Andrew Trueblood-Capstone -National Univeristy

Running head: INFLUENCE OF SOCIAL SUPPORT 1

THE INFLUENCE OF SOCIAL SUPPORT ON DEPRESSION AMONG VETERANSAndrew Trueblood

Capstone ProjectNational 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

Brandon Eggleston, 07/27/16,

Avoid short sentences in your writing because it breaks the flow for the reader instead after the word rise place a comma plus the word and to connect to the next sentence.on the rise, and the increase of depression or depression related symptoms has been observed in multiple studies


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.


Start all tables on a seprate page


Variables

Questions Possible Answers SPSS Variable

NameHave 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? (Active duty does not include training for the Reserves or National 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?


ADDEPEV2

How often do you get the social and emotional support you need?

Always Usually Sometimes Rarely Never Don’t know/Not sure 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

White Black or African

RRCLASS2


African American, Hispanic or Latino, Asian, Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native, or some other group?

American Hispanic or Latino Asian Native Hawaiian or

other Pacific Islander American Indian or

Alaskan Native Don’t know/Not sure Some other group Refused

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?


QLACTLM2

Is your annual household income from all sources:

Less than $10,000 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 Don’t know/Not sure 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 1Odds 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

$20,00085 (5.5%) 1.791b [1.097, 2.924]


$25,000132 (8.6%) 1.856b [1.220, 2.822]


$35,000197 (12.8%) 1.313 [.911, 1.893]


$50,000293 (19.1%) 1.165 [.847, 1.603]


$75,000301 (19.6%) 1.043 [.764, 1.426]

$75,000 or more 460 (29.9%) Ref Ref

Education Elementary- some high

school56 (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]

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]

a p.01b p.05


Place in brackets


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 Depression in 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 Depression in 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

American390 (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)

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)

c Ages after 80 years old are classified as 80 to protect anonymity of the respondents


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 StatusMarried 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 LimitationYes 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/

Refused67 (0.4) 13 (0.7) 54 (0.4)

Annual incomeLess 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/

Refused1,720 (11.6) 193 (10.8) 1,527 (11.6)

Have you ever been told you

had a depressive disorder?Yes 2,805 (18.9) 301 (16.8) 2,504 (19.1)

No 12,042 (80.8) 1,476 (82.6) 10,566 (80.6)


Don't know/

Refused51 (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/

Refused278 (1.9) 59 (3.3) 219 (1.7)

Appendix B


Emotional Support*Diagnosed with Depression: Chi-Square Tests

ARE YOU A VETERAN Value dfAsymptotic Significance (2-sided)

Yes Pearson Chi-Square 84.647b 4 .000Likelihood Ratio 71.771 4 .000Linear-by-Linear Association

36.170 1 .000

N of Valid Cases 1718No Pearson Chi-Square 562.911c 4 .000

Likelihood Ratio 513.485 4 .000Linear-by-Linear Association

327.928 1 .000

N of Valid Cases 12855Total Pearson Chi-Square 641.682a 4 .000

Likelihood Ratio 581.640 4 .000Linear-by-Linear Association

358.409 1 .000

N of Valid Cases 14573a. 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 ValueApproximate Significance

Yes Nominal by Nominal

Phi .222 .000Cramer's V .222 .000

N of Valid Cases 1718No Nominal by

NominalPhi .209 .000Cramer's V .209 .000

N of Valid Cases 12855Total Nominal by

NominalPhi .210 .000Cramer's V .210 .000

N of Valid Cases 14573


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 NoHow often get emotional support needed

Always Count 131 911 1042Row % 12.6% 87.4% 100.0%Adjusted Residual -6.4 6.4

Usually Count 77 328 405Row % 19.0% 81.0% 100.0%Adjusted Residual 1.1 -1.1

Sometimes Count 55 78 133Row % 41.4% 58.6% 100.0%Adjusted Residual 7.6 -7.6

Rarely Count 18 30 48Row % 37.5% 62.5% 100.0%Adjusted Residual 3.8 -3.8

Never Count 16 74 90Row % 17.8% 82.2% 100.0%Adjusted Residual .1 -.1

Total Count 297 1421 1718Row % 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 NoHow often get emotional support needed

Always Count 980 6304 7284Row % 13.5% 86.5% 100.0%Adjusted Residual -19.1 19.1

Usually Count 930 3017 3947Row % 23.6% 76.4% 100.0%Adjusted Residual 8.2 -8.2

Sometimes Count 408 676 1084Row % 37.6% 62.4% 100.0%Adjusted Residual 16.0 -16.0

Rarely Count 118 138 256Row % 46.1% 53.9% 100.0%Adjusted Residual 11.0 -11.0

Never Count 41 243 284Row % 14.4% 85.6% 100.0%Adjusted Residual -2.1 2.1

Total Count 2477 10378 12855Row % 19.3% 80.7% 100.0%

Veterans: Logistic Regression

Model Summary

Step-2 Log

likelihoodCox & Snell

R SquareNagelkerke R

Square1 1510.219a .041 .068a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.


