Social Support's Impact on Veteran Depression

Running head: INFLUENCE OF SOCIAL SUPPORT 1
THE INFLUENCE OF SOCIAL SUPPORT ON DEPRESSION AMONG VETERANS
Andrew Trueblood
Capstone Project
National University
August 31, 2016

INFLUENCE OF SOCIAL SUPPORT 2
Abstract
Depression is a major cause of concern in the veteran community. This study aims to analyze the
relationship between social support and depression among veterans and compare it to the non-
veteran population. It also seeks to identify the association between social support and age,
gender, race, education level, employment status, marital status, income, and activity limitations.
To achieve these objectives, 14,898 responses from participants of the Behavioral Risk Factor
Surveillance System (BRFSS) were examined, while SPSS version 24 was used to conduct
statistical testing. The relationship between social support and depression in veterans was
statistically significant but was similar to non-veterans. Education level, employment status,
marital status, income, and activity limitations were found to have a significant impact on social
support but age, gender and race did not.
.

Table of Contents
Introduction………………………………………………………………………………..4
Literature Review……………………………………………………………………….…5
Methods…………………………………………………………………………………..13
Results……………………………………………………………………………………21
Discussion………………………………………………………………………………..26
Conclusion………………………………………………………………………...……..29
References………………………………………………………………………………..30
Appendix A……………………………………………………………………………....39
Appendix B……………………………………………………………………...……….43
Appendix C………………………………………………………………………………48
Appendix D………………………………………………………………………………57

Introduction
With the influx of veterans from the recent wars in Iraq and Afghanistan the mental
health impact of military service has taken on a renewed importance. Over 2 million military
service members have served in these wars (Committee on the Assessment, 2013) and their
continuing transition into the veteran population has put increasing pressure on veteran mental
health resources. The total veteran population has expanded to over 21 million (United States
Census Bureau, 2014) providing a significant public health challenge for the country. Depression
is a significant mental health issue that many veterans face. The National Alliance on Mental
Illness (NAMI) has found that 14% of veterans are diagnosed with depression. However, they
also suggest that depression is under-diagnosed (NAMI, 2009). The Department of Veterans
Affairs’ (VA) research estimated one out of three veterans being treated at primary care locations
have some symptoms of depression with one out of five showing serious symptoms (Health
Service Research and Development Service, 2008, p. 1-4). According to the VA, depression is
the second most prevalent and expensive illness that the VA health system faces, using 14.3% of
all VA healthcare spending (Office of Research and Development, 2015). The two year cost of
treating a single veteran with major depression is estimated between $15,461 to $25,757
(Tanielian and Jaycox, 2008, p. xxiii). The societal impact of depression cannot simply be
measured by costs of treatment. Lost productivity, substance abuse, suicide ideation,
unemployment and family instability can all be caused or exacerbated by depression (Kessler,
2011). To combat this, the underlying risk factors of depression have been studied to create
effective interventions. One such risk factor is perceived social support.
Social support is an important aspect of the transition from the military to civilian life.
The civilian-military divide can provide challenges for veterans. For example, the VA’s Mental

Health Service (n.d.) identified differences between the communal culture of the military and the
highly individualistic culture in the civilian United States. They also highlighted the fact that the
veteran is leaving an already established community for one that the veteran will have to help
create. These challenges can impact the perceived social support of the transitioning veteran.
Even after integrating into the civilian population social support remains important for mental
health. World War II veterans still recognized social support as an important coping mechanism
throughout their lives even fifty years after the war (Demers, 2011). Thus, to better understand
depression in the veteran population it is important to understand the influence of social support.
Literature Review
Depression
Depression is a major public health issue in the United States. The National Institute of
Health (2015) estimated 15.7 million American adults have at least one major depressive episode
in the past year. Depression also appears to be on the rise, and the increase of depression or
depression related symptoms has been found in multiple studies (Andrade et al., 2003; Kessler et
al., 2007; Twenge, 2015). Interestingly, higher rates of depression are found in countries with
higher GDPs. This may be due to modern culture or the individualistic nature of many capitalist
societies. The focus on extrinsic goals and increased materiel expectations may be having a
negative impact on mental health (Hidaka, 2012; Twenge, 2015). Social support may be
overlooked in modern society as an important part of mental health.
Perceived and received social support can both influence depression. While research on
received social support and depression has been mixed (Bolger & Amarel, 2007; Uchino, 2009)
perceived social support has been consistently shown to improve mental health (Melrose, Brown,
& Wood, 2015). Also, that received and perceived social support have been found to be

unrelated (Smith, Benight, & Cieslak, 2013). As depression rates have risen in the general
population over the past century the individualistic and competitive society lacking in social
support has been identified as one possible cause (Hidaka, 2012). However difficult social
support is to find in modern society the perceived social support that individuals receive is an
important buffer from onset of depression.
Depression, PTSD, & TBI
Previous research has looked at the effects of military service on the mental health of the
service members. The stressful nature and possible traumatic experiences involved in combat
deployments contribute to a higher risk of developing mental health conditions (Hoglund &
Schwartz, 2014; Wells et al., 2010). This has caused veterans to have a higher prevalence of
depression than their civilian counterparts (Hoglund & Schwartz, 2014, p. 23). However, other
adverse mental health conditions can also be caused by combat deployments. Many veterans
have been diagnosed with post-traumatic stress disorder (PTSD). Depression may appear in
veterans comorbid with PTSD (Erickson, 2001; Iverson et al., 2005; Seal, Bertenthal, Miner,
Sen, & Marmar, 2007). A study of VA health care data found 56% of veterans who were
diagnosed with a mental health condition had two or more distinct diagnoses (Seal, Bertenthal,
Miner, Sen, & Marmar, 2007). Studies of different veteran population have found opposite
results whether PTSD or depression is more prevalent. A study at Veterans Health
Administration (VHA) facilities found that 17.4% of returning Operation Enduring Freedom
(OEF)/Operation Iraqi Freedom (OIF) veterans received a depression diagnosis compared to
21.8% with a PTSD diagnosis (Seal et al., 2009). However, a study of British veterans found
depression to occur more frequently than PTSD (Iverson et al., 2005, p.483). Another condition
linked to depression is traumatic brain injury (TBI). TBI has been associated with an increased

risk of depression (Morissette et al., 2011; Carlson et al., 2011; Hoge et al., 2008; Vasterling,
Verfaellie, & Sullivan, 2009). A study of OIF veterans found that those who sustained a TBI had
a rate of depression of 22.9% compared to 6.6% who did not have a TBI (Hoge et al., 2008).
Combat deployments are a major risk factor for veterans developing depression or other
conditions that can lead to depression.
Perceived social support can impact depression in relation to PTSD and TBI. Social
support decreases the risk of PTSD (Duax, Bohnert, Rauch, & Defever, 2014). Having PTSD can
cause withdrawal from social support structures causing the onset of depression or making it
worse. Therefore, the impact of social support in lessening the frequency or severity of PTSD
will also positively impact depression in those veterans. The depression associated with TBI can
be caused by the traumatic event associated with sustaining the injury, dealing with the lasting
injury, or changes to the brain itself (Osborn, Mathias, & Fairweather-Schmidt, 2014). Perceived
social support helps veterans manage this injury and lessen the impact of any comorbid diagnosis
or depression. Perceived social support helps to lessen the likelihood of PTSD and the
management of TBI thus decreasing the risk of depression.
Female Veterans
Female veterans face specific challenges that may lead to depression that many of their
male counterparts do not. According to the National Defense Research Institute (2014) 5% of
female service members are victims of sexual assault annually. The trauma experienced during
sexual assault leads to an increased risk of depression (Au et al., 2013). Furthermore, female
military personnel experience sexual harassment at a rate of 22% annually (National Defense
Research Institute, 2014), while 47% of women experienced gender discrimination (Defense
Manpower Data Center, 2013). These three factors place additional stressors on female service

