Skip to main content
Full access
Articles
Published Online: 15 October 2014

Characteristics and Service Use of Homeless Veterans and Nonveterans Residing in a Low-Demand Emergency Shelter

Abstract

Objectives

This study examined use of U.S. Department of Veterans Affairs (VA) and non-VA services and predictors of service use among veterans and nonveterans who resided in a low-demand emergency shelter.

Methods

Equal numbers (N=110) of veterans and nonveterans recruited between January and June 2008 at a low-demand emergency shelter were interviewed about demographic characteristics, histories of military service and homelessness, general medical and mental functioning, current alcohol and drug problems and substance use, and use of medical, psychiatric, and substance abuse services. The Behavioral Model for Vulnerable Populations was used to identify need-based, enabling, and predisposing variables for analysis.

Results

Both groups reported high rates of arrest and incarceration, very low incomes, extensive histories of homelessness, and a similar need for services. However, significantly more veterans than nonveterans used psychiatric services, nonemergency medical services, and inpatient substance use services. Similar proportions of veterans and nonveterans used public non-VA health care services. Need-based variables appropriately predicted service use, but veterans and individuals with insurance were also more likely to access services.

Conclusions

The veterans and nonveterans residing in a low-demand shelter faced several barriers to escaping homelessness. Both groups made similar use of non-VA services, but veterans used more services overall because of their access to VA services. The predictive power of insurance indicated that veterans may experience barriers to care despite the availability of VA services. The presence of veterans in this low-demand shelter may represent evidence of barriers to veteran and other public housing services.
Veterans of military service continue to represent a sizable subpopulation of the people who are homeless in the United States. Recent point-in-time counts identified just over 62,000 homeless veterans on a single night (1), and estimates are that over 130,000 veterans will experience homelessness over the course of a year (2).
For the general homeless population, assistance is offered by various programs, such as permanent supportive housing, transitional housing, emergency shelter, medical care, mental health and substance abuse treatment, employment training, and providers of food (3). Veterans of U.S. military service also may have access (based on eligibility) to an additional network of programs exclusively for veterans who are homeless (4). These programs, often provided by the U.S. Department of Veterans Affairs (VA), mirror many of those available to homeless nonveterans, including access to permanent supportive housing through the Department of Housing and Urban Development Veterans Affairs Supportive Housing (HUD-VASH) program (5).
Despite this array of assistance services, people who are homeless continue to seek services from low-demand, public emergency shelter programs that provide basic overnight shelter or shelter during inclement weather rather than engaging in long-term transitional or permanent supportive housing programs. For veterans who are homeless, the use of emergency shelters indicates a lack of engagement not only in mainstream housing assistance services but also in the VA continuum of care, including domiciliary care for homeless veterans and grant and per diem programs. Little is known about the characteristics of users of low-demand emergency shelters, and even less is known about the subset of homeless veterans who use these services.
The purpose of this study was to describe the characteristics of veterans and nonveterans who use low-demand shelters, identify variables that predict their use of services, and compare the predictors of use of services by veterans and nonveterans. The Behavioral Model for Vulnerable Populations (6) was used to identify variables that might predict service use. This model has been used extensively with homeless and other impoverished populations (4,610). It proposes that service use is driven by need for services (general medical, psychiatric, and substance abuse problems), predisposing characteristics (demographic characteristics, such as level of education and housing status), and enabling factors (insurance, income, and service use that facilitates further service use [medical service use that leads to psychiatric service use]).

Methods

Sample

The sample consisted of two subgroups, one of veterans and one of nonveterans, each comprising 110 unaccompanied homeless male adults (≥18 years of age). Study participants were recruited simultaneously over a six-month period (January–June 2008) by random selection prior to admission to a private, low-demand nonprofit emergency shelter located in Texas. Six percent of the shelter’s guests are veterans of military service (11). Low-demand shelters have no length-of-stay restrictions, provide shelter services at no cost, and do not require government-issued identification or a breathalyzer test prior to entry. No consideration was given during the sampling process to the number of previous nights they had stayed in the shelter. Veterans reporting a dishonorable discharge were not eligible to participate, given that typically they are not eligible for the VA services examined by this study. All participants were given a $5 gift card in appreciation of their participation. Institutional review board approvals were obtained from the University of Texas at Arlington and the Dallas VA Medical Center in advance of the study.

