Rural and urban differences in patients with a dual diagnosis

Schizophrenia Research 48 (2001) 93±107

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Rural and urban differences in patients with a dual diagnosis Kim T. Mueser a,b,c,*, Susan M. Essock d,e, Robert E. Drake a,b,c, Rosemarie S. Wolfe a, Linda Frisman e a

New Hampshire-Dartmouth Psychiatric Research Center, Concord, NH 03301, USA b Department of Psychiatry, Dartmouth Medical School, Hanover, NH, USA c Departments of Community and Family Medicine, Dartmouth Medical School, Hanover, NH, USA d Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, USA e Connecticut Department of Mental Health and Addition Services, Hartford, CT, USA Received 3 September 1999; accepted 31 March 2000

Abstract Objectives: To evaluate the differences between two cohorts of patients with severe mental illness (schizophrenia-spectrum or bipolar disorder) and co-occurring substance-use disorders, living in either predominantly rural areas or urban areas. Methods: Two study groups of patients with a dual diagnosis, recruited using the same criteria, were evaluated, including 225 patients from New Hampshire and 166 patients from two cities in Connecticut. The two study groups were compared on demographic characteristics, housing, legal problems, psychiatric and substance use diagnoses, substance use and abuse, psychiatric symptoms, and quality of life. Results: Patients in the Connecticut study group had higher rates of cocaine-use disorder, more involvement in the criminal justice system, more homelessness, and were more likely to be from minority backgrounds. The Connecticut group also had a higher proportion of patients with schizophrenia and more severe symptoms, as well as lower rates of marriage, educational attainment, and work than the New Hampshire study group. Alcohol-use disorder was higher in the New Hampshire group. Subsequent analyses within the Connecticut group indicated that although African American patients had higher rates of cocaine-use disorder than white patients, cocaine disorder and not minority status was most strongly related to criminal involvement and homelessness. Conclusions: Because of the substances abused and the greater degree of psychiatric illness severity, patients with a dual diagnosis who are living in urban areas may require greater ancillary services, such as residential programs, Assertive Community Treatment, and jail diversion programs in order to treat their disorders successfully. q 2001 Elsevier Science B.V. All rights reserved. Keywords: Dual diagnosis; Psychopathology; Rural; Schizophrenia; Severe mental illness; Substance abuse; Urban

1. Introduction Substance-use disorders are common in persons with severe mental illnesses such as schizophrenia * Corresponding author. Present address: NH-Dartmouth Psychiatric Research Center, Main Building, 105 Pleasant Street, Concord, NH 03301, USA. Tel.: 11-603-271-5747; fax: 11-603-271-5265. E-mail address: [email protected] (K.T. Mueser).

and bipolar disorder (Kessler et al., 1996; Mueser et al., 1992; Regier et al., 1990). These comorbid disorders, or dual disorders, can have a dramatic effect on the clinical course of the psychiatric disorder, such as relapse and rehospitalization, as well as other areas of functioning, including interpersonal violence and victimization, homelessness, legal problems, and behaviors that put these individuals at risk for HIV (Drake and Brunette, 1998). Recognition of the

0920-9964/01/$ - see front matter q 2001 Elsevier Science B.V. All rights reserved. PII: S 0920-996 4(00)00065-7

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problem of dual disorders has led to improved methods for the detection and assessment of substance-use disorders in persons with severe mental illness (Mueser et al., 1995; Rosenberg et al., 1998), and the development of integrated services to treat both disorders simultaneously (Drake et al., 1993; Mueser et al., 1998). The importance of dual disorders is widely accepted, but relatively little is known about environmental factors that may in¯uence the demographic, clinical, and other characteristics of patients in need of treatment. Differences between patients in urban and rural settings may be especially pertinent to dual disorders for two reasons. First, the prevalence of schizophrenia is higher in urban than rural areas, due to either migration into urban areas or the effects of cities on increasing vulnerability to schizophrenia (Eaton, 1974; Lewis et al., 1992; Peen and Dekker, 1997; Takai et al., 1995; Torrey et al., 1997). Second, patterns of substance use tend to differ, with mixed evidence that alcohol use and abuse are more common in rural areas, and that drug use and drug disorders, especially of `hard' drugs such as cocaine and heroine, are more common in urban areas (Anthony and Helzer, 1991; Cronk and Sarvela, 1997; Johnson and Muf¯er, 1992; Thomas, 1993). Prior research on urban±rural differences in patients with severe mental illness has focused on broad differences, such as demographic characteristics, symptoms, and housing. The general ®ndings indicate that urban patients are less likely to be married, are more symptomatic, have higher rates of drug-use disorders, and have poorer housing than patients in rural areas (Blazer et al., 1985; Fischer et al., 1996; Greenley and Dottl, 1997; Sommers, 1989), although rural patients with alcohol-use disorders tend to have a worse outcome than similar patients in urban areas (Davies et al., 1989). However, differences between dual diagnosis patients in rural and urban areas have not been examined. Determining how such patients differ could have important policy implications for planning dual diagnosis treatment services designed to address their clinical and social needs. To the extent that substance-use patterns differ between urban and rural areas, persons with dual disorders living in urban settings may be more prone to experiencing certain consequences unique to

