Role of Gender, Substance Use, and Serious Mental Illness in Anticipated Postjail Homelessness

Role of Gender, Substance Use, and Serious Mental Illness in Anticipated Postjail

Homelessness Lauren Fries, Gina Fedock, and Sheryl Pimlott Kubiak

Incarcerated individuals, particularly women, experience high rates of mental health and sub- stance use disorders, potentially placing them at an increased risk for homelessness. This study examined factors associated with anticipated postjail homelessness among men and women (N = 725) incarcerated in an urban county jail. Participants were categorized into three groups on the basis of scores of screening measures for substance misuse and mental illness: (1) substance use disorder only, (2) serious mental illness or co-occurring substance use dis- order (SMI/COD), and (3) no disorder. Gender differences within the three groups were examined, and logistic regressions were used to assess factors associated with anticipated post- jail homelessness. Women were more likely than men to be homeless prejail and present with a serious mental illness, a substance use disorder, or both. SMI/COD and gender, but not substance use disorder only, were significantly associated with anticipated postjail homeless- ness. Women were twice as likely as men to anticipate postjail homelessness. Results display the complexity of service needs among women in the criminal justice system and support the need for services that address mental illness and substance use within the jail setting to reduce long-term homelessness.

KEY WORDS: homelessness; jail; mental illness; substance use; women

Homelessness is commonly associated withjail incarceration. Almost half (49%) ofhomeless adults have experienced at least one stay in jail (Burt et al., 1999), and home- lessness for those incarcerated in jails is 7.5 times higher than for the general population (Greenberg & Rosenheck, 2008). Jails are heavily populated and experience rapid turnover. For example, jails across the country admit 250,000 individuals per week and have a weekly turnover rate ranging from 52% to 137% depending on the jail size (Min- ton, 2011).Even though jail sentences are brief, jail is a disruption to an individual’s life. Rapid turn- over and a dearth of services within jail often lead to housing instability at a greater rate for those dis- charged from jail (Metraux & Culhane, 2006). However, pre- and postrelease services for housing, social services, and case management are generally lacking within jails (Steadman & Veysey, 1997). Refinement of service needs is crucial to better treat those incarcerated in jail to prevent recidivism and further negative outcomes, such as postincar- ceration homelessness. Exploring the role of gen- der is one step in clarifying these needs, as gender

differences exist for both pathways to incarceration and homelessness.

RISK FACTORS FOR JAIL INCARCERATION AND HOMELESSNESS Individuals in jail have high rates of several risk fac- tors, such as serious mental illness, substance use dis- orders, and dual disorders, that are often associated with homelessness (Greenberg & Rosenheck, 2008; James & Glaze, 2006; McNeil, Binder, & Robinson, 2005; Theriot & Segal, 2005). In partic- ular, more than half (64%) of jail inmates have a mental health problem, and 76% of these inmates also have a substance use disorder ( James & Glaze, 2006). Furthermore, those with a mental illness are almost twice as likely as those without a mental ill- ness (17% versus 9%) to have experiences of home- lessness ( James & Glaze, 2006). Serious mental illness, especially untreated mental health disorders, substance abuse and dependency, and dual dis- orders are also risk factors for homelessness in com- munity samples (Folsom et al., 2005; Greenberg & Rosenheck, 2010; Levin, Culhane, DeGenova, O’Quinn, & Bainbridge, 2009). In addition,

doi: 10.1093/swr/svu014 © 2014 National Association of Social Workers 107

economic disadvantage and persistent unemploy- ment, lack of support from family and friends, low educational achievement, incarceration, and histories of childhood adversity have been identi- fied as risk factors for homelessness among adults (Caton et al., 2005; Kertesz et al., 2005; McNeil et al., 2005;Reardon, Burns, Preist, Sachs-Ericsson, & Lang, 2003; Shelton, Taylor, Bonner, & van den Bree, 2009).

Gender, Risk, and Jail Incarceration Gender is an important factor to examine in relation to jail incarceration because women are considered to have different pathways into the criminal justice system and thus different key service needs than male offenders (Belknap, 2007; Belknap & Holsinger, 2006; Chesney-Lind, 1997; Chesney- Lind & Shelden, 2004). For example, in Daly’s (1994) often cited work on pathways to crime, men and women differed in their most common pathways —specifically, the pathway category with the high- est proportion of men (35%) was related to using violence for control and the prominent role of mas- culinity in promoting criminal behaviors, whereas the pathway with the largest proportion of women (37%) was based on a history of extensive abuse, victimization, substance abuse, mental health dis- tress, and subsequent criminal behaviors. While acknowledging that some men and women may have similar contexts for their involvement in crim- inal behavior (for example, Reisig, Holtfreter, & Morash, 2006), more recent research on gender comparisons offers empirical support of differences in these pathways. For example, although home- lessness is generally considered a “gender-neutral” risk factor for incarceration, homelessness in con- nection with extreme poverty has been identified as placing women on a distinct trajectory to incarcer- ation (Holtfreter, Reisig, & Morash, 2004),especially when considering the impact of marginalization through race, socioeconomic status (SES), and gen- der (Richie, 1996). Also, a recent multisite study of women in rural and urban jails found that serious mental illness, as well as victimization histories, in- creased the risk for women’s involvement in criminal behavior (Lynch, DeHart, Belknap, & Green, 2012).