Instruments

After providing informed consent, participants completed a structured interview that obtained information about demographic characteristics; history of homelessness, employment, and military service; and specific substance use in the past 30 days. The interview was developed by using items from a study of chronic homelessness (12) and the homeless supplement to the Diagnostic Interview Schedule (13). The Short Michigan Alcohol Screening Test (SMAST) and the Drug Abuse Screening Test (DAST-10) were used to obtain information about alcohol and drug problems in the past 12 months. The SMAST and the DAST have demonstrated good discriminant and known-groups validity and are reliable (Cronbach’s α=.86 and .93, respectively) (1416). Possible scores range from 0 to 10 for the DAST-10 and 0 to 13 for the SMAST, and scores of ≥1 for the DAST-10 and ≥3 for the SMAST indicate a positive screen.
Mental and physical functioning in the past four weeks were measured by the Veterans Rand 12-Item Health Survey (VR-12) (17). Possible scores on the mental and physical functioning scales range from 0 to 100, with higher scores indicating better health (18). Participants were also asked about their use of services in the general medical, psychiatric, and substance abuse sectors in the previous 12 months. Use of services was assessed by subcomponent (inpatient, outpatient, and emergency subcomponents of the medical and psychiatric sectors and inpatient and outpatient subcomponents of the substance abuse sector). Veterans were asked to provide information separately about use of VA services and non-VA services.

Data analysis

Dichotomous variables for alcohol and drug problems were defined as SMAST scores of ≥3 and DAST scores of ≥1, respectively, in accordance with the scoring convention for each measure (15). Variables representing summary scores for the VR-12 components for physical and mental health were used as indicators of general medical and mental functioning.
Statistical analysis was completed by using IBM SPSS statistics, version 19. Descriptive data were summarized with raw numbers, percentages, and means and standard deviations. Categorical variables were compared by using chi square tests, and continuous variables were compared with Student’s t tests. Statistical significance level was set at α=.05.
Three multiple logistic regression models were constructed to predict use (dichotomized as yes or no) of general medical, psychiatric, and substance abuse services (one per model) on the basis of predisposing, need, and enabling factors from the Behavioral Model for Vulnerable Populations (6). In each of these regression models, service use (dependent variable) was predicted by entering two enabling factors (veteran status and insurance) as independent variables. Predisposing variables (age and education) and need variables (an alcohol problem, 30-day cocaine use, and mental and physical functioning) that were found in bivariate analyses to be associated with service use were entered into the model as independent covariates.
Service use variables were initially evaluated as covariates for prediction of other services—for example, use of medical services as a predictor of use of psychiatric services—but ultimately they could not be included in the final models because their strong associations with other independent variables caused unacceptable levels of confounding. The models used 30-day cocaine use rather than results for the DAST-10 as an indicator of drug problems because use of cocaine constituted a majority of drug use and was highly associated with service use in bivariate analyses and because previous research has established that cocaine use has a substantial prevalence and salience in homeless populations (1921).
For each model, separate analyses were conducted by entering independent variables simultaneously and by a stepwise fashion in which the need-based, enabling, and predisposing variables were entered one at a time. The results produced by simultaneous versus stepwise methods of variable entry did not differ, so the results of the models that entered variables simultaneously are presented.

