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comorbid_psychiatric_disorders.pdf

Comorbid Psychiatric Disorders in Youth in Juvenile Detention Karen M. Abram, PhD; Linda A. Teplin, PhD; Gary M. McClelland, PhD; Mina K. Dulcan, MD

Objective: To estimate 6-month prevalence of comor- bid psychiatric disorders among juvenile detainees by demographic subgroups (sex, race/ethnicity, and age).

Design: Epidemiologic study of juvenile detainees. Mas- ter’s level clinical research interviewers administered the Diagnostic Interview Schedule for Children Version 2.3 to randomly selected detainees.

Setting: A large temporary detention center for juve- niles in Cook County, Illinois (which includes Chicago and surrounding suburbs).

Participants: Randomly selected, stratified sample of 1829 African American, non-Hispanic white, and His- panic youth (1172 males, 657 females, aged 10-18 years) arrested and newly detained.

Main Outcome Measure: Diagnostic Interview Sched- ule for Children.

Results: Significantly more females (56.5%) than males (45.9%) met criteria for 2 or more of the following disor- ders: major depressive, dysthymic, manic, psychotic, panic, separation anxiety, overanxious, generalized anxiety, ob- sessive-compulsive, attention-deficit/hyperactivity, con-

duct, oppositional defiant, alcohol, marijuana, and other substance; 17.3% of females and 20.4% of males had only one disorder. We also examined types of disorder: affec- tive, anxiety, substance use, and attention-deficit/ hyperactivity or behavioral. The odds of having comor- bid disorders were higher than expected by chance for most demographic subgroups, except when base rates of dis- orders were already high or when cell sizes were small. Nearly 14% of females and 11% of males had both a ma- jor mental disorder (psychosis, manic episode, or major depressive episode) and a substance use disorder. Com- pared with participants with no major mental disorder (the residual category), those with a major mental disorder had significantly greater odds (1.8-4.1) of having substance use disorders. Nearly 30% of females and more than 20% of males with substance use disorders had major mental dis- orders. Rates of some types of comorbidity were higher among non-Hispanic whites and older adolescents.

Conclusions: Comorbid psychiatric disorders are a ma- jor health problem among detained youth. We recom- mend directions for research and discuss how to im- prove treatment and reduce health disparities in the juvenile justice and mental health systems.

Arch Gen Psychiatry. 2003;60:1097-1108

M ANY OF our nation’syouth are involved inthe juvenile justicesystem. The US De-partment of Justice es- timates that each year there are 2.5 mil- lion juvenile arrests.1 Moreover, nearly 1.8 million cases are referred to juvenile courts.2 On an average day in the United States, approximately 109 000 youth younger than 18 years are incarcerated3; nearly 15% of these are youth housed in adult facilities that may lack mental health services for youth.4 African American and Hispanic youth are overrepresented in the juvenile justice system, accounting for more than 60% of young offenders in ju- venile justice facilities.5 The number of fe- males in the juvenile justice system is in-

creasing at an even faster rate than the number of males.5

Many detained youth have psychiat- ric disorders.6-9 Teplin et al8 found that even after excluding conduct disorder (symptoms of which include delinquent behaviors), approximately 60% of males and 70% of females had a psychiatric dis- order. These rates of disorder far exceed those of youth in the community.8,10

Advocacy groups and public policy experts believe that many youth in the ju- venile justice system have comorbidity: more than 1 alcohol, other drug, or men- tal (ADM) disorder.11 The Surgeon Gen- eral’s report12 on children’s mental health notes that youth with comorbidity may be arrested because our fragmented mental health system has little to offer them. Re-

ORIGINAL ARTICLE

From the Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University (Drs Abram, Teplin, and McClelland), and Children’s Memorial Hospital (Dr Dulcan), Chicago, Ill.

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lated research suggests that ADM comorbidity among ju- venile detainees is common. Comorbidity is prevalent among youth in the community,13-16 adolescent treat- ment samples,17,18 and adult jail detainees.19,20 Rates of comorbidity among detained adolescents may be even higher than rates among detained adults.15,21,22

Despite its importance, there have been few empiri- cal studies of ADM comorbidity among juvenile detain- ees and no large-scale investigations, to our knowledge.23

Three studies found high rates of comorbidity24-26; how- ever, their samples were too small to estimate its true preva- lence or how patterns of comorbidity vary by sex, race/ ethnicity and age.

Data on ADM comorbidity among juvenile detain- ees are needed for 2 reasons:

1. To improve treatment of detained youth. De- tention centers are legally mandated to treat detainees with major mental disorders.27 However, treating detain- ees who have ADM comorbidity is far more complex than treating youth who have only one disorder.28,29 Sound epi- demiologic data on comorbidity will help us target youth with the most common diagnostic profiles.

2. To improve treatment for high-risk youth in the community. Although committed (sentenced) juve- niles stay an average of 5 months,5 juveniles in deten- tion have an average stay of 2 weeks.5 Moreover, many high-risk youth (eg, substance abusers, abused and ne- glected youth) eventually cycle through the juvenile jus- tice system. Without treatment, disorders are likely to persist and worsen, contributing to negative social out- comes and recidivism.30 Data on ADM comorbidity among detainees are needed to develop more effective interven- tions for high-risk youth in the community and to tailor services for special populations, such as females and mi- norities.

We present findings on the prevalence and pat- terns of ADM comorbidity from the Northwestern Juve- nile Project, a large-scale study of psychiatric disorders in detained youth.

METHODS

PARTICIPANTS AND SAMPLING PROCEDURES

Participants were 1829 male and female youth, 10 to 18 years old, randomly sampled at intake into the Cook County Juve- nile Temporary Detention Center (CCJTDC) from November 20, 1995, through June 14, 1998. The sample was stratified by sex, race/ethnicity (African American, non-Hispanic white, His- panic), age (10-13 years or �14 years), and legal status (pro- cessed as a juvenile or as an adult) to obtain enough partici- pants to compare key subgroups (eg, females, Hispanics, and younger children).

The CCJTDC receives approximately 8500 admissions each year (John Howard Association, Chicago, unpublished data, 1992) and is used solely for pretrial detention and for offend- ers sentenced for fewer than 30 days. All detainees younger than 17 years are held at the CCJTDC, including youth processed as adults (automatic transfers to adult court). Youth up to 21 years may be detained in the CCJTDC if they are being pros- ecuted for an arrest that occurred when they were younger than 17 years. Like juvenile detainees nationwide, approximately 90% of the CCJTDC detainees are male, and most are racial/ethnic

minorities.5 The CCJTDC’s population is 77.9% African Ameri- can, 5.6% non-Hispanic white, 16.0% Hispanic, and 0.5% other racial or ethnic groups. The age and offense distributions of the CCJTDC detainees are also similar to detained juveniles na- tionwide.5

We chose the detention center in Cook County (which includes Chicago and surrounding suburbs) for 3 reasons. First, nationwide, most juvenile detainees live in and are detained in urban areas.31 Second, Cook County is ethnically diverse and has the third largest Hispanic population in the United States.32

Studying Hispanics is important because they are the largest minority group in the United States33 and they are overrepre- sented in the justice systems.5 Third, the detention center’s size (daily census of approximately 650 youth and intake of 20 youth per day) ensured that enough participants would be available.

