Senior Seminar—Capstone ECNU692

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Senior Seminar—Capstone
ECNU692
Group Project
 

  1. From the Syllabus…

 
The group presentation project requires each group to identify a Nobel Laureate economist and work together to identify key contributions to the body of economic knowledge:  this requires the review and analysis of the economist’s major works (beginning with their acceptance speech:  http://nobelprize.org/nobel_prizes/economics/laureates/
 
Each group member should prepare a 5-7 page summary write-up of their findings and each group should present their collective findings in a PowerPoint presentation on the groups’ assigned presentation session.   The goal of the exercise is to identify (and understand) the theoretical and empirical contributions (“the ivory tower”) so to APPLY them to a subject area of importance (for example, the game theory of Schelling to nuclear disarmament).

  1. List of relevant Nobel Laureates…

 
2007
Maskin
“for having laid the foundations of mechanism design theory”
 
2005
Schelling
“for having enhanced our understanding of conflict and cooperation through game-theory analysis”
 
2001
Akerloff and Stiglitz
“for their analyses of markets with asymmetric information”
 
1998
Sen
“for his contributions to welfare economics”
 
1997
Merton and Scholes
“for a new method to determine the value of derivatives”
 
1996
Vickrey
“for their fundamental contributions to the economic theory of incentives under asymmetric information”
 
1994
Nash
“for their pioneering analysis of equilibria in the theory of non-cooperative games”
 
1992
Becker
“for having extended the domain of microeconomic analysis to a wide range of human behaviour and interaction, including nonmarket behaviour”
 
1991
Coase
“for his discovery and clarification of the significance of transaction costs and property rights for the institutional structure and functioning of the economy”
 
1990
Markowitz, Miller, Sharpe
“for their pioneering work in the theory of financial economics”
 
1988
Allais
“for his pioneering contributions to the theory of markets and efficient utilization of resources”
 
1987
Solow
“for his contributions to the theory of economic growth”
 
1985
Modigliani
“for his pioneering analyses of saving and of financial markets”
 
1982
Stigler
“for his seminal studies of industrial structures, functioning of markets and causes and effects of public regulation”
 
