25:35 MAIN STREET - Rethinking Homeless America

For 10 months, the shelter has provided a stable home, a place where dinner is guaranteed. But that security is falling away now. Kenneth Davis right wraps his arm around Janice as they walk down the halls of Dallas Life after their graduation. Of that, the pouring rain is a spiteful reminder. Still, homeless is not a word Kenneth, at 35, is ready to apply to himself.

Dallas Life occupies a former warehouse south of downtown. The front entrance sits along train tracks. Just inside, a metal detector bleeps at every person who enters. Kenneth has no interest in being among them. Janice and Kenneth came without the kids. The oldest daughter, 22, has gone to the Salvation Army with her children. The next oldest, 20, went to stay with a friend. The younger children are with relatives.

Though not as sunny in disposition as her husband, and given to bouts of depression, she sometimes thinks more clearly than he does. Splitting up the family, for now, seems the only way to put things back together. His grandfather survived by filling a cart full of scrap metal.

His father ran a small roofing outfit. At Woodrow Wilson High School, he played football and wrestled and managed to get a diploma. Janice, like Kenneth, had generations of poverty to outrun. Her great-grandmother picked cotton in rural Texas. Her father had no more than a third- or fourth-grade education. She dropped out of school in the eighth grade, not long after her mother and father split up. As a teen, Janice met a man from New Orleans. She moved there and spent about 15 years in a bad marriage. Janice met Kenneth soon after that.

Kenneth worked a succession of low-paying jobs, from warehouse work to fast food to loading milk crates in a dairy. From Kenneth, Janice picked up a marijuana habit. They were lax about making sure the rent got paid. At one low point, they lived near Fair Park in a house with no running water. By the time Janice became homeless, she had several grandchildren. Her year-old was pregnant. Her year-old was also pregnant and had run away with her boyfriend. Still, this rainy afternoon in April , as Kenneth and Janice sit on the concrete in front of Dallas Life, they argue over whether to go inside.

Kenneth wants to return to a business he knows well. He still has plenty of drug connections from his old neighborhood. This afternoon, when the shelter opens its doors to newcomers, Janice and Kenneth walk through the metal detector. She finds it hard to let her guard down.

They came to the shelter together the afternoon before, in April , after sending their kids off in several directions. The youngest went to relatives. The oldest went to another shelter. Today, Janice and Kenneth move into one of its 50 rooms for families, knowing some of their children will soon join them. People tend to arrive at homeless shelters angry — at bosses who fired them, landlords who kicked them out, relatives who let them down, at themselves. Janice is no different. She feels they resent her for it, and she resents them back. Being an unwanted guest is exhausting.

If something goes missing, you probably took it. Though it has no service, it manages to reach a Wi-Fi connection across the street. She opens Facebook and vents. Kenneth, too, feels he knows what people are thinking. Married men here — there are not many — face a silent admonition: What did you do that got your family here?

Bob Sweeney, and its board are mostly free to run it as they please. A Christian conservative with the charisma to win over donors, Sweeney derides government plans to end homelessness. God put the homeless on this Earth to teach something, he says; maybe trying to help them is the best way to learn it.

The Bible, he points out, says the poor will always be with us. Sweeney describes his approach to the homeless as confrontational. Another word he uses is accountability. If you want a place to sleep, go to any shelter, he says. If you want to change your life, come here. The first five nights at Dallas Life are free.

Each night, Janice and Kenneth, like all new residents here, watch the same minute video of Sweeney explaining the rules. After that, they have a choice: She persuades Kenneth to join the program. For the first 30 days, new arrivals are not allowed to leave the property. Time enough to lay low from the dope man, angry family members, or whoever else might try to drag them backward.

After that first month, new arrivals begin to take classes: One class, about addiction, is taught by a solemn, imposing man named Hurel Booker. He teaches from the same manual that helped him kick a drug habit 20 years ago. Demons, the manual explains, are invisible to the eye. They have supernatural powers, and a living human can become their host. Engaging in certain sinful activities seems to attract them.

Janice, in a seat toward the back, believes that. One of her most vivid childhood memories is getting a migraine in the third grade. Her mother, who had a problem with pills, went out for some medicine. As an adult, Janice developed her own addiction to marijuana. It was not much of a vice, relative to what she grew up around. But on top of her poverty, it was enough to invite more misfortune. Booker tells his students to grip imaginary garbage cans, then turn them upside down. Dump out the pain, the issues and the mistakes, he says.