No single site can represent the entire country because dif- ferent jurisdictions have different options for diversion.34,35 Nev- ertheless, Illinois’ criteria for detaining juveniles are similar to those of other states.34 All states allow pretrial detention if the youth needs protection, is likely to flee, or is considered a dan- ger to the community.34,35

Detainees were eligible to participate, regardless of their psychiatric morbidity, state of alcohol or other drug intoxica- tion, or fitness to stand trial. Within each stratum of sex, race/ ethnicity, age, and legal status, we used a random-numbers table to select names from the CCJTDC’s intake log. Throughout the study, we tracked how many participants were needed to fill each cell. Project staff sampled the rarest categories first. When more than one participant was available for a cell, a random- numbers table was used. The final sampling fractions ranged from 0.018 to 0.689. (Additional information on the sample is available from the authors.)

Studying detained youth requires special procedures be- cause they are minors, they are detained, and many do not have a parent or guardian who can provide appropriate consent.36

Project staff approached participants in their units, explained the project, and assured them that anything they told us (ex- cept acute suicidal or homicidal risk) would be confidential. Participants signed an assent form (if they were younger than 18 years) or consent form (if they were 18 years or older). Fed- eral regulations allow parental consent to be waived if the re- search involves minimal risk (45 CFR §46.116(c), 45 CFR §46.116(d), and 45 CFR §46.408(c)).36,37 The Northwestern Uni- versity Institutional Review Board, the Centers for Disease Con- trol and Prevention Institutional Review Board, and the US Of- fice of Protection from Research Risks waived parental consent. However, as ethicists recommend, we nevertheless tried to con- tact parents to provide them an opportunity to decline partici- pation and to offer them additional information (45 CFR §46.116(d)[4]).38,39 Despite repeated attempts to contact the parent or guardian, none could be found for 43.8% of partici- pants. In lieu of parental consent, youth assent was overseen by a participant advocate who represented the interests of the participants. Federal regulations allow for a participant advo- cate when parental consent is not feasible (45 CFR §46.116(d)).38

Of the 2275 names selected, 4.2% (34 youth and 62 par- ents or guardians) refused to participate. There were no sig- nificant differences in refusal rates by sex, race/ethnicity, or age. Some youth processed as adults (automatic transfers) were coun- seled by their lawyers to refuse participation; in this stratum, the refusal rate was 7.1% (26 of 368 youth). Twenty-seven youth left the detention center before we could schedule an inter- view; 312 were not interviewed because they left while we were attempting to locate their caretakers for consent. Eleven oth- ers were excluded: 9 became physically ill during the inter- view and could not finish it, 1 was too cognitively impaired to be interviewed, and 1 appeared to be lying. The final sample size was 1829. This sample size allows us to reliably detect (ie,

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distinguish from zero) disorders that have a base rate in the general population of 1.0% or greater with a power of 0.80.40

The final sample comprised 1172 males (64.1%) and 657 females (35.9%), 1005 African Americans (54.9%), 296 non- Hispanic whites (16.2%), 524 Hispanics (28.7%), and 4 oth- ers (0.2%). The mean age of participants was 14.9 years, and the median age was 15 years.

Participants were interviewed in a private area, almost al- ways within 2 days of intake. Most interviews lasted 2 to 3 hours, depending on how many symptoms were reported. We used both male and female interviewers. Female participants were always interviewed by female interviewers. Interviewers were trained for at least a month; most had a master’s degree in psy- chology or an associated field and experience interviewing high- risk youth. One third of our interviewers were fluent in Span- ish. We maintained consistency throughout the study by monitoring scripted interviews with mock participants.

PSYCHIATRIC DIAGNOSES

We used the Diagnostic Interview Schedule for Children (DISC) Version 2.3,41,42 the most recent English and Spanish versions then available. The DISC 2.3 assesses the presence of DSM- III-R disorders in the past 6 months. The DISC is highly struc- tured, contains detailed symptom probes, has acceptable reli- ability and validity,41,43-46 and requires relatively brief training.

As in our previous work,8 2 of the diagnoses required spe- cial management. The DISC psychosis module, a broad symp- tom screen, does not generate a specific diagnosis. Instead, this module flags participants if they endorse any “possible” or “prob- able” pathognomonic symptoms or at least 3 nonpathogno- monic symptoms of psychosis. More than one quarter of our participants scored positive on this screen. To be conserva- tive, we counted these participants as psychotic only if (1) their symptoms persisted for at least 1 week; (2) they had not used alcohol, other drugs, or medication during this time; and (3) a project clinician (a child and adolescent psychiatrist or clini- cal psychologist) judged that the symptoms were “probably in- dicative of psychosis” after reviewing the protocol and discuss- ing the case with the interviewer. Twelve participants met these criteria. Project clinicians classified another 8 participants as psychotic who, although they denied symptoms, were judged by the research interviewer to have auditory hallucinations, de- lusions, or thought disorder during the interview.

Attention-deficit/hyperactivity disorder (ADHD) is diffi- cult to assess via self-report47 and is even more challenging to diagnose among delinquent youth.48 In addition, the DSM- III-R requires that symptoms of ADHD be present before the age of 7 years. In many studies, age of onset is reported by the caretaker. Most of our participants who reported symptoms of ADHD could not remember when these symptoms began. To avoid underreporting, we calculated rates of ADHD in 2 ways: in the conventional manner (requiring that symptoms be pres- ent before the age of 7 years) and counting the disorder as pres- ent regardless of the reported age of onset. (We present only the latter; the former rates are available from the authors.)

We determined rates of disorders in 2 ways. As most in- vestigators have done, we report rates using the standard DISC computer algorithms to calculate rates using DSM-III-R crite- ria. We also calculated more conservative (less inclusive) rates for diagnoses that met both DSM-III-R criteria and diagnosis- specific impairment criteria, reported by participants.41 Al- though youth are poor reporters of their own impairment,41,49

we calculated these latter rates because psychiatric diagnoses are best determined by the presence of both symptoms and func- tional impairment.41,50-52 These more conservative estimates, sub- stantially similar to those reported herein, are available from the authors.

STATISTICAL ANALYSIS

Because we stratified our sample by sex, race/ethnicity, age, and legal status, we weighted all prevalence estimates to reflect the distributions of these variables in the detention center’s popu- lation. All reported SEs and tests of significance have been cor- rected for design characteristics with Taylor series lineariza- tion.53,54 We used 2-tailed tests; our level of significance for all tests was .05. We report disorders for males and females sepa- rately, because combining them masks important differences.

RESULTS

COMORBIDITY OF PSYCHIATRIC DISORDERS

Specific Disorders

Significantly more females (56.5%) than males (45.9%) met criteria for 2 or more of the following disorders: ma- jor depressive, dysthymic, manic, psychotic, panic, sepa- ration anxiety, overanxious, generalized anxiety, obses- sive-compulsive, ADHD, conduct, oppositional defiant, alcohol, marijuana, and other substance (t1812=3.13, P=.002); 17.3% of females and 20.4% of males had only 1 disorder. (The DISC 2.3 did not include posttrau- matic stress disorder; posttraumatic stress disorder di- agnoses, available on a subsample, will be presented in future articles.) These analyses are available from the au- thors; analyses of single disorders are available else- where.8 Even after excluding conduct and substance use disorders, which are common among delinquent youth, significantly more females (33.6%) than males (24.2%) had 2 or more disorders (t1813=2.81, P=.005).