1975
Koopmans
“for their contributions to the theory of optimum allocation of resources”
i
DEFENSIVE PESSIMISM AND CONCEALED CARRY OF WEAPONS ON
CAMPUS: CAUSE FOR CALM OR CONCERN
A dissertation submitted
by
R. BRIAN WRIGHT
April, 2014
to
School of Organizational Leadership
UNIVERSITY OF THE ROCKIES
Upon the recommendation of the Faculty and the approval of the Board of Trustees, this
dissertation is hereby accepted in partial fulfillment of the requirements for the degree of
DOCTOR OF PSYCHOLOGY
Approved by:
________________________
Dr. Eszter Barra-Johnson, PhD
Committee Chair
Committee Members:
Dr. James Castleberry, JD, PhD
Dr. Ronald Curtis, EdD.
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ii
Copyright © by
R. Brian Wright
2014
iii
Defensive Pessimism and Concealed Carry of Weapons on Campus:
Cause for Calm or Concern
by
R. Brian Wright
Abstract
Acknowledging that lower level needs must be met before higher level needs can be
pursued, based upon Maslow’s theory of the Hierarchy of Needs (Maslow, 1943); the issues
of personal safety in educational settings are addressed. In a relatively stable society marked
by occasional acts of violence on college campuses, how can an individual meet his or her
basic psychological needs for safety and yet still pursue the higher-level goal of obtaining an
education in a face-to-face setting? Could the support of Concealed Carry Weapons (CCW)
be a solution? The current research proposes that Defensive pessimism, a cognitive coping
strategy, provides the bridge that completes Maslow’s hierarchy of needs for some
individuals. It was hypothesized that defensive pessimism, fear, and responsibility are
correlated with the decision whether to support or deny CCW on campus. The Defensive
Pessimism Questionnaire (Norem, 2002), the Fear Questionnaire (Antony, Orsillo, &
Roemer, 2001), the Responsibility Attitude Scale (Antony et al., 2001), and a simple “yes or
no” question concerning support of CCW on campus were utilized to test the proposed
hypothesis. One hundred sixty-nine participants were included in the sample taken from a
small Liberal Arts college in Virginia. A quantitative research methodology was applied.
The data did not show a significant correlation between support for CCW on campus and
defensive pessimism or responsibility. However, a relationship between fear and support for
CCW was indicated. Additionally, a weak relationship between support for CCW and
iv
defensive pessimism appeared to be possible. The relationship between the support of CCW
and Fear and Defensive Pessimism did indicate potential for future research.
Key Words: Defensive Pessimism, Fear, Responsibility, Concealed Carry Weapons
v
TABLE OF CONTENTS
I. INTRODUCTION…………………………………………………………………………………………1
General Statement and Background of Study………………………………………………….4
Additional Background………………………………………………………………………………11
Statement of Problem…………………………………………………………………………………13
Importance of the Study……………………………………………………………………………..13
Purpose of the Study ………………………………………………………………………………….14
Research Overview ……………………………………………………………………………………16
Overview of Research Design …………………………………………………………………….16
Assumptions and Limitations ……………………………………………………………………..19
Summary………………………………………………………………………………………………….20
II. REVIEW OF LITERATURE……………………………………………………………………….22
Search Strategy …………………………………………………………………………………………23
Review of Literature and Research………………………………………………………………23
Virginia Takes the National Stage ……………………………………………………………….26
The Law School Difference ……………………………………………………………………33
A New National Psyche …………………………………………………………………………33
The Debate Begins………………………………………………………………………………..34
Debate Continues………………………………………………………………………………….36
Defensive Pessimism: The Positive Power of Negative Thinking?…………………..41
A Closer Look at Defensive Pessimism……………………………………………………48
A Divergent View of Defensive Pessimism ………………………………………………….60
The Role of Fear ……………………………………………………………………………………….62
vi
Responsibility as a Factor…………………………………………………………………………..64
Summary………………………………………………………………………………………………….68
III. METHODS ………………………………………………………………………………………………69
Methodology…………………………………………………………………………………………….70
Procedure …………………………………………………………………………………………………71
Population and Sample ………………………………………………………………………………77
Ethical Concerns……………………………………………………………………………………….78
Pilot Study………………………………………………………………………………………………..78
Data Collection …………………………………………………………………………………………79
Data Analysis……………………………………………………………………………………………80
Summary………………………………………………………………………………………………….83
IV. RESEARCH FINDINGS……………………………………………………………………………85
Pilot Study Results…………………………………………………………………………………….87
Data Analysis……………………………………………………………………………………………88
Analysis Conclusions…………………………………………………………………………………91
Assessment of Defensive Pessimism Scale 1-3……………………………………….92
Assessment of FQ 17 …………………………………………………………………………..92
Assessment of FQ 16 …………………………………………………………………………..93
Assessment of RAS……………………………………………………………………………..93
Assessment of Demographics……………………………………………………………….93
Summary………………………………………………………………………………………………….94
V. REVIEW………………………………………………………………………………………………….96
Findings……………………………………………………………………………………………………99
vii
Interpretation and Findings……………………………………………………………………….100
Defensive Pessimism Scale…………………………………………………………………101
FQ17 ……………………………………………………………………………………………….101
FQ16 ……………………………………………………………………………………………….102
RAS…………………………………………………………………………………………………102
Demographics…………………………………………………………………………………..102
Limitations of the Study……………………………………………………………………………103
Implications…………………………………………………………………………………………….105
Future Research ………………………………………………………………………………………106
Discussion………………………………………………………………………………………………107
REFERENCES …………………………………………………………………………………………….109
viii
LIST OF TABLES
Table 1: Criterion and Predictor Variables Defined ……………………………………………17
Table 2: Divergent and Convergent Correlates of the Defensive Pessimism
Questionnaire (DPQ)………………………………………………………………………..55
Table 3: Criterion and Predictor Variables………………………………………………………..72
Table 4: Demographic Variables……………………………………………………………………..74
Table 5: Utilizing Linear Regression an Association can only be Established
in Relation to the FQ17 Category Significant at the Extremes of the
Response Scale ……………………………………………………………………………….95
ix
LIST OF APPENDICES
Appendix A: Consent Form……………………………………………………………………………117
Appendix B: General Statement/Demographics……………………………………………….119
Appendix C: Defensive Pessimism Questionnaire ……………………………………………120
Appendix D: Fear Questionnaire ……………………………………………………………………121
Appendix E: Responsibility Attitude Scale ……………………………………………………..123
1
CHAPTER I: INTRODUCTION
Maslow proposed his Hierarchy of Needs theory in 1943. He proposed that human
beings have various basic and intrinsic psychological requirements. These requirements are
categorized by their importance for human survival and satisfaction. Frequently depicted as
a pyramid, the need for safety is found at the base of this hierarchy (Maslow, 1943). As
humankind advances and stabilizes, safety continues to be an important factor in the pursuit
of higher level needs. It is only when basic needs are met, including safety, that higher levels
can be attained. Personal safety has become a concern for many in the United States. Part of
this has been attributed to an increase in gun violence (Lucas & Molden, 2011). In fact,
information recently released by the Pew Research Center (PRC, 2013), indicated there has
been a distinct change since 1999 in the reasoning offered for gun ownership in the United
States (PRC, 2013). The PRC made this determination by comparing two studies. A
February 2013 study of 1,504 adults (a change of 2.9% from the 1999 number of
participants) utilized the same instrument of measure employed in a 1999 study (PRC, 2013).
In 1999, 49% of respondents indicated that they owned a gun specifically for hunting
purposes (PRC, 2013). Only 26% of respondents in the same study indicated they
maintained a firearm for protection purposes. In the February 2013 study, the PRC found a
reversal of these trends. The percentage of those who reported owning firearms for
protection increased by 22% to an overall 48%. The number of respondents who reported
owning firearms for hunting saw a decrease of 17% to an overall 32%. Likewise, the PRC
found a slight decrease in the number of respondents who claimed to have owned weapons
for target or sport shooting, Second Amendment issues, and collecting. Protection
(i.e., safety) of self or loved ones became the number one reason to own a firearm.
2
Interestingly, of those who reported they did not own fire arms, the PRC found that 58%
cited concerns about safety as a determining factor in keeping guns out of their homes. This
is compared to 26% in 1999. Safety was obviously a concern from both points of view.
Additionally, according to the PRC, 58% were very concerned that the federal government’s
current move toward more restrictive gun laws would make it more difficult for individuals
to access fire arms and ammunition to protect themselves. The counter view, in households
that did not own fire arms, the PRC (2013) reported that 66% believed stricter gun laws
would prevent events, such as mass shootings. Gun owners did not concur. According to the
PRC, only 35% of gun owners believed stricter laws would prevent deaths caused by mass
shootings.
As the PRC (2013) pointed out, 37% of U.S. households owned firearms.
Approximately 79% of those reported that gun ownership makes them feel safer.
Additionally, 78% reported a sense of enjoyment from gun ownership. From the same group
of respondents, only 16% reported being uncomfortable having a gun in the household while,
for those households with no gun ownership, 40% reported they would be comfortable with a
gun in their household (PRC, 2013). When broken down across gender lines, 49% of males
in households with no gun ownership indicated they would be comfortable with a gun in the
household. In comparison, only 33% of women in households with no gun ownership
reported they would be comfortable with a gun in the household.
The PRC (2013) data indicated that even among households not owning any guns,
guns could be associated with a sense of safety. Similarly, when addressing CCW on college
campuses, Bouffard, Nobles, and Wells (2012) indicated that one possible reason for high
support for CCW among criminal justice majors could lie in the fact that they already see
3
themselves as responsible for the safety of those around them. Guns are a means to this
safety. By looking at college student support of CCW by academic major, the PRC offered
data to underscore the common denominator of safety as a potential interpretation of CCW as
a means of positive support. As indicated above, the major reason gun owners provide for
owning a weapon was concern for safety. Safety was the main reason non-gun-owners
provided for not owning fire arms according to the PRC. Thirty-nine percent of those
surveyed indicated the reason they would be uncomfortable was the risk of an accident,
including 29% who specifically mentioned concerns about children. Another 22% expressed
more general concerns about the dangers of gun ownership (PRC, 2013). According to
Bouffard et al., the same could be said of some students who seek CCW and see themselves
as responsible for the safety of those around them. Regardless of the reason, guns are viewed
through very subjective lenses and are generally, based upon PRC’s research, placed into two
categories. They are either a positive or a negative component in an individual’s overall
sense of safety.
Such concern does not necessarily represent a regression on Maslow’s Pyramid of
Needs, but it does represent a blurring of the lines between certain stages. For the purposes
of this study, the lines between the base level of safety and higher levels of cognition appear
to be in a state of fluctuation. This was particularly true on university and college campuses
in the United States based upon acts of mass violence, such as the shootings at Virginia Tech
(Virginia Polytechnic Institute and State University) and Northern Illinois University. This
study focused on the subject of safety within such an environment.
Just a decade ago, such a study may have seemed alarmist in nature, but as the PRC
(2013) indicated, attitudes on this subject have changed. Historically, United States’ higher
4
education was seen as a bastion of isolation. Overt acts of deadly violence were nearly
unheard. As an example, Roark (1987) provided a snapshot into life on U.S. campuses of
higher education in the latter half of the 20th Century. According to the author, criminal acts
of concern did occur during this time period. However, as addressed by the author, these
involved what could be viewed as mild, based upon current definitions. In fact, Roark used
the term violence to refer to the most frequent acts seen in the latter half of the 20th century.
“Most commonly, rape, assault, harassment, and hazing” were issues of great concern at the
time of the author’s research, though she does mention the fact that “murder [was] not
unknown” (Roark, 1987, p. 367). However, the act of murder was apparently viewed as
quite uncommon. As of this writing, that same form of violence, murder, was of greater
concern as it had become much more familiar in the years following Roark’s writing.
Violence seemed to permeate life, particularly in the United States in the 21st century, a
century in its brief existence that was marked by turbulence and terrorism both foreign and
domestic. This raised new questions as to how one was to remain safe while still pursuing
higher-level goals. Living on a college campus and getting an education was an example of
trying to achieve a higher goal.
General Statement and Background of Study
According to Roark (1987), college campuses are viewed as microcosms reflecting
society as a whole. In other words, if society becomes more violent, one can expect the same
of the nation’s college and university campus populations. Germana (2007) emphasized this
point. The author, though writing about self-actualization, indicated that Maslow believed in
“a sine qua non of creativeness” (p. 67) that is translated as “a fusion of person and world”
(p. 67). Best, Day, McCarthy, Darlington, and Pinchbeck (2008) emphasized that Maslow,
5
even though he was the creator of the needs hierarchy, was often more interested in the
higher end needs of human experience and how they related to his apex of self-actualization.
However, if one were to accept the emphasis that the environment does impact the
individual, then the same approach can be applied to Maslow’s base needs in addition to his
pyramid’s peak. In fact, Maslow (as cited by Best et al., 2007) wrote of the higher needs:
If all other needs are unsatisfied, and the organism is then dominated by the
physiological needs, all other needs may become simply non-existent or be pushed
into the background. It is then fair to characterize the whole organism by saying
simply that it is hungry, for consciousness is almost completely preempted by hunger.
(p. 306)
In other words, according to Brown and Cullen (2006), until lower or base needs are met,
higher needs cannot be realized. The same can be argued for belongingness/love, esteem,
and, in particular, cognition as they relate to level two of Maslow’s hierarchy of needs, safety
(Brown & Cullen, 2006).
According to Rollings (2010), who cited Soden, 2006; Colaner, 2006; Graveline,
2003; and Fisher and Smith, 2009, college and university campuses have been seen as “Ivory
Towers” (p. 1) where students are “insulated from the community and protected from hurt,
harm, and/or dangers” (p. 1). This no longer necessarily holds true. Similarly, much
research has gone into why certain individuals become violent in various situations and
settings. From a sociological point of view, as Staub (2003) indicated in a study of mass acts
of violence, society offers insight. As the author pointed out, all societies can be divided into
“us” and “them” (p. 791) components. These monikers imply that there is an imbalance–real
or perceived–between two groups. The “them” group feels “devalued” (p. 792) in one way
or another. As Staub discussed, this equation can be used to define intra-societal violence.
When applied to a college or university campus setting, this argument remains true.
6
Perpetrators of violence often claim retaliation for some perceived discrepancy. It could be
argued that in a college and university setting, such a feeling could be attributed to feelings
discussed by Staub. These can include individual situations such as bullying to an outright
sense of being socially oppressed. This said, all of the injustices of the overall society could
also be found intensified within the nation’s college and university campus societies. In fact,
such an assumption seems perfectly logical. However, as Roark (1987) discussed, there is an
opposing point of view.
As previously indicated, Roark (1987) wrote that violence on campus was a growing
area of concern. She also noted that “it seems to many student affairs professionals that there
is an increase in violence on campus” (Roark, 1987, p. 367). However, despite the clear
pronouncement, the author indicated that such a straightforward interpretation was debated.
In other words, this was an assessment that was tempered with theory and not necessarily
with reason. According to the author, some student affairs professionals saw the data, which
reflected an increase in violence, as simply the result of greater awareness as well as
enhanced documentation procedures when incidents of violence occurred. This is an
important statement of differentiation between campus violence in the 1980s and campus
violence that garners national and international attention in the early 21st Century. Such an
interpretation did not necessarily hold true then, and it does not currently hold true. Citing
Hanson, Turbett, and Whelehan (1986), Roark (1987) wrote, “Interpersonal violence is
underreported, underprosecuted, and underpunished, thus allowing it to occur in secrecy,
ignorance, and shame” (p. 367). In other words, crime on campuses was often “hidden” and
even “denied” (Roark,
p. 367). While this tendency to embellish campus safety may still be exhibited by college
7
administration in some cases, and, to a certain extent, concerns of overt violence in society
and on college campuses has been steadily increasing (Nyland, Forbes-Mewett, &
Marginson, 2010).
The question thus arises–how can an individual with elevated safety concerns
function and move upward on the hierarchy of needs within such a setting? How does an
individual continue to climb Maslow’s pyramid without becoming obsessed with safety
concerns in such a situation? Noltemeyer, Bush, Patton, and Bergen (2012) discussed this
point in a study involving 390 secondary school students in a Mid-western state. They used
Maslow’s own words to begin their argument:
It is quite true that man lives by bread alone–when there is no bread. But what
happens to man’s desires when there is plenty of bread and his belly is chronically
filled? At once other (and “higher”) needs emerge and these, rather than
physiological hungers, dominate the organism. And when these in turn are satisfied,
again new (and still “higher”) needs emerge and so on. This is what we mean by
saying the basic human needs are organized into a hierarchy of relative prepotency.
(pp. 1864-1865)
Noltemeyer et al. (2012) indicated that Maslow theorized, at any given time, any need
can take priority. In addition, “It is possible for an individual to be motivated by multiple
needs simultaneously” (p. 1863). In their own study, the authors addressed such a scenario
as it related to secondary school students. They indicated, based upon Maslow’s work, if socalled
“deficiency needs” (lower level needs) have been met, one cannot preclude them from
becoming an issue again. When this happens, the individual in question might not be able to
perform at peak capacity in relation to the hierarchy of needs and the journey toward higherlevel
goals.
Using the same secondary school students study as a model, Noltemeyer et al. (2012)
stated such an argument was valid. They argued that all students in the nation’s school
8
system are expected to maintain a certain academic level despite what may be occurring with
their base or deficiency needs. The authors indicated that such a theory was quite useful in
explaining why some children failed to perform as expected. However, they also indicated
that research into this theory was weak. Noltemeyer et al. indicated that the idea of
underperformance of students with basic needs issues was widely accepted despite the lack
of data to support the theory. In reviewing 14 studies, Noltemeyer et al. reported that Wahba
and Bridwell (1976) found only partial or incompatible data to validate the theory of poor
performance related to needs issues. However, more recent research (as cited in Noltemeyer
et al., 2012) has shed new light.
Noltemeyer et al. (2012) reported that such studies have found limited evidence
supporting performance linked to Maslow’s hierarchy of needs. The authors indicated that
the theory concerning performance and hierarchy needs is often impacted by socioeconomic
status. In particular, this held true of secondary school students in the lower socioeconomic
realm when compared to middle socioeconomic bracket students. “However, the researchers
did not find that cluster analysis showed the concepts were unitary” (p. 1863). In a survey
study, Acton and Malathum (2000; as cited by Noltemeyer et al., 2012) cited a report that a
relationship between Maslow’s needs hierarchy and health concerns was present. In
discussing individuals who were high in physical, love and belonging, and self-actualization
needs, Acton and Malathum (as cited in Noltemeyer et al., 2012) found that such individuals
made positive life choices regarding their physical health and wellbeing. In a study
involving 166 undergraduate college students, the authors found that basic level needs do
have an impact on student well-being. In the case of Lester et al. (1983; as cited by
9
Noltemeyer et al., 2012), basic needs satisfaction was related to their specific realm of study
and level of psychological health.
Studies related to Maslow’s upper level hierarchy needs and children’s academic
success were even more limited in number. According to Noltemeyer et al. (2012), they
were only able to find one study related to the subject. This was a study by Smith, Gregory,
and Pugh (1987; as cited by Noltemeyer et al., 2012). This particular study investigated
students’ needs in relation to four of Maslow’s hierarchical levels: security, love/belonging,
esteem, and self-actualization. The fact that security was one of the needs addressed in
academic success gives credence to the proposed study of CCW and the need for safety in a
higher education setting. Noltemeyer et al. also pointed out that there was already a wellestablished
link between academic success and very basic needs, such as food and housing,
in young students.
For example, Smith, Brooks-Gunn, and Klebanov (1997; as cited in Notlemeyer et
al., 2012) wrote that familial poverty had a direct impact on “child cognitive abilities and
academic achievement” (p. 1863). This stood true even when controlling for family
structure. Additionally, schools with fewer resources also had a similar impact. Notlemeyer
et al. highlighted studies by Bean, Bush, McKenry, and Wilson (2003) as well as Anderson,
Lindner, and Bejinion (1992) involving adolescents, positive familial support, and academic
success. Both variables, cognitive abilities and academic achievement, were positively
related to academic success. Interestingly, one of the components addressed by Anderson et
al. (1992) was the absence of conflict. Of course, this was viewed in terms of intrafamilial
conflict and belongingness as related to academic success. This could also be viewed as a
safety issue with bearing on the proposed research.
10
Notlemeyer et al. (2012) also directly addressed the role of safety on the academic
success in their study of secondary school children. The authors addressed the issue of safety
from a health perspective while recognizing that little research exists into this particular
arena. Kitzman et al. (2010) is an exception according to the authors. As cited in
Notlemeyer et al., Kitman et al. researched home nurse visits and the academic success of the
children visited.
They found the children of parents who had been visited by nurses, compared to a
control group who did not receive such visits, scored higher on individuallyadministered
reading and math achievement tests and scored higher on groupadministered
reading and math standardized tests during their first six years of school.
(p. 1863)
Despite such results, Notlemeyer et al. (2012) indicated that a significant percentage
of school-aged children have a deficiency as related to Maslow’s needs hierarchy. In
particular, the authors noted that what is not understood is how physiological needs, safety
needs, and love/belonging needs actually relate to each other and how they relate to an
individual’s academic success. They also indicated that it is unclear whether Maslow’s
hierarchy of needs can be used as an empirically supported theory for supporting such a
hypothesis. Research has not yet examined the dependency between certain deficiency needs
(e.g., physiological, safety, and love/belonging needs) and definite growth needs (e.g.,
academic and cognitive outcomes). The authors indicated that such research could help
further clarify Maslow’s theory while shedding new light on areas of need so students’
academic careers can be enhanced.
Notlemeyer et al. (2012) found similar results in their own research. They indicated
that their study offered “some support for Maslow’s assertion that growth needs such as
academic progress may be positively related to improvements in deficiency needs such as
11
safety and love/belonging” (p. 1866). This is the basic theory suggested by the presented
research. Perception of personal safety is a real safety need. In an environment in which
violence has increased, how do individuals with specific safety needs deal with growth needs
in an academic setting? Could individuals in question employ Defensive Pessimism, a
particular cognitive coping strategy, in the pursuit of such a higher need?
Additional Background
The 2012 Trayvon Martin case (and 2013 verdict) in Florida highlighted a change in
thinking in the United States that brought personal safety to the forefront (Bellin, 2012). The
case involved the death of a 17-year-old African American adolescent at the hands of an
armed community watch volunteer who claimed he feared extreme bodily harm at the hands
of the adolescent as the result of an altercation between the two. In response to the case,
angry protests occurred around the nation as the community-watch volunteer ultimately used
deadly force against the unarmed Martin. At the center of the issue was a Florida law known
as stand your ground (Fla. Stat. §§ 776.012, .013, .032, 2005). As Bellin pointed out, the
stand your ground laws allow an individual to use deadly force against another person if the
individual perceives a deadly threat. This principle stands true even if the perception of
threat is later determined to be erroneous (Bellin, 2012).
This legal stance represented a major shift in Florida law as well as nearly half of the
50 United States (Bellin, 2012). Prior to 2005, Florida residents had a duty to retreat when
met with a threatening situation. In other words, the administration of deadly force was an
option to be used only as a last resort. As Bellin indicated, there has been a long-standing
exception to this standard in the nation. This exception has been known as the Castle
Doctrine. This doctrine allowed individuals who faced violence on their own property to
12
react with violence, without the duty to retreat. In other words, they were allowed to stand
their ground. Understanding this legal evolution from the Castle Doctrine to stand your
ground is necessary in appreciating how such a dichotomy in the law could have developed.
In the first 10 years of the 21st Century, a decade marked by terrorist activity and
national violence, the legal necessity of the duty to retreat was reconsidered. As a result,
perceiving a threat of violence, or a potentially deadly altercation, became enough to justify
armed intervention in many states. Thus, when such violence occurred, it then became the
burden of the prosecution to prove the assailant did not perceive such a threat (Bellin, 2012).
Such endeavors became “a heavy burden” (Bellin, 2012, para. 12) as the prosecution was
then expected to “prove” the defendant’s state of mind. This was born out in the jury’s
decision in the George Zimmerman trial. Zimmerman was the armed community watch
volunteer who fatally shot Trayvon Martin. Zimmer was found not guilty by a Florida jury
because of the stand your ground law (Jonsson, 2013).
The purpose of the study was not to debate the Trayvon Martin case, nor was it to
discuss the duty to retreat. Rather, it is presented as an example of the extremes in a
changing national environment concerning firearms and their proper place. It serves to
highlight the concept that firearms, safety, and the theory behind Maslow’s needs hierarchy
could be applicable to college campus violence. The specific purpose of the work was to
attempt to determine why individuals, within certain perimeters, would support a policy
condoning CCW on a college campus, a practice that increased in the overall society by a
factor of six since the 1980s (Stuckey, 2010). According to Cola (2007), from 2007 to 2008,
Ohio’s concealed carry weapons increased by 53%. Oklahoma saw its number of CCW
13
permits increase by a factor of two from 2007 to 2008. In Utah, the number increased from
2,548 in February 2008 to 10,878 by 2009.
Statement of Problem
As Taylor (2008) pointed out, over 20 years of effort have been dedicated to
protecting students in an academic setting. Despite these efforts, violence remains. Despite
these efforts, violence has increased. Citing the California Department of Education (2003),
Taylor indicated that safety, insulation from violence, has supplanted the primary goal of
education as students and faculty can be distracted if they feel unsafe. Baker and Boland
(2011) reaffirmed this ideology. The authors acknowledged that students neglect their
studies out of fear for personal safety. The same issue has plagued faculty and staff as well.
Such changes have been documented by other means. As addressed above, the PRC
(2013) saw marked changes in the number of gun owners claiming ownership for personal
safety. In the past, this was not the case. The PRC (2013) found other reasons outranking
safety when legitimizing weapons ownership. Looking at safety from a Maslovian
perspective, as a basic need that must be satisfied in order to attain higher pursuits, the issue
of gun violence becomes a viable area of study. One area in particular is within higher
education.
Importance of the Study
Little information exists regarding a possible correlation between guns and cognitive
coping strategies. Currently, a psychological scale to measure anxiety, fear, or any other
construct related to guns does not exist. This study provides insight into the psychological
(cognitive and emotive) aspects of support for firearms. In addition, the study adds to the
body of research concerning the role of fear in attitudes.
14
The study may also serve as a guide for colleges and universities in the modern era.
With college tuition at traditional schools climbing higher and higher, students will seek out
the situation that is best for them. Additionally, if safety is an issue for students on
traditional campuses, safety could become as important a selling point as prestige when
recruiting students. Enhanced campus environments (knowing they are not defenseless
against armed intruders) will benefit students as they explore educational venues. This is
especially true as online education becomes more widely accepted as an alternative to
traditional brick and mortar schools. Put simply, if students do not feel safe in brick-andmortar
schools, this may impact their ability to excel.
Purpose of the Study
This study was designed to quantitatively determine if support for concealed carry
weapons (CCW) on campus could be determined by individual levels of a cognitive coping
strategy known as defensive pessimism, individual fear, and responsibility in subjects. A
quantitative design allowed for the testing of cause and effect using specific measurement
tools and correlational statistical outcomes in this narrowly focused study. Assessing 169
students on a rural Virginia private Liberal Arts college campus accomplished this goal. If
causation, or even a correlation, between coping strategy, fear, responsibility, and CCW
support on campus was established, researchers may gain a better understanding of the role
firearms play in the United States, as well as a broader understanding of how needs are
placated and pursued within Maslow’s hierarchy.
It was unclear whether a specific cognitive coping strategy, level of fear, and assumed
responsibility were correlated with support for the presence of firearms. The study was
designed to determine whether a correlation between support for CCW on campus, defensive
15
pessimism (as a cognitive coping strategy), and the variables of fear and responsibility
existed. The predictor variables addressed included responsibility attitudes as reflected by
the Responsibility Attitude Scale (RAS). Fear was measured using the Marks and Mathews
Fear Questionnaire. Defensive Pessimism, as addressed in Norem’s (2001) revised
Defensive Pessimism Questionnaire, was used to determine whether an individual was a true
defensive pessimist, a strategic optimist, or whether both strategies were utilized. The
anchoring, or criterion variable, was the study participants’ support or rejection of CCW on
campus. This was determined from participants’ responses to a simple yes or no statement.
The need for this type of research may be debatable. Some may argue that it is
unimportant because many in the United States embrace guns, and these firearms are simply
a part of life in the United States. An assertion could also be made that the law of the land
protects gun owners; therefore, the number of, and support for, firearms will not be
decreasing in the foreseeable future. However, debating support for firearms was not the
purpose of this study. This study was designed to determine whether coping strategy
(defensive pessimism), level of fear, and level of responsibility create an internal need for
safety that included support for CCW.
Wendell Phillips, a 19th
-century attorney, once said, “Law is nothing unless close
behind it stands a warm living public opinion” (Singh, 2013, para. 19). This sentiment
seemed to stand true for guns in United States’ society. It also seems to explain why the
argument for CCW on campuses remained alive, and even supported, by such legal
components as stand your ground, even though widespread implementation of this policy has
the potential to make the nation a more dangerous place by allowing individuals to, arguably,
16
take the law into their own hands. This researcher proposes that investigation into this realm
could open up a new area of research.
Research Overview
The support of CCW on campus was the keystone of this quantitative correlational
study. Specifically, to what degree does an individual’s level of defensive pessimism, fear,
and responsibility have on such a decision? Levels of defensive pessimism, fear, and
responsibility were weighed against the acceptance or denial of CCW on campus. These
were assessed in terms of the proposed hypothesis (H1) that defensive pessimism, fear, and
responsibility would prove to be significant predictors of the probability that a participant
would support CCW on campus. This stood in direct contrast to the null hypothesis (H0) in
which defensive pessimism, fear, and responsibility would not prove to be significant
predictors of the probability that a participant would support CCW on campus. To achieve
this end, the quantitative research methodology was applied. This was underpinned by a
correlational design. As stated above, the research question that guided this study was: What
are the relationships between the participants’ support for concealed carry weapons (CCW)
on campus and their levels of defensive pessimism, fear, and responsibility?
Overview of Research Design
The research question that guided this study was, “What are the relationships between
the participants’ support for CCW on campus, and individual levels of defensive pessimism,
fear, and responsibility?” The participants were recruited from a small Liberal Arts college
within an hour’s drive of the scene of the nation’s deadliest campus shooting, Virginia
Polytechnic Institute and State University (Virginia Tech).
17
Table 1
Criterion and Predictor Variables Defined
Variable Conceptual definition Functional definition Operational definition
Support for
CCWs on
Campus
Whether or not a participant
supports or opposes CCWs on
campus
One criterion
(response)
variable, classified
into two nominal
categories
Yes = 1 or No = 0, measured with a simple
poll
Defensive
Pessimism
A coping strategy employed
by a participant to prepare for
any event perceived as
stressful, by which negative
thinking transforms anxiety
into action (Norem, 2002)
One predictor
variable, measured at
the scale level
Measured with 17 items in the Revised
Defensive Pessimism Questionnaire
(Appendix 3). Each item is measured on a 7-
point scale (1, not at all true of me; to 7, very
true of me). Higher scores indicate higher
levels of defensive pessimism. Scores will be
divided into three categories: 22 – 41 will be
considered Strategic Optimists; 42 – 61 will
be viewed as bi-strategists; scores ranging
from 62 – 79 will be considered Defensive
Pessimists. The numeral 1 will represent
Strategic Optimists, 2 will represent bistrategists,
and 3 will represent Defensive
Pessimists.
Fear The extent to which a
participant has feelings of
agoraphobia, social phobia and
blood/injury phobia (Antony et
al. 2001) An additional single
item is added concerning
CCWs in one’s environment.
One predictor
variable, measured at
the scale level
Measured with 17 items in the Fear
Questionnaire (Appendix 4). Each item is
measured on a 7-point scale (1,would not
avoid it; to 8, markedly avoid it). Fear is
operationalized as the sum of the scores for
the three sub-scales (Agoraphobia + Social
Phobia + Blood/Injury Phobia). These scales
are represented by questions 2 – 16 (FQ16).
Question 17 (FQ17) is a specific issue fear
(guns) and is of main interest to this study.
The global phobic distress index (an
anxiety/depression scale) is not utilized for the
purposes of this study.
Responsibility A participant’s tendency to
assume responsibility in
certain areas and situations.
Identifies individuals with
OCD (Antony et al. 2001 ).
One predictor
variable, measured at
the scale level
Measured with 26 items in the Responsibility
Attitude Scale (Appendix V). Each item is
scored on a 7-point scale (1, totally agree; to
7, totally disagree). Averaging the scores for
the 26 items operationalizes the
Responsibility Attitude Scale. Lower scores
represent higher levels of responsibility.
Before a correlational design could be successfully implemented, it was imperative to
explicitly define the criterion and predictor variables, and to explain how the variables were
operationalized. This information was essential to justify the use of appropriate methods of
18
statistical analysis. Accordingly, the conceptual, functional, and operational definitions of
the variables collected by the instruments administered in this study are outlined in Table 1.
The single criterion (response) variable, named Support for CCWs on Campus, had
only two categories, measured with nominal numerical value labels, in a binary format
(Yes = 1 or No = 0). Support for CCWs on Campus was assumed to be a hypothetical
attitudinal response of the participants to three predictor variables, specifically (a) Defensive
Pessimism;
(b) Fear, divided into two categories (FQ16 and FQ17); and (c) Responsibility.
The components of the predictor named defensive pessimism were measured on a
scale from 1 to 7. The variables were added to produce a final unidimensional defensive
pessimism score. The predictor named Fear offered three sub-scales: agoraphobia, social
phobias, and simple phobias. For the purposes of this study, only two were utilized. Fear
was operationalized as the sum of items 2–16 (total phobia scale) offering a unidimensional
variable named FQ16 by the researcher. Additionally, item 17 on the Fear Questionnaire, a
specific phobia statement oriented toward CCW, produced a unidimensional value named
FQ17 by the researcher.
The predictor variable named Responsibility was a unidimensional variable, with
each item measured on a scale from 1 to 8. Averaging the scores for 26 items
operationalized responsibility. This said, the research hypothesis (H1) stated that defensive
pessimism, fear, and responsibility were significant predictors of the probability that a
participant would support CCW on campus (relative to not supporting CCWs on campus).
The Null hypothesis (H0) stated that defensive pessimism, fear, and responsibility were not
19
significant predictors of the probability that a participant would support CCW on campus
(relative to not supporting CCW on campus).
Assumptions and Limitations
The main assumption was that students would be completely honest about their
responses on the various instruments as well as their response to the criterion statement. The
study had limitations. The study took place on a campus that was within a one hour drive of
Virginia Tech, the site of the nation’s deadliest school shooting. An assumption was made
that the affinity many had with the Blacksburg campus did not taint the view of some
students. The subject of gun rights was one of the most debated issues in the nation. There
has been a long tradition of debating Second Amendment rights in this country, and people
have had very strong feelings concerning the expansion or limitation of these rights. This
was especially true in the aftermath of the December, 2012, Newtown, Connecticut shooting
of 20 first graders. The study took place in rural Virginia, where gun ownership and hunting
continued to be a way of life. An assumption was made that this would not impact the
participant responses to the instruments.
Participants for the study were chosen through convenience sampling. As Black
(1999) pointed out, convenience sampling could bias the results as subjects might not be
representative of the population as a whole. This is often because participants are willing to
volunteer to participate. In this case, classes were selected that had a mixture of college
freshmen, sophomores, juniors, and seniors of varying majors to provide a random approach.
As Ferguson (2009) related, in areas that are under-researched, such sampling can help
establish an initial view.
20
Every attempt was made to isolate participants from each other to avoid any
questionnaire response contamination and to prevent potential threats to the validity of the
study. Participants were separated from each other at classroom tables and asked not to
communicate. Materials were fully discussed prior to testing. Any questions were addressed
by the raising of hands. By taking such precautions, keeping the threats to validity at a
minimum, the potential shortcomings associated with convenience sampling might have been
partially overcome. As mentioned above, Ferguson (2009) indicated in areas that are underresearched,
convenience sampling could help establish an initial view. This might help allow
the findings to be generalized to colleges and universities across the nation instead of limiting
the impact of them to the campus in question.
The nature of the design created limitations as well. As Lomax and Li (2013)
discussed, a quantitative correlational design does not allow for tests of “strong casual
inference” (para. 19), meaning a correlation could be indicated that could have other factors
involved that have not been recognized. The authors also indicated that this research
approach could produce statistical linear relationships causing the researcher to miss
relationships that are not linearly indicated. The authors also indicated that multiple
variables may produce a false correlation through simple chance. However, this was not a
concern in this research with limited variables.
Summary
Violence seems to become a common thread of life in the 21st Century. Recent
events of domestic and international violence, including acts of terrorism, brought a new era
marked by turbulence and caution. Recognizing the potential for violence, Maslow’s theory
of the Hierarchy of Needs was employed. Acknowledging that lower level needs must be
21
met before higher level needs can be pursued, the issues of personal safety within a college
environment were addressed. In other words, in a stable society marked by occasional acts
of violence, even on college campuses, how can an individual meet their safety needs yet still
pursue the higher level goal of obtaining an education? The presented research proposed that
defensive pessimism, a cognitive coping strategy, provided the bridge that completed
Maslow’s hierarchy of needs for some individuals by supporting CCW on campus. In other
words, defensive pessimism filled the void on the safety level so that attention could be
placed on a personal growth level (attaining an education). This assumption was not clearly
indicated in the current study.
22
CHAPTER II: REVIEW OF LITERATURE
Deadly violence on school campuses has become an all too common occurrence,
nationally and internationally, in the last 25 years. According to National School Safety and
Security Services (NSSSS, 2010), in the 2009-2010 school year (the most recent year for
which data was available), 11 students died from violent incidents which occurred on school
grounds; of these victims, seven were shot, three were stabbed, and one died from injuries
received in a fistfight. Additionally, there were 33 shootings that did not result in the taking
of a life. NSSSS also reported 82 other incidents. Those 82 incidents included, but were not
limited to, (a) attempted bombings, (b) attempted attacks with swords, (c) an attempted attack
with a chainsaw, and (d) bus hijackings. Additionally, there were gun incidents in which
someone was able to intervene before deadly violence ensued. Of course, the NSSSS
recorded data related to the K-12 programs nationwide during the years indicated above. The
NSSSS did not record violence that occurred on the nation’s college campuses, but the data
indicated the type of violence that had the potential to possibly graduate to the arena of
higher education.
Clint Van Zandt (2010) studied violence on college campuses within the United
States. He indicated that violence dramatically increased on college campuses around the
nation. This was especially true over the last 20 years: 1990-2010. The author reported that
since the year 1900, there have been 272 incidents of what he called “targeted violence”
(para. 1). Of these 272 incidents of violence on college campuses, 60% reportedly took place
since the year 1990; however, nearly 100 of these attacks occurred since the year 2000.
23
Search Strategy
The majority of the information utilized in this study came from searching online
peer-reviewed journals. For instance, EBSCO, PsyNet, ProQuest, University of the Rockies
Library, and the Virtual Library of Virginia resources proved to be invaluable. Campus
violence, violence, Concealed Carry Weapons (CCW), defensive pessimism, feelings of
personal safety and a plethora of other headings were searched using the identified databases.
Additionally, defensive pessimism was discussed with one of its founders, Dr. Julie Norem at
Wellesley College.
Additionally, because the work was theoretically framed by Maslow’s pyramid
theory, extensive research was conducted into Maslow and subsequent researchers. This was
especially true as far as safety issues were concerned. However, with many recent events,
such as the Virginia Tech shooting and the Appalachian School of law shooting, as well as
issues of societal violence in general, mainstream press and contemporary organizations’
websites, including the federal government, were also utilized to help integrate some of the
real world numbers with the theoretical approach presented in peer-reviewed journals. This
being said, information that focused on a sense of personal well-being (i.e., safety) formed
the foundation of the study. Every effort was made to keep the research limited to within
five years of the current date. However, certain seminal works as related to the subject were
addressed from outside that five-year period.
Review of Literature and Research
Because of the researcher’s interest in defensive pessimism, Dr. Julie Norem’s work
proved to have a significant impact on the structure of the current study. Norem (2002)
argued that the concept known as defensive pessimism was a real coping strategy. It allowed
24
anxious individuals to control their anxieties so that they could use it as a tool for progress
instead of allowing it to tear them down. In other words, it was a process that could “aid our
efforts toward self-discovery and enhance[s] our personal growth” (Norem, 2002, p. 3). Put
simply, it addressed anxiety rather than ignoring it. In short, Norem (2002) defined
defensive pessimism as:
the process that allows anxious people to do good planning. They can’t plan
effectively until they control their anxiety. They have to go through their worst-case
scenarios and exhaustive mental rehearsal in order to start the process of planning,
carry it through effectively, and then get from planning to doing. (p. 48)
Levels of defensive pessimism, fear, and responsibility were weighed against the
acceptance or denial of CCW on campus. These were assessed in terms of the proposed
hypotheses (H1) that defensive pessimism, fear, and responsibility are significant predictors
of the probability that a participant will support CCW on campus. This stood in direct
contrast to the null hypothesis (H0) in which defensive pessimism, fear, and responsibility
were not significant predictors of the probability that a participant might support CCW on
campus. To achieve this end, the quantitative research methodology was applied. The
research structure was underpinned by a correlational design.
The overall research question that guided this study was, “What are the relationships
between the participants’ support for CCW on campus, and their levels of defensive
pessimism, fear, and responsibility?” This was a question spawned by the researcher’s
interest in campus violence in his home state. Based upon campus violence in the
Commonwealth of Virginia, the research project became quite clear.
As already stated, research studies into the cognitive process and weapons appeared
to not have been undertaken to any great extent. Nagtegaal, Rassin, and Muris (2009)
studied the link between aggression and guns. They reported that the existing literature was
25
quite broad as far as this relationship was concerned. Nagtegaala et al. (2009) indicated that,
to some, even the presence of firearms was believed to make individuals aggressive.
Referring to the Berowitz’s and LePage’s (1967) famous study, Nagtegaala et al. (2009)
emphasized the finding that study participants who were angry administered a greater
number of electrical shocks to test subjects in the presence of a gun than they did in the
presence or absence of another object. This became known as the weapons effect and
spawned extensive research (Nagtegaala et al., 2009).
Similarly, Nagtegaala et al. (2009) researched a link between aggression and gun club
membership. Their research was born out of a violent incident that occurred in the
Netherlands in April 2004 in which a member of a Dutch gun club opened fire, killing three
before committing suicide. The authors reported that members of mainstream Dutch society
developed the view that gun owners were more aggressive individuals when compared to
average Dutch citizens. The results of a study carried out by the authors utilizing a
nationwide sample of 59 gun club members and 67 control individuals did not support this
hypothesis. The researchers found that gun club members scored differently on both
aggression and aggression-related variables when compared to study controls. Gun club
members scored lower on aggression than did the controls. They also scored lower on
impulsivity and aggressive thoughts when compared to the controls. The conclusion that gun
owners were more aggressive was clearly not borne out by the study conducted by Nategaala
and others.
In addition, Nagtegaala et al. (2009) noted that studies by Bartholow, Anderson,
Carnagey, and Benjamin (2005) indicated that gun owners, especially hunters, had a different
view of aggression when compared to non-gun owners. In contrast, Nagtegaala et al. (also
26
discussed in Huesmann, 1998) theorized that “interacting with weapons increases the chance
of behaving aggressively, due to rehearsal and subsequent activation of a hyperactive
aggressive script” (Nagtegaala et al., 2009, p. 322). From a differing viewpoint, Gleason,
Jensen-Campbell, and South-Richardson (2004), Tremblay and Ewart (2005), and Walker
and Gudjonsson (2006), as referenced by Nagtegaala et al., 2009, reported that a connection
between neuroticism or psychoticism and aggression has been established. Individuals who
are hostile by nature, or very self-oriented (i.e., psychotic), and those who are emotionally
unstable (i.e., neurotic) actually behave more aggressively than the norm. Nagtegaala et al.
(2009), referencing Bartholow et al., 2005, reported that “there may be differences in
underlying knowledge structures, or cognitive scripts, between the two samples” (p. 322).
Defensive pessimism, one such cognitive script, was important to this study’s approach.
Virginia Takes the National Stage
Violence within the state of Virginia also came to bear on the study. As Van Zandt
(2010) mentioned, two of the most glaring incidents of violence in the past decade occurred
within the Commonwealth of Virginia. On January 16, 2002, a 43-year-old student from
Nigeria, Africa, Peter Odighizuwa, went on an armed rampage at the Appalachian School of
Law in Grundy, Virginia. On Tuesday, January 15, Odighizuwa was dismissed from the law
school because of poor performance (Okereke, 2002). On Wednesday, January 16, using a
.380-caliber semiautomatic weapon, Odighizuwa began exacting his revenge. He killed the
Dean of Students, a professor, and a student. Three other students were critically wounded in
the shooting (Okereke, 2002).
According to Okereke (2002) and Kahn (2004), Odighizuwa came to the law school
with a history of mental instability. Lawsuits filed by the families of the victims demanded
27
the school share a portion of the blame. They reasoned that the school was aware
Odighizuwa had a reputation for past violence. An attorney for a group of the victims
reported, “Not only was this situation foreseeable, it was probable, based upon Peter’s
[Odighizuwa] prior conduct” (Kahn, 2004, para. 6). Two years after the shooting, having
been diagnosed with paranoid schizophrenia, Odighizuwa seemed to confirm such suspicions
by stating, “I feel like I’m God sometimes, and I was running demons out of the school. It
was like an exorcism” (Kahn, 2004, para. 3). However, he also added, “The students
shouldn’t get anything from the school. The law school isn’t a psychiatrist. It doesn’t know
what is in my head” (Kahn, 2004, para. 13).
Yet, at the same time, Odighizuwa partially blamed the school for his act of violence.
He indicated fellow students had socially ostracized him. “I wasn’t just shooting all over the
place. I saw the people who were menacing me” (Kahn, 2004, para. 24). Feeling threatened,
Odighizuwa began carrying a concealed weapon (Kahn, 2004). After he finally became
violent, he claimed those who ridiculed him were his targets. The students who were shot
were reported to have been particularly “mean” to him (Kahn, 2004, para. 23). Yet, as he
was shooting those he claimed ridiculed him, he also said he was “taking care” of Central
Intelligence Agency (CIA) agents, Federal Bureau of Investigations (FBI) agents, and
Komitet Gosudarstvennoy Bezopasnosti (Committee for State Security or KGB) agents
(Kahn, 2004, para. 25).
A very similar case of violence occurred in 2007 in Blacksburg, Virginia. On April
16, a young South Korean immigrant student engaged in a massacre. The shooting was
reminiscent of the Columbine High School shooting in Littleton, Colorado, just 8 years
earlier, in which two high school students killed 13 people in a similar manner. Prior to the
28
Virginia Tech shooting, the nation’s most tragic college campus shooting occurred in 1966 at
the University of Texas at Austin when a shooter in a clock tower killed 16 people. In
Blacksburg, 33 people died (including the shooter), and 15 were wounded in a singlegunman
rampage that occurred over two and one half hours following a single shooting
incident from the same gunman much earlier that morning in a campus dormitory. During
what some called the “deadliest shooting rampage in American history,” the perpetrator lined
victims up against a wall and shot them execution style (Hauser & O’Connor, 2007, para. 1,
3).
The shooter was Cho Seung-Hui, a 23-year-old senior at Virginia Tech. Johnson et
al., (2007) reported that Cho was socially inept. In addition, he seemed to have a speech
impediment or a considerable lack of English language skills. In one instance, reported by a
high school classmate, a teacher asked Cho to read aloud in class. After being threatened
with a failing participation grade, Cho finally acquiesced. “As soon as he started reading, the
whole class started laughing and pointing and saying, ‘Go back to China,’ the classmate
reported” (Johnson et al., 2007, para. 7). Similarly, Cho’s classmates in his high school
English classes called him “the Question mark kid,” according to a student (Johnson et al.,
2007). The authors wrote that he earned this moniker because he signed a class attendance
sheet with a question mark instead of his name.
These issues followed Cho to Blacksburg, as some of his high school classmates also
attended Virginia Tech. Prior to the shooting, he reportedly left a message on the dry erase
board of a fellow student’s dorm room door. That message was a simple question mark
(Johnson et al., 2007). In the end, two of the victims of the violence were former high school
29
classmates. In a message left for the press, Cho indicated that the time had come for him
carry out his revenge (Johnson et al., 2007).
As in the case of the Appalachian Law School shooting and Peter Odighizuwa, there
were so-called red flags to Cho’s troubled nature (Johnson et al., 2007). In fact, according to
the authors, multiple entities within the Virginia Tech community raised these red flags. A
Virginia Tech professor had him removed from class because of macabre writing. Two
female students reported him to campus police for allegedly sending them disconcerting
messages. A Virginia magistrate also ordered Cho to submit to a psychiatric evaluation
(Johnson et al., 2007). According to the authors, Virginia Tech had been dealing with
various behavioral issues involving Cho for two years prior to his ultimate act of violence
(Johnson et al., 2007). Still, this did not indicate a potential for violence.
Zhou, Knoke, and Sakamoto (2005) indicated that students from foreign cultures,
including East Asian cultures, find difficulty assimilating into western educational
environments because of cultural and communication barriers. Hodne (1997) wrote from
personal experiences in teaching ESL at the college level. In one example, she asked an East
Asian student about her math class. Particularly, she asked about how she was integrating.
The student responded that she had not met anyone. Instead, the student relayed that “the
Americans all sit and read” (Hodne, 1997, p. 85). Hodne also had a son in the same class.
When she asked her son about student interaction with the Asian students, she was told that
the Asians students isolated themselves and spoke in their native language. This distance,
according to Hodne, has a “dark side.” The author referenced a 1990 report from the
California State University (CSU) system. This study, according to Hodne reported that
students of an Asian Pacific background were the least satisfied of all cultural groups. Citing
30
the Asian Pacific American Education Advisory Committee of 1990, Hodne reported that
“the stress of adjusting to a rigorous academic load is compounded not only by language
difficulties but also by cultural differences, value conflicts, and both subtle and overt racism”
(p. 86). Hodne went on to say such challenges were not specific to California. In
interviewing similar students from Massachusetts, the author indicated that they found US
college classrooms to be places “that silenced them, that made them feel fearful and
inadequate, that limited possibilities for engagement, involvement, [and] inclusion” (Hodne,
1997, p. 86). Additionally, despite superior college performance, students can be viewed as
“less intelligent” (Hodne, 1997, p. 86) if their English language skills are not flawless. The
author also stated that it is, in part, the professor’s role to make such students feel welcome in
a classroom. To fail to do so can create an environment in which the student in question can
view the professor as being prejudiced (Hodne, 1997). She went on to state that “non-native
speakers risk confusion and embarrassment if teachers misunderstand them, and it is even
worse when their classmates misperceive, ignore, or ridicule them” (p. 86). The same may
come from friends and family.
Hodne (1997) told of a Cambodian student. She indicated the man came to her office
where he cried as he told her about a recent telephone conversation. He said that when he
answered the phone the voice on the other end accused him of sounding differently. Hodne
indicated that this was a success to her. “To my American ear, he was simply speaking more
audibly,” she said (Hodne, 1997, p. 89). However, from the caller’s point of view, this was
not so. In using his new American way of speaking, as he had been taught to do, Hodne
indicated that he felt that “he was losing the gentle, soft-spoken voice Cambodian people
cultivate and value” (p. 89). Such friction, as discussed by Wei-Chin and Wood (2009) who
31
were citing Birman (2006), has been linked to mental health issues in the Asian community.
Additionally, the author indicated exactly how these acculturative problems “lead to poor
mental health” (p. 124) is not well understood. Acculturating more quickly, being educated
in the US, and having better English language skills are believed to add to the already
accepted generational gap problems all families experience according to Wei-Chin and Wood
who cited Szapocznik, Santisteban, Kurtines, Perez-Vidal, and Hervis (1984). Despite these
issues, the authors indicated that research has supported increased depressive disorders
amongst Chinese adolescents in the United States. The authors also found research that
supported the idea that when the family adhered to strong mother-culture practices, the youth
in question had greater levels of maladjustment and, according to Wang, Probst, Moore,
Martin, and Bennett (2011), violent disagreement. In a study carried out by Wang et al., this
was especially true in Asian homes where the parent was born in another country. For
students, according to Wei-Chin and Wood, this could mean disagreements over everything
from dating to what to study in school. Additionally, the authors indicated that these
incongruities became greater in adolescence and young adulthood. According to Leung,
Monit, and Tsui (2012), this may have a detrimental impact as Asian youth often prefer to
turn to family members when in need. However, this did not include mental health issues
according to the authors. “In studies of Chinese Americans, help seeking behavior has been
found to be related to ‘environmental or hereditary causes,’ and has seldom been reported as
personal or psychological problems” (Leung et al., 2012, p. 61). Additionally, as the authors
pointed out, Asian Pacific peoples in the US underutilize mental health services. Family and
personal outlets are seen as desirous in certain cases. In dysfunctional family situations this
can be detrimental to the individual in question.
32
Similarly, students also expressed concerns about losing valued culture norms in
learning to fit in within their new environments. Hodne (1997) went on to conclude that the
“American academic culture directly challenges the social ethics that many Asian immigrant
students bring to their American classrooms” (p. 90). There was a distinct alienation. Poon
and Byrd (2013) discussed similar alienation in the 1.5 and second generation Asian youth in
an educational setting. As Zhang and Hong (2013) indicated, as far as Asian students are
concerned, where there is a perception of discrimination, there is also increased levels of
psychological stress. Additionally, discrimination perception and distress was found by the
authors to be greater in the educated. As Bittle (2013) indicated, this can cause Asian
students to feel “invisible in their own schools” (p. 58). According to Bittle, life is made
difficult because the media stereotype of Asians permeated society including the classroom.
Such difficulties put Asian families at risk for internal violence based upon the research of
Kim-Goh and Baello (2008). This violence is underreported, according to the authors. The
same emotional damage studies have shown to have been exacted upon members of other
groups is also exacted upon the Asian family unit; but, as the authors point out, this is an area
that is understudied because of the enduring misconception that Asians are the “model
minority” (p. 647).
This being said, the point of this discussion is not to question the actions of either
school or any of those involved in the cases. It is not meant to question the actions of other
students who could obviously be viewed as bullying. It is not intended to question the
cultural sensitivity of the schools, their professors, or the other students. The point of the
discussion is to use the two examples from Virginia to lay the foundation for an argument
33
that gained momentum around the nation. That argument was the support for CCW on
campus.
The Law School Difference
What many people do not remember about the deadly shooting at the Appalachian
School of Law in Grundy, Virginia, is that an armed student brought Odighizuwa’s actions to
an end. It may never be known whether this action saved lives. However, it is obvious that
the action rendered Odighizuwa’s rampage inert. According to news sources, including the
Associated Press (2002), three former police officers were also students at the small law
school. One of those students retrieved a weapon from his vehicle. According to the news
sources, upon seeing the shooter place his gun on the ground for a moment, the former
officers-turned-students made their move. One of them aimed his weapon at Odighizuwa
(The Associated Press, 2002). The source then reported the three students seized
Odighizuwa. They handcuffed him while awaiting the arrival of law enforcement officials.
A New National Psyche?
In addressing the media viewpoint, the Associated Press (2002) made a noteworthy
correlation between these tragic incidents and the national and international nature of reality
in the 21st century–a reality in which safety concerns were elevated. According to the news
source, in light of the war on terror in which the United States had been involved, aggressive
actions to achieve safety were seen as commendable and even necessary. As an example, the
source highlighted the average citizens who took action on a jetliner that crashed in
Pennsylvania on September 11, 2001. This was a jetliner believed to be targeting the White
House. Passengers who prevented shoe-bomber Richard Reid from carrying out his task
34
aboard another airliner were also mentioned. In fact, the news sources referred to these
individuals as “brave” and as “heroes” (The Associated Press, 2002, para. 4).
The goal of this dissertation was not to determine the impact of the changing national
perception of CCW. Nonetheless, incidents like those described change public opinion and
consequently affect the study of CCW. The overwhelming sense of vulnerability at home
and abroad did come to bear on the way people thought. In Virginia, actions taken shortly
after the Appalachian School of Law shooting reflected shifting attitudes.
The Debate Begins
According to Hall (2002), in Northern Virginia, the George Mason University (GMU)
School of Law’s Second Amendment Group called for an end to the school’s ban of weapons
on campus shortly after the Appalachian law school shooting. Second Amendment Group
president, Orest J. Jowyk, explained, “I think the middle ground is to allow concealed
handgun permit holders to carry just like they can anywhere else in Virginia. You provide
extra safety to the student body that way” (Hall, 2002, para. 3). Jowyk reported that he
moved to adopt such a choice because of the Grundy shooting, but he was specifically
spurred on by the actions of the armed students who confronted the gunman. This pushed
him to challenge the GMU gun ban policy. However, the Chief of Police for the law school
did not agree. He stated that “it is my opinion that that (sic; students carrying guns) would
increase the propensity for somebody getting hurt, and I don’t want to see that” (Hall, 2002,
para. 12). The dilemma about whether or not to allow CCW on campus did not remain
confined to the boundaries of the Commonwealth of Virginia. A similar argument began in
Utah.
35
After the Appalachian School of Law shooting in Grundy, Virginia, the Utah
Attorney General challenged a 25-year-old ban on concealed weapons by the University of
Utah claiming it was in conflict with state law (Hall, 2002). University of Utah President,
Bernie Machen, said the university needed the right to maintain the ban because it helped
foster “a safe learning environment” (Hall, 2002, para. 16). In March 2002, a Republican
sponsored bill moved to cut the school’s administrative budget in half if the gun ban was not
discontinued. The school filed suit in the US District Court and lost (Hall, 2002). Utah
became the only state in the nation to allow guns on all state college and university campuses
(Fennell, 2009).
The reasoning applied in the Utah debate was understandable. According to Fennell
(2009), an act of shooting violence on a college campus was one of the most feared possible
events in academia. This being said, it was not difficult to understand why many states
sought the expansion of Second Amendment rights to include the nation’s college and
university campuses. Additionally, the author cited an article in a 2002 edition of the
Journal of American College Health (JACH), in which a study conducted at 119 colleges
found that 4% of college students already carried a weapon on campus. Fennel noted that,
extrapolating from the 2009 numbers, the expectation of finding 700,000 weapons on those
same 119 college campuses was reasonable. If extended to the nation’s 4,300 colleges and
universities, the number of CCW might exceed 20 million. According to watchdog
organizations Campaign to Keep Guns Off Campus and Coalition to Stop Gun Violence,
both of who reported to the public on an internet site (Armedcampuses.org), after Utah, four
other states joined the list of states that allowed colleges and universities to permit their
students CCW on campus, in some form. Michigan, Colorado, Virginia, and Oregon were
36
among the first to join this exclusive club (“Colleges and Universities that Allow Guns on
Campus”, n. d.; Associated Press, 2012). Michigan did not allow weapons inside campus
buildings, according to the previous sources. A private college, Liberty University in
Virginia, followed Michigan’s example (Associated Press, 2011). However, according to
Fennell, Utah was actually the only state in the US where guns were allowed on all state
property, including college campuses. Citing Lipka (2008), Bouffard et al. (2011) indicated
that state legislatures in Alabama, Georgia, Indiana, Louisiana, Oklahoma, South Carolina,
South Dakota, Texas, and Washington also “initiated attempts to allow students and/or
faculty and staff with appropriate CHL [concealed handgun license] to carry firearms on
campus” (p. 285).
Debate Continues
With this in mind, Drysdale, Modzeleski, and Simons (2010) remarked that college
campuses brought together a combination of life stressors that were not necessarily found in