As the weeks turn to months, Janice seems to thrive within the structure and boundaries of the shelter. The staff disciplines with a system of strikes. Rooms are subject to frequent inspection. The list of potential violations is long: Many residents get a strike within their first week. Not the first week, and not in the following months. Moving a couple of hundred women and children through nine shower stalls each night is a feat.

Janice will later recount the night when, as she stands outside the showers, a woman she knows storms through the hallway. Janice watches them all crying as they leave with a few bags of clothes. But sometimes, she is realizing, it means she is smart. God is not finished with me yet. Lyric tosses items on the floor to try to wake up her brother, Milton Hensley, in their room at Dallas Life shelter. Sweeney requires everyone in his program to eventually get a job. Kenneth gets hired with a landscaping company to pick up trash along the road.

The roadside work is hot, boring, and makes him feel like a convict. Later, he is promoted to helping with the intake of new residents. That boss has more confidence in Janice than she has in herself.

35 Main Street, Bob Sweeney - Shop Online for Books in Fiji

As graduation approaches, she begins to feel uneasy. In his book, Janice knows she has to cut loose of things: None of it was worth where it left her family. While in an activity room at the shelter, Janice draws a picture of a house with herself, her husband and her seven children. A yellow school bus stops along Cadiz Street in front of Dallas Life shelter. Its doors swing open to return boys and girls from a nearby elementary school, Martin Luther King Jr. She means the small playground behind the shelter.

Janice spends an instant on the decision, one in the never-ending stream every parent must make. She decides the park will have to wait. Homework comes first, today at least. They walk into the shelter, through the metal detector, up the stairs, and into Room They have a short grace period to find a place to live and move out. But on this day, Janice is consumed with life here and now, the unrelenting work of motherhood.

The girls go inside the room and unload their backpacks. The television is on, set to an episode of Curious George.

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Janice spreads their assignments across a bed. Janice dropped out of school before finishing the eighth grade. Janice wants her children to have a better mother than she had. They eat from plastic trays in the cafeteria and share bathrooms with strangers. Things here are far from perfect. But at least here, unlike in their life before the shelter, order and structure prevail. Their room holds four beds, a desk, a television stand and a dresser. A small closet juts into the living space. The floors are cement. The walls are livened with magic-marker drawings.

Two framed diplomas, the ones Janice and Kenneth earned at graduation, hang above the desk. The girl, who can barely read and write, is easily distracted from her homework. As the girls continue to procrastinate, someone knocks on the door. She and the girls head down to the office of Estella Johnson, a stern-looking, bespectacled woman with a cross on the wall behind her desk. They organize cleanup, monitor bathrooms and handle other chores. Lately, the toilets have been left dirty.

Johnson wants Janice to make sure the supervisors are keeping their eyes out. She got a call from the school. School officials want a meeting. But once back upstairs, no one touches the homework. On Wednesday evenings, Janice has to make the weekly schedule for the floor supervisors. She rushes off to meet with them, leaving the girls in the room playing on her phone. Only after dinner — spaghetti in the cafeteria — do they get back to the homework.

Lyric finishes hers and heads for the showers. With or without the device, the year-old is easily distracted. She missed months of school as the family moved from place to place and finally became homeless. The girl wanders over. Tonight's assignment is reading comprehension, about park rangers who, during a drought, encounter a doe and her fawns.

After showers, they head to an activity room down the hall. Milton sits down to play cards with friends. Janice and the girls pull poster paper and paints from the shelf and spread them across the floor. Each decides to paint a house. A brown zig-zag — stairs leading to a second floor. Then, she makes a stray, accidental stroke.

You gotta make what you messed up into something. Later, back in Room 46, they climb into bed. This time, things have to be different. Janice normally presents a tough exterior. But tonight, she is crying. Nothing is worth having your children sleep outside, she thinks. One morning that March, Janice and Kenneth sit on a metal bench at a downtown rail station, waiting.

A few days earlier, the Dallas Housing Authority approved their application for a Section 8 voucher. The housing authority, which covers seven counties, maintains vouchers for 18, families. New families are admitted only when others drop out. Every couple of years, the authority opens the waiting list, and during a hour window, 30, applications pour in.

A lottery culls that to 5, And even those lucky winners may wait several years. Janice and Kenneth had an advantage: Their homelessness put them on top of the list within a few months of applying. The train carries them to a downtown stop, where they catch Bus No. When the bus stops along Lone Star Drive, they hurry into a brick building and find their way to the training session. Dozens of people, mostly women, pack the room.

