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Differential Impact of Supported Housing on Selected Subgroups of Homeless Veterans With Substance Abuse Histories
Maria J. O'Connell, Ph.D.; Wesley J. Kasprow, Ph.D., M.P.H.; Robert A. Rosenheck, M.D.
Psychiatric Services 2012; doi: 10.1176/appi.ps.201000229
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Dr. O’Connell is affiliated with the Department of Psychiatry, Yale School of Medicine, 319 Peck St., Building 1, New Haven, CT 06513 (e-mail: maria.oconnell@yale.edu). Dr. Kasprow and Dr. Rosenheck are with the Department of Psychiatry, Yale University, and with the Veterans Affairs New England Mental Illness Research, Education and Clinical Center, both in New Haven, Connecticut.

Abstract

Objective  Studies have demonstrated that supported housing is an effective intervention for individuals who are homeless and have a mental illness or substance use disorder. This study examined data from an experimental trial of the U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing (HUD-VASH) program to identify differences in the program’s impact on subgroups defined by sociodemographic or clinical characteristics.

Methods  Data were analyzed from 259 male homeless veterans with substance abuse problems who were randomly assigned to HUD-VASH (intensive case management [ICM] plus rent subsidy vouchers), ICM only, or treatment as usual between June 1992 and December 1995. Four subgroups were defined: African American versus Caucasian, younger versus older than 42.3 years, co-occurring diagnoses of mental illness versus diagnosis of a substance use disorder only, and active versus less active substance use upon program entry. Mixed models were used to identify significant interactions between HUD-VASH assignment and each subgroup.

Results  Compared with ICM alone, HUD-VASH was associated with more positive housing outcomes for Caucasians, veterans with co-occurring mental disorders, and veterans who were active substance users. HUD-VASH was associated with more positive socioclinical outcomes for African Americans. No differences were observed in housing or socioclinical outcomes as a function of age.

Conclusions  Among homeless veterans with a substance use disorder, Caucasians and those with active substance use showed greater housing benefits than other veterans from HUD-VASH than from ICM alone. African Americans showed greater socioclinical benefit than Caucasians from HUD-VASH versus ICM. Interaction analysis deserves further study.

Abstract Teaser
Figures in this Article

Research on supported housing has demonstrated that the combination of case management support and subsidized community housing is effective in helping formerly homeless individuals acquire and maintain housing and can contribute to improvements in quality of life, social support, symptoms, and substance use (112). However, little is known about the extent to which supported housing is beneficial to subgroups of individuals with various sociodemographic or clinical characteristics (13,14).

Recent examinations of data within and across studies suggest that there may be important differences in the types of outcomes experienced by different subgroups of individuals in various housing settings (1517). In their recent review, Kertesz and colleagues (16) cautioned that although models that provide direct access to housing without preconditions of sobriety or treatment engagement (such as Housing First) are associated with more positive housing outcomes, there are limited data pertaining to outcomes of individuals with primary substance use issues. Given that substance use is one of the major risk factors for loss of housing and subsequent homelessness among veterans (2,3,7), this is an especially critical area for further investigation.

Subgroup analysis is a common post hoc method used by researchers to determine whether clients with different types of problems respond differently to an intervention (18). Such analyses can be conducted by examining the differential effects of treatment on the subgroup samples separately or, preferably, by examining treatment-by-subgroup interaction effects within the entire sample, which is thought to limit the frequency of spurious findings (19). Few studies have used such analyses to evaluate whether supported housing and treatment-only models of care have different effects on individuals with differing characteristics. Given the scarcity of resources available for such programs, policy makers have an interest in learning whether some subgroups benefit more than others from such services (1416).

In this study, we examined diverse outcomes of a supported housing intervention among four patient subgroups that have been associated in previous research with differential treatment outcomes (2,3,8,2023). The subgroups are defined by race, age, co-occurring diagnoses of substance use disorders and mental illness, and current substance use at program entry.

The existence of racial and ethnic disparities in mental health treatment has been well documented (24). Research has also shown that compared with whites, African Americans experience poorer access to health care, have greater unmet needs for mental health and substance abuse treatment, and have been subject to housing discrimination (25,26). A recent study that did not use subgroup analyses found that compared with white veterans, African-American veterans experienced greater delays in becoming housed but no difference in housing tenure once housed (23).

Second, there is a need to identify types of treatments and services that best serve the unique needs of the growing population of older adults. Some older adults may be at especially high risk of homelessness because of reductions in social support (for example, the death of a spouse or partner), increased isolation, lack of availability of appropriate medical and social services, and increases in comorbid medical conditions (27). An examination of data on Veterans Affairs (VA) patients age 65 or older concluded that compared to the general population of aged individuals, older veterans carried significantly more risk factors for suicide, including higher rates of depression and substance abuse, poorer social support, and more comorbid chronic general medical conditions (28). Older veterans who served in Vietnam seem to be a particularly vulnerable group for medical and psychological risk factors (29).

The selection of the third subgroup, individuals with co-occurring mental health and substance use disorders or with only a substance use disorder, was informed by recent commentary on supported housing that suggested that individuals with addictive disorders may have more positive housing outcomes in models that emphasize initial placement into homes regardless of continued substance use but may have more positive clinical outcomes in models that address treatment issues before housing is secured (16). The programming associated with many supported housing models is often geared toward addressing behavioral health issues. Thus individuals with a co-occurring psychiatric diagnosis may be a special subgroup whose experience in supported housing deserves further examination.

Finally, there has been considerable debate about whether abstinence from alcohol or drugs should be a prerequisite to independent housing (30,31). One recent study used interactional subgroup analyses to compare outcomes among individuals who were or were not abstinent at the time of housing (15). Active substance use at the time of housing entry was associated with higher rates of substance use over time and poorer mental health outcomes but with no differences in housing outcomes. Although these data provide some evidence in support of harm reduction approaches, additional research is needed to understand differential outcomes for individuals with substance use disorders who may be using substances at the time of entry into supported housing programs.

