homelessness research paper example

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• Published: 22 August 2017

Social conditions of becoming homelessness: qualitative analysis of life stories of homeless peoples

• Mzwandile A. Mabhala   ORCID: orcid.org/0000-0003-1350-7065 1 , 3 ,
• Asmait Yohannes 2 &
• Mariska Griffith 1  

International Journal for Equity in Health volume  16 , Article number:  150 ( 2017 ) Cite this article

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It is increasingly acknowledged that homelessness is a more complex social and public health phenomenon than the absence of a place to live. This view signifies a paradigm shift, from the definition of homelessness in terms of the absence of permanent accommodation, with its focus on pathways out of homelessness through the acquisition and maintenance of permanent housing, to understanding the social context of homelessness and social interventions to prevent it.

However, despite evidence of the association between homelessness and social factors, there is very little research that examines the wider social context within which homelessness occurs from the perspective of homeless people themselves. This study aims to examine the stories of homeless people to gain understanding of the social conditions under which homelessness occurs, in order to propose a theoretical explanation for it.

Twenty-six semi-structured interviews were conducted with homeless people in three centres for homeless people in Cheshire North West of England.

The analysis revealed that becoming homeless is a process characterised by a progressive waning of resilience capacity to cope with life challenges created by series of adverse incidents in one’s life. The data show that final stage in the process of becoming homeless is complete collapse of relationships with those close to them. Most prominent pattern of behaviours participants often describe as main causes of breakdown of their relationships are:

engaging in maladaptive behavioural lifestyle including taking drugs and/or excessive alcohol drinking

Being in trouble with people in authorities.

Homeless people describe the immediate behavioural causes of homelessness, however, the analysis revealed the social and economic conditions within which homelessness occurred. The participants’ descriptions of the social conditions in which were raised and their references to maladaptive behaviours which led to them becoming homeless, led us to conclude that they believe that their social condition affected their life chances: that these conditions were responsible for their low quality of social connections, poor educational attainment, insecure employment and other reduced life opportunities available to them.

It is increasingly acknowledged that homelessness is a more complex social and public health phenomenon than the absence of a place to live. This view signifies a paradigm shift, from the definition of homelessness in terms of the absence of permanent accommodation [ 1 , 2 , 3 , 4 , 5 ], with its focus on pathways out of homelessness through the acquisition and maintenance of permanent housing [ 6 ], to understanding the social context of homelessness and social interventions to prevent it [ 6 ].

Several studies explain the link between social factors and homelessness [ 6 , 7 , 8 , 9 , 10 ]. The most common social explanations centre on seven distinct domains of deprivation: income; employment; health and disability; education, skills and training; crime; barriers to housing and social support services; and living environment [ 11 ]. Of all forms, income deprivation has been reported as having the highest risk factors associated with homelessness [ 7 , 12 , 13 , 14 ]: studies indicate that people from the most deprived backgrounds are disproportionately represented amongst the homeless [ 7 , 13 ]. This population group experiences clusters of multiple adverse health, economic and social conditions such as alcohol and drug misuse, lack of affordable housing and crime [ 10 , 12 , 15 ]. Studies consistently show an association between risk of homelessness and clusters of poverty, low levels of education, unemployment or poor employment, and lack of social and community support [ 7 , 10 , 13 , 16 ].

Studies in different countries throughout the world have found that while the visible form of homelessness becomes evident when people reach adulthood, a large proportion of homeless people have had extreme social disadvantage and traumatic experiences in childhood including poverty, shortage of social housing stocks, disrupted schooling, lack of social and psychological support, physical, sexual, and emotional abuse, neglect, dysfunctional family environments, and unstable family structures, all of which increase the likelihood of homelessness [ 10 , 13 , 14 ].

Furthermore, a large body of evidence suggests that people exposed to diverse social disadvantages at an early age are less likely to adapt successfully compared to people without such exposure [ 9 , 10 , 13 , 17 ], being more susceptible to adopting maladaptive coping behaviours such as theft, trading sex for money, and selling or using drugs and alcohol [ 7 , 9 , 18 , 19 ]. Studies show that these adverse childhood experiences tend to cluster together, and that the number of adverse experiences may be more predictive of negative adult outcomes than particular categories of events [ 17 , 20 ]. The evidence suggests that some clusters are more predictive of homelessness than others [ 7 , 12 ]: a cluster of childhood problems including mental health and behavioural disorders, poor school performance, a history of foster care, and disrupted family structure was most associated with adult criminal activities, adult substance use, unemployment and subsequent homelessness [ 12 , 17 , 21 ]. However, despite evidence of the association between homelessness and social factors, there is very little research that examines the wider social context within which homelessness occurs from the perspective of homeless people themselves.

This paper adopted Anderson and Christian’s [ 18 ] definition, which sees homelessness as a ‘function of gaining access to adequate, affordable housing, and any necessary social support needed to ensure the success of the tenancy’. Based on our synthesis of the evidence, this paper proposes that homelessness is a progressive process that begins at childhood and manifests itself at adulthood, one characterised by loss of the personal resources essential for successful adaptation. We adopted the definition of personal resources used by DeForge et al. ([ 7 ], p. 223), which is ‘those entities that either are centrally valued in their own right (e.g. self-esteem, close attachment, health and inner peace) or act as a means to obtain centrally valued ends (e.g. money, social support and credit)’. We propose that the new paradigm focusing on social explanations of homelessness has the potential to inform social interventions to reduce it.

In this study, we examine the stories of homeless people to gain understanding of the conditions under which homelessness occurs, in order to propose a theoretical explanation for it.

The design of this study was philosophically influenced by constructivist grounded theory (CGT). The aspect of CGT that made it appropriate for this study is its fundamental ontological belief in multiple realities constructed through the experience and understanding of different participants’ perspectives, and generated from their different demographic, social, cultural and political backgrounds [ 22 ]. The researchers’ resulting theoretical explanation constitutes their interpretation of the meanings that participants ascribe to their own situations and actions in their contexts [ 22 ].

The stages of data collection and analysis drew heavily on other variants of grounded theory, including those of Glaser [ 23 ] and Corbin and Strauss [ 24 ].

Setting and sampling strategy

The settings for this study were three centres for homeless people in two cities (Chester and Crewe) in Cheshire, UK. Two sampling strategies were used in this study: purposive and theoretical. The study started with purposive sampling and in-depth one-to-one semi-structured interviews with eight homeless people to generate themes for further exploration.

One of the main considerations for the recruitment strategy was to ensure that the process complies with the ethical principles of voluntary participation and equal opportunity to participate. To achieve this, an email was sent to all the known homeless centres in the Cheshire and Merseyside region, inviting them to participate. Three centres agreed to participate, all of them in Cheshire – two in Chester and one in Crewe.

Chester is the most affluent city in Cheshire and Merseyside, and therefore might not be expected to be considered for a homelessness project. The reasons for including it were: first, it was a natural choice, since the organisations that funded the project and the one that led the research project were based in Chester; second, despite its affluence, there is visible evidence of homelessness in the streets of Chester; and third, it has several local authority and charity-funded facilities for homeless people.

The principal investigator spent 1 day a week for 2 months in three participating centres, during that time oral presentation of study was given to all users of the centre and invited all the participants to participate and written participants information sheet was provided to those who wished to participate. During that time the principal investigator learned that the majority of homeless people that we were working with in Chester were not local. They told us that they came to Chester because there was no provision for homeless people in their former towns.

To help potential participants make a self-assessment of their suitability to participate without unfairly depriving others of the opportunity, participants information sheet outline criteria that potential participants had to meet: consistent with Economic and Social Research Council’s Research Ethics Guidebook [ 25 ], at the time of consenting to and commencing the interview, the participant must appear to be under no influence of alcohol or drugs, have a capacity to consent as stipulated in England and Wales Mental Capacity Act 2005 [ 26 ], be able to speak English, and be free from physical pain or discomfort.

As categories emerged from the data analysis, theoretical sampling was used to refine undeveloped categories in accordance with Strauss and Corbin’s [ 27 ] recommendations. In total 26 semi-structured interviews were carried out. Theoretical sampling involved review of memos or raw data, looking for data that might have been overlooked [ 27 , 28 ], and returning to key participants asking them to give more information on categories that seemed central to the emerging theory [ 27 , 28 ].

The sample comprised of 22 male and 4 female, the youndgest participant was 18 the eldest was 74 years, the mean age was 38.6 years. Table 1 illustrates participant’s education history, childhood living arrangements, brief participants family and social history, emotional and physical health, the onset of and trigger for homelessness.

Ethical approval

Ethical approval was obtained from the Research Ethics Committee of the University of Chester. The centre managers granted access once ethical approval had been obtained, and after their review of the study design and other research material, and of the participant information sheet which included a letter of invitation highlighting that participation was voluntary.

Data analysis

In this study data collection and analysis occurred simultaneously. Analysis drew on Glaser’s [ 23 ] grounded theory processes of open coding, use of the constant comparative method, and the iterative process of data collection and data analysis to develop theoretical explanation of homelessness.

