Psychological Resilience in Correctional Officers The Role of Demographics

Chapter 1: Introduction to the Study

Background of the Study

Correctional officers face the difficult task of working in

hostile, and often traumatic, environments and are highly

susceptible to developing mental health issues (Constantini et al.,

2010). While researchers have identified the psychological strain

associated with professionals who work with criminals (Gould,

Watson, Price, & Valliant, 2013), these efforts have been deficient

in identifying the roles of specific U.S. correctional officers’

demographics (level of education, marital status, gender, and

race/ethnicity) as they pertain to this population’s psychological

well-being (Andrews & Bonta, 2010).

Researchers have found factors associated with gender,

race/ethnicity, level of education, and marital status to influence

the way individuals respond to and/or cope with stressful intrusions

on everyday life (Hamby & Grych, 2013; Masten, 2011; Rutter,

2012; Xiu & Musad, 2009). This study’s topic was formulated to

address a gap in the current available literature and could provide

much needed information pertaining to the role of demographics as

protective factors for scholars investigating correctional officers’

psychological resilience. In this study, I was concerned with

identifying the positive role of specific demographics as they may

relate to correctional officers' psychological resilience. This study's

demographic questionnaire included gender and race/ethnicity for

the sole purpose of investigating their roles related to

psychological resilience. Correctional officers face many

psychological challenges as a result of working in high stress

environments among dangerous inmates (Xanthakis, 2009). Many

stressors that influence the mental health and well-being of

correctional officers have been identified in previous studies

(Brough & Williams, 2007; Gould et al., 2013; Senol-Durak,

Durak, & Gencoz, 2006). Research has yielded valuable

information pertaining to the neuropsychological activity that

occurs when individuals face stressful encounters (Xiu & Musad,

2009). The current minimal understanding of these factors, coupled

with the potential unique interplays that exist between them,

prompted in large part this study’s focus on individuals’

vulnerability to stress. Intensive research efforts have concluded

that trained psychologists in correctional institutions are much

more susceptible to developing psychological problems when

compared to other psychologists working outside of correctional

facilities (Senter, Morgan, Serna-McDonald, & Bewley, 2010).

One can only speculate that if well-trained psychologists have been

deemed higher risk for developing psychological problems (Senter

et al., 2010), correctional officers who are less trained in

recognizing the emergence of psychopathological symptoms are at

even greater risks of developing mental health issues. To provide

insight into the role that demographics play in correctional officers’

psychological resilience, further understanding of the elements that

contribute to healthy psychological functioning and the unique

interplays that may exist between them must be investigated

(Masten, 2007).

Gould et al. (2013) suggested that correctional officers,

because of their increased face-to- face encounters with inmates,

are among those most susceptible to psychological problems.

Previous findings have made it apparent that research efforts

should be focused on investigating the psychological well-being of

correctional officers, as they serve an important human service role

in maintaining society’s safety and assisting in the rehabilitation of

inmates (Andrews & Bonta, 2010; Constantini et al., 2010;

Xanthakis,

2009).

The positive social implication for researching the role of

demographics in correctional officers’ psychological resilience

affects everyone. Correctional officers’ contributions to society

stretch far beyond the inmates they assist to rehabilitate. Insight

into the psychological resilience of correctional officers will

improve understanding of factors that affect their ability to perform

vital services for all of society. Research has validated the

importance of identifying individuals considered clinical high risk

for mental health illnesses at the early phases of the diagnosis in

order to develop and implement the most effective treatment plans.

Future researchers focused on targeting prevention approaches for

this population may use this study’s investigation of demographic

factors and the possible unique interplays that exist between them.

Ultimately, efforts such as this one are necessary to provide insight

into demographics that act as protective factors on psychological

resilience and will provide a sturdier foundation for future research

efforts to build upon.

Problem Statement

Due in part to the rise of prison populations, it has become

apparent that research in effective coping strategies for correctional

staff is needed (Andrews & Bonta, 2010). Researchers have

identified that psychological resilience among professionals who

work in high stress environments can help avoid burnout (Andrews

& Bonta, 2010; Constantini et al., 2010). I developed the present

study in an effort to address the lack of information regarding U.S.

correctional officers’ psychological resilience and to provide a

foundation for future efforts concerned with investigating the

coping strategies that correctional officers employ on a daily basis.

Many studies have focused on various factors associated with

correctional officer burnout in countries outside of the United

States (Gould et al., 2013). Studies have explained the

psychological strain that accompanies officers who work with

criminals (Constantini et al., 2010) and have investigated their

reluctance towards accessing mental health services (Wester,

Arndt, Sedivy, & Arndt, 2010). This study not only addressed the

growing concern associated with the high turnover rate that affects

the 469,500 correctional officers working in U.S. prisons (Bureau

of Labor Statistics, U.S. Department of Labor, n.d.; Constantini et

al., 2010) and the inmates they help to rehabilitate, but also the

U.S. population they are tasked with protecting.

Purpose of the Study

Investigating the roles of gender, race/ethnicity, level of

education, and marital status on correctional officers’

psychological resilience allowed me to identify whether one

demographic factor (or a combination of demographic factors) can

be considered more protective against the onset and/or

development of psychopathology than others. The correctional

officers’ descriptive demographic factors were collected

simultaneously with data pertinent to establishing their

psychological resilience.

Research Questions and Hypotheses

RQ1: Are there differences in psychological resilience

between levels of education among correctional officers?

[Dependent Variable (DV)- psychological resilience, Independent

Variable (IV)- educational level]

H01 = There will be no difference in psychological resilience

between levels of education among correctional officers.

H11 = Correctional officers with higher levels of education

will have higher psychological resilience scores.

RQ2: Are there differences in psychological resilience

between different marital statuses among correctional officers?

(DV-psychological resilience, IV- marital status) H02 = There will

be no differences in psychological resilience between different

marital statuses among correctional officers.

H12 = There will be significant differences in psychological

resilience between different marital statuses among

correctional officers.