Moreover, in jail, women present with higher rates of risk factors for incarceration than men. Women have more than double the rate of serious mental illness than men in jail (31% versus 15%); Kubiak, Beeble, & Bybee, 2012; Steadman, Osher,

Robbins, Case, & Samuels, 2009) and, in general, have high rates of mental illness, substance abuse disorders, and dual disorders (Abram, Teplin, & McClelland, 2003; Green, Miranda, Daroowalla, & Siddique, 2005; Teplin, Abram, & McClelland, 1996). Also, more women in jail present with mul- tiple morbidities compared with men; for example, 31% of women reported two risk factors versus 16% of men, and 20% of women reported three risk fac- tors versus 6% of men (Fedock, Fries, & Pimlott Kubiak, 2013).

Gender, Risk, Homelessness, and Jail Incarceration Although a myriad of studies have examined risk factors associated with homelessness for adults, most studies have used low proportions of women in their samples, leading to a dearth of knowledge on gender differences in these factors. One study, which used a small sample of low-income adults to explore correlates of homelessness for men and women, found that alcohol and drug use and low monthly income were associated with men’s home- lessness, whereas only engagement in sex trade and recent incarceration were significantly associated with women’s homelessness (Riley et al., 2007). A study comparing men’s and women’s pathways to being homeless found that men were more likely to name loss of job, mental health problems, and substance abuse problems as contributing to their homelessness, whereas women were more likely to name eviction, interpersonal conflict, and loss of social support. Economic strain was reported at similar rates for both men and women (Tessler, Rosenheck, & Gamache, 2001).

In comparing homeless and housed women, homeless women have a higher rate of experiencing intimate partner violence (IPV), as well as a signifi- cantly higher rate of cumulative lifetime victimiza- tion (Browne & Bassuk, 1997). Homeless women have also reported high rates of recent victimization. One study found that one-third of homeless women had been physically assaulted in the previ- ous year (Kushel, Evans, Perry, Robertson, & Moss, 2003); another study reported that one-fourth of homeless women had experienced victimization in the preceding 30 days (Wenzel, Koegel, & Gelberg, 2000). Furthermore, IPV is the most commonly given reason for homelessness among homeless women with children (Tischler, Rademeyer, & Vostanis, 2007).

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The relatively few studies that have examined gender in relation to homelessness among the incarcerated population have found that jail is a more potent risk factor for homelessness for women than for men (Freudenberg, Mosely, Lebriola, Daniels, & Murrill, 2007; Riley et al., 2007) and that homelessness is a common concern for women released from jail (Richie, 2001; Van Olphen, Eliason, Freudenberg, & Barnes, 2009). Research- ers have suggested that women face particularly heavy negative stigma after incarceration (Richie, Freudenberg, & Page, 2001) and often lack access to sufficient treatment needs, especially for mental health and substance use disorders after release, which inhibits successful reentry into the commu- nity (Weiss, Kung, & Pearson, 2003). These untreated service needs, in combination with expe- riences of incarceration and homelessness, may place women at risk for further victimization (Lam & Rosenheck, 1998).

CURRENT STUDY The existing literature shows a cyclical and inter- connected relationship between homelessness and incarceration and suggests that this relationship is mediated by factors of mental health and substance use disorders for adults, as well as other potential factors, such as trauma, particularly for women. A specific aspect of this relationship in need of further examination is the identification of risk factors for homelessness postjail release among incarcerated men and women (Greenberg & Rosenheck, 2008). Existing studies have failed to examine the role of gender in relation to postincarceration homelessness while simultaneously considering the effects of se- rious mental illness and substance use disorders. Therefore, this study focuses on the role of gender among risk factors of anticipated homelessness post- incarceration to inform jail discharge planning for service providers, especially social workers who are often involved in this process (Goldstrom, Hender- son, Male, & Manderscheid, 1998). Our research questions are as follows: Do rates of homelessness pre- jail incarceration differ by gender? Does anticipated homelessness postjail differ by gender when control- ling for substance use and mental health disorders?

METHOD The sample was obtained from a midwestern urban-county jail. The jail processes approximately 45,000 individuals each year and has an average

daily population of 2,600 detainees. Those detained may be awaiting trial or convicted and serving sen- tences. Similar to national statistics concerning the composition of county jail populations (87% male versus 13% female) (Harrison & Beck, 2006), approximately 89% of inmates housed in this facility are male.

Procedure Purposeful sampling strategies were used in this study to obtain representative samples of incarcerated men and women. Our data collection approaches for men and women varied slightly because of the nature of the facility and the limited number of women on a given day. Therefore, when collecting data from women, three rounds of data collection were completed over six months, with approxi- mately four weeks in between each round to allow for turnover. Male data collection was done in one continuous round lasting approximately three months. Self-report surveys were disseminated to all inmates booked during the data collection period in 2009 by trained research staff (see Kubiak, Beeble, & Bybee, 2010, for further procedural detail). The study was approved by Michigan State University’s institutional review board.