This study used outcome data from an experimental trial of the Department of Housing and Urban Development and the VA Supported Housing program (HUD-VASH), which was initiated in 1992 to provide permanent housing subsidies (vouchers) and intensive case management (ICM) to homeless veterans with psychiatric and substance use disorders. A total of 460 veterans at four sites were randomly assigned to HUD-VASH (N=182), ICM only (N=90), or treatment as usual (N=188) (9). Findings from noninteraction subgroup analyses indicated that outcomes for veterans belonging to different subgroup samples did not differ from those of veterans in the larger study (9).

This descriptive study expands upon the results of the experimental trial by employing a more rigorous analysis of the interaction of treatment assignment by four patient characteristics—minority race, older age, co-occurring diagnoses of mental illness and substance use disorders, and active use of drugs or alcohol at the time of program entry. Although we regard this study as primarily descriptive, we hypothesized that these potentially vulnerable subgroups, albeit overlapping in membership to some degree, would derive significantly greater benefit than other veterans from the rapid access to housing vouchers offered by the HUD-VASH program. Perhaps less vulnerable subgroups have additional supports or resources that may moderate the negative impacts of the longer waits for access to housing in the ICM or treatment as usual conditions.

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Procedures

Recruitment for the study took place between June 1, 1992, and December 31, 1995. In addition to VA eligibility, criteria for inclusion in the HUD-VASH program included living in a shelter or on the street for at least 30 days and the presence of a psychiatric or substance use disorder at the time of initial contact with the VA’s Health Care for Homeless Veterans program, which provided the intensive case management and treatment-as-usual supports to veterans in the study.

Participants were given a complete description of the study, and written informed consent was obtained. After a detailed baseline assessment, participants were assigned at random in 2:1:2 proportions to HUD-VASH, ICM, or standard, short-term VA homeless service (treatment as usual). HUD-VASH and ICM case managers had a maximum caseload of 25 clients and, through use of a modified assertive community treatment model (ACT) (32), encouraged weekly face-to-face contact, delivered community-based care, and provided linkages to VA services, including employment and substance abuse counseling (9). The primary modifications of the ACT model were the larger caseloads and the fact that clients were encouraged to use other VA health services as needed.

In addition to receiving ICM, participants in the HUD-VASH condition were given priority access to a Section 8 housing voucher and assistance from case managers to obtain a housing voucher and locate an apartment. Retaining the apartment was not contingent upon involvement in VA or case management treatment, although continued involvement was encouraged. Participants in treatment as usual received standard care, which involved shorter-term, brokered case management to ensure referrals to VA health services.

Independent research assistants conducted follow-up interviews every three months for up to five years or for as long as participants continued in the program. The protocol was approved by the human investigations committees at each VA medical center. Participants were paid $20 after each interview.

Of the 460 individuals who participated in the experimental trial, 41 did not have a follow-up interview after baseline. Although interviews were scheduled to occur every three months, they were not always conducted according to schedule. For each remaining individual, we identified the interviews conducted closest to six, 12, 18, 24, 30, and 36 months after the baseline time period. An interview was included in the analysis if it fell within a 30-day window before or after the scheduled interview date. Using these parameters, we determined that 307 individuals had a six-month interview, 332 had a 12-month interview, 318 had an 18-month interview, 306 had a 24-month interview, 230 had a 30-month interview, and 216 had a 36-month interview. Given the proportion of people who did not remain in the study after the 24-month period, we limited the current analysis to the interviews conducted at six-month intervals during the 24 months after baseline.

Of the 306 remaining individuals, ten were females, 11 (one female) were of an ethnicity other than African American or Caucasian, 27 (two females) had a diagnosis of mental illness without a substance use disorder, and two were missing data on gender or ethnicity. Because the purpose of the study was to identify patterns of outcomes for well-defined subgroups of individuals, these 47 veterans were excluded from the analysis, leaving a total sample of 259 veterans with diagnoses of a substance use disorder (N=119, HUD-VASH; N=52, ICM; and N=88, treatment as usual).

In addition to having differences in diagnoses, gender, and ethnicity, participants in the sample had fewer years of formal education, less income, a history of more minor crimes, larger social networks, and more medical problems than participants who were not included in the sample.

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Measures

The baseline and follow-up interviews assessed, among other things, demographic characteristics, duration of current episode of homelessness, and number of nights in the previous 90 days categorized as days housed (one’s own or someone else’s apartment or house), days in institutions (hospital or nursing home or domiciliary), days homeless (hotel or boarding home, shelter, outdoors or abandoned building, or automobile or boat), or days in other residences.

Composite scores and information about days of drug or alcohol use in the past 30 days, including days of intoxication, from the Addiction Severity Index (ASI) (33) were used to assess alcohol, drug, and psychiatric status. Higher scores on the ASI alcohol, drug, and psychiatric subscales indicate more serious problems. Employment was assessed by the number of days employed in the past 30 days. Quality of life was evaluated with the satisfaction-with-living-situation subscale and a question about how the individual feels about his or her life from the Lehman Quality of Life Interview (34). Responses range from 1 to 7, with higher scores indicating greater satisfaction with living situation and life in general.

Social support was measured by the number of people in nine different categories to whom the participant reported feeling close and an index of the total frequency of contacts with these people, with higher scores on the index reflecting more frequent contact (35).