members that can contribute to adverse mental health conditions including depression (Street,
Vogt, & Dutra, 2009, p. 689-690). Wells et al. (2010) found that female veterans experience
new-onset depression at higher rates than men whether they experienced combat (5.7% vs
15.7%), did not deploy (3.9% vs 7.7%), or deployed but did not experience combat (2.3% and
5.1%). This could be explained by deployed women’s less perceived support from their peers
and superiors in their unit (Street, Vogt, & Dutra, 2009, p. 690; Kanesarajah, Waller, Zheng, &
Dobson, 2015) Lacking social support makes female veterans more susceptible to depression as
this support can be critical to preventing its onset. This lack of social support can also extend to
the home front. Until 2016 women were not allowed in direct combat jobs. This has led to some
in the public to not view women as real veterans even though they may have experienced combat
or dealt with the aftermath in support units. The lack of recognition can cause female veterans to
feel unsupported and marginalized. Therefore, returning home can become more stressful and
contribute to depression (Street, Vogt, & Dutra, 2009, p. 691). Thus, female veterans face unique
obstacles that can help contribute to the increased prevalence of depression.
Unit Cohesion
There are multiple factors that veterans face that can mitigate the impact of depression.
Unit cohesion has been researched as a possible mitigating factor for the onset of depression. In a
study of US Marines, unit cohesion was found to moderate the negative impact of combat
exposure on developing depression (Armistead-Jehle, Johnston, Wade, & Ecklund, 2011).
Research done with US Air Fore pararescuemen and Sri Lankan Navy special forces found
similar results where unit cohesion lessened depression severity and negative mental health
conditions (Armstrong, Bryan, Stephenson, Bryan, & Morrow, 2015; Hanwella & Silva, 2012).
This may also explain the better mental health of special forces units compared to regular units

and regular units compared to reserve units even though special forces experience more combat
than regular units or reserve units. (Hanwella & Silva, 2012). However, a study by Breslau,
Setodji, and Vaughan (2016) found no relationship between unit cohesion and depression. Thus,
unit cohesion may have a positive impact on depression but there are questions on the
effectiveness.
Perceived social support is an important aspect in unit cohesion. Without it unit cohesion
will likely not last long service members will not get the coping or stress reduction benefits
(Armistead-Jehle, Johnston, Wade, & Ecklund, 2011). This will leave them more susceptible to
depression. By fostering coping mechanisms to deal with the stress of combat, perceived social
support from the service member’s unit can help prevent or lessen the onset of depression.
Moral Injury and Meaning Making
Moral injury is another area of study in how military service can impact mental health.
Moral injury, the “damage done to an individual’s core morality or moral worldview as a result
of a stressful or traumatic life event” (Yan, 2016), has been proposed by researchers as an
outcome of combat deployments. These researchers have found that veterans with a moral injury
are more likely to suffer from depression (Yan, 2016; Currier, Holland, & Malott, 2015;
Frankfurt & Frazier, 2016). Veterans that are unable to incorporate the stressful or traumatic
events during combat into their moral framework are likely to struggle with depression along
with other mental health conditions. Meaning making can be used to counter moral injury. Being
able to give the traumatic events a meaning in an individual’s worldview can lessen the impact of
moral injuries (Currier, Holland, & Malott, 2015) Social support, especially from their unit, can
help with meaning making (Pietrzak et al., 2010). The social support from the unit can help the
veteran understand what happened on a deployment and incorporate it into their worldview.

Moral injury is a hazard that veterans face but by creating a meaning out of the events they
participated in and witnessed they can mitigate its impact.
International Veterans
Veterans from other nations face many of the same struggles as American veterans but
there have been noted differences. British veterans of the Iraq war were found to have similar
rates of depression as American veterans in a study by Iverson et al. (2009). However, sailors in
the Sri Lankan Navy had fewer mental health problems than British or American veterans
(Hanwella & Silva, 2012). The differences between the conflicts faced by British and American
servicemen and Sri Lankan servicemen can help explain the difference as the conflict in Sri
Lanka is in their own country while British and American forces travel far away from home. In a
study of former child soldiers in Nepal it was found that the child soldiers had higher rates of
depression than civilian children even when controlling for trauma (Kohrt et al., 2008). This
suggests that the depression faced by the child soldiers in Nepal may not have been solely based
on the traumatic experiences they faced but also by social factors they encountered returning to
civilian life. The difficult societal situation that the child soldiers faced may have been similar to
the lack of support many Vietnam veterans faced upon their return to the United States. Vietnam
veterans have been found to have higher rates of depression than US veterans from other wars
(Villa, Harada, Washington, & Damron-Rodriguez, 2002; Gould, Rideaux, Spira, & Beaudreau,
2015). While the high levels of societal support for the Sri Lankan servicemen can help explain
the lower levels of mental health problems the lack of social support may explain the increased
levels of depression in reintegrating child soldiers and Vietnam veterans.
Transition and Reintegration
Transitioning home after a deployment or into civilian life after the military may be a

cause of stress and depression for veterans. Many mental health problems can increase or appear
120 days or more after coming home from deployment (Bliese, Wright, Adler, Thomas, & Hoge,
2007). This transitional time can be stressful for veterans as they attempt to reintegrate into their
families and society while also losing some of the closeness they previously had with their
military colleagues. The feeling that non-veterans do not understand the experience of veterans
can also have an isolating effect (Hinojosa &Hinojosa, 2011). Furthermore, reintegration can be
complicated as veterans have to navigate family, employment, and social change (Kukla,
Rattray, & Salyers, 2015). The stress that reintegration brings can exacerbate mental health
conditions. However, having a support system involving both former colleagues and civilian
family and friends in place can help the veteran transition (Hinojosa & Hinojosa, 2011; Duax,
Bohnert, Rauch, & Defever, 2014). Social support and its benefit in reintegration helps explain
the lower negative mental health risk in Sri Lankan sailors (Hanwella & Silva, 2012) and the
lack of social support has led to the increased levels of depression in child soldiers attempting to
reintegrate in Nepal and Sierra Leone (Kohrt et al., 2008; Betancourt, Agnew-Blais, Gilman,
Williams, & Ellis, 2010) as well as Vietnam veterans in the United States (Gould, Rideaux,
Spira, & Beaudreau, 2015). The period of transition from deployment or military service and the
reintegration into civilian life is important for the mental health of veterans. As the transition
home from deployment or into the civilian world is inherently stressful perceived social support
is important for the mental health of veterans.
Treatment
Veterans who need professional help to address their mental health issues often do not get
the treatment they need. Many veterans do not seek to utilize the treatment options available to
them. Studies of OEF/OIF veterans found that only one-third to half of those who screened