Participants A total of 1,092 participants were approached to participate in this study, and 83 (8%) declined par- ticipation. Of the 1,009 participants, 49% were men and 51% were women. Because of changes in the measure, approximately half (n = 284) of the women were not surveyed on all measures and were removed for purposes of this analysis. A com- parison of characteristics between the women used in the analysis sample (n = 231) and the omitted sample (n = 284) revealed no differences in age, t(512) = 0.27, p = .79; length of incarceration, t(513) = 0.02, p = .98; or proportion with a serious mental illness, χ2(1, N = 512) = 2.02, p = .09. Our final sample consisted of 725 participants, 68% of whom were men (n = 494) and 32% of whom were women (n = 231). Participants ranged in age from 18 to 64 years, and length of incarceration ranged from one day to slightly under three years. Other demographic information, such as race– ethnicity, income, or marital status, was not captured from participants. Although race was not collected on individual participants, the overall 2007 census indicated that 59% of adults incarcerated in this

Fries et al. / Role of Gender, Substance Use, and Serious Mental Illness in Anticipated Postjail Homelessness 109

facility were African American (personal commu- nication with R. Pitts, data analyst for Wayne County Jail, Detroit, 2008).

Measures Serious Mental Illness (SMI). The K6 (Kessler et al., 2002, 2003), a brief six-item screening mea- sure often used in general population studies, was used to assess symptoms of psychological distress. The K6 measures the extent to which individuals feel (1) nervous, (2) hopeless, (3) restless or fidgety, (4) so depressed that nothing can cheer them up, (5) that everything was an effort, and (6) worthless dur- ing the four weeks preceding their screening. Item responses were based on a five-point Likert-type scale, ranging from 0 (none of the time) to 4 (all of the time). All responses were summed into an overall scale, with scores ranging from 0 to 24. Cronbach’s alpha of the K6 for the current sample was .95 (M = 7.99; SD = 7.84). A recommended overall cutoff score of 13 (Kessler et al., 2003) distin- guishes those with SMI from those without. The K6 identified 164 participants (23%), 15% of men and 40% of women, as having an SMI.

Homelessness. Homelessness prior to incarcera- tion was assessed using a single-item question. Par- ticipants were asked, “Where did you live during the four weeks before you came to jail?” Response categories included “house/apartment that I own or rent,” “with a family member or friend,” “moved around or stayed with more than one fam- ily member/friend,” and “homeless shelter, treat- ment facility, housing program.” A dichotomous variable was created to identify participants who were homeless prior to incarceration on the basis of the federal definition of homelessness (U.S. Department of Housing and Urban Development, 2011).The definition considered in federal policy is that homeless individuals are those living in a place not meant for human habitation, such as a tempo- rary institution or shelter; those who will be losing their place of nighttime residence, including a motel, within two weeks; or those continuing to have unstable housing because of reasons such as mental health disorder or lack of employment (H. R. 2523, 2009) Only participants who selected “moved around or stayed with more than one fam- ily member/friend” or “homeless shelter, treatment facility, housing program” were identified as hous- ing insecure and thus constituted our homeless prior to jail incarceration group for purposes of

this analysis. Among our sample, 68 participants (11%), 9% of men and 16% of women, identified as being homeless prejail. Similar procedures were used to identify participants who anticipated home- lessness postjail incarceration. Although anticipated homelessness does not ensure homelessness postjail, previous research compared women’s expected and actual needs postjail and found that inmates were able to accurately predict their needs, including housing stability (Freudenberg, Daniels, Crum, Perkins, & Richie, 2005). Participants were asked, “Where will you most likely live when you leave jail?” The identical response categories were also merged into a dichotomous variable to determine the proportion of participants with anticipated postjail homelessness. Among our sample, 67 participants (11%), 6% of men and 20% of women, met this cri- terion. Fifty-one participants selected homeless shelter, treatment facility, housing program, and 16 participants selected moved around or stayed with more than one family member/friend.

Substance Use Disorder (SUD). The CAGE Alcohol and Drug Screening Questionnaires (Ewing, 1984) were used to screen for current sub- stance use disorders. CAGE is used in primary care settings and has been found valid and reliable in screening for alcohol use disorders across a variety of populations (Dhalla & Kopec, 2007). Alcohol disorders were assessed using the four-item scale, which was preceded by one item to screen for prior alcohol use, “Have you ever used alcohol?” Alco- hol consumption guided participants to complete the remaining items (for example, “Have you ever felt you should cut down on your drinking?” “Have you ever felt bad or guilty about your drink- ing?”). A similar four-item scale was used to assess drug disorders. Participants who answered “yes” on “Have you ever used legal or illegal drugs inap- propriately?” were asked to complete four addi- tional questions. Item responses were scored 0 or 1 and summed to create a scale score ranging from 0 to 4. A total score of 2 or higher was used as the lower limit to indicate the probable presence of a substance use problem. The CAGE alcohol scale (α = .78) and CAGE drug scale (α = .78) dem- onstrated high reliability with the current sample. Participants who screened positive on the CAGE alcohol or CAGE drug screen were considered to have an SUD for purposes of analysis. A total of 390 participants (56%), 49% of men and 71% of women, met criteria for an SUD.