Types of Disorders

Figure 1 and Figure 2 show substantial comorbidity for females and males. (We omitted psychoses from this analy- sis because there were so few cases.) Patterns of overlap differ somewhat by sex. Nearly one third of females (29.5%) and males (30.8%) had both substance use disorders and

Anxiety 31.5%

Substance 44.5%

2.6%

2.0% 4.8%

6.7%

3.9%

2.0%

2.3%

4.9%

6.0%

14.0% 7.6%

9.6%

2.9%

ADHD or Behavioral

46.3%

None of the Listed Disorders

27.2%

Affective 26.4%

1.2% 2.2%

Figure 1. Comorbid types of disorder among females. ADHD indicates attention-deficit/hyperactivity disorder.

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ADHD or behavioral disorders; approximately half of these also had anxiety disorders, affective disorders, or both.

Significantly more females (47.8%) than males (41.6%) had 2 or more of the following types of disor-

ders: affective, anxiety, substance use, and ADHD or be- havioral (t1813=2.56, P=.02). Again, even when exclud- ing conduct and substance use disorders, significantly more females (25.1%) than males (18.0%) had 2 or more types of disorders (t1812=2.64, P=.01). Significantly more females (22.5%) than males (17.2%) had 3 or more types of disorders (t1813=2.09, P=.04). These analyses are avail- able from the authors.

Racial/Ethnic Differences. Among females, signifi- cantly more non-Hispanic whites (63.1%) had 2 or more types of disorders than African Americans (42.6%; t639= 3.21, P = .002). Among males, signifi- cantly more non-Hispanic whites (53.1%) had 2 or more types of disorders than African Americans (40.7%; t1142=3.92, P�.001). These analyses are avail- able from the authors.

Table 1 and Table 2 give the prevalence of comorbidity by race/ethnicity among females and males with affective, substance use, anxiety, and ADHD or behavioral disorders. The odds of having comorbid disorders are higher than expected by chance for most racial/ethnic subgroups, except when base rates of disorders were already high or when cell sizes were small.

Anxiety 21.1%

Substance 49.8%

6.9%

2.1% 2.1%

4.3%

16.4% 6.7%

3.2%

1.4%

14.6%

1.1%

1.2% 2.0% 0.7% 1.6%

1.0%

ADHD or Behavioral

41.7%

None of the Listed Disorders

34.8%

Affective 17.9%

Figure 2. Comorbid types of disorder among males. ADHD indicates attention-deficit/hyperactivity disorder.

Table 1. Prevalence and Odds Ratios (ORs) of Comorbidity Among Female Juvenile Detainees With Affective, Substance Use, Anxiety, and ADHD or Behavioral Disorders by Race/Ethnicity*

Disorder

Total (n = 656)

African American (n = 430)

Non-Hispanic White (n = 89)

Hispanic (n = 136)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Affective disorders (n = 144) Substance use disorders 56.4 (47.8-64.7) 1.8† (1.2-2.6) 51.0 (40.6-61.2) 1.6 (1.0-2.5) 60.9 (37.5-80.2) 1.0 (0.3-3.2) 75.9 (57.8-87.8) 4.5† (1.7-12.2) Anxiety disorders 64.2 (55.7-71.9) 6.3‡ (4.1-9.6) 63.4 (52.9-72.8) 5.7‡ (3.5-9.5) 60.9 (37.5-80.2) 6.2† (2.0-19.3) 69.4 (50.9-83.2) 9.2‡ (3.4-25.1) ADHD or behavioral

disorders 71.2 (62.4-78.6) 3.9‡ (2.5-6.1) 70.9 (60.7-79.4) 5.0‡ (3.0-8.4) 70.8 (46.2-87.3) 1.7 (0.5-5.6) 72.3 (44.7-89.4) 2.8 (0.8-10.3)

Substance use disorders (n = 303)

Affective disorders 25.7 (20.8-31.3) 1.8† (1.2-2.6) 25.8 (19.8-32.8) 1.6 (1.0-2.5) 18.8 (10.3-31.8) 1.0 (0.3-3.2) 30.9 (19.0-46.0) 4.5† (1.7-12.2) Anxiety disorders 34.1 (28.5-40.1) 1.3 (0.9-1.9) 36.6 (29.8-44.1) 1.5 (1.0-2.3) 22.6 (12.9-36.4) 0.5 (0.2-1.4) 35.2 (22.5-50.3) 1.6 (0.6-4.4) ADHD or behavioral

disorders 65.2 (59.0-70.9) 4.4‡ (3.1-6.4) 60.3 (52.9-67.3) 4.2‡ (2.8-6.3) 79.6 (66.3-88.5) 7.7‡ (2.7-22.2) 69.0 (50.5-82.9) 3.2§ (1.1-9.2)

Anxiety disorders (n = 206) Affective disorders 42.8 (35.8-50.1) 6.3‡ (4.1-9.6) 42.4 (34.2-50.9) 5.7‡ (3.5-9.5) 41.1 (24.4-60.2) 6.2† (2.0-19.3) 45.4 (27.8-64.3) 9.2‡ (3.4-25.1) Substance use disorders 49.8 (42.5-57.1) 1.3 (0.9-1.9) 48.5 (40.1-57.1) 1.5 (1.0-2.3) 47.8 (30.0-66.2) 0.5 (0.2-1.4) 56.0 (35.9-74.3) 1.6 (0.6-4.4) ADHD or behavioral

disorders 58.9 (51.6-66.0) 2.2‡ (1.5-3.2) 57.9 (49.4-66.0) 2.8‡ (1.8-4.3) 62.5 (43.2-78.6) 1.1 (0.4-3.2) 60.8 (39.8-78.4) 1.6 (0.6-4.5)

ADHD or behavioral disorders (n = 317)

Affective disorders 32.1 (26.9-37.7) 3.9‡ (2.5-6.1) 36.9 (30.0-44.3) 5.0‡ (3.0-8.4) 21.2 (12.2-34.2) 1.7 (0.5-5.6) 26.4 (17.6-37.6) 2.8 (0.8-10.3) Substance use

disorders 64.7 (58.6-70.4) 4.4‡ (3.1-6.4) 62.3 (54.9-69.3) 4.2‡ (2.8-6.3) 78.5 (65.3-87.6) 7.7‡ (2.7-22.2) 60.8 (45.6-74.2) 3.2§ (1.1-9.2)

Anxiety disorders 39.9 (34.2-45.9) 2.2‡ (1.5-3.2) 44.9 (37.6-52.4) 2.8‡ (1.8-4.3) 28.6 (17.6-42.9) 1.1 (0.4-3.2) 33.9 (22.5-47.5) 1.6 (0.6-4.5)

Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval. *Participants may have more than one disorder. Each cell is weighted to reflect the population of the detention center. Statistically significant ORs indicate that

comorbidity exceeds the level expected by chance, given the prevalence of that disorder in the sample. Affective, substance use, anxiety, and ADHD or behavioral disorders are missing for 1 participant. This participant is excluded from all analyses in this table. All available data from the 656 remaining participants are used for each cell. Of these, 3 participants are missing for affective disorders, 13 are missing for substance use disorders, and 8 are missing for anxiety disorders. Because 1 participant of “other” race/ethnicity is included only in the Total column, racial/ethnic subcategories sum to 655, not 656.

†P�.01. ‡P�.001. §P�.05.

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Age Differences. Significantly more males aged 16 years and older had 2 or more types of disorders (41.2%) than males aged 13 years and younger (27.0%; t1158=3.57, P�.001). Similarly, significantly more males aged 14 and 15 years had 2 or more types of disorders (45.3%) than males aged 13 years and younger (t1158=3.75, P�.001). Among females, there were no significant age differ- ences in the overall prevalence of types of disorder. These analyses are available from the authors.