Results

Table 1 presents demographic and other characteristics of the two study subgroups. Nearly half (N=103, 47%) of the sample was Caucasian, 50% (N=110) were African American, and 3% (N=7) were members of other racial groups. Nine percent (N=19) reported Hispanic ethnicity. Few (N=15, 7%) were currently married. Total lifetime homelessness averaged almost four years. Most participants (N=157, 71%) had a history of adult felony conviction, and an overwhelming majority (N=209, 95%) had been incarcerated; many (N=38, 17%) had a recent arrest with criminal charges. Approximately three-quarters (N=158, 72%) of the sample reported working for pay, but the average income earned by the sample in the past 30 days was very low ($463.3±$392.6). Compared with nonveterans, the veterans were older and more educated, more likely to have ever married, and less likely to have private or public (non-VA) health care insurance. In addition, veterans were significantly older upon first experiencing homelessness.
Table 1 Characteristics of veterans and nonveterans residing in a low-demand emergency shelter
CharacteristicVeterans
(N=110)Nonveterans
(N=110)Test statistic 
N%N%df
Age (M±SD)49.3±9.2 42.1±11.5 t=–5.05**208
Racial-ethnic minority52476559  
Ever married82755247χ2=17.18**1
Currently married55109  
Education (M±SD years)12.3±2.0 11.0±2.2 t=4.93**218
High school diploma or GED95544337χ2=36.42**1
Has children81736862  
Health insurance in past yeara19173431χ2=5.59*1
History of homelessness      
 Age first homeless (M±SD)40.9±11.735.3±12.1t=3.46**218
 Length of current episode (M±SD months)15.0±25.416.9±20.7  
 Total lifetime (M±SD months)46.3±51.943.8±46.7  
Income and employment      
 Income in past 30 days (M±SD $)466±431 461±352 
 No income in past 30 days1413109
 Currently working75688376
Physical functioning (M±SD score)b43.8±9.1 46.0±8.4   
Mental functioning (M±SD score)b39.4±14.3 40.5±12.7   
Alcohol problem68627266  
Drug problem87799486  
Illicit drug use in past 30 days61566559  
 Cocaine42384440  
 Marijuana37334440  
Criminal history      
 Adult felony conviction78717972
 History of incarceration1049510595
 Arrested and charged in past 90 days16152220
Branch of military service      
 Army5449
 Marine Corps2523
 Navy1917
 Air Force1110
 Coast Guard11
Service era      
 Post-Vietnam (May 1975–April 1991)4945
 Vietnam (August 1964–April 1975)4743
 Persian Gulf (August 1991–present)1211
 Korea (June 1950–January 1955)22
Served in war zone3229    
Discharge type      
 Honorable7467
 General2523
 Medical1110
Non–service-connected pension2119    
Non–service-connected pension amount per month (M±SD $)871±275     
Service-connected disability benefits2018    
a
Public or private insurance, not including access to U.S. Department of Veterans Affairs services
b
Possible scores on the physical and mental functioning scales of the Veterans Rand 12-Item Health Survey range from 0 to 100, with higher scores indicating better health.
*p<.05, **p<.001
Compared with a national population norm, the sample’s mean±SD VR-12 scores were significantly better for physical functioning (44.9±8.8 versus 38.4±12.2; t=10.9, df=219, p<.001) but significantly worse for mental functioning (40.0±13.5 versus 51.1±11.4; t=–12.2, df=219, p<.001) (22). Approximately two-thirds (N=140, 64%) of the sample had an identified alcohol problem, and a vast majority of the sample (N=181, 82%) had an identified drug problem. More than half of the sample (N=127, 58%) reported having used illicit drugs in the past 30 days; among those reporting drug use, cocaine and marijuana were the most frequently used substances. No significant differences were found between veterans and nonveterans in physical or mental functioning scores, alcohol or drug problems, or use of specific substances.
Veteran participants had served most often in the Army and during the Vietnam and post-Vietnam service eras. Slightly fewer than one-third served in a war zone, and just over two-thirds had received an honorable discharge. Fewer than one-fifth received a non–service-connected pension or service-connected disability benefits. A clear majority of veterans (N=101, 92%) reported that they were able to access VA clinical services in the past year.
