May;40(5):549–55.

32. Molidor CE, Nissen LB, Watkins TR. The development of theory and treatment with substance abusing female juvenile offenders. Child & Adolescent Social Work Journal. 2002 Jun;19(3):209–25.

33. Palmer EJ, Jinks M, Hatcher RM. Substance use, mental health, and relationships: a comparison of male and female offenders serving community sentences. Int J Law Psychiatry. 2010 Mar–Apr;33(2):89–93. Epub 2009 Dec 24.

34. Roe-Sepowitz DE. Comparing male and female juveniles charged with homicide: child maltreatment, substance abuse, and crime details. J Interpers Violence. 2009 Apr; 24(4):601–17.

35. Riehman K, Iguchi M, Zeller M, et al. The influence of partner drug use and relation-ship power on treatment engagement. Drug and Alcohol Dependence. 2003 May; 70(1):1–10.

36. Stoolmiller M, Blechman EA. Substance use is a robust predictor of adolescent recidi-vism. Criminal Justice and Behavior. 2005 Jun;32(3):302–28.

37. Goldstein NE, Arnold DH, Weil J, et al. Comorbid symptom patterns in female juvenile offenders. Int J Law Psychiatry. 2003 Sep–Oct;26(5):565–82.

38. Ariga M, Uehara T, Takeuchi K, et al. Trauma exposure and posttraumatic stress dis-order in delinquent female adolescents. Journal of Child Psychology and Psychiatry. 2008 Jan;49(1):79–87.

39. Dembo R, Schmeidler J, Childs K. Correlates of male and female juvenile offender abuse experiences. J Child Sex Abus. 2007;16(3):75–94.

40. Chesney-Lind M, Morash M, Stevens T. Girls’ troubles, girls’ delinquency, and gender responsive programming: a review. Australian and New Zealand Journal of Criminol-ogy. 2008 Apr;41(1, Spec Iss):162–89.

41. Dixon A, Howie P, Starling J. Trauma exposure, posttraumatic stress, and psychiatric comorbidity in female juvenile offenders. J Am Acad Child Adolesc Psychiatry. 2005 Aug;44(8):798–806.

222 Minority female juvenile offenders and health

42. United States Census Bureau. Children and the households they live in. Washington, DC: United States Census Bureau, 2000.

43. Flores G, Tomany-Korman SC. Racial and ethnic disparities in medical and dental health, access to care, and use of services in U.S. children. Pediatrics. 2008 Feb; 121(2):e286–98.

44. Brody G, Ge X, Simons R, et al. The influence of neighborhood disadvantage, col-lective socialization, and parenting on African American children’s affiliation with deviant peers. Child Development. 2001 Jul;72(4):1231–46.

45. Piquero A, Moffitt T, Lawton B. Race and crime: the contribution of individual, familial, and neighborhood-level risk factors to life-course-persistent offending. Our children, their children: confronting racial and ethnic differences in American juvenile justice. Chicago, IL: University of Chicago Press, 2005.

46. Freudenberg N. Jails, prisons, and the health of urban populations: a review of the impact of the correctional system on community health. Journal of Urban Health. 2001 Jun;78(2):214–35.

47. Odgers C, Robins S, Russell M. Morbidity and mortality risk among the “forgot-ten few”: why are girls in the justice system in such poor health? Law and Human Behavior. 2010 Dec;34(6):429–44.

48. Griel L, Loeb S. Health issues faced by adolescents incarcerated in the juvenile justice system. Journal of Forensic Nursing. 2009 Sep;5(3):162–79.

49. Kane M, DiBartolo M. Complex physical and mental health needs of rural incarcer-ated women. Mental Health Nursing. 2002 Apr;23(3):209–29.

50. Voisin D, DiClemente R, Salazar L, et al. Ecological factors associated with STD risk behaviors among detained female adolescents. Social Work. 2006 Jan;51(1):71–9.