other environments. As students sought an education, they had to deal with those stressors.
They might have been newly independent. They might have experienced new academic
pressures. At the same time, they might have lived on campus, and that might have added to
the stressors they faced. This created an environment in which, if violence occurred, it would
be similar to types seen in mainstream society (Drysdale et al., 2010). This was especially
true with regard to murder. In most all cases, the victim and the perpetrator knew each other.
In addition, one half of all campus murders were committed with a handgun. What is not
well understood is why. Drysdale et al. (2010) emphasized this point. “Little is known at
this time about the nature and characteristics of murders on campus” (Brumley, 2005, as
37
cited in Drysdale et al., 2010, p. 5). The existence of this apparent gap in understanding
underscored the need for the proposed study.
Citing a 2001 U.S. Department of Education report, in an article titled “Colleges and
Universities That Allow Guns on Campus” (2013), claimed that the anti-gun laws that had
been the norm on the nation’s 4,300 plus colleges and universities have been the reason for
the overall lack of violence on college campuses. For example, the USDE reported that the
rate of murder on college campuses was 0.07 per 100,000 based upon 1999 statistics. In
mainstream society, also according to the USDE, that number was 5.7 murders per 100,000.
For individuals aged 17-29 in mainstream society, the USDE reported the number of murders
was 14.1 per 100,000. The USDE implied that the lack of firearms access was a major
reason behind the low numbers. Yet, when murders did occur on college campuses, firearms
still played a key role. In other words, despite legal bans, guns still claimed lives on the
nation’s college campuses. According to Miller, Hemenway, and Wechsler (2002), in a
study of 10,000 college students, 4.3% of students reported having a functioning firearm with
them on campus. In addition, 1.6% had been threatened with a gun on campus. Also,
“students with guns were more likely than students without guns to have alcohol-related
problems, such as getting into fights attributed to drinking alcohol and being arrested for
drinking while intoxicated” (Miller et al., 2002, p. 57). Clearly, these students engage in
reckless behavior that could pose a threat when a gun was involved.
Despite such data, the debate about CCW on campus was far from over (Fennell,
2009). Opponents feared that the presence of guns on campus would lead to more deaths.
Proponents highlighted the idea that, although guns have long permeated our society,
massacres have very rarely occurred. Fennell stated that the United States, as a society,
38
operated on a “hypothesis based on fear” (p. 100). Based upon this hypothesis, he indicated
he saw no problem with law-abiding citizens carrying CCW on the nation’s campuses.
However, he indicated that in real world settings, this hypothesis of fear might cause
complications. For example, in the event of shootings, such as those at Virginia Tech or the
Appalachian School of Law, multiple problems could arise for a CCW carrier. In particular,
Fennell questioned how law enforcement would be able to distinguish the real perpetrator
from an armed defender. “What if the person was just trying to defend him/herself and was
shot in a case of mistaken identity by the police or another person with a CCW?” (Fennell,
2009, p. 100). With such potential for confusion, the author claimed the best approach, in his
opinion, was to keep firearms accessible, yet keep them out of the hands of those with mental
health issues. If access to firearms was limited, the author says that “Unfortunately, those
with legal concealed carry weapon permits who follow the law will be defenseless to protect
themselves during an attack” (Fennell, 2009, p. 100). Despite potential negative
consequences, support for CCW remained. For example, in a student newspaper at the
University of Wisconsin, Milwaukee, a student wrote an article entitled “9mm is faster than
9-1-1” (Prellwitz, 2011, p. 17).
Such staunch support has been met with a sense of balance. In Oregon, the courts
have ruled that University policy could not circumvent state laws that allowed CCW
(Richardson, 2012). However, the same courts ruled that Universities in Oregon have
sweeping control over their properties. To this end, weapons were denied in buildings and at
any campus event. Additionally, any individuals (including students) who engaged in a
business arrangement with Oregon State University schools could not carry a weapon as a
condition of the contract into which they had entered (Richardson, 2012). As a result,
39
virtually no one could legally carry a weapon on campus unless the carrier was a random
stranger with no connection to the state’s universities or a member of the exempted
university police (Richardson, 2012). Interestingly, as the author pointed out, this approach
might seem to violate the court’s original ruling. However, when legally challenged in a
court of law, these policies were upheld (Richardson, 2012). Virginia faced a similar issue.
Concealed weapons on campuses were legal, but schools could make individual policies that
effectively preclude the presence of CCW in buildings, but not on campuses. Virginia’s
Republican governor, Bob McDonnell, said he would not support any legislation that
tampered with the schools’ individual choices because the system, as it stood, seemed to be
adequate (Sluss, 2012).
As the debate continued, neither side seemed to be backing down. Opponents of
CCW, especially on college campuses, pointed to a study conducted by the Washington, D.C.
based Violence Policy Center. The center compiled data involving crimes in which an
individual with a CCW permit was involved in any way. As of February 16, 2012, legal
concealed carriers had killed 11 law enforcement officers. Additionally, legally permitted
concealed carriers had killed 380 private citizens, carried out 20 mass shootings, and
committed 30 murder-suicides (Violence Policy Center, 2012). The center tracked those
numbers beginning in May 2007 (one month after the Virginia Tech shootings).
Citing the Florida Sun Sentinel, the watchdog organizations Campaign to Keep Guns
Off Campus and Coalition to Stop Gun Violence, reporting on their collective website,
Keepgunsoffcampus.org and Armedcampuses.org found that there were over 1,750 incidents
reported in Florida in which concealed carry permits had been granted to individuals who did
not meet the state’s standards. This number included “more than 1,400 people who had pled
40
guilty, or no contest to a felony; 216 people with outstanding warrants; 128 people with
active domestic violence injunctions; and six registered sex offenders” (“Concealed Carry
Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 4). In Texas, by
conducting four studies, the Violence Policy Center determined that “from 1996 to 2000,
Texas concealed handgun permit holders were arrested for weapon-related offenses at a rate
81 percent higher than that of the general population of Texas aged 21 and older”
(“Concealed Carry Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 6).
Similarly, in Tennessee, watchdog organizations cited a study by the Memphis Commercial
Appeal that found in one county, Shelby County, 70 citizens received concealed carry
permits despite having been arrested for violent crimes (robbery, assault, and domestic
violence). In one instance in Tennessee, a single individual had 25 arrests on record yet still
received a concealed weapon permit. After the fact, the same individual faced federal bank
robbery charges. According to the Memphis Commercial Appeal, “administrative glitches”
in the state’s system caused these occurrences (“Concealed Carry Does Not Reduce Crime
Does Threaten Public Safety”, n.d., para. 8). The Indianapolis Star found 450 such glitches
in two counties as late as 2009. The paper reported, in broad terms, the Star found a system
that breaks down in numerous ways, enabling people with troubled and often violent pasts to
legally keep a loaded gun in their waistbands and on their passenger seats (“Concealed Carry
Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 9). The organizations
went on to state “as more is learned, it becomes absolutely clear that concealed carry systems
do not work as promised but operate to arm and embolden many dangerous individuals”
(“Concealed Carry Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 9).
Similarly, Sulkowski and Lazarus (2011), writing for the Journal of School Violence,
41
reported that in order to maintain safe campuses, schools needed to develop a system devoid
of glitches like those mentioned above. Sulkowski and Lazarus recommended the use of
criminal and shooter profiling, emergency plans, increased security technology on campus,
and threat assessment procedures, just to name a few, to facilitate effective campus security.
Even then, it was considered to be impossible to eliminate all threats (Sulkowski & Lazarus,
2011). However, in the nation’s recent economic situation in which states struggled to make
ends meet and higher education budgets were suffering cuts, it was difficult to envision
expenditures for such endeavors.
In the United States’ litigious environment, failure to act can be just as costly. On
March 14, 2012, a Christiansburg, Virginia, court awarded the families of two victims of the
2007 massacre at Virginia Tech $4 million each (CNN, 2012). The jury found that Virginia
Tech was negligent in its handling of the incident and ruled against the University. The
mother of one student who was wounded in the shooting stated, “Vindication has finally
come. This is about them being accountable” (CNN, 2012, para. 4).
Defensive Pessimism: The Positive Power of Negative Thinking?
Such legal ramifications, along with the huge unknowns that colleges and universities
faced, brought into question why anyone would want to allow weapons on a college campus.
Based upon the research presented above from the Violence Policy Center, the two seemed a
potentially dangerous combination. Still, as indicated, there were those who desired just that
combination. What could have influenced someone to think that allowing concealed carry
weapons on campus was a good idea. Perhaps it had to do with the way they processed their
world and dealt with the issues found therein. Defensive pessimism might be an explanation.
It could lead individuals to see CCW on campus as the safest route to a controlled
42
environment when confronted with their own levels of fear and responsibility. Accepting or
denying CCWs on campus might have helped defensive pessimists alleviate or placate the
fear and responsibility they might have faced concerning possible violence.
Norem (2002) argued that the concept known as defensive pessimism was a real
coping strategy. It allowed anxious individuals to control their anxieties so that they could
use it as a tool for progress instead of allowing it to tear them down. In other words, it was a
process that could “aid our efforts toward self-discovery and enhance[s] our personal
growth” (Norem, 2002, p. 3). Put simply, it addressed anxiety rather than ignoring it. In
short, Norem defined defensive pessimism as:
the process that allows anxious people to do good planning. They cannot plan
effectively until they control their anxiety. They have to go through their worst-case
scenarios and exhaustive mental rehearsal in order to start the process of planning,
carry it through effectively, and then get from planning to doing. (p. 48)
Additionally, according to Cantor, Zirkel, and Norem (1993), transitional periods can
exacerbate this anxiety. Cantor et al. additionally indicated that within a particular group
there could be varied rankings and appraisals of life’s tasks. Cantor et al. wrote that these
appraisals reflect “current concerns that consume people’s thoughts and guide their attention
selectively; the personal strivings that organize actions in the service of desired outcome; and
the common age-graded life tasks which individuals pursue in unique ways” (p. 426). In
short, people have different goals at different points in time. Safety was one of the goals
pertinent to this study.
Instead of pessimism resulting in the negative outcomes our society was used to
hearing about, in Norem’s (2002) view, defensive pessimism was a coping strategy “by
which negative thinking transform[s] anxiety into action” (p. 5). In other words, people who
dealt with life via a defensive pessimism coping strategy actually “manage instead of banish
43
their negative emotions” (Norem, 2002, p. 6). It helped to confront, instead of deny, the
negative feelings they experienced (Norem, 2002).
Norem (2002) recognized that such a concept is contrary to the perceived national
belief of the past few years–the positive psychology approach that has been afoot in U.S.
culture dictated individuals must see the positive side of things. Norem stated that to
approach something from a negative point of view was “almost heretical” (p. 1) in this
society. Doing so was contrary to the brave and heroic status emphasized by the mainstream
press and discussed earlier in this chapter. This is why Norem reported that positive
psychology has been sweeping the nation. However, the definition of this positive
psychology has been quite limited and tended to revolve around optimism as the key to
positivity. According to Csikszentmihalyi and Hunter (2003), positive psychology focused
on what made life worthwhile. The authors noted that James, Dewey, Rogers, and Maslow
all focused on psychological well-being. According to the authors, in some areas of the
world, particularly the West, people needed something more. With base needs presumably
met, individuals needed other psychological fulfillment. Czikszentmihalyi and Hunter
highlighted Inglehart’s (1997) theory that happiness decreased as a nation’s economic state
improved beyond the basic needs. In other words, economically advanced nations were ripe
for the so-called good life positive psychology had to offer. However, and to the intent of
this study, such an ideology did not take into account a world in which safety became an
uncertainty. To this end, what such positive thinking proponents failed to recognize was that
“negative thinking is positive psychology” (Norem, 2002, p. 13). It was positive because it
helped individuals cope with the unease of the modern world.
44
Simply put, the defensive pessimism coping mechanism allowed those who utilized it
to attain their objectives. Additionally, Cantor et al. (1993) reported that other researchers, in
particular Swann (1987), indicated that defensive pessimists were open to the views of others
when they were in a state of ambiguity. As a result, individuals in such situations could seek
out conditions that provided them with positive emotional states instead of negative ones.
They often did this by seeking out others who were in similar situations or harbored views
similar to their own (Cantor et al., 1993). This could indicate a need for self-protection that
could theoretically account for CCW support. “Individuals can and do use their social world
in useful ways to navigate crises and transitions, small and large” (Cantor et al., 1993, p.
275).
Norem (2002) believed that defensive pessimism increased peoples’ feelings of
control. She implied that being overly confident about a situation, to a defensive pessimist,
was to almost welcome calamity and subvert the goal of the strategy that, as has already been
alluded to, was a strategy for controlling a given situation. Simply put, defensive pessimists
planned for every contingency that could cause them anxiety. They have to think situations
through multiple times. This helped them slowly alleviate their anxiety as a plan began to
form in their minds (Norem, 2002).
Anxiety became the crux of the defensive pessimist strategy (Norem, 2002).
However, there was an important distinction to make about defensive pessimism. The
anxiety was used for a positive outcome, so successful use of the strategy did not depend on
past anxiety. It was a strategy that utilized anxiety about what was to come, a strategy that
used a new situation and the anxiety this new situation brought to begin a planning process
that would bring about the most positive outcome for the strategist in question. Defensive
45
pessimists simply were unable to function well when they were anxious. When they felt they
had done what they could to elicit a positive outcome, they became better prepared to
function without the anxiety. In the scenario of potential violence as proposed here, Norem
(2002) made an interesting observation in discussing evolutionary anxiety toward predators:
Few of us are faced with situations involving literal predators these days [of course,
the decade since 9/11 has altered this view in the minds of some individuals]. Still,
even when we’re faced with a nonlethal threat like a predatory coworker or the
prospect of failure, vanquishing the powerful urge to run away when we feel anxious
is no easy mandate. Thus, the first problem posed by anxiety is the problem of
making ourselves stay in the game; we have to be able to tolerate the tension to
remain in whatever situation (or pursuit of whatever goal) makes us anxious. (p. 38)
For those who fear violence in society and feel a sense of responsibility regarding
safety, this could include creating their interpretation of a safe environment. Additionally,
and of great importance to the process, the coping strategy of defensive pessimism was
important in the preparation for particular situations. It did not involve the way those
situations were described (Norem, 2002). In other words, defensive pessimism allowed
anxious individuals to embrace what made them anxious so that they could convert the
anxiety into a tool for progress (Norem, 2002). This made defensive pessimism a two-step
strategy (Lim, 2009). First, there had to be a situation in which the strategist anticipated a
potentially negative outcome. This led to the second step. This was where the strategist
attempted to employ a strategy to avoid those possible negative outcomes.
This self-protection cognitive theory, a defensive pessimism component, was
reportedly quite common (Lim, 2009). A study by Eronen, Nurmi, and Salmela-Aro (1998,
as cited in Lim, 2009) found that defensive pessimism was the most common coping strategy
among college students. It was also found to be a strategy very commonly used among
Asians (Lim, 2009). This did not mean that defensive pessimism unto itself was the prime
46
reason for supporting CCW on campus. However, it was a possible explanation as to why
individuals who utilized such a strategy might support such a stance.
Similar to Lim’s (2009) claim that defensive pessimism was a two-step process,
Gasper, Lozinski, and LeBeau (2009) reported there were also two independent tendencies
that influenced defensive pessimism. Pessimism is one part; reflectivity is the second. They
operated independently of each other, but they collectively served the individual using the
strategy. This separated defensive pessimists from true pessimists. This is the process that
occurred when the strategist deemed an outcome important. It was not a strategy employed
by strategic optimists (Gasper et al., 2009).
The goal was of paramount importance to the defensive pessimism process (Gasper et
al., 2009). If the goal was not of adequate value to the individual in question, then the
defensive pessimism process failed to engage. In other words, if the goal was not important
enough, then the individual in question felt neither pessimism nor anxiety. The theory did
not apply in such circumstances.
However, when the theory did apply, Gasper et al., (2009) found that reflection played
a vital role in the process. The trio found that in a study of students engaged in a first-time
task, reflection was most associated with elevated levels of outcome expectations. This was
especially true of those high in pessimism. This could, in the case of CCW on campus, in
theory, help identify an individual who has spent considerable time thinking about individual
safety in a new environment. Such an environment could be a post-secondary school
campus. As students gained more experience and more, what might be termed selfexperience,
the need to reflect and plan began to diminish. This could help explain why
47
some would feel an initial desire for safety, or in the current state of national and
international unease, a prolonged need to seek a continued state of safety.
In addition, defensive pessimists were more likely to weigh the pros and the cons of a
given situation and the likelihood of both good and bad things happening (Newman, Nibert,
& Winer, 2009). CCW on campus could represent one area in which addressing both the
positive and the negative might be important. In other words, guns might be associated with
violence overall, but a barrier between a safe environment and the potential for violence from
the outside world was countered by the coping strategy of some defensive pessimists.
Thomas (2011) reported that the defensive pessimism strategy was associated with better
mental health. Also, defensive pessimists paid much more attention to tactics that “may
mitigate disasters” (Thomas, 2011, p. 1). Thomas explained, “What the pessimist does is
take careful advance precautions so that this disaster does not happen” (p. 1). Although she
expressed this concept in general terms, it still applied to the original question posed. Could
defensive pessimists see CCW on campus as a positive strategy for self-protection? Thomas
offered clues to possible answers. She indicated that pessimism “makes people more alert to
their surroundings” (Thomas, 2011, p. 1). She cited Bergsma (2010), who stated, “Pessimists
may be more vigilant in situations of possible danger” (Thomas, 2011, p. 1). Thomas
discussed an optimistic friend who only saw the good in her fellow man. Her friend sought
directions from even the most questionable-looking characters. Thomas noted that it never
occurred to her friend that it could be dangerous to reveal that she was lost to questionable
individuals, in questionable areas, or in unfamiliar locales. In such circumstances, it never
dawned on her friend that she could become the victim of a crime (Thomas, 2011).
48
This being said, Elliot (2003) and Norem (2002) believed that defensive pessimism
was not self-handicapping. Elliot indicated that defensive pessimism was a tool that “aids an
individual’s striving in a particular domain of life such as the achievement domain” (p. 370).
In theory, this could apply to feelings of personal safety as well. Defensive pessimists do
worry relentlessly about future events (Lim, 2009). However, they do not just give up and
succumb to whatever will be. Instead, they used their worry as an impetus to begin actively
planning to avoid certain scenarios or achieve others. Support of CCW on campus might be
one path to achieve personal safety in a potentially violent society. Hazlett, Molden, and
Aaron (2011) gave a clue gleaned from their research. They indicated that individuals with a
concern for safety and security deal with these issues best through a pessimistic approach.
Del Valle and Mateos (2008), who studied the impact of mood on optimists, defensive
pessimists, and dispositional pessimists, emphasized this issue. The authors determined that
mood plays a role in how optimists and defensive pessimists viewed their worlds. As the
authors indicated, their findings were consistent with those of Sanna (1998, as cited by Del
Valle & Mateos, 2008). Del Valle and Mateos reported that when in an induced negative
mood, defensive pessimists were more likely to focus on the negative aspects of a given
situation. Additionally, although defensive pessimists anticipated negative results, they
continued to strive for the best outcome. The design of the proposed study will help
determine if the same can be said for campus safety and defensive pessimists.
A Closer Look at Defensive Pessimism
Nancy Cantor and her students coined the term defensive pessimism in the 1980s
(Norem, 2001). As previously discussed, defensive pessimism related to one overall
cognitive strategy for dealing with what life might offer. Untethered from the past,
49
embracing this concept was one way of dealing with anxiety concerning a wide variety of
issues. The concept derived from a social-cognitive approach to researching personality and
behavior. According to Norem (1989), Cantor and Kihlstrom (1987) labeled it a social
intelligence theory. Citing her own work, Norem (1989) stated, “Strategies describe coherent
patterns of expectations, appraisals, planning, effort, and retrospection as individuals pursue
personally relevant goals” (p. 78). The defensive pessimism strategy served to control
behaviors and emotions (Norem, 2001). Norem believed that the theory came straight out of
what Alfred Adler (1935/1979) said was the individual’s ability to adapt to his or her own
temperament and environment.
Studies undertaken in recent years have addressed defensive pessimism in an academic
setting. Yamawaki, Tschanz, and Feick (2004), attempting to isolate defensive pessimism in
such a setting, found that the theory does not work well in such a limited environment. It has
been determined, in an academic setting, that college students who were identified as
defensive pessimists in their freshman year experienced more negative than positive
encounters. Based upon the theory, this finding was not unexpected. Citing Cantor and
Norem (1989), Yamawaki et al. (2004) indicated that these same students had more negative
psychological symptoms and lower life satisfaction when compared to optimists. This is
contrary to the theory proposed by Norem (2001). Yamawaki et al. indicated that defensive
pessimists also showed lower self-esteem when compared to their optimistic counterparts.
Additionally, citing Showers and Ruben (1990), the authors emphasized that defensive
pessimists experienced higher rates of depression In fact, Yamawaki et al. stated that
evidence for the defensive pessimism theory that indicated anxiety served to boost
performance “is not especially strong” (p. 234). This, too, ran contrary to the theory. Norem
50
and Illingsworth (1993), as cited by Yamawaki et al., noted that when study participants
behaved in accordance with the defensive pessimism theory, they “showed a consistent, but
nonsignificant, tendency to report less anxiety relative to defensive pessimists who had been
prevented from engaging in this strategy” (p. 234). Citing Sanna (1998), Norem and
Illingsworth (1993) reported that the most notable aspect of the theory they found was that
the “performance-preparatory effects outweighed the anxiety-buffering effects” (p. 234).
This seemed counter-productive to the theory of defensive pessimism Norem (2001)
presented.
Yamawaki et al. (2004) further investigated these negative aspects of defensive
pessimism. Yamawaki et al. reaffirmed that defensive pessimism served those who practiced
the strategy well in the area(s) in which they were pessimistic. This is an important
distinction. In such a realm, the individual in question performed well and had greater
feelings of self-esteem and satisfaction. In all other areas, such as academics, the researchers
found that self-esteem appeared to be lower in so-called defensive pessimists. They believed
this was a consequence of negative self-thoughts. Yamawaki et al. indicated that this
translated into more depressive issues instead of the positive aspects associated with
defensive pessimism.
In fact, Yamawaki et al. (2004) pointed out that in areas where defensive pessimism
was not practiced, individuals showed a shorter period of enjoyment when an activity worked
out. Additionally, their self-reported enjoyment level was lower, and they were less involved
with the task than their counterparts. A test utilizing 500 psychology students found very
similar results. Their results showed that with regard to avoidance, unengaged defensive
pessimists scored significantly higher than their counterparts. They also found that on a
51
survey of mastery, the same subjects had significantly lower scores. Yamawaki et al. found
that correlations between self-esteem and negative-thought and self-esteem and self-esteem
instability were also significant. When they controlled for these factors, they determined
self-esteem does have an impact on how optimists and defensive pessimists perceive their
worlds in an academic setting. All things being equal, Yamawaki et al. determined that
individuals with moderate self-esteem might actually be more apt to employ the defensive
pessimism strategy because of the fact that they can access a cache of negative self-thoughts.
These negative self-thoughts, in turn, serve as an impetus to succeed rather than fail.
Nonetheless, self-esteem can still break down if negative self-thoughts are allowed to
dominate the situation. However, in an area in which the defensive pessimist is determined
to succeed, this is not necessarily the expected norm. Campbell (1996, as cited in Norem,
2001) reported that there was a negative correlation between self-esteem and defensive
pessimism. Personal views of the self are a part of the defensive pessimist approach.
Cardell, Wong, and Scott (n.d.) also studied defensive pessimism in an academic
setting. They discussed the original defensive pessimism scale as developed by Cantor and
Norem (1986) and discussed in Norem (2002) that consisted of nine items and focused on
distinguishing between optimists and pessimists in an academic setting. Cardell et al.
indicated that only one of the nine items in the questionnaire distinguished the defensive
pessimists from true pessimists. They defended this stance by highlighting the idea that
defensive pessimism was much broader than the original scale (the Academic Defensive
Pessimism Questionnaire) offered by Cantor and Norem (1986). Cardell et al. argued that
these broader aspects of defensive pessimism should be included when trying to develop a
scale to measure defensive pessimism. The authors also argued that this broader approach
52
was necessary to distinguish defensive pessimism from other coping strategies.
Consequently, the authors set out to create what they viewed as a more valid scale for use in
the academic setting.
Utilizing a group comprised of 109 students, both male and female, Cardell et al. (n.d.)
constructed a defensive pessimism scale with 30, as opposed to nine, items. The design of
this new tool allowed the researchers to assess the attitudes of individuals approaching
performance circumstances. In addition, the authors designed the measure to account for
“various coping strategies used, ruminatory thought patterns, types of failure attributions
made, and patterns of anticipatory reflectivity” (para. 5). After analysis, the authors reduced
their scale from 30 items to 17. Another study utilizing 126 students (male and female) was
later carried out. In the second study, Cardell et al. used their scale in conjunction with (a)
Cantor and Norem’s (1986) original defensive pessimism questionnaire used to assess
general optimism and pessimism, (b) Trice’s (1985) Academic Locus of Control Scale used
to measure internal versus external locus of control in academic settings, (c) Crandall,
Katkovsky, and Crandall’s (1965) Intellectual Achievement Responsibility Questionnaire
used to measure internal versus external failure attributions to assess locus of control in
failure situations, and (d) the Marlowe-Crowne Social Desirability Inventory by Reynolds
(1982) used to assess social desirability bias (as cited by Cardell et al., n.d.).
Cardell et al. (n.d.) determined that both of their studies found internal consistency in
their Academic Defensive Pessimism Scale. They indicated that their tool would be useful in
future studies in which defensive pessimism was the subject. They also indicated that the
questionnaire might be useful for student feedback. Specifically mentioned was the idea that
the students might perform better under negative circumstances as their anxiety served as a
53
motivating factor. This was an important factor as they claimed performance anxiety was
key to their study. To this end, the authors stated that the limitation of their work was that
“the current scale is intended only as a measure of defensive pessimism in academic settings
and has been tested only in a university setting” (para. 34). Norem’s (2001) revised scale is
much broader.
Norem (2001) believed that defensive pessimism was a strategy employed to prepare
for any event perceived as stressful. Driven by theory, not empirical data, the original scale
evolved around an academic setting. In discussing the original scale, the OptimismPessimism
Prescreening Questionnaire (OPPQ), Norem indicated that “when the items were
generated, the research team focused on elaborating the description of defensive pessimism”
(p. 81). Six of the items on the early questionnaire thus referred to the two hypothesized
components of defensive pessimism: pessimistic expectations and negative thinking, and
their presumed opposites (Norem, 2001, pp. 81-82). There were also two items seeking
measures of pessimistic and optimistic expectations and two items about positive and
negative thoughts and feelings. Additionally, Norem noted that there were two questions
about feelings after the performance to measure satisfaction.
In the revised version, Norem (2001) reported that two factors reflectivity and
pessimism rotated obliquely. She reported that the 2001 version of the Defensive Pessimism
Scale measured the “thinking through” (p. 82) process that was defensive pessimism. This
was key. “I continue to use a single defensive pessimism score computed by summing both
the pessimism and reflectivity items (with appropriate reverse scoring)” (Norem, 2001, p.
82). When compared to the original scale, the revised scale correlates at r = .65 with even
higher reliability (Cronbach’s alpha = .78). The reflectivity and pessimism subscales had
54
average Cronbach’s alphas of .74 (Norem, 2001). Test-retest also proved to be strong over 3
years. For general purposes, it appeared that the revised Defensive Pessimism Questionnaire
(DPQ) by Norem best served the purposes concerning a study of CCW on campus. As
Norem pointed out, the DPQ was not limited to an academic model.
Utilizing defensive pessimism (in theory) satisfied an individual’s need to manage
anxiety. Table 2 offers the statistical differences established by Norem (2001) in the initial
academic and the revised versions of the scale used in a coed sample. Of the revised scale,
Norem wrote, “The DPQ does not appear, however, to be correlated with measures of more
general motivations such as need for cognition or need for structure” (p. 86). Accordingly,
the revised scale better served a study involving CCW on campus. As Norem suggested, the
DPQ “is intended for use as a domain–specific measure of strategies, and the specific
wording of the items should reflect the domain under study” (p. 86). As of 2001, the scale
proved useful in researching social, recreational/sports, and health defensive pessimism
(Norem, 2001). Additionally, defensive pessimism could be utilized in the academic realm
as seen in Cardell et al.’s (n.d.) and Norem’s original academic scales. However, when
comparing the scales, only a “small-to-moderate correlation between the social and academic
versions of the scale” (Norem, 2001, p. 86) was found. She added, “The Social DPQ,
worded so that ratings are given for social situations, taps into a broader domain [emphasis
added] than the academic version, which presumably refers to a more restricted goal domain”
(p. 86).
55
Table 2
Divergent and Convergent Correlates of the Defensive Pessimism Questionnaire (DPQ)
Academic Version Social Version
NEO-FFI Extraversion -.29 -.36
NEO-FFI Neuroticism .22 .27
NEO-FFI Conscientiousness .23 .11
NEO-FFI Agreeableness -.24 -.20
NEO-FFI Openness .05 .04
Need for Cognition (n Cog) .13 .09
Need for Structure (n Struct) .15 .32
Fear of Negative Evaluation (FNE) .22 .36
Beck Depression Inventory (BDI) .18 .22
Self-Handicapping scale (SHS) .27 .49
Repression-Sensitizing (R-S) (high score = sensitizing) .26 .29
Optimism (LOT) -.23 .30
DPQ Social version -.38 n/a
Note. Norem, 2001, p. 85
Similarly, referring to how the process worked, Norem (2001) wrote that defensive
pessimism served to harness anxiety and use it positively instead of succumbing to its
negative and potentially debilitating effects. However, in academic and social (the revised
scale) scenarios, some researchers suggested that defensive pessimists might lack the drive
that was so vital to Norem’s theory.
Karademas, Kafetsios, and Sideridis (2007) indicated that optimism could reflect “a
more benign assessment of the environment rather than of the personal capabilities” (pp. 285-
286). In other words, optimism can lead to a milder view of reality. They also stated that
there was a positive association between optimism and self-efficacy. In addition, the authors
pointed out that optimism and self-efficacy were found to be “inversely associated with
56
depression and anxiety” (p. 286). Karademas et al. also found that optimists exhibited more
positive perceptions about their own well-being and the environment around them. The
authors also indicated that such outcomes were the result of individual “cognitive structures”
(p. 286). In other words, Karademas et al. indicated that individuals biased their perceptions
because of these schemas. Karademas et al. additionally indicated that the duo of selfefficacy
and optimism kept such schemas “easily accessible” (p. 287). A positive bias was
the result. This was obviously not what was occurring based upon Norem’s (2001) definition
of defensive pessimism.
Karademas et al. (2007) studied the relationship between optimism and self-efficacy
and what the authors called “well-being stimuli” and “threat stimuli” (p. 287). Results
showed that individuals who ranked high in self-efficacy and optimism showed a propensity
toward well-being and not toward neutral or threat-related stimuli. Similarly, the authors
found that test participants with low optimism responded more positively to threat related
stimuli. However, high and low optimism participants did not show great differences.
According to Karedemas et al. (2007), “Perceived stress is negatively predicted by
optimism, which is positively predicted by [the study’s] well-being colour-naming [sic]
latencies as well as by self-efficacy, which is negatively predicted by threat-related latencies”
(pp. 289-290). Further, the authors cited Bandura (1997), Carver et al. (2005), Giltay et al.
(2004), and Luszcyzynska et al. (2005) in establishing that optimism and general selfefficacy
are “strongly associated with well-being and adaption” (p. 291). The study by the
authors bore this out. Individuals who were rated high in optimism or self-efficacy presented
a predisposition toward “well-being related stimuli” (p. 291). Alternately, Karedemas et al.
57
found that individuals with low self-efficacy showed greater biases toward personal threat
and general threat related stimuli.
Similarly, Karedemas et al. (2007) reported that pessimists showed a tendency toward
negative stimuli based upon informational biases. Karedemas et al. also found that
moderately optimistic individuals showed an equal propensity toward both positive and
negative biases. Strong optimists and those strong in self-efficacy showed a sound
connection with positive biases. However, individuals low in only the optimism category did
not show the expected opposite results. Those low in self-efficacy did show such biases.
According to the researchers, low self-efficacy showed “greater interference for threatrelated
stimuli” (p. 291). In short, the authors found that individuals high in optimism and
self-efficacy were more prone to align with “well-being and control information” (p. 291)
while individuals reflecting low self-efficacy were more prone to “threat related” stimuli (p.
291). Karademas et al. indicated that such findings were consistent with those found by
Erblich et al. (2003), MacLeod (1991), and Williams et al. (1996). Informational biases can
impact an individual’s behavioral/emotional responses. Karademas et al. reported that these
reactions played a key role in producing and sustaining an individual’s emotions. Similarly,
the authors indicated, as addressed above, that they also assisted in the formation of
“decisions and actions” (p. 292). This indicated, according the authors, those high in
optimism and self-efficacy had a more positive view of themselves and the world around
them. This being said, the authors wrote that such individuals “focus more on the positive
aspects of stressful situations” (p. 292). This was the exact opposite of what was happening
in defensive pessimism as discussed by Norem (2001). In other words, Karademas et al.
indicated these predispositions promoted positive interpretations and a more stable sense of
58
well-being. Additionally, the authors also indicated that such a process actually weakened
the impact of negative information when it was offered. However, and as stated above, this
is not the fact when low self-efficacy entered the equation.
According to Karademas et al. (2007), individuals with low self-efficacy proved to be
more preoccupied with “threat-related stimuli” (p. 292). The authors wrote that for such
individuals “after the identification of a threat, an elaborative processing of threat-relate
material is activated and almost all informational resources are allocated towards those
stimuli” (p. 292). Buckley et al. (2000), Kindt and Brosschot (1997), and Williams et al.
(1996) found similar results according to Kardemas et al. (2007). The authors went on to
point out that once this occurred in such an individual’s life, the individuals found it difficult
to separate their fearful view of their surroundings. Therefore, such individuals saw an
increase in stress due to this inability to overcome their fears. Karademas et al. indicated that
“this process may assist the employment and perpetuation of maladaptive behaviors” (p.
292). This was an extremely important finding as far as this study was concerned because
this is the opposite of what happens in defensive pessimism. As Norem (2001) pointed out,
defense pessimism allowed individuals to address certain situations, to vigorously think
about and plan a course of action that would alleviate the “maladaptive behaviors” (p. 292)
the previous authors discussed. This stood in contrast to the concept presented by
Karademas et al. They indicated that individuals low on self-efficacy tended to focus more
on threat-related stimuli with “greater interference” than others high in optimism and selfefficacy.
The authors argued that such individuals were not as capable of dealing with
threats as their more positive counterparts. They underscored their argument with Bandura’s
(1977; as cited by Kardemas et al., 2007) definition of self-efficacy: “the evaluation of
59
personal capabilities in the face of a problem” (p. 292). In other words, Karademas et al.
posited that optimists were much more able to deal with negative or threatening stimuli
because they simply did not utilize as much of the brain’s information processing resources,
whereas those low in self-efficacy utilized too much of the brain’s information processing
resources. Norem may not have necessarily disagreed with this finding. Yes, some people
focused more on the negative, but this additional focusing and planning proved beneficial to
those who utilize the defensive pessimism cognitive processing. In fact, as Karademas et al.
indicated in citing A.T. Beck (1993) and J.S. Beck (1995) that optimistic assessment and
self-efficacy opinions can be modified. This, as the authors pointed out, can allow the
individual to shift toward positive expectations. This was similar to the theory of defensive
pessimism as processed by Norem.
Still, the bias toward optimism was the most common cognitive disposition according
to Sharot (2011). It was present in 80% of the population according to the author. In fact,
according to Sharot the optimism bias “is one of the most consistent, prevalent, and robust
biases documented in psychology” (p. R941). Such a bias seems to be hard wired.
According to the author, optimists are unwilling to change, and they are unwilling to change
because frontal lobe areas of the brain do not “code errors” (p. R943) that would change their
positive beliefs. This was a process that involved the amygdala and the rostral anterior
cingulated (rACC) according to Sharot (2011). However, there was an exception. That
exception, according to the authors, was found in individuals who suffered from depression.
This was particularly true of Major Depressive Disorder (MDD).
According to Sharot (2011), in individuals with depression, the amygdala and rACC
“show abnormal function and impaired connectivity” (p. R944). This could be one
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explanation as to why certain individuals do not construct future positive schemas. However,
Sharot, who also cited Seligman (2006), suggested that the lack of positive schemas could
also be attributed to an environment that has not produced positive outcomes for the
individual in question. Such an environment, according to the author, led to a depressed state
in animal studies. In fact, Sharot indicated it was such a lack of pessimism that allowed
humans to evolve without extinction. Based upon Norem’s (2001) definition of defensive
pessimism, the opposite could very well be argued.
A Divergent View of Defensive Pessimism
Norem (2001) pointed out that in a 3-year longitudinal study students deemed
defensive pessimists had more psychological and physical symptoms, as well as lower
grades, than did their optimistic counterparts. However, the worst outcomes occurred for
those individuals who used the strategy in academic and social settings. Additionally, selfesteem
issues correlated to a greater extent with the social defensive pessimism scale than
with the academic scale (Norem, 2001). Norem wrote, “It may also be that social anxiety is
more generally debilitating than anxiety about academic performance” (p. 92). Of
importance to the proposed study, Norem also stated that defensive pessimism might be less
effective for some in social situations because of the subjectivity of goals. However, as
already stated, there was an exception. When the goal was important and the means for
attaining the goal could be planned, the previous did not hold true and the social side of
defensive pessimism engaged.
Kiehl (1995, as cited by Norem, 2001) offered a prime example while researching
AIDS-related activities. The author found that defensive pessimists considered certain
behaviors far riskier than optimists. In another study, when a fictitious new disease was
61
discussed in front of test subjects, the defensive pessimists were more interested in getting
additional information on the disease mentioned than were optimists (Norem, 2001). This
was in line with Norem’s findings that people have varied goals and can be hypothesized to
be true of certain individuals’ views of CCW on campus. To further substantiate this line of
inquiry, Norem (2008) provided an example of how defensive pessimism works. She stated
that strategies reflected how an individual responds to ongoing events in life so that those
events proceeded in a manner that ensured the individual’s goals were met. Norem used an
example of driving to illustrate her point. A nervous driver wanted to be safe. In order to be
as safe as possible, the driver wanted no distractions. The radio was turned off. The driver
took a moment to prepare. He or she asked the passengers to stay very quiet so that all focus
could be on the road ahead. From the provided example, it became clear that individual
situations influenced peoples’ strategies as those situations impacted relevant goals and
obstacles. Application of the same approach helped determine why individuals would
support CCW on campus just as some were more interested in a fictitious disease than others.
Similarly, results of the work by Del Valle and Mateos (2008) showed that negative
feelings, or mood, directly affected the defensive pessimist. This established the importance
of fear for the purposes of this study. As Gasper et al. (2009) concluded that if safety or any
other variable was not a goal of defensive pessimists, then it was of no concern to them.
Similarly, if they did not have something that caused anxiety, or even fear, there was also no
concern. To this end, whether or not the individual participants had a concern about weapons
on campus needs to be determined. For the purposes of this research, the fear questionnaire
by Marks and Mathews (as cited in Antony et al., (2001) was utilized. This was a scale in
which support for concealed carry would also be presented.
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The Role of Fear
The fear questionnaire consisted of three sub-scales that addressed agoraphobia, social
phobia, and blood/injury phobia (Gillis, Hagga, & Ford, 1995). Gillis et al. claimed that the
scale was free of social desirability response bias. Further, in addressing the fear
questionnaire, the authors underscored the belief that the device did not reflect differences
when it came to sex, race, or income. However, age did affect the outcome of the fear
questionnaire (Gillis et al., 1995). Participants up to the age of 44 scored significantly higher
than their older counterparts (accommodations for this factor were included in the design of
this study). The median score for the younger group in an overall sample of 242 was 11.4
out of a total score of 28.6 (Gillis et al., 1995). For participants over 45, the median score
was 9.3 (Gillis et al., 1995). These results helped reinforce the idea that fear was a strong
variable in dealing with young people who might have concerns about their safety on college
campuses.
Higgins (2004) reported that the tendency to develop certain fears was consistent
across cultures. In a study of the fears of young Chinese and British women, a concrete list
of fears and opened-ended questions about fears elicited reactions from participants
concerning archetypal and conditional fears. The finding of the Higgins study that applied to
this CCW study was that open-ended questions showed cross-cultural similarities; whereas,
the concrete list showed cultural differences. For example, Chinese women reported much
higher fear of caterpillars than did the Western women (Higgins, 2004). However, with
regard to open-ended fears (fears not specifically presented in the list), death and injury were
very common concerns. Additionally, fear of the unknown was almost as common when
63
tabulating open-ended fears (Higgins, 2004). Again, this had a bearing on the question of
CCW on campus as it related to common fears of death and injury.
Based upon high fear questionnaire scores, individuals tended to take a defensive
stance that oriented them away from the perceived threat (Perkins, Cooper, Abdelall, Smillie,
& Corr, 2010). Additionally, individuals who were fear-prone also tended to see threats as
being greater than they were in reality. Using an example in which an individual would
suddenly encounter a ferocious dog, the authors indicated that most people initially
experienced fear. This fear would then be followed by avoidance. In a scenario in which an
individual who could control his or her fear suddenly encountered a ferocious dog about to
attack a small child, fear and anxiety would still be present; however, in this instance, if a
sense of responsibility were present, the individual would utilize the fear and anxiety not to
flee but to move to protect the child. Interestingly, if the threat was seen as being distant
(i.e., not immediate), individuals generally would engage in higher prefrontal cortex activity.
In such situations, they planned and thought about things that would benefit them the most in
possibly threatening scenarios (Perkins et al., 2010). To test this concept, Perkins et al.
reported that the fear questionnaire scores “were positively correlated with a tendency to
select scenario responses that entail orientation away from threat (such as ‘run away’)” (p.
1073). However, trait anxiety questionnaire scores did not reflect the same results. In a
study to replicate the original findings of Perkins and Corr (2006), Perkins et al. found that
their results showed that “fear scores, but not trait anxiety scores, were significantly (p <.01)
and positively correlated with the tendency to orient away from threat, a clear replication of
the same finding by Perkins and Corr” (Perkins et al., 2010, p. 1077). Interestingly,
individuals high on psychoticism tended to move toward threats (Perkins et al., 2010).
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Similarly, Frombach, Asmundson, and Cox (1999) reported that the Marks and Mathews
Fear Questionnaire was a much better tool for measuring fear than any “unidimensional, twofactor,
hierarchical three-factor, or categorical three-factor models” (p. 117). This was
determined to affect answers to the question of whether the fear felt by defensive pessimists
might contribute to their support of CCW on campus. The Marks and Mathews fear
questionnaire was, therefore, an excellent tool for gauging such support.
Responsibility as a Factor
Gasper, Lozinski, and LeBeau (2009) discussed defensive pessimism in terms of goal
importance. If the goal was not of adequate value to an individual, the defensive pessimism
strategy remained dormant. For the purposes of the this research, the question of individual
responsibility also came to bear on the question of whether or not defensive pessimism might
play a role in affirming the acceptance of CCW on campus. The intentions of individuals in
the ferocious dog example presented above supported this idea. A sense of responsibility
must engage.
According to Mancini (2001), responsibility played a key role in how an individual
perceived his or her environment. For example, general threat appraisals were one area in
which level of responsibility could have an effect. One tool that was quite useful in
measuring responsibility was the Responsibility Attitude Scale (RAS). Even though the RAS
was a tool often associated with the study of obsessive behaviors, the RAS has proven to be
quite useful in non-clinical subjects (Mancini, 2001). In fact, the elements offered by the
RAS were more indicative of true views of individual responsibility than obsessivecompulsive
issues (Mancini, 2001). The RAS revealed more of an individual’s true tendency
to assume responsibility in certain areas or situations (Mancini, 2001). This was especially
65
true in areas where the individual subject had doubts or fears of possible intrusions. The 26-
item RAS questionnaire was designed to assess general beliefs about responsibility (Mancini,
2001).
The RAS correlated well with the Revised Defensive Pessimism Questionnaire crafted
by Norem (2002). As Mancini (2001) noted, there was a significant correlation between an
individual’s feelings of responsibility and the individual’s anxiety. High anxiety scores on
tests correlated positively with high responsibility scores (Mancini, 2001). In addition, the
RAS showed a very strong correlation to a factor Mancini called prevention. Prevention
translated into a desire to prevent harm from coming to the subject and others. In fact,
Mancini found this to be true of subjects who doubted their own abilities in questionable
situations. This indicated a potentially strong correlation between defensive pessimism and
responsibility in terms of the proposed query concerning CCW on campus.
Snorrason, Sma´ri, and O’lafsson (2011) investigated the potential connection between
obsessive–compulsive symptoms and impulsivity. Additionally, a connection between
responsibility and impulsiveness in connection with obsessive–compulsive symptoms was
examined (Snorrason et al., 2011). This was accomplished by studying 205 university and
college students. Once again, participants were non-clinical individuals.
The RAS was one of the tools utilized in the Snorrason et al. (2011) study. Using the
RAS, they probed the link between high responsibility and obsessive-compulsive thoughts.
Citing Sma´ri et al. (2003) and Salkovskis et al. (2000), the authors found a close association
between obsessive–compulsive symptoms and responsibility attitudes in clinical subjects and
in university students. Additionally, they attempted to determine if there was a correlation
between responsibility and impulsivity (Snorrason et al., 2011).
66
Using an Icelandic college and university student study sample, Snorrason et al.
(2011) reaffirmed what others had previously found. There was an interaction between
responsibility and impulsivity. Together, these greatly added to the possibility of obsessivecompulsive
symptoms. This accounted for attentional impulsiveness, defined by Patton,
Stanford, and Barratt (1995) as racing or intrusive thoughts, which, in turn, could be linked to
irrational thinking that helped explain, for the purposes of this study, why an individual
might be willing to accept CCW on campus (Patton et al., 1995; Snorrason et al., 2011).
However, there were some differences between clinical and nonclinical study groups that
warrant recognition.
Snorrason et al. (2011) found marked differences between non-clinical control groups
and those with OCD symptoms. The authors reported that attentional impulsiveness was
much higher in those assessed as having OCD symptoms when compared to the control
group. Summerfeldt (2004) found similar outcomes. However, as Snorrason et al. remarked,
and in accordance with the findings of Summerfeldt, those with OCD symptoms did score
higher in the cognitive/attentional subscale (irrational thinking) than did the normal control
group; they did not score higher than those with anxiety issues. Therefore, impulsivity does
not have a unique relationship to issues of OCD (Snorrason 2011). This might vary simply
as a function of (a) how an individual thought, (b) the individual’s level of anxiety, and (c)
the decision-making that resulted from this process. This provided a link to anxiety and
CCW on campus.
Similarly, Mather and Cartwright-Hatton (2004), in a study of adolescents that
examined the same correlations Snorrason et al. (2011) studied above, also found a
connection between responsibility appraisals and the way individuals thought. The authors
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directly quoted Salkovskis (1985), who stated that understanding OCD in this population lay
less in understanding intrusive thoughts and more in understanding how these thoughts were
appraised or interpreted. This said, anxiety, as a component of defensive pessimism, and
responsibility played a role in the proposed research. These factors also played a role in
defensive pessimism, but this research was offered in exclusion of issues, such as OCD, that
were addressed by these authors. However, the link between anxiety (in terms of defensive
pessimism), fear, responsibility, and the decision to support or deny CCW on campus was
clearer based upon presented evidence.
Mather and Cartwright-Hatton (2004) criticized Salkovski’s (1985) work because of
the failure to address the role of what was called “general metacognitive beliefs” (p. 743).
This exclusion was extremely important because the addressed beliefs “concern the meaning
of thoughts themselves and beliefs about the danger, or power of thoughts and consequences
of emotion or discomfort” (Mather & Cartwright-Hatton, 2004, pp. 743-744). This appeared
to have a direct bearing on anxiety as a component of defensive pessimism, fear, and
responsibility.
Additionally, Mather and Cartwright-Hatton (2004) cited Rachman (1993), who
introduced a concept called thought-action fusion. Rachman believed that both thoughts and
beliefs could merge to violate potentially intrusive thoughts in the case of those with OCD
symptoms. One example was someone with OCD who kept having the intrusive thought that
he was going to hurt his children. The individual wanted the children to be safe, so he kept
checking on them constantly to make sure the action had not occurred. Mather and
Cartwright-Hatton reported that the appraisal of the thought brought about a behavioral
reaction. This was very similar to what could be happening in a defensive pessimism view of
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CCW on campus. Having weapons available might belay an individual’s obsessive thoughts
about personal safety.
Mather and Cartwright-Hatton (2004) utilized the RAS as a key component of their
study. They chose the tool because of the ability to use the 26-item questionnaire to measure
general responsibility beliefs and because of its strong psychometric properties. The RAS’s
readability was key as it was easily read by 13-year-olds. Additionally, the RAS was highly
reliable for use on younger subjects.
Summary
Fear, responsibility, and defensive pessimism served as the predictor variables as
measured against the criterion variable of support for CCW on campus. This was a simple
“yes or no” questionnaire measured against the predictor variables. A comparison
determined whether the pro-CCW individuals and those concerned about safety on campus
showed higher defensive pessimism scores when compared to those opposed to CCW on
campus that were not necessarily as concerned about campus safety. Comparing these scores
to the data garnered from the FQ and the RAS allowed the determination of whether there
might be a correlation between fear, responsibility, defensive pessimism, and support for
CCW on campus.
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CHAPTER III: METHODS
This chapter serves to describe the method utilized to examine the relationship
between support of CCW on campus, defensive pessimism, fear, and responsibility. Levels
of defensive pessimism, fear, and responsibility were weighed against the acceptance or
denial of CCW on campus. These were assessed in terms of the proposed hypothesis (H1)
that elevated levels of defensive pessimism, fear, and responsibility were significant
predictors of the probability that a participant would support CCW on campus. This stood in
direct contrast to the null hypothesis (H0) in which defensive pessimism, fear, and
responsibility were not significant predictors of the probability that a participant supported
CCW on campus. To achieve this end, the quantitative research methodology was applied.
Specifically, a linear regression and correlation analysis was performed. The research
question that guided this study was “What are the relationships between the participants’
support for CCW on campus, and their levels of defensive pessimism, fear, and
responsibility?” This translated into a research hypothesis (H1) in which defensive
pessimism, fear, and responsibility were significant predictors of the probability that a
participant would support CCW on campus (relative to not supporting CCW on campus).
The null hypothesis (H0) would indicate the opposite. Defensive pessimism, fear, and
responsibility were not significant predictors of the probability that a participant would
support CCW on campus (relative to not supporting CCW on campus.) Each hypothesis, H1
and H0, was addressed in terms of the criterion variable, support for CCW, and its
relationship with each of the predictor variables: defensive pessimism, fear, and
responsibility. To this end, the participants were recruited from students at a small Liberal
Arts college within an hour’s drive of the scene of the nation’s deadliest campus shooting,
Virginia Polytechnic Institute and State University (Virginia Tech).
70
Methodology
As Agresti and Finlay (2009) pointed out, linear regression and correlation allow
researchers to test the association between variables through (a) statistical association, (b) the
strength of a potential association by using the correlation association, and, finally (c) by
using a regression equation to predict explanatory variables. The Model was based upon the
following equation:
E(y) = α + βx with a prediction equation of ŷ = a + bx
Where: y would denote the response as to the support or denial of CCW on campus and x
would represent an explanatory variable. As a linear function, y was viewed as a function of
x with a straight-line graph in which beta was represented by slope β and the alpha by the y
intercept. In such a model, as Agresti and Finlay (2009) pointed out, if β was positive then y
would increase as x increased. Conversely, if β was negative then y would decrease as x
increased.
The linear regression and correlation model was chosen because it, according to
Agresti and Finlay (2009), “approximates the true relationship” (p. 288) between the
variables that make up the study in question. Additionally, as the authors pointed out, the
linear regression and correlation model “is adequate for describing the relationship and
making predictions but that is still simple enough to interpret easily” (p. 288). As the goal of
this research involved establishing possible correlations between support or denial of CCWs
on campus and three independent predictor variables, the linear regression and correlation
model was seen as ideal. Additionally, as the authors pointed out, as future research evolves
and becomes more complex, more complicated models can be utilized by building upon the
findings offered by a linear regression and correlation model. Until that time, as Agresti and
71
Finlay addressed, since two variables at a time were addressed (position on CCW on campus
and one of three predictor variables), the linear regression and correlation model was
sufficient.
Procedure
The research (H1) hypothesis and null (H0) hypothesis were as follows:
H1: defensive pessimism, fear, and responsibility were significant predictors of the
probability that a participant would support CCW on campus (relative to not supporting
CCW on campus).
H0: defensive pessimism, fear, and responsibility were not significant predictors of
the probability that a participant would support CCW on campus (relative to not supporting
CCW on campus).
Before a correlational design could be successfully implemented, it was imperative to
explicitly define the criterion and predictor variables, and to explain how the variables were
operationalized. This information was essential to justify the use of appropriate methods of
statistical analysis. Furthermore, the measurement levels of the variables (nominal, ordinal,
or scale) were entered into the SPSS data editor (Field, 2009).
Accordingly, the conceptual, functional, and operational definitions of the variables
collected by the instruments administered in this study are outlined in Table 3.
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Table 3
Criterion and Predictor Variables
Variable Conceptual definition Functional definition Operational definition
Support for
CCW on
Campus
Whether or not a participant
supports or opposes CCW on
campus
One criterion
variable, classified
into two nominal
categories
Yes = 1 or No = 0, measured with a simple
poll
Defensive
Pessimism
A coping strategy employed
by a participant to prepare for
any event perceived as
stressful, by which negative
thinking transforms anxiety
into action (Norem, 2002)
One predictor
variables, measured
at the scale level
Measured with 17 items in the Revised
Defensive Pessimism Questionnaire
(Appendix 3). Each item is measured on a 7-
point scale (1, not at all true of me; to 7, very
true of me). Higher scores indicate higher
levels of defensive pessimism. Scores will be
divided into three categories: 22 – 41 will be
considered Strategic Optimists; 42 – 61 will
be viewed as bi-strategists; scores ranging
from 62 – 79 will be considered Defensive
Pessimists. The numeral 1 will represent
Strategic Optimists, 2 will represent bistrategists,
and 3 will represent Defensive
Pessimists.
Fear The extent to which a
participant has feelings of
agoraphobia, social phobia and
blood/injury phobia (Antony et
al. 2001)
One predictor
variable, measured at
the scale level
Measured with 17 items in the Fear
Questionnaire (Appendix 4). Each item is
measured on a 7-point scale (1,would not
avoid it; to 8, markedly avoid it). Fear is
operationalized as the sum of the scores for
the three sub-scales (Agoraphobia + Social
Phobia + Blood/Injury Phobia). These scales
are represented by questions 2 – 16 (FQ16).
Question 17 (FQ17) is a specific issue fear
(guns) and is of main interest to this study.
The global phobic distress index (an
anxiety/depression scale) is not utilized for the
purposes of this study.
Responsibility A participant’s tendency to
assume responsibility in
certain areas and situations.
Identifies individuals with
OCD (Antony et al. 2001 ).
One predictor
variable, measured at
the scale level
Measured with 26 items in the Responsibility
Attitude Scale (Appendix 5). Each item is
scored on a 7-point scale (1, totally agree; to
7, totally disagree). Averaging the scores for
the 26 items operationalizes the
Responsibility Attitude Scale. Lower scores
represent higher levels of responsibility.
The single criterion (response) variable, named Support for CCW on Campus, had
only two categories, measured with nominal numerical value labels, in a binary format
(Yes = 1 or No = 0). Support for CCW on Campus was assumed to be a hypothetical
73
attitudinal response of the participants to three predictor variables, specifically (a) defensive
pessimism; (b) fear, divided into two categories (FQ16 and FQ17); and (c) responsibility.
The predictor named defensive pessimism was measured on a scale from 1 to 7. The
variables were added to produce a final unidimensional defensive pessimism score. The
predictor named fear was a three-dimensional variable, though only two were utilized for this
study, based on the scores for 17 items, measured on a scale from 1 to 8. Fear was then
operationalized as the sum of items 2016 (a total phobia scale) offering a unidimensional
variable named FQ16 by the researcher. Additionally, item 17 on the fear questionnaire, a
specific statement oriented toward CCW, produced a unidimensional value named FQ17 by
the researcher. The predictor variable named responsibility was a unidimensional variable,
with each item measured on a scale from 1 to 8. Averaging the scores for 26 items
operationalized responsibility. The variables, with their ordinal or nominal value labels, used
to categorize the demographic characteristics the participants are outlined in Table 4.
74
Table 4
Demographic Variables (these variables were gathered for future use and do not apply to the
outcome of this study)
Characteristic Level Categories and Value Labels
Age (Years) Ordinal < 20 = 1
21-24 = 2
25-30 = 3
31-34 = 4
35-40 = 5
> 40 = 6
Gender Nominal Female = 0
Male = 1
Level of Education Ordinal Freshman = 1
Sophomore = 2
Junior = 3
Senior = 4
Race African-American = 1
Asian-American = 2
Hispanic = 3
Native-American = 4
Pacific Islander = 5
White = 6
Other = 7
In short, would positive support of CCW on campus reflect elevated levels of
defensive pessimism, fear, and responsibility as the proposed hypothesis argued, or would
the null hypothesis, that positive support for CCW on campus would not reflect in elevated
levels of defensive pessimism, fear, and responsibility, stand?
Norem (2001) reported that the 2001 version of the Defensive Pessimism
Questionnaire measured the “thinking through” (p. 82) process that is defensive pessimism.
The revised scale correlated at r = .65 with even higher reliability (Cronbach’s alpha = .78).
The reflectivity and pessimism subscales averaged Cronbach’s alphas of .74. Test-retest
reliability also proved to be strong over 3 years (Norem, 2001).
The Defensive Pessimism Questionnaire proposed that the individual taking the
measurement think of a situation related to the study topic. In this case, personal safety was
75
the subject that framed the measure’s questions. The study participants assigned a numeric
response to each statement. The number 1 represented a scenario that was “not at all true of
me.” The number 7 represented a scenario that was “very true of me.” The numbers
between 1 and 7 represented the spectrum between the two extremes. These scores were then
added for a final score on the RDPQ. Seventeen statements were prepared and presented to
participants (See Appendix C).
Marks and Mathews created the Fear Questionnaire (FQ) in 1979 (as cited in Antony
et al., 2001). The Fear Questionnaire consisted of three sub-scales that addressed
agoraphobia, social phobia, and blood/injury phobia (Gillis et al., 1995). The scale was
reportedly free of social desirability response bias. Further, the FQ did not reflect differences
when it came to sex, race, or income. Murisa et al. (2000) reported that the FQ was a very
widely utilized tool with three or five subscales. In the three-subscale version, called the