The process began by reading the text line-by-line identifying and open coding the significant incidents in the data that required further investigation. The findings from the initial stage of analysis are published in Mabhala [ 29 ]. The the second stage the data were organised into three themes that were considered significant in becoming homeless (see Fig. 1 ):

Engaging in maladaptive behaviour

Being in trouble with the authorities.

Being in abusive environments.

Social explanation of becoming homeless. Legend: Fig. 1 illustrates the process of becoming homeless

The key questions that we asked as we continued to interrogate the data were: What category does this incident indicate? What is actually happening in the data? What is the main concern being faced by the participants? Interrogation of the data revealed that participants were describing the process of becoming homeless.

The comparative analysis involved three processes described by Glaser ([ 23 ], p. 58–60): each incident in the data was compared with incidents from both the same participant and other participants, looking for similarities and differences. Significant incidents were coded or given labels that represented what they stood for, and similarly coded or labeled when they were judged to be about the same topic, theme or concept.

After a period of interrogation of the data, it was decided that the two categories - destabilising behaviour, and waning ofcapacity for resilience were sufficiently conceptual to be used as theoretical categories around which subcategories could be grouped (Fig. 1 ).

Once the major categories had been developed, the next step consisted of a combination of theoretical comparison and theoretical sampling. The emerging categories were theoretically compared with the existing literature. Once this was achieved, the next step was filling in and refining the poorly defined categories. The process continued until theoretical sufficiency was achieved.

Figure 1 illustrates the process of becoming homeless. The analysis revealed that becoming homeless is a process characterised by a progressive waning of resilience created by a series of adverse incidents in one’s life. Amongst the frequently cited incidents were being in an abusive environment and losing a significant person in one’s life. However, being in an abusive environment emerged from this and previously published studies as a major theme; therefore, we decided to analyse it in more detail.

The data further show that the final stage in the process of becoming homeless is a complete collapse of relationships with those with whom they live. The most prominent behaviours described by the participants as being a main cause of breakdown are:

Engaging in maladaptive behaviour: substance misuse, alcoholism, self-harm and disruptive behaviours

Being in trouble with the authorities: theft, burglary, arson, criminal offenses and convictions

The interrogation of data in relation to the conditions within which these behaviours occurred revealed that participants believed that their social contexts influenced their life chance, their engagement with social institution such as education and social services and in turn their ability to acquire and maintain home. Our experiences have also shown that homeless people readily express the view that behavioural lifestyle factors such as substance misuse and engaging in criminal activities are the causes of becoming homeless. However, when we spent time talking about their lives within the context of their status as homeless people, we began to uncover incidents in their lives that appeared to have weakened their capacity to constructively engage in relationships, engage with social institutions to make use of social goods [ 29 , 30 , 31 ] and maturely deal with societal demands.

Being in abusive environments

Several participants explicitly stated that their childhood experiences and damage that occurred to them as children had major influences on their ability to negotiate their way through the education system, gain and sustain employment, make appropriate choices of social networks, and form and maintain healthy relationships as adults.

It appears that childhood experiences remain resonant in the minds of homeless participants, who perceive that these have had bearing on their homelessness. Their influence is best articulated in the extracts below. When participants were asked to tell their stories of what led to them becoming homeless, some of their opening lines were:

What basically happened, is that I had a childhood of so much persistent, consistent abuse from my mother and what was my stepfather. Literally consistent, we went around with my mother one Sunday where a friend had asked us to stay for dinner and mother took the invitation up because it saved her from getting off her ass basically and do anything. I came away from that dinner genuinely believing that the children in that house weren’t loved and cared for, because they were not being hit, there was no shouting, no door slamming. [Marco]

It appears that Marco internalised the incidents of abuse, characterised by shouting, door slamming and beating as normal behaviour. He goes on to intimate how the internalised abusive behaviour affected his interaction with his employers.

‘…but consistently being put down, consistently being told I was thick, I started taking jobs and having employers effing and blinding at me. One employer actually used a “c” word ending in “t” at me quite frequently and I thought it was acceptable, which obviously now I know it’s not. So I am taking on one job after another that, how can I put it? That no one else would do basically. I was so desperate to work and earn my own money. [Marco]

Similarly, David makes a connection between his childhood experience and his homelessness. When he was asked to tell his life story leading to becoming homeless, his opening line was:

I think it [homelessness] started off when I was a child. I was neglected by my mum. I was physically and mentally abused by my mum. I got put into foster care, when I left foster care I was put in the hostel, from there I turn into alcoholic. Then I was homeless all the time because I got kicked out of the hostels, because you are not allowed to drink in the hostel. [David]

David and Marco’s experiences are similar to those of many participants. The youngest participant in this study, Clarke, had fresh memories of his abusive environment under his stepdad:

I wouldn't want to go back home if I had a choice to, because before I got kicked out me stepdad was like hitting me. I wouldn't want to go back to put up with that again. [I didn't tell anyone] because I was scared of telling someone and that someone telling me stepdad that I've told other people. ‘[Be] cause he might have just started doing again because I told people. It might have gotten him into trouble. [Clarke]

In some cases, participants expressed the beliefs that their abusive experience not only deprived them life opportunities but also opportunities to have families of their own. As Tom and Marie explain:

We were getting done for child neglect because one of our child has a disorder that means she bruise very easily. They all our four kids into care, social workers said because we had a bad childhood ourselves because I was abused by my father as well, they felt that we will fail our children because we were failed by our parents. We weren’t given any chance [Tom and Marie]

Norma, described the removal of her child to care and her maladaptive behaviour of excessive alcohol use in the same context as her experience of sexual abuse by her father.

I had two little boys with me and got took off from me and put into care. I got sexually abused by my father when I was six. So we were put into care. He abused me when I was five and raped me when I was six. Then we went into care all of us I have four brothers and four sisters. My dad did eighteen months for sexually abusing me and my sister. I thought it was normal as well I thought that is what dads do [Norma]

The analysis of participants in this study appears to suggest that social condition one is raised influence the choice of social connections and life partner. Some participants who have had experience of abuse as children had partner who had similar experience as children Tom and Marie, Lee, David and his partners all had partners who experienced child abuse as children.

Tom and Marie is a couple we interviewed together. They met in hostel for homeless people they have got four children. All four children have been removed from them and placed into care. They sleep rough along the canal. They explained:

We have been together for seven years we had a house and children social services removed children from us, we fell within bedroom tax. …we received an eviction order …on the 26th and the eviction date was the 27th while we were in family court fighting for our children. …because of my mental health …they were refusing to help us.

Our children have been adopted now. The adoption was done without our permission we didn’t agree to it because we wanted our children home because we felt we were unfairly treated and I [Marie] was left out in all this and they pin it all on you [Tom] didn’t they yeah, my [Tom] history that I was in care didn’t help.

Tom went on to talk about the condition under which he was raised:

I was abandoned by my mother when I was 12 I was then put into care; I was placed with my dad when I was 13 who physically abused me then sent back to care. [Tom].

David’s story provides another example of how social condition one is raised influence the choice of social connections and life partner. David has two children from two different women, both women grew up in care. Lisa one of David’s child mother is a second generation of children in care, her mother was raised in care too.

I drink to deal with problems. As I say I’ve got two kids with my girlfriend Kyleigh, but I got another lad with Lisa, he was taken off me by social services and put on for adoption ten years ago and that really what started it; to deal with that. Basically, because I was young, and I had been in care and the way I had been treated by my mum. Basically laid on me in the same score as my mum and because his mum [Lisa] was in care as well. So they treated us like that, which was just wrong. [David]

In this study, most participants identified alcohol or drugs and crime as the cause of relationships breakdown. However, the language they used indicates that these were secondary reasons rather than primary reasons for their homelessness. The typical question that MA and MG asked the interview participants was “tell us how did you become homeless”? Typically, participants cited different maladaptive behaviours to explain how they became homeless.

Alvin’s story is typical of:

Basically I started off as a bricklayer, … when the recession hit, there was an abundance of bricklayers so the prices went down in the bricklaying so basically with me having two young children and the only breadwinner in the family... so I had to kinda look for factory work and so I managed to get a job… somewhere else…. It was shift work like four 12 hour days, four 12 hour nights and six [days] off and stuff like that, you know, real hard shifts. My shift was starting Friday night and I’ll do Friday night, Saturday night to Monday night and then I was off Tuesday, Wednesday and Thursday, but I’d treat that like me weekend you know because I’ve worked all weekend. Then… so I’d have a drink then and stuff like that, you know. 7 o’ clock on a Monday morning not really the time to be drinking, but I used to treat it like me weekend. So we argued, me and my ex-missus [wife], a little bit and in the end we split up so moved back to me mum's, but kept on with me job, I was at me mum’s for possibly about five years and but gradually the drinking got worse and worse, really bad. I was diagnosed with depression and anxiety. … I used to drink to get rid of the anxiety and also to numb the pain of the breakup of me marriage really, you know it wasn’t good, you know. One thing led to another and I just couldn’t stop me alcohol. I mean I’ve done drugs you know, I was into the rave scene and I’ve never done hard drugs like heroin or... I smoke cannabis and I use cocaine, and I used to go for a pint with me mates and that. It all came to a head about November/December time, you know it was like I either stop drinking or I had to move out of me mum's. I lost me job in the January through being over the limit in work from the night before uum so one thing led to another and I just had to leave. [Alvin]

Similarly, Gary identified alcohol as the main cause of his relationship breakdown. However, when one listens to the full story alcohol appears to be a manifestation of other issues, including financial insecurities and insecure attachment etc.