positive for PTSD or major depression received any mental health care (Elbogen et al., 2013;
Vogt, Fox, & Di Leone, 2014). There are many reasons that veterans do not seek treatment for
depression. The type of treatments available can cause veterans to not seek treatment or
discontinue the treatment before it is finished (Davis, Deen, Fortney, Sullivan, & Hudson, 2014;
Vogt, Fox, & Di Leone, 2014). For example, some veterans do not want to take medication so
they will avoid or stop treatment if that is the only option available to them. Also, negative
beliefs about mental health treatment, not wanting to appear weak, and fear of being labelled as
having a mental illness have been identified as some reasons veterans may not seek treatment
(Vogt, Fox, & Di Leone, 2014). Many veterans do not receive the help they need for depression
and working to create treatments that are effective and that veterans are willing to participate in
is an important step.
Time
The passage of time from traumatic events and age has an impact on depression. As
veterans get older and more time passes from their wartime experience how they view it will be
impacted by their life back home. Hunt and Robbins (2001) found that fifty years after the war,
war related mental issues were reemerging for many veterans. While masking symptoms in
middle age is normal after retirement the impact of traumatic experiences may come back. The
nature of retirement, more time, reflecting on one’s life, loss of structure, or the death of friends
and family can impact the reemergence of mental health issues. While World War II veterans
provide a possible glimpse into the future for younger veterans, Gulf War veterans provide
insight into what the next decades could possibly look like for OEF/OIF veterans. Researchers
found that the rates of depression seen five years after the war dropped by ten years after the war
(Black et al., 2004). This may be part of what Hunt and Robbins (2001) explained in that

masking symptoms is normal in middle age. Gulf War veterans may feel fully reintegrated into
society and have social support systems to help them that World War II veterans are losing as
they age. However, age and time may play a role but the social support that veterans feel when
returning home may also play a role. Vietnam veterans constantly show higher levels of
depression than veterans both older and younger (Villa, Harada, Washington, & Damron-
Rodriguez, 2002; Gould, Rideaux, Spira, & Beaudreau, 2015). Thus, societal support of veterans
and the particular war they fought in may also play a role in depression as veterans age.
As depression is a major chronic condition in the United States and has been shown to
occur more frequently in veterans it is important to understand the unique causes and mitigating
factors related to depression among veterans. By examining how perceived social support
interacts with depression among veterans this study seeks to build on the knowledge of the
relationship between depression and veterans.
Methods
Sample
This research will be conducted using Behavioral Risk Factor Surveillance System
(BRFSS) survey. The BRFSS survey population is national, including all 50 states, Puerto Rico,
the District of Columbia, Guam, Federated States of Micronesia, Palau, and American Samoa.
However, for this study only individuals who responded to the questions: “Have you ever served
on active duty in the United States Armed Forces, either in the regular military or in a National
Guard or military reserve unit?” (Centers for Disease Control and Prevention [CDC], 2015b).
Since the second question was an optional question for the states it was not required to be asked.
Only participants from Minnesota were asked this question, limiting the sample for this research
to only include individuals from Minnesota (CDC, 2015c).

BRFSS uses telephone numbers to collect data. The sample record is one telephone
number selected randomly by the system. The CDC requires all participating states and
territories to ensure that their sample records are representative of their population. For the 2014
data collected, the CDC reported that all states and territories have met this requirement. A
simple random sample was used by Guam and Puerto Rico while the rest of the participating
entities used a disproportionate stratified sample (DSS) for landline telephone numbers.
The entities using DSS split numbers into two strata. The two strata are high-density and
medium-density. Within both strata are telephone numbers expected to belong to households.
Numbers are split into the two strata depending on the amount of household numbers in their
hundred block (set of 100 telephone numbers with same area code + first 5 numbers). The
numbers in each stratum are each sampled to create a probability sample of all the households in
the area.
For cellular phones random sampling is used. For the BRFSS survey the vendor,
Telecordia, was used to provide a database of telephone exchanges and banks. To randomly
select cellular telephone numbers to call an interval is created. This interval is the calculated by
taking the population of telephone numbers in the banks and dividing it by the required sample
size. One telephone number is selected per bank. The population for those reached by cellular
phone is the same as the landline except they receive at least 90% of their calls on their mobile
device (CDC, 2015a).
Data Collection
Interview. As mentioned above the BRFSS survey is conducted by telephone. The
Computer Assisted Telephone Interview (CATI) system is used in conjunction with Ci3
WinCATI to aide in the collection process. The survey consists of core questions from the CDC

with the possibility of states adding their own supplemental questions. CATI and Ci3 WinCATI
provide assistance with programming questions and questionnaire scripting for state added
questions. The interview with core questions provided by the CDC takes around 18 minutes to
complete. The additional state questions usually increase the completion time by 5 to 10 minutes.
The survey is conducted during day and evening hours, during each month, and conducted seven
days a week.
Interviewers collect the data with specific training regarding the BRFSS survey.
According to BRFSS regulations, the interviewers are required to be evaluated. Monitors can
listen to interviewer only or listen to both the interviewer and interviewee in a remote location
(CDC, 2014a).
Questionnaire. The CDC takes great care in developing the BRFSS survey. In order to
provide quality data, the questionnaire includes established questions from the National Health
Interview Survey and the National Health and Nutrition Examination Survey. The rest of the
questions are developed and must go through cognitive testing before their inclusion in the
survey. By closely monitoring the quality of the questions the BRFSS survey produces high
quality data.
The creation of the questionnaire is broken into three parts. The quality controls
described above pertain only to two of the three. The first part is the core component. This is
required to be asked by every entity. These questions are asked yearly or alternated to provide
comparable information between different years. The core questions include demographic
information and questions about health conditions, behaviors, and preconceptions. The second
part is the optional BRFSS module. There were 19 optional modules for the 2014 BRFSS survey.
These modules include questions on specific topics that states and territories can include in their

BRFSS survey. The third part is questions developed by the state or territory. The CDC does not
evaluate information collected in this part and the they do not develop the questions (CDC,
2014a).
Ethical Considerations. The CDC takes ethical considerations into account when
conducting the BRFSS survey. For example, to help protect confidentiality certain variables that
could lead to individuals being identified were removed. This includes specific geographic
locations and subjects who had reported ages over 80. This allows respondents to remain
anonymous and protect their privacy. Furthermore, BRFSS limits its respondents to non-
institutionalized individuals. This removes the risk of adverse ethical repercussions, such as
coercion, that could arise by including institutionalized individuals. In addition, the interviewers
employed to conduct the survey are monitored thus helping to prevent any unethical behavior by
individual interviewers. These examples show that the CDC has considered ethical questions
when designing and conducting the survey (CDC, 2014a).
Data Analysis
The data in this research study will be analyzed using SPSS version 24. The table below
shows the variables that will be used in the research study.