Table 3 and Table 4 give the prevalence of co- morbidity by age among females and males with affec- tive, substance use, anxiety, and ADHD or behavioral dis- orders. These tables show that the odds of having comorbid disorders are higher than expected by chance for most age groups.

SUBSTANCE USE DISORDERS AND MAJOR MENTAL DISORDERS

More than one tenth of males (10.8%) and 13.7% of fe- males had both a major mental disorder (psychosis, manic

episode, or major depressive episode) and a substance use disorder. We examined these disorders in depth because detention centers are mandated to treat major mental dis- orders and because comorbidity complicates treatment.

Rates of Substance Use Disorders Among Youth With Major Mental Disorders

What are the odds that participants with major mental disorders had co-occurring substance use disorders? Table 5 shows that compared with participants with no major mental disorder (the residual category), both fe- males and males with any major mental disorder had sig- nificantly greater odds (1.8-4.1) of having substance use disorders. We also examined 2 subcategories of major mental disorder: psychosis or manic episode (combined because there were too few cases to analyze separately and because these disorders present similarly) and ma- jor depressive episode. Most odds ratios for these sub- categories were statistically significant, except when cell sizes were small.

Table 2. Prevalence and Odds Ratios (ORs) of Comorbidity Among Male Juvenile Detainees With Affective, Substance Use, Anxiety, and ADHD or Behavioral Disorders by Race/Ethnicity*

Disorder

Total (n = 1170)

African American (n = 574)

Non-Hispanic White (n = 207)

Hispanic (n = 386)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Affective disorders (n = 150)

Substance use disorders

72.9 (59.7-83.0) 3.1† (1.7-5.8) 74.8 (58.7-86.1) 3.7‡ (1.7-8.0) 58.2 (20.4-88.4) 0.9 (0.2-5.2) 68.9 (43.8-86.3) 2.1 (0.7-6.2)

Anxiety disorders 71.2 (58.1-81.6) 16.4† (8.5-31.8) 69.3 (52.9-82.0) 15.1† (6.8-33.3) 68.2 (38.5-88.0) 19.3† (5.1-73.4) 81.0 (66.1-90.4) 25.8† (10.2-64.8) ADHD or behavioral

disorders 81.5 (70.0-89.3) 7.8† (4.0-15.3) 83.1 (68.8-91.7) 9.6‡ (4.1-22.3) 81.1 (55.3-93.7) 2.9 (0.8-10.5) 74.1 (48.4-89.7) 4.7‡ (1.5-14.8)

Substance use disorders (n = 571)

Affective disorders 21.0 (15.8-27.3) 3.1† (1.7-5.8) 21.7 (15.4-29.6) 3.7‡ (1.7-8.0) 13.6 (8.4-21.2) 0.9 (0.2-5.2) 21.0 (12.6-32.8) 2.1 (0.7-6.2) Anxiety disorders 28.9 (23.0-35.6) 2.5† (1.5-4.1) 29.1 (22.0-37.4) 2.7‡ (1.4-4.9) 16.6 (10.8-24.6) 0.8 (0.2-2.7) 31.5 (21.5-43.5) 2.2 (0.9-5.0) ADHD or behavioral

disorders 62.0 (55.0-68.5) 5.7† (3.7-8.8) 61.0 (52.3-69.0) 5.9† (3.5-10.1) 72.2 (63.3-79.6) 2.6§ (1.2-5.4) 61.7 (50.4-71.9) 5.6† (2.7-11.5)

Anxiety disorders (n = 230)

Affective disorders 47.8 (37.4-58.3) 16.4† (8.5-31.8) 46.5 (34.1-59.4) 15.1† (6.8-33.3) 52.6 (26.1-77.7) 19.3† (5.1-73.4) 54.6 (37.1-71.1) 25.8† (10.2-64.8) Substance use

disorders 67.4 (56.8-76.5) 2.5† (1.5-4.1) 67.8 (54.8-78.5) 2.7‡ (1.4-4.9) 53.7 (25.1-80.1) 0.8 (0.2-2.7) 68.0 (49.7-82.1) 2.2 (0.9-5.0)

ADHD or behavioral disorders

68.4 (57.9-77.3) 4.0† (2.4-6.6) 67.3 (54.3-78.1) 4.1† (2.2-7.5) 78.4 (56.8-90.9) 2.5 (0.9-7.2) 69.0 (51.0-82.6) 4.1† (1.8-9.3)

ADHD or behavioral disorders (n = 524)

Affective disorders 27.6 (21.3-34.9) 7.8† (4.0-15.3) 28.7 (20.9-37.9) 9.6† (4.1-22.3) 17.9 (8.1-35.1) 2.9 (0.8-10.5) 28.4 (18.5-41.0) 4.7‡ (1.5-14.8) Substance use

disorders 73.8 (66.8-79.8) 5.7† (3.7-8.8) 73.8 (64.8-81.1) 5.9† (3.5-10.1) 68.4 (55.0-79.2) 2.6§ (1.2-5.4) 76.6 (65.4-85.0) 5.6† (2.7-11.5)

Anxiety disorders 34.7 (27.9-42.1) 4.0† (2.4-6.6) 34.6 (26.3-44.0) 4.1† (2.2-7.5) 22.7 (12.1-38.4) 2.5 (0.9-7.2) 39.9 (28.9-52.0) 4.1† (1.8-9.3)

comorbidity exceeds the level expected by chance, given the prevalence of that disorder in the sample. Affective, substance use, anxiety, and ADHD or behavioral disorders are missing for 2 participants. These 2 participants are excluded from all analyses in this table. All available data from the 1170 remaining participants are used for each cell. Of these, 13 participants are missing for affective disorders, 16 are missing for substance use disorders, 9 are missing for anxiety disorders, and 1 is missing for ADHD or behavioral disorders. Because 3 participants of “other” race/ethnicity are included only in the Total column, racial/ethnic subcategories sum to 1167, not 1170.

†P�.001. ‡P�.01. §P�.05.

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Sex Differences. Table 5 shows that among youth with major mental disorders (n=305), more than half of fe- males and nearly three quarters of males had any sub- stance use disorder. Differences between females and males (and the corresponding odds ratios) were not sta- tistically significant (t1784=1.92, P=.055; this analysis is available from the authors).

Racial/Ethnic Differences. Among females with major mental disorders, significantly more non-Hispanic whites and Hispanics had both drug and alcohol use disorders than did African Americans (50.0% and 43.4%, respec- tively, vs 21.3%); significantly more Hispanic females had alcohol use disorders than did African Americans (52.5% vs 26.6%). Among males with major mental disorders, there were no significant differences by race/ethnicity. These analyses are available from the authors.

Age Differences. Among females with major mental dis- orders, there were no significant differences by age. Among males, nearly 90% aged 16 years and older who had a ma- jor mental disorder also had a substance use disorder,

significantly more than males 10 to 13 years and 14 to 15 years of age (55.2% and 60.6%, respectively). These analyses are available from the authors.

Rates of Major Mental Disorder Among Youth With Substance Use Disorders

What are the odds that participants with substance use disorders had co-occurring major mental disorders? Table 6 shows that compared with participants with no substance use disorder (the residual category), both fe- males and males with any substance use disorder had sig- nificantly greater odds of having any major mental dis- order and its subcategory, major depressive episode. Among males, odds ratios for psychosis or a manic epi- sode were significant for some subcategories of sub- stance use disorders.