It [the process of becoming homeless] mainly started with the breakdown of the relationship with me partner. I was with her for 15 years and we always had somewhere to live but we didn't have kids till about 13 years into the relationship. The last two years when the kids come along, I had an injury to me ankle which stopped me from working. I was at home all day everyday. …I was drinking because I was bored. I started drinking a lot ‘cause I couldn't move bout the house. It was a really bad injury I had to me ankle. Um, and one day me and me partner were having this argument and I turned round and saw my little boy just stood there stiff as a board just staring, looking at us. And from that day on I just said to me partner that I'll move out, ‘cause I didn't want me little boy to be seeing this all the time. [Gary]

In both cases Gary and Alvin indicate that changes in their employment status created conditions that promoted alcohol dependency, though both explained that they drank alcohol before the changes in their employment status occurred and the breakdown of relationships. Both intimated that that their job commitment limited the amount of time available to drink alcohol. As Gary explained, it is the frequency and amount of alcohol drinking that changed as a result of change in their employment status:

I used to have a bit of a drink, but it wasn’t a problem because I used to get up in the morning and go out to work and enjoy a couple of beers every evening after a day’s work. Um, but then when I wasn't working I was drinking, and it just snowballed out, you know snowball effect, having four cans every evening and then it went from there. I was drinking more ‘cause I was depressed. I was very active before and then I became like non-active, not being able to do anything and in a lot of pain as well. [Gary]

Furthermore, although the participants claim that drinking alcohol was not a problem until their employment circumstances changed, one gets a sense that alcohol was partly responsible for creating conditions that resulted in the loss of their jobs. In Gary’s case, for example, alcohol increased his vulnerability to the assault and injuries that cost him his job:

I got assaulted, kicked down a flight of stairs. I landed on me back on the bottom of the stairs, but me heel hit the stairs as it was still going up if you know what I mean. Smashed me heel, fractured me heel… So, by the time I got to the hospital and they x-rayed it they wasn't even able to operate ‘cause it was in that many pieces, they weren't even able to pin it if you know what I mean. [Gary]

Alvin, of the other hand, explained that:

I lost my job in the January through being over the limit in work from the night before, uum so one thing led to another and I just had to leave. [Alvin]

In all cases participants appear to construct marriage breakdown as an exacerbating factor for their alcohol dependence. Danny, for example, constructed marriage breakdown as a condition that created his alcohol dependence and alcohol dependence as a cause of breakdown of his relationship with his parents. He explains:

I left school when I was 16. Straight away I got married, had children. I have three children and marriage was fine. Umm, I was married for 17 years. As the marriage broke up I turned to alcohol and it really, really got out of control. I moved in with my parents... It was unfair for them to put up with me; you know um in which I became... I ended up on the streets, this was about when I was 30, 31, something like that and ever since it's just been a real struggle to get some permanent accommodation. [Danny]

Danny goes on to explain:

Yes [I drank alcohol before marriage broke down but] not very heavily, just like a sociable drink after work. I'd call into like the local pub and have a few pints and it was controlled. My drinking habit was controlled then. I did go back to my parents after my marriage break up, yes. I was drinking quite heavily then. I suppose it was a form of release, you know, in terms of the alcohol which I wish I'd never had now. When I did start drinking heavy at me parents’ house, I was getting in trouble with the police being drunk and disorderly. That was unfair on them. [Danny]

The data in this study indicate that homelessness occurs when the relationships collapse, irrespective of the nature of the relationship. There were several cases where lifestyle behaviour led to a relationship collapse between child and parents or legal guardians.

In the next excerpt, Emily outlines the incidents: smoking weed, doing crack and heroin, and drinking alcohol. She also uses the words ‘because’, ‘when’ and ‘obviously’, which provide clues about the precipitating condition for her behaviours “spending long time with people who take drugs”.

I've got ADHD like, so obviously my mum kicked me out when I was 17 and then like I went to **Beswick** and stuff like that. My mum in the end just let me do what I wanted to do, ‘cause she couldn't cope anymore. …I mean I tried to run away from home before that, but she'd always like come after me in like her nightie and pyjamas and all that. But in the end she just washed her hands of me . [Emily]

Emily presented a complex factors that made it difficult for her mother to live with her. These included her mother struggle with raising four kids as a single parent, Emily’s mental health (ADHD], alcohol and drug use. She goes on to explain that:

Ummm, well the reason I got kicked out of my hostel was ‘cause of me drinking, so I'd get notice to quit every month, then I’d have a meeting with the main boss and then they'd overturn it and this went on every month for about six months. Also, it was me behaviour as well, but obviously drink makes you do stuff you don't normally do and all that shit. I lived here for six months, got kicked out because I jumped out the window and broke me foot. I was on the streets for six months and then they gave me a second chance and I've been here a year now. So that's it basically. [Emily]

There were several stories of being evicted from accommodation due to excessive use of alcohol. One of those is David:

I got put into foster care. When I left foster care I was put in the hostel, from there I turn into alcoholic. Then I was homeless all the time because I got kicked out of the hostels, because you are not allowed to drink in the hostel. It’s been going on now for about… I was thirty-one on Wednesday, so it’s been going on for about thirteen years, homeless on and off. Otherwise if not having shoplifted for food and then go to jail, and when I don’t drink I have lot of seizures and I end up in the hospital. Every time I end up on the street. I trained as a chef, I have not qualified yet, because of alcohol addiction, it didn’t go very well. I did couple of jobs in restaurants and diners, I got caught taking a drink. [David]

Contrary to the other incidents where alcohol was a factor that led to homelessness, Barry’s description of his story appears to suggest that the reason he had to leave his parents’ home was his parents’ perception that his sexuality brought shame to the family:

When I came out they I’m gay, my mum and dad said you can’t live here anymore. I lived in a wonderful place called Nordic... but fortunately, mum and dad ran a pub called […] [and] one of the next door neighbours lived in a mansion. His name was [….] [and] when I came out, he came out as in he said “I'm a gay guy”, but he took me into Liverpool and housed me because I had nowhere to live. My mum and dad said you can't live here anymore. And unfortunately, we get to the present day. I got attacked. I got mugged... only walked away with a £5 note, it’s all they could get off me. They nearly kicked me to death so I was in hospital for three weeks. By the time I came out, I got evicted from my flat. I was made homeless. [Barry]

We used the phrase “engaging in maladaptive behaviour” to conceptualise the behaviours that led to the loss of accommodation because our analysis appear to suggest that these behaviours were strategies to cope with the conditions they found themselves in. For example, all participants in this category explained that they drank alcohol to cope with multiple health (mental health) and social challenges.

In the UK adulthood homelessness is more visible than childhood homelessness. However, most participants in this research reveal that the process of becoming homeless begins at their childhood, but becomes visible after the legal age of consent (16). Participants described long history of trouble with people in authority including parents, legal guardians and teachers. However, at the age of 16 they gain legal powers to leave children homes, foster homes, parental homes and schools, and move outside some of the childhood legal protections. Their act of defiance becomes subject to interdiction by the criminal justice system. This is reflected in number of convictions for criminal offenses some of the participants in this study had.

Participants Ruddle, David, Lee, Emily, Pat, Marco, Henry and many other participants in this study (see Table 1 ) clearly traced the beginning of their troubles with authority back at school. They all expressed the belief that had their schooling experience been more supportive, their lives would have been different. Lee explains that being in trouble with the authorities began while he was at school:

‘The school I came from a rough school, it was a main school, it consisted of A, B, C, D and The school I came from [was] a rough school, it was a main school, it consisted of A, B, C, D and E. I was in the lowest set, I was in E because of my English and maths. I was not interested, I was more interested in going outside with big lads smoking weed, bunking school. I used to bunk school inside school. I used to bunk where all cameras can catch me. They caught me and reported me back to my parents. My mum had a phone call from school asking where your son is. My mum grounded me. While my mum grounded me I had a drain pipe outside my house, I climbed down the drain pipe outside my bedroom window. I used to climb back inside. [Lee]

Lee’s stories constructed his poor education experiences as a prime mover towards the process of becoming homeless. It could be noted in Table 1 that most participants who described poor education experiences came from institutions such as foster care, children home and special school for maladjusted children. These participants made a clear connection between their experiences of poor education characterised by defiance of authorities and poor life outcomes as manifested through homelessness.