Variables
Questions Possible Answers SPSS
Variable
Name
Have you ever servedon active duty in the
United States Armed Forces, either in the
regular military or in a National Guard or
military reserve unit? (Active duty does not
include training for the Reserves orNational
Guard, but DOES include activation, for
example, for the Persian Gulf War.)
 Yes
 No
 Don’t know/Not sure
 Refused
VETERAN3
(Ever told) you that you have a depressive
disorder, including depression, major
depression, dysthymia, or minor depression?
 Yes
 No
 Refused
ADDEPEV2
How often do you get the social and
emotional support you need?
 Always
 Usually
 Sometimes
 Rarely
 Never
 Refused
EMTSUPRT
Are you: (marital status)?  Married
 Divorced
 Widowed
 Separated
 Never Married
 Member of an
unmarried couple
 Refused
MARITAL
Indicate sex of respondent  Male
 Female
SEX
Are you currently…?  Employed for wages
 Self-employed
 Out of work for 1 year
or more
 Out of work for less
than 1 year
 A homemaker
 A student
 Retired
 Unable to work
 Refused
EMPLOY1

How do other people usually classify you in
this country? Would you say White, Black or
African American, Hispanic or Latino,
Asian, Native Hawaiian or Other Pacific
Islander, American Indian or Alaska Native,
or some other group?
 White
 Black or African
American
 Hispanic or Latino
 Asian
 Native Hawaiian or
other Pacific Islander
 American Indian or
Alaskan Native
 Some other group
 Refused
RRCLASS2
What is the highest grade or year of school
you completed
 Never attended school
or only kindergarten
 Grades 1 through 8
(Elementary)
 Grades 9 through 11
(Some high school)
 Grade 12 or GED (High
school graduate)
 College 1 year to 3 years
(Some college or
technical school)
 College 4 years or more
(College graduate)
 Refused
EDUCA
Are you limited in any way in any activities
because of physical, mental, or emotional
problems?
 Yes
 No
 Refused
QLACTLM2
Is your annual household income from all
sources:
 Less than $10,000
 $75,000 or more
 Refused
INCOME2
(CDC, 2015b)

Hypothesis
To research depression among veterans the following questions will be examined: How
does perceived social support impact depression among veterans? Is there a difference in the
impact of social support between veterans and non-veterans? Does age, gender, employment,
education, income, or limited activity influence perceived social support and depression?
To answer the research questions, a secondary data analysis will be conducted using the
BRFSS survey conducted by the CDC. Previous research in the field of depression created
expectations for the results of this study leading to the development of the following hypotheses.
Null hypotheses: Social support will have no impact (relationship) on depression among
veterans.
There will be no difference in the impact of social support and depression
between veterans and non-veterans.
Age, gender, employment, education, race, marital status, income, and limited
activity will have no impact on perceived social support and depression.
Research hypotheses: The perceived social support veterans receive significantly changes
depression among veterans.
There is a difference on the impact of social support and depression
between veterans and non-veterans.
Age, gender, employment, education, race, marital status, income and

limited activity are significantly associated with perceived social support
and depression.
Data Analysis Plan
To test these hypotheses a plan was developed using SPSS to conduct statistical tests on
the data. First, the descriptive statistics were used to observe the demographics of the sample
population. Also, the sample was divided into veterans and non-veterans for the demographics of
each group to be observed. To conduct statistical tests some categories of variables have been
combined. For race all non-white responses have been combined into one category. The no
school, elementary school, and some high school categories for the education level variable have
been combined. Also, for the employment status variable the categories out of work for more
than a year, out of work for less than a year, students, and homemakers have been combined.
Lastly, the divorced and separated responses have been combined for the marital status variable
and those making less than $10,000 and those making $10,000-$15,000 have been combined in
the income variable.
Next, to test the impact of social support on depression in veterans a chi-square test was
run. The adjusted residual for each cell in the cross tabulation was used to calculate the p-value
and find which cells were statistically significant. Also, a logistic regression was used to
calculate the odds associated with social support and depression. This process was also done for
non-veterans to compare to the veteran sample. To test which variables influenced social support
among veterans, chi square tests were also run, testing education level, employment status,
marital status, race, gender, and physical activity limitations. Adjusted residuals were also used
to find which responses in these variables was statistically significant. Also, to find the impact of
age on social support an ANOVA will be analyzed. Finally, an ordinal regression was used to

calculate the odds ratios to determine the independent variables impact on social support in
veterans.
Results
Demographics
The majority of participants were female (54.2%), white (91.6%), have at least some
college education (71.3%), and are currently employed (51.5%) (Appendix A). The average age
of respondents for this study was 53 (however, ages above 80 were all recorded as 80). Twelve
percent of the sample are veterans and there are differences between the demographics of
veterans and non-veterans. Veterans are older, more likely to be male, and retired. Veterans in
the sample are less likely than non-veterans to have been told they have a depressive disorder.
While veterans are also more likely to respond that they always get the social support they need
they are also more likely to respond rarely or never.
Bivariate Analysis
Impact of Social Support on Depression. A chi-square test to determine if social
support has an impact on depression among veterans showed that there is a statistically
significant relationship (𝜒2
= 84.647, 𝑑𝑓 = 4, p.0001) (Appendix B). The strength of the
relationship was tested using Cramer’s V finding a moderate impact (0.222). By using the
adjusted residual the responses always (p.0001), sometimes (p.0001), and rarely (p.001)
were shown to be significant in determining if a veteran would be diagnosed with depression.
The logistic regression showed that social support explained 6.8% (Nagelkerke 𝑅2
) of the
variance. Veterans responding rarely were 3.261 (CI: 1.718-6.192) times more likely to have
depression than those responding always, while veterans responding never were 2.775 (CI:
1.252-6.151) times more likely. These two responses were both significant at the p.001 and

p.05 level respectively.
To find if there is a difference in how social support impacts veterans and non-veterans in
relation to depression a chi-square test was used to establish if there is an association between
social support and depression in non-veterans (Appendix B). The chi-square test was statistically
significant (𝜒2
= 562.911, 𝑑𝑓 = 4, p.0001) and Cramer’s V also found a moderate impact
(0.209). The responses always (p.0001), sometimes (p.0001), and rarely (p.0001) were again
significant in determining if someone would be diagnosed with depression but the response
usually (p.0001) was also significant. The logistic regression showed that veterans responding
sometimes, rarely, and never were statistically significant at the p.001 level. While veterans
responding sometimes had an odds ratio of 1.827 (CI: 1.302-2.564), the rarely and never
response had higher odds ratios of 3.577 (CI: 2.513-5.091) and 5.068 (3.356-7.653), respectively.
The model also explained 6.3% (Nagelkerke 𝑅2
) of the variance.
Variables Influencing Social Support for Veterans. Chi square tests were run to study
how various variables influenced social support among veterans (Appendix C). Education level
(𝜒2
= 39.957, 𝑑𝑓 = 12, p.0001) is statistically significant but has a weak correlation (Cramer’s
V=.088). Similar results were found for employment (𝜒2
= 63.116, 𝑑𝑓 = 16, p.0001, Cramer’s
V=.096), marital status (𝜒2
= 62.177, 𝑑𝑓 = 16, p.0001, Cramer’s V=.095), income (𝜒2
=
90.241, 𝑑𝑓 = 24, p.0001, Cramer’s V=.121), and physical activity limitations (𝜒2
=
24.141, 𝑑𝑓 = 4, p.0001, Cramer’s V=.119). For education, using the adjusted residual, having
a high school diploma (p.0001) had a significant relationship with the response never.
Employment had significant relationships with those unable to work and the responses always
(p.001) and rarely (p.002). Also, marital status had significant responses for married and
divorced with the responses always (married, p.0001; divorced, p.0001), sometimes (married,