particular substances. Speci®cally, the higher rate of crack cocaine use in urban than rural areas, combined with stiffer legal penalties for possessing and selling crack (Duster, 1997), would be expected to lead to higher rates of arrest and incarceration of patients with a dual diagnosis who are living in these areas. Similarly, cocaine abuse in patients with a dual diagnosis living in urban settings could result in more severe psychotic symptoms, as compared with other substances such as alcohol, because of the potent effects cocaine on stimulating dopamine neurotransmission and provoking symptom exacerbations in schizophrenia (Brady et al., 1990; Shaner et al., 1995). Thus, identifying differences between patients with a dual diagnosis living in urban versus rural regions could have service and policy implications for meeting their clinical and social needs, such as more closely monitoring patient symptoms or coordinating psychiatric intervention with the criminal justice system. The present study examined differences between two cohorts of patients with a dual diagnosis, one in New Hampshire, a predominantly rural state, and one in two urban areas in Connecticut. The patients were participants in two similar studies of dual disorders who were recruited using similar eligibility criteria and assessed with the same measures. Analyses focused on comparing the urban and rural samples on patient demographic characteristics, psychopathology and substance abuse, housing and legal problems, and quality of life.

2. Methods 2.1. Study groups and settings The subjects were patients participating in two studies of case management for dual diagnosis, one in New Hampshire and one in Connecticut. The participants in New Hampshire were 225 psychiatric outpatients who were receiving public services in one of seven community mental health catchment areas throughout the state. Patients were recruited into the New Hampshire study between 1989 and 1991. The participants in Connecticut were 199 outpatients receiving public services from the statefunded lead mental health centers in the cities of

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Hartford and Bridgeport. Patients were recruited into the Connecticut study between 1993 and 1998. The US Census Bureau de®nes a `metropolitan area' as a city with over 50 000 inhabitants. There are two cities in New Hampshire that are metropolitan areas, Manchester, with a population during the study of 99 332, and Nashua, with a population of 79 662. Both Bridgeport and Hartford are metropolitan areas, with populations during the study of 139 555 and 135 631. Although the population numbers are not dramatically different, another way of characterizing the urban±rural nature of a region is population density. In New Hampshire, both Manchester and Nashua are located in Hillsborough County, which has a population density of 383 persons per square mile. The other counties in New Hampshire included in this study have substantially lower population densities than Hillsborough County. By contrast, Bridgeport is in Fair®eld County, which has population density of 1330 persons per square mile, and Hartford is in Hartford County, which has a population density of 1142 persons per square mile. Because of the smaller populations of Manchester and Nashua than Bridgeport and Hartford, and the much lower population density of Hillsborough County compared to Fair®eld and Hartford Counties (approximately one-third), we grouped all of the New Hampshire sites together as a rural group, and we included the two Connecticut sites together as an urban group. Similar inclusion/exclusion criteria were employed for participation in the study in either state. The one criterion that was different between the two studies was the Axis I psychiatric disorder. In New Hampshire, the study group was limited to patients with a DSM-III-R diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder. In Connecticut, in addition to these three diagnoses, the study group also included other DSM-IV Axis I diagnoses with psychosis (e.g., schizophreniform disorder, major depression with psychotic features, psychotic disorder NOS). In order to compare the New Hampshire and Connecticut study groups using the same diagnoses, the results reported here are based on the subsample of 166 patients from the Connecticut study group with diagnoses of schizophrenia, schizoaffective disorder, or bipolar disorder based on the Structured Clinical Interview for DSM-III-R or DSM-IV (SCID; First et al., 1996; Spitzer et al., 1988).

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In addition to the aforementioned psychiatric diagnostic criteria, the two study groups met the following inclusion/exclusion criteria: (1) substance (alcohol or drug) abuse or dependence diagnosis within the past 6 months according to DSM-III-R or DSM-IV criteria (excluding nicotine and caffeine); (2) over 17 years old; (3) absence of mental retardation or medical conditions severe enough to preclude participation in a longitudinal research study; and (4) willingness to provide written informed consent to participate in the study. In the New Hampshire study group, eligibility criteria also included recent homelessness or at risk of homelessness. In the Connecticut study group eligibility also included: (1) literal homelessness over the past year or such poor independent living skills while not hospitalized that the patient frequently lacked a ®xed regular or adequate nighttime residence (e.g., was unable to provide for shelter more than twice in the past year, required ongoing assistance at least weekly to meet personal care needs, hospitalized or in jail with no permanent residence to return to); and (2) high service utilization (de®ned as one state hospital admission of at least 6 months, or two or more admissions to a psychiatric facility, crisis program, or emergency room for psychiatric or substance-abuse treatment over the past 2 years; incarceration in the past 6 months was counted as one hospitalization). Psychiatric and substance-use diagnoses were based on the SCID. 2.2. Measures A comprehensive battery of assessments was conducted, including substance abuse, symptomatology, housing, legal problems, and quality of life. Information from the baseline assessments was used in the analyses presented here. 2.2.1. Substance abuse Several measures of substance abuse were included to evaluate both the types and amounts of substances used, and the consequences of such use. The TimeLine Follow-Back (TLFB; Sobell et al., 1980), a structured self-report measure, was used to assess days of alcohol and drug use over the past 6 months. The number of days in the past 30 days that the patient reported drinking to intoxication or using drugs, as