RQ3: Are there differences in psychological resilience

between races/ethnicities among correctional officers? (DV-

psychological resilience, IV- race/ethnicity) H03 = There will be

no differences in psychological resilience between

races/ethnicities among correctional officers.

H13 = There will be significant differences in psychological

resilience between races/ethnicities among correctional

officers.

RQ4: Are there differences in psychological resilience

between genders among correctional officers? (DV-psychological

resilience, IV- gender)

H04 = There will be no signification differences in

psychological resilience between genders among correctional

officers.

H14 = There will be significant differences in psychological

resilience between genders among correctional officers.

Theoretical Framework

The theoretical framework that drove this research was the

stress-vulnerability model (Gibson et al., 2014) and the American

Psychiatric Association’s (APA) (2013) definition of psychological

resilience. Researchers have used the stress-vulnerability model

consistently to examine the point at which an individual’s ability to

effectively respond to stressors is exceeded, thus resulting in the

emergence of psychopathological symptoms. The APA explained

that individuals who were resilient possessed the ability to

effectively respond and cope with adversity (APA, 2013). Serious

mental health issues have emerged among individuals exposed to

high stress environments and include negative symptoms such as

the inability to feel pleasure (anhedonia), flat affect, and/or social

withdraw (Rutter, 2012). Correctional officers were among the

individuals who were exposed to high stress and often traumatic

environments; however, their encounters with such conditions were

considered part of the job (Brough & Williams, 2007).

Research has identified the high stress and potential negative

psychological symptoms associated with correctional officers

(Brough & Williams, 2007; Senol-Durak et al., 2006). By utilizing

the stress-vulnerability model as a basis for investigating the role

of demographics as they pertain to correctional officers’

psychological resilience, I was able to identify whether specific

demographic factors contributed to a correctional officer’s ability

to effectively respond to and cope with adversity. I employed the

stressvulnerability model as the theoretical structure from which to

formulate the investigation, using positive psychology (Goh &

Agius, 2010; Seligman, 2000; Snyder & Lopez, 2007).

Emphasizing positive psychology, I used the stress-vulnerability

model to investigate not only the role of demographics, but also the

manner in which they might strengthen psychological resilience

among correctional officers.

Nature of the Study

I conducted a survey-designed study, following Creswell’s

(2014) definition, in order to investigate the interaction between

demographics (level of education, marital status, gender, and

race/ethnicity) and correctional officers’ psychological resilience.

Quantitative research that investigates the relationship between

multiple independent variables and a single dependent variable is

best suited for a factorial design (Creswell, 2014). I used a two-

way analysis of variance (ANOVA) full factorial design in order to

examine the manner in which each individual demographic factor

and the combination of demographic factors potentially related to

psychological resilience. Factorial two-way ANOVA allowed me to

determine if demographic factor(s) contributed to correctional

officers’ ability to effectively respond and cope with adversity.

Using the Connor-Davidson Resilience Scale 10 (CD-RISC-

10; Campbell-Sills & Stein, 2007), I gained objective data that I

utilized to determine a correctional officer’s ability to respond to

and/or cope with stress. The CD-RISC-10 survey has been used in

many research efforts in order to measure the psychological

resilience of various populations (Scali et al., 2012; Stephens,

2012) and entails 10 items, each consisting of a five-response

Likert scale. Responders who have higher total item scores are

determined to have higher psychological resilience. Participant

data derived from the CD-RISC-10 and a descriptive data

questionnaire provided this study with the necessary information to

appropriately use a two-way ANOVA full factorial design.

The dependent variable in this study was correctional

officers’ psychological resilience and the independent variables

consisted of four demographic factors (i.e., level of education,

marital status, gender, and race/ethnicity). All information

pertaining to independent variables was collected via a descriptive

data questionnaire inquiring about a responder’s level of education,

marital status, gender, and race/ethnicity. The descriptive data

questionnaire and CD-RISC-10 survey were offered to the

responder simultaneously, and participants were asked to return

both data collection tools simultaneously as well.

Definitions

Coping strategies: Conscious efforts to address personal and

interpersonal problems.

Demographic factors: Statistical data relating to the

characteristics of human populations.

Gender: The physical and/or social condition of being male

or female.

Intrinsic factors: Belonging to the essential nature of a

person.

Level of education: Highest of education achieved from a

recognized academic institution.

Positive psychology: The study of strengths that contribute to

an individual’s and/or community’s psychological well-being.

Protective factors: Attributes or conditions that contribute to

an individual’s ability to respond to and cope with stressful events

effectively.

Psychological resilience: An individual’s ability to properly

adapt to stress and adversity.

Psychopathological symptoms: Symptom(s) that contribute to

mental illness or distress.

Race/ethnicity: The race or races that individuals most

closely identify with related to both biological and sociological

factors.

Assumptions

Collection of survey data required an assumption that

responders provided information requested in a forthright and

accurate manner. The present study involved the assumption that

the measure (CD-RISC-10) provided accurate data related to the

construct of psychological resilience. For this study, I also assumed

that all participants were employed as correctional officers at the

time that they completed both the CDRISC-10 and descriptive data

questionnaire and that they were able to read at a fifthgrade level.

Scope and Delimitations

For the present study, I did not collect data beyond that of

which is contained in the CD-RISC-10 and the descriptive data

questionnaire. This study did not include the utilization of

descriptive data that encompasses genders beyond that of male or

female, marital status beyond that of married or not married, and/or

levels of education lower than that of a high school diploma or

general equivalency diploma (GED).

Limitations

Because this study’s focus was on the psychological

resilience of correctional officers who work in the United States,

data produced may not be applicable to correctional officers

working outside of the United States. Another limitation pertinent

to the utilization of information yielded from this study was that it

may only be applicable to correctional officers who work face-to-

face with inmates and not those employed in positions that do not

require direct interaction with inmates. Correctional officers who

do not have the necessary access or the ability to gain access to an

online medium utilized in this study’s data collection (e.g.,

Facebook, Survey Monkey Audience, Yahoo Focus

Groups, LinkedIn) were able to participate via U.S. Postal Service

mail correspondence.