51. Douglas N, Plugge E. The health needs of imprisoned female juvenile offenders: the views of the young women prisoners and youth justice professionals. Int J Prisoner Health. 2008 Jun;4(2):66–76.

52. Guthrie BJ, Young AM, Boyd CJ, et al. Ebb and flow when navigating adolescence: predictors of daily hassles among African-American adolescent girls. Journal for Specialists in Pediatric Nursing. 2002 Oct;7(4):143–52.

53. Mullis RL, Cornille TA, Mullis AK, et al. Female juvenile offending: a review of characteristics and contexts. Journal of Child and Family Studies. 2004;13(2):205–18.

54. Kroupa SE. Perceived parental acceptance and female juvenile delinquency. Adoles-cence. 1988 Spring;23(89):171–85.

55. Leve LD, Chamberlain P. Female juvenile offenders: defining an early-onset pathway for delinquency. Journal of Child & Family Studies. 2004 Dec;13(4):439–52.

56. Chesney-Lind M, Shelden RG. Girls, delinquency, and juvenile justice (2nd ed.). Belmont, CA: West/Wadsworth, 1998.

57. McCabe KM, Lansing AE, Garland A, et al. Gender differences in psychopathology, functional impairment, and familial risk factors among adjudicated delinquents. J Am Acad Child Adolesc Psychiatry. 2002 Jul;41(7):860–7.

58. Vandiver D, Teske R. Juvenile female and male sex offenders: a comparison of offender, victim, and judicial processing characteristics. Int J Offender Ther Comp Criminol. 2006 Apr;50(2):148–65.

59. Siegel LJ, Senna JJ. Essentials of criminal justice. Belmont, CA: Wadsworth Publishing Company, 2008.

60. Pittman LD, Chase-Lansdale PL. African American adolescent girls in impoverished communities: parenting style and adolescent outcomes. Journal of Research on Ado-lescence. 2001 Jul;11(2):199–224.

223Guthrie, Cooper, Brown, and Metzger

61. Doswell W, Millor G, Thompson H, et al. Self-image and self-esteem in African-American preteen girls: implications for mental health. Mental Health Nursing. 1998 Jan;19(1):71–94.

62. Hendriks J, Bijleveld C. Female adolescent sex offenders—an exploratory study. Journal of Sexual Aggression. 2006 Mar;12(1):31–41.

63. Niregi K. The attributional style and self-esteem of female juvenile delinquents. Japanese Journal of Counseling Science. 2006 Jun;39(2):99–112.

64. Miller LD. Adolescents, self-esteem, and substance use. In: Lewis JA, eds. Addictions: concepts and strategies for treatment. Gaithersburg, MD: Aspen Publishers, 1994.

65. Hubbard D. Getting the most out of correctional treatment: testing the responsivity principle on male and female offenders. Federal Probation. 2007 Jun;71(1):2–8.

66. Vander Stoep A, Evens CC, Taub JI. Risk of juvenile justice system referral among children in a public mental health system. Journal of Mental Health Administration. 1997;24(4):428–42.

67. Guthrie B, Hoey E, Ravoira L, et al. Girls in the juvenile justice system: leave no girl’s health un-addressed. Journal of Pediatric Nursing. 2002 Dec;17(6):414–23.

68. Espelage D, Cauffman E, Broidy L, et al. A cluster-analytic investigation of MMPI profiles of serious male and female juvenile offenders. J Am Acad Child Adolesc Psychiatry. 2003 Jul;42(7):770–8.

69. Odgers CL, Moretti MM, Burnette ML, et al. A latent variable modeling approach to identifying subtypes of serious and violent female juvenile offenders. Aggress Behav. 2007 Jul–Aug;33(4):339–52.

70. Bachman JG, O’Malley PM, Johnston LD, et al. Racial/ethnic differences in the rela-tionship between parental education and substance use among U.S. 8th-, 10th-, and 12th-grade students: findings from the Monitoring the Future project. J Stud Alcohol Drugs. 2011 Mar;72(2):279–85.

71. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement. 1977 Jun;1(3):385–401.

72. Roberts R, Andrews J, Lewinsohn P, et al. Assessment of depression in adolescents using the center for epidemiologic studies depression scale. Psychological Assessment. 1990 Jun;2(2):122–8.

73. Coley R. Daughter-father relationships and adolescent psychosocial functioning in low-income African American families. Journal of Marriage & Family. 2003 Nov; 65(4):867–75.

74. Spielberger C, Edwards D, Lushene R, et al. State-trait anxiety inventory for children. Palo Alto, CA: Consulting Psychologists Press Inc., 1973.

75. Carter M, Sbrocco T, Lewis E, et al. Parental bonding and anxiety: differences between African American and European American college students. Journal of Anxiety Dis-orders. 2001 Nov;15(6):555–69.

76. Magnus K, Cowen E, Wyman P, et al. Correlates of resilient outcomes among highly stressed African-American and White urban children. Journal of Community Psy-chology. 1999 Jul;27(4):473–88.

77. Rowlison RT, Felner RD. Major life events, hassles, and adaptation in adolescence: confounding in the conceptualization and measurement of life stress and adjustment revisited. J Pers Soc Psychol. 1988 Sep;55(3):432–44.

78. Dubois DL, Felner RD, Meares H. Prospective investigation of the effects of socio-economic disadvantage, life stress, and social support on early adolescent adjustment. Journal of Abnormal Psychology. 1994 Aug;103(3):511–22.

224 Minority female juvenile offenders and health

79. Guthrie B, Flinchbaugh L. Gender-specific substance prevention programming: going beyond just focusing on girls. Journal of Early Adolescence. 2001 Aug;21(3):354–72.

80. Levitt M, Guacci-Franco N, Levitt J, et al. Child behavior rating scale. Developmental Psychology. 1993 Jan;29(3):811–8.

81. Dembo R, Schmeidler J, Burgos W, et al. Environmental setting and early drug involvement among inner city junior high school youths. Int J Addict. 1985 Aug;20(8):1239–55.

82. Griffin KW, Scheier LM, Botvin G J, et al. Interpersonal aggression in urban minority youth: mediators of perceived neighborhood, peer, and parental influences. Journal of Community Psychology. 1999;27(3):281–98.

83. Scheier LM, Botvin GJ, Miller NL. Life events, neighborhood stress, psychosocial functioning, and alcohol use among urban minority youth. Journal of Child & Ado-lescent Substance Abuse, 1999 May;9(1):19–50. doi:10.1300/J029v09n01_02

84. Rosenberg M. Society and the adolescent self-image. Princeton, NJ: Princeton Univer-sity Press, 1965.

85. Salazar L, Wingood G, DiClemente R, et al. The role of social support in the psy-chological well-being of African American girls who experience dating violence victimization. Violence and Victims. 2004 Apr;19(2):171–87.

86. Harris, KM. The national longitudinal study of adolescent health. Chapel Hill, NC: University of North Carolina at Chapel Hill, 2009.

87. Caldwell R, Wiebe R, Cleveland H. The influence of future certainty and contextual factors on delinquent behavior and school adjustment among African American adolescents. Journal of Youth and Adolescence. 2006 Aug;35(4):591–602.

88. Muthén LK, Muthén BO. Mplus user’s guide (5th ed.). Los Angeles, CA: Muthén and Muthén, 1998.

89. Nylund K, Asparouhov T, Muthén B. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Structural Equation Modeling. 2007;14(4):535–69.

90. Hagenaars JA, McCutcheon AL. Applied latent class analysis. New York, NY: Cam-bridge University Press, 2002.

91. Lo Y, Mendell NR, Rubin DB. Testing the number of components in a normal mixture. Biometrika. 2001;88(3):767–78.

92. Kempf-Leonard K. Minority youths and juvenile justice: disproportionate minority contact after nearly 20 years of reform efforts. Youth Violence and Juvenile Justice. 2007 Jan;5(1):71–87.