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well as the alcohol and drug composite scales, were used from the Addiction Severity Index (ASI; McLellan et al., 1992). Substance abuse over the past 6 months was also rated using the Alcohol Use Scale (AUS), the Drug Use Scale (DUS) (Drake et al., 1990; Mueser et al., 1995), and the Substance Abuse Treatment Scale (SATS; McHugo et al., 1995). The AUS and DUS are ®ve-point scales based on the DSM criteria for alcohol and drug use disorders: 1 ˆ no use, 2 ˆ use without impairment, 3 ˆ abuse, 4 ˆ dependence, and 5 ˆ severe dependence. The SATS is an eight-point scale that indicates progression toward recovery from a substance-use disorder according to Osher and Kofoed's (1989) model of treatment and recovery: 1±2 ˆ early and late stages of engagement, 3±4 ˆ stages of persuasion, 5±6 ˆ stages of active treatment, and 7±8 ˆ stages of relapse prevention. Implementing the model entails ®rst building a relationship with the patient to establish a working alliance (engagement), followed by helping him or her acknowledge a substance-use problem (persuasion). Next, the focus of treatment shifts to actual reduction of substance use to non-harmful levels or abstinence (active treatment), which is followed by maintaining awareness of vulnerability to relapse and working on other goals in the patient's life (relapse prevention). AUS, DUS, and SATS ratings were made by a team of reviewers, who based their ratings on a comprehensive review of all available information, including interviews, hospitalizations, time in jail, days in the community, clinicians' ratings, and laboratory measures. Inter-rater reliabilities for the reviewers' ratings of the AUS, DUS, and SATS were high, with intraclass correlation coef®cients (ICCs) of 0.93 or higher. 2.2.2. Psychopathology Psychiatric symptoms over the past 2 weeks were assessed with the Expanded Brief Psychiatric Rating Scale (BPRS; Lukoff et al., 1986). Subscale scores were computed based on the ®ve-factor solution (Guy, 1976), including: Anergia, Thought Disorder, Disorganization, Affect, and Activation. Inter-rater reliabilities for the BPRS subscales were acceptable for the BPRS total score and subscales, with ICCs of 0.70 or higher.

2.2.3. Other measures Demographic information was obtained using the Uniform Client Data Inventory (Tessler and Goldman, 1982). The Quality of Life Interview (QOLI; Lehman, 1988) was used to assess objective and subjective dimensions of quality of life. Housing history and institutional stays were assessed using a self-report calendar supplemented by outpatient and hospital records (Clark et al., 1996). Health and legal problems were assessed using the medical and legal subscales of the ASI. 2.3. Procedure Patients were recruited into the study through informational meetings with patients, families, and mental health professionals. After con®rming eligibility, interested patients provided informed consent (or their legal conservators provided consent) and completed the baseline assessments. 3. Results We ®rst examined demographic, housing, and legal differences between the Connecticut and New Hampshire study groups. Second, we evaluated psychiatric and substance-use disorder diagnostic differences between the groups. Third, we compared the two study groups on speci®c dimensions of substance abuse, restricting the analyses to those patients with a similar substance-use disorder at baseline. Fourth, we compared the groups on psychiatric symptoms and quality of life. Fifth and last, we conducted analyses to explore variables that differed between the two study groups, including psychiatric diagnosis, race, age, and the presence of a cocaine-use disorder. We note in the tables where statistical differences reached signi®cance using the Bonferroni correction for multiple tests. Because of the number of tests conducted, in this section we concentrate on effects signi®cant at the P , 0.01 level or at the Bonferroni level, and in the Discussion we consider effects signi®cant at the P , 0.05 level to be `trends'. 3.1. Demographic, housing, and legal differences To evaluate whether the Connecticut and New Hampshire study groups differed in the categorical

K.T. Mueser et al. / Schizophrenia Research 48 (2001) 93±107

variables, chi-square tests were computed. Most of the continuous variables were severely skewed due to left censoring of the data (frequent 0s); therefore, differences between the two groups were tested using

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a non-parametric test, the Mann±Whitney U-test. The results of these analyses are summarized in Table 1. The most marked difference between the study groups in demographic characteristics was in racial

Table 1 Demographic and background characteristics of Connecticut and New Hampshire samples

Categorical variables Gender Male Female Race White Non-white Marital status Ever married Never married Education High school graduate Less than high school Housing Living with family Recently homeless Crime Ever convicted Ever incarcerated Ever charged Work Recently worked c Currently working Health Chronic medical problems Prescribed meds physical problem

Continuous variables Age Days in psychiatric hospital c Days in substance abuse treatment c Lifetime months incarcerated Lifetime number of convictions Lifetime number of times charged Days in jail/prison c Days of literal homelessness c Days of marginal homelessness c Monthly income a b c

Connecticut (N ˆ 166) N (%)

New Hampshire (N ˆ 225) N (%)

Chi-square test a N (%)

122 (73.5) 44 (26.5)

170 (75.6) 55 (24.4)

0.21

47 (28.3) 119 (71.7)

217 (96.4) 8 (3.6)

202.19*** b

42 (25.3) 124 (74.7)

86 (38.2) 139 (61.8)

7.24**

83 (50.0) 83 (50.0)

141 (62.9) 83 (37.1)

6.54*

63 (38.2) 65 (39.6)

76 (33.9) 60 (26.9)

0.75 7.00**

94 (59.9) 94 (58.8) 128 (79.5)

112 (49.8) 90 (40.7) 145 (64.4)

3.79 12.08*** b 10.28**

46 (27.9) 15 (9.1)

99 (45.2) 43 (19.2)

12.02*** b 7.52**

61 (37.0) 32 (19.9)

68 (30.2) 48 (21.4)

1.96 0.04

N

Mean (S.D.)

N

Mean (S.D.)