Service use data are provided in Table 2. Almost three-quarters (N=158, 72%) of the sample reported some use of general medical services, especially emergency and outpatient care, in the past 12 months. Just over one-third (N=86, 39%) reported use of psychiatric services, usually outpatient services (86% of those using any psychiatric services). One-quarter (N=57, 26%) reported use of substance abuse services, especially inpatient services (71% of those using any substance abuse services).
Table 2 Use of services by veterans and nonveterans residing in a low-demand emergency shelter, by sector
 Veterans (N=110)      
 VA
servicesNon-VA
servicesAll
servicesNonveterans
(N=110)Non-VA
servicesAll services
SectorN%N%N%N%χ2apχ2ap
General medical7064575293846559  17.61<.001
 Emergency2422454161565550    
 Inpatient18162220383534313.45.044  
 Outpatient656023217669454110.30<.00117.65<.001
Psychiatric4541242261562529  23.47<.001
 Emergency10914132220877.57.005
 Inpatient12111413242212114.78.022
 Outpatient393617165247211919.70<.001
Substance abuse109252334312220    
 Inpatient87201827251312    
 Outpatient339812111312  5.90.011
a
df=1
Significantly more veterans than nonveterans used any medical or any psychiatric services, but there were no differences between the groups in the proportion that used any substance abuse services. Significantly more veterans than nonveterans used medical outpatient services; psychiatric emergency, inpatient, and outpatient services; and substance abuse inpatient services. No differences were found in the proportions of veterans and nonveterans who used non-VA medical, psychiatric, or substance abuse services. However, more nonveterans than veterans used two subcomponents of non-VA medical services (inpatient and outpatient services). Because veterans and nonveterans did not differ in the proportions using non-VA medical, psychiatric, or substance abuse services, the finding that more veterans than nonveterans used any medical, psychiatric, and substance abuse services was accounted for by the veterans’ additional use of VA services in these sectors.
Table 3 presents the results of multiple logistic regression models predicting use of services (dependent variable) in the general medical, psychiatric, and substance abuse sectors on the basis of need-based, predisposing, and enabling variables (independent covariates). Use of services in the medical sector was predicted by veteran status and having insurance and also by poor physical and mental functioning. Use of services in the psychiatric sector was predicted by younger age, veteran status, and poor physical and mental functioning. Use of services in the substance abuse sector was predicted by veteran status, lower mental functioning, an alcohol problem, and 30-day cocaine use.
Table 3 Predictors of use of services by veterans (N=110) and nonveterans (N=110) residing in a low-demand emergency sheltera
Service sector and predictorUnstandardized betaExp(B) OR95% CIpNagelkerke R2χ2p
General medical services    .26745.2<.001
 Veteran1.625.082.34–11.05<.001
 Age–.01.99.95–1.02.469
 Education–.06.95.80–1.12.508   
 Insurance1.344.001.54–10.19.004   
 Alcohol problem–.24.79.35–1.76.558   
 Cocaine use past 30 days–.10.90.41–1.97.795   
 Physical functioning–.08.93.88–.98.003   
 Mental functioning–.03.97.94–.99.020   
Psychiatric services    .31758.5<.001
 Veteran1.987.253.31–15.87<.001
 Age–.04.97.93–1.00.049
 Education–.14.87.74–1.02.088
 Insurance.401.48.68–3.21.324
 Alcohol problem–.10.91.42–1.97.806
 Cocaine use past 30 days.201.23.57–2.63.602
 Physical functioning–.05.95.91–.97.008
 Mental functioning–.62.94.92–.97<.001
Substance abuse services    .29148.1<.001
 Veteran.792.371.07–5.28.034
 Age–.01.99.96–1.04.904
 Education–.14.86.72–1.03.102
 Insurance–.38.66.27–1.62.367
 Alcohol problem.972.731.03–7.21.043
 Cocaine use past 30 days1.042.921.32–6.49.008
 Physical functioning.011.01.97–1.06.695
 Mental functioning–.05.94.92–.97<.001
a
The Nagelkerke R2 analysis indicates the proportion of the variance in use of services that was based on the predictive power of the independent variables, and the chi square analysis indicates statistical significance for the multiple regression models for each service (df=3).
The results of similar multiple logistic regression models for predicting the use of specific subcomponents of services in the medical, psychiatric, and substance abuse sectors were almost completely consistent with the results described above (data not shown). The only exception was that a lower level of education (p=.027) and having insurance (p=.016) also predicted use of psychiatric inpatient services.

