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Education as a Pathway to Help Job Searching Military Veterans’ Transition to Civilian Life

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Education as a Pathway to Help Job Searching Military Veterans’ Transition to Civilian Life

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The transition from military to civilian life can be a difficult process. Two distinct samples of working United States military veterans were studied: combat (n = 56) and non-combat (n=43). The goal of this study was to investigate the specific role of furthering one’s education as a pathway to help job-searching military veterans in their transition to civilian life. Across both samples, veterans who were actively job searching had higher burnout and general exhaustion than veterans not actively searching. There was partial support for finding veterans who were actively job searching to be currently furthering their education, and for those currently furthering their education to perceive higher occupational alternatives. High percentages in both samples were currently going to school to further their education. The importance of education as a pathway to support military veterans making a successful transition to civilian life is discussed.
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Journal of Education and Development; Vol. 5, No. 1; April, 2021
ISSN 2529-7996 E-ISSN 2591-7250
Published by July Press
1
Education as a Pathway to Help Job Searching Military Veterans’
Transition to Civilian Life
Gary Blau1 & Glen Miller1
1 Fox School of Business & Management, Temple University, Philadelphia, USA
Correspondence: Gary Blau, HRM Department, Fox School of Business & Management, Temple University,
Philadelphia, PA, USA. Tel: 1-215-204-6906.
Received: November 2, 2020 Accepted: December 4, 2020 Online Published: January 5, 2021
doi:10.20849/jed.v5i1.822 URL: https://doi.org/10.20849/jed.v5i1.822
Abstract
The transition from military to civilian life can be a difficult process. Two distinct samples of working United
States military veterans were studied: combat (n = 56) and non-combat (n=43). The goal of this study was to
investigate the specific role of furthering one’s education as a pathway to help job-searching military veterans in
their transition to civilian life. Across both samples, veterans who were actively job searching had higher burnout
and general exhaustion than veterans not actively searching. There was partial support for finding veterans who
were actively job searching to be currently furthering their education, and for those currently furthering their
education to perceive higher occupational alternatives. High percentages in both samples were currently going to
school to further their education. The importance of education as a pathway to support military veterans making
a successful transition to civilian life is discussed.
Keywords: burnout, furthering education, general exhaustion, job search, military veterans, transition to civilian
life
1. Introduction
As United States (US) military veterans leave the military, their successful transition to civilian life can be
difficult. The Pew Research Center (2019) found that only 25% of the veterans they surveyed had civilian jobs
ready to immediately start after they left the military. In addition this survey found that only 16% felt that the
military prepared veterans very well for their transition. A transition to civilian life scale (TCLS) for military
veterans was recently published (Weiss, Rubin & Graeser, 2019). This 15-scale identified three factors:
psychosocial, economic and physical health, with nine of 15 items loading on the psychosocial factor, sample
item “I participate in enjoyable recreation activities.” One of the five economic items asked about education, i.e.,
“I can get the education I need,” but this item was part of a more general economic factor which also asked about
stability of finances, being happy with quality of housing, and feeling optimistic about future career. Although
three factors were mentioned, reliability data was only presented for the full 15-item scale. The goal of this study
was to pursue the specific role of furthering one’s education as a pathway to support job-searching military
veterans in their transition to civilian life.
1.1 Relevant Scholarship
Burnout is an important mental health issue for many types of workers (Maslach & Leiter, 1997). Burnout is
composed of three distinct dimensions: emotional exhaustion, depersonalization, and diminished personal
accomplishment. Emotional exhaustion involves feeling a lack of energy and that one’s emotional resources are
gone; depersonalization is described as an insensitive, callous attitude towards treating people; and diminished
personal accomplishment is a tendency to self-evaluate negatively, as the individual experiences feelings of job
incompetence. Most burnout research has focused on health care or mental health workers, e.g., doctors, nurses,
therapists, social workers, counselors (Morse, Salybers, Rollins, Monroe-DeVita & Pfhaler, 2012).
Military-related research has also tended to focus on either military mental health professionals e.g.,
Ballenger-Browning et al. (2011); Kok et al., (2016) or military health care professionals, e.g., Adler et al.
(2017); Smith et al. (2015). Less research has focused on testing burnout among more general military veteran
samples, as this study did. At a general level, burnout has been associated with intent to quit and other
turnover-related behaviors (Dreison, Luther, Bonfils, Sliter, McGrew & Salyers, 2018).