Mann±Whitney (Z-score) a

166 164 166 160 157 161 163 162 166 156

36.09 (8.57) 17.85 (34.85) 2.70 (7.35) 14.11 (31.70) 2.74 (6.31) 4.80 (7.11) 11.75 (37.31) 20.25 (55.38) 19.00 (53.92) 1764.74 (2993.04)

225 212 224 221 214 225 225 223 223 208

33.85 (8.37) 31.94 (55.94) 0.54 (3.00) 8.55 (26.05) 1.56 (3.14) 3.08 (4.96) 8.87 (45.82) 7.28 (32.68) 2.77 (25.46) 693.82

3.58*** b 2.20* 4.30*** b 3.31*** b 2.12* 3.04** 4.15*** b 1.63*** b 6.20*** b 4.02** b

Signi®cance: *P , 0.05; **P , 0.01; ***P , 0.001. Meets Bonferroni correction for multiple statistical tests at the P , 0.05 level. Over the past year.

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3.2. Psychiatric and substance-use diagnoses

composition, with few patients from minority backgrounds in the New Hampshire group and many in the Connecticut group, re¯ecting differences between the two states' populations. The Connecticut study group was also less likely to have ever married, was slightly older (2 years), and was less likely to be currently or recently working. However, the Connecticut group had higher income levels than the New Hampshire group (US$1764 vs. $693 per month). The two study groups also differed signi®cantly on most measures of housing instability, crime, and institutionalization. The Connecticut patients were more likely to have been homeless recently and had more legal problems, including charges and time in jail or prison. Finally, the Connecticut patients had spent more time in substance-abuse treatment.

Chi-square tests were computed to compare the Connecticut and New Hampshire study groups on psychiatric and substance-use diagnoses. The results of these analyses are summarized in Table 2. There were many signi®cant differences in substance-use diagnoses between the two study groups. Across both recent and lifetime measures, patients in New Hampshire had higher rates of alcohol and cannabis use disorder, and lower rates of cocaine use disorder compared with patients in Connecticut. Although the study groups did not differ in their current use of most of the other drugs, the New Hampshire patients were more likely to have a lifetime history of sedative-, amphetamine-, or

Table 2 Psychiatric and substance-use disorder diagnoses for the Connecticut and New Hampshire samples Connecticut

Psychiatric diagnosis Schizophrenia Schizoaffective Bipolar Disorder Substance-use diagnosis Recent Alcohol Any drug Cannabis Cocaine Sedatives Amphetamines Narcotics Hallucinogens Other Polysubstance Lifetime Alcohol Any drug Cannabis Cocaine Sedatives Amphetamines Narcotics Hallucinogens Other Polysubstance a b

Chi-square a

New Hampshire

N

%

N

%

108 43 15

65.1 25.9 9.0

118 54 53

52.4 24.0 23.6

14.35*** b

112 128 66 101 1 6 6 1 4 33

67.5 77.1 39.8 60.8 0.6 3.6 3.6 0.6 2.4 19.9

183 114 88 34 11 13 12 6 10 24

81.7 50.7 39.1 15.1 4.9 5.8 5.3 2.7 4.4 10.7

10.47** 28.32*** b 0.02 88.38*** b 5.90* 0.99 0.64 2.33 1.15 6.51*

134 137 95 114 12 16 23 12 12 75

80.7 82.5 57.2 68.7 7.2 9.6 13.9 7.2 7.2 45.2

214 192 173 71 54 70 33 56 29 182

95.1 85.3 76.9 31.6 24.0 31.1 14.7 24.9 12.9 80.9

20.20*** b 0.56 17.12*** b 52.80*** b 19.15*** b 25.67*** b 0.05 20.74*** b 3.26 54.07*** b

Signi®cance: *P , 0.05; **P , 0.01; ***P , 0.001. Meets Bonferroni correction for multiple statistical tests at the P , 0.05 level.

K.T. Mueser et al. / Schizophrenia Research 48 (2001) 93±107

hallucinogen-use disorder, as well as polysubstanceuse disorder. 3.3. Substance use and abuse t-Tests were conducted to examine differences in substance-use behavior and severity of substance abuse between the two study groups, within the subgroup of patients with an alcohol-use disorder and within the subgroup of patients with a drug-use disorder (each based on the SCID). The results of these analyses are summarized in Table 3. Among patients with an alcohol-use disorder, those living in New Hampshire had a higher score on the ASI Alcohol Composite scale and had consumed alcohol on more days over the past 30 days. Among patients with a drug-use disorder, the Connecticut study group had a more severe disorder on the Drug Use Scale and had more cocaine use over the past 30 days.

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3.4. Psychopathology and quality of life Differences in symptoms and quality of life ratings were evaluated by computing t-tests on the subscales, and are summarized in Table 4. The Connecticut study group had signi®cantly higher BPRS ratings on the activation and disorganization subscales. The ratings from the Quality of Life Interview revealed a mixed pattern of differences between the two study groups. Patients in Connecticut reported higher general life satisfaction and satisfaction with social relations, as well as higher levels of family contact. Patients in New Hampshire reported engaging in more daily activities. 3.5. Additional analyses As previously indicated, the Connecticut and New Hampshire study groups were recruited based on slightly different inclusion criteria, and also differed signi®cantly in psychiatric diagnosis, age, race, and

Table 3 Substance use for Connecticut and New Hampshire samples Connecticut

Alcohol c Alcohol Use Scale Stages of Treatment Scale ASI Alcohol Composite e Alcohol past 30 days Drug d Drug Use Scale Stages of Treatment Scale ASI Drug Composite e Any drug use past 30 days Polydrug use past 30 days Cannabis use past 30 days Narcotics use past 30 days Sedatives use past 30 days Cocaine past 30 days Amphetamines past 30 days Hallucinogen past 30 days Inhalants past 30 days a b c d e

t-test a

New Hampshire

N

Mean (S.D.)