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Analysis

A series of univariate analyses of variance (ANOVAs) and chi square analyses were conducted to identify baseline characteristics that significantly differentiated participants within the four subgroups. To compare the groups on outcomes over the four follow-up periods, linear mixed-effects regression models with scaled identity or diagonal covariance matrices were evaluated by using the SPSS-Linear Mixed Model (36). The interactions between treatment group and participant subgroup were modeled, with random intercepts for participants and fixed effects for treatment condition and subgroup, significant baseline covariates differentiating subgroups, a dummy-coded site variable, time since baseline, and the baseline value of the dependent variable. Separate models were conducted to examine the two-way interaction between time and subgroup. A Bonferroni correction was applied to correct for multiple comparisons, so that p≤.01 was considered significant.

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Sample characteristics

Four subgroups were identified for the analyses: African Americans (N=172, 66%) versus Caucasians (N=87, 34%), older (N=132, 51%) versus younger (N=127, 49%) participants, individuals with co-occurring mental disorders (N=145, 56%) versus individuals with a substance use disorder only (N=114, 44%), and active (N=99, 38%) versus less active (N=160, 62%) users of drugs and alcohol. Older and younger individuals were defined as persons above or below the median age of 42.3 years. Active drug or alcohol use was defined as the use of drugs or alcohol on 15 or more of the 30 days prior to baseline. The demographic characteristics of the subgroups and results of subgroup comparisons are presented in Table 1 and Table 2.

 
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Table 1Sociodemographic variables at baseline among 259 veterans with a history of a substance use disorder, by treatment condition and sociodemographic or clinical subgroup
Table Footer Note

a ICM, intensive case management; HUD-VASH, U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing. Significant differences were found between ICM and treatment as usual on days housed (p<.01).

Table Footer Note

b Significant differences were found between the white and black veterans on age (p<.05).

Table Footer Note

c Age groups were below or equal to (younger) or above (older) the median age of 42.3 years. Significant differences were found between the younger and older veterans on age and months in war zone (p<.001) and race (p<.05).

Table Footer Note

d Significant differences were found between veterans with and without a co-occurring mental disorder on race and years of education (p<.05); service-connected psychiatric disability (p<.01); and days homeless, days in institution, and months in war zone (p<.001).

Table Footer Note

e Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview. Significant differences were found between veterans with less active and active substance abuse on age, percentage of income from benefits, and month in war zone (p<.05).

Table Footer Note

f Past 30 days

Table Footer Note

g Past 90 days

 
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Table 2Socioclinical variables at baseline among 259 veterans with a history of a substance use disorder, by treatment condition and sociodemographic or clinical subgroup
Table Footer Note

a ICM, intensive case management; HUD-VASH, U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing

Table Footer Note

b Significant differences were found between white and black veterans on the percentage with a mood disorder, a co-occurring mental disorder, thoughts of suicide, and a serious medical condition and on substance abuse expenditures (p<.05); on social network contacts (p<.01); and on minor crimes and social network members and the percentage with drug abuse or dependence (p<.001).

Table Footer Note

c Age groups were below or equal to (younger) or above (older) the median age of 42.3 years. Significant differences were found between the younger and older veterans on days intoxicated, substance abuse expenditures, and social network contacts (p<.05); on the percentage with a co-occurring mental disorder and thoughts of suicide, drug use, and social network members (p<.01); and on income spent on drugs and on the percentage of veterans with drug abuse or dependence, posttraumatic stress disorder (PTSD), or a serious medical condition (p<.001).

Table Footer Note

d Significant differences were found between veterans with and without a co-occurring mental disorder on the percentage with other psychotic disorder, quality of life, and social network contacts (p<.05); on the percentage with schizophrenia or mood disorder (p<.01); and on the percentage with drug abuse or dependence or PTSD and thoughts of suicide (p<.001).

Table Footer Note

e Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview. Significant differences were found between veterans with less active and active substance abuse on the percentage with a serious medical condition (p<.05) and on days intoxicated, days used drugs, income spent on drugs, and substance abuse expenditures (p<.001).

Table Footer Note

f Past 30 days

Table Footer Note

g Measured by the Lehman Quality of Life Scale. Possible scores range from 1 to 7, with higher scores indicating greater satisfaction with living situation.

Table Footer Note

h Measured by the Quality of Life Interview. Possible scores range from 1 to 7, with higher scores indicating greater quality of life.

Table Footer Note

i Past 90 days

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Outcomes of HUD-VASH, subgroup, and time: main effects

After controlling for significant covariates, as in the original study, the study found that veterans in HUD-VASH had better housing outcomes than veterans receiving ICM or standard care, as indicated by average results across all follow-up time periods for days housed, days homeless, and days institutionalized (Table 3 and Table 4, model 1).

 
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Table 3Housing and other outcomes among 259 veterans with a history of a substance use disorder, by treatment condition and sociodemographic or clinical characteristica
Table Footer Note

a Data are estimated marginal means averaged across the 2-year follow-up period and controlled for significant baseline covariates in the model. Data are reported for the past 90 days for days housed, days homeless, and days in institutions and for the past 30 days for days intoxicated, days of drug use, and days worked.

Table Footer Note

b Possible scores on the Addiction Severity Index psychiatric (ASIP), alcohol (ASIA), and drug (ASID) subscales range from 0 to 1, with higher scores indicating more serious problems.

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cMeasured by the Quality of Life Interview. Possible scores range from 1 to 7, with higher scores indicating greater quality of life.

Table Footer Note

d Frequency of contacts in the past 90 days with individuals with whom the veteran feels close. Possible scores range from 0 to 6, with higher scores indicating greater frequency of contact.

Table Footer Note

e Significant differences were found between veterans in the U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing (HUD-VASH) versus treatment as usual and intensive case management (ICM) in days housed, days homeless, and days in institution (p<.001).

Table Footer Note

f Significant differences were found between white and black veterans in scores for ASIP and ASIA (p<.01) and days of drug use (p<.001).

Table Footer Note

g Significant differences were found between veterans with and without a co-occurring mental disorder in days homeless and social contacts (p<.01) and in days housed, scores for ASIP, and quality of life (p<.001).