Total Phobia Scale, there were 15 questions designed to measure three sub-scales. This scale
was utilized for this study. The 15-question version had strong internal consistency with
Cronbach’s alphas of 0.81 for the total phobia score, 0.71 for the agoraphobia, 0.73 for the
blood-injury phobia, and 0.66 for the social phobia (Murisa et al., 2000). The 5-item
subscale also contained a global phobic distress subscale and an anxiety/depression subscale.
Both versions of the scale were well validated (Antony et al., 2001).
The FQ took fewer than 10 minutes to administer (Antony et al., 2001). The test
design reportedly had adequate to good internal consistency. Citing Oei, Moylan, and Evans
(1991), Antony et al. reported internal consistencies of .71 to .83 for the three subscales.
Antony et al. also reported a good short term and longer-term test retest reliability. Oneweek
test-retest values ranged from .82 to .96, whereas the 3-week test-retest reliability
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ranged from .84 to .90. Validity was also reported to be strong. Antony et al., citing
Davidson (1991), reported that correlations between the social phobia scales and other
measures of social anxiety are high, ranging from .59 to .83. This was important to this study
as social fears could contribute to the support of CCW on campus. The FQ17 portion of the
Fear Questionnaire (based solely upon question 17) showed a more marked difference to be
discussed in the next chapter.
Salkovskis et al. (2000; as cited in Antony et al., 2001) created the Responsibility
Attitude Scale (RAS) in 2000. Although the scale typically measured the parameters of
obsessive-compulsive individuals, as established above, the scale successfully analyzed
responsibility when utilized with normal populations. The results offered by the RAS were
more indicative of true views of individual responsibility than obsessive-compulsive issues
(Mancini, 2001).
According to Antony et al. (2001), the RAS was a 26-item scale designed to “assess
general attitudes, assumptions, and beliefs” (p. 230) concerning responsibility. Responses to
statements ranged from 1 to 7. One was equivalent to totally agreeing while seven was
equivalent to totally disagreeing. According to the authors, the RAS final score was the
mean score of all 26 questions. Antony et al. reported that validation studies show strong
consistency. Mean scores were 4.69 for subjects diagnosed with OCD. Mean scores for
subjects with other disorders were 4.00 (Antony et al., 2001). The same sources reported that
in a non-clinical control study the mean score was 3.48.
Reliability and validity studies indicated similar results. Internal consistency was
deemed excellent according to Antony et al. (2001). Antony et al. reported that the RAS had
a Cronbach’s alpha of .92. Test-retest was also reported to be high (r = .94). Participants
77
with OCD scored significantly higher than participants with other anxiety disorders and the
controls. Interestingly, Antony et al. reported that the RAS was a strong predictor of
obsessionality; however, this was not true of depression and anxiety. This could play a vital
role when safety could be an obsessive issue.
The criterion variable was presented within the Demographic Questionnaire. A
simple poll requiring a Yes or No answer served to determine individual support for the
presence of CCW on campus, and whether the individual was concerned about safety on
campus. In addition, the participant was asked to answer a few demographic questions
including age, gender, level of education, and race (see Appendix B).
While the purpose of the pilot study was not to gauge the participants according to
measured responses, it served to highlight potential problems in understanding the outcome
measures later. To this end, the pilot study served as a valuable tool.
Population and Sample
The target population for this study was students from a small liberal arts college
within a one-hour drive of Virginia Tech’s Blacksburg campus. Evaluation of students was
undertaken during the spring semester of 2013. The school had approximately 400 on
campus students, but it was impossible to survey all of them.
Participants were recruited to provide sufficient power to conduct linear regression
and correlation analysis. If the sample size were too low, then a Type II error would occur
(i.e., the null hypothesis is not rejected when, in fact, the data are consistent with the
rejection of the null hypothesis). In this study, there were three predictor variables in the
linear regression and correlation model; therefore, the minimum number of participating
students should have been about 120 to 160. Power analysis was performed using G*Power
78
3.1.2 software (Faul, Erdfelder, Lang, & Buchner, 2007). The input parameters were the
expected probability of the criterion variable = .5; the expected odds ratio = 1.5, the
significance level for rejecting the null hypothesis, α = .05, and the power to reject the null
hypothesis, 1 – β = 0.8. The computed minimum sample size was N = 163. One hundred
sixty-nine participants were utilized in the final study.
Ethical Concerns
Ethical concerns were monitored at all times. Ethical training dealing with human
subjects was required by the researcher’s university. Proof of this training was required
before research could begin. Additionally, each participant and organization involved was
informed that participation was wholly voluntary and said participation could be revoked at
any time by request of the participant. This occurred when the researcher visited the
classrooms in question. A full explanation of the study was offered. The instruments were
handed out and fully discussed. Any questions were addressed. The informed consent (see
Appendix A) was then handed out, discussed, and signatures were acquired. Participants
were guaranteed protection of their information in two ways. First, the measures completed
had no identifying marks. Secondly, the measures would remain in a locked, secure, or
otherwise safe state.
Pilot Study
As previously mentioned, a pilot study was carried out with 20 students participating.
The pilot study group was comprised of 11 males and 9 females. Eighteen of the students
ranged in age from 17 to 24 years of age. Two were males aged 42 and 44. Eleven of the
students were sophomores, and nine were freshmen.
79
Data Collection
The researcher was able to visit random classrooms at a small liberal arts college in
Virginia as a means of gaining convenient access to students. Students were approached
with college permission. The study was explained to each class as a group. Information
within the consent form was discussed (see Appendix A), and each measure was addressed.
Requests were made that the students take the measures seriously. They were also asked not
to communicate with each other during the process. The researcher was available for
specific questions if needed by the raising of hands.
Students were simply told that research was being conducted to determine a
correlation between support/opposition for CCW on campus, defensive pessimism as a
coping strategy, fear, and responsibility. The researcher told students that approximately 20
minutes were required to complete the study’s measures; however, they were also told that
they were to read carefully and to take their time. They were informed that time was not an
issue as truthful rather than quick responses were desired. As mentioned previously, the
measures utilized were the Defensive Pessimism Questionnaire (see Appendix C), the Fear
Questionnaire (see Appendix D), and the Responsibility Attitude Scale (see Appendix E).
Each participant was handed a prepared packet that included a review of the proposed
project, a consent form to be signed, and assurances of privacy explaining how the materials
would only be available to the researcher before being locked away upon research
completion. Upon accepting the conditions of research as outlined in the informed consent,
the participants were also asked to answer a few demographic questions including age,
gender, level of education, and race. This page also included a poll that required Yes or No
answers regarding whether the participating individual supported the presence of CCW on
80
campus and whether he or she was concerned about safety on campus. The DPQ, the FQ,
and the RAS followed. The packet was comprised of these materials only. Students were
given a copy of the consent form for their own personal use.
Completed materials were maintained on site in a closed container (a pilot’s case)
with a combination lock, and the container was under the constant surveillance of the
researcher. After returning from the research site, materials were kept in a locked filing
cabinet in this researcher’s home office. The materials were not and will not be accessible to
anyone with the exception of this researcher. Once the research was conducted, materials
were kept safe in a locked environment where they will be held for 7 calendar years. After
this 7-year period, all data (surveys, discs, etc.) will be destroyed via shredding.
The majority of the research went very smoothly. Two separate incidents occurred in
which participants wanted to argue an “it depends” attitude as far as the criterion variable
statement allowing CCW on campus was concerned. These students were asked to simply
explain their positions in writing on the measure. These two student responses, in their
entirety, were later removed from the final number as they did not answer “Yes” or “No” to
the measure in question. The request to have the students write their responses seemed to
work as no disruption was brought as a result of the questions.
Data Analysis
The criterion variable was dichotomous, representing only two possible outcomes,
coded by 1 (for the outcome that the researcher wants to predict) and 0 (for a reference
outcome). In the study, the researcher wanted to predict the likelihood that a participant
would support CCW on campus (relative to not supporting CCW on campus). Consequently,
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all of the participants who answered Yes in the poll were coded with 1, and all the
participants who answered No were coded with 0.
There were three potential predictors of the criterion variable, measured at the
scale/interval level, specifically (a) defensive pessimism; (b) fear; and (c) responsibility. The
variables were analyzed using a linear regression and correlation model. Because linear
regression offered a non-parametric method, the variables did not have to be normally
distributed, so testing for normality was not essential. It was, however, assumed that the
predictor variables were independent, meaning that they should not be very highly
intercorrelated with each other, otherwise the statistical inferences may be compromised
(Hosmer & Lemeshow, 2000). This assumption was checked by correlation analysis. If two
or more of the predictor variables were very strongly inter-correlated (indicated by a
correlation coefficient > .8), they were transformed by multiplication to create a composite
predictor variable.
If the three-predictor variables in this study were measured using different numerical
scales, they would be standardized so that their relative effects on the criterion variable could
be directly compared. The three variables would be standardized by conversion to z-scores
(i.e., subtracting the mean value from each score, and dividing by the standard deviation, so
that each predictor is measured with a standard scale, ranging from a minimum of about -3 to
a maximum of about +3, assuming that they are approximately normally distributed).
However, since each measure’s results were converted to a three-point scale, this was not
necessary.
A logistic regression model must not be fitted with too many or too few predictor
variables. Only meaningful predictors with β coefficients that are significantly different from
82
zero should be included (Hosmer & Lemeshow, 2000). The three standardized variables
were tested for their statistical significance as predictors of the criterion variable using the
Wald χ
2 statistic. The β coefficient was significantly different from zero if p < .05 for the
Wald χ
2
statistic, justifying the retention of the predictor variable in the model. If p > .05 for
the Wald χ2
statistic, then the β coefficient was not significantly different from zero,
justifying the deletion of the predictor variable from the model.
The odds ratio (OR = e β
) was computed to represent the effect size attributed to each
predictor variable. The OR measured the relative effect that a standardized predictor variable
had on the criterion variable (Hosmer & Lemeshow, 2000). For example, in this study, if OR
= 2.0 for Pessimism and OR = 4.0 for Fear, then it could be inferred that Fear had a relatively
greater effect than Pessimism on the probability that a participant would support CCW on
campus. If the codes for the criterion variable were reversed, the reciprocals of the ORs were
obtained (e.g., if all the participants who answered Yes in the poll were coded with 1, and all
the participants who answered No are coded with 0, then each of the OR values would
become 1/OR). If the OR = 1.0, the predictor variable had no significant effect. If the OR >
1.0, an increase in the standardized score of the predictor variable increased the likelihood
that the participant supported CCW on campus. If the OR < 1.0 then an increase in the
standardized score of the predictor variable decreased the likelihood that the participants
supported CCW on campus. If the 95% confidence intervals for the OR did not include 1.0,
the OR was significantly different from 1.0 at p < .05. If the 95% confidence intervals for
the OR did include 1.0, the OR was not significantly different from 1.0.
The researcher expected that the outcome of the logistic regression analysis would be
that all three of the β coefficients would be significantly different from zero, and all three of
83
the ORs would be significantly different from 1.0. These statistics would provide the
evidence to reject the null hypothesis, and support the research hypothesis, that pessimism,
fear, and responsibility were significant predictors of the probability that a participant would
support CCW on campus (relative to not supporting CCW on campus).
If one or more of the three variables were not significant predictors, the research
hypothesis would not be completely supported. If none of the variables were significant
predictors, the research hypothesis was not at all supported, so it would be concluded that
pessimism, fear, and responsibility were not significant predictors of the probability that a
participant would support CCW on campus. Results would indicate correlational
relationships as opposed to causation. Whatever the results of the analysis, the logistic
regression model provided evidence that would warrant inclusion in the following Chapter
IV.
Summary
This chapter was designed to provide the methodology of the proposed study. A
convenience sampling of N = 169 students was utilized. The campus in question chose
participants because they represented a spectrum of majors as well as varying levels
(i.e., freshmen, sophomores, etc.). This was viewed as more beneficial than a volunteer
convenience sampling as it was a random cross section. A pilot study was employed to
verify the understandability of the measures utilized by the researcher. Areas of concern
were uncovered and corrected before the final sampling. Issues of validity were also
addressed. Internally, there was concern that the relationships discovered between the
criterion variable and the predictor variables might be been due to chance instead of
causality. However, results discovered in the study were found to be in line with other
84
studies strengthening concerns of internal and external validity. This will be addressed in the
following chapter. Lack of random sampling was a concern as well as the potential for
contamination by those with extreme views related to the criterion variable. Mortality was
not an issue. Pretest subjects were not utilized in the final study. A logistic regression and
correlation model was utilized to examine the relationship between the criterion and predictor
variables as the hypotheses were tested. Results of the study are presented in the following
chapters.
85
CHAPTER IV: RESEARCH FINDINGS
The keystone of this quantitative study was the question as to whether support for
CCW on campus could be determined by addressing levels of defensive pessimism, fear, and
responsibility. Levels of defensive pessimism, fear, and responsibility were weighed against
the acceptance or denial of CCW on campus. These were assessed in terms of the
hypotheses (H1) that defensive pessimism, fear, and responsibility would prove to be
significant predictors of the probability that a participant would support CCW on campus.
This stood in direct contrast to the null hypothesis (H0) in which defensive pessimism, fear,
and responsibility would not prove to be significant predictors of the probability that a
participant would support CCW on campus. To achieve this end, quantitative research
methodology, a linear regression model, was applied. This was underpinned by a
correlational design, defined as “research that involves collecting data in order to determine
the degree to which a relationship exists between two or more variables” (Fraenkel &
Wallen, 2010). As stated above, the research question that guided this study was “What are
the relationships between the participants’ support for concealed carry weapons (CCW) on
campus and their levels of defensive pessimism, fear, and responsibility?”
This chapter describes how the individual components (defensive pessimism, fear,
and responsibility) of the null hypothesis were tested, based upon analysis of the data mined
from 169 student responses. As mentioned in the previous chapter, the only statistical
method that could be justified to predict a nominal criterion variable was logistic regression
analysis (Hosmer & Lemeshhow, 2000). Because the criterion variable in this study had two
categories, linear regression analysis was necessary, based on the following model:
E(y) = α + βx with a prediction equation of ŷ = a + bx
86
Where: y would denote the response as to the support or denial of CCW on campus and x
would represent an explanatory variable. As a linear function, y is viewed as a function of x
with a straight-line graph in which beta is represented by slope β and the alpha by the
y intercept. In such a model, as Agresti and Finlay (2009) point out that if β is positive then
y will increase as x increases. Conversely, if β is negative then y will decrease as x
increases. In short, the study was designed to individually address each component of the
hypothesis. Assessment of the data began with an overview of the information as it related to
demographic variables. The data was then reviewed in terms of each of the variables (and
their variations) presented within the research question–defensive pessimism, fear, and
responsibility. Each of the following factors was addressed from two points of view (see
definitions in Table 1). Defensive pessimism was assessed based upon raw scores as well as
a scale conversion. Fear was assessed based upon the FQ17–one question specifically
addressing the fear of CCW in the respondent’s environment. FQ 16 is a scale based upon
total phobia scores. The Responsibility Attitude Scale was addressed based upon a singular
inverted scale. In short, though one research question was addressed, that question had
variations within the variables, and those were addressed accordingly and individually within
this chapter.
The purpose of this study was to determine if elevated levels of defensive pessimism,
fear, and responsibility–elements of the hypothesis, influenced the support of CCW on
campus. This stood in direct contrast to the null hypothesis that the support for CCW would
not be reflected in elevated levels of defensive pessimism, fear, and responsibility.
87
Pilot Study Results
The study proved very useful in testing the time commitment needed to complete the
study measures. It was assumed the average student would need 20 minutes to complete all
the measures of the study. This included reading and signing the consent form, completing
the biographical data page, and completing the Defensive Pessimism scale, the Fear
Questionnaire, and the Responsibility Scale. In conducting the pilot study, the average time
needed to complete the instruments was 19.1 minutes. However, fours students completed
the measures in 16 minutes while another four completed the measures in 18 minutes.
The pilot study also proved useful in determining certain problems students may have
with the measuring instruments. Two misspellings were discovered in the pilot study. An
error was found in the Defensive Pessimism Scale and the Fear Questionnaire. The
misspellings were corrected to prevent any possible misunderstanding on behalf of the
participants. Additionally, an important discovery was the need to differentiate the proposed
scenario from other instructions on the Defensive Pessimism Questionnaire. As originally
presented, the same font was used in the Defensive Pessimism Scale instructions and the
proposed scenario to which the participant was to react. This was seen as confusing to the
participants as they seemed to simply skim the directions and neglect the very important
scenario. The scenario was set apart by bolding and italics.
Overall, the pilot study proved useful. It must be reported that the researcher was
surprised to find that a majority of the students supported the presence of CCW as a means to
safety. This served as an impetus to pursue a study in which the roles of defensive
pessimism, fear, and responsibility are weighed against this support.
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Data Analysis
Altogether, 169 students from 21 different areas of study fully completed surveys
utilized for this study. Of the 169 participants, 38 (22.5%) indicated they did not support
CCW on campus while 131 (77.5%) did support CCW on campus. In addition, of the 169,
77 (45.6%) were female and 92 (54.4%) were male. Freshmen accounted for 103 (60.9%) of
the respondents; 40 (23.7%) were sophomores; 17 (10.1%) were juniors; 9 (5.3%) were
seniors. Racial identity was as follows: 20 (11.8%) were African American; 1 (.6%)
identified as Asian American; 3 (1.8%) identified as Hispanic; 136 (80.5%) identified as
White/Caucasian; and 8 (4.7%) identified as Other (including bi-racial). Of the 169
respondents, only 2 (1.2%) were not United States Citizens; 167 (98.8%) identified as United
States Citizens. Age breakdown was as follows: 124 (73.4%) were age 20 or under; 29
(17.2%) were aged 21 to 24; 3 (1.8%) respondents were aged 25 to 30; 3 (1.8%) was in the
31 to 34 age category; 5 (3%) were in the 35 to 40 age category; and 5 (3%) were in the over
40 age category.
Norem’s (2001) Defensive Pessimism Questionnaire (DPQ) also had 169 complete
responses. DPQ scores ranged from 22 to 79. These scores were then categorized to
correspond to the other variables. A score of 22 to 41 would not be categorized as a
Defensive Pessimist and would be labeled a 1. This range was considered strategic
optimism. A score of 42 to 61 would be labeled a 2 and would be categorized as using
strategic optimism and defensive pessimism. A score of 62 to 79 would be labeled a 3 and
categorized as a defensive pessimist. The mean score was 50.51. The standard deviation
was 11.106. Scores were recorded in two formats. The first format was a scaled version of
the responses. For the purposes of this sample, a score of 22 to 41, labeled a 1 in the scaled
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version, would not be categorized as a Defensive Pessimist. This range is considered
strategic optimism. A score of 42 to 61, labeled a 2 in the scaled version, would be
categorized as using strategic optimism and defensive pessimism. A score of 62 to 79,
labeled a three in the scaled version, would be categorized as a defensive pessimist. A record
of raw, unscaled, scores was also maintained. Of the 169 respondents in the current study, 42
(24.9%) could be labeled as strategic optimists; 101 (59.8%) are defined as using both
strategies. In this particular sample, 26 (15.4%) are defined as being defensive pessimists.
These scores were then scaled to correspond to the other variables. Again, a score of 22 to
41 would not be categorized as a Defensive Pessimist and would be labeled a 1. This range
is considered strategic optimism. A score of 42 to 61 would be labeled a 2 and would be
categorized as using strategic optimism and defensive pessimism. A score of 62 to 79 would
be labeled a 3 and categorized as a Defensive Pessimist. The raw scores were maintained as
a separate record to compare against the scaled version as a means of researcher validation.
The Fear Questionnaire was utilized in two ways. First, a total phobia score was
determined based upon responses to Questions 2-16 of the tool. This was labeled FQ16 by
the researcher. Seventy-six (45%) of the respondents fell into the “would not avoid to
slightly avoid” category (labeled category 1 by the researcher). These scores indicated an
absence or lack of real concern as far as common phobias were concerned. Similarly, 77
(45.6%) also fell into the “slightly avoid to definitely avoid” category (labeled category 2 by
the researcher), indicating a stronger presence of fear as was related to common phobias.
Finally, 16 (9.5%) fell into the “definitely avoid to markedly avoid” category (labeled
category 3 by the researcher), indicating higher levels of phobic response. None of the 169
respondents fell into the final category of “definitely avoid to always avoid.” Based upon
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categorical labeling, the mean of the FQ16 was 1.64 with a SD of .649. Then, a single
response was ascertained based upon one’s response to an item concerning one’s level of fear
in being in an environment where one knows there are CCW present. This was labeled FQ17
by the researcher. The Fear Questionnaire was not utilized beyond these two areas of
inquiry. As far as the general phobia portion (labeled FQ 16 by the researcher) of the
measure was concerned, 76 (45%) of the respondents fell into the “would not avoid to
slightly avoid” category (labeled category 1 by the researcher). These scores indicated an
absence or lack of real concern as far as common phobias are concerned. Similarly, 77
(45.6%) also fell into the “slightly avoid to definitely avoid” category (labeled category 2 by
the researcher) indicating a stronger presence of fear as is related to common phobias.
Finally, 16 (9.5%) fell into the “definitely avoid to markedly avoid” category (labeled
category 3 by the researcher) indicating higher levels of phobic response. None of the 169
respondents fell into the final category of “definitely avoid to always avoid.” The mean of
the FQ16 was 1.64 with a SD of .649.
The FQ17 portion of the FQ showed a more marked difference. Of the 169 complete
responses, 105 (62.1%) indicated they “would not avoid to slightly avoid” an environment in
which a known CCW was present. This was labeled FQ17-1 by the researcher. Another
36 (21.3%) indicated they would “slightly avoid to definitely avoid” an environment in
which a known CCW was present. This was labeled FQ17-2 by the researcher. Only 28
(16.6%) indicated they would “markedly avoid to always avoid” an environment in which
CCW were present. This was labeled FQ17-3 by the researcher. Based upon the categorical
labeling, the mean categorical score was 1.54 with a SD of .763.
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The Responsibility Attitude Scale (RAS) provided an average score from the 27
questions within the measure. RAS scores ranged from 1.81 to 6.12 with lower scores
representing higher levels of responsibility. These scores were then converted into scaled
variables corresponding to the other predictor variables. Low levels of responsibility, 4.69-
6.12, were labeled as a 1. Midlevels of responsibility, 3.25-4.68, were labeled as a 2. High
levels of responsibility, 1.81-3.24, were labeled as 3. The most frequent result was 3.92.
The mean was 3.6736. As cited in Antony et al. (2001), Salkovskis et al. (2000) indicated,
the average score on the measure for non-clinical controls was 3.48 with an SD of 1.01
during validation studies. The test was intended, as Antony et al. (2001) pointed out, “To
assess general attitudes, assumptions, and beliefs about responsibility” (p. 230). The lower
the score on the RAS, the great the personal feelings of responsibility. The higher the score,
the lower the personal feelings of responsibility. Scores were broken down into three
categories to meet the same standards of data presentation that can be seen in the RDPQ, the
FQ16, and the FQ17. Since the RAS returns higher levels of responsibility as lower
numbers, this particular scale will be reversed.
Analysis Conclusions
Per Hosmer and Lemeshow (2000), the three-predictor variables do not show a high
intercorrelation as is indicated by a correlation coefficient greater than .8. This being said, it
was determined that the three variables had no need to be transformed by multiplication to
create a composite predictor variable. Instead, regression was utilized to determine the
strength of each variable as a predictor of the proposed hypothesis that each factor would
show increased levels based upon how participants responded to the criterion variable.
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Utilizing Linear Regression and comparing the criterion variable to the predictor
variables, a varied image begins to appear. Beginning with the predictor variables, each
variable will be addressed.
Assessment of Defensive Pessimism Scale 1-3
Based upon the Linear Regression analysis and a confidence interval of .95, it was
determined that the null hypothesis was retained. The data supplied within this study did not
bear out the proposed hypothesis that indicated a relationship between the criterion variable
of support for CCW and defensive pessimism, fear, and responsibility. As far as defensive
pessimism scaled scores (DPSCALE) were concerned, research found a correlation of .077.
When the defensive pessimism raw scores (DP) replaced the scaled version of the scores
(DPSCALE), the correlation was recorded at .063. The two-tailed significance level for DP
was .320. Again, the Null Hypothesis, as far as DP and DPSCORE were concerned, was
retained. The similarities were too small to support the proposed hypothesis.
Assessment of FQ 17
A similar scenario was revealed when the criterion variable was analyzed in
conjunction with the FQ17 predictor variable. The correlation level returned was .434,
indicating a weak possibility a relationship exists. However, the two-tailed significance was
.000. Chance was not really a factor in comparing these two items simply because of the
similar nature of the information sought in the variables. This being said, the null hypothesis
was not retained based upon the empirical data. A strong relationship was indicated between
the variable FQ17 and support or denial of CCW.
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Assessment of FQ 16
When the criterion variable was addressed in terms of the FQ16 a correlation rate of
-.120 was returned. The significance level was .119. Again, this was outside the .05 level.
However, the data does suggest that an inverse relationship was possible (i.e., a negative
correlation between the two variables). This was expected, but it is not statistically
significant. Perhaps a larger sample size would bear this out. However, based upon the
parameters of the study, the null hypothesis was retained. A linear regression curve fit shows
this inverse relationship.
Assessment of RAS
In looking at the RAS raw data, a correlation of only .005 was returned along with a
significance level of .935. When addressing the RASADJ, an inverse correlation of -.007
and a significance level of .924 were returned. The null hypothesis was retained.
Assessment of Demographics
Though not variables in the study, it was relevant to mention the demographic
components. Age correlated with each of the factors as follows: with the Yes/No criterion
variable there was a correlation of .098, with DP there was a correlation of .061, with FQ17
there was a correlation of -.09, with FQ 16 there was a correlation of -.098, and with RAS
there was a correlation of -.157. Class correlated with the variables as follows: with Yes/No
there was a correlation of .077, with DP there was a correlation of -.009, with FQ17 there
was a correlation of -.080, with FQ16 there was a correlation of -.096, and with RAS there
was a correlation of -.049.
Sex correlated to the variables as follows: the criterion variable correlated at -.037,
DP correlated at .030, FQ17 correlated at -.048, FQ16 correlated at -.263, and RAS
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correlated at -.089. Major correlated at -.022 for the criterion variable, for DP it correlated at
.184, FQ17 correlated at .051, FQ16 reported at .014, and RAS reported at -.096. Because of
the disproportionate number of Caucasian and US citizen respondents, these two areas were
not addressed.
Summary
Based upon the data mined from 169 student responses, it was concluded that the null
hypothesis was supported. The evidence simply did not support the researcher’s entire
hypothesis. All variables were insignificant when viewed via a correlational and logistical
regression approach. The only exception, as has been discussed and was born out in the
following chart (see Table 5), was the relationship between the predictor variable and the
criterion variable labeled FQ17. Based upon the data, it appears that fear plays a role in two
sub-areas of FQ 17: “would not avoid to slightly avoid” and “markedly avoid to always
avoid.” In the FQ17 category as a whole data returned a Wald Chi Square score of 23.797
and a significance rate of .000. This indicates a strong relationship. When addressed based
upon scaled responses, the fear element is even more marked. The “would not avoid to
slightly avoid category” saw a Wald Chi Square score of 20.312 and a significance rate of
.000. The “markedly avoid to always avoid” category saw a Wald Chi Square score of
21.912 and a significance rate of .000. When compared to the middle FQ17 category the
significance is marked in comparison. Scaled level 2 of FQ17 only saw a Wald Chi Square
of 3.554 and a significance rate of .059. Other than the FQ17 variables, data indicated weak
relationships between the predictor variables and the criterion variable.
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Table 5
Utilizing Linear Regression an Association can only be Established in Relation to the FQ17
Category Significant at the Extremes of the Response Scale.
B S.E. Wald Df Sig Exp(B)
DPscore .021 .041 .259 1 .611 1.021
FQ17 21.912 2 .000
FQ17(1) 2.693 .598 20.312 1 .000 14.782
FQ17(2) 1.106 .587 3.554 1 .059 3.023
FQ16 .433 2 .805
FQ16(1) -.539 .821 .431 1 .512 .583
FQ16(2) -.380 .750 .257 1 .612 .684
RAS -.055 .664 .007 1 .935 .947
DPscale .318 2 .853
DPscale(1) .076 1.335 .003 1 .955 1.079
DPscale(2) .292 .840 .121 1 .728 1.339
RASadj .048 2 .976
RASadj(1) 19.697 13549.94 .000 1 .999 3.583E8
RASadj(2) .173 .788 .048 1 .826 1.189
Constant -1.206 3.841 .099 1 .754 .299
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CHAPTER V: REVIEW
The goal of this work was to address limited possibilities (predictors) as to why
individuals may support CCW on a college campus. In this chapter, the confines in which
those limited possibilities (predictors) were addressed are reviewed, findings are addressed,
and these findings are assessed in relation to similar studies. Implications for future study are
then addressed. In short, this chapter serves to emphasize the need for continued work in the
area of weapons, CCW in particular, and the effort to understand why certain individuals feel
safer when such weapons are present.
The hypothesis, H1, was framed around the premise that defensive pessimism, fear,
and level of responsibility would be significant predictors of the probability that a participant
would support CCW on campus (relative to not supporting CCW on campus). The null
hypothesis, H0, asserted that defensive pessimism, fear, and level of responsibility would not
be significant predictors of the probability that a participant would support CCW on campus
(relative to not supporting CCW on campus). Based upon the data mined from 169 student
responses, it was concluded that the null hypothesis must stand in the cases of defensive
pessimism and level of responsibility. The evidence simply did not support the researcher’s
hypothesis as far as the two-predictor variables were concerned. They were insignificant
when viewed via a correlational and logistical regression approach. The same did not hold
true as far as fear was concerned. Fear (FQ 17) was a strong indicator. High levels of fear
were found to indicate support for and against CCW on campus. In other words, fear (FQ
17) was duplicitous. For those who strongly supported CCW on campus, there was a clear
statistical relationship. For those who strongly opposed CCW on campus, there was also a
strong statistical relationship. The same did not hold true for those who had median fear as
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associated with weapons on campus. This was in line with the findings of the PRC (2013) in
which reasons for firearm ownership closely correlated with issues of personal safety. This
stood to pique the researcher’s further interest in weapons and what may draw certain
individuals to them as opposed to others. Though this type of study did not seem to have
been carried out in the past in any detail, research does exist that indicates there is a tie
between weapons and attitudes of individuals.
As previously mentioned, very recent research by the PRC (2013) indicated a change
in attitude toward weapons. According to the PRC, there has been a distinct change in the
reasoning offered by US citizens for gun ownership since 1999. The PRC made this
determination by comparing two studies. The first was carried out in 1999. This study was
then compared to a February 2013 study that utilized the same instrument of measure
employed in the 1999 study. In 1999, 49% of respondents indicated that they owned a gun
specifically for hunting purposes. In the same study, only 26% of respondents indicated they
maintained a firearm for protection purposes. In the February 2013 study, the PRC found a
reversal of these standings. Those who reported owning firearms for protection increased
22% to an overall 48%. Those who reported owning firearms for hunting saw a decrease of
17% to an overall 32%. Likewise, the PRC found slight decreases in the number of
respondents who claimed to have owned weapons for target/sport shooting, 2nd Amendment
issues, and collecting. Protection (i.e., safety) was the number one issue stated by
respondents. Similarly, of those who reported they did not own guns, the PRC found that
58% cited concerns about safety as a determining factor in keeping guns out of their homes.
In conclusion, safety was a concern from both points of view. Additionally, according to the
PRC, 58% were very concerned that the federal government’s current move toward more
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restrictive guns laws would make it more difficult for individuals to access guns to protect
themselves. When broken down along ownership lines, the difference was even more
marked. In households that did not own guns, the PRC reported that 66% believed stricter
gun laws would prevent events such as mass shootings. Gun owners did not concur.
According to the PRC, only 35% of gun owners believed stricter laws would prevent deaths
caused by mass shootings.
Framing such attitudes with the educational environment and Maslow’s theories
further complicated the issue. As Notlemeyer et al. (2012) pointed out, studies related to
Maslow’s hierarchy and academic success were very limited. The authors indicated they
were only able to find one study related to the subject; this was a study they cited by Smith,
Gregory, and Pugh (1987). This particular study investigated students’ needs in relation to
four of Maslow’s hierarchical levels: security, love/belonging, esteem, and self-actualization.
The fact that security was one of the needs addressed in academic success gives credence to
the study of CCW and the need for safety in a higher education setting despite limited
research. This stood in contrast, as Noltemeyer et al. pointed out, to the link between
academic success and very basic needs, such as health in young students (mainly elementary
aged) has already been well established.
This said, Notlemeyer et al. (2012) indicated that a sizeable portion of school-aged
children have a deficiency as related to Maslow’s needs hierarchy. In particular, the authors
noted that what was not understood was how physiological needs, safety needs, and
love/belonging needs actually related to each other and how they related to an individual’s
academic success. “Research has not yet examined the relationships between particular
deficiency needs (e.g., physiological, safety, and love/belonging needs) and specific growth
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needs (e.g., academic and cognitive outcomes)” (Notlemeyer et al., 2012, p. 1864). The
authors indicated that such research could help further clarify Maslow’s theory while
shedding new light on areas of need so students’ academic careers can be enhanced.
Additionally, given instances of violence at the Appalachian School of Law and
Virginia Tech, coupled with continued insistence on the behalf of lawmakers concerning gun
rights within the researcher’s home state of Virginia, the very presence of weapons
(including CCW) remained an interest based upon research. Nagtegaala, Rassinb, and Muris
(2009) studied the link between aggression and guns, and they found that the existing
literature was quite broad as far as this relationship was concerned. For example, they
indicated that to some even the presence of firearms was believed to make individuals
aggressive. Referring to the Berowitz and LePage (1967) famous study, Nagtegaala et al.
emphasized the finding that study participants who were angry administered a greater
number of electrical shocks to test subjects in the presence of a gun than they did in the
presence or absence of another object. This became known as the weapons effect and
spawned extensive research (Nagtegaala et al., 2009). This added validation to the research
question posed by the researcher.
Findings
The research (H1) hypothesis was tested using linear regression and correlation
analysis. The research hypothesis, H1, proposed that defensive pessimism, fear, and
responsibility were significant predictors of the probability that a participant would support
CCW on campus (relative to not supporting CCW on campus). The null hypothesis, H0,
contended that defensive pessimism, fear, and responsibility were not significant predictors
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of the probability that a participant would support CCW on campus (relative to not
supporting CCW on campus).
As stated in the previous chapter, based upon the data mined from 169 student
responses, the null hypothesis for all predictor variables except FQ17 was born out. The
evidence simply did not support the researcher’s hypothesis as far as the remaining predictor
variables were concerned. All variables were insignificant (with the exception of FQ17)
when viewed via a correlational and logistical regression approach. The only exception, as
was discussed in Chapter IV, was the relationship between the criterion variable and the
predictor variable labeled FQ17. However, the fact that the “would not avoid to slightly
avoid category” saw a Wald Chi Square score of 20.312 and a significance rate of .000, and
the “markedly avoid to always avoid” category saw a Wald Chi Square score of 21.912 and a
significance rate of .000 is intriguing when compared to the middle FQ17 category with a
Wald Chi Square of 3.554 and a significance rate of .059. The fear is definitely polarized
and supports data presented by the PRC (2013) in which those who reported owning firearms
for protection increased 22% to an overall 48% while those who reported owning firearms
for hunting saw a decrease of 17% to an overall 32%. Clearly, fear was a factor in these
changes and represents an area of potential research for the future. However, other than fear,
data indicated weak relationships between the criterion variable and the predictor variables.
Interpretation of the Findings
The presented study was designed to determine whether a linear and correlational
relationship existed between support for CCW on campus and the variables of defensive
pessimism (as a cognitive coping strategy), fear, and responsibility. The predictor variables
addressed included responsibility attitudes as reflected by the Responsibility Attitude Scale
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(RAS). Fear was measured using the Marks and Mathews Fear Questionnaire in two ways.
First, in what was labeled FQ16, a total social phobia score was obtained. Secondly, in what
was labeled FQ17, a single dimension fear specifically related to CCW in one’s environment
was established. Defensive pessimism, as addressed in Norem’s (2001) revised DPQ was
also utilized. This variable was also addressed in two ways. First, the raw score was
addressed in what was labeled DPSCORE. Next, the score was broken down into a threetiered
scale in which the number 1 represented an individual who was definitely not a
defensive pessimist, but were, instead, strategic optimist. The number two represented
individuals who utilized defensive pessimism and strategic optimism equally. Finally, the
number three represented individuals who were true defensive pessimists. The anchoring
variable (criterion variable) was the study participants’ support or rejection of concealed
weapons on campus. This was determined from participants’ response to a simple yes or no
statement.
Defensive Pessimism Scale
Based upon linear regression analysis, a confidence interval of .95 and a correlation
of .077 determined that the null hypothesis was to be retained. Defensive pessimism scores
and support for CCW was not born out; the data supplied within this particular study did not
bear out the proposed hypothesis. When the defensive pessimism raw scores (DP) replaced
the DPSCALE (1-3) the correlation was recorded at .063. The two-tailed significance level
for DP was .320. So, again, the null hypothesis was retained.
FQ 17
A similar scenario was revealed when the criterion variable was analyzed in
conjunction with the FQ17 predictor variable. The two-tailed significance was .000. This
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indicated a strong relationship between the support or denial of CCW on campus and specific
personal safety feelings. The polarized results between the categories, as previously
discussed, do prove very interesting as they indicate a divided society.
FQ 16
When the criterion variable was addressed in terms of FQ16, a correlation rate of
-.120 was returned. A significance level of .119 was also returned. Again, this was outside
the .05 level. However, the data did suggest that an inverse relationship was possible (i.e., a
negative correlation between the two variables). This was expected, but it was not
statistically significant. Perhaps a larger and more diverse sample size would bear this out.
However, based upon the parameters of the study, the null hypothesis was retained.
RAS
In looking at the RAS raw data, a correlation of only .005 was returned as was a
significance level of .935. When addressing the RASADJ, an inverse correlation of -.007
existed as did a significance level of .924. Again, the null hypothesis was retained.
Demographics
Though not variables in the study, it was relevant to mention the demographic
components. Age correlated with each of the factors as follows: with the Yes/No criterion
variable there was a correlation of .098, with DP there was a correlation of .061, with FQ17
there was a correlation of -.09, with FQ 16 there was a correlation of -.098, and with RAS
there was a correlation of -.157. Class correlated with the variables as follows: with Yes/No
there was a correlation of .077, with DP there was a correlation of -.009, with FQ17 there
was a correlation of -.080, with FQ16 there was a correlation of -.096, and with RAS there
was a correlation of -.049.
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Sex correlated to the variables as follows: the criterion variable correlated at -.037,
DP correlated at .030, FQ17 correlated at -.048, FQ16 correlated at -.263, and RAS
correlated at -.089. Major correlated at -.022 for the criterion variable, for DP it correlated at
.184, FQ17 correlated at .051, FQ16 reported at .014, and RAS reported at -.096. Because of
the disproportionate number of Caucasian and US citizen respondents, these two areas are
not addressed.
Limitations of the Study
This study was constructed around the premise that violence has become a part of life
in the 21st century. This premise was framed around the knowledge that based upon recent
events of domestic and international violence, including acts of terrorism, a new era marked
by turbulence and caution has emerged. Recognizing this potential for violence and the
concerns it created for some, Maslow’s theory of the hierarchy of needs was employed.
Acknowledging that lower level needs must be met before higher level needs can be pursued,
the issues of personal safety and educational pursuits formed the foundation of the proposed
hypothesis. In other words, in a stable society marked by occasional acts of violence, even
on college campuses, how can an individual meet his or her safety needs yet still pursue the
higher level goal of obtaining an education? The research hypothesized that defensive
pessimism, a cognitive coping strategy, provided a bridge that completed Maslow’s hierarchy
of needs for some individuals by supporting CCW on campus. In other words, defensive
pessimism filled the void on the safety level so that attention can be placed on personal
growth.
In constructing this hypothesis, it was assumed that there would be a correlation
between defensive pessimism and the support for CCW on college campuses as well as the
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need to satisfy lower level needs in order to pursue higher level needs. It was also assumed
that there would be a correlation between defensive pessimism and fear, and between
defensive pessimism and responsibility would. Data collected from students at a small
Liberal Arts college in Southwestern Virginia were utilized in the attempt to help prove or
disprove the hypotheses for this study.
The study had limitations. First, the study took place on a campus that was within a
one hour drive of Virginia Polytechnic Institute and State University (Virginia Tech), the site
of the nation’s deadliest school shooting. The affinity many had with the Blacksburg campus
could have possibly tainted the views of many students. Secondly, the subject of gun rights
was one of the most debated issues in the nation. There was a long tradition of debating
Second Amendment rights in this country, and people have had very strong feelings
concerning the expansion or limitation of these rights. This is especially true in the aftermath
of the December, 2012, Newtown, Connecticut shooting of 20 first graders. In addition, the
campus and many of its students hailed from rural areas where gun ownership was
commonplace. This was reflected by the fact that of the 169 participants, 77.5%, or 131
students, believed that CCW on campus was a good idea. In other words, only 22.5%
opposed CCW on campus.
The participants were chosen through convenience sampling. As Black (1999)
pointed out, convenience sampling can bias the results because subjects might not be
representative of the population as a whole. This was a concern. However, the research site
in question chose the classes that could be accessed. The classes were representative as far
as majors and class level. Concern still remained. One issue was the rural setting of the
college in question coupled with the fact that some of the participants came from rural
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settings where gun ownership tends to be higher. Further cases of national violence, such as
the Newtown, CT shooting, could also have heightened fears in study participants and caused
a positive response to the CCW question without allowing proper time to “think through” the
components of the measures. This was reflective of the recent research presented by the Pew
Center (2013) in which guns were found to be more associated with safety than in previous
years.
Implications
Despite the results of the data in this particular study, the failure of the hypothesis, the
researcher believed that a better understanding as to why some individuals feel greater levels
of safety when in the presence of firearms could be determined. For one, Maslow’s theories
have been widely accepted. Germana (2007) indicated that Maslow believed in “a sine qua
non of creativeness” (p. 67) that is translated as “a fusion of person and world” (p. 67). This
being said, personal safety could not be ignored as one progresses the levels of his hierarchy.
Additionally, as Roark (1987) pointed out, “College campuses are a part of society and are
subject to the same forces that permeate contemporary society” (p. 367). In other words, if
society becomes more violent, we can expect the same of the nation’s college and university
campus populations. Individuals who are concerned about personal safety must cope in some
manner. This is especially true when an educational environment is taken into account for
your adults. According to Rollins (2010), and as mentioned in Chapter I, college and
university campuses have been seen as “Ivory Towers” where students were “insulated from
the community and protected from hurt, harm, and/or dangers” (p. 1). This no longer
necessarily holds true. Similarly, much research has gone into why certain individuals
become violent in various situations and settings. From a sociological point of view, as
106
Staub (2003) indicated in a study of mass acts of violence, society offers insight. As the
author pointed out, all societies can be divided into “us” and “them” (p. 792) components.
These monikers imply that there is an imbalance–real or perceived–between two groups.
The “them” group feels “devalued” (Staub, 2003, p. 792) in one way or another. As Staub
discussed, this equation can be used to define intra-societal violence. When applied to a
college and university campus setting, this argument can be seen to stand true as well. After
all, Notlemeyer et al. (2012) indicated that their own work offered “some support for
Maslow’s assertion that growth needs such as academic progress may be positively related to
improvements in deficiency needs such as safety and love/belonging” (p. 1866). Finally, as
Nagtegaala et al. (2009) indicated in citing Berowitz and LePage (1967), to some, even the
presence of firearms was believed to have an impact on the way an individual felt in a given
setting (the weapons effect). The hypothesis was but one way of testing such a concept and
has borne out that fear is an issue as far as CCW are concerned.
Future Research
The one thing that stood out based upon the collected data and data analysis was that,
though not significant, there was a tendency to indicate that there could be a relationship
between the support for CCW on campus and Defensive Pessimism. Based upon a
confidence interval of .95, research found a correlation of .077 between the two variables.
When the DP raw scores (DP) replace the DPSCALE (1-3) the correlation is recorded at
.063. These returns are very intriguing and warrant further investigation. The two-tailed
significance level for DP was .320. Though not significant according to the boundaries of
this study, this number does represent, by the researcher’s interpretation, a real need to dig
deeper and expand the research field. Though the similarities are too small to support the
107
proposed hypothesis, the structure of the current research could have produced a Type II
error.
Discussion
As discussed, Norem (2002) argued that the concept known as defensive pessimism
was a real coping strategy. It allowed anxious individuals to control their anxieties and
progress instead of allowing those same anxieties to tear them down. In other words, it
addressed anxiety rather than ignoring it. Norem defined defensive pessimism as:
the process that allows anxious people to do good planning. They can’t plan
effectively until they control their anxiety. They have to go through their worst-case
scenarios and exhaustive mental rehearsal in order to start the process of planning,
carry it through effectively, and then get from planning to doing. (p. 48)
Additionally, citing Klinger (1975), Emmons (1986), Little (1983), and Cantor and
Kihlstrom (1987), Cantor et al. (1991) wrote that these appraisals reflect “current concerns
that consume people’s thoughts and guide their attention selectively” (p. 426). In short,
people have different goals at different points in time. Safety has been one of the goals
pertinent to this study. Based upon the analysis returned in this study, the researcher feels
this remained true. As Norem (2002) made clear, defensive pessimism is a coping strategy
“by which negative thinking transform[s] anxiety into action” (p. 5). The evidence points out
that there was an interesting correlation between the criterion variable and the predictor
variable of defensive pessimism. Additionally, it was important to keep in mind that,
according to Norem, anxiety was used for a positive outcome, so successful use of the
strategy did not depend on past anxiety. It was a strategy that utilized anxiety about what is
to come, a strategy that used a new situation and the anxiety this new situation brought began
a planning process that brought about the most positive outcome. As Cantor et al. (1993)
pointed out, “Individuals can and do use their social world in useful ways to navigate crises
108
and transitions, small and large” (p. 275). In this process, as Norem (2008) pointed out,
defensive pessimism “can mitigate” (p. 123) the negative aspects of an individual’s anxiety
so that attention can be placed on goal performance.
Additionally, as the PRC (2013) pointed out, 37% of US households had a gun
present. Seventy-nine percent of this number reported that gun ownership made them feel
safer. Similarly, of those who reported they did not own guns, the PRC found that 58% cited
concerns about safety as a determining factor in keeping guns out of their homes. Safety was
a concern from both points of view. However, as previously discussed, in households that
did not own guns, the PRC reported that 66% believed stricter gun laws would prevent events
such as mass shootings. Gun owners did not concur. According to the PRC, only 35% of
gun owners believed stricter laws would prevent deaths caused by mass shootings. This
being said, perhaps a better line of inquiry would be to determine gun ownership status and
then test for the presence of defensive pessimism. Fear and responsibility could once again
be variables. After all, as Ferguson (2009) clearly related, in areas that are under-researched,
convenience sampling can help establish an initial view for future research.
109
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Appendix A
Informed Consent Form / IRB Approval # 12-041-0
You are being invited to participate in a research project conducted by Brian Wright, who is a
doctoral candidate at University of the Rockies.
You are invited to participate in a research study about defensive pessimism as a coping strategy as it
relates to the support of concealed carry weapons on campus, fear, and responsibility. The title of this
dissertation research project is DEFENSIVE PESSIMISM AND CONCEALED CARRY WEAPONS
ON CAMPUS: CAUSE FOR CALM OR CONCERN
You will be asked to state your position as to concealed carry weapons on campus. You will also be
asked to participate in three short measures: the defensive pessimism questionnaire, the Fear
Questionnaire, and the Responsibility Attitude Scale. Participation will take about 20 minutes of your
time. You will simply read the questions presented in the measures and respond by writing or
circling a numeric or pre-determined response as to level of agreement.
It is anticipated that the potential risk associated with this study will be negligible. However, you will
be asked to be honest concerning your fears and level of responsibility. If you do experience any
discomfort, please see the information at the end of this document regarding resources that you can
access. You will receive nothing as far as compensation for your participation.
If you have decided to participate in this project, please be reassured that your participation is
voluntary, and that you have the right to withdraw your consent or discontinue participation at any
time without repercussion. You also have the right to refuse to answer any question(s) for any reason
with no repercussion.
In addition, your individual privacy will be maintained in all publications or presentations resulting
from this study. Names will NEVER be used as a part of this or any future study. The researcher will
maintain, under lock and key, the instruments of measure and all related forms, and said documents
will be securely discarded after 7 years using a shredder. The findings will never be shared with
anyone in any way in which anonymity will be violated.
If you have any questions regarding this project, you may contact the researcher at 276-964-7207.
If you have questions regarding your rights as research participant or any concerns regarding this
project, you may report them – confidentially, if you wish, to Dr. David Solly or Dr. Deborah
DeSorbo, the UoR Chairpersons of the Institutional Review Board at (719) 442-0505. The extension
for Dr. DeSorbo is 1617, and for Dr. Solly, 1652. You may also contact my Dissertation Chair, Dr.
E. Barra-Johnson., at Eszter.Barra.Johnson1@rockies.edu.
A copy of this consent form will be provided to you.
118
Important information for you:
Because of the nature of the current study and associated gun violence seen around the nation, it is
important to recognize that certain emotions and/or feelings may be elicited. The University of the
Rockies and the researcher in question seek as little distress as possible for research participants. If
you, as a participant, in any way, feel distress or concern for your personal safety it is recommended
that you contact the student counseling center or other counselor as quickly as possible to discuss
your concerns.
Bluefield College offers a wide array of services including counseling for enrolled students of all
academic levels at the Student Development House. The center is located in the Student Development
House on Faculty Row on the Bluefield College campus. The Center can be reached by phone at
(276) 326-4473 or email at ksomers@bluefield.edu.
I understand the above information and voluntarily consent to participate in the research.
Signature of Participant: ______________________________ Date: _____________
IRB Approval Number: ___12-041-0_______ IRB Expiration Date: _____9/12/2013____
119
Appendix B
General Statement
I believe that qualified individuals carrying concealed weapons on a college campus is good for
the overall safety of the campus.
Please indicate whether you agree or disagree with the above statement by circling on of the
following:
Yes, I agree with the statement No, I disagree with the statement.
Please provide the following information by circling or writing in the proper response:
I am:
Male Female
I am:
A Freshman A Sophomore A Junior A Senior A Grad student
I am:
– White (includes Arabian)
– Black (includes Jamaican, Bahamian, and other Caribbeans of African but not Hispanic or Arabian
descent)
– Hispanic (includes persons of Mexican, Puerto Rican, Central or South American or Spanish origin
or culture).
– Asian and Asian American (includes Pakistanis, Indians, and Pacific Islanders)
– American Indian (includes Alaskans)
I am:
A US citizen not a US citizen
I am (Please state your age)______________________.
My major is _______________________.
120
Appendix C
The Revised Defensive Pessimism Questionnaire
When you answer the following questions, please think about how you
prepare for and think about the following situations.
I am regularly assessing my campus
environment because I am concerned about my personal safety.
In the blank space beside each statement, please indicate
how true the above statement is of you, in your campus environment by writing your numeric
response.
1———–2———-3———4———-5———-6———7
not at all Very true of me
true of me
1. I go into campus situations expecting the worst, even though I know I will
probably do OK. _______
2. I generally go into campus situations with positive expectations about how
I will do. _______
3. I’ve generally done pretty well in these campus situations in the past._______
4. I carefully consider all possible outcomes before these campus situations._______
5. When I do well in these campus situations, I often feel really happy. _______
6. I often worry, in these campus situations, that I won’t be able to carry through
my intentions. _______
7. I often think about how I will feel if I do very poorly in these campus situations._______
8. I often think about how I will feel if I do very well in these campus situations._______
9. When I do well in these campus situations, it is usually because I didn’t get too
worried about it beforehand._______
10. I often try to figure out how likely it is that I will do very poorly in these
campus situations._______
11. I’m careful not to become overconfident in these campus situations._______
12. I spend a lot of time planning when one of these campus situations is coming
up._______
13. When working with others in these campus situations, I often worry that they will
control things or interfere with my plans._______
14. I often try to figure out how likely it is that I will do very well in these
campus situations. _______
15. In these campus situations, sometimes I worry more about looking like a fool
than doing really well. _______
16. Prior to these campus situations, I avoid thinking about possible bad outcomes._______
17. Considering what can go wrong in campus situations helps me to prepare. _______
121
Appendix D
Fear Questionnaire (FQ)
Choose a number from the scale below to show how much you would avoid each of the
situations listed below because of fear or other unpleasant feelings. Then write the number you chose
on the line beside each situation.
0————1———-2———–3———-4——–5———6———–7———-8
Would not Slightly Definitely Markedly Always
Avoid it avoid it avoid it avoid it avoid it
1. Main phobia you want treated (describe in your own words)…..___N/A_____
2. Injections or minor surgery………………………………………________
3. Eating or drinking with other people…………………………………..__________
4. Hospitals…………………………………………………………________
5. Traveling alone by bus or coach…………………………………________
6. Walking alone in busy streets…………………………………….________
7. Being watched or stared at………………………………………..________
8. Going into crowded shops………………………………………….._________
9. Talking to people in authority………………………………………._________
10. Sight of blood……………………………………………………….._________
11. Being criticized……………………………………………………….________
12. Going alone far from home……………………………………………________
13. Thought of injury or illness……………………………………………________
14. Speaking or acting to an audience……………………………………________
15. Large open spaces……………………………………………………._______
16. Going to the dentist……………………………………………………._______
17. Being in an environment where people are armed with concealed guns………________
122
Now choose a number from the scale below to show how much you are troubled by each problem
listed and write the number on the line opposite.
0——–1———-2———–3———-4——–5———6———–7———-8
Hardly Slightly Definitely Markedly Very severely
at all troublesome troublesome troublesome troublesome
18. Feeling miserable or depressed………………………………………….._______
19. Feeling irritable or angry…………………………………………………_______
20. Feeling tense of Panicky…………………………………………………._______
21. Upsetting thoughts coming into your mind………………………………_______
22. Feeling you or your surrounding area are strange or unreal………………_______
23. Feeling you are unprotected in a social setting……………………………_______
Now, based upon the following scale,
24. How would you rate the present state of your phobic symptoms on the scale below?
0————1———-2———–3———-4——–5———6———–7———-8
no phobias Slightly Definitely Markedly Very severely
present disturbing/ disturbing/ disturbing/ disturbing
not really disabling disabling disabling
disabling
Circle one number between 0 and 8.
123
Appendix E
Responsibility Attitude Scale (RAS)
This questionnaire lists different attitudes or beliefs which people sometimes hold. Read each
statement carefully and decide how much you agree or disagree with it.
For each of the attitudes, show your answer by putting a circle around the words which best describe
how you think. Be sure to choose only one answer for each attitude. Because people are different,
there is no right answer or wrong answer to these statements. To decide whether a given attitude is
typical of your way of looking at things, simply keep in mind what you are like most of the time.
1. I often feel responsible for things which go wrong.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
2. If I don’t act when I can foresee danger, then I am to blame for any consequences if it
happens.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
3. I am too sensitive to feeling responsible for things going wrong.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
4. If I think bad things, this is as bad as doing bad things.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
5. I worry a great deal about the effects of things which I do or don’t do.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
6. To me, not acting to prevent disaster is as bad as making disaster happen.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
124
7. It I know that harm is possible, I should always try to prevent it, however unlikely it
seems.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
8. I must always think through the consequences of even the smallest actions.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
9. I often take responsibility for things which other people don’t think are my fault.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
10. Everything I do can cause serious problems.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
11. I am often close to causing harm.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
12. I must protect others from harm.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
13. I should never cause even the slightest harm to others.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
125
14. I will be condemned for my actions.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
15. If I can have even a slight influence on things going wrong, then I must act to prevent it.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
16. To me, not acting where disaster is a slight possibility is as bad as making that disaster happen.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
17. For me, even slight carelessness is inexcusable when it might affect other people.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
18. In all kinds of daily situations, my inactivity can cause as much harm as deliberate bad intentions.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
19. Even if harm is a very unlikely possibility, I should always try to prevent it at any cost.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
20. Once I think it is possible that I have caused harm, I can’t forgive myself.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
126
21. Many of my past actions have been intended to prevent harm to others.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
22. I have to make sure other people are protected from all of the consequences of things I do.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
23. Other people should not rely on my judgement.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
24. If I cannot be certain I am blameless, I feel that I am to blame.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
25. If I take sufficient care then I can prevent any harmful accidents.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
26. I often think that bad things will happen if I am not careful enough.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
 