Significance of the Study

Identifying factors that contribute to psychological resilience

in correctional officers will improve the ability to target prevention

approaches. As correctional officers struggle to protect themselves

against the negative psychopathological symptoms that result from

working in a highly stressful and volatile environment (Andrews &

Bonta, 2010), both their performance and mental health become

highly susceptible to fatigue (McCraty, Atkinson, & Tiller, 2003).

It is necessary to first identify the crucial role of protective factors

that may contribute to the psychological resilience of correctional

officers in order to gain insight into appropriate treatment

measures.

Research has validated the importance of identifying

individuals who are considered clinical high risk for mental health

illnesses at the early phases of the diagnosis in order to develop

and implement the most effective treatment plans (Cannon et al.,

2008). By identifying demographics that contribute to correctional

officers’ psychological resilience, therapists may be able to

determine those who are clinical high risk earlier and target

prevention approaches that are evidenced-based and in alignment

with the respective demographic factors.

While most studies seemingly focus on identifying the factors

that negatively contribute to the psychological resilience of

individuals who are employed in high stress and high risk

positions, this study was aligned with positive psychology. The

idea of focusing on the factors that contribute to an individual’s

well-being has become in recent years the interest of many scholar

practitioners who seek to build on the strength of their clients

(Drvaric et al., 2015). Should this study have identified

demographic factors related to correctional officers’ psychological

resilience, therapists would be better equipped to identify optimal

prevention approaches. A method rooted deeply in the workings of

positive psychology is to make apparent what has gone right

instead of what has gone wrong (Seligman, 2000).

The significance of this study is directly associated with its

goal to determine the positive role that demographics play in the

promotion of correctional officers’ psychological resilience. By

first making apparent the role of demographics as they pertain to

psychological resilience in correctional officers, and then in the

future examining these strengths, my hope with this study was to

provide insight into the factors that these individuals rely on to

mitigate the negative psychopathological symptoms that they face.

Therapists will have a better understanding of demographic factors

that contribute to psychological resilience and the positive

emotions they evoke when the results of this study are

disseminated.

A renowned expert in the area of positive psychology,

Seligman (2000) wrote, “A science of positive subjective

experience, positive individual traits, and positive institutions

promises to improve quality of life and prevent the pathologies that

arise when life is barren and meaningless” (p. 5). Positive emotions

such as excitement, satisfaction, and pride may be associated with

race/ethnicity and/or gender and could potentially play a role when

therapists help their clients to develop or maintain a positive sense

of well-being.

Implications for Positive Social Change

In this study, I investigated the role of demographics that act

as protective factors against psychopathological symptoms and

attempted to identify factors that could be further built upon to

improve mental health well-being. The results of this study

increased understanding of whether demographic factors are

related to the psychological resilience of individuals working in

high stress environments. Gaining a better understanding of

psychological resilience allows mental health professionals to

employ positive psychology strategies to build on the strengths of

their clients (Drvaric et al., 2015). Mental health professionals

working with correctional officers will be able to develop

treatment plans based on positive emotions, relationships, meaning

and purpose, and accomplishments as they consider correctional

officers’ psychological resilience. Therapists working with

correctional officers may also benefit from this study’s inclusion of

race/ethnicity and gender. Correctional officers are tasked with

ensuring the safety of both inmates and the public. Targeting

prevention approaches that assist correctional officers to maintain

and/or strengthen their psychological resilience is vital to ensure

their well-being, the safety of the public, and the inmate

population.

The U.S. population includes individuals who have been

imprisoned at one point. Efforts to rehabilitate prisoners carry

significant social implications. The idea of self-care plays a vital

role in many professions; however, this study was developed on the

assumption that those who work in volatile professions are

especially in need of identifying their protective factors. Research

has identified that correctional officers face high stress working

environments on a daily basis (Brough & Williams, 2007). The

information gained from this study could potentially contribute to

the development of programs that improve their psychological

resilience and prevent the onset of psychopathology. Demographic

factors such as correctional officers’ race/ethnicity and gender

cannot be changed if a link between them and psychological

resilience was made; however, this study’s data serve to increase

awareness of those considered to be at higher

risk.

Summary and Transition

Close to a half of a million correctional officers report to

work in U.S. prisons (Bureau of Labor Statistics, U.S. Department

of Labor, n.d.). U.S. correctional officers have direct contact with

large populations of inmates who are released into the general

public every day. It is to the benefit of society as a whole to ensure

that those tasked with protecting it are psychologically equipped.

According to the Substance Abuse and Mental Health Service

Administration (2015), positive self-image is recognized as an

individuallevel protective factor that may contribute to

psychological resilience. Determining whether significant links

between levels of genders and races/ethnicities and correctional

officers’ psychological resilience existed may have resulted in

identifying individuallevel protective factors that may contribute to

correctional officers’ self-image. The data may assist in the

development of therapeutic strategies that align with positive

psychological interventions for correctional officers who are at

higher risks by focusing on building their positive self-image.

Chapter 2 provides an in-depth review of this study’s data

search strategy, an explanation of the demographic factors

investigated, and overview of research that has contributed to the

understanding of psychological resilience. Included in Chapter 3

are the research design, participant information, the rationale for

choosing the methods utilized in this study’s design, and analyses.