Table Footer Note

h Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview.

On other outcome main effects, African Americans, who had significantly lower baseline scores on ASI psychiatric and alcohol subscales, reported fewer days of use of drugs than Caucasian individuals across all follow-up time periods. Individuals with co-occurring mental disorders were housed fewer days, had more days homeless, had higher ASI psychiatric scores, and had fewer social network contacts and lower ratings of quality of life across the follow-up periods than individuals with only a substance use disorder.

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Subgroup-by-time interactions independent of treatment

A second set of models analyzed subgroup by time interactions for each of the main effects and covariates presented in Table 3 (data not shown). Comparison of baseline and follow-up values among African Americans and Caucasians found that African-American veterans experienced significantly greater decreases than Caucasian veterans in ASI psychiatric scores at 24 months, ASI alcohol scores at 18 and 24 months, ASI drug scores at 18 and 24 months, and days of drug use at 18 and 24 months.

Compared with younger veterans, older individuals had significantly fewer gains at 18 and 24 months in days worked and less decrease at six months in days of drug use.

Individuals with a co-occurring psychiatric disorder versus those with only a substance use disorder had significantly less improvement after 18 months in days housed, greater reductions after 12 and 24 months in days homeless, greater increases after 12, 18, and 24 months in days institutionalized, less increase after 24 months in social network contact, and less improvement during all follow-up periods in days employed.

Main effects of time showed that active substance users had significantly greater decreases in ASI alcohol and drug scores, days intoxicated, and days of drug use over time than less active substance users.

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Subgroup-by-treatment condition interaction effects

A final set of four models examined the addition of a subgroup by treatment interaction term, the term of principal interest, to the previous model. Significant interactions (p<.01) were found for at least one outcome for all subgroups except older individuals (Table 4). [A set of figures describing significant findings of the four models is available online as a data supplement to this article.]

 
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Table 4Estimates of main effects and subgroup by condition interaction terms among 259 veterans enrolled in treatment as usual, HUD-VASH, or ICMa
Table Footer Note

a Linear mixed-model analyses were used. Covariates included all baseline variables with one or more significant between-subgroup differences (p<.05) and baseline values of the dependent variable. HUD–VASH, U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing; ICM, intensive case management

Table Footer Note

b Addiction Severity Index psychiatric (ASIP), alcohol (ASIA), and drug (ASID) subscales

Table Footer Note

c Age subgroups were classified as equal to or below (younger) or above (older) the median age of 42.3 years.

Table Footer Note

d Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview.

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Race.

Significant interactions were found between race and treatment condition for days homeless, days institutionalized, drug use, quality of life, and employment (Table 4, model 2). A comparison of the impact of HUD-VASH and ICM on African Americans versus Caucasians found that among African Americans, HUD-VASH had a lesser impact on reducing days homeless (t=–2.8, df=905, p=.01, B=–15.5), a greater impact on reducing days institutionalized (t=2.9, df=905, p<.01, B=16.4), and a greater impact on reducing drug use (t=3.3, df=880, p=.001, B=.07) and was associated with greater improvements in quality of life (t=–2.6, df=906, p<.01, B=–.65). The number of days employed among veterans enrolled in HUD-VASH compared with veterans who received treatment as usual was greater among African Americans than among Caucasians (t=3.1, df=902, p=.001, B=–4.8).

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Co-occurring disorders.

HUD-VASH was associated with fewer days homeless than treatment as usual among individuals with co-occurring disorders but not among individuals with only a substance use disorder (t=–3.0, df=905, p=.001, B=13.9).

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Active substance use.

Active substance users had significantly more days housed (t=–2.5, df=905, p=.01, B=–16.9) and significantly fewer days homeless (t=2.6, df=905, p<.01, B=13.7) than less active substance users among the veterans enrolled in HUD-VASH compared with those enrolled in ICM.

This study examined the degree to which supported housing, as implemented through the HUD-VASH program, may have contributed to especially beneficial outcomes for several high-risk subgroups of homeless veterans. Although a number of studies have found that supported housing enhances housing outcomes but does not reduce substance use (16,31), our data suggested that these effects may not be universal across subgroups. Comparison of housing outcomes among veterans enrolled in HUD-VASH and treatment-only conditions found that the access to housing vouchers facilitated by HUD-VASH was associated with particularly beneficial housing outcomes for Caucasian veterans, veterans with co-occurring disorders, and veterans with more active substance use.

Services provided through supported housing such as HUD-VASH may be a better fit for individuals who struggle with psychiatric illnesses in addition to substance use, perhaps because the types of programming or service agencies may be more geared toward behavioral health issues. Although active substance users did not experience differential rates of improvement on socioclinical outcomes, the positive housing findings among individuals who reported drinking or using drugs more than 15 days a month at baseline may provide further evidence in support of harm reduction models of housing, such as Housing First.

African Americans enrolled in HUD-VASH seemed to derive more benefit in socioclinical outcomes than in housing outcomes compared with Caucasians. African Americans in HUD-VASH also demonstrated greater reductions in severity of drug problems, greater decreases in days institutionalized, more improvement in quality of life, and more days employed than African-American veterans in treatment-only conditions. The more positive housing outcomes for Caucasians enrolled in HUD-VASH seems to be attributable largely to an increase in days homeless from baseline to six and 12 months among Caucasians enrolled in ICM. It is possible that African Americans were able to avoid a similar uptick in days homeless because their larger social networks, identified at baseline, provided interim housing supports that were not available to Caucasian veterans. Research has shown that African Americans who participate in supported-housing programs report stronger religious faith and greater religious participation than Caucasian individuals (37). These connections may have also served to provide external, natural supports that augmented treatment efforts.