Patrick made a distinct link between his school experience and his homelessness, for example, when asked to tell his story leading up to becoming homeless, Patrick’s response was:

I did not go to school because I kept on bunking. When I was fifteen I left school because I was caught robbing. The police took me home and my mum told me you’re not going back to school again, you are now off for good. Because if you go back to school you keep on thieving, she said I keep away from them lads. I said fair enough. When I was seventeen I got run over by a car. [Patrick]

Henry traces the beginning of his troubles with authorities back at school:

[My schooling experience]… was good, I got good, well average grades, until I got myself into [a] few fights mainly for self-defence. In primary schools, I had a pretty... I had a good report card. In the start of high school, it was good and then when the fights started that gave me sort of like a... bad reputation. I remember my principal one time made me cry. Actually made me cry, but eh... I don't know how, but I remember sitting there in the office and I was crying. My sister also stuck up for me when she found out what had happened, she was on my side; but I can’t remember exactly what happened at that time. [Henry]

Emily’s story provides some clues about the series of incidents - including, delay in diagnosing her health condition, being labelled as a naughty child at school, being regularly suspended from school and consequently poor educational attainment.

Obviously, I wasn't diagnosed with ADHD till I was like 13, so like in school they used to say that's just a naughty child. … So it was like always getting suspended, excluded and all that sort of stuff. And in the end [I] went to college and the same happened there. [Emily]

The excerpt above provides intimations of what she considers to be the underlying cause of her behaviour towards the authorities. Emily suggests that had the authorities taken appropriate intervention to address her condition, her life outcomes would have been different.

Although the next participant did not construct school as being a prime mover of their trouble with authorities, their serious encounters with the criminal justice system occurred shortly after leaving school:

Well I did a bit of time at a very early age, I was only 16… I did some remand there, but then when I went to court ‘cause I'd done enough remand, I got let out and went to YMCA in Runcorn. Well, that was when I was a kid. When I was a bit older, ‘cause it was the years 2000 that I was in jail, I was just trying to get by really. I wasn’t with Karen at the time. I was living in Crewe and at the time I was taking a lot of amphetamines and was selling amphetamines as well, and I got caught and got a custodial sentence for it. But I've never been back to jail since. I came out in the year 2000 so it's like 16 years I've kept meself away from jail and I don't have any intentions of going back. [Gary]

The move from school and children social care system to criminal justice was a common pathways for many participants in this study. Some including Lee, Crewe, David, Patrick spent multiple prison sentences (see Table 1 ). Although Crewe did not make connection between his schooling experiences and his trouble with law, it could be noted that his serious encounter with criminal justice system started shortly after leaving foster care and schooling systems. As he explains:

I was put into prison at age of 17 for arson that was a cry for help to get away from the family, I came out after nine months. I have been in prison four times in my life, its not very nice, when I came out I made a promise to myself that I’m never going to go back to prison again. [Crewe]

Lee recalls his education experience. He explained:

I left school when I was fifteen… then I went off the rails. I got kidnapped for three and half months. When I came back I was just more interested in crime. When I left school I was supposed to go to college, but I went with travellers. I was just more interested in getting arrested every weekend, until my mum say right I have enough of you. I was only seventeen. I went through the hostels when I was seventeen. [Lee]

None describe the educational experience with a similar profundity to Marco:

On few occasions I came out on the corridors I would be getting battered on to my hands and knees and teachers walk pass me. There was quite often blood on the floor from my nose, would be punched on my face and be thrown on the floor. …. It was hard school, pernicious. I would go as far as saying I never felt welcome in that school, I felt like a fish out of the water, being persistently bullied did my head in. Eventually I started striking back, when I started striking back suddenly I was a bad one. My mother decided to put me in … school for maladjusted boys, everyone who been there including myself have spent time in prison. [Marco]

The trouble with authorities that was observes in participants stories in this category appear to be part of the wider adverse social challenges that the participants in this study were facing. Crewe’s description of arson as a cry for help appears to be an appropriate summation of all participants in this category.

The participants’ description of the social conditions in which were raised and their references to maladaptive behaviours which led to them becoming homeless, led us to conclude that they believe that their social condition affected their life chances: that these conditions were responsible for their low quality of social connections, poor educational attainment, insecure employment and other reduced life opportunities available to them.

The key feature that distinguish this study from comparable previous studies is that it openly acknowledges that data collection and analysis were influenced by the principles of social justice [ 28 , 30 , 31 ]. The resulting theoretical explanation therefore constitutes our interpretation of the meanings that participants ascribe to their own situations and actions in their contexts. In this study, defining homelessness within the wider socioeconomic context seemed to fit the data, and offered one interpretation of the process of becoming homeless.

While the participants’ experiences leading to becoming homeless may sound trite. What is pertinent in this study is understanding the conditions within which their behaviours occurred. The data were examined through the lens of social justice and socio-economic inequalities: we analysed the social context within which these behaviours occurred. We listened to accounts of their schooling experiences, how they were raised and their social network. The intention was not to propose a cause-and-effect association, but to suggest that interventions to mitigate homelessness should consider the social conditions within which it occurred.

Participants in this study identified substance misuse and alcohol dependency as a main cause of their homelessness. These findings are consistent with several epidemiological studies that reported a prevalence of substance misuse amongst the homeless people [ 32 , 33 , 34 , 35 , 36 ]. However, most these studies are epidemiological; and by nature epidemiological studies are the ‘gold standard’ in determining causes and effects, but do not always examine the context within which the cause and effect occur. One qualitative study that explored homelessness was a Canadian study by Watson, Crawley and Cane [ 37 ]. Participants in the Watson, et al. described ‘lack of quality social interactions and pain of addition. However, Watson et al. focus on the experiences of being homeless, rather than the life experiences leading to becoming homeless. To our knowledge the current study is one of very few that specifically examine the conditions within which homelessness occurs, looking beyond the behavioural factors. Based on the synthesis of data from previous studies, it makes sense that many interventions to mitigate homelessness focus more on tackling behavioural causes of homelessness rather than fundamental determinants of it [ 38 ]. From the public health intervention’ point of view, however, understanding the conditions within which homelessness occurs is essential, as it will encourage policymakers and providers of the services for homelessness people to devote equal attention to tackling the fundamental determinants of homelessness as is granted in dealing behavioural causes.

Participants in this study reported that they have been defiant toward people in positions of authority. For most of them this trouble began when they were at school, and came to the attention of the criminal justice system as soon as they left school at the age of 16. These findings are similar to these in the survey conducted by Williams, Poyser, and Hopkins [ 39 ] which was commissioned by the UK Ministry of Justice. This survey found that 15 % of prisoners in the sample reported being homeless before custody [ 39 ]; while three and a half percent of the general population reported having ever been homeless [ 39 ]. As the current study reveals there are three possible explanations for the increased population of homeless young people in the criminal justice system: first, at the age of 16 they gain legal powers to leave their foster homes, parents homes, and schools and move beyond some of the childhood legal protections; second, prior to the age of 16 their defiant behaviours were controlled and contained by schools and parents/legal guardians; and third, after the age of 16 their acts of defiant behaviour become subject to interdiction by the criminal justice system.

The conditions in which they were born and raised were described by some participants in this study as ‘chaotic’, abusive’, ‘neglect’, ‘pernicious’ ‘familial instability’, ‘foster care’, ‘care home’, etc. Taking these conditions, and the fact that all but one participants in this left school at or before the age of 16 signifies the importance of living conditions in educational achievement. It has been reported in previous studies that children growing up in such conditions struggle to adjust in school and present with behavioural problems, and thus, poor academic performance [ 40 ]. It has also been reported that despite these families often being known to social services, criminal justice systems and education providers, the interventions in place do little to prevent homelessness [ 40 ].

Analysis of the conditions within which participants’ homelessness occurred reveals the adverse social conditions within which they were born and raised. The conditions they described included being in an abusive environment, poor education, poor employment or unemployment, poor social connections and low social cohesion. These conditions are consistent with high index of poverty [ 37 , 41 , 42 ]. And several other studies found similar associations between poverty and homelessness [ 42 ]. For example, the study by Watson, Crowley et al. [ 37 ] found that there were extreme levels of poverty and social exclusion amongst homeless people. Contrary to previous studies that appear to construct homelessness as a major form of social exclusion, the analysis of participants’ stories in this current study revealed that the conditions they were raised under limited their capacity to engage in meaningful social interactions, thus creating social exclusion.

Homeless people describe the immediate behavioural causes of homelessness; however, this analysis revealed the social and economic conditions within which homelessness occurred. The participants’ descriptions of the social conditions in which were raised and their references to maladaptive behaviours which led to them becoming homeless, led us to conclude that they believe that their social condition affected their life chances: that these conditions were responsible for their low quality of social connections, poor educational attainment, insecure employment and other reduced life opportunities available to them.