Chapter 2: Literature Review

Introduction

Correctional officers have reported the psychological strain

that accompanies working in high stress prison settings

consistently over the last three decades (Andrews & Bonta, 2010;

Castle & Martin, 2006; Cheek & Miller, 1983; Cullen, Link,

Wolfe, &

Frank, 1985; Dowden & Tellier, 2004; Gould et al., 2013; Keinan

& Malach-Pines, 2007; Lambert, 2001; Morgan, Van Haveren, &

Pearson, 2002; Senol-Durak et al. 2006). However, studies have

yet to make apparent the positive role that specific demographics

play in a correctional officer’s psychological resilience. A long

time ago researchers identified that prison correctional officers

face daunting working environments that entail potential

psychologically damaging work characteristics (Dollard &

Winefield, 1995). These work characteristics include highly

stressful demands and low control that present themselves in many

scenarios. Approximately 469,500 correctional officers in the

United States are challenged with developing and maintaining

psychological resilience as they strive to meet the demands of

working in a high stress environment (Constantini et al., 2010;

Gould, et al., 2013; Bureau of Labor Statistics, U.S. Department of

Labor, n.d.). While minimal studies have investigated the

relationship between work characteristics that are common in

prison settings and psychological strain (Andrews & Bonta, 2010),

less insight has been shed into correctional officers’ effective

coping strategies and the role of demographics.

This study’s purpose was to investigate demographic factors

that might contribute to the psychological resilience of correctional

officers, and I focused on trying to understand the roles that

gender, educational levels, marital statuses, and race/ethnicities

occupy in promoting good mental health among this population.

The literature review included published research related to

stress causing factors found in prison settings, factors associated

with psychological resilience, correctional officers’ and their

ability to identify the emergence of psychopathological symptoms,

and correctional officers’ susceptibility for developing

psychological problems.

Literature Search Strategy

In order to ensure that the highest quality of data was

compiled during the formation of this study, many EBSCO

databases were utilized. The EBSCO databases included the

following: Academic Search Complete, CINAHLPlus, PsychInfo,

PsychArticles, PsychExtra, Sage Premier, SocINDEX, and

Thoreau. This study was primarily focused on the most recent

information published within the past 6 years; however, data

retrieved from articles published as early as 1995 were included in

order to explain the historical significance of the problem. Specific

words and combination of words were used in conducting the

search for this study: psychological resilience; correctional

officers; stress; stress causing factors, stress and work

characteristics; high stress environments and conditions;

psychological strain and officers; and work stressors.

Research was also retrieved from search engines and

websites that included the following: American Psychological

Association; Bureau of Labor Statistics, U.S.

Department of Labor; Google Scholar; and National Institute of

Mental Health.

Theoretical Framework

The theoretical framework utilized during the development of

this study was the stress-vulnerability model (Zubin et al., 1977),

which details the APA’s (2013) definition of resilience. Scholars

historically have used the stress-vulnerability model the help

identify the point at which an individual displays difficulty

responding to and/or coping with adversity. This study was

intended to provide insight into demographic factors that might

have contributed to a correctional officer’s ability to effectively

respond to and/or cope with high stress demands in alignment with

the APA’s explanation of psychological resilience.

According to recent research that used the stress-vulnerability

model’s framework, many individuals began to experience

psychopathological symptoms when exposed to stressful events

and/or scenarios (Gibson et al., 2014). The stress-vulnerability

model can be used in identifying the point at which an individual

has become susceptible to stress because of deficient coping

mechanisms (Gibson et al., 2014). Built on research that made

apparent the devastating negative symptoms that entail the inability

to feel pleasure (anhedonia), flat affect, and/or social withdraw

(Ruhrmann, 2010), the stressvulnerability model provides a

framework for research efforts that concern factors that affect

psychological resilience. Built on the theory that there may be

certain factors that increase the chances of psychopathological

symptoms emerging and other protective factors that decrease

these chances, the stress-vulnerability model is suited perfectly for

studies such as this one.

The high stress demands associated with correctional

officers’ daily assigned work duties may have damaging effects on

their mental health states; however, by applying the work of

Gibson et al. (2014), it is possible to gain further insight into those

elements that contribute to an officer’s psychological resilience. By

investigating demographic factors, mental health professionals

might gain the ability to gauge the risk of a correctional officer’s

susceptibility to stressful demands.

As the neurosciences continue to evolve with help of ever-

emerging technology, it has become clear that there indeed exists a

unique interplay between stress and potential factors that increase

an individual’s susceptibility to stress. These factors exist both

inside and outside of the brain (Goh & Agius, 2010). By using the

stress-vulnerability model and integrating what researchers know

currently about predisposition to mental illness, this study had a

strong foundation from which to investigate the role of

demographic factors on psychological resilience. The stress

vulnerability model examines the unique interplay between stress

and an individual’s vulnerability to stress. The theory defines two

primary factors (stress and vulnerability) and focuses on their

interaction. Earlier research explained stress as an individual’s

ability to adapt to or change to a life situation; however, in recent

research the terms adapt and change have been used

interchangeably with respond and coping (Gibson et al., 2014).

Stress Vulnerability Model: Intrinsic Vulnerability

Zubin and Spring (1977) focused on identifying and

explaining the reason some individuals were more or less

vulnerable to stress and acknowledged the existence of

predisposition factors that affect susceptibility to stress. The model

took into account the interaction between two elements, the first of

which the authors referred to as intrinsic vulnerability. Zubin and

Spring (1977) explained intrinsic vulnerability as potential

abnormal brain functional organization and suggested that humans

may have inherited genetic predispositions to mental illness.

Advances in neuro imaging have allowed researchers to infer that

stress is regulated by hypothalamic neurons through a process

called synaptic transmission (Xiu & Musad, 2009). The process

entails the release of the neuro transmitter orexin by the

hypothalamic neuron resulting in elevated stress levels (Xiu &

Musad, 2009). Increased synapse activity involving orexin affects

locomotor activity, arousal, cardiovascular response, and has also

been linked to increased activity in the hypothalamus (Xiu &

Musad, 2009). Zubin and Spring identified the potential for genetic

predisposition factors to affect an individual’s ability to adapt or

respond to stress and is often utilized as the foundation for current

stress and vulnerability research (Goh & Agius, 2010). Ultimately,

researchers have a better understanding of the influence stress has

on the brain because of Zubin and Spring’s (1977) work; however,

their theory also made apparent the potential influence that

psychosocial stressors and mental illness have on stress and

coping. It is important to note that findings have established that

neuro imaging does not stand alone in diagnosing psychiatric

illness and that in most cases a bio-psychosocial approach is

necessary.