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Data Analysis Incarcerated men and women were compared on demographic and clinical characteristics using t tests and chi-square tests. Participants were categorized into three disorder groups, (1) SUD only, (2) SMI only or SMI with co-occurring SUD (SMI/COD), and (3) no disorder, on the basis of the scores of the clinical instruments that measured substance use and symptoms associated with mental illness. Gender differences among the three groups were examined using chi-square tests. Stepwise logistic regression was used to examine the role of gender, SUD, and SMI/COD on anticipated postjail homeless- ness. The first model examined the relationship of gender, SUD, and SMI/COD on anticipated post- jail homelessness while accounting for prejail homelessness, age, and length of incarceration. The first model was conducted in the following three steps: (1) age, incarceration length, prejail homelessness; (2) membership in the SMI/COD- or SUD-only groups; and (3) gender. In the second model, the interaction of gender with prejail home- lessness, SUD, and SMI/COD was tested. The sec- ond model was conducted in the following four steps: (1) age, incarceration length, prejail home- lessness; (2) membership in the SMI/COD- or SUD-only group; (3) gender; and (4) gender × prejail homelessness, gender × SMI/COD, and gender × SUD. Because none of the interactions with gender were significant, we present results only of the main effects model.

RESULTS The women in our sample were slightly older than the men and had also served a significantly greater number of days within jail at the time of our survey than the men. A significantly greater proportion of women identified as being homeless prior to jail and anticipated higher rates of homelessness postjail when compared with men (see Table 1). Women were also significantly more likely to present with an SMI and SUD than men. The frequencies asso- ciated with membership group (SUD, 39%; SMI with SUD, 18%; SMI without SUD, 6%; and no disorder, 38%), by gender, are illustrated in Table 2. The SUD-only group had the highest membership, with equivalent proportions of the male and female population. Initially, we considered separate groups for SMI only and those with COD; however, because of the small numbers of those with SMI only (n = 40), we collapsed these groups into one

category—SMI/COD. Gender was significantly associated with membership in the SMI category and the SMI/COD category. Men were more likely to belong to the no disorder group (see Table 2).

The correlation matrix for the study variables are presented in Table 3. Prejail homelessness was posi- tively and weakly correlated with length of incarceration, gender, SMI/COD, and SUD. Anti- cipated postjail homelessness was also positively and weakly correlated with gender, SMI/COD, and SUD. Prejail and anticipated postjail homelessness were positively and moderately correlated (r = .39). SMI/COD and SUD were positively and weakly correlated (r = .21). No study variables were highly correlated.

Prejail homelessness was significantly associated with anticipated postjail homelessness (OR = 10.71, 95% CI [5.18, 22.11]). After controlling for demo- graphic variables and prejail homelessness (step 1), the addition of SMI/COD and SUD explained 29% of the variance with SMI/COD as the only sig- nificant factor (OR = 3.85, 95% CI [1.96, 7.55]) (see Table 4). In the full model, SMI/COD remained sig- nificant (OR = 3.30, 95% CI [1.66, 6.57]). Gender was also significantly associated with anticipated post- jail homelessness even while controlling for prejail homelessness, SMI/COD, and SUD (OR = 2.17, 95% CI [1.08, 4.34]). Variance explained increased in the full model (30%). Of the interactionstested in our second model (gender × prejail homelessness, gender × SUD, gender × SMI/COD), no significant interaction effects were found.

DISCUSSION In this study, data from a purposeful sample of incarcerated men and women from a midwestern, urban jail were used to examine rates and risk factors associated with anticipated postjail homelessness. Our first aim was to examine gender differences in rates of prejail homelessness and anticipated post- jail homelessness as well as other risk factors associ- ated with homelessness, mainly SMI and SUD. We also sought to determine whether gender was asso- ciated with anticipated postjail homelessness above and beyond SUD and SMI and COD. Our final aim was to examine gender differences in risk factors for anticipated postjail homelessness. Notably, our research is one of the few studies to use a sample of incarcerated individuals when examining home- lessness among jail populations, as the majority of

Fries et al. / Role of Gender, Substance Use, and Serious Mental Illness in Anticipated Postjail Homelessness 111

studies have examined past criminal justice in- volvement in samples of homeless individuals (Greenberg & Rosenheck, 2008).

Our results showcased the complexity of service needs and severity of morbidities among women involved in the criminal justice system. Women in our sample presented with higher rates of prejail homelessness, anticipated postjail homelessness, SMI, SUD, and COD than men. Women were also half as likely as the men to fall into the “no dis- order” category. Other studies have documented high rates of mental illness and substance use among incarcerated women (that is, Abram et al., 2003); however, our findings that women in jail were more likely to experience homelessness prejail and to anticipate homelessness postjail than their male counterparts are novel.

Although gender was not the strongest risk factor for postjail homelessness in our final model, gender played a unique and significant role in anticipated postjail homelessness beyond SMI and COD and SUD. Women in our sample were two times more likely than men to anticipate homelessness upon release. Despite this disproportion, none of the interactions tested between the risk factors and gen- der (prejail homelessness × gender; SUD × gender; SMI/COD × gender) emerged significant. This indicates that men and women do not differ in these risk factors associated with anticipated postjail homelessness. It may be that what is uniquely con- nected to women’s experiences of homelessness was not assessed. One possibility is victimization history (for example, domestic violence, sexual– physical assault), which when combined with

Table 1: Within-Group Comparisons on Selected Variables Based on Gender

Variable

Total Sample (N = 725) Men (n = 494)

Women (n = 231)