p.0001; divorced, p.0005) , and rarely (married, p.002; divorced, p.0005) while never
married was significant for the response always (p.0005). Furthermore, income was significant
at veterans making $15,000-$20,000 and the responses always (p.002) and sometimes (p.001).
Veterans making $20,000-$25,000 had a significant relationship when the response was rarely
(p.0001). In addition, physical activity limitation was significant with the response always
(p.0001). However, gender (𝜒2
= 5.952, 𝑑𝑓 = 4, p=.203) and race (𝜒2
= 5.671, 𝑑𝑓 =
4, p=.225) do not have a statistically significant association with social support. To test the
impact of age on social support an ANOVA was conducted and the results were not significant
(p=.774).
Multivariate Analysis
The ordinal regression analyzing the impact of activity limitation, income, education
level, employment status, and marital status on social support found variables in activity
limitation, income, and employment to be significant (Appendix D). Respondents answering yes
to being limited in any way in any activities because of physical, mental, or emotional problems
was significant. They were 1.4 (CI: 1.105-1.775) times more likely to never get the social
support they need than respondents answering no. In addition, veterans making $15,000 -$20,000
and $20,000-$25,000 were almost twice as likely (OR:1.791, 1.856; CI: 1.097-2.924, 1.220-
2.822) to never get the social support they need as the those making over $75,000. Employment
status also had two significant variables. Employed (OR: .555; CI: .334-.924) and retired (OR:
.491; CI: .303, .795) veterans had lower odds of never getting the social support they need.
Veterans who have never been married and those who were divorced were more likely than
veterans who are part of an unmarried couple to never get the social support they need but the
results were not significant.

Table 1
Odds Ratios
Population Odds
Ratio
95% Confidence
Interval
Limited physical
activity
Yes n%
425 (27.7%)
1.400a [1.105, 1.775]
No 1,112 (72.3%) Ref Ref
Annual income Less than $15,000 69 (4.5%) .625 [.346, 1.128]
$15,000 to less than
$20,000
85 (5.5%) 1.791b [1.097, 2.924]
$25,000
132 (8.6%) 1.856b [1.220, 2.822]
$35,000
197 (12.8%) 1.313 [.911, 1.893]
$50,000
293 (19.1%) 1.165 [.847, 1.603]
$75,000
301 (19.6%) 1.043 [.764, 1.426]
$75,000 or more 460 (29.9%) Ref Ref
Education Elementary- some high
school
56 (3.6%) 1.447 [.830, 2.521]
High school graduate 409(26.6%) 1.054 [.801, 1.386]
Some college 545 (35.5%) .964 [.751, 1.237]
College graduate 527(34.3%) Ref Ref
Employment status Employed 564 (36.7%) .555c [.334, .924]
Self-employed 116 (7.5%) .891 [.497, 1.597]
Out of work 59 (3.8%) .855 [.448, 1.631]
a p.01
b p.05

Retired 723 (47.0%) .491b [.303, .795]
Unable to work 75 (4.9%) Ref Ref
Marital status Married 1,015 (66.0%) 1.008 [.419, 2.426]
Divorced/ Separated 229 (14.9%) 1.799 [.730, 4.436]
Widowed 142 (9.2%) 1.081 [.425, 2.753]
Never married 130 (8.5%) 1.960 [.779, 4.930]
Unmarried couple 21 (1.4%) Ref Ref

Discussion
Social Support and Depressionin Veterans
This study sought to examine the effect of social support on depression among veterans.
The perceived social support that veterans received has a statistically significant relationship
with being diagnosed with depression. The response always, to getting the social support they
need was significant in reducing the number of depression diagnoses in veterans. The responses
sometimes and rarely had the opposite effect, increasing the likelihood of a depression diagnosis.
These results are consistent with Melrose, Brown, & Wood’s (2015) finding that higher
perceived social support has a positive impact on mental health. However, social support only
explained 6.8% of the variance of being diagnosed with depression. Depression has many causes
and other factors may play a larger role influencing it than social support.
Social Support and Depressionin Veterans and Non-Veterans
Contrary to expectations veteran status did not impact the effect of social support on
depression. Non-veterans had a similar positive relationship between greater social support and
less depression diagnoses. Those answering rarely to getting the social support they need in both
groups were more than three times as likely to have a depression diagnosis. However, for non-
veterans were over 5 times more likely to have a depression diagnosis when responding never
compared to 2.8 times more likely for veterans. Thus, there is not a larger impact of the effect of
social support on depression among veterans and in fact in some instances non-veterans appear
to be more greatly impacted. Some studies have shown similar rates in depression among
veterans and non-veterans (Black et al., 2004; Gould, Rideaux, Spira, & Beaudreau, 2015). Black
et al. (2004) found that 10 years after the Gulf War, veterans’ depression decreased to a similar
rate as the civilian population. While veterans may feel isolated and lacking social support

because of a lack of understanding among the civilian population (Hinojosa &Hinojosa, 2011)
this may be replaced by veterans groups and organizations, providing veterans the social support
they lost. After leaving the military veterans face a challenge but over time may become similar
to their non-veteran counterparts. This may be an actual shift or as Hunt and Robbins (2001)
explain a masking of symptoms common in middle age. Therefore, they may not be large
differences in how important social support is to veterans and non-veterans.
Impact on Social Support
In examining social support in veterans, employment status, education level, marital
status, income, and physical activity limitation had a significant impact. Those with activity
limitations may have a harder time getting the social support they need. Having a mental
problem such as PTSD or a physical ailment such as multiple sclerosis has been shown to
encourage isolation (Duax, Bohnert, Rauch, & Defever, 2014) or a needed increase in social
support (Williams et al., 2004). Married veterans have higher levels of social support, supporting
research by Williams et al. (2004). Their research found married veterans having higher levels of
social support. By having a partner married veterans have more access to social support than
other veterans. Working is a significant factor in influencing social support. Employed veterans
in the study have higher levels of social support. Being employed gives veterans an opportunity
for increased social support and in integrating and feeling productive in society. Retired veterans
were also observed to have higher levels of social support. This is the opposite of Hunt and
Robbins (2001) who found that retired veterans had higher rates of depression, partly because of
decreased social support. Income was also found to impact social support. This coincides with
Brummett, Barefoot, Vitaliano, and Siegler (2003) who also found that those with lower income
report lower social support. In conclusion, social support is influenced by many factors that need

to be taken into consideration when examining the causes of social support levels.
Age, gender, and race had no significant effect on social support. Unlike this study,
Street, Vogt, & Dutra (2009) and Kanesarajah, Waller, Zheng, & Dobson (2015) found that
female veterans have lower perceived social support. However, their studies focused on female
veterans of OEF/OIF while the female veterans in this sample used in this study were not limited
by conflict. The age of veterans may not be significant because of others factors influencing
social support. Whether veterans were engaged in combat, deployed oversees, and branch of
service all could play a role. Meanwhile, the low number of minority respondents in the sample
prevent making any reliable predications about the meaning of its lack of significance
Limitations
A limitation of the study is the social support question was in an optional module for the
states conducting the BRFSS survey. As only Minnesota, home to 1.7% of veterans, (United
States Census Bureau, 2014) used the question it limits the relatability of the sample to the rest of
the veterans in the United States. The low number of minority veteran respondents is a further
limitation to the study as minorities represent only 5% of the sample but 22% of veterans in the
United States (National Center for Veterans Analysis and Statistics, 2016). The depression
variable used asked, ever told you that you have a depressive disorder, including depression,
major depression, dysthymia, or minor depression, which excludes individuals who may be
experiencing depression symptoms but never diagnosed. Also, not every respondent answered all
the questions resulting in missing data which may have led to changes in the composition of the
population involved in each statistical test. In addition, respondents self-reported which could
lead to respondents not answering truthfully or not fully understanding the questions presented.
Future Research