Limitations

The conclusions drawn relate only to the social and economic context of the participants in this study, and therefore may not be generalised to the wider population; nor can they be immediately applied in a different context. It has to be acknowledged that the method of recruitment of the 26 participants generates a bias in favour of those willing to talk. The methodology used in this study (constructivist grounded theory) advocates mutual construction of knowledge, which means that the researchers’ understanding and interpretations may have had some influence on the research process as the researchers are an integral part of the data collection and analysis

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Acknowledgements

The authors wish to thank all participants in this study; without their contribution it would not have been possible to undertake the research. The authors acknowledge the contribution of Professor Paul Kingston and Professor Basma Ellahi at the proposal stage of this project. A very special thanks to Robert Whitehall, John and all the staff at the centres for homeless people for their help in creating a conducive environment for this study to take place; and to Roger Whiteley for editorial support. A very special gratitude goes to the reviewers of this paper, who will have expended considerable effort on our behalf. 

This research was funded by quality-related research (QR) funding allocation for the University of Chester.

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The datasets generated during and/or analysed during the current study are not publicly available due to ethical restriction and privacy of participant data but are available from the corresponding author on reasonable request.

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MM wrote the entire manuscript, designed the study, collected data, analysed and interpreted data, and presented the findings. AY contributed to transcribing data and manuscript editing. MG contributed to data collection, and transcribed the majority of data. All authors read and approved the final manuscript.

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Mabhala, M.A., Yohannes, A. & Griffith, M. Social conditions of becoming homelessness: qualitative analysis of life stories of homeless peoples. Int J Equity Health 16 , 150 (2017). https://doi.org/10.1186/s12939-017-0646-3

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Homelessness and the Persistence of Deprivation: Income, Employment, and Safety Net Participation

Homelessness is arguably the most extreme hardship associated with poverty in the United States, yet people experiencing homelessness are excluded from official poverty statistics and much of the extreme poverty literature. This paper provides the most detailed and accurate portrait to date of the level and persistence of material disadvantage faced by this population, including the first national estimates of income, employment, and safety net participation based on administrative data. Starting from the first large and nationally representative sample of adults recorded as sheltered and unsheltered homeless taken from the 2010 Census, we link restricted-use longitudinal tax records and administrative data on the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, Disability Insurance (DI), Supplemental Security Income (SSI), veterans’ benefits, housing assistance, and mortality. Nearly half of these adults had formal employment in the year they were observed as homeless, and nearly all either worked or were reached by at least one safety net program. Nevertheless, their incomes remained low for the decade surrounding an observed period of homelessness, suggesting that homelessness tends to arise in the context of long-term, severe deprivation rather than large and sudden losses of income. People appear to experience homelessness because they are very poor despite being connected to the labor market and safety net, with low permanent incomes leaving them vulnerable to the loss of housing when met with even modest disruptions to life circumstances.

The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applies to this release, authorization number CBDRB-FY2022-CES005-015. We thank the U.S. Census Bureau for their support, as well as John Abowd, Mark Asiala, George Carter, James Christy, Dennis Culhane, Kevin Deardorff, Conor Dougherty, Ingrid Gould Ellen, Anne Fletcher, Katie Genadek, Tatiana Homonoff, Kristin Kerns, William Koerber, Margot Kushel, Larry Locklear, Tim Marshall, Brian McKenzie, Brendan O’Flaherty, James Pugh, Trudi Renwick, Annette Riorday, Nan Roman, William Snow, Eddie Thomas, Matthew Turner, and John Voorheis for providing feedback and answering questions. We also thank participants in seminars at Yale University (Labor/Public Economics Workshop), the University of Chicago (Demography Workshop), APPAM, NTA, NBER Labor Studies, IRS/Census (Income Measurement Workshop), and the Institute for Research on Poverty. Ilina Logani and Mandana Vakil provided excellent research assistance. We appreciate the financial support of the Alfred P. Sloan Foundation, the Russell Sage Foundation, the Charles Koch Foundation, the Menard Family Foundation, and the American Enterprise Institute. Wyse thanks the National Institute on Aging for their support. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Analyzing the impact of social factors on homelessness: a Fuzzy Cognitive Map approach

Vijay k mago, hilary k morden, charles fritz, tiankuang wu, sara namazi, parastoo geranmayeh, rakhi chattopadhyay, vahid dabbaghian.

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Received 2012 Jul 25; Accepted 2013 Aug 12; Collection date 2013.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The forces which affect homelessness are complex and often interactive in nature. Social forces such as addictions, family breakdown, and mental illness are compounded by structural forces such as lack of available low-cost housing, poor economic conditions, and insufficient mental health services. Together these factors impact levels of homelessness through their dynamic relations. Historic models, which are static in nature, have only been marginally successful in capturing these relationships.

Fuzzy Logic (FL) and fuzzy cognitive maps (FCMs) are particularly suited to the modeling of complex social problems, such as homelessness, due to their inherent ability to model intricate, interactive systems often described in vague conceptual terms and then organize them into a specific, concrete form (i.e., the FCM) which can be readily understood by social scientists and others. Using FL we converted information, taken from recently published, peer reviewed articles, for a select group of factors related to homelessness and then calculated the strength of influence (weights) for pairs of factors. We then used these weighted relationships in a FCM to test the effects of increasing or decreasing individual or groups of factors. Results of these trials were explainable according to current empirical knowledge related to homelessness.

Prior graphic maps of homelessness have been of limited use due to the dynamic nature of the concepts related to homelessness. The FCM technique captures greater degrees of dynamism and complexity than static models, allowing relevant concepts to be manipulated and interacted. This, in turn, allows for a much more realistic picture of homelessness. Through network analysis of the FCM we determined that Education exerts the greatest force in the model and hence impacts the dynamism and complexity of a social problem such as homelessness.

Conclusions

The FCM built to model the complex social system of homelessness reasonably represented reality for the sample scenarios created. This confirmed that the model worked and that a search of peer reviewed, academic literature is a reasonable foundation upon which to build the model. Further, it was determined that the direction and strengths of relationships between concepts included in this map are a reasonable approximation of their action in reality. However, dynamic models are not without their limitations and must be acknowledged as inherently exploratory.

Keywords: Homelessness, Complex social system, Fuzzy logic, Fuzzy Cognitive Map, Network analysis

Homelessness

Homelessness is a complex social problem with a variety of underlying economic and social factors such as poverty, lack of affordable housing, uncertain physical and mental health, addictions, and community and family breakdown. These factors, in varying combinations, contribute to duration, frequency, and type of homelessness. To be fully homeless is to live without shelter; however, many experience partial homelessness that can include uncertain, temporary, or sub-standard shelter. Homelessness is difficult to define, thus governments struggle with uncertainty when creating and implementing policies they hope will effectively manage or eradicate this problem.

Levels of government, in countries like Canada, add to the complexity of dealing with homelessness. Being governed at three different levels, federal, provincial, and municipal, requires high levels of agreement to effectively create and administer policies. In Canada, each level of government is responsible for different facets of homelessness. The federal government, responsible for the whole of Canada, creates and administers policies and funding for aboriginal peoples (a segment of Canada’s population over-represented in homeless counts), seniors, and social housing, as well as transfers funds to the provinces to help pay for their social programs. The provincial government, responsible for needs of the provinces and territories, creates and administers policies regarding mental illness, addictions, welfare, minimum wage laws, landlord and tenant acts, and child protection services and shares responsibility with the federal government for seniors and social housing. The municipal governments, are seen as the hands or arms of the provincial government, and are technically not responsible for homelessness; however are often involved in choosing sites for social housing, supporting emergency shelters and hospital emergency wards, as well as providing support, in a variety of ways, to facilitate these initiatives. The fact that there is no comprehensive national housing strategy to co-ordinate these levels of government often leads to inadequate policies and funding that fall far short of meeting the country’s housing needs [ 1 ]. This lack of coordination towards policy and funding for homelessness has recently come to the attention of courts in Canada who have begun to make decisions which support shelter as an essential right for Canadians [ 2 ]. The UN Special Rapporteur on adequate housing in Canada has also strongly urged the federal government to commit sufficient funding to create a national housing strategy by working with the provinces and territories [ 3 ].

Metro Vancouver is one city in Canada which conducts a comprehensive homeless count every three years [ 4 ]. Counters make every effort to include in the count those considered sheltered homeless (individuals who spend nights in shelters, safe houses, transition houses, hospitals, jails, remand centres, and detox/recovery facilities) and those who are unsheltered homeless (individuals who spend their nights unsheltered on streets, in parks, or at drop-in programs). Counts are shown in Figure 1 .

Homeless count in Metro Vancouver.

It becomes apparent that if the complex and oft-times chaotic experiences such as job loss that lead to family breakdown, mental illness, and drug/alcohol addiction, which may lead to homelessness, were better understood then social policies and procedures which constitute “best practices” would be more effective in reducing and preventing homelessness [ 5 ]. Fuzzy logic and fuzzy cognitive maps are especially useful for modelling complex social problems due to their inherent ability to capture and model vague concepts and values [ 6 ]. In relationship to homelessness, syllogisms such as, “if there is a lack of affordable housing, then there will be a significant increase in homelessness” can be accurately modelled by assigning a value to the parameter based on the retrieved linguistic terms taken from existing empirical literature. In this way greater meaning, which captures and aggregates the nuances of the stressors and protective factors, is given to the existing empirical literature related to homelessness. This also allows the complex social issue to be graphically described in a manner which may be more readily understood. This, in turn, may then help social policy-makers to refine their decision-making, leading to effective changes in social policies with the goal of reducing homelessness.

