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Running head: THESIS Final 1
Thesis Final
Aaron Sweazy
Concordia University of Nebraska
Applied Research in Public Health
MPH 598
Dr. Diane Neal
April 26,2015
THESIS FINAL 2
Abstract
Individuals perceived to be depressed as well as homeless were compared to see if there
was a significant relationship between the 2 cohorts. A meta-analysis was conducted to
extrapolate data to give a more precise answer to the relationship of depression and homelessness
while attempting to eliminate pure speculation on association between them. The results of the
meta-analysis showed support for the hypothesis of there being statistical significance of 50% or
more of individuals living being homeless also had depression with a .combined effect falling in
between the lower and upper confidence levels which showed no significance in there being
enough statistical data to reject the hypothesis. In this exploration of poverty’s association with
medical problems of mental health, I tested the hypothesis associated with my research question.
The null hypothesis is, Hₒ: µ≤ .50 = There is no statistically significant relationship showing less
than half the people living in poverty who have mental health issues, while the alternative
hypothesis is, Hα: µ>.50 = There is a statistically significant relationship showing less than half
the people living in poverty who have mental health issues.
Additionally I believe study design should be examined to see if any flaws existed in
reporting as there was a rather large NIa and NIc conglomeration in some of the studies, which
I feel overshadow the other studies in the meta-analysis that have fewer. I will say however, by
having a wide range of results you get a very broad range of outcomes which in turn makes me
want to dissect the study down further to see what is the main reason certain studies had a higher
follow up rate than their peers. A major issue prevalent in the studies were identifying if the
antecedent was depression causing homelessness, or homelessness causing depression. If all
studies would have been able to pinpoint the exact causation of the two cohorts it would have
been a more valuable study in terms of finding what caused the other.
THESIS FINAL 3
Thesis Draft
Introduction
Problem Statement
Individuals in lower socio-economic situations find themselves unable to seek treatment
for medical issues due to priorities such as trying to pay rent or amenities; however, by delaying
medical help, stress may ensue which in turn can result in public health issue in a given
environment (World Health Organization [WHO], n.d.). Poverty is socio-economic status as it
pertains to the variables in living conditions along with income, educational background and
employment (Iyengar, 1990, p. 19-23). Initially researchers evaluated the effects of
individualized perception of net worth on mental health, regardless of actual household income
explored regardless of how much income was attributed to a household, by taking previously
documented cases of mental health with relationships to poverty (Dombeck & Wells-Moran,
2006, p. 22). Information was classified by using variables of age and low socio-economic
status based on the standards set forth as to how to measure poverty as presented by the U.S.
Department of Commerce’s Census Bureau (2014). By taking the information available from
previous research, the idea was to infer whether or not the antecedent (poverty) had an adverse
effect on mental health. Furthermore, if the aforementioned did prove to be relevant, what
conclusions could be drawn from the research to help solidify a call to action to help circumvent
the issue of a correlation between poverty and mental health? Other mental health disparities
found to result from complications of societal pressure and poverty were also dichotomized
based on assumptions from the readings (Moser, 1996).
Purpose
THESIS DRAFT 4
Poverty is a lifestyle which continues to gain momentum in society whether individuals
want to be part of it or not. Economic dependence on government assistance and lethargic
work ethics have crippled our economy and resulted in a complacent society simply looking for
handouts. Poverty in the United States is based on income, in most of the United States it starts
off with a household of one being set at an annual income of $11,700 whereas each additional
person within a household is an extra $4,160 (The Federal Register & Department of Health and
Human Services (HHS), 2015, p. 3236 -3237). The purpose of this research was to determine if
the poverty lifestyle has an effect on the mental health diagnosis. Because, poverty was
determined to be an antecedent to medical issues associated with mental health, it has helped
pave the way to finding resolutions to eradicate poverty.
Research Questions and Associated Hypothesis
Guiding my research was the question; “Is there statistical significance of 50% or more of
individuals living in poverty having mental health issues?”