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Senior Seminar—Capstone ECNU692

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Senior Seminar—Capstone
ECNU692
Group Project
 

  1. From the Syllabus…

 
The group presentation project requires each group to identify a Nobel Laureate economist and work together to identify key contributions to the body of economic knowledge:  this requires the review and analysis of the economist’s major works (beginning with their acceptance speech:  http://nobelprize.org/nobel_prizes/economics/laureates/
 
Each group member should prepare a 5-7 page summary write-up of their findings and each group should present their collective findings in a PowerPoint presentation on the groups’ assigned presentation session.   The goal of the exercise is to identify (and understand) the theoretical and empirical contributions (“the ivory tower”) so to APPLY them to a subject area of importance (for example, the game theory of Schelling to nuclear disarmament).

  1. List of relevant Nobel Laureates…

 
2007
Maskin
“for having laid the foundations of mechanism design theory”
 
2005
Schelling
“for having enhanced our understanding of conflict and cooperation through game-theory analysis”
 
2001
Akerloff and Stiglitz
“for their analyses of markets with asymmetric information”
 
1998
Sen
“for his contributions to welfare economics”
 
1997
Merton and Scholes
“for a new method to determine the value of derivatives”
 
1996
Vickrey
“for their fundamental contributions to the economic theory of incentives under asymmetric information”
 
1994
Nash
“for their pioneering analysis of equilibria in the theory of non-cooperative games”
 
1992
Becker
“for having extended the domain of microeconomic analysis to a wide range of human behaviour and interaction, including nonmarket behaviour”
 
1991
Coase
“for his discovery and clarification of the significance of transaction costs and property rights for the institutional structure and functioning of the economy”
 
1990
Markowitz, Miller, Sharpe
“for their pioneering work in the theory of financial economics”
 
1988
Allais
“for his pioneering contributions to the theory of markets and efficient utilization of resources”
 
1987
Solow
“for his contributions to the theory of economic growth”
 
1985
Modigliani
“for his pioneering analyses of saving and of financial markets”
 
1982
Stigler
“for his seminal studies of industrial structures, functioning of markets and causes and effects of public regulation”
 