93. Marquart J, Brewer V, Simon P, et al. Lifestyle factors among female prisoners with histories of psychiatric treatment. Journal of Criminal Justice. 2001 Jul;29(4):319–28.

94. Bor W, McGee T, Hayatbakhsh R, et al. Do antisocial females exhibit poor outcomes in adulthood? An Australian cohort study. Australian & New Zealand Journal of Psychiatry. 2010 Jul;44(7):648–57.

95. Chassin L, Collins R, Ritter J, et al. Vulnerability to substance use disorders across the lifespan. Vulnerability to psychopathology: risk across the lifespan (2nd ed.). New York, NY: Guilford Press, 2010.

96. Townsend TG, Hawkins SR, Batts AL. Stress and stress reduction among African American women: a brief report. J Prim Prev. 2007 Nov;28(6):569–82. Epub 2008 Feb 14.

97. Kawachi I, Berkman LF. Social ties and mental health. J Urban Health. 2001 Sep;78(3):458–67.

225Guthrie, Cooper, Brown, and Metzger

98. Veselka Z, Geckova AM, Orosova O, et al. Self-esteem and resilience: the connection with risky behavior among adolescents. Addict Behav. 2009 Mar;34(3):287–91. Epub 2008 Nov 21.

99. Baumeister R, Bushman B, Campbell W. Self-esteem, narcissism, and aggression: does violence result from low self-esteem or from threatened egotism? Current Directions in Psychological Science. 2000 Feb;9(1):26–9.

100. Kernis MH, Paradise AW, Whitaker DJ, et al. Master of one’s psychological domain? Not likely if one’s self-esteem is unstable. Pers Soc Psychol Bull. 2000 Nov;26(10):1297–305.

101. Harter S, Brown K, Striegel-Moore R, et al. Perceived competence scale for children—global self-worth, physical appearance, and social acceptance subscales. Journal of Adolescent Health. 1998 Jan;23(2):7–19.

102. Sondhaus E, Kurtz R, Strube M. Body attitude, gender, and self-concept: a 30-year perspective. Journal of Psychology. 2001 Jul;135(4):413–29.

103. Tiggemann M, Rothblum E. Gender differences in internal beliefs about weight and negative attitudes towards self and others. Psychology of Women Quarterly. 1997 Dec;21(4):581–93.

104. Wild LG, Flisher AJ, Bhana A, et al. Associations among adolescent risk behaviours and self-esteem in six domains. Journal of Child Psychology and Psychiatry. 2004 Nov;45(8):1454–67.

105. Williams B. Gaining with integration: three healthcare organizations use integrated financial-clinical systems to achieve ROI, process improvement and patient care objectives. Health Management Technology. 2002 Jun;23(6):10–5.

106. HealthyPeople.gov. Yearly report. Washington, DC: HealthyPeople.gov, 2009. 107. Guthrie B. Toward a gender-responsive restorative correctional health care model.

Journal of Obstetrics, Gynecologic, Neonatal Nurses. 2011 Jun;40(4):1–9. 108. Van Voorhis P, Wright EM, Salisbury E, et al. Women’s risk factors and their contri-

butions to existing risk/needs assessment: the current status of a gender-responsive supplement. Criminal Justice and Behavior. 2010 Mar;37(3):261–88.

109. Committee on Adolescent Health. Health care for children and adolescents in the juvenile correctional care system. Pediatrics. 2001;107(2):799–803.

110. Gallagher CA, Dobrin A. Can juvenile justice detention facilities meet the call of the American Academy of Pediatrics and National Commission on Correctional Health Care? A national analysis of current practices. Pediatrics. 2007 Apr 1;119(4):e991–1001.