Table 6 also shows that nearly 30% of females and more than 20% of males with any substance use disor- der also had a major mental disorder. Among youth with both drug and alcohol use disorders, more than one third of females and more than one quarter of males had a ma-

Table 3. Prevalence and Odds Ratios (ORs) of Comorbidity Among Female Juvenile Detainees With Affective, Substance Use, Anxiety, and ADHD or Behavioral Disorders by Age*

Disorder

Total (n = 656)

Age 10-13 y (n = 56)

Age 14-15 y (n = 353)

Age �16 y (n = 247)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Affective disorders (n = 144)

Substance use disorders

56.4 (47.8-64.7) 1.8† (1.2-2.6) 45.4 (18.9-74.9) 2.8 (0.6-12.7) 60.4 (48.6-71.0) 2.2† (1.3-3.8) 52.4 (38.7-65.7) 1.1 (0.6-2.2)

Anxiety disorders 64.2 (55.7-71.9) 6.3‡ (4.1-9.6) 61.4 (30.1-85.4) 4.6 (0.9-23.5) 69.4 (58.1-78.7) 7.8‡ (4.4-13.9) 56.5 (42.5-69.5) 4.5‡ (2.3-8.7) ADHD or behavioral

disorders 71.2 (62.4-78.6) 3.9‡ (2.5-6.1) 88.1 (48.1-98.3) 12.9§ (1.4-119.4) 75.1 (62.6-84.5) 4.2‡ (2.2-8.0) 61.8 (47.7-74.2) 3.0† (1.5-5.8)

Substance use disorders (n = 303)

Affective disorders 25.7 (20.8-31.3) 1.8† (1.2-2.6) 25.3 (10.4-49.7) 2.8 (0.6-12.7) 29.3 (22.3-37.4) 2.2† (1.3-3.8) 21.1 (14.6-29.5) 1.1 (0.6-2.2) Anxiety disorders 34.1 (28.5-40.1) 1.3 (0.9-1.9) 20.9 (7.7-45.5) 0.6 (0.1-2.4) 41.4 (33.4-49.8) 2.0† (1.2-3.3) 26.3 (18.9-35.2) 0.8 (0.4-1.4) ADHD or behavioral

disorders 65.2 (59.0-70.9) 4.4‡ (3.1-6.4) 72.4 (47.6-88.4) 6.4† (1.8-22.9) 71.9 (63.3-79.1) 5.9‡ (3.5-9.9) 55.4 (45.4-65.1) 3.3‡ (1.8-5.9)

Anxiety disorders (n = 206)

Affective disorders 42.8 (35.8-50.1) 6.3‡ (4.1-9.6) 33.4 (13.9-60.8) 4.6 (0.9-23.5) 46.3 (36.8-56.1) 7.8‡ (4.4-13.9) 39.2 (28.7-50.8) 4.5‡ (2.3-8.7) Substance use

disorders 49.8 (42.5-57.1) 1.3 (0.9-1.9) 21.8 (7.4-49.4) 0.6 (0.1-2.4) 57.0 (47.0-66.5) 2.0† (1.2-3.3) 44.3 (33.4-55.8) 0.8 (0.4-1.4)

ADHD or behavioral disorders

58.9 (51.6-66.0) 2.2‡ (1.5-3.2) 67.5 (39.6-86.8) 3.7 (1.0-13.4) 61.8 (51.6-71.1) 2.2† (1.3-3.6) 52.1 (40.7-63.3) 2.0§ (1.1-3.6)

ADHD or behavioral disorders (n = 317)

Affective disorders 32.1 (26.9-37.7) 3.9‡ (2.5-6.1) 29.9 (15.2-50.3) 12.9§ (1.4-119.4) 33.7 (27.0-41.1) 4.2‡ (2.2-8.0) 29.9 (21.4-40.0) 3.0† (1.5-5.8) Substance use

disorders 64.7 (58.6-70.4) 4.4‡ (3.1-6.4) 45.9 (26.3-66.8) 6.4† (1.8-22.9) 66.3 (58.5-73.2) 5.9‡ (3.5-9.9) 66.9 (55.9-76.4) 3.3‡ (1.8-5.9)

Anxiety disorders 39.9 (34.2-45.9) 2.2‡ (1.5-3.2) 42.1 (22.8-64.2) 3.7 (1.0-13.4) 41.6 (34.4-49.2) 2.2† (1.3-3.6) 36.4 (26.9-47.1) 2.0§ (1.1-3.6)

†P�.01. ‡P�.001. §P�.05.

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jor mental disorder. There were no significant differ- ences by sex, race/ethnicity, or age (analyses are avail- able from the authors).

RELATIVE ONSET OF MAJOR MENTAL DISORDERS AND SUBSTANCE USE DISORDERS

One quarter of both females (27.2%) and males (25.0%) reported that their major mental disorder preceded their substance use disorder by more than 1 year. One tenth of females (9.8%) and 20.7% of males reported that their sub- stance use disorder preceded their major mental disorder by more than 1 year. Nearly two thirds of females (63.0%) and 54.3% of males developed their disorders within the same year. Findings were similar for subcategories of dis- orders. (Analyses are available from the authors.)

COMMENT

Psychiatric disorders are a major health problem among detained youth, exacerbated by high rates of comorbid- ity. Can we estimate how many youth with comorbidity are processed through detention nationwide? Precise es- timates are difficult because our data reflect only one county and because the Department of Justice tabulates only numbers of admissions to detention annually, not

individuals.5,55 To the extent that Cook County is typi- cal, our findings suggest that on an average day, there may be as many as 47000 detained youth who have 2 or more types of psychiatric disorder; more than 12000 have both a major mental disorder and a substance use dis- order. The juvenile courts, which the Department of Jus- tice estimates manage 1100000 individuals per year5,55

(Melissa Sickmund, PhD, Office of Juvenile Justice and Deliquency Prevention, e-mail communication, Decem- ber 18, 2002), may process as many as 550000 youth with comorbidity per year.

Not surprisingly, among the disorders assessed, de- tainees are more likely to have substance use plus ADHD or behavioral disorders than any other combination. Half of these detainees also have an affective or anxiety dis- order. Among adolescent substance users, these inter- nalizing disorders are associated with more severe sub- stance use56,57 but better treatment outcomes.58 Our findings suggest that we must reexamine how we man- age substance use and behavioral problems in our chil- dren. Early onset of these disorders predicts worse out- comes; hence, early intervention is critical.48,59,60

Psychiatric care has a chance to succeed where crimi- nalization never can.