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Education can be positively related to increased job search activity (Wanberg, Basbug, Van Hooft & Santani,
2012). Increased education was positively related to self-reported happiness and self-rated health by Post-9/11
military veterans (Morgan, Desmarais & Neupert, 2017). Bagby, Barnard-Brak, Thompson and Sulak (2015)
found that the university-related educational experiences of 11 student veterans, which included joining social
networks, and interacting with same-major student peers, and faculty contacts useful, as they transitioned from
military to civilian life. In their implications for research Bagby et al. (2015) called for more research on the link
between student veteran academic decisions and success outcomes, e.g., employment.
1.2 Research Question and Research Design
This is an exploratory study, working with smaller samples of working combat veterans and non-combat
veterans. Some of the veterans in each sample were actively job searching and some were not. Some of the
veterans were currently going to school to further their education and some were not. In addition, we tested if
those veterans going to school perceived higher occupational alternatives then those not going to school. This led
to three research questions:
RQ1 – combat veterans and non-combat veterans who are actively searching for a new job will perceive higher
burnout and general exhaustion than those veterans who are not actively searching
RQ2 – combat veterans and non-combat veterans who are actively searching for a new job are more likely to be
currently going to school to further their education than those who are not actively searching
RQ3 – combat veterans and non-combat veterans who are currently going to school to further their education
will have higher perceived occupational alternatives than those who are not currently going to school
2. Method
2.1 Participants and Procedure
In the spring of 2019 respondents received a pre-tested Qualtrics survey link asking if they had experienced a
past traumatic event (TE), and if so to then answer questions about how they experienced/dealt with this TE.
There is generally very low risk when asking respondents to recall a prior TE (Ferrier-Auerbach, Erbes &
Polusny, 2009). In addition, participants could omit an item if it was too distressing to answer. Military veteran
respondents, either with combat experience or not, came from several different sources. One source was the
University student chapter Veterans’ Association. This University was located in the Mid-Atlantic United States
(US). A second source was contacts the second author had as a military veteran with different US-based
veteran-oriented associations. These associations were primarily smaller non-profits formed to support veterans
and their families. The survey was anonymous and took approximately 15-20 minutes to complete. Once
respondents submitted this first survey, they were automatically taken to a separate second brief survey. This
survey asked for an email address so participants could be randomly selected for either $50, $20, or $10 multiple
gift card drawings. The first item in the initial survey was a voluntary consent item, and respondents were
instructed not to take the survey if they were under 18 years old. University Institutional Review Board approval
was given for this project. Over a period of approximately three months, there were 320 respondents to the first
survey, and 269 to the second survey. Unfortunately, 68 (21%) of the participants to the first survey had over
90% missing data and were discarded, leaving a sample of 252 participants. Within this sample there were 153
(61%) military veterans. Of these 153 military veterans, 99 (65%) were currently working. These 99 participants
constituted the study sample.
2.2 Measures
Combat versus non-combat veteran. Military veteran respondents were asked, “Are you a combat veteran?”,
where 1 = yes (n = 56, 57%), and 2 = no (n = 43, 43%).
Demographic variables. Four demographic variables were asked: gender, where 1 = male, 2 = female; race,
where 1 = African American, 2 = American Indian, 3 = Asian, 4 = Hispanic, 5 = Multi-racial, 6 = Pacific
Islander, 7 = White; age, indicated in years; highest education level, where 1 = high school diploma, to 6 =
doctorate, medical, dental or law degree. The breakdown for the combat versus non-combat sample is shown in
Tab l e 1 .