Gender Comparison M SD M SD M SD Statistical Test

Age 32.59 10.87 31.76 11.09 34.24 10.23 t(681) = –2.83** Incarceration length 26.99 76.80 17.88 67.31 44.50 89.92 t(664) = –4.30**

n % n % n % Statistical Test Prejail homelessness χ2 (1, N = 622) = 6.49* Yes 68 10.93 37 8.75 31 15.58

No 554 89.07 386 91.25 168 84.42

Anticipated postjail homelessness χ2(1, N = 625) = 26.34** Yes 67 10.72 26 6.24 41 19.71

No 558 89.28 391 93.76 167 80.29

Serious mental illness χ²(1, N = 708) = 55.03** Yes 164 23.16 72 15.03 92 40.17

No 544 76.84 407 84.97 137 59.83

Substance use disorder χ²(1, N = 695) = 30.03** Yes 390 56.12 232 49.05 158 71.17

No 305 43.88 241 50.95 64 28.83 *p = .05. **p < .001.

Table 2: Gender Differences in the Frequency of Group Membership

Variable

Total Sample (N = 681)

Men (n = 461)

Women (n = 220)

Gender Comparison n % n % n % χ²

Substance use disorder 263 38.60 178 38.60 85 38.60 χ²(1) = 0.000 Serious mental illness 160 23.50 70 15.20 90 40.90 χ²(1) = 54.83*** With substance use 120 17.62 48 10.41 72 32.73 χ²(1) = 51.09*** Without substance use 40 5.87 22 4.77 18 8.18 χ²(1) = 3.13

No disorder 258 37.90 213 46.20 45 20.50 χ²(1) = 41.96*** Note: Serious mental illness is defined as meeting criteria for serious mental illness with or without substance use disorder, and “no disorder” refers to not meeting criteria for substance use disorder or serious mental illness. Counts and percentages are within group for men and women. ***p < .000.

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mental illness has been found to be a precursor for both homelessness (Kushel et al., 2003) and incar- ceration (Daly, 1994) for women. Other studies have suggested that shifts in interpersonal support contribute to women’s experiences of homeless- ness (Tessler et al., 2001). Future studies should continue to investigate which risk factors for postjail homelessness differ for men and women and should consider the role of trauma and shifts in social sup- port for women. Identifying these gender differ- ences more precisely may be essential in tailoring jail-based services and interventions.

The tailoring of services to address CODs and SMI within the jail may have the ability to promote successful reentry and possibly prevent high rates of homelessness among the incarcerated population. In our study, experiencing an SMI or a COD was significantly associated with anticipated postjail homelessness for both men and women. Those who presented with an SMI or a COD were three times more likely to anticipate postjail homeless- ness than inmates with no disorder. Because the majority of those experiencing SMI within our sample also met criteria for an SUD (approximately 75%), it is likely that the unique combination of the two occurring together places inmates at a greater risk. Services within jails are lacking because of rapid turnover and brief stays (Minton, 2011). As such, local providers, including community mental health centers, could be instrumental in collaborating with jails to provide in-reach or translational services geared toward COD. Interventions such as inte- grated dual diagnosis treatment (Mueser, Noordsy, Drake, & Fox, 2003)and Critical Time Intervention

(Draine & Herman, 2007) could be integrated in the jail setting for inmates with CODs to provide the practical and emotional support needed for commu- nity reentry.

Although interventions should be available for all incarcerated individuals with COD as one mecha- nism to reduce homelessness, they may be particu- larly important for women who presented with higher rates of COD and were more likely to antic- ipate homelessness upon release. Although women represent a small proportion of the jail population, they may require additional or more complex ser- vices for reintegration because of their risk for long- term homelessness (Riley et al., 2007), likely role as sole caregiver (Mumola, 2000), higher need for mental health and substance use treatment, and safety issues associated with higher rates of physical and sexual assault (Fedock et al., 2013). Victimiza- tion history, such as past experiences of domestic violence and physical or sexual assault, may be one crucial factor underlying the high rates of COD for women in our sample. As such, future treatments developed with gender-sensitive issues in mind (for example, Beyond Trauma [Covington, 2003], Seeking Safety [Najavits, 2001], and trauma recovery and empowerment model [Harris & Anglin, 1998]) could be instrumental in reducing the disproportionate rates of homelessness among women and ultimately prevent recidivism.

Social workers can play a key role in assessing needs upon jail entrance and in connecting for- merly incarcerated individuals with community services on discharge. Mental health screening in jails by qualified providers as part of the admission process, as well as immediate referral to treatment, is a recommended best practice (International Associ- ation for Correctional and Forensic Psychology, 2010). Screening for CODs upon jail intake is per- haps the first and most crucial step social workers can take to reduce homelessness among the incar- cerated population. Moreover, because jail stays are brief in nature, there is a small window to identify individuals with needs to subsequently link them to comprehensive treatments and community services upon reintegration.

Limitations Our findings should be viewed in the context of the following limitations. Our analyses are based on a cross-sectional design, precluding casual associa- tions between variables. In addition, purposeful

Table 3: Correlation of Study Variables

Variable 1 2 3 4 5 6 7

1. Age —

2. Incarceration length .10** —

3. Gender .12** .17** —

4. Prejail homelessness .01 .19** .10* —

5. Anticipated postjail homelessness .08 .11** .21** .39** —

6. Serious mental illness and co-occurring disorder .02 .01 .28** .09* .22** —

7. Substance use disorder .26** .02 .21** .14** .14** .21** —

*p < .05. **p < .01.