In this exploration of poverty’s association with medical problems of mental health, I
tested the hypothesis associated with my research question. The null hypothesis is, Hₒ: µ≤ .50 =
There is no statistically significant relationship showing less than half the people living in
poverty who have mental health issues, while the alternative hypothesis is, Hα: µ>.50 = There
is a statistically significant relationship showing less than half the people living in poverty who
have mental health issues.
If my hypothesis is found to be accurate, the awareness of poverty and it’s direct effect
on mental health could be taken into a more serious form and methods to find a cure for poverty
could be taken more seriously in order to in turn hopefully reduce mental health.
THESIS DRAFT 5
Potential Significance
Wellness programs could be established due to the correlation being found between
poverty and mental health. Lifestyle coaching at no cost could be provided in local
communities to help educate individuals in poverty. Specific education could help alleviate
struggles financially and in turn help to diminish the effect of mental illness. By providing a
free or sliding scale fee with educational treatment options the prevalence of poverty could
potentially decline which would allow for an independent society and growth among business
and industry.
Literature Review
Theoretical Framework
The Social Cognitive Theory (SCT) has indicated how individuals in a social setting
learn through watching and imitating those in the area around them (Denler, Wolters, & Benzon,
2014), in how it pertained to the association between poverty and mental health. An individual
that was raised in a social setting such as poverty and grew up happy, was likely to be happy
being poor as adults, on the contrary if someone grew up in an affluent household and then
moves out on their own and was surrounded by poverty, they may have adapted to living below
their means to fit in with the rest of society in a classic case of nature vs. nurture (Rowe &
Rodgers, 1997). Social support systems are significant resources in managing stressors,
supporting mental health issues (i.e.: sudden death in family) while attempting to improve the
quality of living (Unger & Wandersman, 1985).
THESIS DRAFT 6
Current Status of Mental Health/Poverty
Poverty was associated with an increased risk for psychological problems (Santiago,
Kaltman, & Miranda, 2013, February 1). Research suggested when low-income individuals do
receive evidence based mental healthcare, they responded well to treatment. A review of
treatment studies have been conducted with low-income groups and provide recommendations
for clinicians working with low-income children or adults. Low-income individuals and families
are engaged in evidence-based care saw their outcome generally be positive in nature.
Acceptance of Depression Treatments for older adults in low-income was examined
within differences of groups (Choi & Morrow-Howell, 2007, p. 423-433). Treatment Evaluation
Inventory (TEI) was conducted to see the basic mental health needs of older adults. Results were
calculated by taking mean TEI scores by treatment modality and homebound status. TEI’s were
composed by the calculations of Clinical Based Cognitive Therapy (CT), In-Home Cognitive
Bibliotherapy (CB), Antidepressant Medication (AM), and Physical Exercise Intervention (PE).
206 participants were documented with 79 being homebound status and 127 being Not
Homebound.
Potential Confounders
Meta-Analysis has a likelihood of bias due to flaws, which could be confusing. Potential
data may be skewed to inaccurately portray final results. In a mental health correlation with
poverty, determining if poverty is an antecedent to mental health is a confounding statistic that
needed to be accounted for in pre-existing mental health issues (National Institutes of Health
(NIH) & National Institute of Neurological Disorders and Stroke (NINDS), 2015). Some
participants may have the same level of poverty as another participant, but data is skewed
because Participant “A” may receive an influx of government assistance into their household,
THESIS DRAFT 7
whereas Participant “B” may have no helping resource (Muhlhausen & Tyrell, 2014).
Additional data can be skewed if participants are included in the research and make income
greater than the poverty guidelines, but are frivolous in their spending habits and live above their
means (Dividend Mantra, 2014, April 24).
Methodology
I will utilized meta-analysis study design with the idea of finding whether or not there is
a direct link connecting socio-economic status (in this case poverty), with mental health
illnesses. Meta-analysis fit for this type of research because it permitted me to save time by
bringing together multiple studies to produce an adequate sample size which in turn allowed for
a more parallel comparison to a population, which allowed me to see that a correlation between
the two actually exists. Through the utilization of Academic Search Premier’s Esbsco Host, I was
able to find articles that helped to better understand the procedural base for the methods section.