Several carry babies; others shush small children. Soon, a housing official, Lauren Kirk, leads them all through a PowerPoint presentation. Don't ask landlords by phone if they accept vouchers. Make a good impression. When the presentation is done, Kirk calls names, one by one, and hands out what everyone came for. Soon, Janice and Kenneth hold their voucher.

They walk back out into the cool air, a step closer to having a home. The sun is working its way through a layer of clouds. Janice and Kenneth check out the approved paperwork for their Section 8 housing voucher — their ticket to life outside the shelter. J anice Hensley eyes a span of razor wire.

1. Situational Variables?
2. After a year in a shelter, a mother and father try to reconstruct a decent life for their family?
3. The long way home.

It coils above an iron gate, which surrounds one of several depressing apartment complexes she will see today. Trash is scattered by a dumpster. Boards seal off apartment windows. People are standing around. She cuts him off: Normally, she uses his nickname, K. Kenneth has spent time apartment hunting on gosection8. Now his sister is driving them through southeast Dallas and Pleasant Grove. They find the office, and Kenneth goes in. When he returns, Janice has a thought: So we got to be careful. Kenneth is ready to pick an apartment, somewhere, anywhere. Just keep to yourself, he figures.

But Janice knows better: The people around you matter. Janice ruled out the area around Oak Cliff, where they were last evicted. She wants to avoid the sound of gunfire at night. She also wants to live close to the shelter, because she and Kenneth need to keep their jobs there. The next complex they visit is better, but not by much.

Buy for others

Janice descends into a chilly silence. Her mood puts Kenneth on the defensive. Tell me, what side of town you want to go to? You said the Pleasant Grove area, so I was just looking some in the Grove. So what you want to do? Kenneth passes money back to Janice after taking their paychecks, earned from their jobs at Dallas Life shelter, to a check cashing business.

The spacious leasing office looks good: Clean tile floor overlaid with large, expensive-looking rugs. Fake trees and leather couches. The management accepts vouchers, and a two-bedroom is available soon. They fill out the application, fudging their rental history to leave out their two evictions. Kenneth hands it to the woman in the leasing office.

They start over, changing a couple of dates to further smooth out the gaps in their rental history. The woman makes copies of their IDs. The hunt for a Section 8 apartment goes nowhere. They spend weeks looking at dozens of places. They pay the application fees and fill out the forms, only to be denied when their past catches up to them. One afternoon in April, Janice and Kenneth enter the leasing office of an apartment complex in far northeast Dallas.

This, it has turned out, is where they are going to live. The complex, Jackson Branch, participates in a program called permanent supportive housing. Homeless persons have poorer physical health when compared to the general population Schanzer et al. Within the homeless population, poorer health has been associated with greater age just as it is in more normative populations Stein et al. As described above, men are more likely to be homeless and to engage in a variety of behaviors that put their health at risk Williams, Health care utilization, injection drug use IDU , and sexual risk behaviors serve as outcome variables.

In general, health care utilization among homeless individuals is low Kushel et al. The model assesses whether pertinent biopsychosocial variables predict or predict negatively health care utilization in addition to the HIV risk behaviors of IDU and sexual risk behaviors. Utilization is defined in this current paper as having a regular place to go for care such as a clinic or private office, and outpatient visits.

Exigent service utilization so common among the homeless, such as emergency room use and hospitalizations, was not included as appropriate use of services. In addition to assessing the significance of bivariate associations among the variables of interest, a model is tested in which the background situational factors social support, severity of homelessness, age, ethnicity, and housing quality predict psychosocial factors of PTSD and emotional distress and health status.

In turn, all of these variables predict the behavioral outcomes of IDU, sexual risk behavior, and health care utilization. Because this model is cross-sectional, it is possible that influences go in other directions.

This study uses baseline information from an ongoing longitudinal study evaluating the effectiveness of an intervention encouraging completion of a hepatitis A and B vaccine series among homeless adults in the Skid Row area of Los Angeles. Data were collected between September and June from participants of whom were heterosexual males 8 men self-identified as homosexual and were deleted from this current sample. Participants were eligible for the intervention if they satisfied the following requirements: Positivity for HBV was grounds for exclusion from the study.

The average age was 42 years S. Demographics of the heterosexual male sample were similar to those of the entire sample. Participating shelters were stratified by type emergency versus residential recovery and size and randomized to one of three treatment programs. Flyers were posted at recruitment sites to inform residents of the study and presentations were held at the sites.