Variables in the EquationB 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


.082 .303 .074 1 .786 1.086 .599 1.968


1.182 .327 13.058 1 .000 3.261 1.718 6.192


1.021 .406 6.317 1 .012 2.775 1.252 6.151

Constant -1.531 .276 30.855 1 .000 .216a. Variable(s) entered on step 1: HOW OFTEN GET EMOTIONAL SUPPORT NEEDED.

Non-Veterans: Logistic Regression

Model Summary

Step-2 Log

likelihoodCox & Snell

R SquareNagelkerke R

Square1 12086.902a .039 .063a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.


Variables in the EquationB S.E. Wald df Sig. Exp(B

)95% C.I.for

EXP(B)Lower Upper

Step 1a


521.263

4 .000


-.082 .172 .226 1 .635 .921 .657 1.291


.603 .173 12.142 1 .000 1.827 1.302 2.564


1.275 .180 50.084 1 .000 3.577 2.513 5.091


1.623 .210 59.554 1 .000 5.068 3.356 7.653

Constant -1.779 .169 111.087

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 .000Likelihood Ratio 36.920 12 .000Linear-by-Linear Association

13.806 1 .000

N of Valid Cases 1722a. 2 cells (10.0%) have expected count less than 5. The minimum expected count is 2.12.

Education: Symmetric Measures

ValueApproximate Significance

Nominal by Nominal Phi .152 .000Cramer's V

.088 .000



How often get emotional support needed * Education Level CrosstabulationEducation Level Total

Elementary-some high school

High School diploma

Some college

4 year college degree


Always Count 37 280 358 364 1039Adjusted Residual

-1.7 .1 -.4 1.0

Usually Count 14 93 148 152 407Adjusted Residual

-.9 -2.1 .8 1.6

Sometimes

Count 10 32 55 37 134Adjusted Residual

1.9 -.8 1.6 -1.6

Rarely Count 5 16 17 12 50Adjusted Residual

2.1 .8 -.1 -1.5

Never Count 7 42 21 22 92Adjusted Residual

1.6 4.2 -2.5 -2.1

Total Count 73 463 599 587 1722

Employment: Chi-Square Tests

Value df



2.511 1 .113

N of Valid Cases 1720a. 5 cells (20.0%) have expected count less than 5. The

minimum expected count is 1.95.


Employment: Symmetric Measures


Nominal by Nominal

Phi .192 .000Cramer's V

.096 .000


How often get emotional support needed * Employment Status CrosstabulationEmployment Status Total

Employed Self-employed

Unemployed Retired Unable to work


Always Count 381 61 33 535 33 1043Adjusted Residual

.8 -2.7 -1.9 3.0 -3.8

Usually Count 151 40 19 172 23 405Adjusted Residual

.7 2.4 .9 -2.7 1.1

Sometimes Count 52 10 8 49 13 132Adjusted Residual

.9 .2 1.3 -2.7 2.9

Rarely Count 11 7 5 20 7 50Adjusted Residual

-2.1 1.9 2.3 -1.2 3.1

Never Count 20 6 2 57 5 90Adjusted Residual

-2.8 -.2 -.8 2.9 .4

Total Count 615 124 67 833 81 1720


Marital Status: Chi-Square Tests

Value df



20.014 1 .000

N of Valid Cases 1721a. 5 cells (20.0%) have expected count less than 5. The minimum expected count is .67.

Marital Status: Symmetric Measures


Nominal by Nominal

Phi .190 .000Cramer's V .095 .000


How often get emotional support needed * Marital Status CrosstabulationMarital Status Total

Married Divorced/Separated

Widowed Never married

Unmarried couple


Always Count 742 122 97 66 14 1041Adjusted Residual

5.5 -4.2 -.5 -3.5 .0

Usually Count 262 62 38 41 4 407Adjusted Residual

-.9 .4 -.2 1.6 -.7

Sometimes

Count 63 33 15 19 2 132Adjusted 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 91Adjusted 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)Pearson Chi-Square 90.241a 24 .000Likelihood Ratio 81.276 24 .000Linear-by-Linear Association

40.378 1 .000


Income: Symmetric Measures


Nominal by Nominal

Phi .241 .000Cramer's V .121 .000



How often get emotional support needed * Annual Income CrosstabulationAnnual 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