Future research can investigate the relationship between veteran status and social support
using data showing exposure to combat and which, if any, conflict the veteran was involved in.
This would enhance the understanding of the impact of combat and if veterans of certain
conflicts differ in their rates of social support. Also, if the social support module is required or
more states include in the BRFSS survey a study can be done with a larger, representative
sample of veterans.
Conclusion
This study examined three hypotheses: the perceived social support veterans receive will
significantly impact depression among veterans, there will be a difference on the impact of social
support and depression between veterans and non-veterans, and age, gender, employment,
education, race, marital status, income, and limited activity will have an impact on perceived
social support and depression. The first hypothesis is supported by the evidence from the study
and thus can be accepted. However, the second hypothesis is not supported by the study and
cannot be accepted while the third hypothesis is partially supported. The third hypothesis can be
accepted for employment, education, marital status, income, and activity limitation while it is not
supported for age, gender, and race. Depression among veterans continues to be a major issue
within the veteran community and further study is needed to examine the role of social support
on depression within different veteran populations.

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Appendix A
Demographic characteristics of participants
Variable
Total
population
Veteran
population
Non-veteran
population
N%
14,898 (100)
n%
1,786 (100)
n%
13,112 (100)
Average Agec
53 63 52
Gender Male 6,732 (45.2) 1,646 (92.2) 5,086 (38.8)
Female 8,166 (54.2) 140 (7.8) 8,026 (62.2)
Race White 13,648 (91.6) 1,695 (95.0) 11,953 (91.2)
Black/African
American
390 (2.6) 19 (1.1) 371 (2.8)
Hispanic/Latino 236 (1.6) 12 (0.7) 224 (1.7)
Asian 219 (1.5) 5 (0.3) 214 (1.6)
Native
Hawaiian/Other
Pacific Islander
21 (0.1) 2 (0.1) 19 (0.1)
American
Indian/Alaskan
Native
133 (0.9) 13 (0.7) 120 (0.9)
Don't Know 106 (0.7) 23 (1.3) 83 (0.6)
Some Other Group 48 (0.3) 1 (0.0) 47 (0.4)
Refused 97 (0.7) 16 (0.9) 81 (0.6)
Education Level No School 15 (0.1) 3 (0.2) 12 (0.1)
c Ages after 80 years old are classified as 80 to protect anonymity of the respondents

Elementary(1-8) 144 (1.0) 18 (1.0) 126 (1.0)
Some High School
(9-11)
442 (3.0) 58 (3.2) 384 (2.9)
High School (12 or
GED)
3,654 (24.5) 487 (27.3) 3,167 (24.2)
Some College (1-3
years)
4,688 (31.5) 617 (34.5) 4,071 (31.0)
College Graduate
(4 years)
5,927 (39.8) 598 (33.5) 5,329 (40.6)
Refused 28 (0.2) 5 (0.3) 23 (0.2)
Employment Status Employed 7,678 (51.5) 630 (35.3) 7,048 (53.8)
Self-employed 1,299 (8.7) 129 (7.2) 1,170 (8.9)
Out of work (1
year or more)
267 (1.8) 24 (1.3) 243 (1.9)
Out of work (Less
than 1 year)
289 (1.9) 22 (1.2) 267 (2.0)
Homemaker 610 (4.1) 6 (0.3) 604 (4.6)
Student 385 (2.6) 15 (0.8) 370 (2.8)
Retired 3,704 (24.9) 870 (48.7) 2,834 (21.6)
Unable to work 613 (4.1) 83 (4.6) 530 (4.0)
Refused 53 (0.4) 7 (0.4) 46 (0.4)
Marital Status
Married 8,617 (57.8) 1,177 (65.9) 7,440 (56.7)
Divorced 1,857 (12.5) 246 (13.8) 1,611 (12.3)
Widowed 1,371 (9.2) 175 (9.8) 1,196 (9.1)
Separated 162 (1.1) 15 (0.8) 147 (1.1)
Never Married 2,414 (16.2) 144 (8.1) 2,270 (17.3)

Unmarried Couple 396 (2.7) 23 (1.3) 373 (2.8)
Refused 81 (0.5) 6 (0.3) 75 (0.6)
Activity Limitation
Yes 2,888 (19.4) 487 (27.3) 2,401 (18.3)
No 11,943 (80.2) 1,286 (72) 10,657 (81.3)
Don’t know/
Refused
67 (0.4) 13 (0.7) 54 (0.4)
Annual income
Less than $10,000 377 (2.5) 27 (1.5) 350 (2.7)
$10,000-$15,000 475 (3.2) 47 (2.6) 428 (3.3)
$15,000-$20,000 746 (5.0) 87 (4.9) 659 (5.0)
$20,000-$25,000 1,043 (7.0) 136 (7.6) 907 (6.9)
$25,000-$35,000 1,373 (9.2) 209 (11.7) 1,164 (8.9)
$35,000-$50,000 2,001 (13.4) 305 (17.1) 1,696 (12.9)
$50,000-$75,000 2,433 (16.3) 310 (17.4) 2,123 (16.2)
Above $75,000 4,730 (31.7) 472 (26.4) 4,258 (32.5)
Don’t know/
Refused
1,720 (11.6) 193 (10.8) 1,527 (11.6)
Have you ever been told you
Yes 2,805 (18.9) 301 (16.8) 2,504 (19.1)

had a depressive disorder?
No 12,042 (80.8) 1,476 (82.6) 10,566 (80.6)
Don't know/
Refused
51 (0.3) 9 (0.5) 42 (0.3)
How often do you get the
social and emotional support
you need?
Always 8,341 (56.0) 1,044 (58.5) 7,297 (55.7)
Usually 4,372 (29.3) 407 (22.8) 3,965 (30.2)
Sometimes 1,224 (8.2) 134 (7.5) 1,090 (8.3)
Rarely 306 (2.1) 50 (2.8) 256 (2.0)
Never 377 (2.5) 92 (5.2) 285 (2.2)
Don't know/
Refused
278 (1.9) 59 (3.3) 219 (1.7)

Appendix B
Emotional Support*Diagnosed with Depression: Chi-Square Tests
ARE YOU A VETERAN Value df
Asymptotic
Significance (2-sided)
Yes Pearson Chi-Square 84.647b 4 .000
Likelihood Ratio 71.771 4 .000
Linear-by-Linear
Association
36.170 1 .000
N of Valid Cases 1718
No Pearson Chi-Square 562.911c 4 .000
Linear-by-Linear
Association
327.928 1 .000
Total Pearson Chi-Square 641.682a 4 .000
Linear-by-Linear
Association
358.409 1 .000
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count
is 57.87.
b. 0 cells (0.0%) have expected count less than 5. The minimum expected count
is 8.30.
c. 0 cells (0.0%) have expected count less than 5. The minimum expected count
is 49.33.
Emotional Support*Diagnosed with Depression: Symmetric
Measures
ARE YOU A VETERAN Value
Approximate
Significance
Yes Nominal by
Nominal
Phi .222 .000
Cramer's V .222 .000
No Nominal by
Nominal
Phi .209 .000
Total Nominal by
Nominal
Phi .210 .000