1975
Koopmans
“for their contributions to the theory of optimum allocation of resources”
i
DEFENSIVE PESSIMISM AND CONCEALED CARRY OF WEAPONS ON
CAMPUS: CAUSE FOR CALM OR CONCERN
A dissertation submitted
by
R. BRIAN WRIGHT
April, 2014
to
School of Organizational Leadership
UNIVERSITY OF THE ROCKIES
Upon the recommendation of the Faculty and the approval of the Board of Trustees, this
dissertation is hereby accepted in partial fulfillment of the requirements for the degree of
DOCTOR OF PSYCHOLOGY
Approved by:
________________________
Dr. Eszter Barra-Johnson, PhD
Committee Chair
Committee Members:
Dr. James Castleberry, JD, PhD
Dr. Ronald Curtis, EdD.
All rights reserved
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The quality of this reproduction is dependent upon the quality of the copy submitted.
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UMI Number: 3620030
ii
Copyright © by
R. Brian Wright
2014
iii
Defensive Pessimism and Concealed Carry of Weapons on Campus:
Cause for Calm or Concern
by
R. Brian Wright
Abstract
Acknowledging that lower level needs must be met before higher level needs can be
pursued, based upon Maslow’s theory of the Hierarchy of Needs (Maslow, 1943); the issues
of personal safety in educational settings are addressed. In a relatively stable society marked
by occasional acts of violence on college campuses, how can an individual meet his or her
basic psychological needs for safety and yet still pursue the higher-level goal of obtaining an
education in a face-to-face setting? Could the support of Concealed Carry Weapons (CCW)
be a solution? The current research proposes that Defensive pessimism, a cognitive coping
strategy, provides the bridge that completes Maslow’s hierarchy of needs for some
individuals. It was hypothesized that defensive pessimism, fear, and responsibility are
correlated with the decision whether to support or deny CCW on campus. The Defensive
Pessimism Questionnaire (Norem, 2002), the Fear Questionnaire (Antony, Orsillo, &
Roemer, 2001), the Responsibility Attitude Scale (Antony et al., 2001), and a simple “yes or
no” question concerning support of CCW on campus were utilized to test the proposed
hypothesis. One hundred sixty-nine participants were included in the sample taken from a
small Liberal Arts college in Virginia. A quantitative research methodology was applied.
The data did not show a significant correlation between support for CCW on campus and
defensive pessimism or responsibility. However, a relationship between fear and support for
CCW was indicated. Additionally, a weak relationship between support for CCW and
iv
defensive pessimism appeared to be possible. The relationship between the support of CCW
and Fear and Defensive Pessimism did indicate potential for future research.
Key Words: Defensive Pessimism, Fear, Responsibility, Concealed Carry Weapons
v
TABLE OF CONTENTS
I. INTRODUCTION…………………………………………………………………………………………1
General Statement and Background of Study………………………………………………….4
Additional Background………………………………………………………………………………11
Statement of Problem…………………………………………………………………………………13
Importance of the Study……………………………………………………………………………..13
Purpose of the Study ………………………………………………………………………………….14
Research Overview ……………………………………………………………………………………16
Overview of Research Design …………………………………………………………………….16
Assumptions and Limitations ……………………………………………………………………..19
Summary………………………………………………………………………………………………….20
II. REVIEW OF LITERATURE……………………………………………………………………….22
Search Strategy …………………………………………………………………………………………23
Review of Literature and Research………………………………………………………………23
Virginia Takes the National Stage ……………………………………………………………….26
The Law School Difference ……………………………………………………………………33
A New National Psyche …………………………………………………………………………33
The Debate Begins………………………………………………………………………………..34
Debate Continues………………………………………………………………………………….36
Defensive Pessimism: The Positive Power of Negative Thinking?…………………..41
A Closer Look at Defensive Pessimism……………………………………………………48
A Divergent View of Defensive Pessimism ………………………………………………….60
The Role of Fear ……………………………………………………………………………………….62
vi
Responsibility as a Factor…………………………………………………………………………..64
Summary………………………………………………………………………………………………….68
III. METHODS ………………………………………………………………………………………………69
Methodology…………………………………………………………………………………………….70
Procedure …………………………………………………………………………………………………71
Population and Sample ………………………………………………………………………………77
Ethical Concerns……………………………………………………………………………………….78
Pilot Study………………………………………………………………………………………………..78
Data Collection …………………………………………………………………………………………79
Data Analysis……………………………………………………………………………………………80
Summary………………………………………………………………………………………………….83
IV. RESEARCH FINDINGS……………………………………………………………………………85
Pilot Study Results…………………………………………………………………………………….87
Data Analysis……………………………………………………………………………………………88
Analysis Conclusions…………………………………………………………………………………91
Assessment of Defensive Pessimism Scale 1-3……………………………………….92
Assessment of FQ 17 …………………………………………………………………………..92
Assessment of FQ 16 …………………………………………………………………………..93
Assessment of RAS……………………………………………………………………………..93
Assessment of Demographics……………………………………………………………….93
Summary………………………………………………………………………………………………….94
V. REVIEW………………………………………………………………………………………………….96
Findings……………………………………………………………………………………………………99
vii
Interpretation and Findings……………………………………………………………………….100
Defensive Pessimism Scale…………………………………………………………………101
FQ17 ……………………………………………………………………………………………….101
FQ16 ……………………………………………………………………………………………….102
RAS…………………………………………………………………………………………………102
Demographics…………………………………………………………………………………..102
Limitations of the Study……………………………………………………………………………103
Implications…………………………………………………………………………………………….105
Future Research ………………………………………………………………………………………106
Discussion………………………………………………………………………………………………107
REFERENCES …………………………………………………………………………………………….109
viii
LIST OF TABLES
Table 1: Criterion and Predictor Variables Defined ……………………………………………17
Table 2: Divergent and Convergent Correlates of the Defensive Pessimism
Questionnaire (DPQ)………………………………………………………………………..55
Table 3: Criterion and Predictor Variables………………………………………………………..72
Table 4: Demographic Variables……………………………………………………………………..74
Table 5: Utilizing Linear Regression an Association can only be Established
in Relation to the FQ17 Category Significant at the Extremes of the
Response Scale ……………………………………………………………………………….95
ix
LIST OF APPENDICES
Appendix A: Consent Form……………………………………………………………………………117
Appendix B: General Statement/Demographics……………………………………………….119
Appendix C: Defensive Pessimism Questionnaire ……………………………………………120
Appendix D: Fear Questionnaire ……………………………………………………………………121
Appendix E: Responsibility Attitude Scale ……………………………………………………..123
1
CHAPTER I: INTRODUCTION
Maslow proposed his Hierarchy of Needs theory in 1943. He proposed that human
beings have various basic and intrinsic psychological requirements. These requirements are
categorized by their importance for human survival and satisfaction. Frequently depicted as
a pyramid, the need for safety is found at the base of this hierarchy (Maslow, 1943). As
humankind advances and stabilizes, safety continues to be an important factor in the pursuit
of higher level needs. It is only when basic needs are met, including safety, that higher levels
can be attained. Personal safety has become a concern for many in the United States. Part of
this has been attributed to an increase in gun violence (Lucas & Molden, 2011). In fact,
information recently released by the Pew Research Center (PRC, 2013), indicated there has
been a distinct change since 1999 in the reasoning offered for gun ownership in the United
States (PRC, 2013). The PRC made this determination by comparing two studies. A
February 2013 study of 1,504 adults (a change of 2.9% from the 1999 number of
participants) utilized the same instrument of measure employed in a 1999 study (PRC, 2013).
In 1999, 49% of respondents indicated that they owned a gun specifically for hunting
purposes (PRC, 2013). Only 26% of respondents in the same study indicated they
maintained a firearm for protection purposes. In the February 2013 study, the PRC found a
reversal of these trends. The percentage of those who reported owning firearms for
protection increased by 22% to an overall 48%. The number of respondents who reported
owning firearms for hunting saw a decrease of 17% to an overall 32%. Likewise, the PRC
found a slight decrease in the number of respondents who claimed to have owned weapons
for target or sport shooting, Second Amendment issues, and collecting. Protection
(i.e., safety) of self or loved ones became the number one reason to own a firearm.
2
Interestingly, of those who reported they did not own fire arms, the PRC found that 58%
cited concerns about safety as a determining factor in keeping guns out of their homes. This
is compared to 26% in 1999. Safety was obviously a concern from both points of view.
Additionally, according to the PRC, 58% were very concerned that the federal government’s
current move toward more restrictive gun laws would make it more difficult for individuals
to access fire arms and ammunition to protect themselves. The counter view, in households
that did not own fire arms, the PRC (2013) reported that 66% believed stricter gun laws
would prevent events, such as mass shootings. Gun owners did not concur. According to the
PRC, only 35% of gun owners believed stricter laws would prevent deaths caused by mass
shootings.
As the PRC (2013) pointed out, 37% of U.S. households owned firearms.
Approximately 79% of those reported that gun ownership makes them feel safer.
Additionally, 78% reported a sense of enjoyment from gun ownership. From the same group
of respondents, only 16% reported being uncomfortable having a gun in the household while,
for those households with no gun ownership, 40% reported they would be comfortable with a
gun in their household (PRC, 2013). When broken down across gender lines, 49% of males
in households with no gun ownership indicated they would be comfortable with a gun in the
household. In comparison, only 33% of women in households with no gun ownership
reported they would be comfortable with a gun in the household.
The PRC (2013) data indicated that even among households not owning any guns,
guns could be associated with a sense of safety. Similarly, when addressing CCW on college
campuses, Bouffard, Nobles, and Wells (2012) indicated that one possible reason for high
support for CCW among criminal justice majors could lie in the fact that they already see
3
themselves as responsible for the safety of those around them. Guns are a means to this
safety. By looking at college student support of CCW by academic major, the PRC offered
data to underscore the common denominator of safety as a potential interpretation of CCW as
a means of positive support. As indicated above, the major reason gun owners provide for
owning a weapon was concern for safety. Safety was the main reason non-gun-owners
provided for not owning fire arms according to the PRC. Thirty-nine percent of those
surveyed indicated the reason they would be uncomfortable was the risk of an accident,
including 29% who specifically mentioned concerns about children. Another 22% expressed
more general concerns about the dangers of gun ownership (PRC, 2013). According to
Bouffard et al., the same could be said of some students who seek CCW and see themselves
as responsible for the safety of those around them. Regardless of the reason, guns are viewed
through very subjective lenses and are generally, based upon PRC’s research, placed into two
categories. They are either a positive or a negative component in an individual’s overall
sense of safety.
Such concern does not necessarily represent a regression on Maslow’s Pyramid of
Needs, but it does represent a blurring of the lines between certain stages. For the purposes
of this study, the lines between the base level of safety and higher levels of cognition appear
to be in a state of fluctuation. This was particularly true on university and college campuses
in the United States based upon acts of mass violence, such as the shootings at Virginia Tech
(Virginia Polytechnic Institute and State University) and Northern Illinois University. This
study focused on the subject of safety within such an environment.
Just a decade ago, such a study may have seemed alarmist in nature, but as the PRC
(2013) indicated, attitudes on this subject have changed. Historically, United States’ higher
4
education was seen as a bastion of isolation. Overt acts of deadly violence were nearly
unheard. As an example, Roark (1987) provided a snapshot into life on U.S. campuses of
higher education in the latter half of the 20th Century. According to the author, criminal acts
of concern did occur during this time period. However, as addressed by the author, these
involved what could be viewed as mild, based upon current definitions. In fact, Roark used
the term violence to refer to the most frequent acts seen in the latter half of the 20th century.
“Most commonly, rape, assault, harassment, and hazing” were issues of great concern at the
time of the author’s research, though she does mention the fact that “murder [was] not
unknown” (Roark, 1987, p. 367). However, the act of murder was apparently viewed as
quite uncommon. As of this writing, that same form of violence, murder, was of greater
concern as it had become much more familiar in the years following Roark’s writing.
Violence seemed to permeate life, particularly in the United States in the 21st century, a
century in its brief existence that was marked by turbulence and terrorism both foreign and
domestic. This raised new questions as to how one was to remain safe while still pursuing
higher-level goals. Living on a college campus and getting an education was an example of
trying to achieve a higher goal.
General Statement and Background of Study
According to Roark (1987), college campuses are viewed as microcosms reflecting
society as a whole. In other words, if society becomes more violent, one can expect the same
of the nation’s college and university campus populations. Germana (2007) emphasized this
point. The author, though writing about self-actualization, indicated that Maslow believed in
“a sine qua non of creativeness” (p. 67) that is translated as “a fusion of person and world”
(p. 67). Best, Day, McCarthy, Darlington, and Pinchbeck (2008) emphasized that Maslow,
5
even though he was the creator of the needs hierarchy, was often more interested in the
higher end needs of human experience and how they related to his apex of self-actualization.
However, if one were to accept the emphasis that the environment does impact the
individual, then the same approach can be applied to Maslow’s base needs in addition to his
pyramid’s peak. In fact, Maslow (as cited by Best et al., 2007) wrote of the higher needs:
If all other needs are unsatisfied, and the organism is then dominated by the
physiological needs, all other needs may become simply non-existent or be pushed
into the background. It is then fair to characterize the whole organism by saying
simply that it is hungry, for consciousness is almost completely preempted by hunger.
(p. 306)
In other words, according to Brown and Cullen (2006), until lower or base needs are met,
higher needs cannot be realized. The same can be argued for belongingness/love, esteem,
and, in particular, cognition as they relate to level two of Maslow’s hierarchy of needs, safety
(Brown & Cullen, 2006).
According to Rollings (2010), who cited Soden, 2006; Colaner, 2006; Graveline,
2003; and Fisher and Smith, 2009, college and university campuses have been seen as “Ivory
Towers” (p. 1) where students are “insulated from the community and protected from hurt,
harm, and/or dangers” (p. 1). This no longer necessarily holds true. Similarly, much
research has gone into why certain individuals become violent in various situations and
settings. From a sociological point of view, as Staub (2003) indicated in a study of mass acts
of violence, society offers insight. As the author pointed out, all societies can be divided into
“us” and “them” (p. 791) components. These monikers imply that there is an imbalance–real
or perceived–between two groups. The “them” group feels “devalued” (p. 792) in one way
or another. As Staub discussed, this equation can be used to define intra-societal violence.
When applied to a college or university campus setting, this argument remains true.
6
Perpetrators of violence often claim retaliation for some perceived discrepancy. It could be
argued that in a college and university setting, such a feeling could be attributed to feelings
discussed by Staub. These can include individual situations such as bullying to an outright
sense of being socially oppressed. This said, all of the injustices of the overall society could
also be found intensified within the nation’s college and university campus societies. In fact,
such an assumption seems perfectly logical. However, as Roark (1987) discussed, there is an
opposing point of view.
As previously indicated, Roark (1987) wrote that violence on campus was a growing
area of concern. She also noted that “it seems to many student affairs professionals that there
is an increase in violence on campus” (Roark, 1987, p. 367). However, despite the clear
pronouncement, the author indicated that such a straightforward interpretation was debated.
In other words, this was an assessment that was tempered with theory and not necessarily
with reason. According to the author, some student affairs professionals saw the data, which
reflected an increase in violence, as simply the result of greater awareness as well as
enhanced documentation procedures when incidents of violence occurred. This is an
important statement of differentiation between campus violence in the 1980s and campus
violence that garners national and international attention in the early 21st Century. Such an
interpretation did not necessarily hold true then, and it does not currently hold true. Citing
Hanson, Turbett, and Whelehan (1986), Roark (1987) wrote, “Interpersonal violence is
underreported, underprosecuted, and underpunished, thus allowing it to occur in secrecy,
ignorance, and shame” (p. 367). In other words, crime on campuses was often “hidden” and
even “denied” (Roark,
p. 367). While this tendency to embellish campus safety may still be exhibited by college
7
administration in some cases, and, to a certain extent, concerns of overt violence in society
and on college campuses has been steadily increasing (Nyland, Forbes-Mewett, &
Marginson, 2010).
The question thus arises–how can an individual with elevated safety concerns
function and move upward on the hierarchy of needs within such a setting? How does an
individual continue to climb Maslow’s pyramid without becoming obsessed with safety
concerns in such a situation? Noltemeyer, Bush, Patton, and Bergen (2012) discussed this
point in a study involving 390 secondary school students in a Mid-western state. They used
Maslow’s own words to begin their argument:
It is quite true that man lives by bread alone–when there is no bread. But what
happens to man’s desires when there is plenty of bread and his belly is chronically
filled? At once other (and “higher”) needs emerge and these, rather than
physiological hungers, dominate the organism. And when these in turn are satisfied,
again new (and still “higher”) needs emerge and so on. This is what we mean by
saying the basic human needs are organized into a hierarchy of relative prepotency.
(pp. 1864-1865)
Noltemeyer et al. (2012) indicated that Maslow theorized, at any given time, any need
can take priority. In addition, “It is possible for an individual to be motivated by multiple
needs simultaneously” (p. 1863). In their own study, the authors addressed such a scenario
as it related to secondary school students. They indicated, based upon Maslow’s work, if socalled
“deficiency needs” (lower level needs) have been met, one cannot preclude them from
becoming an issue again. When this happens, the individual in question might not be able to
perform at peak capacity in relation to the hierarchy of needs and the journey toward higherlevel
goals.
Using the same secondary school students study as a model, Noltemeyer et al. (2012)
stated such an argument was valid. They argued that all students in the nation’s school
8
system are expected to maintain a certain academic level despite what may be occurring with
their base or deficiency needs. The authors indicated that such a theory was quite useful in
explaining why some children failed to perform as expected. However, they also indicated
that research into this theory was weak. Noltemeyer et al. indicated that the idea of
underperformance of students with basic needs issues was widely accepted despite the lack
of data to support the theory. In reviewing 14 studies, Noltemeyer et al. reported that Wahba
and Bridwell (1976) found only partial or incompatible data to validate the theory of poor
performance related to needs issues. However, more recent research (as cited in Noltemeyer
et al., 2012) has shed new light.
Noltemeyer et al. (2012) reported that such studies have found limited evidence
supporting performance linked to Maslow’s hierarchy of needs. The authors indicated that
the theory concerning performance and hierarchy needs is often impacted by socioeconomic
status. In particular, this held true of secondary school students in the lower socioeconomic
realm when compared to middle socioeconomic bracket students. “However, the researchers
did not find that cluster analysis showed the concepts were unitary” (p. 1863). In a survey
study, Acton and Malathum (2000; as cited by Noltemeyer et al., 2012) cited a report that a
relationship between Maslow’s needs hierarchy and health concerns was present. In
discussing individuals who were high in physical, love and belonging, and self-actualization
needs, Acton and Malathum (as cited in Noltemeyer et al., 2012) found that such individuals
made positive life choices regarding their physical health and wellbeing. In a study
involving 166 undergraduate college students, the authors found that basic level needs do
have an impact on student well-being. In the case of Lester et al. (1983; as cited by
9
Noltemeyer et al., 2012), basic needs satisfaction was related to their specific realm of study
and level of psychological health.
Studies related to Maslow’s upper level hierarchy needs and children’s academic
success were even more limited in number. According to Noltemeyer et al. (2012), they
were only able to find one study related to the subject. This was a study by Smith, Gregory,
and Pugh (1987; as cited by Noltemeyer et al., 2012). This particular study investigated
students’ needs in relation to four of Maslow’s hierarchical levels: security, love/belonging,
esteem, and self-actualization. The fact that security was one of the needs addressed in
academic success gives credence to the proposed study of CCW and the need for safety in a
higher education setting. Noltemeyer et al. also pointed out that there was already a wellestablished
link between academic success and very basic needs, such as food and housing,
in young students.
For example, Smith, Brooks-Gunn, and Klebanov (1997; as cited in Notlemeyer et
al., 2012) wrote that familial poverty had a direct impact on “child cognitive abilities and
academic achievement” (p. 1863). This stood true even when controlling for family
structure. Additionally, schools with fewer resources also had a similar impact. Notlemeyer
et al. highlighted studies by Bean, Bush, McKenry, and Wilson (2003) as well as Anderson,
Lindner, and Bejinion (1992) involving adolescents, positive familial support, and academic
success. Both variables, cognitive abilities and academic achievement, were positively
related to academic success. Interestingly, one of the components addressed by Anderson et
al. (1992) was the absence of conflict. Of course, this was viewed in terms of intrafamilial
conflict and belongingness as related to academic success. This could also be viewed as a
safety issue with bearing on the proposed research.
10
Notlemeyer et al. (2012) also directly addressed the role of safety on the academic
success in their study of secondary school children. The authors addressed the issue of safety
from a health perspective while recognizing that little research exists into this particular
arena. Kitzman et al. (2010) is an exception according to the authors. As cited in
Notlemeyer et al., Kitman et al. researched home nurse visits and the academic success of the
children visited.
They found the children of parents who had been visited by nurses, compared to a
control group who did not receive such visits, scored higher on individuallyadministered
reading and math achievement tests and scored higher on groupadministered
reading and math standardized tests during their first six years of school.
(p. 1863)
Despite such results, Notlemeyer et al. (2012) indicated that a significant percentage
of school-aged children have a deficiency as related to Maslow’s needs hierarchy. In
particular, the authors noted that what is not understood is how physiological needs, safety
needs, and love/belonging needs actually relate to each other and how they relate to an
individual’s academic success. They also indicated that it is unclear whether Maslow’s
hierarchy of needs can be used as an empirically supported theory for supporting such a
hypothesis. Research has not yet examined the dependency between certain deficiency needs
(e.g., physiological, safety, and love/belonging needs) and definite growth needs (e.g.,
academic and cognitive outcomes). The authors indicated that such research could help
further clarify Maslow’s theory while shedding new light on areas of need so students’
academic careers can be enhanced.
Notlemeyer et al. (2012) found similar results in their own research. They indicated
that their study offered “some support for Maslow’s assertion that growth needs such as
academic progress may be positively related to improvements in deficiency needs such as
11
safety and love/belonging” (p. 1866). This is the basic theory suggested by the presented
research. Perception of personal safety is a real safety need. In an environment in which
violence has increased, how do individuals with specific safety needs deal with growth needs
in an academic setting? Could individuals in question employ Defensive Pessimism, a
particular cognitive coping strategy, in the pursuit of such a higher need?
Additional Background
The 2012 Trayvon Martin case (and 2013 verdict) in Florida highlighted a change in
thinking in the United States that brought personal safety to the forefront (Bellin, 2012). The
case involved the death of a 17-year-old African American adolescent at the hands of an
armed community watch volunteer who claimed he feared extreme bodily harm at the hands
of the adolescent as the result of an altercation between the two. In response to the case,
angry protests occurred around the nation as the community-watch volunteer ultimately used
deadly force against the unarmed Martin. At the center of the issue was a Florida law known
as stand your ground (Fla. Stat. §§ 776.012, .013, .032, 2005). As Bellin pointed out, the
stand your ground laws allow an individual to use deadly force against another person if the
individual perceives a deadly threat. This principle stands true even if the perception of
threat is later determined to be erroneous (Bellin, 2012).
This legal stance represented a major shift in Florida law as well as nearly half of the
50 United States (Bellin, 2012). Prior to 2005, Florida residents had a duty to retreat when
met with a threatening situation. In other words, the administration of deadly force was an
option to be used only as a last resort. As Bellin indicated, there has been a long-standing
exception to this standard in the nation. This exception has been known as the Castle
Doctrine. This doctrine allowed individuals who faced violence on their own property to
12
react with violence, without the duty to retreat. In other words, they were allowed to stand
their ground. Understanding this legal evolution from the Castle Doctrine to stand your
ground is necessary in appreciating how such a dichotomy in the law could have developed.
In the first 10 years of the 21st Century, a decade marked by terrorist activity and
national violence, the legal necessity of the duty to retreat was reconsidered. As a result,
perceiving a threat of violence, or a potentially deadly altercation, became enough to justify
armed intervention in many states. Thus, when such violence occurred, it then became the
burden of the prosecution to prove the assailant did not perceive such a threat (Bellin, 2012).
Such endeavors became “a heavy burden” (Bellin, 2012, para. 12) as the prosecution was
then expected to “prove” the defendant’s state of mind. This was born out in the jury’s
decision in the George Zimmerman trial. Zimmerman was the armed community watch
volunteer who fatally shot Trayvon Martin. Zimmer was found not guilty by a Florida jury
because of the stand your ground law (Jonsson, 2013).
The purpose of the study was not to debate the Trayvon Martin case, nor was it to
discuss the duty to retreat. Rather, it is presented as an example of the extremes in a
changing national environment concerning firearms and their proper place. It serves to
highlight the concept that firearms, safety, and the theory behind Maslow’s needs hierarchy
could be applicable to college campus violence. The specific purpose of the work was to
attempt to determine why individuals, within certain perimeters, would support a policy
condoning CCW on a college campus, a practice that increased in the overall society by a
factor of six since the 1980s (Stuckey, 2010). According to Cola (2007), from 2007 to 2008,
Ohio’s concealed carry weapons increased by 53%. Oklahoma saw its number of CCW
13
permits increase by a factor of two from 2007 to 2008. In Utah, the number increased from
2,548 in February 2008 to 10,878 by 2009.
Statement of Problem
As Taylor (2008) pointed out, over 20 years of effort have been dedicated to
protecting students in an academic setting. Despite these efforts, violence remains. Despite
these efforts, violence has increased. Citing the California Department of Education (2003),
Taylor indicated that safety, insulation from violence, has supplanted the primary goal of
education as students and faculty can be distracted if they feel unsafe. Baker and Boland
(2011) reaffirmed this ideology. The authors acknowledged that students neglect their
studies out of fear for personal safety. The same issue has plagued faculty and staff as well.
Such changes have been documented by other means. As addressed above, the PRC
(2013) saw marked changes in the number of gun owners claiming ownership for personal
safety. In the past, this was not the case. The PRC (2013) found other reasons outranking
safety when legitimizing weapons ownership. Looking at safety from a Maslovian
perspective, as a basic need that must be satisfied in order to attain higher pursuits, the issue
of gun violence becomes a viable area of study. One area in particular is within higher
education.
Importance of the Study
Little information exists regarding a possible correlation between guns and cognitive
coping strategies. Currently, a psychological scale to measure anxiety, fear, or any other
construct related to guns does not exist. This study provides insight into the psychological
(cognitive and emotive) aspects of support for firearms. In addition, the study adds to the
body of research concerning the role of fear in attitudes.
14
The study may also serve as a guide for colleges and universities in the modern era.
With college tuition at traditional schools climbing higher and higher, students will seek out
the situation that is best for them. Additionally, if safety is an issue for students on
traditional campuses, safety could become as important a selling point as prestige when
recruiting students. Enhanced campus environments (knowing they are not defenseless
against armed intruders) will benefit students as they explore educational venues. This is
especially true as online education becomes more widely accepted as an alternative to
traditional brick and mortar schools. Put simply, if students do not feel safe in brick-andmortar
schools, this may impact their ability to excel.
Purpose of the Study
This study was designed to quantitatively determine if support for concealed carry
weapons (CCW) on campus could be determined by individual levels of a cognitive coping
strategy known as defensive pessimism, individual fear, and responsibility in subjects. A
quantitative design allowed for the testing of cause and effect using specific measurement
tools and correlational statistical outcomes in this narrowly focused study. Assessing 169
students on a rural Virginia private Liberal Arts college campus accomplished this goal. If
causation, or even a correlation, between coping strategy, fear, responsibility, and CCW
support on campus was established, researchers may gain a better understanding of the role
firearms play in the United States, as well as a broader understanding of how needs are
placated and pursued within Maslow’s hierarchy.
It was unclear whether a specific cognitive coping strategy, level of fear, and assumed
responsibility were correlated with support for the presence of firearms. The study was
designed to determine whether a correlation between support for CCW on campus, defensive
15
pessimism (as a cognitive coping strategy), and the variables of fear and responsibility
existed. The predictor variables addressed included responsibility attitudes as reflected by
the Responsibility Attitude Scale (RAS). Fear was measured using the Marks and Mathews
Fear Questionnaire. Defensive Pessimism, as addressed in Norem’s (2001) revised
Defensive Pessimism Questionnaire, was used to determine whether an individual was a true
defensive pessimist, a strategic optimist, or whether both strategies were utilized. The
anchoring, or criterion variable, was the study participants’ support or rejection of CCW on
campus. This was determined from participants’ responses to a simple yes or no statement.
The need for this type of research may be debatable. Some may argue that it is
unimportant because many in the United States embrace guns, and these firearms are simply
a part of life in the United States. An assertion could also be made that the law of the land
protects gun owners; therefore, the number of, and support for, firearms will not be
decreasing in the foreseeable future. However, debating support for firearms was not the
purpose of this study. This study was designed to determine whether coping strategy
(defensive pessimism), level of fear, and level of responsibility create an internal need for
safety that included support for CCW.
Wendell Phillips, a 19th
-century attorney, once said, “Law is nothing unless close
behind it stands a warm living public opinion” (Singh, 2013, para. 19). This sentiment
seemed to stand true for guns in United States’ society. It also seems to explain why the
argument for CCW on campuses remained alive, and even supported, by such legal
components as stand your ground, even though widespread implementation of this policy has
the potential to make the nation a more dangerous place by allowing individuals to, arguably,
16
take the law into their own hands. This researcher proposes that investigation into this realm
could open up a new area of research.
Research Overview
The support of CCW on campus was the keystone of this quantitative correlational
study. Specifically, to what degree does an individual’s level of defensive pessimism, fear,
and responsibility have on such a decision? Levels of defensive pessimism, fear, and
responsibility were weighed against the acceptance or denial of CCW on campus. These
were assessed in terms of the proposed hypothesis (H1) that defensive pessimism, fear, and
responsibility would prove to be significant predictors of the probability that a participant
would support CCW on campus. This stood in direct contrast to the null hypothesis (H0) in
which defensive pessimism, fear, and responsibility would not prove to be significant
predictors of the probability that a participant would support CCW on campus. To achieve
this end, the quantitative research methodology was applied. This was underpinned by a
correlational design. As stated above, the research question that guided this study was: What
are the relationships between the participants’ support for concealed carry weapons (CCW)
on campus and their levels of defensive pessimism, fear, and responsibility?
Overview of Research Design
The research question that guided this study was, “What are the relationships between
the participants’ support for CCW on campus, and individual levels of defensive pessimism,
fear, and responsibility?” The participants were recruited from a small Liberal Arts college
within an hour’s drive of the scene of the nation’s deadliest campus shooting, Virginia
Polytechnic Institute and State University (Virginia Tech).
17
Table 1
Criterion and Predictor Variables Defined
Variable Conceptual definition Functional definition Operational definition
Support for
CCWs on
Campus
Whether or not a participant
supports or opposes CCWs on
campus
One criterion
(response)
variable, classified
into two nominal
categories
Yes = 1 or No = 0, measured with a simple
poll
Defensive
Pessimism
A coping strategy employed
by a participant to prepare for
any event perceived as
stressful, by which negative
thinking transforms anxiety
into action (Norem, 2002)
One predictor
variable, measured at
the scale level
Measured with 17 items in the Revised
Defensive Pessimism Questionnaire
(Appendix 3). Each item is measured on a 7-
point scale (1, not at all true of me; to 7, very
true of me). Higher scores indicate higher
levels of defensive pessimism. Scores will be
divided into three categories: 22 – 41 will be
considered Strategic Optimists; 42 – 61 will
be viewed as bi-strategists; scores ranging
from 62 – 79 will be considered Defensive
Pessimists. The numeral 1 will represent
Strategic Optimists, 2 will represent bistrategists,
and 3 will represent Defensive
Pessimists.
Fear The extent to which a
participant has feelings of
agoraphobia, social phobia and
blood/injury phobia (Antony et
al. 2001) An additional single
item is added concerning
CCWs in one’s environment.
One predictor
variable, measured at
the scale level
Measured with 17 items in the Fear
Questionnaire (Appendix 4). Each item is
measured on a 7-point scale (1,would not
avoid it; to 8, markedly avoid it). Fear is
operationalized as the sum of the scores for
the three sub-scales (Agoraphobia + Social
Phobia + Blood/Injury Phobia). These scales
are represented by questions 2 – 16 (FQ16).
Question 17 (FQ17) is a specific issue fear
(guns) and is of main interest to this study.
The global phobic distress index (an
anxiety/depression scale) is not utilized for the
purposes of this study.
Responsibility A participant’s tendency to
assume responsibility in
certain areas and situations.
Identifies individuals with
OCD (Antony et al. 2001 ).
One predictor
variable, measured at
the scale level
Measured with 26 items in the Responsibility
Attitude Scale (Appendix V). Each item is
scored on a 7-point scale (1, totally agree; to
7, totally disagree). Averaging the scores for
the 26 items operationalizes the
Responsibility Attitude Scale. Lower scores
represent higher levels of responsibility.
Before a correlational design could be successfully implemented, it was imperative to
explicitly define the criterion and predictor variables, and to explain how the variables were
operationalized. This information was essential to justify the use of appropriate methods of
18
statistical analysis. Accordingly, the conceptual, functional, and operational definitions of
the variables collected by the instruments administered in this study are outlined in Table 1.
The single criterion (response) variable, named Support for CCWs on Campus, had
only two categories, measured with nominal numerical value labels, in a binary format
(Yes = 1 or No = 0). Support for CCWs on Campus was assumed to be a hypothetical
attitudinal response of the participants to three predictor variables, specifically (a) Defensive
Pessimism;
(b) Fear, divided into two categories (FQ16 and FQ17); and (c) Responsibility.
The components of the predictor named defensive pessimism were measured on a
scale from 1 to 7. The variables were added to produce a final unidimensional defensive
pessimism score. The predictor named Fear offered three sub-scales: agoraphobia, social
phobias, and simple phobias. For the purposes of this study, only two were utilized. Fear
was operationalized as the sum of items 2–16 (total phobia scale) offering a unidimensional
variable named FQ16 by the researcher. Additionally, item 17 on the Fear Questionnaire, a
specific phobia statement oriented toward CCW, produced a unidimensional value named
FQ17 by the researcher.
The predictor variable named Responsibility was a unidimensional variable, with
each item measured on a scale from 1 to 8. Averaging the scores for 26 items
operationalized responsibility. This said, the research hypothesis (H1) stated that defensive
pessimism, fear, and responsibility were significant predictors of the probability that a
participant would support CCW on campus (relative to not supporting CCWs on campus).
The Null hypothesis (H0) stated that defensive pessimism, fear, and responsibility were not
19
significant predictors of the probability that a participant would support CCW on campus
(relative to not supporting CCW on campus).
Assumptions and Limitations
The main assumption was that students would be completely honest about their
responses on the various instruments as well as their response to the criterion statement. The
study had limitations. The study took place on a campus that was within a one hour drive of
Virginia Tech, the site of the nation’s deadliest school shooting. An assumption was made
that the affinity many had with the Blacksburg campus did not taint the view of some
students. The subject of gun rights was one of the most debated issues in the nation. There
has been a long tradition of debating Second Amendment rights in this country, and people
have had very strong feelings concerning the expansion or limitation of these rights. This
was especially true in the aftermath of the December, 2012, Newtown, Connecticut shooting
of 20 first graders. The study took place in rural Virginia, where gun ownership and hunting
continued to be a way of life. An assumption was made that this would not impact the
participant responses to the instruments.
Participants for the study were chosen through convenience sampling. As Black
(1999) pointed out, convenience sampling could bias the results as subjects might not be
representative of the population as a whole. This is often because participants are willing to
volunteer to participate. In this case, classes were selected that had a mixture of college
freshmen, sophomores, juniors, and seniors of varying majors to provide a random approach.
As Ferguson (2009) related, in areas that are under-researched, such sampling can help
establish an initial view.
20
Every attempt was made to isolate participants from each other to avoid any
questionnaire response contamination and to prevent potential threats to the validity of the
study. Participants were separated from each other at classroom tables and asked not to
communicate. Materials were fully discussed prior to testing. Any questions were addressed
by the raising of hands. By taking such precautions, keeping the threats to validity at a
minimum, the potential shortcomings associated with convenience sampling might have been
partially overcome. As mentioned above, Ferguson (2009) indicated in areas that are underresearched,
convenience sampling could help establish an initial view. This might help allow
the findings to be generalized to colleges and universities across the nation instead of limiting
the impact of them to the campus in question.
The nature of the design created limitations as well. As Lomax and Li (2013)
discussed, a quantitative correlational design does not allow for tests of “strong casual
inference” (para. 19), meaning a correlation could be indicated that could have other factors
involved that have not been recognized. The authors also indicated that this research
approach could produce statistical linear relationships causing the researcher to miss
relationships that are not linearly indicated. The authors also indicated that multiple
variables may produce a false correlation through simple chance. However, this was not a
concern in this research with limited variables.
Summary
Violence seems to become a common thread of life in the 21st Century. Recent
events of domestic and international violence, including acts of terrorism, brought a new era
marked by turbulence and caution. Recognizing the potential for violence, Maslow’s theory
of the Hierarchy of Needs was employed. Acknowledging that lower level needs must be
21
met before higher level needs can be pursued, the issues of personal safety within a college
environment were addressed. In other words, in a stable society marked by occasional acts
of violence, even on college campuses, how can an individual meet their safety needs yet still
pursue the higher level goal of obtaining an education? The presented research proposed that
defensive pessimism, a cognitive coping strategy, provided the bridge that completed
Maslow’s hierarchy of needs for some individuals by supporting CCW on campus. In other
words, defensive pessimism filled the void on the safety level so that attention could be
placed on a personal growth level (attaining an education). This assumption was not clearly
indicated in the current study.
22
CHAPTER II: REVIEW OF LITERATURE
Deadly violence on school campuses has become an all too common occurrence,
nationally and internationally, in the last 25 years. According to National School Safety and
Security Services (NSSSS, 2010), in the 2009-2010 school year (the most recent year for
which data was available), 11 students died from violent incidents which occurred on school
grounds; of these victims, seven were shot, three were stabbed, and one died from injuries
received in a fistfight. Additionally, there were 33 shootings that did not result in the taking
of a life. NSSSS also reported 82 other incidents. Those 82 incidents included, but were not
limited to, (a) attempted bombings, (b) attempted attacks with swords, (c) an attempted attack
with a chainsaw, and (d) bus hijackings. Additionally, there were gun incidents in which
someone was able to intervene before deadly violence ensued. Of course, the NSSSS
recorded data related to the K-12 programs nationwide during the years indicated above. The
NSSSS did not record violence that occurred on the nation’s college campuses, but the data
indicated the type of violence that had the potential to possibly graduate to the arena of
higher education.
Clint Van Zandt (2010) studied violence on college campuses within the United
States. He indicated that violence dramatically increased on college campuses around the
nation. This was especially true over the last 20 years: 1990-2010. The author reported that
since the year 1900, there have been 272 incidents of what he called “targeted violence”
(para. 1). Of these 272 incidents of violence on college campuses, 60% reportedly took place
since the year 1990; however, nearly 100 of these attacks occurred since the year 2000.
23
Search Strategy
The majority of the information utilized in this study came from searching online
peer-reviewed journals. For instance, EBSCO, PsyNet, ProQuest, University of the Rockies
Library, and the Virtual Library of Virginia resources proved to be invaluable. Campus
violence, violence, Concealed Carry Weapons (CCW), defensive pessimism, feelings of
personal safety and a plethora of other headings were searched using the identified databases.
Additionally, defensive pessimism was discussed with one of its founders, Dr. Julie Norem at
Wellesley College.
Additionally, because the work was theoretically framed by Maslow’s pyramid
theory, extensive research was conducted into Maslow and subsequent researchers. This was
especially true as far as safety issues were concerned. However, with many recent events,
such as the Virginia Tech shooting and the Appalachian School of law shooting, as well as
issues of societal violence in general, mainstream press and contemporary organizations’
websites, including the federal government, were also utilized to help integrate some of the
real world numbers with the theoretical approach presented in peer-reviewed journals. This
being said, information that focused on a sense of personal well-being (i.e., safety) formed
the foundation of the study. Every effort was made to keep the research limited to within
five years of the current date. However, certain seminal works as related to the subject were
addressed from outside that five-year period.
Review of Literature and Research
Because of the researcher’s interest in defensive pessimism, Dr. Julie Norem’s work
proved to have a significant impact on the structure of the current study. Norem (2002)
argued that the concept known as defensive pessimism was a real coping strategy. It allowed
24
anxious individuals to control their anxieties so that they could use it as a tool for progress
instead of allowing it to tear them down. In other words, it was a process that could “aid our
efforts toward self-discovery and enhance[s] our personal growth” (Norem, 2002, p. 3). Put
simply, it addressed anxiety rather than ignoring it. In short, Norem (2002) defined
defensive pessimism as:
the process that allows anxious people to do good planning. They can’t plan
effectively until they control their anxiety. They have to go through their worst-case
scenarios and exhaustive mental rehearsal in order to start the process of planning,
carry it through effectively, and then get from planning to doing. (p. 48)
Levels of defensive pessimism, fear, and responsibility were weighed against the
acceptance or denial of CCW on campus. These were assessed in terms of the proposed
hypotheses (H1) that defensive pessimism, fear, and responsibility are significant predictors
of the probability that a participant will support CCW on campus. This stood in direct
contrast to the null hypothesis (H0) in which defensive pessimism, fear, and responsibility
were not significant predictors of the probability that a participant might support CCW on
campus. To achieve this end, the quantitative research methodology was applied. The
research structure was underpinned by a correlational design.
The overall research question that guided this study was, “What are the relationships
between the participants’ support for CCW on campus, and their levels of defensive
pessimism, fear, and responsibility?” This was a question spawned by the researcher’s
interest in campus violence in his home state. Based upon campus violence in the
Commonwealth of Virginia, the research project became quite clear.
As already stated, research studies into the cognitive process and weapons appeared
to not have been undertaken to any great extent. Nagtegaal, Rassin, and Muris (2009)
studied the link between aggression and guns. They reported that the existing literature was
25
quite broad as far as this relationship was concerned. Nagtegaala et al. (2009) indicated that,
to some, even the presence of firearms was believed to make individuals aggressive.
Referring to the Berowitz’s and LePage’s (1967) famous study, Nagtegaala et al. (2009)
emphasized the finding that study participants who were angry administered a greater
number of electrical shocks to test subjects in the presence of a gun than they did in the
presence or absence of another object. This became known as the weapons effect and
spawned extensive research (Nagtegaala et al., 2009).
Similarly, Nagtegaala et al. (2009) researched a link between aggression and gun club
membership. Their research was born out of a violent incident that occurred in the
Netherlands in April 2004 in which a member of a Dutch gun club opened fire, killing three
before committing suicide. The authors reported that members of mainstream Dutch society
developed the view that gun owners were more aggressive individuals when compared to
average Dutch citizens. The results of a study carried out by the authors utilizing a
nationwide sample of 59 gun club members and 67 control individuals did not support this
hypothesis. The researchers found that gun club members scored differently on both
aggression and aggression-related variables when compared to study controls. Gun club
members scored lower on aggression than did the controls. They also scored lower on
impulsivity and aggressive thoughts when compared to the controls. The conclusion that gun
owners were more aggressive was clearly not borne out by the study conducted by Nategaala
and others.
In addition, Nagtegaala et al. (2009) noted that studies by Bartholow, Anderson,
Carnagey, and Benjamin (2005) indicated that gun owners, especially hunters, had a different
view of aggression when compared to non-gun owners. In contrast, Nagtegaala et al. (also
26
discussed in Huesmann, 1998) theorized that “interacting with weapons increases the chance
of behaving aggressively, due to rehearsal and subsequent activation of a hyperactive
aggressive script” (Nagtegaala et al., 2009, p. 322). From a differing viewpoint, Gleason,
Jensen-Campbell, and South-Richardson (2004), Tremblay and Ewart (2005), and Walker
and Gudjonsson (2006), as referenced by Nagtegaala et al., 2009, reported that a connection
between neuroticism or psychoticism and aggression has been established. Individuals who
are hostile by nature, or very self-oriented (i.e., psychotic), and those who are emotionally
unstable (i.e., neurotic) actually behave more aggressively than the norm. Nagtegaala et al.
(2009), referencing Bartholow et al., 2005, reported that “there may be differences in
underlying knowledge structures, or cognitive scripts, between the two samples” (p. 322).
Defensive pessimism, one such cognitive script, was important to this study’s approach.
Virginia Takes the National Stage
Violence within the state of Virginia also came to bear on the study. As Van Zandt
(2010) mentioned, two of the most glaring incidents of violence in the past decade occurred
within the Commonwealth of Virginia. On January 16, 2002, a 43-year-old student from
Nigeria, Africa, Peter Odighizuwa, went on an armed rampage at the Appalachian School of
Law in Grundy, Virginia. On Tuesday, January 15, Odighizuwa was dismissed from the law
school because of poor performance (Okereke, 2002). On Wednesday, January 16, using a
.380-caliber semiautomatic weapon, Odighizuwa began exacting his revenge. He killed the
Dean of Students, a professor, and a student. Three other students were critically wounded in
the shooting (Okereke, 2002).
According to Okereke (2002) and Kahn (2004), Odighizuwa came to the law school
with a history of mental instability. Lawsuits filed by the families of the victims demanded
27
the school share a portion of the blame. They reasoned that the school was aware
Odighizuwa had a reputation for past violence. An attorney for a group of the victims
reported, “Not only was this situation foreseeable, it was probable, based upon Peter’s
[Odighizuwa] prior conduct” (Kahn, 2004, para. 6). Two years after the shooting, having
been diagnosed with paranoid schizophrenia, Odighizuwa seemed to confirm such suspicions
by stating, “I feel like I’m God sometimes, and I was running demons out of the school. It
was like an exorcism” (Kahn, 2004, para. 3). However, he also added, “The students
shouldn’t get anything from the school. The law school isn’t a psychiatrist. It doesn’t know
what is in my head” (Kahn, 2004, para. 13).
Yet, at the same time, Odighizuwa partially blamed the school for his act of violence.
He indicated fellow students had socially ostracized him. “I wasn’t just shooting all over the
place. I saw the people who were menacing me” (Kahn, 2004, para. 24). Feeling threatened,
Odighizuwa began carrying a concealed weapon (Kahn, 2004). After he finally became
violent, he claimed those who ridiculed him were his targets. The students who were shot
were reported to have been particularly “mean” to him (Kahn, 2004, para. 23). Yet, as he
was shooting those he claimed ridiculed him, he also said he was “taking care” of Central
Intelligence Agency (CIA) agents, Federal Bureau of Investigations (FBI) agents, and
Komitet Gosudarstvennoy Bezopasnosti (Committee for State Security or KGB) agents
(Kahn, 2004, para. 25).
A very similar case of violence occurred in 2007 in Blacksburg, Virginia. On April
16, a young South Korean immigrant student engaged in a massacre. The shooting was
reminiscent of the Columbine High School shooting in Littleton, Colorado, just 8 years
earlier, in which two high school students killed 13 people in a similar manner. Prior to the
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Virginia Tech shooting, the nation’s most tragic college campus shooting occurred in 1966 at
the University of Texas at Austin when a shooter in a clock tower killed 16 people. In
Blacksburg, 33 people died (including the shooter), and 15 were wounded in a singlegunman
rampage that occurred over two and one half hours following a single shooting
incident from the same gunman much earlier that morning in a campus dormitory. During
what some called the “deadliest shooting rampage in American history,” the perpetrator lined
victims up against a wall and shot them execution style (Hauser & O’Connor, 2007, para. 1,
3).
The shooter was Cho Seung-Hui, a 23-year-old senior at Virginia Tech. Johnson et
al., (2007) reported that Cho was socially inept. In addition, he seemed to have a speech
impediment or a considerable lack of English language skills. In one instance, reported by a
high school classmate, a teacher asked Cho to read aloud in class. After being threatened
with a failing participation grade, Cho finally acquiesced. “As soon as he started reading, the
whole class started laughing and pointing and saying, ‘Go back to China,’ the classmate
reported” (Johnson et al., 2007, para. 7). Similarly, Cho’s classmates in his high school
English classes called him “the Question mark kid,” according to a student (Johnson et al.,
2007). The authors wrote that he earned this moniker because he signed a class attendance
sheet with a question mark instead of his name.
These issues followed Cho to Blacksburg, as some of his high school classmates also
attended Virginia Tech. Prior to the shooting, he reportedly left a message on the dry erase
board of a fellow student’s dorm room door. That message was a simple question mark
(Johnson et al., 2007). In the end, two of the victims of the violence were former high school
29
classmates. In a message left for the press, Cho indicated that the time had come for him
carry out his revenge (Johnson et al., 2007).
As in the case of the Appalachian Law School shooting and Peter Odighizuwa, there
were so-called red flags to Cho’s troubled nature (Johnson et al., 2007). In fact, according to
the authors, multiple entities within the Virginia Tech community raised these red flags. A
Virginia Tech professor had him removed from class because of macabre writing. Two
female students reported him to campus police for allegedly sending them disconcerting
messages. A Virginia magistrate also ordered Cho to submit to a psychiatric evaluation
(Johnson et al., 2007). According to the authors, Virginia Tech had been dealing with
various behavioral issues involving Cho for two years prior to his ultimate act of violence
(Johnson et al., 2007). Still, this did not indicate a potential for violence.
Zhou, Knoke, and Sakamoto (2005) indicated that students from foreign cultures,
including East Asian cultures, find difficulty assimilating into western educational
environments because of cultural and communication barriers. Hodne (1997) wrote from
personal experiences in teaching ESL at the college level. In one example, she asked an East
Asian student about her math class. Particularly, she asked about how she was integrating.
The student responded that she had not met anyone. Instead, the student relayed that “the
Americans all sit and read” (Hodne, 1997, p. 85). Hodne also had a son in the same class.
When she asked her son about student interaction with the Asian students, she was told that
the Asians students isolated themselves and spoke in their native language. This distance,
according to Hodne, has a “dark side.” The author referenced a 1990 report from the
California State University (CSU) system. This study, according to Hodne reported that
students of an Asian Pacific background were the least satisfied of all cultural groups. Citing
30
the Asian Pacific American Education Advisory Committee of 1990, Hodne reported that
“the stress of adjusting to a rigorous academic load is compounded not only by language
difficulties but also by cultural differences, value conflicts, and both subtle and overt racism”
(p. 86). Hodne went on to say such challenges were not specific to California. In
interviewing similar students from Massachusetts, the author indicated that they found US
college classrooms to be places “that silenced them, that made them feel fearful and
inadequate, that limited possibilities for engagement, involvement, [and] inclusion” (Hodne,
1997, p. 86). Additionally, despite superior college performance, students can be viewed as
“less intelligent” (Hodne, 1997, p. 86) if their English language skills are not flawless. The
author also stated that it is, in part, the professor’s role to make such students feel welcome in
a classroom. To fail to do so can create an environment in which the student in question can
view the professor as being prejudiced (Hodne, 1997). She went on to state that “non-native
speakers risk confusion and embarrassment if teachers misunderstand them, and it is even
worse when their classmates misperceive, ignore, or ridicule them” (p. 86). The same may
come from friends and family.
Hodne (1997) told of a Cambodian student. She indicated the man came to her office
where he cried as he told her about a recent telephone conversation. He said that when he
answered the phone the voice on the other end accused him of sounding differently. Hodne
indicated that this was a success to her. “To my American ear, he was simply speaking more
audibly,” she said (Hodne, 1997, p. 89). However, from the caller’s point of view, this was
not so. In using his new American way of speaking, as he had been taught to do, Hodne
indicated that he felt that “he was losing the gentle, soft-spoken voice Cambodian people
cultivate and value” (p. 89). Such friction, as discussed by Wei-Chin and Wood (2009) who
31
were citing Birman (2006), has been linked to mental health issues in the Asian community.
Additionally, the author indicated exactly how these acculturative problems “lead to poor
mental health” (p. 124) is not well understood. Acculturating more quickly, being educated
in the US, and having better English language skills are believed to add to the already
accepted generational gap problems all families experience according to Wei-Chin and Wood
who cited Szapocznik, Santisteban, Kurtines, Perez-Vidal, and Hervis (1984). Despite these
issues, the authors indicated that research has supported increased depressive disorders
amongst Chinese adolescents in the United States. The authors also found research that
supported the idea that when the family adhered to strong mother-culture practices, the youth
in question had greater levels of maladjustment and, according to Wang, Probst, Moore,
Martin, and Bennett (2011), violent disagreement. In a study carried out by Wang et al., this
was especially true in Asian homes where the parent was born in another country. For
students, according to Wei-Chin and Wood, this could mean disagreements over everything
from dating to what to study in school. Additionally, the authors indicated that these
incongruities became greater in adolescence and young adulthood. According to Leung,
Monit, and Tsui (2012), this may have a detrimental impact as Asian youth often prefer to
turn to family members when in need. However, this did not include mental health issues
according to the authors. “In studies of Chinese Americans, help seeking behavior has been
found to be related to ‘environmental or hereditary causes,’ and has seldom been reported as
personal or psychological problems” (Leung et al., 2012, p. 61). Additionally, as the authors
pointed out, Asian Pacific peoples in the US underutilize mental health services. Family and
personal outlets are seen as desirous in certain cases. In dysfunctional family situations this
can be detrimental to the individual in question.
32
Similarly, students also expressed concerns about losing valued culture norms in
learning to fit in within their new environments. Hodne (1997) went on to conclude that the
“American academic culture directly challenges the social ethics that many Asian immigrant
students bring to their American classrooms” (p. 90). There was a distinct alienation. Poon
and Byrd (2013) discussed similar alienation in the 1.5 and second generation Asian youth in
an educational setting. As Zhang and Hong (2013) indicated, as far as Asian students are
concerned, where there is a perception of discrimination, there is also increased levels of
psychological stress. Additionally, discrimination perception and distress was found by the
authors to be greater in the educated. As Bittle (2013) indicated, this can cause Asian
students to feel “invisible in their own schools” (p. 58). According to Bittle, life is made
difficult because the media stereotype of Asians permeated society including the classroom.
Such difficulties put Asian families at risk for internal violence based upon the research of
Kim-Goh and Baello (2008). This violence is underreported, according to the authors. The
same emotional damage studies have shown to have been exacted upon members of other
groups is also exacted upon the Asian family unit; but, as the authors point out, this is an area
that is understudied because of the enduring misconception that Asians are the “model
minority” (p. 647).
This being said, the point of this discussion is not to question the actions of either
school or any of those involved in the cases. It is not meant to question the actions of other
students who could obviously be viewed as bullying. It is not intended to question the
cultural sensitivity of the schools, their professors, or the other students. The point of the
discussion is to use the two examples from Virginia to lay the foundation for an argument
33
that gained momentum around the nation. That argument was the support for CCW on
campus.
The Law School Difference
What many people do not remember about the deadly shooting at the Appalachian
School of Law in Grundy, Virginia, is that an armed student brought Odighizuwa’s actions to
an end. It may never be known whether this action saved lives. However, it is obvious that
the action rendered Odighizuwa’s rampage inert. According to news sources, including the
Associated Press (2002), three former police officers were also students at the small law
school. One of those students retrieved a weapon from his vehicle. According to the news
sources, upon seeing the shooter place his gun on the ground for a moment, the former
officers-turned-students made their move. One of them aimed his weapon at Odighizuwa
(The Associated Press, 2002). The source then reported the three students seized
Odighizuwa. They handcuffed him while awaiting the arrival of law enforcement officials.
A New National Psyche?
In addressing the media viewpoint, the Associated Press (2002) made a noteworthy
correlation between these tragic incidents and the national and international nature of reality
in the 21st century–a reality in which safety concerns were elevated. According to the news
source, in light of the war on terror in which the United States had been involved, aggressive
actions to achieve safety were seen as commendable and even necessary. As an example, the
source highlighted the average citizens who took action on a jetliner that crashed in
Pennsylvania on September 11, 2001. This was a jetliner believed to be targeting the White
House. Passengers who prevented shoe-bomber Richard Reid from carrying out his task
34
aboard another airliner were also mentioned. In fact, the news sources referred to these
individuals as “brave” and as “heroes” (The Associated Press, 2002, para. 4).
The goal of this dissertation was not to determine the impact of the changing national
perception of CCW. Nonetheless, incidents like those described change public opinion and
consequently affect the study of CCW. The overwhelming sense of vulnerability at home
and abroad did come to bear on the way people thought. In Virginia, actions taken shortly
after the Appalachian School of Law shooting reflected shifting attitudes.
The Debate Begins
According to Hall (2002), in Northern Virginia, the George Mason University (GMU)
School of Law’s Second Amendment Group called for an end to the school’s ban of weapons
on campus shortly after the Appalachian law school shooting. Second Amendment Group
president, Orest J. Jowyk, explained, “I think the middle ground is to allow concealed
handgun permit holders to carry just like they can anywhere else in Virginia. You provide
extra safety to the student body that way” (Hall, 2002, para. 3). Jowyk reported that he
moved to adopt such a choice because of the Grundy shooting, but he was specifically
spurred on by the actions of the armed students who confronted the gunman. This pushed
him to challenge the GMU gun ban policy. However, the Chief of Police for the law school
did not agree. He stated that “it is my opinion that that (sic; students carrying guns) would
increase the propensity for somebody getting hurt, and I don’t want to see that” (Hall, 2002,
para. 12). The dilemma about whether or not to allow CCW on campus did not remain
confined to the boundaries of the Commonwealth of Virginia. A similar argument began in
Utah.
35
After the Appalachian School of Law shooting in Grundy, Virginia, the Utah
Attorney General challenged a 25-year-old ban on concealed weapons by the University of
Utah claiming it was in conflict with state law (Hall, 2002). University of Utah President,
Bernie Machen, said the university needed the right to maintain the ban because it helped
foster “a safe learning environment” (Hall, 2002, para. 16). In March 2002, a Republican
sponsored bill moved to cut the school’s administrative budget in half if the gun ban was not
discontinued. The school filed suit in the US District Court and lost (Hall, 2002). Utah
became the only state in the nation to allow guns on all state college and university campuses
(Fennell, 2009).
The reasoning applied in the Utah debate was understandable. According to Fennell
(2009), an act of shooting violence on a college campus was one of the most feared possible
events in academia. This being said, it was not difficult to understand why many states
sought the expansion of Second Amendment rights to include the nation’s college and
university campuses. Additionally, the author cited an article in a 2002 edition of the
Journal of American College Health (JACH), in which a study conducted at 119 colleges
found that 4% of college students already carried a weapon on campus. Fennel noted that,
extrapolating from the 2009 numbers, the expectation of finding 700,000 weapons on those
same 119 college campuses was reasonable. If extended to the nation’s 4,300 colleges and
universities, the number of CCW might exceed 20 million. According to watchdog
organizations Campaign to Keep Guns Off Campus and Coalition to Stop Gun Violence,
both of who reported to the public on an internet site (Armedcampuses.org), after Utah, four
other states joined the list of states that allowed colleges and universities to permit their
students CCW on campus, in some form. Michigan, Colorado, Virginia, and Oregon were
36
among the first to join this exclusive club (“Colleges and Universities that Allow Guns on
Campus”, n. d.; Associated Press, 2012). Michigan did not allow weapons inside campus
buildings, according to the previous sources. A private college, Liberty University in
Virginia, followed Michigan’s example (Associated Press, 2011). However, according to
Fennell, Utah was actually the only state in the US where guns were allowed on all state
property, including college campuses. Citing Lipka (2008), Bouffard et al. (2011) indicated
that state legislatures in Alabama, Georgia, Indiana, Louisiana, Oklahoma, South Carolina,
South Dakota, Texas, and Washington also “initiated attempts to allow students and/or
faculty and staff with appropriate CHL [concealed handgun license] to carry firearms on
campus” (p. 285).
Debate Continues
With this in mind, Drysdale, Modzeleski, and Simons (2010) remarked that college
campuses brought together a combination of life stressors that were not necessarily found in