Stress Vulnerability Model: Psychosocial Stressors

While there has been emergent information to substantiate

the biological changes that occur as a result of stress, the unique

interplay between psychosocial stressors and neuro activity has

been the focus of much research. The stress vulnerability model

explained psychosocial stressors may consist of interpersonal and

occupational stressors (Zubin, 1977). The model made apparent the

importance of examining both vulnerability and stressors in order

to determine the potential for psychopathology (Goh & Agius,

2010). Psychosocial stressors have become the focus of much

research in recent years, and efforts have identified that stress has

indeed contributed to the development of psychosis (Ho,

Andreasen, Dawson, & Wassink, 2007). Specifically, the stress

vulnerability model identified potential mental illnesses that may

have resulted from the interaction of intrinsic vulnerability and

psychosocial stressors. Stressors in the environment may have

increased an individual’s respective biological vulnerability (Xiu &

Masud, 2009); however, many individuals have developed and

maintained effective coping mechanisms that contributed to their

ability to ward off any potential psychopathology. Zubin and

Spring (1977) explained that the influence of psychosocial

stressors on an individual’s intrinsic vulnerability may have

lessened if his or her psychological resilience were strengthened.

Current researchers have used the stress vulnerability model to

further investigate biological vulnerability (intrinsic vulnerability)

and concluded that improving psychological resilience can have a

significant impact on responding to and/or coping with

psychosocial stressors (Stress Vulnerability Model of

Co-occurring Disorders, 2008).

Stress Vulnerability Model: Psychological Resilience

Authors of recent studies have explained psychological

resilience as protective factors and processes that affected an

individual’s ability to cope with stress (Grych,

Hamby, & Banyard, 2015). Protective factors may be utilized to

respond to a variety of diverse intrusions that presented themselves

throughout life; however, most research efforts investigated

protective factors as they pertain to diverse forms of exposure to

violence (Houston & Grych, 2015). Masten (2011) posed that in

order to gain the best insight into psychological resilience it was

necessary to have a thorough understanding of the individual’s life

and the protective factors that were present at the point when the

stressor(s) emerged. Three main factors were analyzed and

included the type of stressor(s), the individual’s perceived risk, and

the individual’s protective factors at the time of the intrusion

(Masten, 2011; Rutter, 2012). Establishing individuals’

psychological resilience entailed much more than merely

investigating their reaction to the stressful event(s); it entailed a

thorough examination of the constellation of factors that

contributed to the process of adaptation. Particular attention was

focused on identifying elements that contributed to the

maintenance of healthy functioning at the time the stressor was

occurring. These elements have unique interplays that emerged

within various populations after the intrusion (Masten, 2007). The

elements that contributed to responding to and/or coping with

stress included a variety of intrinsic and extrinsic factors, many of

which began to form during formative years (Luthar, Cicchetti, &

Becker, 2000; Xiu & Masud, 2009).

The types of stressors may not be as important as the

environmental contexts that were present at the time of their

occurrences (Hamby & Grych, 2013). The context during the time

the stressor occurred was examined as carefully as the incident

itself (Grych et al., 2015). Pertaining to the environmental context

that exists at the time of the stressor,

Grych et al. (2015) stated the need for further understanding into

psychological

resilience. According to Park (2010), when the stressor was

identified, the individual immediately engaged in a common

thought process that attempted to make sense of the incident;

however, Grych et al. stated “efforts to make meaning of stressful

events do not invariably improve wellbeing” (p. 347). The stressor

excited the individuals’ desire to determine how the intrusion

would affected him or her. In alignment with the work of

Bronfenbrenner’s (1977) social-ecological framework, the

interruption of healthy functioning after the stressor had occurred

may be attributed to the interplay between individuals and their

relationships with family, peers, and community.

Psychological Resilience: Gender and Race/Ethnicity

Research studies have explained the importance of examining

age as it pertains to psychological resilience, and in recent years

these studies focused on the crucial roles that gender and

race/ethnicity occupy during the maintenance of healthy

psychological functioning over a person’s life (Kwong, Du, & Xu,

2015). Psychological resilience was affected by race/ethnic

discrimination and may have contributed to the depletion of

psychological reserves due to chronic exposure or exposure to a

major traumatic discriminatory episode (Pascoe & Smart Richman,

2009; Williams & Mohammed, 2009). This current study was

concerned with identifying the role of specific demographics as

they may have related to correctional officers' psychological

resilience. This study's demographic questionnaire included gender

and race/ethnicity for the sole purpose of investigating their

potential roles related to psychological resilience. Understanding

that it is possible to achieve positive psychological growth

resulting from a stressful event, should the correct environmental

context at the point of its emergence be present (Tedeschi &

Calhoun, 2004), may be the key in examining the role of gender

and race/ethnicity as they pertain to the stressor(s). Psychological

resilience occurs when mental health has been preserved despite

the intrusion of the traumatic event (Zoellner & Maercker, 2006).

When discrimination between gender and race/ethnicity and

psychological resilience were investigated, the results showed

prevalence in the development of ineffective coping strategies that

included unhealthy behaviors (substance abuse and alcohol abuse;

Borrell et al., 2010). Individuals’ psychological resilience has been

less capable of sustaining healthy functioning after a stressful event

has occurred if they have been exposed to chronic discrimination

and/or a major discriminatory event (Luo, Xu, Granberg, &

Wentworth, 2012). It is important to note that individuals who have

endured such discrimination are also at greater risk for developing

depressive symptoms when compared to those who have not.

These depressive symptoms may have been compounded by the

unhealthy coping strategies they employed (Luo et al., 2012).