Finally, the lack of differential findings by age suggests that for older veterans, most of whom served during the Vietnam era, receiving VA treatment may mitigate vulnerabilities otherwise associated with aging. Given that older individuals may be less likely to seek treatment in nonspecialty settings (27), more likely to use Medicare services than VA health care (38), and unaware of their VA benefits (39), older homeless veterans who are not engaged in VA care may experience more negative outcomes.

The results of this study, which conducted interactional analyses, are different from the findings of the original subgroup analyses reported in 2003 (9), which presented separate analyses for the different subgroups. These differential subgroup analyses highlighted the importance of conducting interactional subgroup analyses to test the assumption that supported housing has similar benefits for all subgroups.

The study had some limitations. Data analyzed in this study were collected in the 1990s as part of the first wave of HUD-VASH voucher administration. Although the data are older, the model of care and housing supports is very similar to models used today. Given that a second major wave of HUD-VASH vouchers has been released, and the field’s continued need for information about the differential impacts of programs on subgroups of individuals, the findings are relevant, timely, and useful in informing analyses of future HUD-VASH data.

Second, individuals were categorized into active or less active substance-use groups on the basis of data from a single, self-report measure—the ASI. The ASI has been criticized for having unstable criterion-related validity and is subject to under- or overreporting of use (40,41). However, as recommended by some authors, this study reports both composite scores and days reported of alcohol and drug use.

Additionally, because of comparatively small representation in the sample, females, Hispanics, individuals who did not remain in the study for 24 months, and individuals without a substance use diagnosis were excluded from the analyses. Compared with excluded veterans, those in the analytic sample had less formal education, less income, a history of more minor crimes, larger social networks, and more medical problems. Thus the generalizability of the results are limited to non-Hispanic Caucasian or African-American male veterans with a substance use disorder who share those socioeconomic, criminal, and medical characteristics—a fairly common profile for VA patients.

Finally, because it is impossible to include all individual characteristics in statistical models, the average findings for a subsample should not be overinterpreted or used to determine the treatment of individuals (42). Descriptive subgroup findings such as those presented here may be helpful, however, in highlighting potential areas for further investigation or hypothesis generation (19).

In this study, supported housing offered by HUD-VASH was associated with more positive housing outcomes for Caucasians, veterans with co-occurring psychiatric disorders, and individuals with active substance use and with more positive socioclinical outcomes for African Americans. Further exploration of interactions among sociodemographic and clinical subgroups of individuals should be conducted to inform not only supported housing but also other community-based mental health programs.

This study was funded by the Veterans Affairs New England Mental Illness Research, Education and Clinical Center.

The authors report no competing interests.

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Kertesz  SG;  Crouch  K;  Milby  JB  et al:  Housing first for homeless persons with active addiction: are we overreaching? Milbank Quarterly 87:495–534, 2009
[CrossRef] | [PubMed]
 
Leff  HS;  Chow  CM;  Pepin  R  et al:  Does one size fit all? What we can and can’t learn from a meta-analysis of housing models for persons with mental illness.  Psychiatric Services 60:473–482, 2009
[CrossRef] | [PubMed]
 
Lagakos  SW:  The challenge of subgroup analyses—reporting without distorting.  New England Journal of Medicine 354:1667–1669, 2006
[CrossRef] | [PubMed]
 
Brookes  ST;  Whitley  E;  Peters  TJ  et al:  Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and false-negatives.  Health Technology Assessment 5:1–56, 2001
[PubMed]
 
Folsom  DP;  Hawthorne  W;  Lindamer  L  et al:  Prevalence and risk factors for homelessness and utilization of mental health services among 10,340 patients with serious mental illness in a large public mental health system.  American Journal of Psychiatry 162:370–376, 2005
[CrossRef] | [PubMed]
 
Bebout  RR;  Drake  RE;  Xie  H  et al:  Housing status among formerly homeless dually diagnosed adults.  Psychiatric Services 48:936–941, 1997
[PubMed]
 
Olfson  M;  Mechanic  D;  Hansell  S  et al:  Prediction of homelessness within three months of discharge among inpatients with schizophrenia.  Psychiatric Services 50:667–673, 1999
[PubMed]
 
O’Connell  M;  Kasprow  W;  Rosenheck  RA:  National dissemination of supported housing in the VA: model adherence vs model modification.  Psychosocial Rehabilitation Journal 33:308–319, 2010
[CrossRef]
 
 Mental Health: Culture, Race, and Ethnicity—A Supplement to Mental Health: A Report of the Surgeon General .  Rockville, Md,  US Department of Health and Human Services, 2001
 
Alegría  M;  Canino  G;  Ríos  R  et al:  Inequalities in use of specialty mental health services among Latinos, African Americans, and non-Latino whites.  Psychiatric Services 53:1547–1555, 2002
[CrossRef] | [PubMed]
 
Wells  K;  Klap  R;  Koike  A  et al:  Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care.  American Journal of Psychiatry 158:2027–2032, 2001
[CrossRef] | [PubMed]
 
Crane  M;  Warnes  AM:  Homelessness among older people and service responses.  Reviews in Clinical Gerontology 20:354–363, 2010
[CrossRef]
 
Lambert  MT;  Fowler  DR:  Suicide risk factors among veterans: risk management in the changing culture of the Department of Veterans Affairs.  Journal of Mental Health Administration 24:350–358, 1997
[CrossRef] | [PubMed]
 
Brooks  MS;  Laditka  SB;  Laditka  JN:  Evidence of greater health care needs among older veterans of the Vietnam War.  Military Medicine 173:715–720, 2008
[PubMed]
 
Tsemberis  S;  Asmussen  S:  From streets to homes: pathways to housing consumer preference supported housing model.  Alcoholism Treatment Quarterly 17:113–131, 1999
[CrossRef]
 