Discussion

This sample of low-demand shelter users was similar in age and duration of lifetime homelessness to samples of shelter users studied elsewhere, although this sample had fewer participants who were members of racial-ethnic minority groups (10). The high rate of participants with an alcohol problem in the current study’s low-demand sample (64%) was identical to the rate for a sample of unsheltered homeless persons in New York City (23), but it was considerably higher than the rates for two sheltered samples of homeless persons in New York City (41% and 38%) (24,25).
A comparison of the veteran and nonveteran subgroups in this study found that veterans were older, first experienced homelessness later in life, were better educated, and were more likely to have ever been married. These results are consistent with differences between veterans and nonveterans, both in the general population and other homeless samples, that have been noted in other research (2628). Veterans were also found to be less likely than nonveterans to possess health insurance. Both groups reported extensive criminal histories, which can impede access to critical services (including housing) and other resources (29). A majority of both groups reported working for pay, but mean monthly incomes reported by either group were extremely low. The prevalence of a current alcohol problem and cocaine use and levels of physical or mental functioning were similar for veterans and nonveterans. A notable finding was that the sample’s mean physical functioning score was higher than that of the general population norm. This finding reflects the demands of living in a low-demand shelter, which require that individuals be ambulatory and be able to transport all of their belongings, tolerate the daytime conditions outside the shelter, and negotiate the admission process. Despite a comparable need for services, however, considerably more veterans than nonveterans accessed services in all three sectors.
The Behavioral Model for Vulnerable Populations proved to be a useful framework for this assessment of low-demand emergency shelter users and their use of services. Service sector use was predicted by indicators of need linked to each sector. For example, use of general medical services was linked to physical functioning, use of psychiatric services was linked to mental functioning, and use of substance abuse services was linked to an alcohol problem and recent cocaine use. These linkages point to the appropriate use of services by the study sample. Mental functioning, however, further predicted the use of medical and substance abuse services, and physical functioning predicted the use of psychiatric services, suggesting that service use is a complex phenomenon characterized by multiple viable pathways for obtaining services in various sectors. It was somewhat surprising that an alcohol problem and cocaine use did not predict the use of medical services, given the negative physical effects of problematic alcohol use and cocaine use and their prevalence in this sample.
In the multivariate model, the enabling variable of insurance predicted use of services in the medical sector. Only one-quarter of the sample reported possessing insurance, however, indicating that many individuals may not be able to afford needed medical services, limiting their use of much-needed services. The enabling factor of veteran status was also found to be predictive of use of all service sectors, which confirms that in the midst of comparable rates of non-VA service use by veterans and nonveterans, the ability to access the parallel service system provided by the VA was a significant source of the services used by the veteran subgroup.
This study had a number of methodological strengths. Users of low-demand emergency shelters, particularly veterans, have not been characterized in previous studies. Other methodological strengths included the random sampling of the study sample and the study’s construction around the Behavioral Model for Vulnerable Populations, which informed the inclusion of predisposing, enabling, and need variables relevant to the study.
This study was not without noteworthy limitations. The study sample did not represent the more general homeless population, and thus the comparisons between veterans and nonveterans and other findings do not necessarily generalize beyond the population of low-demand shelter users. The study also did not verify veteran status or the use of services or use objective diagnostic measures to assess general medical, mental, and substance abuse problems, which may have limited the accuracy of some of the data. Additional limitations were that the study did not gather information about the type of employment of study participants or the length of time between military discharge and first experience of homelessness.
Although the data collected by this study predate the more recently stated VA goal of ending homelessness, the findings have direct relevance for assessing current VA policy regarding homelessness among veterans, in particular the focus on housing veterans who are chronically homeless. With a mean lifetime duration of homelessness of almost four years and a current homeless episode duration of greater than a year, this sample of veterans from a low-demand shelter likely met the current VA definition of chronic homelessness. The finding that these veterans were relatively involved with VA health care services suggests that they were not completely alienated from the system and thus might be engaged in VA housing services, validating the VA’s current emphasis on community outreach.
Together, the fundamental similarities of the veteran and nonveteran homeless groups using low-demand shelter in this study and the finding that veterans were somewhat engaged in VA services (especially medical) suggest possibilities for improving services for homeless veterans. At the time that data were collected, local VA housing options required that individuals meet requirements regarding program participation or treatment compliance, for example, sobriety. An example of this service approach is the VA grant and per diem transitional housing program housed within the low-demand shelter facility, which required veterans to participate in substance abuse treatment or VA employment programs before being linked with permanent housing. At a conceptual level, it might be argued that homeless veterans in low-demand shelters have rejected or have been unable to comply with these programmatic demands, but their continued use of VA medical services indicates that they are still receptive to seeking care from the VA. Therefore, opportunities may still exist to engage this population, and the shelter may serve an important function by keeping this population linked to the assistance network—if only for shelter and food (30).
Although this study provided important information relative to policy and current practices, the limitations noted earlier point to some clear next steps for future research. The recent changes in VA policy on homelessness, including the adoption of the low-demand Housing First intervention, invite subsequent investigation of whether these policy shifts have affected veterans’ use of low-demand shelters. This information would be especially important considering the prevalence of cocaine use among the participants of this study, a practice that undermines housing stability, including in Housing First programs (31,32). Now that a new policy has been implemented, repeating the current study using identical methods would allow comparison of findings immediately before and after the shift in policy. One other promising direction for future research is to conduct longitudinal studies of low-demand shelter users. Examining housing trajectories as these individuals engage (or fail to engage) in housing services might provide important information about the predictors of their success in achieving permanent housing.