N

Mean (S.D.)

112 112 109 111

3.28 (1.02) 2.71 (1.19) 0.20 (0.19) 6.86 (9.85)

167 168 172 183

3.55 (0.83) 2.72 (0.83) 0.30 (0.22) 10.16 (10.80)

2.40* 0.09 4.17***b 2.68**

127 127 126 126 127 127 127 127 127 126 127 127

3.61 (1.11) 2.80 (1.32) 0.12 (0.09) 6.92 (9.67) 2.62 (6.41) 2.28 (5.91) 0.51 (3.57) 0.99 (4.80) 5.05 (8.71) 0.00 (0.00) 0.00 (0.00) 0.03 (0.25)

106 106 112 114 114 114 114 114 114 114 114 114

3.07 (1.08) 2.59 (0.73) 0.11 (0.10) 6.65 (9.74) 3.11 (5.88) 4.55 (8.18) 0.71 (5.79) 2.61 (7.99) 0.68 (2.98) 0.04 (0.39) 0.08 (0.50) 0.03 (0.21)

3.72***b 1.53 0.73 0.22 0.62 2.44* 0.32 1.87 5.31***b 1.22 1.68 0.17

Signi®cance: *P , 0.05; **P , 0.01; ***P , 0.001. Meets Bonferroni correction for multiple statistical tests at the P , 0.05 level. Analyses restricted to patients with an alcohol-abuse disorder. Analyses restricted to patients with a drug-use disorder. ASI ˆ Addiction Severity Index.

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Table 4 Psychopathology and quality of life for Connecticut and New Hampshire samples at baseline Connecticut

Brief Psychiatric Rating Scale Affect Anergia Thought Disorder Activation Disorganization Total BPRS Quality of Life Interview Satisfaction scales General life satisfaction Housing Family relations Social Relations Leisure Safety Finances Health Job Town (safety/satisfaction) Medical Care Other scales Adequate ®nancial support Daily activities Community living skills Social contact Victimization Continuity of mental health providers Family contact a b

t-test a

New Hampshire

N

Mean (S.D.)

N

Mean (S.D.)

164 166 163 166 166 161

2.33 (1.06) 2.03 (1.04) 2.48 (1.51) 1.71 (0.80) 1.88 (0.91) 48.71 (13.43)

220 224 215 224 224 201

2.46 (1.08) 1.89 (0 .98) 2.45 (1.46) 1.49 (0.66) 1.32 (0.71) 45.33 (13.30)

161 166 160 162 165 163 162 163 15 166 163

4.50 (1.57) 4.66 (1.37) 4.39 (1.63) 4.76 (1.21) 4.55 (1.22) 4.52 (1.33) 3.63 (1.58) 4.82 (1.21) 5.04 (0.59) 4.58 (1.37) 4.95 (1.40)

220 221 219 221 224 221 218 222 41 72 71

4.05 (1.50) 4.89 (1.05) 4.43 (1.48) 4.38 (1.20) 4.26 (1.20) 4.81 (1.22) 3.47 (1.42) 4.55 (1.08) 4.64 (1.00) 4.68 (1.08) 4.83 (1.26)

2.81** 1.84 0.23 3.01** 2.28* 2.19* 1.06 2.27* 1.47 0.61 0.64

161 165 164 162 161 160

0.60 (0.33) 0.46 (0.16) 1.65 (0.63) 2.53 (0.93) 1.25 (0.48) 0.38 (0.38)

224 225 220 225 215 210

0.61 (0.29) 0.51 (0.15) 1.60 (0.65) 2.74 (0.81) 1.24 (0.43) 0.45 (0.36)

0.23 2.70** 0.88 2.34* 0.19 1.78

158

3.95 (2.16)

173

3.39 (0.92)

3.00**

1.24 1.39 0.18 3.01** 6.58*** b 2.39*

Signi®cance: *P , 0.05; **P , 0.01; ***P , 0.001. Meets Bonferroni correction for multiple statistical tests at the P , 0.05 level.

cocaine-use disorders. Subsequent analyses were conducted to evaluate the relationships among inclusion criteria, diagnosis, age, race, and cocaine on the study variables. The rationale for conducting these analyses was to evaluate which of these variables (if any) contributed to the observed pattern of differences between the urban and rural study groups. For example, if differences between African American and white patients within the Connecticut study group closely paralleled the differences between the urban and rural study groups, it might be concluded that race differences between the two groups were predictive of the observed differences in substance abuse, involvement in the criminal justice system, and psychopathology. On the other hand, if patients

with a cocaine-use disorder, compared with other substance-use disorders, tended to differ on the same variables as the urban and rural study groups, whereas the comparison of racial groups showed few differences, this would suggest that differences in cocaine-use disorder across the two study groups were more likely responsible for the observed urban-rural differences. Finally, an additional set of analyses was conducted to evaluate differences within the New Hampshire study group of patients living in metropolitan areas compared to nonmetropolitan areas. Patients living in metropolitan areas (Manchester and Nashua) were compared with patients living in nonmetropolitan areas in New Hampshire to determine whether these

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differences paralleled the differences between the New Hampshire and Connecticut study groups.

remaining differences (including leisure, safety, and health) were not.