Tsemberis  S;  Gulcur  L;  Nakae  M:  Housing First, consumer choice, and harm reduction for homeless individuals with a dual diagnosis.  American Journal of Public Health 94:651–656, 2004
[CrossRef] | [PubMed]
 
Stein  LI;  Santos  AB:  Assertive Community Treatment of Persons With Severe Mental Illness .  New York,   Norton, 1998
 
McLellan  AT;  Luborsky  L;  Woody  GE  et al:  An improved diagnostic evaluation instrument for substance abuse patients: the Addiction Severity Index.  Journal of Nervous and Mental Disease 168:26–33, 1980
[CrossRef] | [PubMed]
 
Lehman  A:  A quality of life interview for the chronically mentally ill.  Evaluation and Program Planning 11:51–62, 1988
[CrossRef]
 
Lam  JA;  Rosenheck  R:  Social support and service use among homeless persons with serious mental illness.  International Journal of Social Psychiatry 45:13–28, 1999
[CrossRef] | [PubMed]
 
 IBM SPSS Statistics 18 for Windows, Rel 18.0.0 .  Chicago,  SPSS Inc, 2009
 
Tsai  J;  Rosenheck  RA:  Racial differences among supported housing clients in outcomes and therapeutic relationships.  Psychiatric Quarterly 83:103–112, 2012
[CrossRef] | [PubMed]
 
Weeks  WB;  Bott  DM;  Lamkin  RP  et al:  Veterans Health Administration and Medicare outpatient health care utilization by older rural and urban New England veterans.  Journal of Rural Health 21:167–171, 2005
[CrossRef] | [PubMed]
 
National Survey of Veterans, Active Duty Service Members, Demobilized National Guard and Reserve Members, Family Members, and Surviving Spouses. Washington, DC, US Department of Veterans Affairs, 2010. Available at www.va.gov/vetdata/docs/SurveysAndStudies/NVSSurveyFinalWeightedReport.pdf
 
Eyrich  KM;  North  CS;  Pollio  DE:  Comparing methods of drug-use data collection: self-report screener versus urine drug test versus self-report CIDI-SAM (abstract).  Drug and Alcohol Dependence 63(suppl 1):S45, 2001
 
Mäkelä  K:  Studies of the reliability and validity of the Addiction Severity Index.  Addiction 99:398–410, discussion 411–418, 2004
[CrossRef] | [PubMed]
 
Yusuf  S;  Wittes  J;  Probstfield  J  et al:  Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials.  JAMA 266:93–98, 1991
[CrossRef] | [PubMed]
 
References Container
Anchor for Jump
Table 1Sociodemographic variables at baseline among 259 veterans with a history of a substance use disorder, by treatment condition and sociodemographic or clinical subgroup
Table Footer Note

a ICM, intensive case management; HUD-VASH, U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing. Significant differences were found between ICM and treatment as usual on days housed (p<.01).

Table Footer Note

b Significant differences were found between the white and black veterans on age (p<.05).

Table Footer Note

c Age groups were below or equal to (younger) or above (older) the median age of 42.3 years. Significant differences were found between the younger and older veterans on age and months in war zone (p<.001) and race (p<.05).

Table Footer Note

d Significant differences were found between veterans with and without a co-occurring mental disorder on race and years of education (p<.05); service-connected psychiatric disability (p<.01); and days homeless, days in institution, and months in war zone (p<.001).

Table Footer Note

e Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview. Significant differences were found between veterans with less active and active substance abuse on age, percentage of income from benefits, and month in war zone (p<.05).

Table Footer Note

f Past 30 days

Table Footer Note

g Past 90 days

Anchor for Jump
Table 2Socioclinical variables at baseline among 259 veterans with a history of a substance use disorder, by treatment condition and sociodemographic or clinical subgroup
Table Footer Note

a ICM, intensive case management; HUD-VASH, U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing

Table Footer Note

b Significant differences were found between white and black veterans on the percentage with a mood disorder, a co-occurring mental disorder, thoughts of suicide, and a serious medical condition and on substance abuse expenditures (p<.05); on social network contacts (p<.01); and on minor crimes and social network members and the percentage with drug abuse or dependence (p<.001).

Table Footer Note

c Age groups were below or equal to (younger) or above (older) the median age of 42.3 years. Significant differences were found between the younger and older veterans on days intoxicated, substance abuse expenditures, and social network contacts (p<.05); on the percentage with a co-occurring mental disorder and thoughts of suicide, drug use, and social network members (p<.01); and on income spent on drugs and on the percentage of veterans with drug abuse or dependence, posttraumatic stress disorder (PTSD), or a serious medical condition (p<.001).

Table Footer Note

d Significant differences were found between veterans with and without a co-occurring mental disorder on the percentage with other psychotic disorder, quality of life, and social network contacts (p<.05); on the percentage with schizophrenia or mood disorder (p<.01); and on the percentage with drug abuse or dependence or PTSD and thoughts of suicide (p<.001).

Table Footer Note

e Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview. Significant differences were found between veterans with less active and active substance abuse on the percentage with a serious medical condition (p<.05) and on days intoxicated, days used drugs, income spent on drugs, and substance abuse expenditures (p<.001).

Table Footer Note

f Past 30 days

Table Footer Note

g Measured by the Lehman Quality of Life Scale. Possible scores range from 1 to 7, with higher scores indicating greater satisfaction with living situation.

Table Footer Note

h Measured by the Quality of Life Interview. Possible scores range from 1 to 7, with higher scores indicating greater quality of life.

Table Footer Note

i Past 90 days

Anchor for Jump
Table 3Housing and other outcomes among 259 veterans with a history of a substance use disorder, by treatment condition and sociodemographic or clinical characteristica
Table Footer Note

a Data are estimated marginal means averaged across the 2-year follow-up period and controlled for significant baseline covariates in the model. Data are reported for the past 90 days for days housed, days homeless, and days in institutions and for the past 30 days for days intoxicated, days of drug use, and days worked.