other environments. As students sought an education, they had to deal with those stressors.
They might have been newly independent. They might have experienced new academic
pressures. At the same time, they might have lived on campus, and that might have added to
the stressors they faced. This created an environment in which, if violence occurred, it would
be similar to types seen in mainstream society (Drysdale et al., 2010). This was especially
true with regard to murder. In most all cases, the victim and the perpetrator knew each other.
In addition, one half of all campus murders were committed with a handgun. What is not
well understood is why. Drysdale et al. (2010) emphasized this point. “Little is known at
this time about the nature and characteristics of murders on campus” (Brumley, 2005, as
37
cited in Drysdale et al., 2010, p. 5). The existence of this apparent gap in understanding
underscored the need for the proposed study.
Citing a 2001 U.S. Department of Education report, in an article titled “Colleges and
Universities That Allow Guns on Campus” (2013), claimed that the anti-gun laws that had
been the norm on the nation’s 4,300 plus colleges and universities have been the reason for
the overall lack of violence on college campuses. For example, the USDE reported that the
rate of murder on college campuses was 0.07 per 100,000 based upon 1999 statistics. In
mainstream society, also according to the USDE, that number was 5.7 murders per 100,000.
For individuals aged 17-29 in mainstream society, the USDE reported the number of murders
was 14.1 per 100,000. The USDE implied that the lack of firearms access was a major
reason behind the low numbers. Yet, when murders did occur on college campuses, firearms
still played a key role. In other words, despite legal bans, guns still claimed lives on the
nation’s college campuses. According to Miller, Hemenway, and Wechsler (2002), in a
study of 10,000 college students, 4.3% of students reported having a functioning firearm with
them on campus. In addition, 1.6% had been threatened with a gun on campus. Also,
“students with guns were more likely than students without guns to have alcohol-related
problems, such as getting into fights attributed to drinking alcohol and being arrested for
drinking while intoxicated” (Miller et al., 2002, p. 57). Clearly, these students engage in
reckless behavior that could pose a threat when a gun was involved.
Despite such data, the debate about CCW on campus was far from over (Fennell,
2009). Opponents feared that the presence of guns on campus would lead to more deaths.
Proponents highlighted the idea that, although guns have long permeated our society,
massacres have very rarely occurred. Fennell stated that the United States, as a society,
38
operated on a “hypothesis based on fear” (p. 100). Based upon this hypothesis, he indicated
he saw no problem with law-abiding citizens carrying CCW on the nation’s campuses.
However, he indicated that in real world settings, this hypothesis of fear might cause
complications. For example, in the event of shootings, such as those at Virginia Tech or the
Appalachian School of Law, multiple problems could arise for a CCW carrier. In particular,
Fennell questioned how law enforcement would be able to distinguish the real perpetrator
from an armed defender. “What if the person was just trying to defend him/herself and was
shot in a case of mistaken identity by the police or another person with a CCW?” (Fennell,
2009, p. 100). With such potential for confusion, the author claimed the best approach, in his
opinion, was to keep firearms accessible, yet keep them out of the hands of those with mental
health issues. If access to firearms was limited, the author says that “Unfortunately, those
with legal concealed carry weapon permits who follow the law will be defenseless to protect
themselves during an attack” (Fennell, 2009, p. 100). Despite potential negative
consequences, support for CCW remained. For example, in a student newspaper at the
University of Wisconsin, Milwaukee, a student wrote an article entitled “9mm is faster than
9-1-1” (Prellwitz, 2011, p. 17).
Such staunch support has been met with a sense of balance. In Oregon, the courts
have ruled that University policy could not circumvent state laws that allowed CCW
(Richardson, 2012). However, the same courts ruled that Universities in Oregon have
sweeping control over their properties. To this end, weapons were denied in buildings and at
any campus event. Additionally, any individuals (including students) who engaged in a
business arrangement with Oregon State University schools could not carry a weapon as a
condition of the contract into which they had entered (Richardson, 2012). As a result,
39
virtually no one could legally carry a weapon on campus unless the carrier was a random
stranger with no connection to the state’s universities or a member of the exempted
university police (Richardson, 2012). Interestingly, as the author pointed out, this approach
might seem to violate the court’s original ruling. However, when legally challenged in a
court of law, these policies were upheld (Richardson, 2012). Virginia faced a similar issue.
Concealed weapons on campuses were legal, but schools could make individual policies that
effectively preclude the presence of CCW in buildings, but not on campuses. Virginia’s
Republican governor, Bob McDonnell, said he would not support any legislation that
tampered with the schools’ individual choices because the system, as it stood, seemed to be
adequate (Sluss, 2012).
As the debate continued, neither side seemed to be backing down. Opponents of
CCW, especially on college campuses, pointed to a study conducted by the Washington, D.C.
based Violence Policy Center. The center compiled data involving crimes in which an
individual with a CCW permit was involved in any way. As of February 16, 2012, legal
concealed carriers had killed 11 law enforcement officers. Additionally, legally permitted
concealed carriers had killed 380 private citizens, carried out 20 mass shootings, and
committed 30 murder-suicides (Violence Policy Center, 2012). The center tracked those
numbers beginning in May 2007 (one month after the Virginia Tech shootings).
Citing the Florida Sun Sentinel, the watchdog organizations Campaign to Keep Guns
Off Campus and Coalition to Stop Gun Violence, reporting on their collective website,
Keepgunsoffcampus.org and Armedcampuses.org found that there were over 1,750 incidents
reported in Florida in which concealed carry permits had been granted to individuals who did
not meet the state’s standards. This number included “more than 1,400 people who had pled
40
guilty, or no contest to a felony; 216 people with outstanding warrants; 128 people with
active domestic violence injunctions; and six registered sex offenders” (“Concealed Carry
Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 4). In Texas, by
conducting four studies, the Violence Policy Center determined that “from 1996 to 2000,
Texas concealed handgun permit holders were arrested for weapon-related offenses at a rate
81 percent higher than that of the general population of Texas aged 21 and older”
(“Concealed Carry Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 6).
Similarly, in Tennessee, watchdog organizations cited a study by the Memphis Commercial
Appeal that found in one county, Shelby County, 70 citizens received concealed carry
permits despite having been arrested for violent crimes (robbery, assault, and domestic
violence). In one instance in Tennessee, a single individual had 25 arrests on record yet still
received a concealed weapon permit. After the fact, the same individual faced federal bank
robbery charges. According to the Memphis Commercial Appeal, “administrative glitches”
in the state’s system caused these occurrences (“Concealed Carry Does Not Reduce Crime
Does Threaten Public Safety”, n.d., para. 8). The Indianapolis Star found 450 such glitches
in two counties as late as 2009. The paper reported, in broad terms, the Star found a system
that breaks down in numerous ways, enabling people with troubled and often violent pasts to
legally keep a loaded gun in their waistbands and on their passenger seats (“Concealed Carry
Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 9). The organizations
went on to state “as more is learned, it becomes absolutely clear that concealed carry systems
do not work as promised but operate to arm and embolden many dangerous individuals”
(“Concealed Carry Does Not Reduce Crime Does Threaten Public Safety”, n.d., para. 9).
Similarly, Sulkowski and Lazarus (2011), writing for the Journal of School Violence,
41
reported that in order to maintain safe campuses, schools needed to develop a system devoid
of glitches like those mentioned above. Sulkowski and Lazarus recommended the use of
criminal and shooter profiling, emergency plans, increased security technology on campus,
and threat assessment procedures, just to name a few, to facilitate effective campus security.
Even then, it was considered to be impossible to eliminate all threats (Sulkowski & Lazarus,
2011). However, in the nation’s recent economic situation in which states struggled to make
ends meet and higher education budgets were suffering cuts, it was difficult to envision
expenditures for such endeavors.
In the United States’ litigious environment, failure to act can be just as costly. On
March 14, 2012, a Christiansburg, Virginia, court awarded the families of two victims of the
2007 massacre at Virginia Tech $4 million each (CNN, 2012). The jury found that Virginia
Tech was negligent in its handling of the incident and ruled against the University. The
mother of one student who was wounded in the shooting stated, “Vindication has finally
come. This is about them being accountable” (CNN, 2012, para. 4).
Defensive Pessimism: The Positive Power of Negative Thinking?
Such legal ramifications, along with the huge unknowns that colleges and universities
faced, brought into question why anyone would want to allow weapons on a college campus.
Based upon the research presented above from the Violence Policy Center, the two seemed a
potentially dangerous combination. Still, as indicated, there were those who desired just that
combination. What could have influenced someone to think that allowing concealed carry
weapons on campus was a good idea. Perhaps it had to do with the way they processed their
world and dealt with the issues found therein. Defensive pessimism might be an explanation.
It could lead individuals to see CCW on campus as the safest route to a controlled
42
environment when confronted with their own levels of fear and responsibility. Accepting or
denying CCWs on campus might have helped defensive pessimists alleviate or placate the
fear and responsibility they might have faced concerning possible violence.
Norem (2002) argued that the concept known as defensive pessimism was a real
coping strategy. It allowed anxious individuals to control their anxieties so that they could
use it as a tool for progress instead of allowing it to tear them down. In other words, it was a
process that could “aid our efforts toward self-discovery and enhance[s] our personal
growth” (Norem, 2002, p. 3). Put simply, it addressed anxiety rather than ignoring it. In
short, Norem defined defensive pessimism as:
the process that allows anxious people to do good planning. They cannot plan
effectively until they control their anxiety. They have to go through their worst-case
scenarios and exhaustive mental rehearsal in order to start the process of planning,
carry it through effectively, and then get from planning to doing. (p. 48)
Additionally, according to Cantor, Zirkel, and Norem (1993), transitional periods can
exacerbate this anxiety. Cantor et al. additionally indicated that within a particular group
there could be varied rankings and appraisals of life’s tasks. Cantor et al. wrote that these
appraisals reflect “current concerns that consume people’s thoughts and guide their attention
selectively; the personal strivings that organize actions in the service of desired outcome; and
the common age-graded life tasks which individuals pursue in unique ways” (p. 426). In
short, people have different goals at different points in time. Safety was one of the goals
pertinent to this study.
Instead of pessimism resulting in the negative outcomes our society was used to
hearing about, in Norem’s (2002) view, defensive pessimism was a coping strategy “by
which negative thinking transform[s] anxiety into action” (p. 5). In other words, people who
dealt with life via a defensive pessimism coping strategy actually “manage instead of banish
43
their negative emotions” (Norem, 2002, p. 6). It helped to confront, instead of deny, the
negative feelings they experienced (Norem, 2002).
Norem (2002) recognized that such a concept is contrary to the perceived national
belief of the past few years–the positive psychology approach that has been afoot in U.S.
culture dictated individuals must see the positive side of things. Norem stated that to
approach something from a negative point of view was “almost heretical” (p. 1) in this
society. Doing so was contrary to the brave and heroic status emphasized by the mainstream
press and discussed earlier in this chapter. This is why Norem reported that positive
psychology has been sweeping the nation. However, the definition of this positive
psychology has been quite limited and tended to revolve around optimism as the key to
positivity. According to Csikszentmihalyi and Hunter (2003), positive psychology focused
on what made life worthwhile. The authors noted that James, Dewey, Rogers, and Maslow
all focused on psychological well-being. According to the authors, in some areas of the
world, particularly the West, people needed something more. With base needs presumably
met, individuals needed other psychological fulfillment. Czikszentmihalyi and Hunter
highlighted Inglehart’s (1997) theory that happiness decreased as a nation’s economic state
improved beyond the basic needs. In other words, economically advanced nations were ripe
for the so-called good life positive psychology had to offer. However, and to the intent of
this study, such an ideology did not take into account a world in which safety became an
uncertainty. To this end, what such positive thinking proponents failed to recognize was that
“negative thinking is positive psychology” (Norem, 2002, p. 13). It was positive because it
helped individuals cope with the unease of the modern world.
44
Simply put, the defensive pessimism coping mechanism allowed those who utilized it
to attain their objectives. Additionally, Cantor et al. (1993) reported that other researchers, in
particular Swann (1987), indicated that defensive pessimists were open to the views of others
when they were in a state of ambiguity. As a result, individuals in such situations could seek
out conditions that provided them with positive emotional states instead of negative ones.
They often did this by seeking out others who were in similar situations or harbored views
similar to their own (Cantor et al., 1993). This could indicate a need for self-protection that
could theoretically account for CCW support. “Individuals can and do use their social world
in useful ways to navigate crises and transitions, small and large” (Cantor et al., 1993, p.
275).
Norem (2002) believed that defensive pessimism increased peoples’ feelings of
control. She implied that being overly confident about a situation, to a defensive pessimist,
was to almost welcome calamity and subvert the goal of the strategy that, as has already been
alluded to, was a strategy for controlling a given situation. Simply put, defensive pessimists
planned for every contingency that could cause them anxiety. They have to think situations
through multiple times. This helped them slowly alleviate their anxiety as a plan began to
form in their minds (Norem, 2002).
Anxiety became the crux of the defensive pessimist strategy (Norem, 2002).
However, there was an important distinction to make about defensive pessimism. The
anxiety was used for a positive outcome, so successful use of the strategy did not depend on
past anxiety. It was a strategy that utilized anxiety about what was to come, a strategy that
used a new situation and the anxiety this new situation brought to begin a planning process
that would bring about the most positive outcome for the strategist in question. Defensive
45
pessimists simply were unable to function well when they were anxious. When they felt they
had done what they could to elicit a positive outcome, they became better prepared to
function without the anxiety. In the scenario of potential violence as proposed here, Norem
(2002) made an interesting observation in discussing evolutionary anxiety toward predators:
Few of us are faced with situations involving literal predators these days [of course,
the decade since 9/11 has altered this view in the minds of some individuals]. Still,
even when we’re faced with a nonlethal threat like a predatory coworker or the
prospect of failure, vanquishing the powerful urge to run away when we feel anxious
is no easy mandate. Thus, the first problem posed by anxiety is the problem of
making ourselves stay in the game; we have to be able to tolerate the tension to
remain in whatever situation (or pursuit of whatever goal) makes us anxious. (p. 38)
For those who fear violence in society and feel a sense of responsibility regarding
safety, this could include creating their interpretation of a safe environment. Additionally,
and of great importance to the process, the coping strategy of defensive pessimism was
important in the preparation for particular situations. It did not involve the way those
situations were described (Norem, 2002). In other words, defensive pessimism allowed
anxious individuals to embrace what made them anxious so that they could convert the
anxiety into a tool for progress (Norem, 2002). This made defensive pessimism a two-step
strategy (Lim, 2009). First, there had to be a situation in which the strategist anticipated a
potentially negative outcome. This led to the second step. This was where the strategist
attempted to employ a strategy to avoid those possible negative outcomes.
This self-protection cognitive theory, a defensive pessimism component, was
reportedly quite common (Lim, 2009). A study by Eronen, Nurmi, and Salmela-Aro (1998,
as cited in Lim, 2009) found that defensive pessimism was the most common coping strategy
among college students. It was also found to be a strategy very commonly used among
Asians (Lim, 2009). This did not mean that defensive pessimism unto itself was the prime
46
reason for supporting CCW on campus. However, it was a possible explanation as to why
individuals who utilized such a strategy might support such a stance.
Similar to Lim’s (2009) claim that defensive pessimism was a two-step process,
Gasper, Lozinski, and LeBeau (2009) reported there were also two independent tendencies
that influenced defensive pessimism. Pessimism is one part; reflectivity is the second. They
operated independently of each other, but they collectively served the individual using the
strategy. This separated defensive pessimists from true pessimists. This is the process that
occurred when the strategist deemed an outcome important. It was not a strategy employed
by strategic optimists (Gasper et al., 2009).
The goal was of paramount importance to the defensive pessimism process (Gasper et
al., 2009). If the goal was not of adequate value to the individual in question, then the
defensive pessimism process failed to engage. In other words, if the goal was not important
enough, then the individual in question felt neither pessimism nor anxiety. The theory did
not apply in such circumstances.
However, when the theory did apply, Gasper et al., (2009) found that reflection played
a vital role in the process. The trio found that in a study of students engaged in a first-time
task, reflection was most associated with elevated levels of outcome expectations. This was
especially true of those high in pessimism. This could, in the case of CCW on campus, in
theory, help identify an individual who has spent considerable time thinking about individual
safety in a new environment. Such an environment could be a post-secondary school
campus. As students gained more experience and more, what might be termed selfexperience,
the need to reflect and plan began to diminish. This could help explain why
47
some would feel an initial desire for safety, or in the current state of national and
international unease, a prolonged need to seek a continued state of safety.
In addition, defensive pessimists were more likely to weigh the pros and the cons of a
given situation and the likelihood of both good and bad things happening (Newman, Nibert,
& Winer, 2009). CCW on campus could represent one area in which addressing both the
positive and the negative might be important. In other words, guns might be associated with
violence overall, but a barrier between a safe environment and the potential for violence from
the outside world was countered by the coping strategy of some defensive pessimists.
Thomas (2011) reported that the defensive pessimism strategy was associated with better
mental health. Also, defensive pessimists paid much more attention to tactics that “may
mitigate disasters” (Thomas, 2011, p. 1). Thomas explained, “What the pessimist does is
take careful advance precautions so that this disaster does not happen” (p. 1). Although she
expressed this concept in general terms, it still applied to the original question posed. Could
defensive pessimists see CCW on campus as a positive strategy for self-protection? Thomas
offered clues to possible answers. She indicated that pessimism “makes people more alert to
their surroundings” (Thomas, 2011, p. 1). She cited Bergsma (2010), who stated, “Pessimists
may be more vigilant in situations of possible danger” (Thomas, 2011, p. 1). Thomas
discussed an optimistic friend who only saw the good in her fellow man. Her friend sought
directions from even the most questionable-looking characters. Thomas noted that it never
occurred to her friend that it could be dangerous to reveal that she was lost to questionable
individuals, in questionable areas, or in unfamiliar locales. In such circumstances, it never
dawned on her friend that she could become the victim of a crime (Thomas, 2011).
48
This being said, Elliot (2003) and Norem (2002) believed that defensive pessimism
was not self-handicapping. Elliot indicated that defensive pessimism was a tool that “aids an
individual’s striving in a particular domain of life such as the achievement domain” (p. 370).
In theory, this could apply to feelings of personal safety as well. Defensive pessimists do
worry relentlessly about future events (Lim, 2009). However, they do not just give up and
succumb to whatever will be. Instead, they used their worry as an impetus to begin actively
planning to avoid certain scenarios or achieve others. Support of CCW on campus might be
one path to achieve personal safety in a potentially violent society. Hazlett, Molden, and
Aaron (2011) gave a clue gleaned from their research. They indicated that individuals with a
concern for safety and security deal with these issues best through a pessimistic approach.
Del Valle and Mateos (2008), who studied the impact of mood on optimists, defensive
pessimists, and dispositional pessimists, emphasized this issue. The authors determined that
mood plays a role in how optimists and defensive pessimists viewed their worlds. As the
authors indicated, their findings were consistent with those of Sanna (1998, as cited by Del
Valle & Mateos, 2008). Del Valle and Mateos reported that when in an induced negative
mood, defensive pessimists were more likely to focus on the negative aspects of a given
situation. Additionally, although defensive pessimists anticipated negative results, they
continued to strive for the best outcome. The design of the proposed study will help
determine if the same can be said for campus safety and defensive pessimists.
A Closer Look at Defensive Pessimism
Nancy Cantor and her students coined the term defensive pessimism in the 1980s
(Norem, 2001). As previously discussed, defensive pessimism related to one overall
cognitive strategy for dealing with what life might offer. Untethered from the past,
49
embracing this concept was one way of dealing with anxiety concerning a wide variety of
issues. The concept derived from a social-cognitive approach to researching personality and
behavior. According to Norem (1989), Cantor and Kihlstrom (1987) labeled it a social
intelligence theory. Citing her own work, Norem (1989) stated, “Strategies describe coherent
patterns of expectations, appraisals, planning, effort, and retrospection as individuals pursue
personally relevant goals” (p. 78). The defensive pessimism strategy served to control
behaviors and emotions (Norem, 2001). Norem believed that the theory came straight out of
what Alfred Adler (1935/1979) said was the individual’s ability to adapt to his or her own
temperament and environment.
Studies undertaken in recent years have addressed defensive pessimism in an academic
setting. Yamawaki, Tschanz, and Feick (2004), attempting to isolate defensive pessimism in
such a setting, found that the theory does not work well in such a limited environment. It has
been determined, in an academic setting, that college students who were identified as
defensive pessimists in their freshman year experienced more negative than positive
encounters. Based upon the theory, this finding was not unexpected. Citing Cantor and
Norem (1989), Yamawaki et al. (2004) indicated that these same students had more negative
psychological symptoms and lower life satisfaction when compared to optimists. This is
contrary to the theory proposed by Norem (2001). Yamawaki et al. indicated that defensive
pessimists also showed lower self-esteem when compared to their optimistic counterparts.
Additionally, citing Showers and Ruben (1990), the authors emphasized that defensive
pessimists experienced higher rates of depression In fact, Yamawaki et al. stated that
evidence for the defensive pessimism theory that indicated anxiety served to boost
performance “is not especially strong” (p. 234). This, too, ran contrary to the theory. Norem
50
and Illingsworth (1993), as cited by Yamawaki et al., noted that when study participants
behaved in accordance with the defensive pessimism theory, they “showed a consistent, but
nonsignificant, tendency to report less anxiety relative to defensive pessimists who had been
prevented from engaging in this strategy” (p. 234). Citing Sanna (1998), Norem and
Illingsworth (1993) reported that the most notable aspect of the theory they found was that
the “performance-preparatory effects outweighed the anxiety-buffering effects” (p. 234).
This seemed counter-productive to the theory of defensive pessimism Norem (2001)
presented.
Yamawaki et al. (2004) further investigated these negative aspects of defensive
pessimism. Yamawaki et al. reaffirmed that defensive pessimism served those who practiced
the strategy well in the area(s) in which they were pessimistic. This is an important
distinction. In such a realm, the individual in question performed well and had greater
feelings of self-esteem and satisfaction. In all other areas, such as academics, the researchers
found that self-esteem appeared to be lower in so-called defensive pessimists. They believed
this was a consequence of negative self-thoughts. Yamawaki et al. indicated that this
translated into more depressive issues instead of the positive aspects associated with
defensive pessimism.
In fact, Yamawaki et al. (2004) pointed out that in areas where defensive pessimism
was not practiced, individuals showed a shorter period of enjoyment when an activity worked
out. Additionally, their self-reported enjoyment level was lower, and they were less involved
with the task than their counterparts. A test utilizing 500 psychology students found very
similar results. Their results showed that with regard to avoidance, unengaged defensive
pessimists scored significantly higher than their counterparts. They also found that on a
51
survey of mastery, the same subjects had significantly lower scores. Yamawaki et al. found
that correlations between self-esteem and negative-thought and self-esteem and self-esteem
instability were also significant. When they controlled for these factors, they determined
self-esteem does have an impact on how optimists and defensive pessimists perceive their
worlds in an academic setting. All things being equal, Yamawaki et al. determined that
individuals with moderate self-esteem might actually be more apt to employ the defensive
pessimism strategy because of the fact that they can access a cache of negative self-thoughts.
These negative self-thoughts, in turn, serve as an impetus to succeed rather than fail.
Nonetheless, self-esteem can still break down if negative self-thoughts are allowed to
dominate the situation. However, in an area in which the defensive pessimist is determined
to succeed, this is not necessarily the expected norm. Campbell (1996, as cited in Norem,
2001) reported that there was a negative correlation between self-esteem and defensive
pessimism. Personal views of the self are a part of the defensive pessimist approach.
Cardell, Wong, and Scott (n.d.) also studied defensive pessimism in an academic
setting. They discussed the original defensive pessimism scale as developed by Cantor and
Norem (1986) and discussed in Norem (2002) that consisted of nine items and focused on
distinguishing between optimists and pessimists in an academic setting. Cardell et al.
indicated that only one of the nine items in the questionnaire distinguished the defensive
pessimists from true pessimists. They defended this stance by highlighting the idea that
defensive pessimism was much broader than the original scale (the Academic Defensive
Pessimism Questionnaire) offered by Cantor and Norem (1986). Cardell et al. argued that
these broader aspects of defensive pessimism should be included when trying to develop a
scale to measure defensive pessimism. The authors also argued that this broader approach
52
was necessary to distinguish defensive pessimism from other coping strategies.
Consequently, the authors set out to create what they viewed as a more valid scale for use in
the academic setting.
Utilizing a group comprised of 109 students, both male and female, Cardell et al. (n.d.)
constructed a defensive pessimism scale with 30, as opposed to nine, items. The design of
this new tool allowed the researchers to assess the attitudes of individuals approaching
performance circumstances. In addition, the authors designed the measure to account for
“various coping strategies used, ruminatory thought patterns, types of failure attributions
made, and patterns of anticipatory reflectivity” (para. 5). After analysis, the authors reduced
their scale from 30 items to 17. Another study utilizing 126 students (male and female) was
later carried out. In the second study, Cardell et al. used their scale in conjunction with (a)
Cantor and Norem’s (1986) original defensive pessimism questionnaire used to assess
general optimism and pessimism, (b) Trice’s (1985) Academic Locus of Control Scale used
to measure internal versus external locus of control in academic settings, (c) Crandall,
Katkovsky, and Crandall’s (1965) Intellectual Achievement Responsibility Questionnaire
used to measure internal versus external failure attributions to assess locus of control in
failure situations, and (d) the Marlowe-Crowne Social Desirability Inventory by Reynolds
(1982) used to assess social desirability bias (as cited by Cardell et al., n.d.).
Cardell et al. (n.d.) determined that both of their studies found internal consistency in
their Academic Defensive Pessimism Scale. They indicated that their tool would be useful in
future studies in which defensive pessimism was the subject. They also indicated that the
questionnaire might be useful for student feedback. Specifically mentioned was the idea that
the students might perform better under negative circumstances as their anxiety served as a
53
motivating factor. This was an important factor as they claimed performance anxiety was
key to their study. To this end, the authors stated that the limitation of their work was that
“the current scale is intended only as a measure of defensive pessimism in academic settings
and has been tested only in a university setting” (para. 34). Norem’s (2001) revised scale is
much broader.
Norem (2001) believed that defensive pessimism was a strategy employed to prepare
for any event perceived as stressful. Driven by theory, not empirical data, the original scale
evolved around an academic setting. In discussing the original scale, the OptimismPessimism
Prescreening Questionnaire (OPPQ), Norem indicated that “when the items were
generated, the research team focused on elaborating the description of defensive pessimism”
(p. 81). Six of the items on the early questionnaire thus referred to the two hypothesized
components of defensive pessimism: pessimistic expectations and negative thinking, and
their presumed opposites (Norem, 2001, pp. 81-82). There were also two items seeking
measures of pessimistic and optimistic expectations and two items about positive and
negative thoughts and feelings. Additionally, Norem noted that there were two questions
about feelings after the performance to measure satisfaction.
In the revised version, Norem (2001) reported that two factors reflectivity and
pessimism rotated obliquely. She reported that the 2001 version of the Defensive Pessimism
Scale measured the “thinking through” (p. 82) process that was defensive pessimism. This
was key. “I continue to use a single defensive pessimism score computed by summing both
the pessimism and reflectivity items (with appropriate reverse scoring)” (Norem, 2001, p.
82). When compared to the original scale, the revised scale correlates at r = .65 with even
higher reliability (Cronbach’s alpha = .78). The reflectivity and pessimism subscales had
54
average Cronbach’s alphas of .74 (Norem, 2001). Test-retest also proved to be strong over 3
years. For general purposes, it appeared that the revised Defensive Pessimism Questionnaire
(DPQ) by Norem best served the purposes concerning a study of CCW on campus. As
Norem pointed out, the DPQ was not limited to an academic model.
Utilizing defensive pessimism (in theory) satisfied an individual’s need to manage
anxiety. Table 2 offers the statistical differences established by Norem (2001) in the initial
academic and the revised versions of the scale used in a coed sample. Of the revised scale,
Norem wrote, “The DPQ does not appear, however, to be correlated with measures of more
general motivations such as need for cognition or need for structure” (p. 86). Accordingly,
the revised scale better served a study involving CCW on campus. As Norem suggested, the
DPQ “is intended for use as a domain–specific measure of strategies, and the specific
wording of the items should reflect the domain under study” (p. 86). As of 2001, the scale
proved useful in researching social, recreational/sports, and health defensive pessimism
(Norem, 2001). Additionally, defensive pessimism could be utilized in the academic realm
as seen in Cardell et al.’s (n.d.) and Norem’s original academic scales. However, when
comparing the scales, only a “small-to-moderate correlation between the social and academic
versions of the scale” (Norem, 2001, p. 86) was found. She added, “The Social DPQ,
worded so that ratings are given for social situations, taps into a broader domain [emphasis
added] than the academic version, which presumably refers to a more restricted goal domain”
(p. 86).
55
Table 2
Divergent and Convergent Correlates of the Defensive Pessimism Questionnaire (DPQ)
Academic Version Social Version
NEO-FFI Extraversion -.29 -.36
NEO-FFI Neuroticism .22 .27
NEO-FFI Conscientiousness .23 .11
NEO-FFI Agreeableness -.24 -.20
NEO-FFI Openness .05 .04
Need for Cognition (n Cog) .13 .09
Need for Structure (n Struct) .15 .32
Fear of Negative Evaluation (FNE) .22 .36
Beck Depression Inventory (BDI) .18 .22
Self-Handicapping scale (SHS) .27 .49
Repression-Sensitizing (R-S) (high score = sensitizing) .26 .29
Optimism (LOT) -.23 .30
DPQ Social version -.38 n/a
Note. Norem, 2001, p. 85
Similarly, referring to how the process worked, Norem (2001) wrote that defensive
pessimism served to harness anxiety and use it positively instead of succumbing to its
negative and potentially debilitating effects. However, in academic and social (the revised
scale) scenarios, some researchers suggested that defensive pessimists might lack the drive
that was so vital to Norem’s theory.
Karademas, Kafetsios, and Sideridis (2007) indicated that optimism could reflect “a
more benign assessment of the environment rather than of the personal capabilities” (pp. 285-
286). In other words, optimism can lead to a milder view of reality. They also stated that
there was a positive association between optimism and self-efficacy. In addition, the authors
pointed out that optimism and self-efficacy were found to be “inversely associated with
56
depression and anxiety” (p. 286). Karademas et al. also found that optimists exhibited more
positive perceptions about their own well-being and the environment around them. The
authors also indicated that such outcomes were the result of individual “cognitive structures”
(p. 286). In other words, Karademas et al. indicated that individuals biased their perceptions
because of these schemas. Karademas et al. additionally indicated that the duo of selfefficacy
and optimism kept such schemas “easily accessible” (p. 287). A positive bias was
the result. This was obviously not what was occurring based upon Norem’s (2001) definition
of defensive pessimism.
Karademas et al. (2007) studied the relationship between optimism and self-efficacy
and what the authors called “well-being stimuli” and “threat stimuli” (p. 287). Results
showed that individuals who ranked high in self-efficacy and optimism showed a propensity
toward well-being and not toward neutral or threat-related stimuli. Similarly, the authors
found that test participants with low optimism responded more positively to threat related
stimuli. However, high and low optimism participants did not show great differences.
According to Karedemas et al. (2007), “Perceived stress is negatively predicted by
optimism, which is positively predicted by [the study’s] well-being colour-naming [sic]
latencies as well as by self-efficacy, which is negatively predicted by threat-related latencies”
(pp. 289-290). Further, the authors cited Bandura (1997), Carver et al. (2005), Giltay et al.
(2004), and Luszcyzynska et al. (2005) in establishing that optimism and general selfefficacy
are “strongly associated with well-being and adaption” (p. 291). The study by the
authors bore this out. Individuals who were rated high in optimism or self-efficacy presented
a predisposition toward “well-being related stimuli” (p. 291). Alternately, Karedemas et al.
57
found that individuals with low self-efficacy showed greater biases toward personal threat
and general threat related stimuli.
Similarly, Karedemas et al. (2007) reported that pessimists showed a tendency toward
negative stimuli based upon informational biases. Karedemas et al. also found that
moderately optimistic individuals showed an equal propensity toward both positive and
negative biases. Strong optimists and those strong in self-efficacy showed a sound
connection with positive biases. However, individuals low in only the optimism category did
not show the expected opposite results. Those low in self-efficacy did show such biases.
According to the researchers, low self-efficacy showed “greater interference for threatrelated
stimuli” (p. 291). In short, the authors found that individuals high in optimism and
self-efficacy were more prone to align with “well-being and control information” (p. 291)
while individuals reflecting low self-efficacy were more prone to “threat related” stimuli (p.
291). Karademas et al. indicated that such findings were consistent with those found by
Erblich et al. (2003), MacLeod (1991), and Williams et al. (1996). Informational biases can
impact an individual’s behavioral/emotional responses. Karademas et al. reported that these
reactions played a key role in producing and sustaining an individual’s emotions. Similarly,
the authors indicated, as addressed above, that they also assisted in the formation of
“decisions and actions” (p. 292). This indicated, according the authors, those high in
optimism and self-efficacy had a more positive view of themselves and the world around
them. This being said, the authors wrote that such individuals “focus more on the positive
aspects of stressful situations” (p. 292). This was the exact opposite of what was happening
in defensive pessimism as discussed by Norem (2001). In other words, Karademas et al.
indicated these predispositions promoted positive interpretations and a more stable sense of
58
well-being. Additionally, the authors also indicated that such a process actually weakened
the impact of negative information when it was offered. However, and as stated above, this
is not the fact when low self-efficacy entered the equation.
According to Karademas et al. (2007), individuals with low self-efficacy proved to be
more preoccupied with “threat-related stimuli” (p. 292). The authors wrote that for such
individuals “after the identification of a threat, an elaborative processing of threat-relate
material is activated and almost all informational resources are allocated towards those
stimuli” (p. 292). Buckley et al. (2000), Kindt and Brosschot (1997), and Williams et al.
(1996) found similar results according to Kardemas et al. (2007). The authors went on to
point out that once this occurred in such an individual’s life, the individuals found it difficult
to separate their fearful view of their surroundings. Therefore, such individuals saw an
increase in stress due to this inability to overcome their fears. Karademas et al. indicated that
“this process may assist the employment and perpetuation of maladaptive behaviors” (p.
292). This was an extremely important finding as far as this study was concerned because
this is the opposite of what happens in defensive pessimism. As Norem (2001) pointed out,
defense pessimism allowed individuals to address certain situations, to vigorously think
about and plan a course of action that would alleviate the “maladaptive behaviors” (p. 292)
the previous authors discussed. This stood in contrast to the concept presented by
Karademas et al. They indicated that individuals low on self-efficacy tended to focus more
on threat-related stimuli with “greater interference” than others high in optimism and selfefficacy.
The authors argued that such individuals were not as capable of dealing with
threats as their more positive counterparts. They underscored their argument with Bandura’s
(1977; as cited by Kardemas et al., 2007) definition of self-efficacy: “the evaluation of
59
personal capabilities in the face of a problem” (p. 292). In other words, Karademas et al.
posited that optimists were much more able to deal with negative or threatening stimuli
because they simply did not utilize as much of the brain’s information processing resources,
whereas those low in self-efficacy utilized too much of the brain’s information processing
resources. Norem may not have necessarily disagreed with this finding. Yes, some people
focused more on the negative, but this additional focusing and planning proved beneficial to
those who utilize the defensive pessimism cognitive processing. In fact, as Karademas et al.
indicated in citing A.T. Beck (1993) and J.S. Beck (1995) that optimistic assessment and
self-efficacy opinions can be modified. This, as the authors pointed out, can allow the
individual to shift toward positive expectations. This was similar to the theory of defensive
pessimism as processed by Norem.
Still, the bias toward optimism was the most common cognitive disposition according
to Sharot (2011). It was present in 80% of the population according to the author. In fact,
according to Sharot the optimism bias “is one of the most consistent, prevalent, and robust
biases documented in psychology” (p. R941). Such a bias seems to be hard wired.
According to the author, optimists are unwilling to change, and they are unwilling to change
because frontal lobe areas of the brain do not “code errors” (p. R943) that would change their
positive beliefs. This was a process that involved the amygdala and the rostral anterior
cingulated (rACC) according to Sharot (2011). However, there was an exception. That
exception, according to the authors, was found in individuals who suffered from depression.
This was particularly true of Major Depressive Disorder (MDD).
According to Sharot (2011), in individuals with depression, the amygdala and rACC
“show abnormal function and impaired connectivity” (p. R944). This could be one
60
explanation as to why certain individuals do not construct future positive schemas. However,
Sharot, who also cited Seligman (2006), suggested that the lack of positive schemas could
also be attributed to an environment that has not produced positive outcomes for the
individual in question. Such an environment, according to the author, led to a depressed state
in animal studies. In fact, Sharot indicated it was such a lack of pessimism that allowed
humans to evolve without extinction. Based upon Norem’s (2001) definition of defensive
pessimism, the opposite could very well be argued.
A Divergent View of Defensive Pessimism
Norem (2001) pointed out that in a 3-year longitudinal study students deemed
defensive pessimists had more psychological and physical symptoms, as well as lower
grades, than did their optimistic counterparts. However, the worst outcomes occurred for
those individuals who used the strategy in academic and social settings. Additionally, selfesteem
issues correlated to a greater extent with the social defensive pessimism scale than
with the academic scale (Norem, 2001). Norem wrote, “It may also be that social anxiety is
more generally debilitating than anxiety about academic performance” (p. 92). Of
importance to the proposed study, Norem also stated that defensive pessimism might be less
effective for some in social situations because of the subjectivity of goals. However, as
already stated, there was an exception. When the goal was important and the means for
attaining the goal could be planned, the previous did not hold true and the social side of
defensive pessimism engaged.
Kiehl (1995, as cited by Norem, 2001) offered a prime example while researching
AIDS-related activities. The author found that defensive pessimists considered certain
behaviors far riskier than optimists. In another study, when a fictitious new disease was
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discussed in front of test subjects, the defensive pessimists were more interested in getting
additional information on the disease mentioned than were optimists (Norem, 2001). This
was in line with Norem’s findings that people have varied goals and can be hypothesized to
be true of certain individuals’ views of CCW on campus. To further substantiate this line of
inquiry, Norem (2008) provided an example of how defensive pessimism works. She stated
that strategies reflected how an individual responds to ongoing events in life so that those
events proceeded in a manner that ensured the individual’s goals were met. Norem used an
example of driving to illustrate her point. A nervous driver wanted to be safe. In order to be
as safe as possible, the driver wanted no distractions. The radio was turned off. The driver
took a moment to prepare. He or she asked the passengers to stay very quiet so that all focus
could be on the road ahead. From the provided example, it became clear that individual
situations influenced peoples’ strategies as those situations impacted relevant goals and
obstacles. Application of the same approach helped determine why individuals would
support CCW on campus just as some were more interested in a fictitious disease than others.
Similarly, results of the work by Del Valle and Mateos (2008) showed that negative
feelings, or mood, directly affected the defensive pessimist. This established the importance
of fear for the purposes of this study. As Gasper et al. (2009) concluded that if safety or any
other variable was not a goal of defensive pessimists, then it was of no concern to them.
Similarly, if they did not have something that caused anxiety, or even fear, there was also no
concern. To this end, whether or not the individual participants had a concern about weapons
on campus needs to be determined. For the purposes of this research, the fear questionnaire
by Marks and Mathews (as cited in Antony et al., (2001) was utilized. This was a scale in
which support for concealed carry would also be presented.
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The Role of Fear
The fear questionnaire consisted of three sub-scales that addressed agoraphobia, social
phobia, and blood/injury phobia (Gillis, Hagga, & Ford, 1995). Gillis et al. claimed that the
scale was free of social desirability response bias. Further, in addressing the fear
questionnaire, the authors underscored the belief that the device did not reflect differences
when it came to sex, race, or income. However, age did affect the outcome of the fear
questionnaire (Gillis et al., 1995). Participants up to the age of 44 scored significantly higher
than their older counterparts (accommodations for this factor were included in the design of
this study). The median score for the younger group in an overall sample of 242 was 11.4
out of a total score of 28.6 (Gillis et al., 1995). For participants over 45, the median score
was 9.3 (Gillis et al., 1995). These results helped reinforce the idea that fear was a strong
variable in dealing with young people who might have concerns about their safety on college
campuses.
Higgins (2004) reported that the tendency to develop certain fears was consistent
across cultures. In a study of the fears of young Chinese and British women, a concrete list
of fears and opened-ended questions about fears elicited reactions from participants
concerning archetypal and conditional fears. The finding of the Higgins study that applied to
this CCW study was that open-ended questions showed cross-cultural similarities; whereas,
the concrete list showed cultural differences. For example, Chinese women reported much
higher fear of caterpillars than did the Western women (Higgins, 2004). However, with
regard to open-ended fears (fears not specifically presented in the list), death and injury were
very common concerns. Additionally, fear of the unknown was almost as common when
63
tabulating open-ended fears (Higgins, 2004). Again, this had a bearing on the question of
CCW on campus as it related to common fears of death and injury.
Based upon high fear questionnaire scores, individuals tended to take a defensive
stance that oriented them away from the perceived threat (Perkins, Cooper, Abdelall, Smillie,
& Corr, 2010). Additionally, individuals who were fear-prone also tended to see threats as
being greater than they were in reality. Using an example in which an individual would
suddenly encounter a ferocious dog, the authors indicated that most people initially
experienced fear. This fear would then be followed by avoidance. In a scenario in which an
individual who could control his or her fear suddenly encountered a ferocious dog about to
attack a small child, fear and anxiety would still be present; however, in this instance, if a
sense of responsibility were present, the individual would utilize the fear and anxiety not to
flee but to move to protect the child. Interestingly, if the threat was seen as being distant
(i.e., not immediate), individuals generally would engage in higher prefrontal cortex activity.
In such situations, they planned and thought about things that would benefit them the most in
possibly threatening scenarios (Perkins et al., 2010). To test this concept, Perkins et al.
reported that the fear questionnaire scores “were positively correlated with a tendency to
select scenario responses that entail orientation away from threat (such as ‘run away’)” (p.
1073). However, trait anxiety questionnaire scores did not reflect the same results. In a
study to replicate the original findings of Perkins and Corr (2006), Perkins et al. found that
their results showed that “fear scores, but not trait anxiety scores, were significantly (p <.01)
and positively correlated with the tendency to orient away from threat, a clear replication of
the same finding by Perkins and Corr” (Perkins et al., 2010, p. 1077). Interestingly,
individuals high on psychoticism tended to move toward threats (Perkins et al., 2010).
64
Similarly, Frombach, Asmundson, and Cox (1999) reported that the Marks and Mathews
Fear Questionnaire was a much better tool for measuring fear than any “unidimensional, twofactor,
hierarchical three-factor, or categorical three-factor models” (p. 117). This was
determined to affect answers to the question of whether the fear felt by defensive pessimists
might contribute to their support of CCW on campus. The Marks and Mathews fear
questionnaire was, therefore, an excellent tool for gauging such support.
Responsibility as a Factor
Gasper, Lozinski, and LeBeau (2009) discussed defensive pessimism in terms of goal
importance. If the goal was not of adequate value to an individual, the defensive pessimism
strategy remained dormant. For the purposes of the this research, the question of individual
responsibility also came to bear on the question of whether or not defensive pessimism might
play a role in affirming the acceptance of CCW on campus. The intentions of individuals in
the ferocious dog example presented above supported this idea. A sense of responsibility
must engage.
According to Mancini (2001), responsibility played a key role in how an individual
perceived his or her environment. For example, general threat appraisals were one area in
which level of responsibility could have an effect. One tool that was quite useful in
measuring responsibility was the Responsibility Attitude Scale (RAS). Even though the RAS
was a tool often associated with the study of obsessive behaviors, the RAS has proven to be
quite useful in non-clinical subjects (Mancini, 2001). In fact, the elements offered by the
RAS were more indicative of true views of individual responsibility than obsessivecompulsive
issues (Mancini, 2001). The RAS revealed more of an individual’s true tendency
to assume responsibility in certain areas or situations (Mancini, 2001). This was especially
65
true in areas where the individual subject had doubts or fears of possible intrusions. The 26-
item RAS questionnaire was designed to assess general beliefs about responsibility (Mancini,
2001).
The RAS correlated well with the Revised Defensive Pessimism Questionnaire crafted
by Norem (2002). As Mancini (2001) noted, there was a significant correlation between an
individual’s feelings of responsibility and the individual’s anxiety. High anxiety scores on
tests correlated positively with high responsibility scores (Mancini, 2001). In addition, the
RAS showed a very strong correlation to a factor Mancini called prevention. Prevention
translated into a desire to prevent harm from coming to the subject and others. In fact,
Mancini found this to be true of subjects who doubted their own abilities in questionable
situations. This indicated a potentially strong correlation between defensive pessimism and
responsibility in terms of the proposed query concerning CCW on campus.
Snorrason, Sma´ri, and O’lafsson (2011) investigated the potential connection between
obsessive–compulsive symptoms and impulsivity. Additionally, a connection between
responsibility and impulsiveness in connection with obsessive–compulsive symptoms was
examined (Snorrason et al., 2011). This was accomplished by studying 205 university and
college students. Once again, participants were non-clinical individuals.
The RAS was one of the tools utilized in the Snorrason et al. (2011) study. Using the
RAS, they probed the link between high responsibility and obsessive-compulsive thoughts.
Citing Sma´ri et al. (2003) and Salkovskis et al. (2000), the authors found a close association
between obsessive–compulsive symptoms and responsibility attitudes in clinical subjects and
in university students. Additionally, they attempted to determine if there was a correlation
between responsibility and impulsivity (Snorrason et al., 2011).
66
Using an Icelandic college and university student study sample, Snorrason et al.
(2011) reaffirmed what others had previously found. There was an interaction between
responsibility and impulsivity. Together, these greatly added to the possibility of obsessivecompulsive
symptoms. This accounted for attentional impulsiveness, defined by Patton,
Stanford, and Barratt (1995) as racing or intrusive thoughts, which, in turn, could be linked to
irrational thinking that helped explain, for the purposes of this study, why an individual
might be willing to accept CCW on campus (Patton et al., 1995; Snorrason et al., 2011).
However, there were some differences between clinical and nonclinical study groups that
warrant recognition.
Snorrason et al. (2011) found marked differences between non-clinical control groups
and those with OCD symptoms. The authors reported that attentional impulsiveness was
much higher in those assessed as having OCD symptoms when compared to the control
group. Summerfeldt (2004) found similar outcomes. However, as Snorrason et al. remarked,
and in accordance with the findings of Summerfeldt, those with OCD symptoms did score
higher in the cognitive/attentional subscale (irrational thinking) than did the normal control
group; they did not score higher than those with anxiety issues. Therefore, impulsivity does
not have a unique relationship to issues of OCD (Snorrason 2011). This might vary simply
as a function of (a) how an individual thought, (b) the individual’s level of anxiety, and (c)
the decision-making that resulted from this process. This provided a link to anxiety and
CCW on campus.
Similarly, Mather and Cartwright-Hatton (2004), in a study of adolescents that
examined the same correlations Snorrason et al. (2011) studied above, also found a
connection between responsibility appraisals and the way individuals thought. The authors
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directly quoted Salkovskis (1985), who stated that understanding OCD in this population lay
less in understanding intrusive thoughts and more in understanding how these thoughts were
appraised or interpreted. This said, anxiety, as a component of defensive pessimism, and
responsibility played a role in the proposed research. These factors also played a role in
defensive pessimism, but this research was offered in exclusion of issues, such as OCD, that
were addressed by these authors. However, the link between anxiety (in terms of defensive
pessimism), fear, responsibility, and the decision to support or deny CCW on campus was
clearer based upon presented evidence.
Mather and Cartwright-Hatton (2004) criticized Salkovski’s (1985) work because of
the failure to address the role of what was called “general metacognitive beliefs” (p. 743).
This exclusion was extremely important because the addressed beliefs “concern the meaning
of thoughts themselves and beliefs about the danger, or power of thoughts and consequences
of emotion or discomfort” (Mather & Cartwright-Hatton, 2004, pp. 743-744). This appeared
to have a direct bearing on anxiety as a component of defensive pessimism, fear, and
responsibility.
Additionally, Mather and Cartwright-Hatton (2004) cited Rachman (1993), who
introduced a concept called thought-action fusion. Rachman believed that both thoughts and
beliefs could merge to violate potentially intrusive thoughts in the case of those with OCD
symptoms. One example was someone with OCD who kept having the intrusive thought that
he was going to hurt his children. The individual wanted the children to be safe, so he kept
checking on them constantly to make sure the action had not occurred. Mather and
Cartwright-Hatton reported that the appraisal of the thought brought about a behavioral
reaction. This was very similar to what could be happening in a defensive pessimism view of
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CCW on campus. Having weapons available might belay an individual’s obsessive thoughts
about personal safety.
Mather and Cartwright-Hatton (2004) utilized the RAS as a key component of their
study. They chose the tool because of the ability to use the 26-item questionnaire to measure
general responsibility beliefs and because of its strong psychometric properties. The RAS’s
readability was key as it was easily read by 13-year-olds. Additionally, the RAS was highly
reliable for use on younger subjects.
Summary
Fear, responsibility, and defensive pessimism served as the predictor variables as
measured against the criterion variable of support for CCW on campus. This was a simple
“yes or no” questionnaire measured against the predictor variables. A comparison
determined whether the pro-CCW individuals and those concerned about safety on campus
showed higher defensive pessimism scores when compared to those opposed to CCW on
campus that were not necessarily as concerned about campus safety. Comparing these scores
to the data garnered from the FQ and the RAS allowed the determination of whether there
might be a correlation between fear, responsibility, defensive pessimism, and support for
CCW on campus.
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CHAPTER III: METHODS
This chapter serves to describe the method utilized to examine the relationship
between support of CCW on campus, defensive pessimism, fear, and responsibility. Levels
of defensive pessimism, fear, and responsibility were weighed against the acceptance or
denial of CCW on campus. These were assessed in terms of the proposed hypothesis (H1)
that elevated levels of defensive pessimism, fear, and responsibility were significant
predictors of the probability that a participant would support CCW on campus. This stood in
direct contrast to the null hypothesis (H0) in which defensive pessimism, fear, and
responsibility were not significant predictors of the probability that a participant supported
CCW on campus. To achieve this end, the quantitative research methodology was applied.
Specifically, a linear regression and correlation analysis was performed. The research
question that guided this study was “What are the relationships between the participants’
support for CCW on campus, and their levels of defensive pessimism, fear, and
responsibility?” This translated into a research hypothesis (H1) in which defensive
pessimism, fear, and responsibility were significant predictors of the probability that a
participant would support CCW on campus (relative to not supporting CCW on campus).
The null hypothesis (H0) would indicate the opposite. Defensive pessimism, fear, and
responsibility were not significant predictors of the probability that a participant would
support CCW on campus (relative to not supporting CCW on campus.) Each hypothesis, H1
and H0, was addressed in terms of the criterion variable, support for CCW, and its
relationship with each of the predictor variables: defensive pessimism, fear, and
responsibility. To this end, the participants were recruited from students at a small Liberal
Arts college within an hour’s drive of the scene of the nation’s deadliest campus shooting,
Virginia Polytechnic Institute and State University (Virginia Tech).
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Methodology
As Agresti and Finlay (2009) pointed out, linear regression and correlation allow
researchers to test the association between variables through (a) statistical association, (b) the
strength of a potential association by using the correlation association, and, finally (c) by
using a regression equation to predict explanatory variables. The Model was based upon the
following equation:
E(y) = α + βx with a prediction equation of ŷ = a + bx
Where: y would denote the response as to the support or denial of CCW on campus and x
would represent an explanatory variable. As a linear function, y was viewed as a function of
x with a straight-line graph in which beta was represented by slope β and the alpha by the y
intercept. In such a model, as Agresti and Finlay (2009) pointed out, if β was positive then y
would increase as x increased. Conversely, if β was negative then y would decrease as x
increased.
The linear regression and correlation model was chosen because it, according to
Agresti and Finlay (2009), “approximates the true relationship” (p. 288) between the
variables that make up the study in question. Additionally, as the authors pointed out, the
linear regression and correlation model “is adequate for describing the relationship and
making predictions but that is still simple enough to interpret easily” (p. 288). As the goal of
this research involved establishing possible correlations between support or denial of CCWs
on campus and three independent predictor variables, the linear regression and correlation
model was seen as ideal. Additionally, as the authors pointed out, as future research evolves
and becomes more complex, more complicated models can be utilized by building upon the
findings offered by a linear regression and correlation model. Until that time, as Agresti and
71
Finlay addressed, since two variables at a time were addressed (position on CCW on campus
and one of three predictor variables), the linear regression and correlation model was
sufficient.
Procedure
The research (H1) hypothesis and null (H0) hypothesis were as follows:
H1: defensive pessimism, fear, and responsibility were significant predictors of the
probability that a participant would support CCW on campus (relative to not supporting
CCW on campus).
H0: defensive pessimism, fear, and responsibility were not significant predictors of
the probability that a participant would support CCW on campus (relative to not supporting
CCW on campus).
Before a correlational design could be successfully implemented, it was imperative to
explicitly define the criterion and predictor variables, and to explain how the variables were
operationalized. This information was essential to justify the use of appropriate methods of
statistical analysis. Furthermore, the measurement levels of the variables (nominal, ordinal,
or scale) were entered into the SPSS data editor (Field, 2009).
Accordingly, the conceptual, functional, and operational definitions of the variables
collected by the instruments administered in this study are outlined in Table 3.
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Table 3
Criterion and Predictor Variables
Variable Conceptual definition Functional definition Operational definition
Support for
CCW on
Campus
Whether or not a participant
supports or opposes CCW on
campus
One criterion
variable, classified
into two nominal
categories
Yes = 1 or No = 0, measured with a simple
poll
Defensive
Pessimism
A coping strategy employed
by a participant to prepare for
any event perceived as
stressful, by which negative
thinking transforms anxiety
into action (Norem, 2002)
One predictor
variables, measured
at the scale level
Measured with 17 items in the Revised
Defensive Pessimism Questionnaire
(Appendix 3). Each item is measured on a 7-
point scale (1, not at all true of me; to 7, very
true of me). Higher scores indicate higher
levels of defensive pessimism. Scores will be
divided into three categories: 22 – 41 will be
considered Strategic Optimists; 42 – 61 will
be viewed as bi-strategists; scores ranging
from 62 – 79 will be considered Defensive
Pessimists. The numeral 1 will represent
Strategic Optimists, 2 will represent bistrategists,
and 3 will represent Defensive
Pessimists.
Fear The extent to which a
participant has feelings of
agoraphobia, social phobia and
blood/injury phobia (Antony et
al. 2001)
One predictor
variable, measured at
the scale level
Measured with 17 items in the Fear
Questionnaire (Appendix 4). Each item is
measured on a 7-point scale (1,would not
avoid it; to 8, markedly avoid it). Fear is
operationalized as the sum of the scores for
the three sub-scales (Agoraphobia + Social
Phobia + Blood/Injury Phobia). These scales
are represented by questions 2 – 16 (FQ16).
Question 17 (FQ17) is a specific issue fear
(guns) and is of main interest to this study.
The global phobic distress index (an
anxiety/depression scale) is not utilized for the
purposes of this study.
Responsibility A participant’s tendency to
assume responsibility in
certain areas and situations.
Identifies individuals with
OCD (Antony et al. 2001 ).
One predictor
variable, measured at
the scale level
Measured with 26 items in the Responsibility
Attitude Scale (Appendix 5). Each item is
scored on a 7-point scale (1, totally agree; to
7, totally disagree). Averaging the scores for
the 26 items operationalizes the
Responsibility Attitude Scale. Lower scores
represent higher levels of responsibility.
The single criterion (response) variable, named Support for CCW on Campus, had
only two categories, measured with nominal numerical value labels, in a binary format
(Yes = 1 or No = 0). Support for CCW on Campus was assumed to be a hypothetical
73
attitudinal response of the participants to three predictor variables, specifically (a) defensive
pessimism; (b) fear, divided into two categories (FQ16 and FQ17); and (c) responsibility.
The predictor named defensive pessimism was measured on a scale from 1 to 7. The
variables were added to produce a final unidimensional defensive pessimism score. The
predictor named fear was a three-dimensional variable, though only two were utilized for this
study, based on the scores for 17 items, measured on a scale from 1 to 8. Fear was then
operationalized as the sum of items 2016 (a total phobia scale) offering a unidimensional
variable named FQ16 by the researcher. Additionally, item 17 on the fear questionnaire, a
specific statement oriented toward CCW, produced a unidimensional value named FQ17 by
the researcher. The predictor variable named responsibility was a unidimensional variable,
with each item measured on a scale from 1 to 8. Averaging the scores for 26 items
operationalized responsibility. The variables, with their ordinal or nominal value labels, used
to categorize the demographic characteristics the participants are outlined in Table 4.
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Table 4
Demographic Variables (these variables were gathered for future use and do not apply to the
outcome of this study)
Characteristic Level Categories and Value Labels
Age (Years) Ordinal < 20 = 1
21-24 = 2
25-30 = 3
31-34 = 4
35-40 = 5
> 40 = 6
Gender Nominal Female = 0
Male = 1
Level of Education Ordinal Freshman = 1
Sophomore = 2
Junior = 3
Senior = 4
Race African-American = 1
Asian-American = 2
Hispanic = 3
Native-American = 4
Pacific Islander = 5
White = 6
Other = 7
In short, would positive support of CCW on campus reflect elevated levels of
defensive pessimism, fear, and responsibility as the proposed hypothesis argued, or would
the null hypothesis, that positive support for CCW on campus would not reflect in elevated
levels of defensive pessimism, fear, and responsibility, stand?
Norem (2001) reported that the 2001 version of the Defensive Pessimism
Questionnaire measured the “thinking through” (p. 82) process that is defensive pessimism.
The revised scale correlated at r = .65 with even higher reliability (Cronbach’s alpha = .78).
The reflectivity and pessimism subscales averaged Cronbach’s alphas of .74. Test-retest
reliability also proved to be strong over 3 years (Norem, 2001).
The Defensive Pessimism Questionnaire proposed that the individual taking the
measurement think of a situation related to the study topic. In this case, personal safety was
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the subject that framed the measure’s questions. The study participants assigned a numeric
response to each statement. The number 1 represented a scenario that was “not at all true of
me.” The number 7 represented a scenario that was “very true of me.” The numbers
between 1 and 7 represented the spectrum between the two extremes. These scores were then
added for a final score on the RDPQ. Seventeen statements were prepared and presented to
participants (See Appendix C).
Marks and Mathews created the Fear Questionnaire (FQ) in 1979 (as cited in Antony
et al., 2001). The Fear Questionnaire consisted of three sub-scales that addressed
agoraphobia, social phobia, and blood/injury phobia (Gillis et al., 1995). The scale was
reportedly free of social desirability response bias. Further, the FQ did not reflect differences
when it came to sex, race, or income. Murisa et al. (2000) reported that the FQ was a very
widely utilized tool with three or five subscales. In the three-subscale version, called the
Total Phobia Scale, there were 15 questions designed to measure three sub-scales. This scale