Fuzzy logic (FL) is a mutli-valued logic technique that is approximate. Rather than using traditional logic theory where binary sets have a two-valued logic (i.e., true, 1, and false, 0), fuzzy variables have a truth-value between 0 and 1, allowing them to be valued between absolutely true and absolutely false. Using linguistic variables, taken from empirical literature that describes the effect each factor in a knowledge system has on the others, FL can be used to convert the effects into values between 0 and 1. Once determined, these values can then be input into a graphical representation of the system containing all factors with directed lines (edges) showing the calculated strength of the causal relationship between them. This graphical representation is known as a fuzzy cognitive map (FCM). A brief description of the techniques, with an example is presented in the subsequent subsection.

Fuzzy Cognitive Map (FCM)

The FCM is a framework used for modelling interdependence between concepts in the real-world [ 7 ]. This is achieved by graphically representing the causal reasoning relationships between vague or un-crisp concepts [ 6 , 8 ]. FCMs allow scientists to construct virtual worlds in which some of the complex and interdependent concepts of a scenario can be captured and their interactions or causal relationships modelled. Knowledge representation in these maps has an acquisition-processing trade-off. FCMs, by providing a fuzzy graph structure for systematic causal propagation and ease in processing fuzzy knowledge, are applicable in soft-knowledge domains such as the social sciences. At the core of the FCM structure are the concepts to be studied and modelled. Concepts can be understood to represent actors or the parts of the environment which have impact on some phenomenon of interest (and each other), such as those included in the simple FCM of heart disease illustrated in Figure 2 .

Example of a simple FCM to assess heart disease.

The concepts, determined empirically, which relate to heart disease in this model include: exercise (E), food habits (FH), cholesterol (C), blood pressure (BP), and body weight (BW). The links, directionally joining the concepts, represent the fuzzy causal relationships.

Concepts which have no impact on other concepts are not represented via links on the map, however are represented in the subsequent constructed adjacency matrix W and denoted, 0.

As can be seen in Figure 2 , there is no direct effect of BW on C and therefore no link is drawn between these two concepts. The weight values {−1,0,1} are used at this stage for simplicity and testing the FCM and are later refined through the application of empirical linguistic terms and modifiers processed through FL.

The use of an FCM is particularly advantageous for graphically representing the interacting relationships of concepts which appear in phenomena related to social science, political science, organizational theory, military science, and international relations [ 8 ]. The connection matrix, W , may also be defined algebraically, demonstrating the influence concepts have on one another [ 7 ].

Let us denote the i t h concepts of a system as C i . Then the value A i , of a concept C i , expresses the quantity of its corresponding physical value. The FCM converges to a steady state when:

At each step, the value A i of a concept is influenced by the values of concepts-nodes connected to it and is updated according to the following formula:

where A i ( k ) is the value of concept C i at step k, A j ( k ) is the value of concept C j at step k, W ji is the weight of the interconnection from concept C j to concept C i and f is the threshold function used to bound the transformation to a limit cycle. In this example, f ( x ) is a sign function defined in MATLAB [ 9 ] with the following functionality:

Following our heart disease example, consider: the concept, E, is active for some individual. Therefore, E =1. No information is available for all other concepts in the map. Therefore, F H =0, C =0, B W =0, and B P =0. This is expressed by a vector C 1 = (1,0,0,0,0,0). According to equations 2 and 3, the processing is listed in Table 1 .

FCM processing when excercise = 1

The right arrow indicates the threshold function operation in Equation 3. The above results demonstrate that it takes four steps for the system to converge to a stable state (limit cycle). The vector C 4 demonstrates that the increase in E eventually leads to decreases in C, BW, BP, and HD.

The FCM created for our study provides a graphical description of homelessness and facilitates increased understanding of this complex social problem. Through simulation, the usefulness of such a model is demonstrated and implications for its use in policy decision-making are explored. As shown, FCMs related to complex social problems, allow for refinement of knowledge through graphical understanding and simulations that may be useful in improving social policies with the goal of reducing homelessness.

Virtual common-sense map of homelessness

First a virtual common-sense map was built based on the researchers’ personal and historical knowledge of the factors which they perceived to affect homelessness. Using homelessness as the central hub of the map, concepts which directly or indirectly, positively or negatively affected homelessness, and each other, were linked through directed edges. Each edge was assigned a weight depending on whether the antecedent concept exerted a positive effect (+1) or a negative effect (−1) on the consequent concept (Figure 3 ). Three prototypical cases were then developed and the model was run to ensure it would function in accordance with the determined relationships prior to the actual weights on the edges being refined through a literature search for the linguistic terms.

Virtual common-sense map of homelessness.

Experimentation: Virtual common-sense map

Experimentation with the virtual common-sense model was conducted to ensure that it would perform as expected and reach a stable state after iterating prior to the input of the actual weight values. Sample cases were constructed with the goal of describing an extreme case, most likely to result in homelessness; an extreme case, least likely to result in homelessness; and a middle case, more closely representing the possibilities of the real world, in which the likelihood of homelessness would be uncertain, see Table 2 .

Summary of expected outcome, concepts activated and iteration process for three sample cases

• Case 1 : In this scenario, the protective factor of rental subsidy was incapable of preventing the negative social factors, criminal justice system involvement, addictions, and mental illness from overwhelming the model - resulting in certain homelessness.

• Case 2 : In this scenario, the protective factors of education and increased income resulted in the elimination of the need for non-government assistance and a decrease in the likelihood of criminal justice system interaction. This is a highly likely outcome given that those with higher incomes and education are better able to identify and seek help for their mental illnesses which increases the likelihood that they will avoid incarceration. However, the strength of income and education as protective factors against increasing mental illness is shown to be ineffective and the level of mental illness continues to rise. Despite the increase in mental illness, education and income will ensure an ongoing ability to provide shelter, resulting in homelessness being an extremely unlikely outcome.

• Case 3 : In this scenario, at the end of iteration 1, the effects of addiction, prior criminal justice system involvement, and family breakdown are held at bay by the protective factors of income, education and counselling. However, due to the known cumulative negative effects of addiction, social isolation increases, signalling the likelihood that, over time, there will be an increased possibility of family breakdown and greater challenges controlling the addiction resulting in the increased likelihood of crime. Iteration 2 demonstrates the actions of all the concepts present in iteration 1 continuing to exert force on the model with the addition of an increase in mental illness caused by the ongoing addiction resulting in an increasing likelihood of homelessness. As the model continues to iterate, the addictions contribute to increasing social isolation and criminal behavior resulting in a greater likelihood of family breakdown. At this point the protective factors of education, income and counselling are overwhelmed by the ongoing addictions and resulting mental illness and crime and the likelihood of homelessness rises. However, given that education and income continue to exert force, homelessness is not a certainty.

Given the fully explainable results of the model and the fact that it was able to achieve stability after iterating, it was determined that the model functioned properly, and the process of refining the concepts through the search of timely empirical literature was conducted.

Fuzzy Cognitive Map of homelessness supported by empirical studies

To refine the edge weights on the FCM, timely, empirical literature was searched. The original causal map was referred to for the paired concepts such as, education and homelessness. These linked terms were then searched using the academic search engine, Google Scholar. Numerous articles were retrieved and scanned for each pair of linked concepts using only recently published (since the year 2000), peer reviewed, empirical articles. This culminated in the capture of three linguistic statements per concept pair for use in refining the map (see Table 3 ). Linguistic statements were required to be in the antecedent - consequent form as earlier described. In the process of searching, paired concepts were refined (edges and concepts added and removed from the virtual common-sense map Figure 3 after though deliberation with research team) resulting in a final map of 14 concepts and 31 edges (Figure 4 ). To maintain the semantic consistency amongst various concepts, Oxford Canadian Dictionary [ 10 ] was followed.

Linguistic terms and the references

Fuzzy Cognitive Map with qualitative weighted edges.

To calculate the quantitative weight values for each edge, first the qualitative weight values for each of the retrieved linguistic terms was assessed. A Likert-type scale was devised to determine the qualitative weight of each linguistic term. The values, Very Low (VL), Low (L), Medium (M), High (H), and Very High (VH) were used to categorize each term. We only consider five qualitative values for the sake of simplicity. However, the scale could be less or more than five, depending on the intricacies of the system under consideration. Consensus on meaning was achieved through discussion and vote. This process resulted in a scale of ordered and ranked values for each concept pair. For example, it might be stated in one peer-reviewed study that the effect of concept A on concept B was, “profound”; whereas another article may state that the effect was, “significant”. These statements, “profound” and “significant”, would be then ranked on the Likert- type scale in reference to their absolute meaning as well as their relative meaning. Thus, “profound”, would be valued as VH and “significant” would be valued as H. In the case of disagreement or uncertainty regarding the precise meaning of the words, Oxford Dictionary Online was referenced for definitions and synonyms. A word bank was constructed during this process listing all the retrieved terms for both comparative reference and to ensure consistency in the rankings, see Table 4 . Once the different qualitative weight values were determined for each linguistic term, they were then collected into their groups of three and applied to the revised FCM.