Psychological Resilience: Marital Statues

The decision to include marital status in this study was made

in an effort to gauge the risk of a correctional officer’s

susceptibility to stressful demands and possibly provide insight

into the role that this demographic plays in promoting

psychological resilience. Studies on psychological resilience and

marital status have published conflicting results because of the

overwhelming factors that made up the social contexts that lead to

the decision to marry, divorce, or remain single (Nelson, 1994).

Wang and Repetti (2014) stated “there is relative lack of data on

how depression is linked with support couple behavior” (p. 865);

however, they also wrote “support from a romantic partner, in

particular, can play a critical role in how adults cope with stress

and navigate the challenges in everyday life” (p. 864). Research

also examined the psychological “relief” that occurs when

individuals in unhealthy unions separate and/or divorce, (Gorlick,

1988; Mednick, 1987; Nelson, 1994) which has mitigated the

assumption that divorce always results in added stress and lessens

psychological resilience. Other studies that have investigated the

interaction between married individuals and support processes

suggested that job stress definitely influenced support transaction

between couples (Schulz, Cowan, Cowan, & Brennan, 2004; Wang

& Repetti, 2014).

The manner in which people responded to social interactions

was in large part because of their cognitive, affective, and

interpersonal functioning (Wang & Repetti, 2014) and was closely

linked to their ability to maintain interpersonal relationships

(Harvey & Pauwels, 2009). An investigation into the reciprocal

nature of correctional officers’ psychological resilience and

interpersonal relationship functioning may have provided added

insight into the role of the marital status demographics (Snyder &

Lopez, 2009). Correlations between correctional officers’

responses to social interactions, interpersonal relationships, and

their psychological resilience might have afforded researchers the

ability to identify additional protective factors that might be linked

with different marital statuses.

Recent work on the marital status demographic as it pertains

to correlations between relationship functioning and coping with

employment-related stress showed significant findings. Buck and

Neff (2012) investigated the manner in which stress related to

employment affected relationship functioning and found that work

stress was indeed often associated with deficiencies in

interpersonal relationship functioning and overall marital

satisfaction. Individuals’ self-regulatory depletion or failing

psychological resiliency might overpower the desire to repair or

salvage the marriage and may have ultimately ended with the

dissolution of the marriage (Buck & Neff, 2012). Furthermore, the

dissolution of marriages has historically been linked with external

stressors, such as work related stress (Bolger, DeLongis, Kessler,

& Wethington, 1989; Repetti, 1989; Schulz, et al., 2004). An

investigation into the role of marital status and correctional

officers’ psychological resilience may have yielded significant

findings. Specifically, this study sought to provide further

information into how a correctional officers’ marital status might

have correlated with psychological resilience by investigating their

ability to respond to and/or cope with work stress.

Psychological Resilience: Educational Levels

Research efforts have identified a significant correlation

between academic success and psychological resilience in first

year university students (Allan, McKenna, & Dominey, 2013).

University students’ capacity to respond to and/or cope with stress

was a primary contributor to their psychological resilience (Allan

et al., 2013). Inadequate psychological resiliency may be directly

related to deficiencies in academic performance and/or a primary

cause for limited or hindered academic progression (Yorke, 2000).

While there exists a significant correlation between academic

success and psychological resilience, many research efforts have

identified significantly lower levels of psychological deficiencies

in university populations when compared to populations who have

chosen not to attend higher level education (Monk, 2004; Roberts

& Zelenyanski, 2002).

This study proposed the use of correctional officers’

educational levels in order to potentially identify the role that this

demographic plays in correctional officers’ psychological

resilience. In alignment with other research efforts that have

suggested the types of stressors may not be as important as the

environmental contexts that were present at the time of their

occurrences (Hamby & Grych, 2013), research on academic

success and progression as influenced by psychological resilience

has identified the vital role of personal adaptability (Jimerson,

Egeland, & Teo, 1999). The ability to adequately function while

adapting to stressful environmental factors was directly linked to

psychological resilience; (Luthar, 2006; Masten, Burt, &

Coatsworth, 2006) therefore, it may have been possible that this

demographic (educational level) might have an indicator of

correctional officers’ psychological resilience. Research has also

explained the necessary role of examining contextual factors

present at the time of the intrusion, (Masten, 2011; Rutter, 2012;

Wang & Repetti, 2014) making it necessary to include the role of

other demographic factors in an effort to gain insight into the

unique interplays that may exist when examining correctional

officers’ psychological resilience. This study’s motivation for

including educational levels was geared towards identifying

whether or not there were differences among levels of education

and correctional officers’ psychological resilience.

Future Research

Many factors contribute to correctional officers’

psychological resilience. Investigations into the emergence of

psychopathologies that result from correctional officer trauma

continue to be needed. Future investigative efforts that focus on

psychological trauma and specific psychopathologies could yield

valuable information about effective coping strategies (Luo et al.,

2012). The various potential interplays between trauma, contextual

factors at the time of the intrusion, and psychopathology make

future multi-factorial research necessary.

Research is also needed to gain a better understanding of the

roles that cultural norms play in correctional officers’ utilization of

coping strategies and their reluctance to access mental health

services following traumatic events (Grych et al., 2015). Literature

has yet to adequately explain cultural norms and their influences

on acceptable forms of expression pertaining to stress and coping

(Grych et al., 2015). Factors such as allowable expressions during

the process of responding to and/or coping with stress, as they

relate to gender roles and the flexibility of these roles are in need

of much more research

(Grych et al., 2015).

Summary and Conclusions

This literature review provided information pertaining to

many factors that affected psychological resilience and has made

apparent protective factors and processes that affected individuals’

ability to cope with stress (Grych et al, 2015; Houston & Grych,

2015). While previous research has identified possible protective

factors that assist researchers to respond to and cope with stress,

gaining a deeper understanding of contextual factors (present at the

time of the intrusion) and unique interplays between them has yet

to be sufficiently investigated (Hamby & Grych, 2013).