It is difficult to compare our findings with commu- nity studies because few are comparable.61 Also, rates vary

Table 4. Prevalence and Odds Ratios (ORs) of Comorbidity Among Male Juvenile Detainees With Affective, Substance Use, Anxiety, and ADHD or Behavioral Disorders by Age*

Disorder

Total (n = 1170)

Age 10-13 y (n = 315)

Age 14-15 y (n = 361)

Age �16 y (n = 494)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Prevalence of Comorbidity, % (95% CI)

OR (95% CI)

Affective disorders (n = 150)

Substance use disorders

72.9 (59.7-83.0) 3.1† (1.7-5.8) 42.6 (20.0-68.8) 2.3 (0.7-7.0) 60.8 (39.7-78.5) 1.6 (0.7-4.0) 89.3 (74.1-96.0) 9.0† (2.8-29.1)

Anxiety disorders 71.2 (58.1-81.6) 16.4† (8.5-31.8) 84.7 (64.7-94.3) 43.8† (13.6-141.2) 73.7 (52.7-87.6) 18.2† (6.5-51.1) 66.8 (47.2-82.0) 13.0† (5.0-34.0) ADHD or behavioral

disorders 81.5 (70.0-89.3) 7.8† (4.0-15.3) 67.4 (42.2-85.3) 4.9‡ (1.7-14.4) 90.2 (74.0-96.8) 14.6† (4.6-46.6) 75.3 (55.5-88.2) 5.4† (2.0-14.3)

Substance use disorders (n = 571)

Affective disorders 21.0 (15.8-27.3) 3.1† (1.7-5.8) 17.4 (10.5-27.5) 2.3 (0.7-7.0) 18.8 (11.6-29.1) 1.6 (0.7-4.0) 23.0 (15.8-32.3) 9.0† (2.8-29.1) Anxiety disorders 28.9 (23.0-35.6) 2.5† (1.5-4.1) 29.9 (20.6-41.4) 2.4§ (1.1-5.2) 29.4 (20.3-40.5) 2.2§ (1.0-5.0) 28.4 (20.5-37.9) 3.0‡ (1.4-6.7) ADHD or behavioral

disorders 62.0 (55.0-68.5) 5.7† (3.7-8.8) 62.4 (50.9-72.7) 5.5† (2.9-10.5) 63.2 (51.9-73.1) 4.8† (2.4-9.3) 61.0 (51.3-69.9) 7.2† (3.6-14.5)

Anxiety disorders (n = 230)

Affective disorders 47.8 (37.4-58.3) 16.4† (8.5-31.8) 48.0 (29.8-66.7) 43.8† (13.6-141.2) 50.2 (33.8-66.6) 18.2† (6.5-51.1) 45.4 (30.8-60.7) 13.0† (5.0-34.0) Substance use

disorders 67.4 (56.8-76.5) 2.5† (1.5-4.1) 41.1 (25.6-58.7) 2.4§ (1.1-5.2) 65.7 (47.9-80.0) 2.2§ (1.0-5.0) 73.9 (58.5-85.0) 3.0‡ (1.4-6.7)

ADHD or behavioral disorders

68.4 (57.9-77.3) 4.0† (2.4-6.6) 57.9 (40.3-73.7) 3.6† (1.7-7.8) 74.2 (56.9-86.2) 5.1† (2.2-11.7) 64.8 (48.9-77.9) 3.4‡ (1.6-7.3)

ADHD or behavioral disorders (n = 524)

Affective disorders 27.6 (21.3-34.9) 7.8† (4.0-15.3) 21.7 (10.5-39.3) 4.9‡ (1.7-14.4) 31.1 (21.2-43.1) 14.6† (4.6-46.6) 25.3 (17.0-35.9) 5.4† (2.0-14.3) Substance use

disorders 73.8 (66.8-79.8) 5.7† (3.7-8.8) 49.1 (37.1-61.2) 5.5† (2.9-10.5) 71.5 (59.7-80.9) 4.8† (2.4-9.3) 80.1 (70.0-87.4) 7.2† (3.6-14.5)

Anxiety disorders 34.7 (27.9-42.1) 4.0† (2.4-6.6) 33.1 (20.8-48.2) 3.6† (1.7-7.8) 37.6 (27.0-49.6) 5.1† (2.2-11.7) 32.2 (23.0-43.0) 3.4‡ (1.6-7.3)

comorbidity exceeds the level expected by chance, given the prevalence of that disorder in the sample. Affective, substance use, anxiety, and ADHD or behavioral disorders are missing for 2 participants. These 2 participants are excluded from all analyses in this table. All available data from the 1170 remaining participants are used for each cell. Of these, 13 participants are missing for affective disorders, 16 are missing for substance use disorders, 9 are missing for anxiety disorders, and 1 is missing for ADHD or behavioral disorders.

†P�.001. ‡P�.01. §P�.05.

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widely, depending on the sample, method, source of data (subject or collaterals), and whether functional impair- ment was required.50 However, even after excluding con- duct and substance use disorders (expected to be high in detained populations), our rates are substantially higher than those reported in community samples.28,62-65

Mental health professionals who screen incoming detainees should anticipate that at least 1 in 10 youth will have a major mental disorder (psychosis, manic epi- sode, or major depressive episode) and a substance use disorder, rates as high as adult detainees.19,20 Psychia- trists who treat detained youth with major mental dis- orders should expect that as many as three quarters of males and half of females will also have substance use disorders. These clients are a challenge to psychiatry; they are more recalcitrant to traditional treatments, they are more likely to be treatment failures, and they are more difficult to place because their needs cross traditional boundaries between service sectors.22,63,66-68 Conversely, addiction psychiatrists should anticipate that more than one fifth of detainees who abuse or are dependent on drugs will also have a major mental disorder, rates compa- rable to clinical17,69,70 and correctional71,72 samples.

Females had higher rates of comorbidity than males. These sex differences, similar to our analyses of specific

disorders,8 parallel prior studies of adult73,74 and juve- nile detainees75 and may reflect the different ways that delinquent acts by females and males are managed. Crimi- nologists suggest that females are treated more leniently than males for similar offenses, especially at the earliest stages of processing: arrests, station adjustments, and ini- tial court hearings.76 Thus, those females who are de- tained may be more dysfunctional and have more prob- lem behaviors and more disorders than their male counterparts.75

Non-Hispanic whites had the highest rate of comor- bidity; African Americans had the lowest. Again, these racial/ ethnic differences, similar to our analyses of specific dis- orders,8 parallelprior studiesof adultdetainees.19,20 Although minorities have lower rates of comorbidity than other youth, they make up two thirds of youth in the juvenile justice system.5 Thus, more minority adolescents will require ser- vices for comorbidity than nonminorities.

Although comorbidity of major mental and sub- stance use disorders is more prevalent among older de- tainees, we found no dominant sequence of onset. This suggests that there are multiple pathways to disorders. Thus, we cannot target interventions to a single point of vulnerability. Detainees with the same combination of disorders may require different treatments, depending on

Table 5. Prevalence and Odds Ratios (ORs) of Substance Use Disorders Among Juvenile Detainees With Major Mental Disorders*

Variable

No Major Mental Disorder (n = 1501),

% (95% CI)

Major Mental Disorder (n = 305)

Any Major Mental Disorder

(n = 305)

Psychosis or Manic Episode

(n = 54)

Major DepressiveEpisode

(n = 271)

Prevalence, % (95% CI)

OR (95% CI)

Prevalence, % (95% CI)

OR (95% CI)

Prevalence, % (95% CI)

OR (95% CI)

Females (n = 655)† No substance use disorder

(n = 340) 56.9 (52.4-61.2) 41.6 (32.2-51.7) 52.1 (29.9-73.5) 40.3 (30.6-50.9)

Any substance use disorder (n = 303)

43.1 (38.8-47.6) 58.4 (48.3-67.8) 1.8§ (1.2-2.9) 47.9 (26.5-70.1) 1.2 (0.5-3.2) 59.7 (49.1-69.4) 1.9§ (1.2-3.1)