Table Footer Note

b Possible scores on the Addiction Severity Index psychiatric (ASIP), alcohol (ASIA), and drug (ASID) subscales range from 0 to 1, with higher scores indicating more serious problems.

Table Footer Note

cMeasured by the Quality of Life Interview. Possible scores range from 1 to 7, with higher scores indicating greater quality of life.

Table Footer Note

d Frequency of contacts in the past 90 days with individuals with whom the veteran feels close. Possible scores range from 0 to 6, with higher scores indicating greater frequency of contact.

Table Footer Note

e Significant differences were found between veterans in the U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing (HUD-VASH) versus treatment as usual and intensive case management (ICM) in days housed, days homeless, and days in institution (p<.001).

Table Footer Note

f Significant differences were found between white and black veterans in scores for ASIP and ASIA (p<.01) and days of drug use (p<.001).

Table Footer Note

g Significant differences were found between veterans with and without a co-occurring mental disorder in days homeless and social contacts (p<.01) and in days housed, scores for ASIP, and quality of life (p<.001).

Table Footer Note

h Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview.

Anchor for Jump
Table 4Estimates of main effects and subgroup by condition interaction terms among 259 veterans enrolled in treatment as usual, HUD-VASH, or ICMa
Table Footer Note

a Linear mixed-model analyses were used. Covariates included all baseline variables with one or more significant between-subgroup differences (p<.05) and baseline values of the dependent variable. HUD–VASH, U.S. Department of Housing and Urban Development–Veterans Affairs Supported Housing; ICM, intensive case management

Table Footer Note

b Addiction Severity Index psychiatric (ASIP), alcohol (ASIA), and drug (ASID) subscales

Table Footer Note

c Age subgroups were classified as equal to or below (younger) or above (older) the median age of 42.3 years.

Table Footer Note

d Less active substance use was fewer than 15 days and active substance abuse was 15 days or more of alcohol or drug use in the 30 days prior to the baseline interview.

+

References

Cheng  A-L;  Lin  H;  Kasprow  W  et al:  Impact of supported housing on clinical outcomes: analysis of a randomized trial using multiple imputation technique.  Journal of Nervous and Mental Disease 195:83–88, 2007
[CrossRef] | [PubMed]
 
Goldfinger  SM;  Schutt  RK;  Tolomiczenko  GS  et al:  Housing placement and subsequent days homeless among formerly homeless adults with mental illness.  Psychiatric Services 50:674–679, 1999
[PubMed]
 
Hurlburt  MS;  Hough  RL;  Wood  PA:  Effects of substance abuse on housing stability of homeless mentally ill persons in supported housing.  Psychiatric Services 47:731–736, 1996
[PubMed]
 
Hurlburt  MS;  Wood  PA;  Hough  RL:  Providing independent housing for the homeless mentally ill: a novel approach to evaluating long-term longitudinal housing patterns.  Journal of Community Psychology 24:291–310, 1996
[CrossRef]
 
Kasprow  WJ;  Rosenheck  RA;  Frisman  L  et al:  Referral and housing processes in a long-term supported housing program for homeless veterans.  Psychiatric Services 51:1017–1023, 2000
[CrossRef] | [PubMed]
 
Lehman  AF;  Dixon  LB;  Kernan  E  et al:  A randomized trial of assertive community treatment for homeless persons with severe mental illness.  Archives of General Psychiatry 54:1038–1043, 1997
[CrossRef] | [PubMed]
 
Lipton  FR;  Siegel  C;  Hannigan  A  et al:  Tenure in supportive housing for homeless persons with severe mental illness.  Psychiatric Services 51:479–486, 2000
[CrossRef] | [PubMed]
 
O’Connell  MJ;  Kasprow  W;  Rosenheck  RA:  Rates and risk factors for homelessness after successful housing in a sample of formerly homeless veterans.  Psychiatric Services 59:268–275, 2008
[CrossRef] | [PubMed]
 
Rosenheck  R;  Kasprow  W;  Frisman  L  et al:  Cost-effectiveness of supported housing for homeless persons with mental illness.  Archives of General Psychiatry 60:940–951, 2003
[CrossRef] | [PubMed]
 
Shern  DL;  Tsemberis  S;  Anthony  W  et al:  Serving street-dwelling individuals with psychiatric disabilities: outcomes of a psychiatric rehabilitation clinical trial.  American Journal of Public Health 90:1873–1878, 2000
[CrossRef] | [PubMed]
 
Shern  DL;  Tsemberis  S;  Winarski  J  et al:  The effectiveness of psychiatric rehabilitation for persons who are street dwelling with serious disability related to mental illness; in  Mentally Ill and Homeless: Special Programs for Special Needs . Edited by Breakey  WR;  Thompson  JW.  Amsterdam,  Harwood Academic, 1997
 
Tsemberis  SJ;  Moran  L;  Shinn  M  et al:  Consumer preference programs for individuals who are homeless and have psychiatric disabilities: a drop-in center and a supported housing program.  American Journal of Community Psychology 32:305–317, 2003
[CrossRef] | [PubMed]
 
Dennis  DL;  Buckner  JC;  Lipton  FR  et al:  A decade of research and services for homeless mentally ill persons: where do we stand? American Psychologist 46:1129–1138, 1991
[CrossRef] | [PubMed]
 
Newman  S;  Goldman  H:  Putting housing first, making housing last: housing policy for persons with severe mental illness.  American Journal of Psychiatry 165:1242–1248, 2008
[CrossRef] | [PubMed]
 
Edens  EL;  Mares  AS;  Tsai  J  et al:  Does active substance use at housing entry impair outcomes in supported housing for chronically homeless persons? Psychiatric Services 62:171–178, 2011
[CrossRef] | [PubMed]
 