Research efforts have been successful in identifying the need

to take into account factors beyond the individual’s perceived risk

and include not only the types of stress but also protective factors

that are in place at the time of the intrusion (Masten, 2011; Rutter,

2012). Zubin (1997) provided us the stress-vulnerability model that

laid the foundation for much research that followed and

advancements in neuro-imaging have broadened our understanding

of factors associated with intrinsic vulnerabilities (Goh & Agius,

2010; Xiu & Musad, 2009); however, the application of this model

has yet to be utilized when exploring correctional officers’

psychological resilience. Since neuro imaging does not stand alone

when identifying psychopathology, we are tasked with

implementing a biopsychosocial approach in order to advance

knowledge pertaining to psychological resilience and/or stress and

vulnerability (Myint, 2009). Zubin (1977) recognized the

importance of examining interpersonal and occupational stress

when trying to determine the point at which an individual is most

susceptible to stress; however, it was very complex to examine the

manner in which stress contributed to psychopathology that may

include psychosis (Ho et al., 2007). While factors associated with

psychosocial stressors may increase individuals’ biological

vulnerability (Xiu & Masud, 2009), an in-depth exploration of

demographics as protective factors have assisted to expand our

knowledge of psychological resilience. It was necessary to take

into account a constellation of factors that affect an individual’s

psychological resilience (Rutter, 2012), the potential for unique

interplays between these factors (Masten, 2011) and the context

present at the time of the intrusion (Hamby & Grych, 2013).

Researchers explained the importance of examining gender

and race/ethnicity when investigating psychological resilience and

the depletion of psychological reserves (Kwong et al., 2015; Smart

Richman, 2009; Williams and Mohammed, 2009). As correctional

officers struggle to protect themselves against the negative

psychopathological symptoms that result from working in a highly

stressful and volatile environment, (Andrews & Bonta, 2010) both

their performance and mental health become highly susceptible to

fatigue (McCraty et al., 2003). This study’s investigation provided

information associated with psychological resilience between

races/ethnicities among correctional officers and psychological

resilience between genders among correctional officers.

Wang and Repetti (2014) focused their efforts on

investigating psychopathology (primarily depressive symptoms)

and the manner in which support between individuals in

relationships associated with stress and coping occurs;

furthermore, they mention the minimal amount of data that exists

in this area of research. Marital status may have played an

important role in correctional officers’ psychological resilience, as

research has suggested that occupational stress and coping may be

affected by the support found between couples (Schulz et al.,

2004). Research has also found that the dissolution of some

marriages might provide a sense of relief, (Gorlick, 1988;

Mednick, 1987) and one can posit that less support for

occupational stress would be found in unions with high levels of

turmoil. The differences in psychological resilience between

different marital statuses among correctional officers has yet to be

included in research efforts and this study’s goal was to provide

added information into the role of this demographic.

Researchers identified a positive correlation between

academic success and psychological resilience, they established

that university students’ ability to respond to and cope with stress

played a primary role in academic progress and achievement

(Allen et al., 2013; Jimerson et al., 1999). Other researchers used

comparative analysis between university students and individuals

who were not attending higher level education, concluding that

there existed less psychological deficiencies among university

students (Monk, 2004; Robert & Zelenvanski, 2002). It has been

suggested that the focus when investigating psychological

resilience might be more appropriately placed on environmental

factors at the time of the intrusion as opposed to the types of stress

themselves. Maintaining focus on the environmental factors at the

time of the intrusion when engaged in research efforts might allow

researchers to gain a better understanding of the individuals’

vulnerability to stress. Academic success and progression may be a

prime indicator of higher levels of psychological resilience as

indicated by the university student’s ability to maintain functioning

when responding to and coping with academic demands.

Understanding that higher levels of educational achievement and

progress may be indicative of less vulnerability to stress, and that

the type of stress is not as important as the response and coping

mechanisms in place, motivated this study to investigate the

differences in psychological resilience between levels of education

among correctional officers.

This literature review drew from research and explained high

stress and potential negative psychological symptoms associated

with correctional officers (Brough & Williams, 2007; Senol-Durak

et al., 2006). The stress-vulnerability model has been utilized as a

basis for investigating the role of demographics as they pertain to

correctional officers’ psychological resilience, the researcher for

this study identified specific demographic factors that might have

contributed to a correctional officer’s ability to effectively respond

to and cope with occupational adversity. Emphasizing positive

psychology this study employed the stress-vulnerability model

while maintaining focus on the manner in which demographic

factors might strengthen psychological resilience among

correctional officers. In order to gain insight into the psychological

well-being of those tasked with keeping society safe both

contextual and process factors must be taken into account.

Understanding the role that demographics play in correctional

officers’ psychological resilience is fundamental when determining

the point at which they begin to experience psychopathology.

Chapter 3: Research Method

Introduction

This study's purpose was to investigate demographic factors

that might have contributed to the psychological resilience of

correctional officers. The role of the independent variables of

marital statuses, levels of education, races and ethnicities, and

genders on the dependent variable of correctional officers'

psychological resilience have yet to be adequately researched. This

study focused on identifying the role of specific demographics as

they may have related to correctional officers' psychological

resilience. This study's demographic questionnaire included gender

and race/ethnicity for the sole purpose of investigating their

potential roles related to psychological resilience. This study did

not include any demographic factors that should be used for

screening and/or profiling purposes. This chapter entails a

discussion of this study's research design, the methods utilized for

gaining appropriate samples, a detailed explanation of the validity

and reliability of the instruments utilized during analyses, and

procedures for participant recruitment and data collection. This

chapter concludes with a thorough explanation of the ethical

procedures that were developed and maintained in order to ensure

the wellbeing of this study's participants.

Research Design

This study's implementation of a nonexperimental research

design was appropriate as it sought to investigate the potential

relationship between more than two variables (Creswell, 2014). I

used a two-way ANOVA in order to make apparent any significant

differences between groups using four categorical demographic

factors (marital statuses, levels of education, races/ethnicities, and

genders). Implementation of a two-way ANOVA was selected in

order to identify if demographic factors and/or combinations of

demographic factors played significant roles in correctional

officers' psychological resilience (Creswell, 2014). Correctional

officers' information gathered via Internet and mail-in surveys

showed the manner in which demographic factors were not related

to their psychological resilience.