3.5.1. Inclusion criteria As described in the Methods section, the inclusion criteria for the New Hampshire and Connecticut study groups differed slightly with respect to homelessness and institutionalization: New Hampshire required recent homelessness or risk of homelessness, whereas Connecticut required recent homelessness or poor independent living skills that threatened stable housing, and recent hospitalization or time in jail. We conducted analyses to evaluate whether this difference in inclusion criteria in¯uenced the ®ndings. Information on patients' homelessness, hospitalization, and time in jail was available for only the past year in the New Hampshire group. Of the 225 patients in New Hampshire, 89 (39%) had not been hospitalized or in jail in the past year. We dropped these 89 patients from New Hampshire and repeated the analyses comparing the two study groups. There were few changes in the results signi®cant at the P , 0.01 level. In Table 1, the only change was that the number of lifetime months incarcerated and the number of days in jail/prison over the past year were no longer signi®cantly different between the two study groups. However, the differences between the study groups in the proportion of patients ever incarcerated and ever charged with a crime remained signi®cant. There were no differences in the reanalyses for Tables 2±4.

3.5.3. Age To determine whether the age differences between the study groups were related to the results, the analyses were repeated, controlling for age. Partial correlations (controlling for age) were computed for the continuous variables (e.g., BPRS and QOLI subscales) and logistic regressions, including age as a covariate, were performed for the categorical variables (e.g., psychiatric and substance diagnoses). None of these analyses signi®cantly affected the ®ndings.

3.5.2. Psychiatric diagnosis To determine whether differences between the two study groups in demographic characteristics, substance-use diagnoses, homelessness, arrests and time in jail, and psychopathology could be due to differences between the groups in psychiatric diagnosis, we dropped patients with bipolar disorder and repeated the analyses. The results obtained were very similar to those with the full study groups. There were no changes from the ®ndings with the full study groups compared to the ®ndings excluding bipolar disorder for any of the measures on Tables 1±3, or for the BPRS in Table 4. With respect to quality of life (Table 4), differences in general life satisfaction, social relations, daily activities, social contact, and family contact continued to be signi®cant, while the

3.5.4. Race The New Hampshire study group had a signi®cantly lower proportion of patients from minority backgrounds than the Connecticut study group. To evaluate differences related to race, we performed the same analyses summarized in Tables 1±4, comparing the African American patients in the Connecticut group (N ˆ 108) with white patients from the same group (N ˆ 53). There were relatively few differences between the African American and white patients in the Connecticut study group. However, African American patients were less likely to have ever married (P , 0.01), and were less likely to be diagnosed with bipolar disorder and more likely to diagnosed with schizophrenia (P , 0.01) compared with white patients. There were also race differences with respect to substance-use diagnoses. African American patients were more likely than white patients to have lifetime and recent drug-use disorders (both P values ,0.0001), with speci®c differences in lifetime (79% vs. 53%) and recent (71% vs. 47%) cocaine use disorder and lifetime (66% vs. 36%) and recent (49% vs. 19%) cannabis use disorder (African Americans and white patients, respectively) (all P values ,0.001). The signi®cant differences in marital status, psychiatric diagnosis, and cocaine use disorders between the African Americans and whites in Connecticut raised the question of whether differences in these variables between the New Hampshire and Connecticut study groups could be explained by differences in the racial composition of the two

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groups. To evaluate this question, we compared psychiatric diagnosis, marital status, and cocaine-use disorders (recent and lifetime) between white patients in the Connecticut study group and the white patients in the New Hampshire group. Neither psychiatric diagnosis (24% bipolar in New Hampshire vs. 15% in Connecticut) nor marital status (60% never married in both study groups) differed signi®cantly across the two groups. However, white patients in Connecticut were signi®cantly more likely than white patients in New Hampshire to have both recent (47% vs. 15%) and lifetime (53% vs. 31%) cocaine-use disorders (P , 0.00001 and 0.01, respectively). Thus, the higher rate of schizophrenia and lower rate of marriage in the Connecticut group compared with the New Hampshire could re¯ect differences in racial composition between the two groups. Differences in the likelihood of cocaine-use disorder between the two states, however, are not attributable to differences in race across the states. 3.5.5. Cocaine-use disorder Because the differences in cocaine-use disorder between the Connecticut and New Hampshire study groups were so prominent, we conducted additional analyses comparing patients with a recent cocaine-use disorder to other patients across both sites. There were numerous highly statistically signi®cant differences between the two groups, mainly in criminal activity and homelessness. Recent cocaine-use disorder was signi®cantly related to a history of being charged for a crime, being convicted of a crime, time incarcerated, marginal homelessness, literal homelessness, and days in substance abuse treatment (all with P values ,0.001). Analyses comparing patients with a cocaine use disorder to those without a disorder within the Connecticut and New Hampshire study groups revealed a similar pattern of results. 3.5.6. Metropolitan±nonmetropolitan differences in New Hampshire To evaluate differences between patients living in metropolitan areas in New Hampshire compared with those in nonmetropolitan areas (i.e. cities over 50 000), we repeated the analyses by dividing this study group in to two subgroups. The metropolitan subgroup included patients receiving services at the mental health centers in either Manchester or Nashua