I used the terms homeless and depression while limiting studies to full text, references available,
and from the date range of 2003-2013. 6 studies were including in the final analysis with
Rosario’s A, B, and C trials (2012) making up half of the research. As indicated in Table 1 and
Figure 1, I have illustrated the method I carried out to collect the acquired studies used in the
meta-analysis.
Table 1
Inclusion and Exclusion Criteria
Inclusion Criteria Exclusion Criteria
Homeless Studies without full text reports
Depression Studies conducted after 2013 or prior to 2003
THESIS DRAFT 8
After taking into consideration the inclusion and exclusion criteria, I recognized 20
outcomes came from scholarly reviewed peer journals available with full text reports. Based on
the information I was able to extrapolate, I would take account of the information in this meta-
analysis. The total outcomes resulting from inclusion and exclusion is offered in Figure 1.
Figure 1: Results of Inclusion and Exclusion Criteria
Data Analysis Plan
I gauged the correlation of poverty and mental health via the findings from research
which has already been done. These previously conducted studies became a collective cohort by
using a meta-analysis to increase the sample size and which permitted me to draw new
inferences from them. In my research the utilization of Nominal measurements with discrete data
was utilized to identify exposures in poverty. In addition to exposure of poverty, effects of the
measures of Mental Health and Income were used with Nominal measurements using categorical
data in finding Depression/Homeless correlation. With the information gathered, I recorded the
data contained from the remaining five studies on the exposure to poverty and the effect it
attributes to mental health by placing it into MetaEasy (Kontopantelis & Reeves, 2009) data
sheet in Excel (Microsoft, 2014).
Table 2
Studies (6)
Studies excluded (14)
Studies included (20)
THESIS DRAFT 9
Effects and Exposures to be measured
Type of Variable (Effect or Exposure)
Description Level of Measurement
Exposure Poverty Nominal Effect
Effect
Measure of Mental Health
Measure of Income
Nominal
Nominal
Results
Table 3 MetaAnalysis Collection A
Data collectionStudy and Variable
Calculated and Wanted?
Reversed Effect? Method Selected Missing Data from method
Reardon, 2003: Depressive Symptoms
Yes No 7 lCI95(OR) and uCI95(OR)
Reardon, 2003: Bipolar Disorder
Yes No 7 lCI95(OR) and uCI95(OR)
Rosario, 2012a: Depressive & Anxious Symptoms
Yes No 6 OR and lCI95(OR) and uCI95(OR)
Rosario, 2012a: Depressive & Anxious Symptoms
Yes No 6 OR and lCI95(OR) and uCI95(OR)
Rosario 2012 b: Anxious Symptoms
Yes No 6 OR and lCI95(OR) and uCI95(OR)
Rosario, 2012b: Anxious Symptoms
Yes No 6 OR and lCI95(OR) and uCI95(OR)
Rosario 2012 c: Depressive Symptoms
Yes No 6 OR and lCI95(OR) and uCI95(OR)
Rosario, 2012c: Anxious
Yes No 6 OR and lCI95(OR) and
THESIS DRAFT 10
Symptoms uCI95(OR)
Shelton, 2006: Depressive Symptoms, Prescribed antidepressants, Psychiatric hospitalization, Suicidal Ideation
Yes No 2 NONE
Shelton, 2006: Prescribed antidepressants
Yes No 2 NONE
Shelton, 2006: Psychiatric hospitalization,
Yes No 2 NONE
Shelton, 2006: Suicidal Ideation
Yes No 2 NONE
van den Bree, 2009: Depressive Symptoms
Yes No 2 NONE
Excluding Shelton (2006) & van den Bree (2009) the studies in Meta Analysis Table 3
are missing both the lower and upper CI. Studies were complete based on the method they are:
Reardon (2003) is method 7 or Continuous just needing input of Nia and NCa and (P or (T and
DF)) (University of Manchester, n.d.). None of the studies showed revered effects, while on the
contrary, all of the studies were calculated and wanted.