Conclusions

Given the prevalence of alcohol and drug problems and extensive criminal history among users of low-demand emergency shelters, these individuals may represent a distinct subpopulation of people who are homeless. The association between use of general medical, psychiatric, and substance abuse services by the study sample and the need for services was appropriate. However, overall use of substance abuse and psychiatric services seemed low. Despite some basic differences, the veteran and nonveteran subgroups were remarkably similar in terms of substance abuse, mental health, and general medical problems and factors that may contribute to or perpetuate homelessness (criminal histories and low income). Access to the VA service system, however, seemed to offer veterans an advantage that drove greater use of services.

Acknowledgments and disclosures

This study was funded through the U.S. Department of Veterans Affairs Pre-Doctoral Social Work Research Fellowship Program. The views expressed in this article are those of the authors and do not necessarily represent the official position of the United States government.
The authors report no competing interests.

References

1.
The 2012 Point-in-Time Estimates of Homelessness: Volume 1 of the 2012 Annual Homeless Assessment Report. Washington, DC, US Department of Housing and Urban Development, 2012. Available at www.onecpd.info/resources/documents/2012AHAR_PITestimates.pdf
2.
Prevalence and Risk of Homelessness Among US Veterans: A Multisite Investigation. Philadelphia, National Center on Homelessness Among Veterans, 2011. Available at repository.upenn.edu/cgi/viewcontent.cgi?article=1161&context=spp_papers
3.
Opening Doors: Federal Strategic Response to Prevent and End Homelessness. Washington, DC, United States Interagency Council on Homelessness, 2010
4.
O’Toole TP, Conde-Martel A, Gibbon JL, et al.: Health care of homeless veterans. Journal of General Internal Medicine 18:929–933, 2003
5.
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
6.
Gelberg L, Andersen RM, Leake BD: The Behavioral Model for Vulnerable Populations: application to medical care use and outcomes for homeless people. Health Services Research 34:1273–1302, 2000
7.
Padgett D, Struening EL, Andrews H: Factors affecting the use of medical, mental health, alcohol, and drug treatment services by homeless adults. Medical Care 28:805–821, 1990
8.
Wenzel SL, Bakhtiar L, Caskey NH, et al.: Homeless veterans’ utilization of medical, psychiatric, and substance abuse services. Medical Care 33:1132–1144, 1995
9.
Wenzel SL, Audrey Burnam M, Koegel P, et al.: Access to inpatient or residential substance abuse treatment among homeless adults with alcohol or other drug use disorders. Medical Care 39:1158–1169, 2001
10.
Pollio DE, North CS, Eyrich KM, et al.: Modeling service access in a homeless population. Journal of Psychoactive Drugs 35:487–495, 2003
11.
Point in Time Summary for TX-601–Fort Worth/Arlington/Tarrant County Continuum of Care. Fort Worth, Tex, Tarrant County Homeless Coalition, 2013. Available at www.ahomewithhope.org/wp-content/uploads/PITSummaryTX601.pdf
12.
Tsai J, Mares AS, Rosenheck RA: A multi-site comparison of supported housing for chronically homeless adults: “Housing First” versus “residential treatment first.” Psychological Services 7:219–232, 2010
13.
North CS, Eyrich KM, Pollio DE, et al.: The homeless supplement to the Diagnostic Interview Schedule: test-retest analyses. International Journal of Methods in Psychiatric Research 13:184–191, 2004
14.
Fleming MF, Barry KL: A study examining the psychometric properties of the SMAST-13. Journal of Substance Abuse 1:173–182, 1988–1989
15.
Corcoran K, Fischer J: Measures for Clinical Practice: A Sourcebook. New York, Oxford University Press, 2007
16.
Yudko E, Lozhkina O, Fouts A: A comprehensive review of the psychometric properties of the Drug Abuse Screening Test. Journal of Substance Abuse Treatment 32:189–198, 2007
17.
Iqbal SU, Rogers W, Selim A, et al: The Veterans RAND 12-Item Health Survey (VR-12): What It Is and How It Is Used. Bedford, Mass, Center for Health Quality, Outcomes, and Economic Research, 2009
18.
Dobscha SK, Dickinson KC, Lasarev MR, et al.: Associations between race and ethnicity and receipt of advice about alcohol use in the Department of Veterans Affairs. Psychiatric Services 60:663–670, 2009
19.
North CS, Eyrich KM, Pollio DE, et al.: Are rates of psychiatric disorders in the homeless population changing? American Journal of Public Health 94:103–108, 2004
20.
Kertesz SG, Mullins AN, Schumacher JE, et al.: Long-term housing and work outcomes among treated cocaine-dependent homeless persons. Journal of Behavioral Health Services and Research 34:17–33, 2007
21.
Kushel MB, Hahn JA, Evans JL, et al.: Revolving doors: imprisonment among the homeless and marginally housed population. American Journal of Public Health 95:1747–1752, 2005
22.
Selim AJ, Rogers W, Fleishman JA, et al.: Updated US population standard for the Veterans RAND 12-Item Health Survey (VR-12). Quality of Life Research 18:43–52, 2009
23.
Levitt AJ, Culhane DP, DeGenova J, et al.: Health and social characteristics of homeless adults in Manhattan who were chronically or not chronically unsheltered. Psychiatric Services 60:978–981, 2009
24.
Kuhn R, Culhane DP: Applying cluster analysis to test a typology of homelessness by pattern of shelter utilization: results from the analysis of administrative data. American Journal of Community Psychology 26:207–232, 1998
25.
Stefancic A, Tsemberis S: Housing First for long-term shelter dwellers with psychiatric disabilities in a suburban county: a four-year study of housing access and retention. American Journal of Public Health 28:265–279, 2007
26.
Profile of Veterans: 2011 Data From the American Community Survey. Washington, DC, National Center for Veterans Analysis and Statistics, 2013
27.
Prevalence and Risk of Homelessness Among US Veterans: A Multisite Investigation. Philadelphia, National Center on Homelessness Among Veterans, 2011. Available at repository.upenn.edu/cgi/viewcontent.cgi?article=1161&context=spp_papers
28.
Tessler R, Rosenheck R, Gamache G: Comparison of homeless veterans with other homeless men in a large clinical outreach program. Psychiatric Quarterly 73:109–119, 2002
29.
Criminalizing Crisis: The Criminalization of Homelessness in US Cities. Washington, DC, National Law Center on Homelessness and Poverty, 2011
30.
Pollio DE, Spitznagel EL, North CS, et al.: Service use over time and achievement of stable housing in a mentally ill homeless population. Psychiatric Services 51:1536–1543, 2000
31.
North CS, Eyrich-Garg KM, Pollio DE, et al.: A prospective study of substance use and housing stability in a homeless population. Social Psychiatry and Psychiatric Epidemiology 45:1055–1062, 2010
32.
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