Drug use disorder (n = 272) 38.8 (34.6-43.2) 52.9 (42.4-63.2) 1.8� (1.1-2.8) 43.5 (23.1-66.4) 1.2 (0.5-3.2) 54.4 (43.4-64.9) 1.9� (1.9-3.0) Alcohol use disorder (n = 171) 22.7 (19.2-26.5) 38.8 (28.0-51.0) 2.2§ (1.3-3.7) 29.4 (13.4-52.9) 1.4 (0.5-3.9) 39.4 (27.9-52.2) 2.2§ (2.2-3.9) Both drug and alcohol use

disorders (n = 140) 18.7 (15.5-22.4) 33.7 (22.7-46.9) 2.2§ (1.2-4.0) 25.0 (10.5-48.7) 1.4 (0.5-4.2) 34.5 (22.8-48.3) 2.3§ (2.3-4.2)

Males (n = 1167)‡ No substance use disorder

(n = 583) 53.4 (48.2-58.6) 26.2 (16.5-39.0) 28.2 (10.3-57.4) 28.2 (17.5-42.1)

Any substance use disorder (n = 571)

46.6 (41.4-51.8) 73.8 (61.0-83.5) 3.2¶ (1.7-6.0) 71.8 (42.6-89.7) 2.9 (0.8-10.2) 71.8 (57.9-82.5) 2.9§ (2.9-5.6)

Drug use disorder (n = 514) 42.9 (37.8-48.1) 59.6 (46.4-71.6) 2.0� (1.1-3.5) 71.4 (42.4-89.4) 3.3 (1.0-11.5) 56.0 (42.0-69.1) 1.7 (1.7-3.1) Alcohol use disorder (n = 295) 21.0 (17.1-25.5) 52.4 (39.7-64.8) 4.1¶ (2.3-7.4) 55.7 (29.6-78.9) 4.7§ (1.5-14.5) 51.8 (38.2-65.1) 4.0¶ (4.0-7.4) Both drug and alcohol use

disorders (n = 238) 17.4 (13.8-21.8) 38.4 (26.8-51.5) 2.9¶ (1.6-5.4) 56.2 (29.7-79.6) 6.1§ (1.9-19.2) 35.9 (24.0-49.8) 2.6§ (1.4-5.0)

Abbreviation: CI, confidence interval. *Major mental disorder includes psychosis, manic episode, and major depressive episode. Participants may have more than one substance use disorder and more

than one major mental disorder. Each cell is weighted to reflect the population of the detention center. Statistically significant ORs indicate that comorbidity exceeds the level expected by chance, given the prevalence of that disorder in the sample. Psychosis, manic episode, major depressive episode, drug use disorder, and alcohol use disorder are missing for 3 of the 1829 participants; in addition, drug use disorder and alcohol use disorder are missing for 4 other participants. These 7 participants are excluded from all analyses in this table. All available data from the 1822 remaining participants are used for each cell. Because 16 participants are missing the diagnosis of any major mental disorder, this column and the “No Major Mental Disorder” column sum to 1806, not 1822.

†Substance use disorder is missing for 12 females. ‡Substance use disorder is missing for 13 males. §P�.01. �P�.05. ¶P�.001.

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their etiology.14 Psychiatrists should assess the se- quence and interplay of symptoms to determine the best treatments for youth with comorbidity.

LIMITATIONS

This study has several limitations. Because our findings are drawn from a single site, they may pertain only to youth in detention centers with similar demographic com- position. Rates of comorbidity might differ if diagnoses were based on DSM-IV instead of DSM-III-R. Finally, our rates may underestimate the true prevalence of comor- bidity among youth in the entire juvenile justice system for 3 reasons. First, our sample included only detainees; it excluded youth who were not detained because their charges were less serious, because they were immedi- ately released at the police station or detention center, or because they were referred immediately into the men- tal health system. Second, because it was not feasible to

interview caretakers (few would have been available), our data are subject to the reliability and validity of the youth’s self-report. Underreporting of symptoms by youth is en- demic, especially for disruptive behavior disorder.47 Third, estimates of comorbidity would have been higher had we included additional disorders, such as posttraumatic stress, eating, dissociative, and somatoform disorders. Despite these limitations, our findings have implications for men- tal health treatment and research.

IMPLICATIONS FOR TREATMENT

Our findings may reflect our nation’s increasingly puni- tive approaches to delinquency and substance abuse.4,23,77

Our findings may also reflect failures of the social ser- vice systems.78 A recent report to Congress79 and the Sur- geon General’s report12 on children’s mental health have highlighted the paucity of mental health services avail- able to youth with comorbidity. Because the fragmented

Table 6. Prevalence and Odds Ratios (ORs) of Major Mental Disorders Among Juvenile Detainees With Substance Use Disorders*

Variable

No Substance Use Disorder

(n = 923), % (95% CI)

Substance Use Disorder (n = 874)

Any Substance Use Disorder

(n = 874)

Drug Use Disorder (n = 786)

Alcohol Use Disorder (n = 466)

Both Drug and Alcohol Use Disorders

(n = 378)

Prevalence, % (95% CI)

OR (95% CI)

Prevalence, % (95% CI)

OR (95% CI)

Prevalence, % (95% CI)

OR (95% CI)

Prevalence, % (95% CI)

OR (95% CI)

Females (n = 655)† No major

mental disorder (n = 506)

81.7 (77.1-85.4)

70.6 (62.9-77.4)

70.6 (62.2-77.8)

65.6 (54.0-75.6)

64.4 (51.0-75.9)

Any major mental disorder (n = 146)

18.3 (14.6-22.9)

29.4 (22.6-37.1)

1.8§ (1.2-2.9)

29.4 (22.2-37.8)

1.9¶ (1.2-3.0)

34.4 (24.4-46.0)

2.3§ (1.3-4.1)

35.6 (24.1-49.0)

2.5§ (1.3-4.6)

Psychosis or manic episode (n = 18)

2.7 (1.4-5.1)

2.8 (1.5-5.4)

1.1 (0.4-2.7)

2.9 (1.4-5.7)

1.1 (0.4-2.8)

3.1 (1.4-6.8)

1.1 (0.4-3.3)

3.2 (1.3-7.6)

1.2 (0.4-3.7)

Major depressive episode (n = 135)

16.5 (12.9-20.8)

27.7 (21.0-35.4)

1.9§ (1.2-3.1)

27.8 (20.7-36.3)

2.0§ (1.2-3.2)

32.2 (22.3-44.1)

2.4§ (1.3-4.3)

33.5 (22.1-47.2)

2.6§ (1.3-4.9)

Males (n = 1167)‡ No major

mental disorder (n = 995)

92.3 (87.6-95.3)

78.6 (72.4-83.8)

81.0 (74.7-86.0)

70.0 (60.3-78.1)

72.9 (62.4-81.4)

Any major mental disorder (n = 159)

7.7 (4.7-12.4)

21.4 (16.2-27.6)

3.2� (1.7-6.0)

19.0 (14.0-25.3)

2.8§ (1.5-5.3)

30.0 (21.9-39.7)

5.1� (2.6-10.1)

27.1 (18.6-37.6)

4.4� (2.2-9.0)

Psychosis or manic episode (n = 36)

1.9 (0.7-5.1)

4.6 (2.4-8.6)

2.5 (0.7-8.8)

5.1 (2.7-9.5)

2.8 (0.8-9.9)

7.1 (3.4-14.1)

4.0¶ (1.1-14.8)

8.9 (4.3-17.5)

5.1¶ (1.4-19.0)

Major depressive episode (n = 136)

7.4 (4.4-12.1)

18.5 (13.7-24.5)

2.8§ (1.5-5.5)

15.8 (11.3-21.8)

2.4¶ (1.2-4.6)

26.3 (18.6-35.8)

4.5� (2.2-9.0)

22.4 (14.7-32.6)

3.6� (1.7-7.7)

Abbreviation: CI, confidence interval. *Major mental disorder includes psychosis, manic episode, and major depressive episode. Participants may have more than one substance use disorder and more

than one major mental disorder. Each cell is weighted to reflect the population of the detention center. Statistically significant ORs indicate that comorbidity exceeds the level expected by chance, given the prevalence of that disorder in the sample. Psychosis, manic episode, major depressive episode, drug use disorder, and alcohol use disorder are missing for 3 of the 1829 participants; in addition, drug use disorder and alcohol use disorder are missing for 4 other participants. These 7 participants are excluded from all analyses in this table. All available data from the 1822 remaining participants are used for each cell. Because 25 participants are missing the diagnosis of any substance use disorder, this column and the “No Substance Use Disorder” column sum to 1797, not 1822.