Fries et al. / Role of Gender, Substance Use, and Serious Mental Illness in Anticipated Postjail Homelessness 113

sampling was used to compensate for the low prev- alence of women within the jail setting, potentially limiting generalizability and creating artificial differ- ences between men in women in length of stay. Our measure of postjail homelessness is limited in that it is a self-reported prediction that may not equate to actual postjail homelessness. In addition, our findings that men and women did not differ in regard to risk factors associated with anticipated postjail homelessness may have been influenced by our sample size and the relatively small number of inmates who anticipated being homeless upon release (n = 67). Future research should use larger samples to better understand the role of gender on homelessness postincarceration.

Another major limitation of our study was the failure to measure important demographic infor- mation, including race–ethnicity, socioeconomic status, and previous criminal history. Given that race–ethnicity, gender, and SES are factors con- nected to the marginalization and oppression of incarcerated adults through the racialization and feminization of the criminal justice system, their inclusion could provide unique insight into the relationship among incarceration, homelessness, gender, and risk. In addition, variables used in our study to assess abuse history may have been inade- quate as they measured experiences that occurred only over the past 12 months, when it is likely that an extensive history of victimization and abuse accounts for homelessness. Future research using rigorous methods with attention to race– ethnicity and extensive abuse history in the context of gender, incarceration, homelessness, and risk is needed.

Conclusion Our research demonstrates that gender is a unique risk factor associated with substance use, SMI and COD, as well as anticipated postjail homelessness. Understanding risk factors associated with antici- pated postjail homelessness is crucial for enhancing social work services delivery within the jail setting. Jails represent a unique setting to adequately screen and assess for mental health diagnoses, SUDs, and homelessness and to work with local providers to offer short-term mental health services and link inmates with community resources by providing reentry services. Social workers can play a pivotal role in promoting successful community reintegra- tion, ultimately preventing the cyclical nature ofT

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[0 .9 9 , 1 .0 0 ]

0 .0 0 (0 .0 0 )

0 .0 2

1 .0 0

[1 .0 0 , 1 .0 1 ]

P re ja il h om

el es sn es s

2 .5 1 (0 .3 5 )

5 2 .7 3 ** *

1 2 .2 4

[6 .2 3 , 2 4 .0 6 ]

2 .3 6 (0 .3 7 )

4 1 .2 8 ** *

1 0 .5 7

[5 .1 5 , 2 1 .7 0 ]

2 .3 7 (0 .3 7 )

4 1 .0 5* **

1 0 .7 1

[5 .1 8 , 2 2 .1 1 ]

SM I/ C O D

1 .3 5 (0 .3 4 )

1 5 .3 1 ** *

3 .8 5

[1 .9 6 , 7 .5 5 ]

1 .2 0 (0 .3 5 )

1 1 .5 9* *

3 .3 0

[1 .6 6 , 6 .5 7 ]

SU D

0 .7 4 (0 .4 2 )

3 .1 0

2 .0 9

[0 .9 2 , 4 .7 4 ]

0 .6 5 (0 .4 2 )

2 .3 4

1 .9 1

[0 .8 3 , 4 .3 7 ]

G en d er

0 .7 7 (0 .3 5 )

4 .7 9 *

2 .1 7

[1 .0 8 , 4 .3 4 ]

R 2

0 .2 1

0 .2 9

0 .3 0

N o te : St a n d a rd

e rr o rs

a re

in p a re n th e se s. C I=

co n fi d e n ce

in te rv a l; SM

I= se ri o u s m e n ta l il ln e ss ; C O D = co

-o cc u rr in g d is o rd e r; SU

D = su b st a n ce

u se

d is o rd e r.

* p < .0 5 . * * p < .0 1 . * * * p < .0 0 0 .

114 Social Work Research Volume 38, Number 2 June 2014

homelessness and incarceration. Although this research represents an important step in our under- standing of the many needs of incarcerated individ- uals, a great deal of work remains to be done. Future research should investigate service delivery models that can be adapted for the jail setting.

REFERENCES Abram, K. M., Teplin, L. A., & McClelland, G. M. (2003).

Comorbidity of severe psychiatric disorders and sub- stance use disorders among women in jail. American Journal of Psychiatry, 160, 1007–1010.

Belknap, J. (2007). The invisible woman: Gender, crime, and justice (3rd ed.). Belmont, CA: Thompson Wadsworth.

Belknap, J., & Holsinger, K. (2006). The gendered nature of risk factors for delinquency. Feminist Criminology, 1, 48–71.

Browne, A., & Bassuk, S. S. (1997). Intimate violence in the lives of homeless and poor housed women: Prevalence and patterns in an ethnically diverse sample. American Journal of Orthopsychiatry, 67, 261–278.

Burt, M. A., Aron, L. Y., Douglas, T., Valente, J., Lee, E., & Iwen, B. (1999). Homelessness: Programs and the people they serve. Washington, DC: Urban Institute.

Caton, C. M., Dominguez, B., Schanzer, B., Hasin, D. S., Shrout, P. E., Felix, A., et al. (2005). Risk factors for long-term homelessness: Findings from a longitudinal study of first-time homeless single adults. American Journal of Public Health, 95, 1753–1759.