was utilized for this study. The 15-question version had strong internal consistency with
Cronbach’s alphas of 0.81 for the total phobia score, 0.71 for the agoraphobia, 0.73 for the
blood-injury phobia, and 0.66 for the social phobia (Murisa et al., 2000). The 5-item
subscale also contained a global phobic distress subscale and an anxiety/depression subscale.
Both versions of the scale were well validated (Antony et al., 2001).
The FQ took fewer than 10 minutes to administer (Antony et al., 2001). The test
design reportedly had adequate to good internal consistency. Citing Oei, Moylan, and Evans
(1991), Antony et al. reported internal consistencies of .71 to .83 for the three subscales.
Antony et al. also reported a good short term and longer-term test retest reliability. Oneweek
test-retest values ranged from .82 to .96, whereas the 3-week test-retest reliability
76
ranged from .84 to .90. Validity was also reported to be strong. Antony et al., citing
Davidson (1991), reported that correlations between the social phobia scales and other
measures of social anxiety are high, ranging from .59 to .83. This was important to this study
as social fears could contribute to the support of CCW on campus. The FQ17 portion of the
Fear Questionnaire (based solely upon question 17) showed a more marked difference to be
discussed in the next chapter.
Salkovskis et al. (2000; as cited in Antony et al., 2001) created the Responsibility
Attitude Scale (RAS) in 2000. Although the scale typically measured the parameters of
obsessive-compulsive individuals, as established above, the scale successfully analyzed
responsibility when utilized with normal populations. The results offered by the RAS were
more indicative of true views of individual responsibility than obsessive-compulsive issues
(Mancini, 2001).
According to Antony et al. (2001), the RAS was a 26-item scale designed to “assess
general attitudes, assumptions, and beliefs” (p. 230) concerning responsibility. Responses to
statements ranged from 1 to 7. One was equivalent to totally agreeing while seven was
equivalent to totally disagreeing. According to the authors, the RAS final score was the
mean score of all 26 questions. Antony et al. reported that validation studies show strong
consistency. Mean scores were 4.69 for subjects diagnosed with OCD. Mean scores for
subjects with other disorders were 4.00 (Antony et al., 2001). The same sources reported that
in a non-clinical control study the mean score was 3.48.
Reliability and validity studies indicated similar results. Internal consistency was
deemed excellent according to Antony et al. (2001). Antony et al. reported that the RAS had
a Cronbach’s alpha of .92. Test-retest was also reported to be high (r = .94). Participants
77
with OCD scored significantly higher than participants with other anxiety disorders and the
controls. Interestingly, Antony et al. reported that the RAS was a strong predictor of
obsessionality; however, this was not true of depression and anxiety. This could play a vital
role when safety could be an obsessive issue.
The criterion variable was presented within the Demographic Questionnaire. A
simple poll requiring a Yes or No answer served to determine individual support for the
presence of CCW on campus, and whether the individual was concerned about safety on
campus. In addition, the participant was asked to answer a few demographic questions
including age, gender, level of education, and race (see Appendix B).
While the purpose of the pilot study was not to gauge the participants according to
measured responses, it served to highlight potential problems in understanding the outcome
measures later. To this end, the pilot study served as a valuable tool.
Population and Sample
The target population for this study was students from a small liberal arts college
within a one-hour drive of Virginia Tech’s Blacksburg campus. Evaluation of students was
undertaken during the spring semester of 2013. The school had approximately 400 on
campus students, but it was impossible to survey all of them.
Participants were recruited to provide sufficient power to conduct linear regression
and correlation analysis. If the sample size were too low, then a Type II error would occur
(i.e., the null hypothesis is not rejected when, in fact, the data are consistent with the
rejection of the null hypothesis). In this study, there were three predictor variables in the
linear regression and correlation model; therefore, the minimum number of participating
students should have been about 120 to 160. Power analysis was performed using G*Power
78
3.1.2 software (Faul, Erdfelder, Lang, & Buchner, 2007). The input parameters were the
expected probability of the criterion variable = .5; the expected odds ratio = 1.5, the
significance level for rejecting the null hypothesis, α = .05, and the power to reject the null
hypothesis, 1 – β = 0.8. The computed minimum sample size was N = 163. One hundred
sixty-nine participants were utilized in the final study.
Ethical Concerns
Ethical concerns were monitored at all times. Ethical training dealing with human
subjects was required by the researcher’s university. Proof of this training was required
before research could begin. Additionally, each participant and organization involved was
informed that participation was wholly voluntary and said participation could be revoked at
any time by request of the participant. This occurred when the researcher visited the
classrooms in question. A full explanation of the study was offered. The instruments were
handed out and fully discussed. Any questions were addressed. The informed consent (see
Appendix A) was then handed out, discussed, and signatures were acquired. Participants
were guaranteed protection of their information in two ways. First, the measures completed
had no identifying marks. Secondly, the measures would remain in a locked, secure, or
otherwise safe state.
Pilot Study
As previously mentioned, a pilot study was carried out with 20 students participating.
The pilot study group was comprised of 11 males and 9 females. Eighteen of the students
ranged in age from 17 to 24 years of age. Two were males aged 42 and 44. Eleven of the
students were sophomores, and nine were freshmen.
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Data Collection
The researcher was able to visit random classrooms at a small liberal arts college in
Virginia as a means of gaining convenient access to students. Students were approached
with college permission. The study was explained to each class as a group. Information
within the consent form was discussed (see Appendix A), and each measure was addressed.
Requests were made that the students take the measures seriously. They were also asked not
to communicate with each other during the process. The researcher was available for
specific questions if needed by the raising of hands.
Students were simply told that research was being conducted to determine a
correlation between support/opposition for CCW on campus, defensive pessimism as a
coping strategy, fear, and responsibility. The researcher told students that approximately 20
minutes were required to complete the study’s measures; however, they were also told that
they were to read carefully and to take their time. They were informed that time was not an
issue as truthful rather than quick responses were desired. As mentioned previously, the
measures utilized were the Defensive Pessimism Questionnaire (see Appendix C), the Fear
Questionnaire (see Appendix D), and the Responsibility Attitude Scale (see Appendix E).
Each participant was handed a prepared packet that included a review of the proposed
project, a consent form to be signed, and assurances of privacy explaining how the materials
would only be available to the researcher before being locked away upon research
completion. Upon accepting the conditions of research as outlined in the informed consent,
the participants were also asked to answer a few demographic questions including age,
gender, level of education, and race. This page also included a poll that required Yes or No
answers regarding whether the participating individual supported the presence of CCW on
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campus and whether he or she was concerned about safety on campus. The DPQ, the FQ,
and the RAS followed. The packet was comprised of these materials only. Students were
given a copy of the consent form for their own personal use.
Completed materials were maintained on site in a closed container (a pilot’s case)
with a combination lock, and the container was under the constant surveillance of the
researcher. After returning from the research site, materials were kept in a locked filing
cabinet in this researcher’s home office. The materials were not and will not be accessible to
anyone with the exception of this researcher. Once the research was conducted, materials
were kept safe in a locked environment where they will be held for 7 calendar years. After
this 7-year period, all data (surveys, discs, etc.) will be destroyed via shredding.
The majority of the research went very smoothly. Two separate incidents occurred in
which participants wanted to argue an “it depends” attitude as far as the criterion variable
statement allowing CCW on campus was concerned. These students were asked to simply
explain their positions in writing on the measure. These two student responses, in their
entirety, were later removed from the final number as they did not answer “Yes” or “No” to
the measure in question. The request to have the students write their responses seemed to
work as no disruption was brought as a result of the questions.
Data Analysis
The criterion variable was dichotomous, representing only two possible outcomes,
coded by 1 (for the outcome that the researcher wants to predict) and 0 (for a reference
outcome). In the study, the researcher wanted to predict the likelihood that a participant
would support CCW on campus (relative to not supporting CCW on campus). Consequently,
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all of the participants who answered Yes in the poll were coded with 1, and all the
participants who answered No were coded with 0.
There were three potential predictors of the criterion variable, measured at the
scale/interval level, specifically (a) defensive pessimism; (b) fear; and (c) responsibility. The
variables were analyzed using a linear regression and correlation model. Because linear
regression offered a non-parametric method, the variables did not have to be normally
distributed, so testing for normality was not essential. It was, however, assumed that the
predictor variables were independent, meaning that they should not be very highly
intercorrelated with each other, otherwise the statistical inferences may be compromised
(Hosmer & Lemeshow, 2000). This assumption was checked by correlation analysis. If two
or more of the predictor variables were very strongly inter-correlated (indicated by a
correlation coefficient > .8), they were transformed by multiplication to create a composite
predictor variable.
If the three-predictor variables in this study were measured using different numerical
scales, they would be standardized so that their relative effects on the criterion variable could
be directly compared. The three variables would be standardized by conversion to z-scores
(i.e., subtracting the mean value from each score, and dividing by the standard deviation, so
that each predictor is measured with a standard scale, ranging from a minimum of about -3 to
a maximum of about +3, assuming that they are approximately normally distributed).
However, since each measure’s results were converted to a three-point scale, this was not
necessary.
A logistic regression model must not be fitted with too many or too few predictor
variables. Only meaningful predictors with β coefficients that are significantly different from
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zero should be included (Hosmer & Lemeshow, 2000). The three standardized variables
were tested for their statistical significance as predictors of the criterion variable using the
Wald χ
2 statistic. The β coefficient was significantly different from zero if p < .05 for the
Wald χ
2
statistic, justifying the retention of the predictor variable in the model. If p > .05 for
the Wald χ2
statistic, then the β coefficient was not significantly different from zero,
justifying the deletion of the predictor variable from the model.
The odds ratio (OR = e β
) was computed to represent the effect size attributed to each
predictor variable. The OR measured the relative effect that a standardized predictor variable
had on the criterion variable (Hosmer & Lemeshow, 2000). For example, in this study, if OR
= 2.0 for Pessimism and OR = 4.0 for Fear, then it could be inferred that Fear had a relatively
greater effect than Pessimism on the probability that a participant would support CCW on
campus. If the codes for the criterion variable were reversed, the reciprocals of the ORs were
obtained (e.g., if all the participants who answered Yes in the poll were coded with 1, and all
the participants who answered No are coded with 0, then each of the OR values would
become 1/OR). If the OR = 1.0, the predictor variable had no significant effect. If the OR >
1.0, an increase in the standardized score of the predictor variable increased the likelihood
that the participant supported CCW on campus. If the OR < 1.0 then an increase in the
standardized score of the predictor variable decreased the likelihood that the participants
supported CCW on campus. If the 95% confidence intervals for the OR did not include 1.0,
the OR was significantly different from 1.0 at p < .05. If the 95% confidence intervals for
the OR did include 1.0, the OR was not significantly different from 1.0.
The researcher expected that the outcome of the logistic regression analysis would be
that all three of the β coefficients would be significantly different from zero, and all three of
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the ORs would be significantly different from 1.0. These statistics would provide the
evidence to reject the null hypothesis, and support the research hypothesis, that pessimism,
fear, and responsibility were significant predictors of the probability that a participant would
support CCW on campus (relative to not supporting CCW on campus).
If one or more of the three variables were not significant predictors, the research
hypothesis would not be completely supported. If none of the variables were significant
predictors, the research hypothesis was not at all supported, so it would be concluded that
pessimism, fear, and responsibility were not significant predictors of the probability that a
participant would support CCW on campus. Results would indicate correlational
relationships as opposed to causation. Whatever the results of the analysis, the logistic
regression model provided evidence that would warrant inclusion in the following Chapter
IV.
Summary
This chapter was designed to provide the methodology of the proposed study. A
convenience sampling of N = 169 students was utilized. The campus in question chose
participants because they represented a spectrum of majors as well as varying levels
(i.e., freshmen, sophomores, etc.). This was viewed as more beneficial than a volunteer
convenience sampling as it was a random cross section. A pilot study was employed to
verify the understandability of the measures utilized by the researcher. Areas of concern
were uncovered and corrected before the final sampling. Issues of validity were also
addressed. Internally, there was concern that the relationships discovered between the
criterion variable and the predictor variables might be been due to chance instead of
causality. However, results discovered in the study were found to be in line with other
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studies strengthening concerns of internal and external validity. This will be addressed in the
following chapter. Lack of random sampling was a concern as well as the potential for
contamination by those with extreme views related to the criterion variable. Mortality was
not an issue. Pretest subjects were not utilized in the final study. A logistic regression and
correlation model was utilized to examine the relationship between the criterion and predictor
variables as the hypotheses were tested. Results of the study are presented in the following
chapters.
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CHAPTER IV: RESEARCH FINDINGS
The keystone of this quantitative study was the question as to whether support for
CCW on campus could be determined by addressing levels of defensive pessimism, fear, and
responsibility. Levels of defensive pessimism, fear, and responsibility were weighed against
the acceptance or denial of CCW on campus. These were assessed in terms of the
hypotheses (H1) that defensive pessimism, fear, and responsibility would prove to be
significant predictors of the probability that a participant would support CCW on campus.
This stood in direct contrast to the null hypothesis (H0) in which defensive pessimism, fear,
and responsibility would not prove to be significant predictors of the probability that a
participant would support CCW on campus. To achieve this end, quantitative research
methodology, a linear regression model, was applied. This was underpinned by a
correlational design, defined as “research that involves collecting data in order to determine
the degree to which a relationship exists between two or more variables” (Fraenkel &
Wallen, 2010). As stated above, the research question that guided this study was “What are
the relationships between the participants’ support for concealed carry weapons (CCW) on
campus and their levels of defensive pessimism, fear, and responsibility?”
This chapter describes how the individual components (defensive pessimism, fear,
and responsibility) of the null hypothesis were tested, based upon analysis of the data mined
from 169 student responses. As mentioned in the previous chapter, the only statistical
method that could be justified to predict a nominal criterion variable was logistic regression
analysis (Hosmer & Lemeshhow, 2000). Because the criterion variable in this study had two
categories, linear regression analysis was necessary, based on the following model:
E(y) = α + βx with a prediction equation of ŷ = a + bx
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Where: y would denote the response as to the support or denial of CCW on campus and x
would represent an explanatory variable. As a linear function, y is viewed as a function of x
with a straight-line graph in which beta is represented by slope β and the alpha by the
y intercept. In such a model, as Agresti and Finlay (2009) point out that if β is positive then
y will increase as x increases. Conversely, if β is negative then y will decrease as x
increases. In short, the study was designed to individually address each component of the
hypothesis. Assessment of the data began with an overview of the information as it related to
demographic variables. The data was then reviewed in terms of each of the variables (and
their variations) presented within the research question–defensive pessimism, fear, and
responsibility. Each of the following factors was addressed from two points of view (see
definitions in Table 1). Defensive pessimism was assessed based upon raw scores as well as
a scale conversion. Fear was assessed based upon the FQ17–one question specifically
addressing the fear of CCW in the respondent’s environment. FQ 16 is a scale based upon
total phobia scores. The Responsibility Attitude Scale was addressed based upon a singular
inverted scale. In short, though one research question was addressed, that question had
variations within the variables, and those were addressed accordingly and individually within
this chapter.
The purpose of this study was to determine if elevated levels of defensive pessimism,
fear, and responsibility–elements of the hypothesis, influenced the support of CCW on
campus. This stood in direct contrast to the null hypothesis that the support for CCW would
not be reflected in elevated levels of defensive pessimism, fear, and responsibility.
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Pilot Study Results
The study proved very useful in testing the time commitment needed to complete the
study measures. It was assumed the average student would need 20 minutes to complete all
the measures of the study. This included reading and signing the consent form, completing
the biographical data page, and completing the Defensive Pessimism scale, the Fear
Questionnaire, and the Responsibility Scale. In conducting the pilot study, the average time
needed to complete the instruments was 19.1 minutes. However, fours students completed
the measures in 16 minutes while another four completed the measures in 18 minutes.
The pilot study also proved useful in determining certain problems students may have
with the measuring instruments. Two misspellings were discovered in the pilot study. An
error was found in the Defensive Pessimism Scale and the Fear Questionnaire. The
misspellings were corrected to prevent any possible misunderstanding on behalf of the
participants. Additionally, an important discovery was the need to differentiate the proposed
scenario from other instructions on the Defensive Pessimism Questionnaire. As originally
presented, the same font was used in the Defensive Pessimism Scale instructions and the
proposed scenario to which the participant was to react. This was seen as confusing to the
participants as they seemed to simply skim the directions and neglect the very important
scenario. The scenario was set apart by bolding and italics.
Overall, the pilot study proved useful. It must be reported that the researcher was
surprised to find that a majority of the students supported the presence of CCW as a means to
safety. This served as an impetus to pursue a study in which the roles of defensive
pessimism, fear, and responsibility are weighed against this support.
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Data Analysis
Altogether, 169 students from 21 different areas of study fully completed surveys
utilized for this study. Of the 169 participants, 38 (22.5%) indicated they did not support
CCW on campus while 131 (77.5%) did support CCW on campus. In addition, of the 169,
77 (45.6%) were female and 92 (54.4%) were male. Freshmen accounted for 103 (60.9%) of
the respondents; 40 (23.7%) were sophomores; 17 (10.1%) were juniors; 9 (5.3%) were
seniors. Racial identity was as follows: 20 (11.8%) were African American; 1 (.6%)
identified as Asian American; 3 (1.8%) identified as Hispanic; 136 (80.5%) identified as
White/Caucasian; and 8 (4.7%) identified as Other (including bi-racial). Of the 169
respondents, only 2 (1.2%) were not United States Citizens; 167 (98.8%) identified as United
States Citizens. Age breakdown was as follows: 124 (73.4%) were age 20 or under; 29
(17.2%) were aged 21 to 24; 3 (1.8%) respondents were aged 25 to 30; 3 (1.8%) was in the
31 to 34 age category; 5 (3%) were in the 35 to 40 age category; and 5 (3%) were in the over
40 age category.
Norem’s (2001) Defensive Pessimism Questionnaire (DPQ) also had 169 complete
responses. DPQ scores ranged from 22 to 79. These scores were then categorized to
correspond to the other variables. A score of 22 to 41 would not be categorized as a
Defensive Pessimist and would be labeled a 1. This range was considered strategic
optimism. A score of 42 to 61 would be labeled a 2 and would be categorized as using
strategic optimism and defensive pessimism. A score of 62 to 79 would be labeled a 3 and
categorized as a defensive pessimist. The mean score was 50.51. The standard deviation
was 11.106. Scores were recorded in two formats. The first format was a scaled version of
the responses. For the purposes of this sample, a score of 22 to 41, labeled a 1 in the scaled
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version, would not be categorized as a Defensive Pessimist. This range is considered
strategic optimism. A score of 42 to 61, labeled a 2 in the scaled version, would be
categorized as using strategic optimism and defensive pessimism. A score of 62 to 79,
labeled a three in the scaled version, would be categorized as a defensive pessimist. A record
of raw, unscaled, scores was also maintained. Of the 169 respondents in the current study, 42
(24.9%) could be labeled as strategic optimists; 101 (59.8%) are defined as using both
strategies. In this particular sample, 26 (15.4%) are defined as being defensive pessimists.
These scores were then scaled to correspond to the other variables. Again, a score of 22 to
41 would not be categorized as a Defensive Pessimist and would be labeled a 1. This range
is considered strategic optimism. A score of 42 to 61 would be labeled a 2 and would be
categorized as using strategic optimism and defensive pessimism. A score of 62 to 79 would
be labeled a 3 and categorized as a Defensive Pessimist. The raw scores were maintained as
a separate record to compare against the scaled version as a means of researcher validation.
The Fear Questionnaire was utilized in two ways. First, a total phobia score was
determined based upon responses to Questions 2-16 of the tool. This was labeled FQ16 by
the researcher. Seventy-six (45%) of the respondents fell into the “would not avoid to
slightly avoid” category (labeled category 1 by the researcher). These scores indicated an
absence or lack of real concern as far as common phobias were concerned. Similarly, 77
(45.6%) also fell into the “slightly avoid to definitely avoid” category (labeled category 2 by
the researcher), indicating a stronger presence of fear as was related to common phobias.
Finally, 16 (9.5%) fell into the “definitely avoid to markedly avoid” category (labeled
category 3 by the researcher), indicating higher levels of phobic response. None of the 169
respondents fell into the final category of “definitely avoid to always avoid.” Based upon
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categorical labeling, the mean of the FQ16 was 1.64 with a SD of .649. Then, a single
response was ascertained based upon one’s response to an item concerning one’s level of fear
in being in an environment where one knows there are CCW present. This was labeled FQ17
by the researcher. The Fear Questionnaire was not utilized beyond these two areas of
inquiry. As far as the general phobia portion (labeled FQ 16 by the researcher) of the
measure was concerned, 76 (45%) of the respondents fell into the “would not avoid to
slightly avoid” category (labeled category 1 by the researcher). These scores indicated an
absence or lack of real concern as far as common phobias are concerned. Similarly, 77
(45.6%) also fell into the “slightly avoid to definitely avoid” category (labeled category 2 by
the researcher) indicating a stronger presence of fear as is related to common phobias.
Finally, 16 (9.5%) fell into the “definitely avoid to markedly avoid” category (labeled
category 3 by the researcher) indicating higher levels of phobic response. None of the 169
respondents fell into the final category of “definitely avoid to always avoid.” The mean of
the FQ16 was 1.64 with a SD of .649.
The FQ17 portion of the FQ showed a more marked difference. Of the 169 complete
responses, 105 (62.1%) indicated they “would not avoid to slightly avoid” an environment in
which a known CCW was present. This was labeled FQ17-1 by the researcher. Another
36 (21.3%) indicated they would “slightly avoid to definitely avoid” an environment in
which a known CCW was present. This was labeled FQ17-2 by the researcher. Only 28
(16.6%) indicated they would “markedly avoid to always avoid” an environment in which
CCW were present. This was labeled FQ17-3 by the researcher. Based upon the categorical
labeling, the mean categorical score was 1.54 with a SD of .763.
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The Responsibility Attitude Scale (RAS) provided an average score from the 27
questions within the measure. RAS scores ranged from 1.81 to 6.12 with lower scores
representing higher levels of responsibility. These scores were then converted into scaled
variables corresponding to the other predictor variables. Low levels of responsibility, 4.69-
6.12, were labeled as a 1. Midlevels of responsibility, 3.25-4.68, were labeled as a 2. High
levels of responsibility, 1.81-3.24, were labeled as 3. The most frequent result was 3.92.
The mean was 3.6736. As cited in Antony et al. (2001), Salkovskis et al. (2000) indicated,
the average score on the measure for non-clinical controls was 3.48 with an SD of 1.01
during validation studies. The test was intended, as Antony et al. (2001) pointed out, “To
assess general attitudes, assumptions, and beliefs about responsibility” (p. 230). The lower
the score on the RAS, the great the personal feelings of responsibility. The higher the score,
the lower the personal feelings of responsibility. Scores were broken down into three
categories to meet the same standards of data presentation that can be seen in the RDPQ, the
FQ16, and the FQ17. Since the RAS returns higher levels of responsibility as lower
numbers, this particular scale will be reversed.
Analysis Conclusions
Per Hosmer and Lemeshow (2000), the three-predictor variables do not show a high
intercorrelation as is indicated by a correlation coefficient greater than .8. This being said, it
was determined that the three variables had no need to be transformed by multiplication to
create a composite predictor variable. Instead, regression was utilized to determine the
strength of each variable as a predictor of the proposed hypothesis that each factor would
show increased levels based upon how participants responded to the criterion variable.
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Utilizing Linear Regression and comparing the criterion variable to the predictor
variables, a varied image begins to appear. Beginning with the predictor variables, each
variable will be addressed.
Assessment of Defensive Pessimism Scale 1-3
Based upon the Linear Regression analysis and a confidence interval of .95, it was
determined that the null hypothesis was retained. The data supplied within this study did not
bear out the proposed hypothesis that indicated a relationship between the criterion variable
of support for CCW and defensive pessimism, fear, and responsibility. As far as defensive
pessimism scaled scores (DPSCALE) were concerned, research found a correlation of .077.
When the defensive pessimism raw scores (DP) replaced the scaled version of the scores
(DPSCALE), the correlation was recorded at .063. The two-tailed significance level for DP
was .320. Again, the Null Hypothesis, as far as DP and DPSCORE were concerned, was
retained. The similarities were too small to support the proposed hypothesis.
Assessment of FQ 17
A similar scenario was revealed when the criterion variable was analyzed in
conjunction with the FQ17 predictor variable. The correlation level returned was .434,
indicating a weak possibility a relationship exists. However, the two-tailed significance was
.000. Chance was not really a factor in comparing these two items simply because of the
similar nature of the information sought in the variables. This being said, the null hypothesis
was not retained based upon the empirical data. A strong relationship was indicated between
the variable FQ17 and support or denial of CCW.
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Assessment of FQ 16
When the criterion variable was addressed in terms of the FQ16 a correlation rate of
-.120 was returned. The significance level was .119. Again, this was outside the .05 level.
However, the data does suggest that an inverse relationship was possible (i.e., a negative
correlation between the two variables). This was expected, but it is not statistically
significant. Perhaps a larger sample size would bear this out. However, based upon the
parameters of the study, the null hypothesis was retained. A linear regression curve fit shows
this inverse relationship.
Assessment of RAS
In looking at the RAS raw data, a correlation of only .005 was returned along with a
significance level of .935. When addressing the RASADJ, an inverse correlation of -.007
and a significance level of .924 were returned. The null hypothesis was retained.
Assessment of Demographics
Though not variables in the study, it was relevant to mention the demographic
components. Age correlated with each of the factors as follows: with the Yes/No criterion
variable there was a correlation of .098, with DP there was a correlation of .061, with FQ17
there was a correlation of -.09, with FQ 16 there was a correlation of -.098, and with RAS
there was a correlation of -.157. Class correlated with the variables as follows: with Yes/No
there was a correlation of .077, with DP there was a correlation of -.009, with FQ17 there
was a correlation of -.080, with FQ16 there was a correlation of -.096, and with RAS there
was a correlation of -.049.
Sex correlated to the variables as follows: the criterion variable correlated at -.037,
DP correlated at .030, FQ17 correlated at -.048, FQ16 correlated at -.263, and RAS
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correlated at -.089. Major correlated at -.022 for the criterion variable, for DP it correlated at
.184, FQ17 correlated at .051, FQ16 reported at .014, and RAS reported at -.096. Because of
the disproportionate number of Caucasian and US citizen respondents, these two areas were
not addressed.
Summary
Based upon the data mined from 169 student responses, it was concluded that the null
hypothesis was supported. The evidence simply did not support the researcher’s entire
hypothesis. All variables were insignificant when viewed via a correlational and logistical
regression approach. The only exception, as has been discussed and was born out in the
following chart (see Table 5), was the relationship between the predictor variable and the
criterion variable labeled FQ17. Based upon the data, it appears that fear plays a role in two
sub-areas of FQ 17: “would not avoid to slightly avoid” and “markedly avoid to always
avoid.” In the FQ17 category as a whole data returned a Wald Chi Square score of 23.797
and a significance rate of .000. This indicates a strong relationship. When addressed based
upon scaled responses, the fear element is even more marked. The “would not avoid to
slightly avoid category” saw a Wald Chi Square score of 20.312 and a significance rate of
.000. The “markedly avoid to always avoid” category saw a Wald Chi Square score of
21.912 and a significance rate of .000. When compared to the middle FQ17 category the
significance is marked in comparison. Scaled level 2 of FQ17 only saw a Wald Chi Square
of 3.554 and a significance rate of .059. Other than the FQ17 variables, data indicated weak
relationships between the predictor variables and the criterion variable.
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Table 5
Utilizing Linear Regression an Association can only be Established in Relation to the FQ17
Category Significant at the Extremes of the Response Scale.
B S.E. Wald Df Sig Exp(B)
DPscore .021 .041 .259 1 .611 1.021
FQ17 21.912 2 .000
FQ17(1) 2.693 .598 20.312 1 .000 14.782
FQ17(2) 1.106 .587 3.554 1 .059 3.023
FQ16 .433 2 .805
FQ16(1) -.539 .821 .431 1 .512 .583
FQ16(2) -.380 .750 .257 1 .612 .684
RAS -.055 .664 .007 1 .935 .947
DPscale .318 2 .853
DPscale(1) .076 1.335 .003 1 .955 1.079
DPscale(2) .292 .840 .121 1 .728 1.339
RASadj .048 2 .976
RASadj(1) 19.697 13549.94 .000 1 .999 3.583E8
RASadj(2) .173 .788 .048 1 .826 1.189
Constant -1.206 3.841 .099 1 .754 .299
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CHAPTER V: REVIEW
The goal of this work was to address limited possibilities (predictors) as to why
individuals may support CCW on a college campus. In this chapter, the confines in which
those limited possibilities (predictors) were addressed are reviewed, findings are addressed,
and these findings are assessed in relation to similar studies. Implications for future study are
then addressed. In short, this chapter serves to emphasize the need for continued work in the
area of weapons, CCW in particular, and the effort to understand why certain individuals feel
safer when such weapons are present.
The hypothesis, H1, was framed around the premise that defensive pessimism, fear,
and level of responsibility would be significant predictors of the probability that a participant
would support CCW on campus (relative to not supporting CCW on campus). The null
hypothesis, H0, asserted that defensive pessimism, fear, and level of responsibility would not
be significant predictors of the probability that a participant would support CCW on campus
(relative to not supporting CCW on campus). Based upon the data mined from 169 student
responses, it was concluded that the null hypothesis must stand in the cases of defensive
pessimism and level of responsibility. The evidence simply did not support the researcher’s
hypothesis as far as the two-predictor variables were concerned. They were insignificant
when viewed via a correlational and logistical regression approach. The same did not hold
true as far as fear was concerned. Fear (FQ 17) was a strong indicator. High levels of fear
were found to indicate support for and against CCW on campus. In other words, fear (FQ
17) was duplicitous. For those who strongly supported CCW on campus, there was a clear
statistical relationship. For those who strongly opposed CCW on campus, there was also a
strong statistical relationship. The same did not hold true for those who had median fear as
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associated with weapons on campus. This was in line with the findings of the PRC (2013) in
which reasons for firearm ownership closely correlated with issues of personal safety. This
stood to pique the researcher’s further interest in weapons and what may draw certain
individuals to them as opposed to others. Though this type of study did not seem to have
been carried out in the past in any detail, research does exist that indicates there is a tie
between weapons and attitudes of individuals.
As previously mentioned, very recent research by the PRC (2013) indicated a change
in attitude toward weapons. According to the PRC, there has been a distinct change in the
reasoning offered by US citizens for gun ownership since 1999. The PRC made this
determination by comparing two studies. The first was carried out in 1999. This study was
then compared to a February 2013 study that utilized the same instrument of measure
employed in the 1999 study. In 1999, 49% of respondents indicated that they owned a gun
specifically for hunting purposes. In the same study, only 26% of respondents indicated they
maintained a firearm for protection purposes. In the February 2013 study, the PRC found a
reversal of these standings. Those who reported owning firearms for protection increased
22% to an overall 48%. Those who reported owning firearms for hunting saw a decrease of
17% to an overall 32%. Likewise, the PRC found slight decreases in the number of
respondents who claimed to have owned weapons for target/sport shooting, 2nd Amendment
issues, and collecting. Protection (i.e., safety) was the number one issue stated by
respondents. Similarly, of those who reported they did not own guns, the PRC found that
58% cited concerns about safety as a determining factor in keeping guns out of their homes.
In conclusion, safety was a concern from both points of view. Additionally, according to the
PRC, 58% were very concerned that the federal government’s current move toward more
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restrictive guns laws would make it more difficult for individuals to access guns to protect
themselves. When broken down along ownership lines, the difference was even more
marked. In households that did not own guns, the PRC reported that 66% believed stricter
gun laws would prevent events such as mass shootings. Gun owners did not concur.
According to the PRC, only 35% of gun owners believed stricter laws would prevent deaths
caused by mass shootings.
Framing such attitudes with the educational environment and Maslow’s theories
further complicated the issue. As Notlemeyer et al. (2012) pointed out, studies related to
Maslow’s hierarchy and academic success were very limited. The authors indicated they
were only able to find one study related to the subject; this was a study they cited by Smith,
Gregory, and Pugh (1987). This particular study investigated students’ needs in relation to
four of Maslow’s hierarchical levels: security, love/belonging, esteem, and self-actualization.
The fact that security was one of the needs addressed in academic success gives credence to
the study of CCW and the need for safety in a higher education setting despite limited
research. This stood in contrast, as Noltemeyer et al. pointed out, to the link between
academic success and very basic needs, such as health in young students (mainly elementary
aged) has already been well established.
This said, Notlemeyer et al. (2012) indicated that a sizeable portion of school-aged
children have a deficiency as related to Maslow’s needs hierarchy. In particular, the authors
noted that what was not understood was how physiological needs, safety needs, and
love/belonging needs actually related to each other and how they related to an individual’s
academic success. “Research has not yet examined the relationships between particular
deficiency needs (e.g., physiological, safety, and love/belonging needs) and specific growth
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needs (e.g., academic and cognitive outcomes)” (Notlemeyer et al., 2012, p. 1864). The
authors indicated that such research could help further clarify Maslow’s theory while
shedding new light on areas of need so students’ academic careers can be enhanced.
Additionally, given instances of violence at the Appalachian School of Law and
Virginia Tech, coupled with continued insistence on the behalf of lawmakers concerning gun
rights within the researcher’s home state of Virginia, the very presence of weapons
(including CCW) remained an interest based upon research. Nagtegaala, Rassinb, and Muris
(2009) studied the link between aggression and guns, and they found that the existing
literature was quite broad as far as this relationship was concerned. For example, they
indicated that to some even the presence of firearms was believed to make individuals
aggressive. Referring to the Berowitz and LePage (1967) famous study, Nagtegaala et al.
emphasized the finding that study participants who were angry administered a greater
number of electrical shocks to test subjects in the presence of a gun than they did in the
presence or absence of another object. This became known as the weapons effect and
spawned extensive research (Nagtegaala et al., 2009). This added validation to the research
question posed by the researcher.
Findings
The research (H1) hypothesis was tested using linear regression and correlation
analysis. The research hypothesis, H1, proposed that defensive pessimism, fear, and
responsibility were significant predictors of the probability that a participant would support
CCW on campus (relative to not supporting CCW on campus). The null hypothesis, H0,
contended that defensive pessimism, fear, and responsibility were not significant predictors
100
of the probability that a participant would support CCW on campus (relative to not
supporting CCW on campus).
As stated in the previous chapter, based upon the data mined from 169 student
responses, the null hypothesis for all predictor variables except FQ17 was born out. The
evidence simply did not support the researcher’s hypothesis as far as the remaining predictor
variables were concerned. All variables were insignificant (with the exception of FQ17)
when viewed via a correlational and logistical regression approach. The only exception, as
was discussed in Chapter IV, was the relationship between the criterion variable and the
predictor variable labeled FQ17. However, the fact that the “would not avoid to slightly
avoid category” saw a Wald Chi Square score of 20.312 and a significance rate of .000, and
the “markedly avoid to always avoid” category saw a Wald Chi Square score of 21.912 and a
significance rate of .000 is intriguing when compared to the middle FQ17 category with a
Wald Chi Square of 3.554 and a significance rate of .059. The fear is definitely polarized
and supports data presented by the PRC (2013) in which those who reported owning firearms
for protection increased 22% to an overall 48% while those who reported owning firearms
for hunting saw a decrease of 17% to an overall 32%. Clearly, fear was a factor in these
changes and represents an area of potential research for the future. However, other than fear,
data indicated weak relationships between the criterion variable and the predictor variables.
Interpretation of the Findings
The presented study was designed to determine whether a linear and correlational
relationship existed between support for CCW on campus and the variables of defensive
pessimism (as a cognitive coping strategy), fear, and responsibility. The predictor variables
addressed included responsibility attitudes as reflected by the Responsibility Attitude Scale
101
(RAS). Fear was measured using the Marks and Mathews Fear Questionnaire in two ways.
First, in what was labeled FQ16, a total social phobia score was obtained. Secondly, in what
was labeled FQ17, a single dimension fear specifically related to CCW in one’s environment
was established. Defensive pessimism, as addressed in Norem’s (2001) revised DPQ was
also utilized. This variable was also addressed in two ways. First, the raw score was
addressed in what was labeled DPSCORE. Next, the score was broken down into a threetiered
scale in which the number 1 represented an individual who was definitely not a
defensive pessimist, but were, instead, strategic optimist. The number two represented
individuals who utilized defensive pessimism and strategic optimism equally. Finally, the
number three represented individuals who were true defensive pessimists. The anchoring
variable (criterion variable) was the study participants’ support or rejection of concealed
weapons on campus. This was determined from participants’ response to a simple yes or no
statement.
Defensive Pessimism Scale
Based upon linear regression analysis, a confidence interval of .95 and a correlation
of .077 determined that the null hypothesis was to be retained. Defensive pessimism scores
and support for CCW was not born out; the data supplied within this particular study did not
bear out the proposed hypothesis. When the defensive pessimism raw scores (DP) replaced
the DPSCALE (1-3) the correlation was recorded at .063. The two-tailed significance level
for DP was .320. So, again, the null hypothesis was retained.
FQ 17
A similar scenario was revealed when the criterion variable was analyzed in
conjunction with the FQ17 predictor variable. The two-tailed significance was .000. This
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indicated a strong relationship between the support or denial of CCW on campus and specific
personal safety feelings. The polarized results between the categories, as previously
discussed, do prove very interesting as they indicate a divided society.
FQ 16
When the criterion variable was addressed in terms of FQ16, a correlation rate of
-.120 was returned. A significance level of .119 was also returned. Again, this was outside
the .05 level. However, the data did suggest that an inverse relationship was possible (i.e., a
negative correlation between the two variables). This was expected, but it was not
statistically significant. Perhaps a larger and more diverse sample size would bear this out.
However, based upon the parameters of the study, the null hypothesis was retained.
RAS
In looking at the RAS raw data, a correlation of only .005 was returned as was a
significance level of .935. When addressing the RASADJ, an inverse correlation of -.007
existed as did a significance level of .924. Again, the null hypothesis was retained.
Demographics
Though not variables in the study, it was relevant to mention the demographic
components. Age correlated with each of the factors as follows: with the Yes/No criterion
variable there was a correlation of .098, with DP there was a correlation of .061, with FQ17
there was a correlation of -.09, with FQ 16 there was a correlation of -.098, and with RAS
there was a correlation of -.157. Class correlated with the variables as follows: with Yes/No
there was a correlation of .077, with DP there was a correlation of -.009, with FQ17 there
was a correlation of -.080, with FQ16 there was a correlation of -.096, and with RAS there
was a correlation of -.049.
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Sex correlated to the variables as follows: the criterion variable correlated at -.037,
DP correlated at .030, FQ17 correlated at -.048, FQ16 correlated at -.263, and RAS
correlated at -.089. Major correlated at -.022 for the criterion variable, for DP it correlated at
.184, FQ17 correlated at .051, FQ16 reported at .014, and RAS reported at -.096. Because of
the disproportionate number of Caucasian and US citizen respondents, these two areas are
not addressed.
Limitations of the Study
This study was constructed around the premise that violence has become a part of life
in the 21st century. This premise was framed around the knowledge that based upon recent
events of domestic and international violence, including acts of terrorism, a new era marked
by turbulence and caution has emerged. Recognizing this potential for violence and the
concerns it created for some, Maslow’s theory of the hierarchy of needs was employed.
Acknowledging that lower level needs must be met before higher level needs can be pursued,
the issues of personal safety and educational pursuits formed the foundation of the proposed
hypothesis. In other words, in a stable society marked by occasional acts of violence, even
on college campuses, how can an individual meet his or her safety needs yet still pursue the
higher level goal of obtaining an education? The research hypothesized that defensive
pessimism, a cognitive coping strategy, provided a bridge that completed Maslow’s hierarchy
of needs for some individuals by supporting CCW on campus. In other words, defensive
pessimism filled the void on the safety level so that attention can be placed on personal
growth.
In constructing this hypothesis, it was assumed that there would be a correlation
between defensive pessimism and the support for CCW on college campuses as well as the
104
need to satisfy lower level needs in order to pursue higher level needs. It was also assumed
that there would be a correlation between defensive pessimism and fear, and between
defensive pessimism and responsibility would. Data collected from students at a small
Liberal Arts college in Southwestern Virginia were utilized in the attempt to help prove or
disprove the hypotheses for this study.
The study had limitations. First, the study took place on a campus that was within a
one hour drive of Virginia Polytechnic Institute and State University (Virginia Tech), the site
of the nation’s deadliest school shooting. The affinity many had with the Blacksburg campus
could have possibly tainted the views of many students. Secondly, the subject of gun rights
was one of the most debated issues in the nation. There was a long tradition of debating
Second Amendment rights in this country, and people have had very strong feelings
concerning the expansion or limitation of these rights. This is especially true in the aftermath
of the December, 2012, Newtown, Connecticut shooting of 20 first graders. In addition, the
campus and many of its students hailed from rural areas where gun ownership was
commonplace. This was reflected by the fact that of the 169 participants, 77.5%, or 131
students, believed that CCW on campus was a good idea. In other words, only 22.5%
opposed CCW on campus.
The participants were chosen through convenience sampling. As Black (1999)
pointed out, convenience sampling can bias the results because subjects might not be
representative of the population as a whole. This was a concern. However, the research site
in question chose the classes that could be accessed. The classes were representative as far
as majors and class level. Concern still remained. One issue was the rural setting of the
college in question coupled with the fact that some of the participants came from rural
105
settings where gun ownership tends to be higher. Further cases of national violence, such as
the Newtown, CT shooting, could also have heightened fears in study participants and caused
a positive response to the CCW question without allowing proper time to “think through” the
components of the measures. This was reflective of the recent research presented by the Pew
Center (2013) in which guns were found to be more associated with safety than in previous
years.
Implications
Despite the results of the data in this particular study, the failure of the hypothesis, the
researcher believed that a better understanding as to why some individuals feel greater levels
of safety when in the presence of firearms could be determined. For one, Maslow’s theories
have been widely accepted. Germana (2007) indicated that Maslow believed in “a sine qua
non of creativeness” (p. 67) that is translated as “a fusion of person and world” (p. 67). This
being said, personal safety could not be ignored as one progresses the levels of his hierarchy.
Additionally, as Roark (1987) pointed out, “College campuses are a part of society and are
subject to the same forces that permeate contemporary society” (p. 367). In other words, if
society becomes more violent, we can expect the same of the nation’s college and university
campus populations. Individuals who are concerned about personal safety must cope in some
manner. This is especially true when an educational environment is taken into account for
your adults. According to Rollins (2010), and as mentioned in Chapter I, college and
university campuses have been seen as “Ivory Towers” where students were “insulated from
the community and protected from hurt, harm, and/or dangers” (p. 1). This no longer
necessarily holds true. Similarly, much research has gone into why certain individuals
become violent in various situations and settings. From a sociological point of view, as
106
Staub (2003) indicated in a study of mass acts of violence, society offers insight. As the
author pointed out, all societies can be divided into “us” and “them” (p. 792) components.
These monikers imply that there is an imbalance–real or perceived–between two groups.
The “them” group feels “devalued” (Staub, 2003, p. 792) in one way or another. As Staub
discussed, this equation can be used to define intra-societal violence. When applied to a
college and university campus setting, this argument can be seen to stand true as well. After
all, Notlemeyer et al. (2012) indicated that their own work offered “some support for
Maslow’s assertion that growth needs such as academic progress may be positively related to
improvements in deficiency needs such as safety and love/belonging” (p. 1866). Finally, as
Nagtegaala et al. (2009) indicated in citing Berowitz and LePage (1967), to some, even the
presence of firearms was believed to have an impact on the way an individual felt in a given
setting (the weapons effect). The hypothesis was but one way of testing such a concept and
has borne out that fear is an issue as far as CCW are concerned.
Future Research
The one thing that stood out based upon the collected data and data analysis was that,
though not significant, there was a tendency to indicate that there could be a relationship
between the support for CCW on campus and Defensive Pessimism. Based upon a
confidence interval of .95, research found a correlation of .077 between the two variables.
When the DP raw scores (DP) replace the DPSCALE (1-3) the correlation is recorded at
.063. These returns are very intriguing and warrant further investigation. The two-tailed
significance level for DP was .320. Though not significant according to the boundaries of
this study, this number does represent, by the researcher’s interpretation, a real need to dig
deeper and expand the research field. Though the similarities are too small to support the
107
proposed hypothesis, the structure of the current research could have produced a Type II
error.
Discussion
As discussed, Norem (2002) argued that the concept known as defensive pessimism
was a real coping strategy. It allowed anxious individuals to control their anxieties and
progress instead of allowing those same anxieties to tear them down. In other words, it
addressed anxiety rather than ignoring it. Norem defined defensive pessimism as:
the process that allows anxious people to do good planning. They can’t plan
effectively until they control their anxiety. They have to go through their worst-case
scenarios and exhaustive mental rehearsal in order to start the process of planning,
carry it through effectively, and then get from planning to doing. (p. 48)
Additionally, citing Klinger (1975), Emmons (1986), Little (1983), and Cantor and
Kihlstrom (1987), Cantor et al. (1991) wrote that these appraisals reflect “current concerns
that consume people’s thoughts and guide their attention selectively” (p. 426). In short,
people have different goals at different points in time. Safety has been one of the goals
pertinent to this study. Based upon the analysis returned in this study, the researcher feels
this remained true. As Norem (2002) made clear, defensive pessimism is a coping strategy
“by which negative thinking transform[s] anxiety into action” (p. 5). The evidence points out
that there was an interesting correlation between the criterion variable and the predictor
variable of defensive pessimism. Additionally, it was important to keep in mind that,
according to Norem, anxiety was used for a positive outcome, so successful use of the
strategy did not depend on past anxiety. It was a strategy that utilized anxiety about what is
to come, a strategy that used a new situation and the anxiety this new situation brought began
a planning process that brought about the most positive outcome. As Cantor et al. (1993)
pointed out, “Individuals can and do use their social world in useful ways to navigate crises
108
and transitions, small and large” (p. 275). In this process, as Norem (2008) pointed out,
defensive pessimism “can mitigate” (p. 123) the negative aspects of an individual’s anxiety
so that attention can be placed on goal performance.
Additionally, as the PRC (2013) pointed out, 37% of US households had a gun
present. Seventy-nine percent of this number reported that gun ownership made them feel
safer. Similarly, of those who reported they did not own guns, the PRC found that 58% cited
concerns about safety as a determining factor in keeping guns out of their homes. Safety was
a concern from both points of view. However, as previously discussed, in households that
did not own guns, the PRC reported that 66% believed stricter gun laws would prevent events
such as mass shootings. Gun owners did not concur. According to the PRC, only 35% of
gun owners believed stricter laws would prevent deaths caused by mass shootings. This
being said, perhaps a better line of inquiry would be to determine gun ownership status and
then test for the presence of defensive pessimism. Fear and responsibility could once again
be variables. After all, as Ferguson (2009) clearly related, in areas that are under-researched,
convenience sampling can help establish an initial view for future research.
109
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Appendix A
Informed Consent Form / IRB Approval # 12-041-0
You are being invited to participate in a research project conducted by Brian Wright, who is a
doctoral candidate at University of the Rockies.
You are invited to participate in a research study about defensive pessimism as a coping strategy as it
relates to the support of concealed carry weapons on campus, fear, and responsibility. The title of this
dissertation research project is DEFENSIVE PESSIMISM AND CONCEALED CARRY WEAPONS
ON CAMPUS: CAUSE FOR CALM OR CONCERN
You will be asked to state your position as to concealed carry weapons on campus. You will also be
asked to participate in three short measures: the defensive pessimism questionnaire, the Fear
Questionnaire, and the Responsibility Attitude Scale. Participation will take about 20 minutes of your
time. You will simply read the questions presented in the measures and respond by writing or
circling a numeric or pre-determined response as to level of agreement.
It is anticipated that the potential risk associated with this study will be negligible. However, you will
be asked to be honest concerning your fears and level of responsibility. If you do experience any
discomfort, please see the information at the end of this document regarding resources that you can
access. You will receive nothing as far as compensation for your participation.
If you have decided to participate in this project, please be reassured that your participation is
voluntary, and that you have the right to withdraw your consent or discontinue participation at any
time without repercussion. You also have the right to refuse to answer any question(s) for any reason
with no repercussion.
In addition, your individual privacy will be maintained in all publications or presentations resulting
from this study. Names will NEVER be used as a part of this or any future study. The researcher will
maintain, under lock and key, the instruments of measure and all related forms, and said documents
will be securely discarded after 7 years using a shredder. The findings will never be shared with
anyone in any way in which anonymity will be violated.
If you have any questions regarding this project, you may contact the researcher at 276-964-7207.
If you have questions regarding your rights as research participant or any concerns regarding this
project, you may report them – confidentially, if you wish, to Dr. David Solly or Dr. Deborah
DeSorbo, the UoR Chairpersons of the Institutional Review Board at (719) 442-0505. The extension
for Dr. DeSorbo is 1617, and for Dr. Solly, 1652. You may also contact my Dissertation Chair, Dr.
E. Barra-Johnson., at Eszter.Barra.Johnson1@rockies.edu.
A copy of this consent form will be provided to you.
118
Important information for you:
Because of the nature of the current study and associated gun violence seen around the nation, it is
important to recognize that certain emotions and/or feelings may be elicited. The University of the
Rockies and the researcher in question seek as little distress as possible for research participants. If
you, as a participant, in any way, feel distress or concern for your personal safety it is recommended
that you contact the student counseling center or other counselor as quickly as possible to discuss
your concerns.
Bluefield College offers a wide array of services including counseling for enrolled students of all
academic levels at the Student Development House. The center is located in the Student Development
House on Faculty Row on the Bluefield College campus. The Center can be reached by phone at
(276) 326-4473 or email at ksomers@bluefield.edu.
I understand the above information and voluntarily consent to participate in the research.
Signature of Participant: ______________________________ Date: _____________
IRB Approval Number: ___12-041-0_______ IRB Expiration Date: _____9/12/2013____
119
Appendix B
General Statement
I believe that qualified individuals carrying concealed weapons on a college campus is good for
the overall safety of the campus.
Please indicate whether you agree or disagree with the above statement by circling on of the
following:
Yes, I agree with the statement No, I disagree with the statement.
Please provide the following information by circling or writing in the proper response:
I am:
Male Female
I am:
A Freshman A Sophomore A Junior A Senior A Grad student
I am:
– White (includes Arabian)
– Black (includes Jamaican, Bahamian, and other Caribbeans of African but not Hispanic or Arabian
descent)
– Hispanic (includes persons of Mexican, Puerto Rican, Central or South American or Spanish origin
or culture).
– Asian and Asian American (includes Pakistanis, Indians, and Pacific Islanders)
– American Indian (includes Alaskans)
I am:
A US citizen not a US citizen
I am (Please state your age)______________________.
My major is _______________________.
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Appendix C
The Revised Defensive Pessimism Questionnaire
When you answer the following questions, please think about how you
prepare for and think about the following situations.
I am regularly assessing my campus
environment because I am concerned about my personal safety.
In the blank space beside each statement, please indicate
how true the above statement is of you, in your campus environment by writing your numeric
response.
1———–2———-3———4———-5———-6———7
not at all Very true of me
true of me
1. I go into campus situations expecting the worst, even though I know I will
probably do OK. _______
2. I generally go into campus situations with positive expectations about how
I will do. _______
3. I’ve generally done pretty well in these campus situations in the past._______
4. I carefully consider all possible outcomes before these campus situations._______
5. When I do well in these campus situations, I often feel really happy. _______
6. I often worry, in these campus situations, that I won’t be able to carry through
my intentions. _______
7. I often think about how I will feel if I do very poorly in these campus situations._______
8. I often think about how I will feel if I do very well in these campus situations._______
9. When I do well in these campus situations, it is usually because I didn’t get too
worried about it beforehand._______
10. I often try to figure out how likely it is that I will do very poorly in these
campus situations._______
11. I’m careful not to become overconfident in these campus situations._______
12. I spend a lot of time planning when one of these campus situations is coming
up._______
13. When working with others in these campus situations, I often worry that they will
control things or interfere with my plans._______
14. I often try to figure out how likely it is that I will do very well in these
campus situations. _______
15. In these campus situations, sometimes I worry more about looking like a fool
than doing really well. _______
16. Prior to these campus situations, I avoid thinking about possible bad outcomes._______
17. Considering what can go wrong in campus situations helps me to prepare. _______
121
Appendix D
Fear Questionnaire (FQ)
Choose a number from the scale below to show how much you would avoid each of the
situations listed below because of fear or other unpleasant feelings. Then write the number you chose
on the line beside each situation.
0————1———-2———–3———-4——–5———6———–7———-8
Would not Slightly Definitely Markedly Always
Avoid it avoid it avoid it avoid it avoid it
1. Main phobia you want treated (describe in your own words)…..___N/A_____
2. Injections or minor surgery………………………………………________
3. Eating or drinking with other people…………………………………..__________
4. Hospitals…………………………………………………………________
5. Traveling alone by bus or coach…………………………………________
6. Walking alone in busy streets…………………………………….________
7. Being watched or stared at………………………………………..________
8. Going into crowded shops………………………………………….._________
9. Talking to people in authority………………………………………._________
10. Sight of blood……………………………………………………….._________
11. Being criticized……………………………………………………….________
12. Going alone far from home……………………………………………________
13. Thought of injury or illness……………………………………………________
14. Speaking or acting to an audience……………………………………________
15. Large open spaces……………………………………………………._______
16. Going to the dentist……………………………………………………._______
17. Being in an environment where people are armed with concealed guns………________
122
Now choose a number from the scale below to show how much you are troubled by each problem
listed and write the number on the line opposite.
0——–1———-2———–3———-4——–5———6———–7———-8
Hardly Slightly Definitely Markedly Very severely
at all troublesome troublesome troublesome troublesome
18. Feeling miserable or depressed………………………………………….._______
19. Feeling irritable or angry…………………………………………………_______
20. Feeling tense of Panicky…………………………………………………._______
21. Upsetting thoughts coming into your mind………………………………_______
22. Feeling you or your surrounding area are strange or unreal………………_______
23. Feeling you are unprotected in a social setting……………………………_______
Now, based upon the following scale,
24. How would you rate the present state of your phobic symptoms on the scale below?
0————1———-2———–3———-4——–5———6———–7———-8
no phobias Slightly Definitely Markedly Very severely
present disturbing/ disturbing/ disturbing/ disturbing
not really disabling disabling disabling
disabling
Circle one number between 0 and 8.
123
Appendix E
Responsibility Attitude Scale (RAS)
This questionnaire lists different attitudes or beliefs which people sometimes hold. Read each
statement carefully and decide how much you agree or disagree with it.
For each of the attitudes, show your answer by putting a circle around the words which best describe
how you think. Be sure to choose only one answer for each attitude. Because people are different,
there is no right answer or wrong answer to these statements. To decide whether a given attitude is
typical of your way of looking at things, simply keep in mind what you are like most of the time.
1. I often feel responsible for things which go wrong.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
2. If I don’t act when I can foresee danger, then I am to blame for any consequences if it
happens.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
3. I am too sensitive to feeling responsible for things going wrong.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
4. If I think bad things, this is as bad as doing bad things.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
5. I worry a great deal about the effects of things which I do or don’t do.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
6. To me, not acting to prevent disaster is as bad as making disaster happen.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
124
7. It I know that harm is possible, I should always try to prevent it, however unlikely it
seems.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
8. I must always think through the consequences of even the smallest actions.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
9. I often take responsibility for things which other people don’t think are my fault.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
10. Everything I do can cause serious problems.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
11. I am often close to causing harm.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
12. I must protect others from harm.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
13. I should never cause even the slightest harm to others.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
125
14. I will be condemned for my actions.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
15. If I can have even a slight influence on things going wrong, then I must act to prevent it.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
16. To me, not acting where disaster is a slight possibility is as bad as making that disaster happen.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
17. For me, even slight carelessness is inexcusable when it might affect other people.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
18. In all kinds of daily situations, my inactivity can cause as much harm as deliberate bad intentions.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
19. Even if harm is a very unlikely possibility, I should always try to prevent it at any cost.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
20. Once I think it is possible that I have caused harm, I can’t forgive myself.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
126
21. Many of my past actions have been intended to prevent harm to others.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
22. I have to make sure other people are protected from all of the consequences of things I do.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
23. Other people should not rely on my judgement.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
24. If I cannot be certain I am blameless, I feel that I am to blame.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
25. If I take sufficient care then I can prevent any harmful accidents.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
26. I often think that bad things will happen if I am not careful enough.
TOTALLY AGREE AGREE NEUTRAL DISAGREE DISAGREE TOTALLY
AGREE VERY SLIGHTLY SLIGHTLY VERY DISAGREE
MUCH MUCH
 

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