How often get emotional support needed * Ever told you had a depressive disorder * Are
you a veteran Crosstabulation (Veteran)
ARE YOU A VETERAN: Total
Ever told you had a depressive
disorder
TotalYes No
How often get
emotional support
needed
Always Count 131 911 1042
Row % 12.6% 87.4% 100.0%
Adjusted Residual -6.4 6.4
Usually Count 77 328 405
Row % 19.0% 81.0% 100.0%
Adjusted Residual 1.1 -1.1
Sometimes Count 55 78 133
Row % 41.4% 58.6% 100.0%
Rarely Count 18 30 48
Row % 37.5% 62.5% 100.0%
Never Count 16 74 90
Row % 17.8% 82.2% 100.0%
Adjusted Residual .1 -.1
Total Count 297 1421 1718
Row % 17.3% 82.7% 100.0%

How often get emotional support needed * Ever told you had a depressive disorder
Crosstabulation (Non veterans)
Ever told you had a depressive
disorder
TotalYes No
How often get
emotional support
needed
Row % 13.5% 86.5% 100.0%
Row % 23.6% 76.4% 100.0%
Row % 37.6% 62.4% 100.0%
Row % 46.1% 53.9% 100.0%
Row % 14.4% 85.6% 100.0%
Total Count 2477 10378 12855
Row % 19.3% 80.7% 100.0%
Veterans: Logistic Regression
Model Summary
Step
-2 Log
likelihood
Cox & Snell
R Square
Nagelkerke R
Square
1 1510.219a .041 .068
a. Estimation terminated at iteration number 5
because parameter estimates changed by less than
.001.

Variables in the Equation
B S.E. Wald df Sig. Exp(B
)
95% C.I.for
EXP(B)
Lower Upper
Step
1a
How often get
emotional support
needed
75.991 4 .000
How often get
emotional support
needed(1)
-.408 .291 1.963 1 .161 .665 .376 1.177
How often get
emotional support
needed(2)
.082 .303 .074 1 .786 1.086 .599 1.968
How often get
emotional support
needed(3)
1.182 .327 13.058 1 .000 3.261 1.718 6.192
How often get
emotional support
needed(4)
1.021 .406 6.317 1 .012 2.775 1.252 6.151
Constant -1.531 .276 30.855 1 .000 .216
a. Variable(s) entered on step 1: HOW OFTEN GET EMOTIONAL SUPPORT NEEDED.
Non-Veterans: Logistic Regression
Model Summary
Step
-2 Log
likelihood
Cox & Snell
R Square
Nagelkerke R
Square
1 12086.902a .039 .063
a. Estimation terminated at iteration number 4
because parameter estimates changed by less than
.001.

Variables in the Equation
B S.E. Wald df Sig. Exp(B
)
95% C.I.for
EXP(B)
Lower Upper
Step
1a
How often get
emotional support
needed
521.26
3
4 .000
How often get
emotional support
needed(1)
-.082 .172 .226 1 .635 .921 .657 1.291
How often get
emotional support
needed(2)
.603 .173 12.142 1 .000 1.827 1.302 2.564
How often get
emotional support
needed(3)
1.275 .180 50.084 1 .000 3.577 2.513 5.091
How often get
emotional support
needed(4)
1.623 .210 59.554 1 .000 5.068 3.356 7.653
Constant -1.779 .169 111.08
7
1 .000 .169
a. Variable(s) entered on step 1: HOW OFTEN GET EMOTIONAL SUPPORT NEEDED.

Appendix C
Education: Chi-Square Tests
Value df
Asymptotic
Significance
(2-sided)
Pearson Chi-Square 39.957a 12 .000
Linear-by-Linear
Association
13.806 1 .000
a. 2 cells (10.0%) have expected count less than 5. The
minimum expected count is 2.12.
Education: Symmetric Measures
Value
Approximate
Significance
Nominal by Nominal Phi .152 .000
Cramer's
V
.088 .000

How often get emotional support needed * Education Level Crosstabulation
Education Level Total
Elementary-some
high school
High
School
diploma
Some
college
4 year
college
degree
How often
get
emotional
support
needed
Always Count 37 280 358 364 1039
Adjusted
Residual
-1.7 .1 -.4 1.0
Usually Count 14 93 148 152 407
Adjusted
Residual
-.9 -2.1 .8 1.6
Sometim
es
Count 10 32 55 37 134
Adjusted
Residual
1.9 -.8 1.6 -1.6
Rarely Count 5 16 17 12 50
Adjusted
Residual
2.1 .8 -.1 -1.5
Never Count 7 42 21 22 92
Adjusted
Residual
1.6 4.2 -2.5 -2.1
Total Count 73 463 599 587 1722
Employment: Chi-Square Tests
Value df
Asymptotic
Significance (2-
sided)
Linear-by-Linear
Association
2.511 1 .113

Employment: Symmetric Measures
Value
Approximate
Significance
Nominal by
Nominal
Phi .192 .000
Cramer's
V
.096 .000
How often get emotional support needed * Employment Status Crosstabulation
Employment Status Total
Employed Self-
employed
Unemployed Retired Unable
to work
How
often get
emotional
support
needed
Always Count 381 61 33 535 33 1043
Adjusted
Residual
.8 -2.7 -1.9 3.0 -3.8
Usually Count 151 40 19 172 23 405
Adjusted
Residual
.7 2.4 .9 -2.7 1.1
Sometimes Count 52 10 8 49 13 132
Adjusted
Residual
.9 .2 1.3 -2.7 2.9
Rarely Count 11 7 5 20 7 50
Adjusted
Residual
-2.1 1.9 2.3 -1.2 3.1
Never Count 20 6 2 57 5 90
Adjusted
Residual
-2.8 -.2 -.8 2.9 .4
Total Count 615 124 67 833 81 1720

Marital Status: Chi-Square Tests
Value df
Asymptotic
Significance (2-
sided)
Linear-by-Linear
Association
20.014 1 .000
a. 5 cells (20.0%) have expected count less than 5. The minimum
expected count is .67.
Marital Status: Symmetric Measures
Value
Approximate
Significance
Nominal by
Nominal
Phi .190 .000
How often get emotional support needed * Marital Status Crosstabulation
Marital Status Total
Married Divorced/S
eparated
Widowed Never
married
Unmarried
couple
How often get
emotional
support needed
Always Count 742 122 97 66 14 1041
Adjusted
Residual
5.5 -4.2 -.5 -3.5 .0
Usually Count 262 62 38 41 4 407
Adjusted
Residual
-.9 .4 -.2 1.6 -.7
Someti
mes
Count 63 33 15 19 2 132
Adjusted
Residual
-4.7 3.5 .7 2.7 .2
Rarely Count 23 16 4 5 2 50
Adjusted
Residual
-3.1 3.5 -.4 .5 1.7
Never Count 50 19 11 10 1 91
Adjusted
Residual
-2.3 1.7 .8 1.0 -.2
Total Count 1140 252 165 141 23 1721