Information & Authors

Information

Published In

Go to Psychiatric Services
Go to Psychiatric Services

Cover: Griselda, by Maxfield Parrish. © Copyright 2014 National Museum of American Illustration™, Newport, Rhode Island. Photos courtesy of Archives of the American Illustrators Gallery™, New York City.

Psychiatric Services
Pages: 751 - 757
PubMed: 24535542

History

Published in print: June 2014
Published online: 15 October 2014

Authors

Details

James C. Petrovich, Ph.D., L.M.S.W.
Dr. Petrovich is with the Department of Social Work, Texas Christian University, Fort Worth (e-mail: [email protected]). Dr. Pollio is with the Department of Social Work, University of Alabama, Tuscaloosa. Dr. North is with the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas.
David E. Pollio, Ph.D., M.S.W.
Dr. Petrovich is with the Department of Social Work, Texas Christian University, Fort Worth (e-mail: [email protected]). Dr. Pollio is with the Department of Social Work, University of Alabama, Tuscaloosa. Dr. North is with the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas.
Carol S. North, M.D., M.P.E.
Dr. Petrovich is with the Department of Social Work, Texas Christian University, Fort Worth (e-mail: [email protected]). Dr. Pollio is with the Department of Social Work, University of Alabama, Tuscaloosa. Dr. North is with the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas.

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard

View Options

View options

PDF/EPUB

View PDF/EPUB

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login
Purchase Options

Purchase this article to access the full text.

PPV Articles - Psychiatric Services

PPV Articles - Psychiatric Services

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share