Burnout dimensions and general exhaustion. Each of the three burnout dimensions, emotional exhaustion,
depersonalization, and diminished personal accomplishment was measured using three items. This nine-item
short-form version of the Maslach burnout inventory (Maslach & Leiter, 1997) has been used in prior research
(McManus, Keeling & Paice, 2004). A sample item for emotional exhaustion is, “I feel emotionally drained from
my work”; and for depersonalization, “I have become more callous/insensitive towards people since I took this
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job”. A 7-point frequency response scale was used, where 1 = never, 2 = a few times a year, 3 = once a month or
less, 4 = a few times a month, 5 = once a week, 6 = a few times a week, and 7 = every day. A sample item for
personal accomplishment was, “I deal very effectively with any people-related problems at work”. Following
prior research (Blau, Tatum & Goldberg, 2013) these three personal accomplishment items were recoded so that
1 = every day and 7 = never, and the scale was retitled as diminished personal accomplishment. Coefficient alpha
for these scales were: emotional exhaustion = .80, depersonalization = .70, and diminished personal
accomplishment = .65. These reliabilities are consistent with prior research (Blau et al., 2013; Maslach & Leiter,
1997). General exhaustion was adapted from (Moore, 2000) and measured using two-items. A sample item was
“I feel exhausted from life in general.” A 7-point response scale, 1 = strongly disagree to 7 = strongly agree was
used. The coefficient alpha for this scale was .90.
Active job search. One item asked, “I am actively searching for a new or different paid work situation”, where 1
= yes, 2 = no.
Currently going to school. One item asked, “Are you currently going to school to further your education”, where
1 = yes, 2 = no.
Perceived occupational alternatives. A three-item scale was used (Blau, 2003). A sample item was “given my
background and experience, I have other occupational alternatives.” A seven-point response scale was used,
where 1 = strongly disagree to 7 = strongly agree. Coefficient alpha was .89, which is consistent with prior
research (Blau, 2003).
2.3 Data Analyses
All data were analyzed using SPSS-PC version 25 (SPSS, 2015). Frequency breakdowns for the combat versus
non-combat samples were given for the demographic variables, followed by a correlation matrix for continuous
variables using the combined samples. Paired sample t-tests were used to test for differences between the three
burnout dimensions and general exhaustion. Independent sample t-tests on the burnout dimensions and general
exhaustion were used for combat versus non-combat samples, comparing those actively job searching versus not
(RQ1). Chi-square analyses were done for combat versus non-combat samples, comparing those actively job
searching versus not against those currently going to school versus not (RQ2). Finally, independent sample
t-tests were done on perceived occupational alternatives for combat versus non-combat samples comparing those
currently going to school versus not. (RQ3) To determine statistical significance, a cutoff of p < .10 (two-tailed)
was used. Prior research (Hopkins, Marshall, Batterham & Hanin, 2008, p.6) argued that p = .10, with a 90%
confidence is “an appropriate default level of confidence.”
3. Results
3.1 Frequency Breakdown of Demographics for Combat Versus Non-combat Sample
Table 1 presents the frequency breakdown of demographics for the combat versus non-combat sample. Both
samples are predominantly white, male, with a four-year degree being the most frequent category for highest
education level. The most frequent age category for combat veterans was 33 to 39, while for non-combat
veterans it was 19 to 25.
Table 1. Frequency statistics for demographic variables – combat and non-combat veteran samples
Variable Combat Sample (n = 56) Non-combat Sample (n = 43)
Gender
Male
Female
Did not identify
n = 47 (84%)
n = 9 (16%)
n = 0
n = 29 (67%)
n = 13 (30%)
n = 1 (3%)
Race
African American
American Indian
Asian
Hispanic
n = 3 (5%)
n = 0
n = 4 (7%)
n = 4 (7%)
n = 5 (11%)
n = 0
n = 2 (5%)
n = 2 (5%)
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Multi-racial
Pacific Islander
White
n = 5 (9%)
n = 0
n = 40 (71%)
n = 4 (9%)
n = 0
n = 30 (70%)
Age (collapsed into categories for
space)
19 - 25
26 - 32
33 - 39
40 - 46
47 - 53
54 60
61 67
68 74
75 or more
n = 2 (4%)
n = 11 (20%)
n = 22 (38%)
n = 6 (11%)
n = 9 (15%)
n = 2 (4%)
n = 2 (4%)
n = 2 (4%)
n = 0
n = 9 (21%)
n = 8 (19%)
n = 7 (16%)
n = 7 (16%)
n = 5 (12%)
n = 2 (5%)
n = 4 (9%)
n = 1 (2%)
n = 0
Highest Education Level
High School Diploma
Some College
Associate Degree
Four Year Degree
Masters Degree
Doctorate, Medical,
Dental or Law Degree
n = 0
n = 4 (7%)
n = 6 (11%)
n = 21 (37%)
n = 17 (30%)
n = 8 (15%)
n = 1 (2%)
n = 10 (23%)
n = 2 (5%)
n = 16 (37%)
n = 10 (23%)
n = 4 (10%)
3.2 Means, Standard Deviations and Correlations for Continuous Variables for Combined Sample
Table 2 presents the full sample means, standard deviations and correlations for continuous variables for the
combined samples. The means for the three burnout dimensions and general exhaustion were not high, while the
mean for Perceived Occupational Alternative was higher. Paired sample t-tests found significant mean
differences (p < .05) such that General Exhaustion was higher than Emotional Exhaustion, which was higher
than Diminished Personal Accomplishment, which was higher than Depersonalization. Positive correlations
between the three burnout dimensions were consistent with prior research (Blau et al., 2013). The highest
correlation was between general exhaustion and emotional exhaustion, r(97) = .65, p < .01. This correlation
indicated (.65)2 = 42% overlap, which indicated sufficient independence for both variables to be used separately
in subsequent analyses (Stevens, 1996).