Categorization of linguistic terms extracted from literature

Subsequent to the information from the literature review having been transferred to the FCM, the resulting map contained the concepts, the antecedent - consequent relationships indicated via edges, the weight value of each edge (five qualitative, linguistic terms - VL, L, M, H, VH), and the sign value showing the type of the influence (+ or −). Following the application of the qualitative values to the FCM the values were then converted to quantitative weight values using FL theory. Each link was first expressed as a fuzzy rule then used in the Fuzzy Inference System (FIS) to generate a crisp numeric value. For example, if the linguistic term retrieved from the literature was: “The impact of concept A is profound on concept B”. It would then be converted to: “The impact of concept A is VH on concept B”. This graded statement would then be transformed using the rule statement:

The linguistic term ON is a binary variable. VH is defined using the triangular fuzzy membership function, as shown in Figure 5 . ON denotes the presence of the concept and VH denotes the weight value (qualitatively). For simplicity sake, triangular membership functions have been used as suggested in [ 85 ]. Interested readers can find more detailed explanation on membership functions in [ 86 ].

Triangular membership function.

• Example 1: As explained in the previous section, all qualitative values assigned to the edges came from the literature review. As shown in Figure 6 , “addiction” has a positive impact on homelessness. This means that an increase in addiction in a society will lead to an increase in levels of homelessness. The three linguistic terms related to “addiction”, extracted from the literature, were converted to the fuzzy notion of rules as follows:

Impact of addiction on homelessness.

•The degree of impact was then converted from its qualitative value (M, H, VH) to its quantitative value of 0.648 using FL concepts as described in [ 87 ]. All three studies indicated that as levels of addiction increase they exert a positive effect resulting in increases in levels of homelessness. Therefore, it can be stated that addictions affect homelessness by a factor of +0.648.

• Example 2 : As shown in Figure 7 , education has a negative effect on homelessness. This means that with higher levels of education in a society there will be lower levels of homelessness. Therefore, the impact of education on homelessness is modeled as negative - increases in education lead to decreases in homelessness. All literature scanned indicates that as education rises, homelessness falls. The first study stated that the impact of education on homelessness was low , the second, medium , and the third, high . This information is captured to construct a rule base for a Fuzzy Inference System (FIS). For each edge, we constructed an individual FIS and the defuzzified value, in this case 0.5, is assigned to the edge. More information about the procedure can be found in [ 87 - 90 ].

Impact of education on homelessness.

•Similarly, each edge was given a quantitative weight by converting the qualitative values gleaned from the literature search. Once all links on the map had been fully articulated with the rankings of each of the 93 linguistic terms (three for each link), we refined the virtual FCM (shown in Figure 4 ) by substituting quantitative values for the previous qualitative values (see Figure 8 ).

Fuzzy cognitive map with calculated quantitative weights assigned to edges.

Experimentation with the weighted Fuzzy Cognitive Map

Experimentation with the weighted FCM was conducted, (see Algorithm 1), to ensure that it would perform as expected and that the map had captured the dynamics of the factors which affect levels of homelessness. We applied tanh = e 2 x − 1 e 2 x + 1 as the transformation function f of Equation 2. This choice is made as we are interested in understanding the impact of increase or decrease of initial concept values on the overall stability of the map [ 91 ].

Prototypical scenarios, similar to those used for the simplified FCM (Figure 3 ), were constructed with the goal of finding the extreme case most likely to result in homelessness, the extreme case least likely to result in homelessness and several middle cases, more closely representing the possibilities present in the real world, where levels of homelessness are less certain.

The output of each prototypical case was interpreted through knowledge gleaned during the literature search/scan and the opinion of the criminologist-researcher on the team. Each example case had a variety of concepts activated at varying levels. The models were then permitted to iterate as necessary to reach a stable state (no further movement, positive or negative, for all concepts in the model). Final iterations are reported for each model.

• Case 1: Most likely to result in homelessness. The concepts of addiction, family breakdown, government assistance, and mental illness were activated at levels considered sufficiently high to dominate the system leading to certain homelessness as shown in Table 5 . It has been empirically determined that these concepts are often found together and often precede homelessness [ 52 , 70 , 83 ]. Addiction and mental illness are often co-morbid and both commonly precede family breakdown [ 51 ]. During times of increased addiction and mental illness in society it is the usual reaction of the government to put into place policies and funding which will address these problems [ 93 ].

Simulating the result for case 1

•Tracking the effect of these concepts at strengths set to approximately 0.50, the graph initially shows that government assistance is at a lower rate and then sharply rises to address the increasing levels of addiction, mental illness, and family breakdown in the modeled society. However, it takes little time before the triple threat of addiction, mental illness and family breakdown overwhelm the system and levels of homelessness rise dramatically where they remain at a steady, high rate (indicated by the flat line at the top of the graph, Figure 9 ).

Activated concepts at levels most likely to result in homelessness with graphical representation of impact of concepts on levels of homelessness over time.

• Case 2: Least likely to result in homelessness. The concepts of addiction, education, income, family breakdown, and social network support were activated at levels considered sufficiently high to dominate the system leading to a certain outcome of no homelessness as shown in Table 6 . In this case, the protective factors of education, income, and social network support protect society from the negative effects of addiction and prevent homelessness. The link between higher levels of education and higher levels of income have been well documented [ 72 ]. Given that education prepares individuals to think creatively and to problem-solve, it is surmised that those with higher levels of education would have a greater ability to negotiate the complex rules that often are associated with government assistance. Those who are wealthy and educated are also much more likely to be capable of identifying and acquiring the services they might need, such as being able to pay for family counseling rather than being wait-listed for government supplied family counseling.

Simulating the result for case 2

•From Figure 10 , it is noted that this model shows a initial dip in levels of income and education in the first iterations as society attempts to deal with the addictions and threat to family cohesion that result from the addictions. However, very quickly, the protective factors of income, education, and social network support overwhelm the negative factors and the threat of homelessness diminishes and remains at levels close to zero (as indicated by the flat line at the bottom of Figure 10 ). Over time, the threat of family breakdown is also eliminated and income and education both rise back to their initial levels.

Activated concepts at levels least likely to result in homelessness with graphical representation of impact of concepts on levels of homelessness over time.

•This second model demonstrates the critical importance of factors such as income - which lead to health, acquisition of knowledge, better food and health care; and education - which lead to wealth and all the positive factors which wealth can purchase. Though addictions are shown as present in this modeled society, the low levels are unable to overwhelm the model. Through model testing it became apparent that levels of addiction lower than 0.30 often fail to overwhelm the positive factors, as long as social support and education are both present at fairly high levels, see Figure 10 . Much of the empirical literature support this [ 41 , 59 , 78 ]. Those with high levels of social support such as family, church, social groups, community groups, school friends and community friends are often better able to weather threats such as addictions and family breakdown.

• Case 3: Uncertain outcome of homelessness. In this model, we activated low levels of addiction and social network, high levels of education and income, and moderate levels of family breakdown as shown in Table 7 . In this case, the protective factors of education and income delay the onset of homelessness but are insufficiently strong to prevent rising levels as the model iterates. Over time, due to family breakdown and the diminishing social network support, addictions begin to rise and as addictions rise, the likelihood of homelessness rapidly increases. This model demonstrates, once again, the importance of family and social support as well as the incredibly negative effects of drug addiction, both as a cause and result of family breakdown.

Simulating the result for case 3

•As in the case of the common-sense map of homelessness (Figure 3 ), this final model (Figure 11 ), acted in a manner which was fully explainable based on information acquired during the literature search and prior knowledge of the research team. This allowed for confidence that the model was functioning as it ought to and that we had captured not only a number of the integral aspects which contribute to homelessness, but that they were functioning in the direction and strengths which approximated real-life conditions.

Activated concepts at levels most closely representing a typical real-world case with graphical representation of the impact of concepts on levels of homelessness over time.

Analysis of network concepts

The purpose of this network analysis is to compare the degree of impact each of the concepts exerts on the model. During network analysis, we varied the initial value of a single concept from 0.1 to 1 while keeping the initial values of all other concepts at a static level; except for the concept representing homelessness. After several iterations, the value of homelessness was recorded. Then, for each factor, a plot of the value of homelessness versus the initial value of the concept was recorded. Ideally, for a factor with a positive effect on homelessness, the value of homelessness should increase as the value of the factor increases, gradually converging to a positive value. Concepts which have the reverse - a negative effect on homelessness, should demonstrate a decrease in homelessness as they are increased. Concepts which have higher convergent rates should demonstrate a greater impact on levels of homelessness.