Always Count 42 37 65 114 177 193 299 927Adjusted Residual

-.1 -3.1 -2.7 -.9 .1 1.5 2.5

Usually Count 16 19 30 40 73 75 127 380Adjusted Residual

-.4 -.5 -.5 -1.6 .1 .1 1.7

Sometimes

Count 6 15 11 24 27 16 20 119Adjusted Residual

.3 3.6 .3 2.5 1.1 -1.8 -3.2

Rarely Count 3 7 9 8 5 9 7 48Adjusted Residual

.6 2.8 2.6 .8 -1.5 -.2 -2.3

Never Count 4 7 18 14 13 11 10 77Adjusted Residual

.3 1.4 4.8 1.4 -.5 -1.2 -3.3

Total Count 71 85 133 200 295 304 463 1551

Activity limitation: Chi-Square Tests


Value df



12.657 1 .000


Activity limitation: Symmetric Measures


Nominal by Nominal

Phi .119 .000Cramer's V .119 .000


How often get emotional support needed * Activity limitation due to health problems Crosstabulation

Activity limitation due to health problems

Total

Yes NoHow often get emotional support needed

Always Count 247 789 1036Adjusted Residual

-4.2 4.2

Usually Count 127 279 406Adjusted Residual

1.9 -1.9

Sometimes Count 50 83 133Adjusted Residual

2.7 -2.7

Rarely Count 22 27 49Adjusted Residual

2.8 -2.8

Never Count 26 65 91Adjusted Residual

.2 -.2

Total Count 472 1243 1715


Gender: Chi-Square Tests

Value df



.003 1 .958


Gender: Symmetric Measures


Nominal by Nominal

Phi .059 .203Cramer's V .059 .203


Race: Chi-Square Tests

Value df


Pearson Chi-Square 5.671a 4 .225Likelihood Ratio 4.580 4 .333


Linear-by-Linear Association

.939 1 .333


Race: Symmetric Measures


Nominal by Nominal

Phi .058 .225Cramer's V .058 .225


Age: ANOVAHow 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 1.188Total 2040.884 1726


Appendix D

Case Processing Summary

NMarginal

PercentageHow 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 249Total 1786

Model Fitting Information

Model-2 Log

LikelihoodChi-

Square df Sig.Intercept Only

1877.805

Final 1780.986 96.819 18 .000Link function: Logit.

Goodness-of-FitChi-

Square df Sig.Pearson 1680.421 1602 .085Deviance

1280.553 1602 1.000

Link function: Logit.

Pseudo R-Square

Cox and Snell

.061

Nagelkerke .069McFadden .029Link function: Logit.


Parameter EstimatesEstimate Std.

ErrorWald df Sig. 95% Confidence

IntervalLower Bound

Upper Bound

Threshold

[AAAAEMTSUPRT = 1]

.246 .510 .234 1 .629 -.753 1.245

[AAAAEMTSUPRT = 2]

1.615 .511 9.971 1 .002 .613 2.618

[AAAAEMTSUPRT = 3]

2.402 .515 21.759 1 .000 1.393 3.412

[AAAAEMTSUPRT = 4]

2.933 .520 31.836 1 .000 1.914 3.952

Location

[AAAAQLACTLM2=1]

.337 .121 7.746 1 .005 .100 .574

[AAAAQLACTLM2=2]

0a . . 0 . . .

[newemploy=1.00]

-.588 .260 5.133 1 .023 -1.097 -.079

[newemploy=2.00]

-.115 .298 .151 1 .698 -.699 .468

[newemploy=3.00]

-.156 .329 .225 1 .635 -.802 .489

[newemploy=7.00]

-.712 .246 8.345 1 .004 -1.195 -.229

[newemploy=8.00]

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=1.00]

-.471 .301 2.438 1 .118 -1.062 .120

[incomenew=3.00]

.583 .250 5.424 1 .020 .092 1.073

[incomenew=4.00]

.618 .214 8.363 1 .004 .199 1.037

[incomenew=5.00]

.272 .187 2.126 1 .145 -.094 .638

[incomenew=6.00]

.153 .163 .887 1 .346 -.165 .472

[incomenew=7.00]

.042 .159 .071 1 .790 -.270 .355

[incomenew=8.00]

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 . . .

Link function: Logit.a. This parameter is set to zero because it is redundant.

Test of Parallel Linesa

Model-2 Log

LikelihoodChi-

Square df Sig.Null Hypothesis

1780.986

General 1608.034b 172.952c 54 .000The 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.

Documents

Andrew Trueblood-Capstone -National Univeristy