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Table 2. Full sample - means, standard deviations, and correlations for continuous variables
Measure M
d
SD 1 2 3 4 5 6
1. Agea 28.04 16.98 (---)
2. Emotional Exhaustion
b
3.27f 1.62 -.11 (---)
3. Depersonalization
b
2.14
h
1.29 -.28** .49** (---)
4. Diminished Personal
Accomplishmentb
2.82g 1.50 -.13 .17 .16 (---)
5. General Exhaustionc 3.66e 1.81 .01 .65** .30** .29** (---)
6. Perceived Occupational
Alternativesc
4.85 1.94 -.12 -.10 .03 -.26** -.27** (---)
(n = 99) *p < .05; ** p < .01 (two-tailed).
a Age, measured in years
b Emotional Exhaustion, Depersonalization, Diminished Personal Accomplishment, 1 = Never to 7 = Every day
c General Exhaustion, Perceived Occupational Alternatives, 1 = strongly disagree to 7 = strongly agree
d Means with different superscripts, e, f, g. h are significantly different using a paired samples t-test, General
Exhaustion higher than Emotional Exhaustion, which is higher than Diminished Personal Accomplishment,
which is higher than Depersonalization p < .05 level
3.3 Tests of Research Questions
RQ1 stated that combat veterans and non-combat veterans who are actively searching for a new job will perceive
higher burnout and general exhaustion than those veterans who are not actively searching. The results are shown
in Table 3. There is a clear pattern of higher means on all three burnout dimensions and general exhaustion for
those combat and non-combat veterans who are actively searching for jobs versus those who are not actively
searching. Most of the mean differences are significantly different, providing overall support for the first
research question.
Table 3. Independent sample t-tests comparing burnout dimensions and general exhaustion for combat veterans
and non-combat veterans who are actively searching for a new job versus not actively searching
Combat Veterans Non-combat Veterans
Active
Search
Not Active
Search
Active
Search
Not Active
Search
(n=21) (n=35) (n=18) (n=25)
Variable M (SD) M (SD) t-value M (SD) M (SD) t-value
1. Emotional Exhaustion 3.58 (1.89) 3.05 (1.44) 1.18 3.71 (1.95) 2.41 (1.01) 2.51*
2. Depersonalization 2.85 (1.79) 1.86 (1.11) 2.24* 2.22 (1.10) 1.58 (.72) 2.08*
3. Diminished Personal
Accomplishment 3.00 (1.41) 2.35 (1.38) 1.66+ 3.67 (1.83) 2.53 (1.08) 2.30*
4. General Exhaustion 4.31 (1.94) 3.20 (1.65) 2.62* 4.36 (1.89) 3.30 (1.88) 2.04*
+ p < .10; * p < .05 (two-tailed)
RQ2 stated that combat veterans and non-combat veterans who are actively searching for a new job are more
likely to be currently going to school to further their education than those who are not actively searching. The
results are shown in Table 4. The Chi-square values show that there is statistical support for combat veterans, but
not non-combat veterans. Thus RQ2 was only partially supported. However, the high percentages of both combat
veterans (40/56 = 71%) and non-combat veterans (35/43 = 81%) going back to school to further their education
is important to note below.