Chesney-Lind, M. (1997). The female offender: Girls, women, and crime. Thousand Oaks, CA: Sage Publications.

Chesney-Lind, M., & Shelden, R. G. (2004). Girls, delin- quency, and juvenile justice (3rd ed.). Belmont, CA: Thompson Wadsworth.

Covington, S. (2003). Beyond trauma: A healing journey for women. Center City, MN: Hazelden.

Daly, K. (1994). Gender, crime, and punishment. New Haven, CT: Yale University Press.

Dhalla, S., & Kopec, J. A. (2007). The CAGE questionnaire for alcohol misuse: A review of reliability and validity studies. Clinical and Investigative Medicine, 30, 33–41.

Draine, J., & Herman, D. B. (2007). Critical time inter- vention for reentry from prison for persons with mental illness. Psychiatric Services, 58, 1577–1581.

Ewing, J. A. (1984). Detecting alcoholism: The CAGE questionnaire. JAMA, 252, 1905–1907.

Fedock, G., Fries, L., & Pimlott Kubiak, S. (2013). Service needs for incarcerated adults: Exploring gender differ- ences. Journal of Offender Rehabilitation, 52, 493–508.

Folsom, D. P., Hawthorne, W., Lindamer, L., Gilmer, T., Bailey, A., Golshan, S., et al. (2005). 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.

Freudenberg, N., Daniels, J., Crum, M., Perkins, T., & Richie, B. (2005). Coming home from jail: The social and health consequences of community reentry for women, male adolescents, and their families and communities. American Journal of Public Health, 95, 1725–1736.

Freudenberg, N., Mosely, J., Lebriola, M., Daniels, J., & Murrill, C. (2007). Comparison of health and social characteristics of people leaving New York City jails by age, gender, and race/ethnicity: Implication for public health interventions. Public Health Reports, 122, 733–743.

Goldstrom, I., Henderson, M., Male, A., & Manderscheid, R. W. (1998). Jail mental health services: A national survey. In R. W. Manderscheid, & M. J. Henderson (Eds.), Mental health, United States, 1998 (pp. 176–187). Washington, DC: U.S. Government Printing Office.

Green, B. L., Miranda, J., Daroowalla, A., & Siddique, J. (2005). Trauma exposure, mental health functioning, and program needs of women in jail. Crime & Delin- quency, 51, 133–153.

Greenberg, G. A., & Rosenheck, R. A. (2008). Jail incar- ceration, homelessness, and mental health: A national study. Psychiatric Services, 59, 170–177.

Greenberg, G. A., & Rosenheck, R. A. (2010). Mental health correlates of past homelessness in the national comorbidity study replication. Journal of Health Care for the Poor and Underserved, 21, 1234–1249.

Harris, M., & Anglin, J. (1998). Trauma recovery and empow- erment: A clinician’s guide for working with women in groups. New York: Free Press.

Harrison, P. M., & Beck, A. J. (2006). Prison and jail inmates at midyear 2005 (NCJ Publication No 213133). Wash- ington, DC: U.S. Department of Justice.

HEARTH Act, H.R. 2523, 111th Cong. (2009). Retrieved from http://www.govtrack.us/congress/bills/111/hr2523

Holtfreter, K., Reisig, M. D., & Morash, M. (2004). Poverty, state capital, and recidivism among women offenders. Criminology & Public Policy, 3, 185–208.

International Association for Correctional and Forensic Psychology. (2010). Standards for psychology services in jails, prisons, correctional facilities, and agencies. Criminal Justice and Behavior, 34, 749–809.

James, D. J., & Glaze, L. E. (2006). Mental health problems of prison and jail inmates. Washington, DC: Bureau of Justice Statistics.

Kertesz, S. G., Larson, M. J., Horton, N. J., Winter, M., Saitz, R., & Samet, J. H. (2005). Homeless chronicity and health-related quality of life trajectories among adults with addictions. Medical Care, 43, 574–585.

Kessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S. T., et al. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psycholog- ical Medicine, 32, 959–976.

Kessler, R. C., Barker, P. R., Colpe, L. J., Epstein, J. F., Gfroerer, J. C., Hiripi, E., et al. (2003). Screening for serious mental illness in the general population. Archives of General Psychiatry, 60, 184–189.

Kubiak, S. P., Beeble, M., & Bybee, D. (2010). Testing the validity of the K6 in detecting major depression and PTSD among jailed women. Criminal Justice and Behavior, 37, 64–80.

Kubiak, S. P., Beeble, M., & Bybee, D. (2012). Comparing the validity of the K6 when assessing depression, anx- iety, and PTSD among male and female detainees. International Journal of Offender Therapy and Comparative Criminology, 56, 1220–1238.

Kushel, M. B., Evans, J. L., Perry, S., Robertson, M. J., & Moss, A. R. (2003). No door to lock: Victimization among homeless and marginally housed person. Archives of Internal Medicine, 10, 2492–2499.

Lam, J. A., & Rosenheck, R. (1998). The effect of victimi- zation on clinical outcomes of homeless persons with serious mental illness. Psychiatric Services, 49, 678–683.