(N ˆ 110) and the nonmetropolitan subgroup included patients at any of the remaining ®ve mental health centers (N ˆ 115) that participated in the study. Among all of the analyses, only two were signi®cant, both at P , 0.01. Patients living in metropolitan areas in New Hampshire were more likely to have a recent diagnosis of cocaine-use disorder than patients in nonmetropolitan areas (22% vs. 9%), as well as a lifetime sedative-use disorder (9% vs. 1%). The general lack of differences between these two New Hampshire subgroups suggests that there are more similarities than differences between metropolitan and nonmetropolitan areas within the state, and supports our combining the different geographic areas in New Hampshire in the analyses comparing the New Hampshire and Connecticut study groups. 4. Discussion We recognize that New Hampshire does not represent all of rural America and, similarly, Hartford and Bridgeport Connecticut does not represent all of urban America. Furthermore, some of the differences observed may represent the differing mental health service systems (e.g., more private mental health providers in Connecticut could result in public mental health programs serving patients with greater severity). Nevertheless, this comparison does involve two contrasting regions of the northeastern US, one predominantly rural and relatively prosperous, and another urban with the characteristic problems of poverty and drug abuse. The differences between the two study groups in substance-use disorders, psychiatric severity, and the social problems of crime and homelessness point to the importance of considering how the service needs of patients with a dual diagnosis may be in¯uenced by the urban or rural nature of the setting in which they live. Overall, the patients with a dual diagnosis in the Connecticut study group were more psychosocially disadvantaged than those in the New Hampshire group across a range of different variables. With respect to social factors, the Connecticut group, which included a higher proportion of patients from minority groups (mainly African American), were less likely to have married or to be working, and there was a trend for them to have been less likely to complete

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high school than the New Hampshire study group. Patients in the Connecticut study group were also more likely to have been homeless and involved in the criminal justice system, and had greater psychiatric impairment, including more patients with schizophrenia. In addition, patients in Connecticut had more severe symptoms, even when controlling for diagnosis. Perhaps most importantly, the Connecticut study group had a higher rate of current drug-use disorders, that was due to a rate of cocaineuse disorder approximately four times higher in the Connecticut group (61%) than in the New Hampshire group (15%). Furthermore, among patients with a drug-use disorder, those from the Connecticut group had a more severe disorder. There are several possible reasons that may account for the observed disadvantages of the patients in Connecticut, including the high prevalence of cocaine-use disorder, the urban setting, poverty, and the high minority composition of the group. The increased rate of cocaine use disorder is consistent with other research suggesting higher rates of drug abuse in psychiatric patients (Blazer et al., 1985; Sommers, 1989) and homeless persons (The Urban Institute, 1999) living in urban compared with rural areas, and the tendency since the beginning of the crack cocaine era for it to dominate the inner cities (Johnson and Muf¯er, 1992). The ®nding that cocaine-use disorders were higher in metropolitan areas than nonmetropolitan areas in New Hampshire also supports this conclusion. The higher rate of criminal charges, convictions, incarceration, and homelessness in the Connecticut study group appears to be due to the higher rate of cocaine-use disorder. Subsequent analyses comparing patients with a cocaine-use disorder to those without con®rmed the strong associations between criminality, homelessness, and cocaine disorder. Since the 1980s crack cocaine use has had a dramatic effect on the criminal justice system, with high rates of arrest and incarceration for possession and selling (Belenko, 1990; National Institute of Justice, 1991), especially for African American persons (Duster, 1997). Patients with a dual diagnosis appear to be just as susceptible (if not more so) to the legal consequences of cocaine abuse as non-disabled persons. Because of the higher rate of cocaine-use disorder among the African American patients in the

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Connecticut study group compared with the white patients from the same group, similar to other studies of drug-use disorders in psychiatric patients in urban areas (Mueser et al., 1990, 1992), these negative consequences may have an even more dire effect on members of this minority group. Furthermore, while substance-use disorders in psychiatric patients have been repeatedly linked to homelessness (Caton et al., 1994; Smith et al., 1992), crack cocaine appears to have an especially pernicious effect on loss of housing, with about 40% of the Connecticut sample homeless over the past year. Analyses comparing patients with a cocaine-use disorder to those with other substance-use disorders (across both the Connecticut and New Hampshire study groups) con®rmed that cocaine disorder was strongly associated with both homelessness, arrests, and incarceration. Patients in the Connecticut sample were more likely to have schizophrenia, had more severe psychiatric symptoms, were less likely to have married, and tended to have lower levels of education. Although cocaine-use disorder was strongly associated with criminality and homelessness, it was not related to marital status, psychiatric diagnosis, or symptom severity. On the other hand, race was related to both diagnosis and marital status, but not symptom severity. Furthermore, when analyses comparing the two sites were restricted to white patients, there were no longer any differences between the Connecticut and New Hampshire study groups on diagnosis or marital status. The difference in diagnosis is consistent with other research ®nding that African Americans are more likely to be diagnosed with schizophrenia than whites (Adams et al., 1984; Keith et al., 1991). On the other hand, the difference between the study groups in symptom severity cannot be explained by differences in either cocaine-use disorder or race. Several other studies have found that patients with severe mental illness in urban areas have more severe symptoms than patients in rural areas (Chu et al., 1982, 1986; Davies et al., 1989). Although other research has found that among patients with severe mental illness, those living in urban areas are more likely to have schizophrenia (Sommers, 1989) and are less likely to have married (Greenley and Dottl, 1997; Sommers, 1989), we were unable to replicate these differences when comparing the white patients in the Connecticut study group with those in the New