Table 4 MetaAnalysis Collection B
Study and Variable
effect effecti95 Effectu95 Value for Error Bars
Count
Reardon, 2003: Depressive Symptoms
0.2745 0.111 0.4380 0.1635 1
Reardon, 2003: Bipolar disorder
0.2149 0.0514 0.3784 0.1635 2
Rosario, 2012a: Depressive Symptoms
0.4176 0.1038 0.7315 0.3139 6
Rosario, 2012a: Anxious
0.1351 -0.1781 0.4490 0.3139 7
THESIS DRAFT 11
SymptomsRosario,2012b: Depressive Symptoms
0.4176 0.1038 0.7315 0.3139 11
Rosario,2012b: Anxious Symptoms
0.4176 0.1038 0.7315 0.3139 12
Rosario, 2012c: Depressive Symptoms
0.1351 -0.1781 0.4490 0.3139 16
Rosario,2012c:Anxious Symptoms
0.1351 -0.1781 0.4490 0.3139 17
Shelton,2006:Depressive Symptoms
0.2626 0.2626 0.4404 0.1778 21
Shelton,2006: Prescribed Antidepressants
-0.0400 -0.0400 0.2079 0.2479 22
Shelton, 2006: Psychiatric Hospitalization
0.3302 0.3302 0.6190 0.2889 23
Shelton, 2006:Suicidal ideation
0.1096 0.1096 0.3039 0.1943 24
van den Bree, 2009: Depressive Symptoms
0.2990 0.2990 0.3551 0.0561 28
My interpretation of the data stemming from MetaAnalysis Table 4 is the effect is the
most important outcome of the MetaAnalysis, which would be agreed upon by several other
sources of scholarly influence (University of Manchester, n.d.).
Table 5 MetaAnalysis Collection C
THESIS DRAFT 12
Heterogeneity
measures
value df p-value
Cochrane Q 2.80 5 0.7304
tau2
estimate
(DL) 0.0000
tau2
estimate
(ML) 0.0000
tau2
estimate
(PL) 0.0000
I2 %0.00
H2M 0.0000
The P-Value of Cochrane Q measuring heterogeneity was found to be 0.7304 according
to MetaAnalysis Table 5. Due to the P-Value being larger than .05 I was able to utilize the full
effect model in my research.
Results
I used six studies in conducting a Meta-Analysis study. The combined effects (FE) was
to the right of the line of no effect, thus statistically there is significance within the meta-
analysis. Additionally there was a Combined Effect: 0.2866 with a 95% Confidence Interval
THESIS DRAFT 13
show a Lower Limit of 0.2370 and an Upper Limit of 0.3362. Because the LL and the UL
were both positive in nature and tor the right of the line of no effect, there was statistical
significance in the effect. Additionally, you cannot technically reject the null hypothesis
because the data lies within the range of the upper and lower limits.
Conclusions
Interpretation of the Findings
Figure 2. Forest Plot
It is possible that one of the disputes with this meta-analysis is in trying to define exactly
what mental health is. If at the present time there is not a stable definition for mental health and
the ailments linked to it, there may in turn be variances in the results measured. Looking at
van den Bree, 2009
Shelton, 2006
Rosario, 2012c
Rosario, 2012b
Rosario, 2012a
Reardon, 2003
THESIS DRAFT 14
Meta1Summary, 12 of 13 studies favor the control group (NCa) based on the plots on the right
side of the line of no effect (Reid, 2006) just as they were in the Meta 1 Model. To ensure
interpretations do not exceed the data, findings, and scope the results stemming from the meta-
analysis will only be considered when analyzing if there is a correlation between homelessness
and depression.
Limitations of the Study
One of the issues with this meta-analysis is in trying to define exactly what mental health
is. If at the present time there is not a stable definition for mental health and the ailments linked
to it, there may in turn be variances in the results measured I noticed the intervention group size
after (Nia) and the control group size after (NCa) were the same in all three trials conducted by
Rosario (2012). Upon looking closer though the Nia to NCa participants increased from 167 to
1031 (Reardon, 2003), 682 to 14,206 (Shelton, 2006), and 428 to 10,005 (van de Breen, 2009),
which had me wondering the validity of reporting in participants due to the broad range from
start to finish, the results of the meta-analysis seem to agree with previous studies in supporting a
correlation between homelessness and mental health disorders. In the text by Reardon et.al.