†Major mental disorder is missing for 3 females. ‡Major mental disorder is missing for 13 males. §P�.01. �P�.001. ¶P�.05.

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public mental health system has little to offer,80 youth with comorbidity may “fall between the cracks” into the juvenile justice net. Unfortunately, recent innovations to treat comorbidity rarely reach into the juvenile justice system.23 Mental health professionals must collaborate with the juvenile justice system to:

1. Improve screening. Many detention centers do not screen detainees for psychiatric problems.81 Comor- bidity is particularly difficult to detect because intoxica- tion and withdrawal can mask or exacerbate psychiatric symptoms (and vice versa).66,70,82 Although there are prom- ising screening tools,83,84 additional studies are needed to document their validity.

2. Increase diversion and linkage. Youth with major mental disorders who are not a threat to the com- munity should be diverted to treatment facilities on arrest. Most detained youth are charged with nonvio- lent offenses85 and could be placed in community-based programs. Youth who are detained should be linked to services in the community after release. Ensuring that a first appointment is made and kept maximizes the chance of successful linkage to services.86 Only 20% of all delinquency cases result in detention.87 With col- laboration from mental health professionals, juvenile courts and detention centers can help detect and refer many youth who are vulnerable to arrest. Although detained youth stay an average of only 2 weeks, many troubled youth at risk for comorbidity will be arrested during adolescence.88-90

3. Reduce barriers to service in the community. Most delinquent youth experience substantial barriers to services. Youth in the juvenile justice system are dispro- portionately minority, poor, and poorly educated and have few social networks—all characteristics known to limit the type and scope of ADM services that are pro- vided.91,92 The Surgeon General reports that, compared with non-Hispanic whites, racial and ethnic minorities have less access to mental health services, are less likely to receive needed care, and are more likely to receive poor quality care.93 Poor minority youth rarely have private insurance.94-99 Many are ineligible for Medicaid.95,97 More- over, youth of color may be more likely than whites to be arrested, even for the same offenses.100 Reynolds et al101

found that more than one quarter of low-income, Afri- can American urban youth were arrested before the age of 18 years. The stigma of an arrest history may add to already formidable barriers to services.

Success, however, is limited by the availability and quality of services. Children in general are underserved; minority children even more so.92 Courts cannot man- date services where none are available.

FUTURE RESEARCH

Studies are needed in 4 areas: 1. Pathways to comorbidity. We need to deter-

mine the most common pathways to comorbidity, criti- cal periods of vulnerability, and how these differ by sex, race/ethnicity, and age. Longitudinal studies that iden- tify the most common developmental sequences will dem- onstrate when primary and secondary preventive inter- ventions may be most beneficial.67

2. Health disparities. Although juvenile crime is relatively similar across race/ethnicity,102 racial/ethnic mi- norities compose 29% of arrests,5 63% of detainees,85 and 62% of juveniles who are committed (serving sentences).85

Studies are needed to understand (and rectify) racial/ ethnic disparities in the decision to arrest, divert, de- tain, and provide mental health services to juveniles. Such studies will document whether the racial/ethnic differ- ences found in our study indicate systematic disparities in identification and management of comorbidity or re- flect true differences in need.

3. Evaluations of interventions. We must develop more effective treatments for comorbid disorders and iden- tify which treatments work best for special populations (eg, females, minorities, and younger adolescents).67 De- spite the escalating numbers of females in the justice sys- tem,5,103 few sex-specific services are available.104

4. Prevalence, patterns, and outcomes of comor- bid mental and physical disorders. There is growing evi- dence that psychiatric disorders often co-occur with physi- cal disorders in children.105-109 Comorbidity may worsen the prognosis of a physical illness; for example, depres- sion worsens the outcome of children with asthma.110

Health care costs are also much higher for those with both mental and physical disorders than for persons with ei- ther one alone.111

Most juveniles do not remain in detention for long. The responsibility for their care typically falls to the pub- lic mental health system on their release. Only a sus- tained partnership between the mental health and juve- nile justice systems offers hope for a rational response to comorbidity in delinquent youth.

Submitted for publication November 1, 2002; final revision received March 3, 2003; accepted March 5, 2003.

This work was supported by National Institute of Men- tal Health (NIMH) grants R01MH54197 and R01MH59463 and grant 1999-JE-FX-1001 from the Office of Juvenile Jus- tice and Delinquency Prevention. Major funding was also provided by the National Institute on Drug Abuse (Bethesda, Md), the Center for Mental Health Services (Rockville, Md), the Centers for Disease Control and Prevention (CDC) Na- tional Center for HIV, STD, and TB Prevention (Atlanta, Ga), CDC National Center on Injury Prevention and Con- trol (Atlanta), the National Institute on Alcohol Abuse and Alcoholism (Bethesda), the Center for Substance Abuse Pre- vention (Rockville), the Center for Substance Abuse Treat- ment (Rockville), the National Institutes of Health (NIH) Office of Research on Women’s Health (Bethesda), the NIH Center on Minority Health and Health Disparities (Bethesda), the NIH Office of Rare Diseases (Bethesda), the William T. Grant Foundation (New York, NY), and The Robert Wood Johnson Foundation (Princeton, NJ). Additional funds were provided by The John D. and Catherine T. MacArthur Foun- dation (Chicago), the Open Society Institute (New York) and the Chicago Community Trust (Chicago).

Many more people than the authors contributed to this project. Ann Hohmann, PhD, and Kimberly Hoagwood, PhD, provided extensive technical support in the design; Heather Ringeisen, PhD, and Mark Soler, JD, provided helpful ad- vice. Grayson Norquist, MD, and Delores Parron, PhD, pro- vided steadfast support throughout. We thank all project staff,

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especially Amy M. Lansing, PhD, for supervising the data collection. We thank Jennifer Wells, PhD, for her library work and her work on earlier drafts of the paper. We thank Laura Coats, BFA, for additional library work and editing the manu- script. The reviewers provided many creative suggestions. We also greatly appreciate the cooperation of everyone work- ing in the Cook County systems, especially David H. Lux, BA, our project liaison. Without the county’s cooperation, this study would not have been possible. Finally, we thank our subjects for their time and willingness to participate.

Corresponding author: Linda A. Teplin, PhD, Psycho- Legal Studies Program, Department of Psychiatry and Be- havioral Sciences, Feinberg School of Medicine, Northwest- ern University, 710 N Lakeshore Dr, Suite 900, Chicago, IL 60611 (e-mail: [email protected]).

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