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Hampshire group, possibly due to limited statistical power. These ®ndings suggest that, aside from the increased problem of crack cocaine in urban areas, patients with severe mental illness may also have more severe psychiatric symptoms. An unexpected result was that there was a trend for patients in the Connecticut study group to report higher subjective satisfaction with their quality of life (Table 4). Although none of the differences was signi®cant at the Bonferroni correction for the P , 0.05 level, patients in Connecticut reported higher general life satisfaction, and higher satisfaction with social relations, leisure, and health compared with patients in New Hampshire. Furthermore, the differences in general life satisfaction and satisfaction with social relations remained after controlling for diagnostic and age differences. The higher satisfaction of the Connecticut study group may be surprising in light of the higher rates of homelessness and incarceration in Connecticut. However, other research indicates that people adapt quickly to both positive and negative life circumstances, which have only transitory effects on subjective well-being and happiness (Brickman and Campbell, 1971; Diener, 2000). The reasons for the higher satisfaction with life in the Connecticut patients are unclear. Social comparison theory (Diener, 1984) may provide one possible interpretation for these differences. According to this theory, subjective life satisfaction is partly determined by comparing one's own circumstances with those of others, especially proximal others, such as people living in the same community (Carp and Carp, 1982; Michalos, 1980; Wills, 1981). When people perceive themselves to be worse off than their reference group, they report lower subjective satisfaction. For example, within countries there is a modest correlation between wealth and subjective well-being, yet there do not tend to be differences between poor compared with wealthy nations (e.g., Japan and India; Diener, 2000). Based on social comparison theory, it is plausible that patients living in Hartford, Bridgeport, and New Hampshire use proximate others living in similar areas as their reference groups when rating their own quality of life. Thus, considering the high level of poverty and social disadvantages experienced by the general population of persons living in Hartford and Bridgeport compared with New Hampshire (e.g., education, poverty, incarcera-

tion, homelessness, housing), the difference between Connecticut study group and its reference group may have been less than the difference between the New Hampshire study group and its reference group. In other words, the study participants living in New Hampshire may have believed they were worse off compared to others in New Hampshire, whereas the perceived difference was not as prominent in the study participants living in Connecticut. More research is needed to address this intriguing ®nding. A comment is in order concerning possible cohort effects. Although the same instruments were employed in both states, and similar inclusion criteria were used, the New Hampshire study group was recruited several years earlier (1989±1991) than the Connecticut study group (1993±1998). This introduces the possibility of cohort effects accounting for some of the observed group differences. Without overlapping data from both sites, it is dif®cult to estimate the contribution of cohort effects. Perhaps the most important effects would be expected to be related to trends in types of substance abuse, which often change over time (Mueser et al., 1992). To explore this in the Connecticut study sample we compared rates of current substance-use disorders in patients recruited during the ®rst half of the recruitment period (1993±1996) with those recruited during the second half (1996±1998), and found no differences. In addition, based on another study, cocaine-use disorders in hospitalized patients with severe mental illness continued to be relatively low in New Hampshire through 1993±1996 (Rosenberg et al., 1998), suggesting that the crack cocaine epidemic remained a primarily urban problem. Future research on urban±rural differences of patients with a dual diagnosis should attempt to collect data cotemporaneously. We are currently collecting longitudinal follow-up data on both of these study groups, which may shed some light on these questions. The present ®ndings may have important service implications. Effective treatment of patients with a dual diagnosis who live in poor, urban areas such as Hartford and Bridgeport, Connecticut may require greater ancillary supports, such as more structured housing programs, higher levels of service integration [e.g., the Assertive Community Treatment (ACT) model; Stein and Santos, 1998], and better

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coordination with the criminal justice system to reduce incarceration. Independent housing is problematic for patients with a dual diagnosis because they need greater protection from toxic environments in which substance use is normative behavior (Bebout et al., 1997; Drake and Wallach, 1989). A greater range of supported housing options, with graded levels of tolerance for substance use, may be necessary to help protect patients with a dual diagnosis who are living in urban areas from these environmental effects (Osher and Dixon, 1996). Controlled research on the ACT model for patients with a dual diagnosis in the New Hampshire study group found modest bene®ts for ACT compared with standard case management when all patients received integrated mental health and substance abuse treatment (Drake et al., 1998). The higher needs of patients with a dual diagnosis in the Connecticut study group, as re¯ected by both their more severe cocaine abuse and psychiatric impairment, and likely compounded by their greater poverty and the urban setting, suggests that ACT may have even more bene®cial effects for these patients. Finally, special programs aimed at diverting patients with severe mental illness from jails (Steadman et al., 1994; Steadman et al., 1995) may be especially useful in urban settings in which drug abuse frequently results in incarceration. Such strategies may be crucial to improving the prognosis of patients with a dual diagnosis living in urban areas. Acknowledgements This research was supported by NIH grants SM/ TI51802, MH52872, and AA10265 to Susan M. Essock, and MH00839, MH46072, and AA08341 to Robert E. Drake. Thanks to Nancy Covell and David Kavanagh for comments on the manuscript, to Nina Kontos, who oversaw recruitment of most of the study participants in Connecticut, and to Tim Ackerson, who oversaw recruitment of the study participants in New Hampshire. This publication does not express the views of the Department of Mental Health and Addiction Services or the State of Connecticut. The views and opinions expressed are those of the authors.

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