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Table 4. Chi-Square tests comparing combat and non-combat veterans who are actively job searching versus not
and who are currently going to school to further their education versus not
Combat Veterans Non-combat Veterans
Going to School Going to School
Yes No Yes No
Yes 19 1 Yes 15 2
Actively Actively
Job Searching Job Searching
No 21 15 No 20 6
Chi-Square (1, n = 56) = 6.82, p =.01 Chi-Square (1, n = 43) = 1.02, p =.33
RQ3 stated that combat veterans and non-combat veterans who are currently going to school to further their
education will have higher perceived occupational alternatives than those who are not currently going to school.
Although the perceived occupational means were higher for both combat and non-combat veterans going to
school versus those who were not, only the mean difference for non-combat veterans was statistically significant
as shown below in Table 5. Thus, there was partial support for RQ3.
Table 5. Independent sample t-tests comparing perceived occupational alternatives for combat veterans and
non-combat veterans who are currently going to school to further their education versus those who are not going
Combat Veterans Non-combat Veterans
Going to School Not Going Going to School Not Going
(n=40) (n=16) (n=35) (n=8)
Variable M (SD) M (SD) t-value M (SD) M (SD) t-value
Perceived
Occupational
Alternatives 5.44 (1.61) 5.00 (1.74) .90 4.72 (2.05) 2.33 (1.03) 4.12**
** p < .01
4. Discussion
The results of this showed that both combat and non-combat veterans who were actively searching for a new job
perceived higher burnout and general exhaustion than veterans who were not actively searching. This finding is
consistent with research using more general work samples (Dreison et al., 2018). Across both study samples,
emotional exhaustion was higher than the other two burnout dimensions of diminished personal accomplishment
and depersonalization. Burnout has not been as frequently studied with general military veteran samples as done
here versus other military samples, such as mental health professionals (Kok et al., 2016) or health care
professionals, e.g., Adler et al. (2017). In addition, general exhaustion was higher than emotional exhaustion.
These results indicate that veterans searching for new jobs were not as “happy” as those not searching. There
was partial support for veterans who were actively job searching to be currently going to school to further their
education, and veterans currently going to school having higher perceived occupational alternatives. Good initial
job placement as they left the military was found to be a challenging issue for many veterans who felt they had
less than adequate preparation for this transition (Pew Research Center, 2019). The Pew study also found that
officers were twice as likely as enlisted personnel to have a job lined up when they left the military. Although we
don’t know the departing rank or civilian work history of the veterans studied here, the results did show that
those with higher perceived burnout and general exhaustion were more likely to be actively job searching.
Providing resources to all US veterans, e.g., resume building, interviewing, and technological search skills,
regardless of rank, is important as they prepare to transition to civilian life. Anecdotal evidence from employers
and veterans suggest that many veterans have significant leadership and teamwork skills that may not be
understood by employers without a military work history. To help overcome this veteran skill – employer need
gap, the Department of Labor (2019) challenged organizations to create a job-matching software tool to
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eventually be added to the Employment Workshop curriculum for all transitioning service members. Providing
such a tool with stronger skill/need matching should hopefully enable veterans to not only find an initially
satisfying civilian job placement, but to change jobs more easily as needed.
Prior research has found university-related educational experiences to be helpful to transitioning veterans (Bagby
et al., 2015). The results of this study support going back to school to further one’s education as one specific
pathway to help the active job search process and increase the perception of occupational alternatives. This study
found high percentages of both samples were currently going back to school to further their education. Although
we don’t know the level of degree being sought, inspection of the highest education level reported shows that
some veterans had still not attained a four-year degree, and those that had their baccalaureate were perhaps
seeking a higher-level degree. The United States Department of Veterans Affairs (2016) estimated that by 2021,
there will be about 5.1 million veterans who were on active duty after September 10, 2001 (Post-9/11 Veterans).
Of those Post-9/11 Veterans, it was further estimated that only 32% will have a bachelor’s degree or higher. Prior
studies of veterans returning to college have typically focused on student transition concerns, much of which
were related to policies that complicated re-enrollment, such as lapses in student insurance, cancellation of
financial aid, or being off-sequence for infrequently offered courses (e.g., Rumann & Hamrick, 2010). Other
studies have argued the need for increased support for returning-to-college veterans, such as having access to
student veterans’ organizations, additional mentoring, or veterans’ resource centers (e.g., Evans, Pellegrino, &
Hoggan, 2015).