To conduct the network analysis we first set the initial values for all concepts at a level of 0.5 and checked the levels of homelessness after 5 iterations. At this level and number of iterations, the majority of the plots resulted in a straight line at a value of +1. This told us that the initial value of the factor (0.1 to 1) made no difference on levels of homelessness and, obviously, was no help to our analysis. After analyzing the map, we tried reducing the level of the initial values for all concepts as well as reducing the number of iterations. Through a gradual reduction process we found that by setting the initial concept values at 0.01 and running three iterations we were able to generate reasonable and useful plots (see Figure 12 ) which could then be compared for effects on levels of homelessness.

Comparison of the affects of individual concepts on levels of homelessness (a) shows the impact of Addiction, Criminal Justice System, Cost of housing and Social Network on Homelessness (b) highlights the impact of Education, Family Breakdown, Government Assistance and Income on Homelessness and (c) depicts the impact of Mental Illness, NGO, Poverty and Childhood hardships.

Plots can be examined in pairs or groupings so that the effect of the concepts on levels of homelessness can be compared for both intensity and speed. For example, in comparing the plots for, “Addictions”, and, “Cost of Housing”, it can be seen that they both are monotonically increasing. However, the plot for “Addictions” demonstrates a more dramatic increase, resulting in a quicker convergence to +1 than does the plot for “Cost of Housing”. Therefore it can be concluded that addictions have a greater impact on homelessness than does cost of housing.

Another way to visually analyze the impact of various factors on homelessness is through box plota (see Figure 13 ). Making the same comparison, “Addictions” to “Cost of Housing”, it can be seen that the plot of “Addictions” has a narrower median and longer lower quantile. The size of the box determines the variability of concepts, for instance, the size of the box of “Cost of Housing” is greater than size of the box of “Addictions” indicating that the impact of housing cost is more variable and hence not a strong indicator [ 94 ].

Boxplot comparison of the affects of individual concepts on levels of homelessness.

Measure of centrality

Another approach to analyze the most influential factor is through measures of centrality . There are also other measurements for analyzing an FCM, but here we focus on this property. In this subsection, we describe the results of the analysis based on two types of centrality: degree centrality and closeness centrality. Degree centrality of each node/concept, in a given weighted and directed graph, is defined as the sum of the absolute values of the weights of the outgoing and incoming edges [ 8 , 95 ]. For the node, x , of the graph G =< V , E > the degree centrality is mathematically defined as:

where w xy and w yx are the weights of the edge from x to y and the edge from y to x , respectively. Degree centrality of a graph indicates how strongly a concept node in a FCM affects other concept nodes of the graph [ 96 ].

Closeness centrality of a node is the inverse of the sum of the lengths of the shortest paths between that node and all other nodes. For the node, x , of the graph G =< V , E >, the closeness centrality is mathematically defined as:

where d xy denotes the length of the shortest path from node x to node y . Closeness centrality indicates how quickly a concept node affects other nodes of the FCM [ 96 ].

Note : For closeness centrality the distance measured between each pair of nodes is the inverse of the weight of the corresponding edge in the FCM. If there is no edge between nodes then the distance from the one node to the second node would obviously be infinite. Since the FCM is not strongly connected, the length of the shortest path for some pairs of nodes is, in fact, infinite. This then causes the closeness centrality for that node to drop to zero. For example, the length of shortest path for each node to the node, “Cost of Housing”, is infinite. This makes the centrality of all nodes to be zero. To conquer this problem, we choose a numerical value which is large enough to be considered as an infinite value. Since the distance measure between each pair of nodes is defined as the inverse of the weight between the nodes of the FCM, the greatest distance between each two nodes would be 4. This value is corresponding to the edge between “poverty” and “addiction”, whose weight is 0.25. The FCM has 14 concepts, thus each path of the FCM will, at most, have 13 edges. Therefore, the length of each path will be at most 4×13=52, which is still an overestimation of the paths in the graph. Regarding this value, we picked 100 as an large enough value. This approach is similar to the Big-M method described in operation research theories [ 97 ]. Please note that changing 100 to a greater value, may change nodes’ closeness centrality, but the order of the nodes’ closeness centrality will not change.

The result of the degree and closeness centrality computation in our FCM is displayed in Table 8 . As shown, the concept “Education” has the greatest degree centrality while the concept “Cost of Housing” has the least. This means that “Education” gives and receives the greatest direct influence on all other concepts, whereas “Cost of Housing” gives and receives the least. Closeness centrality was determined to act similarly to degree centrality in that “Education” has the greatest amount of degree centrality whereas “Cost of Housing” has the least. This means that “Education” exerts the greatest force on the map in reference to closeness centrality with changes in “Education” resulting in the most prominent changes in the other concepts. Likewise, changes in “Cost of Housing” would result in the least amount of change in all other concepts. These results are consistent with the results of the overall experiment.

Degree centrality and closeness centrality of every concept

This study demonstrates the efficacy of using FCM to graphically represent and simulate the actions and interactions present in the social, personal, and structural factors related to homelessness. The FCM is particularly suited to modeling this type of problem due to its ability to incorporate vast amounts of information, synthesizing what is known about a problem and then allowing for meaningful simulations. The FCM is particularly suitable due to its dynamic nature and ability to simulate potential policy changes and show predicted outcomes on levels of homelessness. Further, the FCM helps to identify those factors that exert the greatest impact in a complex system, in this case: affordable/appropriate housing, access to social support services for those with addictions/mental illness, family support for those with children, positive community support and rental supplements.

The problem of homelessness is really situated in factors that occur at the micro-, meso-, and macro-levels of society; future research should aim to refine the FCM by sorting factors into their appropriate levels thereby allowing differentiation between what the individual is potentially capable of controlling and that which he or she is not. This would allow for clearer identification of where government policy changes would have the greatest effect. Future refinements must also capture the effect of time. Many factors affect the system differently as time progresses (i.e., unemployment insurance) and this would help to make the system more closely replicate reality. Future maps may also wish to include factors which affect the system but which did not make it into this one such as early brain injury in childhood, sexual/physical/emotional abuse in childhood, and learning disabilities - all of which have been shown to affect levels of homelessness.

The initial construction of this map demonstrated the disparity between the empirical truth of homelessness and what the researchers had learned over a lifetime of media and social propaganda. This has implications for government policy-making and, again, demonstrates the usefulness of FCMs for describing complex social problems such as homelessness.

The FCM built to model the complex social system of homelessness reasonably represented reality for the sample scenarios. This provided evidence that FCMs are a viable alternative for conceptualizing homelessness and that a literature search of peer reviewed, academic literature is a reasonable foundation upon which to build the model. Further, it was determined that the direction and strength of relationship between concepts included in this map are a reasonable approximation of their action in reality. However, the concept, homelessness , in this study, is used as a consequent variable. In reality, many of the concepts including homelessness concept could be an antecedent concept resulting in more complex loops. The flexibility of limiting the complexity is one of the advantages of constructing and using FCMs for social science research.

Dynamic modeling does, however, have it’s limitations and this work should be regarded as purely exploratory. For one, by basing our concepts off of peer reviewed literature that was searched semi-systematically there is a possibility of not capturing all possible terms. Future work should search for papers and terms in a similar fashion as systematic or scoping reviews where inclusion and exclusion criteria are highly scrutinized and analyzed by several research team members. A second limitation concerns the interpretation of the results from the FCM. FCMs, and dynamic models more broadly, have the luxury of experimenting with problems in an environment that is encapsulated from the real-world. It should be noted that every societal issue carries with it its own contextual element that cannot always be captured by a modeling environment. Further, FCMs do not fully replicate the mirco-level interactions that may prove to be powerful in determining meso- and macro-level outcomes. Future work should aim to incorporate these influences in to their models and interpretations as best possible. Lastly, dynamic models are exploratory and we can not reasonably assume that outcomes presented in this research will be realized in the real world.

This research provides empirical support for the usefulness of this model, not only for researchers and social scientists, but for others who reside within a society where homelessness is experienced. This model is based on a limited collection of published, peer reviewed scholarly articles but despite this limitation, does justify the use of FCM techniques as a useful tool to analyze the complex situation of homelessness. The role of FCM for the purpose of modelling complex social systems has been strongly supported by this research and should continue to be utilized in future studies.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

VKM and VD conceived the idea and formulated mathematical model. TW, SN, PG, RC and VKM implemented the computational model. HKM, CF wrote the paper along with VKM. All authors critically analyzed the simulations, reviewed the manuscript, read and approved the final version.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1472-6947/13/94/prepub

Contributor Information

Vijay K Mago, Email: [email protected].

Hilary K Morden, Email: [email protected].

Charles Fritz, Email: [email protected].

Tiankuang Wu, Email: [email protected].

Sara Namazi, Email: [email protected].

Parastoo Geranmayeh, Email: [email protected].

Rakhi Chattopadhyay, Email: [email protected].

Vahid Dabbaghian, Email: [email protected].

Acknowledgements

Initial work on this research project was conducted during the IRMACS Modelling Summer School. This research was supported by the SFU CTEF MoCSSy program. We are also grateful for technical support from the IRMACS Centre, Simon Fraser University, BC.

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