Levin, A. J., Culhane, D. P., DeGenova, J., O’Quinn, P., & Bainbridge, J. (2009). Health and social characteristics of homeless adults in Manhattan who were chronically or not chronically unsheltered. Psychiatric Services, 60, 978–981.

Lynch, S. M., DeHart, D. D., Belknap, J., & Green, B. L. (2012). Women’s pathways to jail: The role and intersections of serious mental illness and trauma (NCJ Publication No.

Fries et al. / Role of Gender, Substance Use, and Serious Mental Illness in Anticipated Postjail Homelessness 115

240558). Washington, DC: U.S. Department of Justice.

McNeil, D. E., Binder, R. L., & Robinson, J. C. (2005). Incarceration associated with homelessness, mental disorder, and co-occurring substance abuse. Psychiatric Services, 56, 840–846.

Metraux, S., & Culhane, D. (2006). Recent incarceration history among a sheltered homeless population. Crime and Delinquency, 52, 504–517.

Minton, T. (2011). Jail inmates at midyear 2010 (NCJ Publi- cation No. 233431). Washington, DC: U.S. Depart- ment of Justice.

Mueser, K. T., Noordsy, D. L., Drake, R. E., & Fox, L. (2003). Integrated treatment for dual disorders: A guide to effective practice. New York: Guilford Press.

Mumola, C. J. (2000). Incarcerated parents and their children. (Bureau of Justice Statistics Special Report). Washington, DC: U.S. Department of Justice.

Najavits, L. M. (2001). Seeking safety: A treatment manual for PTSD and substance abuse. New York: Guilford Press.

Reardon, M., Burns, A. B., Preist, R., Sachs-Ericsson, N., & Lang, A. R. (2003). Alcohol use and other psychiatric disorders in the formerly homeless and never homeless: Prevalence, age of onset, comorbidity, temporal sequencing, and service utilization. Substance Use and Misuse, 38, 601–644.

Reisig, M. D., Holtfreter, K., & Morash, M. (2006). Assessing recidivism risk across female pathways to crime. Justice Quarterly, 23, 384–405.

Richie, B. E. (1996). Compelled to crime: The gender entrapment of black battered women. New York: Routledge.

Richie, B. E. (2001). Challenges incarcerated women face as they return to their communities: Findings from life history interviews. Crime Delinquency, 47, 410–427.

Richie, B. E., Freudenberg, N., & Page, J. (2001). Reinte- grating women leaving jail into urban communities: A description of a model program. Journal of Urban Health, 78, 290–303.

Riley, E. D., Weiser, S. D., Sorensen, J. L., Dilworth, S., Cohen, J., & Neilands, T. B. (2007). Housing patterns and correlates of homelessness differ by gender among individuals using San Francisco free food programs. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 84, 415–422.

Shelton, K., Taylor, P., Bonner, A., & van den Bree, M. (2009). Risk factors for homelessness: Evidence from a population-based study. Psychiatric Services, 60, 465–472.

Steadman, H., Osher, F., Robbins, P., Case, B., & Samuels, S. (2009). Prevalence of serious mental illness among jail inmates. Psychiatric Services, 60, 761–765.

Steadman, H. J., & Veysey, B. M. (1997). Providing services for jail inmates with mental disorders. American Jails, 9, 11–23.

Teplin, L. A., Abram, K. M., & McClelland, G. M. (1996). Prevalence of psychiatric disorders among incarcerated women. Archives of General Psychiatry, 53, 505–512.

Tessler, R., Rosenheck, R., & Gamache, G. (2001). Gender differences in self-reported reasons for homelessness. Journal of Social Distress and the Homeless, 10, 243–254.

Theriot, M. T., & Segal, S. P. (2005). Involvement with the criminal justice system among new clients at outpatient mental health agencies. Psychiatric Services, 56, 179–185.

Tischler, V., Rademeyer, A., & Vostanis, P. (2007). Mothers experiencing homelessness: Mental health, support and social care needs. Journal of Health & Social Care in the Community, 15, 246–253.

U.S. Department of Housing and Urban Development. (2011). Homeless assistance. Retrieved from http:// www.hud.gov/homeless/index.cfm

Van Olphen, J., Eliason, M. J., Freudenberg, N., & Barnes, M. (2009). Nowhere to go: How stigma limits the options of female drug users after release from jail. Substance Abuse Treatment, Prevention, and Policy, 4, 10.

Weiss, S., Kung, H., & Pearson, J. (2003). Emerging issues in gender and ethnic differences in substance abuse and treatment. Current Women’s Health, 3, 245–253.

Wenzel, S. L., Koegel, P., & Gelberg, L. (2000). Antecedents of physical and sexual victimization among homeless women: A comparison to homeless men. American Journal of Community Psychology, 28, 367–390.

Lauren Fries, MSW, is a doctoral student, Gina Fedock, MSW, is a doctoral student, and Sheryl Pimlott Kubiak, PhD, is professor, School of Social Work, Michigan State Uni- versity. Address correspondence to Lauren Fries, School of Social Work, Michigan State University, 254 Baker Hall, East Lan- sing, MI 48824; e-mail: [email protected].

Original manuscript received April 16, 2012 Final revision received April 22, 2013 Accepted May 16, 2013 Advance Access Publication June 3, 2014

116 Social Work Research Volume 38, Number 2 June 2014

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