After written informed consent to screening was obtained, outreach workers administered a brief questionnaire covering basic socio-demographic characteristics and a hepatitis-related health history designed to assess eligibility for the vaccination study. Homeless adults that were HBV negative as assessed by a blood test then provided final written informed consent for the study and were administered the larger baseline survey used in the current study.

Several of the constructs used in the current model are represented as latent variables. They were created from multi-item scales from the baseline questionnaire and are described in more detail below. Single items inquired how often various forms of support are available to them if they need it e. Items were rated from 1 none of the time to 5 all of the time. To avoid too many indicators, the 18 scores were randomly combined into parcels of 6 to obtain 3 mean indicators for Social Support.

The number of times they had been homeless and the number of years percent of life they had been homeless in their lifetimes. This variable representing homelessness severity has been used in prior research e. To avoid a spuriously high correlation between age and years of homelessness, percent of lifetime homeless was calculated and used in the analysis rather than years. Twenty-nine percent of the sample reported poor quality housing. Hispanics and others were used as the reference groups for ethnicity. Scores range from 1 all of the time to 6 none of the time and were reverse scored where appropriate so that higher scores indicate more distress.

Another emotional distress variable consisted of a total-item score from the item Center for Epidemiological Studies Depression CES-D scale Radloff, that assesses the frequency of depressive symptoms in the previous week on a 4-point response scale ranging from 1 rarely or none of the time to 4 most of the time. The items were reverse-scored as appropriate, and summed. Sexual Risk Behavior in the past 6 months was indicated by responses to 3 items. These items were the average number of times per week they had sex without a condom for 1 sexual intercourse, 2 oral sex, and 3 anal sex.

Health Care Utilization was indicated by 1 whether they are currently able to receive care at a regular place for care such as a clinic or from a private doctor, 2 whether they had visited a clinic or private doctor in the past 6 months. The analyses were performed using the EQS structural equations program Bentler, Latent variable analysis allows one to evaluate causal hypotheses with correlational, non-experimental data.

The CFI and RCFI range from 0 to 1 and reflect the improvement in fit of a hypothesized model over a model of complete independence among the measured variables. An initial confirmatory factor analysis CFA assessed the adequacy of the hypothesized measurement model and the associations among the latent and single-item variables. Then a latent variable path model positioned the situational Social Support, Chronic Homelessness, and Poor Housing and demographic variables age, ethnicity as predictors of the psychosocial and health-related variables of PTSD, Poor Health Status, and Emotional Distress which served as intervening variables.

Table 2 reports summary statistics of the measured variables and the factor loadings of the hypothesized factor structure. Fit indexes for the CFA model were all excellent: Although the initial fit of the model was outstanding, two supplemental covariances were added between error residuals: These supplementary relationships appear reasonable in light of their high associations with each other and their addition improved the fit further.

Table 3 reports the correlations among the variables in the model. Examining significant associations within Table 3 from top to bottom, Greater Social Support was significantly associated with being younger, better health, less emotional distress, less IDU, and better housing quality. Older homeless men reported worse health, were less likely to report IDU, were more likely to utilize health care, were more likely to be African-American, were less likely to be White, and were more likely to have poor housing quality e.

It was modestly but significantly associated with healthcare utilization and poor quality housing. Emotional Distress was significantly associated with greater IDU, poor housing quality, and was more prevalent among the white males. More Sexual Risk Behavior was associated with poor housing quality. The final predictive structural equation model is presented in Figure 1 after non-significant paths and covariances were gradually deleted. The figure indicates the logical flow of influences from the background demographic and situational factors to the intervening psychosocial and health status factors which in turn predicted the outcome behaviors.

Associations among the predictors are not depicted for readability but are similar to those reported in Table 3. No paths or correlations were added to this model. Fit indexes for the final path model were very good: Final structural path model depicting influences of situational, demographic, psychosocial, and health status variables on HIV risk behaviors and health care utilization among homeless men. Arrows represent regression paths. All regression coefficients are standardized. The large circles designate latent variables; the rectangles represent measured variables. Indirect Effects mediated through the intervening variables were assessed for their significance.

These indirect influences would have flowed through Emotional Distress. Greater age and Severity of Homelessness had significant and positive indirect effects on Health Care Utilization which were probably mainly mediated through Poor Health Status. The outstanding fit of the model confirms the high degree of interconnectedness and relatedness of the variables within the model.