These results suggest that furthering one’s education can be a useful track to support veterans transitioning to
civilian life. To the authors’ knowledge, such a measure of furthering one’s education has not been tested before.
Although education is mentioned in prior work on veterans transitioning to civilian life (Weiss et al., 2019), this
item was part of a more general “economic” factor, and focused on veterans perceiving they can get the
education needed, versus asking if they were currently going to school. Getting the education needed can imply
having necessary financial resources, which can be an important prerequisite to going back to school (Bagby et
al., 2015). Using such an item separately in future research, and not as part of a general scale (Weiss et al., 2019),
could be beneficial. It would be interesting to study the type of major veterans pursue when they go back to
college, while taking advantage of tuition benefits earned as a veteran. For example, prior research has classified
college majors as being more intrinsically (I) versus more extrinsically (E) oriented (Yu & Levesque-Bristol,
2018). Intrinsic motivation involves doing a task for its inherent satisfaction, while extrinsic motivation focuses
on doing the same task to achieve external rewards, such as compensation (Ryan & Deci, 2000). Business
students with such majors as accounting, business management, finance, and marketing, emphasize maximizing
profits, and have a higher extrinsic value orientation than education-related majors, who are more intrinsically
motivated (Vansteenkiste, Duriez, Simons & Soenens, 2006). Yu and Levesque-Bristol (2018) asserted that all
science-related majors, including natural sciences, such as biology, chemistry and physics, as well as social
sciences, should be more intrinsically motivated versus engineering and technology-related majors, which would
tend to attract more extrinsically motivated students due to higher paying jobs. Finding the right major, leading
to a stronger job fit after graduation, would be important to help such veterans make a smoother transition back
to civilian life. This reinforces the importance of giving support, especially appropriate academic advising, to
returning-to-college veterans (Evans et al., 2015).
4.1 Limitations and Future Research
This research has limitations. One is the threat to internal validity, i.e., other explanations for the results found
(Stevens, 1996). Several issues which affect internal validity include: history; maturation; subject selection bias;
and instrumentation (Stevens, 1996). As an example of history, we don’t know the job history of participating
veterans. We only asked if they were currently searching for a new paid work situation. Maturation is an issue
because of the respondent heterogeneity in age, although age only showed a significant relationship to the
burnout dimension of depersonalization. For selection bias, participants self-selected into taking the survey,
based on prior experience with some type of traumatic event. The authors approached different organizational
sources, but had no control over which participants took the survey. Furthermore, the economic reward of
multiple cash gift card drawings had an adverse effect and contributed to 21% of the sample only filling out a
few survey items (over 90% missing data) to then gain gift drawing eligibility. The data from these participants
had to be discarded. This further reduced the already smaller sample sizes of combat and non-combat veterans.
Instrumentation is important to note. Collecting all the data at once in a survey limits causal inference. Both the
active job search and currently going to school items were asked in a Yes-No format. This dichotomous
measurement limited the data analyses that could be done with both. Although the short-form version of the
Maslach scale has been successfully used (McManus et al., 2004), a longer version measure of burnout (Maslach
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& Leiter, 1997), as well as general exhaustion (Moore, 2000), might have affected the results found. All
measures were self-report so method bias is a concern. However, the one-factor test results showed that when
using all items in a principal components analysis (PCA), eight factors had an eigenvalue of over 1 and the first
factor accounted for only 20% of the total variance. Therefore, if this first factor measures method bias, it is not a
severe limitation (Podsakoff, MacKenzie, Lee & Podsakoff, 2003).
5. Conclusion
This study’s goal, i.e., pursuing the specific role of furthering one’s education as a pathway to help job-searching
US military veterans in their transition to civilian life, was unique in the sense of little prior research. As such the
results found are in need of follow-up to test the generalizability of these initial findings. Future military samples
measuring veterans going back to school to further their education would ideally have more heterogeneous
demographics, e.g., gender, race, branch of service, as well as investigating type of college major pursued.
Distinguishing between officers versus enlisted personnel transitioning to civilian life would also be useful (Pew
Research Center, 2019). The findings here also draw attention to less satisfied (greater perceived burnout)
veterans being more active in their job search. This points out the importance of veterans not only being ready
for their first civilian job when leaving the military but also for successive civilian jobs if/when necessary.
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