(2003), there was an issue in defining what homelessness meant as it seems to be a very broad
term with some aspects of homelessness being truly without a home, and some being just
displaced. Limitations furthermore existed with the failure to identify at what point in time
homelessness occurred and if it was a lingering problem or a singular time of struggle. There is
confusion as to what establishes a mental health disorder such as depression. In the research
conducted by van den Bree et.al. (2009), 38 individuals classified as homeless but living in a
group home or shelter were not included in the study, and all participants were provided
information ahead of time without knowledge of the hypothesis (blind study), with a belief of
THESIS DRAFT 15
reduced predisposition in their reporting. Self –reporting was a concern in past trauma effecting
homelessness and mental health in the study by Shelton (2006). In the studies conducted by
Rosario Et Al (2012) recruiting of individuals from gay-focused programs along with a smaller
sample size could show some limitations as well by potentially narrowing the true amount of
individuals associated with homelessness and mental health.
Recommendations
Centered on the results of the meta-analysis, I believe in moving forward the correlation
between homelessness and depression should be dispersed into separate studies so that we can
independently examine which is more likely to cause the other one to happen. Thus I would
conduct a meta-analysis of studies where individuals originally classified with mental illness are
gathered up and counted as a sample size to see how many of “X” individuals were initially
homeless and wound up with mental illness. In a second meta-analysis I would gather
individuals classified just mentally ill and then see how many wind up homeless. Additionally I
believe study design should be examined to see if any flaws existed in reporting as there was a
rather large NIa and NIc conglomeration in some of the studies, which I feel overshadow the
other studies in the meta-analysis that have fewer. I will say however, by having a wide range
of results you get a very broad range of outcomes which in turn makes me want to dissect the
study down further to see what is the main reason certain studies had a higher follow up rate than
their peers. A major issue prevalent in the studies were identifying if the antecedent was
depression causing homelessness, or homelessness causing depression. If all studies would have
been able to pinpoint the exact causation of the two cohorts it would have been a more valuable
study in terms of finding what caused the other. With there being no clear cut definition of what
constitutes mental health illnesses, I believe the range of respondents was far too broad to get a
THESIS DRAFT 16
good grasp on the data. If someone was bipolar for instance they may have potentially had a
higher likelihood of not being homeless as compared to someone who might suffer from the
calamities of being diagnosed with schizophrenia. To make this study more concise, taking an
exact form of mental health illness and examining a cluster of individuals in comparison who are
either currently taking medicine, or not taking medicine, would be valuable in figuring out not
only if a set type of mental illness is a key in homelessness causation, but if medication can help
exacerbate or cure some of the woes associated with the link in homelessness and depression.
Implications for Social Change:
Social change needs to occur among younger individuals to help circumvent mental
health issues and homelessness later on. According to van den Bree ET. Al (2009) “Among a
range of well-established risk factors, a troubled family background, school adjustment problems
and experiences of victimization were found to be the strongest predictors of homelessness in a
general population of young people.” Additionally in the study by Shelton et Al. (2009)
adversity of childhood came in to factor of becoming homeless or having mental health illness
with instances such as having an addiction problem or becoming affiliated with a gang.
Conclusion
No matter which causes the other, the end result is never one that equates to a positive
ending. We need to be able to find ways to combat homelessness or mental illness from the
beginning so it won’t carry on down the line and create worse problems eventually. Sadly a lot
of the issues stem from lack of education when exploring why we have rampant depression or
homelessness, and in many cases both (van den Bree, 2009). Education needs to be available to
THESIS DRAFT 17
help those individuals struggling succeed in life. The homelessness aspect I believe it was said
best by Munia Khan (n.d.); “Aren't we all homeless without a home inside our mind?
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