These results highlight the usefulness of components of the biopsychosocial model in assessing relations among variables related to health and health risk among homeless men e. The structural equation model consists of cross-sectional variables so influences may be flowing in directions other than those pictured or in a bi-directional fashion. However, this model depicted one way that one can conceptualize the flow of behaviors among a group of highly interconnected variables that are pertinent to health and health risk behaviors.

The health-related variables indicating poor health and health care use were minimally associated with HIV risk behaviors. Neither good health nor bad health impacted their high risk behaviors to any appreciable extent. There was only a very small relationship between sexual risk behaviors and IDU. Furthermore, within this vulnerable population, minority ethnicity did not signal a worse situation. Rather, the white men were the most likely to report severity of homelessness, use injection drugs, and report more PTSD and greater emotional distress. Healthcare utilization among men who are homeless is driven by poor health as the very large association between poor health status and utilization indicates.

Alternatives for decreasing HIV risk behaviors among homeless men are through other venues and through recognition of associations among other variables that are pertinent to HIV risk behaviors. This would include better housing, substance abuse treatment, and treatment for mental illness.

Susser, Valencia, and Conover observed that male psychiatric patients in homeless shelters are relatively inaccessible to preventive interventions but they may be reached during the course of their treatment in shelter programs. The predictive model points out the centrality of severity of homelessness even within a sample that by definition is all homeless. Furthermore, poor housing quality was an independent predictor of distress which predicted more IDU and more sexual risk behavior. Thus, leverage points for change may arise out of housing considerations.

Similar results among homeless women of reproductive age have been found as well Stein et al. Women reporting the most homelessness severity also reported other threats to health and more drug use and alcohol problems, greater psychological distress, and a lack of appropriate health care. Social support was an important part of the model. It was associated with better housing quality, less severity of homelessness, and was more prevalent among younger homeless men.

In addition, it predicted considerably less emotional distress and better health status. Benda identified social support as more important among homeless women than among homeless men. However, there is a role for greater social support in improving both physical and mental health outcomes for homeless men, especially the long-term homeless. Because homeless persons are in transient living conditions, and thus at a higher risk for engaging in risky behaviors that can lead to infection, housing is a vital piece of HIV prevention.

Permanent supportive housing programs operate under the assumption that the combination of permanent housing and ongoing supportive services will foster independence and self-sufficiency among homeless persons USDHUD, Residents in permanent supportive housing units receive a rent subsidy, which enables the residents to access resources that will improve their quality of life USDHUD, Stable housing increases the likelihood for a homeless person to seek medical care Burt et al. Relying on the emergency room is detrimental not only to the homeless individual, but also to society as a whole because of costs.

Hospitalization of homeless persons costs 49 times more than supportive housing Bring L. The predictive model that was tested could have been formulated with a different ordering.

Also, self-reports of sexual behaviors, substance abuse and health were used. A 6-month or shorter recall time was used for most of the variables in the model. Among the men including in this study, greater sexual risk behavior was predicted most strongly by poor quality housing and severity of homeless. IDU was associated with greater emotional distress and was much less prevalent among African-Americans. The authors thank Gisele Pham for secretarial and production assistance. National Center for Biotechnology Information , U. Am J Mens Health. Author manuscript; available in PMC May 7.

Stein , Adeline Nyamathi , and Jazmin I. Author information Copyright and License information Disclaimer.

Correspondence concerning this article should be addressed to Judith A. The publisher's final edited version of this article is available at Am J Mens Health. See other articles in PMC that cite the published article. Situational Variables Social support, poor housing quality, and severity of homelessness are important situational variables to explore in regards to homelessness Kingree et al. Behavioral outcomes Health care utilization, injection drug use IDU , and sexual risk behaviors serve as outcome variables.

Hypothetical model In addition to assessing the significance of bivariate associations among the variables of interest, a model is tested in which the background situational factors social support, severity of homelessness, age, ethnicity, and housing quality predict psychosocial factors of PTSD and emotional distress and health status. Methods Participants and procedures This study uses baseline information from an ongoing longitudinal study evaluating the effectiveness of an intervention encouraging completion of a hepatitis A and B vaccine series among homeless adults in the Skid Row area of Los Angeles.

Open in a separate window. Severity of Homelessness was indicated by 2 items The number of times they had been homeless and the number of years percent of life they had been homeless in their lifetimes. Results Confirmatory Factor Analysis Table 2 reports summary statistics of the measured variables and the factor loadings of the hypothesized factor structure.

Table 2 Summary statistics and factor loadings in the CFA model. Table 3 Correlations among latent and measured variables.