Income: Chi-Square Tests
Value df
Asymptotic
Significance
(2-sided)
Linear-by-Linear
Association
40.378 1 .000
Income: Symmetric Measures
Value
Approximate
Significance
Nominal by
Nominal
Phi .241 .000

How often get emotional support needed * Annual Income Crosstabulation
Annual Income Total
Less
than
$15,000
Less
than
$20,000
Less
than
$25,000
Less
than
$35,000
Less
than
$50,000
Less
than
$75,000
$75,000
or more
How often
get
emotional
support
needed
Always Count 42 37 65 114 177 193 299 927
Adjusted
Residual
-.1 -3.1 -2.7 -.9 .1 1.5 2.5
Usually Count 16 19 30 40 73 75 127 380
Adjusted
Residual
-.4 -.5 -.5 -1.6 .1 .1 1.7
Someti
mes
Count 6 15 11 24 27 16 20 119
Adjusted
Residual
.3 3.6 .3 2.5 1.1 -1.8 -3.2
Rarely Count 3 7 9 8 5 9 7 48
Adjusted
Residual
.6 2.8 2.6 .8 -1.5 -.2 -2.3
Never Count 4 7 18 14 13 11 10 77
Adjusted
Residual
.3 1.4 4.8 1.4 -.5 -1.2 -3.3
Total Count 71 85 133 200 295 304 463 155
1
Activity limitation: Chi-Square Tests
Value df
Asymptotic
Significance
(2-sided)
Linear-by-Linear
Association
12.657 1 .000

Activity limitation: Symmetric Measures
Value
Approximate
Significance
Nominal by
Nominal
Phi .119 .000
How often get emotional support needed * Activity limitation due to health problems
Crosstabulation
Activity limitation due to
health problems
Total
Yes No
How often get
emotional support
needed
Adjusted
Residual
-4.2 4.2
Adjusted
Residual
1.9 -1.9
Adjusted
Residual
2.7 -2.7
Adjusted
Residual
2.8 -2.8
Adjusted
Residual
.2 -.2
Total Count 472 1243 1715

Gender: Chi-Square Tests
Value df
Asymptotic
Significance
(2-sided)
Linear-by-Linear
Association
.003 1 .958
Gender: Symmetric Measures
Value
Approximate
Significance
Nominal by
Nominal
Phi .059 .203
Race: Chi-Square Tests
Value df
Asymptotic
Significance
(2-sided)
Linear-by-Linear
Association
.939 1 .333

Race: Symmetric Measures
Value
Approximate
Significance
Nominal by
Nominal
Phi .058 .225
Age: ANOVA
How often get emotional support needed
Sum of
Squares df Mean Square F Sig.
Between
Groups
63.325 62 1.021 .859 .774
Within Groups 1977.558 1664 1.188
Total 2040.884 1726

Appendix D
Case Processing Summary
N
Marginal
Percentage
How often get
emotional support
needed
Always 921 59.9%
Usually 378 24.6%
Sometimes 116 7.5%
Rarely 47 3.1%
Never 75 4.9%
Activity limitation due
to health problem
Yes 425 27.7%
No 1112 72.3%
newemploy Employed 564 36.7%
Self-employed 116 7.5%
Unemployed 59 3.8%
Retired 723 47.0%
Unable to work 75 4.9%
newmarit Married 1015 66.0%
Divorced/Separated 229 14.9%
Widowed 142 9.2%
Never married 130 8.5%
Unmarried couple 21 1.4%
incomenew Less than $15,000 69 4.5%
Less than $20,000 85 5.5%
Less than $25,000 132 8.6%
Less than $35,000 197 12.8%
Less than $50,000 293 19.1%
Less than $75,000 301 19.6%
$75,000 or more 460 29.9%
neweduca Elementary-some high
school
56 3.6%
High School diploma 409 26.6%
Some college 545 35.5%
4 year college degree 527 34.3%
Valid 1537 100.0%
Missing 249
Total 1786

Model Fitting Information
Model
-2 Log
Likelihood
Chi-
Square df Sig.
Intercept
Only
1877.805
Final 1780.986 96.819 18 .000
Link function: Logit.
Goodness-of-Fit
Chi-
Square df Sig.
Pearson 1680.421 1602 .085
Devianc
e
1280.553 1602 1.000
Pseudo R-
Square
Cox and
Snell
.061
Nagelkerke .069
McFadden .029

Parameter Estimates
Estimate Std.
Error
Wald df Sig. 95% Confidence
Interval
Lower
Bound
Upper
Bound
Thresho
ld
[AAAAEMTSU
PRT = 1]
.246 .510 .234 1 .629 -.753 1.245
[AAAAEMTSU
PRT = 2]
1.615 .511 9.971 1 .002 .613 2.618
[AAAAEMTSU
PRT = 3]
2.402 .515 21.759 1 .000 1.393 3.412
[AAAAEMTSU
PRT = 4]
2.933 .520 31.836 1 .000 1.914 3.952
Locatio
n
[AAAAQLACT
LM2=1]
.337 .121 7.746 1 .005 .100 .574
[AAAAQLACT
LM2=2]
0a . . 0 . . .
[newemploy=1.0
0]
-.588 .260 5.133 1 .023 -1.097 -.079
[newemploy=2.0
0]
-.115 .298 .151 1 .698 -.699 .468
[newemploy=3.0
0]
-.156 .329 .225 1 .635 -.802 .489
[newemploy=7.0
0]
-.712 .246 8.345 1 .004 -1.195 -.229
[newemploy=8.0
0]
0a . . 0 . . .
[newmarit=1.00] .008 .448 .000 1 .986 -.870 .886
[newmarit=2.00] .587 .460 1.628 1 .202 -.315 1.490
[newmarit=3.00] .078 .477 .027 1 .870 -.856 1.013
[newmarit=5.00] .673 .471 2.044 1 .153 -.250 1.595
[newmarit=6.00] 0a . . 0 . . .
[incomenew=1.0
0]
-.471 .301 2.438 1 .118 -1.062 .120
[incomenew=3.0
0]
.583 .250 5.424 1 .020 .092 1.073
[incomenew=4.0
0]
.618 .214 8.363 1 .004 .199 1.037

[incomenew=5.0
0]
.272 .187 2.126 1 .145 -.094 .638
[incomenew=6.0
0]
.153 .163 .887 1 .346 -.165 .472
[incomenew=7.0
0]
.042 .159 .071 1 .790 -.270 .355
[incomenew=8.0
0]
0a . . 0 . . .
[neweduca=1.00] .369 .283 1.699 1 .192 -.186 .925
[neweduca=4.00] .052 .140 .139 1 .709 -.222 .326
[neweduca=5.00] -.037 .127 .083 1 .773 -.286 .213
[neweduca=6.00] 0a . . 0 . . .
a. This parameter is set to zero because it is redundant.
Test of Parallel Linesa
Model
-2 Log
Likelihood
Chi-
Square df Sig.
Null
Hypothesis
1780.986
General 1608.034b 172.952c 54 .000
The null hypothesis states that the location parameters
(slope coefficients) are the same across response
categories.
a. Link function: Logit.
b. The log-likelihood value cannot be further increased after
maximum number of step-halving.
c. The Chi-Square statistic is computed based on the log-
likelihood value of the last iteration of the general model.
Validity of the test is uncertain.

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