Kertesz  SG;  Crouch  K;  Milby  JB  et al:  Housing first for homeless persons with active addiction: are we overreaching? Milbank Quarterly 87:495–534, 2009
[CrossRef] | [PubMed]
 
Leff  HS;  Chow  CM;  Pepin  R  et al:  Does one size fit all? What we can and can’t learn from a meta-analysis of housing models for persons with mental illness.  Psychiatric Services 60:473–482, 2009
[CrossRef] | [PubMed]
 
Lagakos  SW:  The challenge of subgroup analyses—reporting without distorting.  New England Journal of Medicine 354:1667–1669, 2006
[CrossRef] | [PubMed]
 
Brookes  ST;  Whitley  E;  Peters  TJ  et al:  Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and false-negatives.  Health Technology Assessment 5:1–56, 2001
[PubMed]
 
Folsom  DP;  Hawthorne  W;  Lindamer  L  et al:  Prevalence and risk factors for homelessness and utilization of mental health services among 10,340 patients with serious mental illness in a large public mental health system.  American Journal of Psychiatry 162:370–376, 2005
[CrossRef] | [PubMed]
 
Bebout  RR;  Drake  RE;  Xie  H  et al:  Housing status among formerly homeless dually diagnosed adults.  Psychiatric Services 48:936–941, 1997
[PubMed]
 
Olfson  M;  Mechanic  D;  Hansell  S  et al:  Prediction of homelessness within three months of discharge among inpatients with schizophrenia.  Psychiatric Services 50:667–673, 1999
[PubMed]
 
O’Connell  M;  Kasprow  W;  Rosenheck  RA:  National dissemination of supported housing in the VA: model adherence vs model modification.  Psychosocial Rehabilitation Journal 33:308–319, 2010
[CrossRef]
 
 Mental Health: Culture, Race, and Ethnicity—A Supplement to Mental Health: A Report of the Surgeon General .  Rockville, Md,  US Department of Health and Human Services, 2001
 
Alegría  M;  Canino  G;  Ríos  R  et al:  Inequalities in use of specialty mental health services among Latinos, African Americans, and non-Latino whites.  Psychiatric Services 53:1547–1555, 2002
[CrossRef] | [PubMed]
 
Wells  K;  Klap  R;  Koike  A  et al:  Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care.  American Journal of Psychiatry 158:2027–2032, 2001
[CrossRef] | [PubMed]
 
Crane  M;  Warnes  AM:  Homelessness among older people and service responses.  Reviews in Clinical Gerontology 20:354–363, 2010
[CrossRef]
 
Lambert  MT;  Fowler  DR:  Suicide risk factors among veterans: risk management in the changing culture of the Department of Veterans Affairs.  Journal of Mental Health Administration 24:350–358, 1997
[CrossRef] | [PubMed]
 
Brooks  MS;  Laditka  SB;  Laditka  JN:  Evidence of greater health care needs among older veterans of the Vietnam War.  Military Medicine 173:715–720, 2008
[PubMed]
 
Tsemberis  S;  Asmussen  S:  From streets to homes: pathways to housing consumer preference supported housing model.  Alcoholism Treatment Quarterly 17:113–131, 1999
[CrossRef]
 
Tsemberis  S;  Gulcur  L;  Nakae  M:  Housing First, consumer choice, and harm reduction for homeless individuals with a dual diagnosis.  American Journal of Public Health 94:651–656, 2004
[CrossRef] | [PubMed]
 
Stein  LI;  Santos  AB:  Assertive Community Treatment of Persons With Severe Mental Illness .  New York,   Norton, 1998
 
McLellan  AT;  Luborsky  L;  Woody  GE  et al:  An improved diagnostic evaluation instrument for substance abuse patients: the Addiction Severity Index.  Journal of Nervous and Mental Disease 168:26–33, 1980
[CrossRef] | [PubMed]
 
Lehman  A:  A quality of life interview for the chronically mentally ill.  Evaluation and Program Planning 11:51–62, 1988
[CrossRef]
 
Lam  JA;  Rosenheck  R:  Social support and service use among homeless persons with serious mental illness.  International Journal of Social Psychiatry 45:13–28, 1999
[CrossRef] | [PubMed]
 
 IBM SPSS Statistics 18 for Windows, Rel 18.0.0 .  Chicago,  SPSS Inc, 2009
 
Tsai  J;  Rosenheck  RA:  Racial differences among supported housing clients in outcomes and therapeutic relationships.  Psychiatric Quarterly 83:103–112, 2012
[CrossRef] | [PubMed]
 
Weeks  WB;  Bott  DM;  Lamkin  RP  et al:  Veterans Health Administration and Medicare outpatient health care utilization by older rural and urban New England veterans.  Journal of Rural Health 21:167–171, 2005
[CrossRef] | [PubMed]
 
National Survey of Veterans, Active Duty Service Members, Demobilized National Guard and Reserve Members, Family Members, and Surviving Spouses. Washington, DC, US Department of Veterans Affairs, 2010. Available at www.va.gov/vetdata/docs/SurveysAndStudies/NVSSurveyFinalWeightedReport.pdf
 
Eyrich  KM;  North  CS;  Pollio  DE:  Comparing methods of drug-use data collection: self-report screener versus urine drug test versus self-report CIDI-SAM (abstract).  Drug and Alcohol Dependence 63(suppl 1):S45, 2001
 
Mäkelä  K:  Studies of the reliability and validity of the Addiction Severity Index.  Addiction 99:398–410, discussion 411–418, 2004
[CrossRef] | [PubMed]
 
Yusuf  S;  Wittes  J;  Probstfield  J  et al:  Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials.  JAMA 266:93–98, 1991
[CrossRef] | [PubMed]
 
References Container
+
+

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