Methodology

Population

Approximately 469,500 correctional officers working in U.S.

prisons face psychologically challenging environments on a daily

basis (Constantini et al., 2010; U.S. Bureau of Labor Statistics,

2014). Participants in this study consisted of men and women

employed as state prison correctional officers enduring such

conditions. The CD-RISC10 and the demographic questionnaire

were used as means to collect participant data via the Internet and

US Postal Service. The Walden University Internal Review Board

approval number for this study is 09-26-16-0233590.

Sampling and Sampling Procedures

This study employed maximum variation sampling in order

to capture a wide range of psychological resilience among

correctional officers. This type of sampling is referred to as

purposive and is best suited for quantitative research intended to

investigate specific characteristics of a population (Frankfort-

Nachmias & Nachmias, 2008). Maximum variation sampling was

used in this study to investigate the potential role(s) of four

demographic characteristics (marital status, gender, race/ethnicity,

and level of education) on the psychological resilience of

correctional officers. This type of sampling allows researchers the

opportunity to collect data from a wide range of characteristics

within a sample. Correctional officers were asked to participate in

this study through recruitment efforts that included online and in-

person invitations (Appendix A). Correctional officers were

accessed through online community groups that allow members of

the Texas Department of Criminal Justice (TDCJ) and the

California Department of Corrections and Rehabilitation (CDCR)

to interact with one another. As the researcher, I was a member of

the Region V TDCJ Facebook group, which had 1,048 correctional

officer members as the time of data collection.

Participants were only considered eligible once they

expressed interest via phone, text, e-mail, or written

correspondence, and recruitment efforts took place before and after

their work shifts. TDCJ and CDCR correctional officers were also

recruited online via Facebook and were directed to complete the

CD-RISC-10 online or request the information be sent to them by

mail. Eligible participants were employed as correctional officers

with the CDCR or the TDCJ. Participants were over the age of 18

and had successfully completed any necessary training academy

requirements prior to gainful employment as a CDCR or TDCJ

correctional officer. Potential participants were provided a link to

the survey and/or mailed the survey along with the demographic

questionnaire. Informed consent was included in the coversheet of

the survey and explained the scope of the study. Participants

provided implied consent before completing the study. The

demographic questionnaire asked for the correctional officer’s

marital status, level of education, race/ethnicity, and gender.

Participants who were not eligible to participate in the study were

notified via mail and/or online.

Sample Size Analysis

This study involved a sample size calculation to determine

the appropriate sample size needed to ensure significant differences

among correctional officers could be drawn (Field, 2013).

However, specific factors that entail statistical power, confidence

intervals, and effect size were taken into account before an

appropriate sample size could be calculated. I ran one analysis with

multiple groups based on the levels of each variable, and used the

G*Power 3.1.9.2. application to calculate sample size. G*Power

3.1.9.2.

application was developed by Buchner, Erdfelder, Faul, and Lang

in 1992. The application allows researchers the ability to calculate

general power analysis and determine appropriate sample sizes

(Faul, Erdfelder, Lang, & Buchner, 2007). The specifications used

to determine sample size when conducting a two-way ANOVA

with the G*Power 3.1.9.2 application were based on 80% power

and an alpha level of .05. Researchers have identified 80% power

and an alpha level of .05 to be acceptable values when conducting

this type of sampling for quantitative research (Burkholder, n.d.).

An alpha level of .05 is indicative of the probability of committing

a type I error (rejecting a null hypothesis that is true), and if the

null hypothesis is true an alpha level of .05 is the probability of

wrongly rejecting it (Frankfort-Nachmias & Nachmias, 2008;

Sheperis,

n.d.). A binary hypothesis test with a power level of 80% will allow

for an acceptable probability of rejecting the null hypothesis

should the alternate hypothesis be true

(Burkholder, n.d.). An alpha level of .05 minimized this study’s

probability of making an inaccurate decision when analyzing data

(Burkholder, n.d.). The effect size in research similar to this one

represents the magnitude of the observed effect and is indicative of the

overall strength of the phenomenon as it pertains to the population (Field,

2013; Sheperis,

n.d.). In studies similar to this one a total effect size of medium =

.040 has been used

(Field, 2013; Sheperis, n.d.). This study involved conducting two

separate two-way ANOVA tests in order to investigate a total of

four variables (marital status, gender, race/ethnicity, level of

education) and their potential relationship with correctional

officers’ psychological resilience. A two-way ANOVA was used to

investigate races/ethnicities (Black, Latino, or White), genders

(male or female), and their potential relationship with

psychological resilience.

Using G*Power 3.1.9.2 analysis for conducting a two-way

ANOVA (fixed effects, special, main effects, and interactions with

a statistical power of .80, Alpha of .05, and a medium effect size of

.40), a total sample size of 52 participants was determined to be

appropriate for drawing significant differences between two

variables (race/ethnicity and gender) and within a total of six levels

(Black, Latino, or White; male or female; Buchner, Faul, &

Erdfelder, n.d.; Sheperis, n.d.).

A two-way ANOVA was also used to investigate marital

statuses (married, not married) and educational levels (GED or

high school diploma, Associates of Arts [AA] or Associates of

Science [AS], bachelor’s degree or beyond) and their potential

relationship with correctional officers’ psychological resilience.

Using G*Power 3.1.9.2 analysis for conducting a two-way

ANOVA (fixed effects, special, main effects and interactions with a

statistical power of .80, Alpha of .05, and a medium effect size of

.40), a total sample size of 52 participants was determined to be

appropriate for drawing significant differences between two

variables (levels of education and marital statuses) and within a

total of six levels (GED or high school diploma, AA or AS,

bachelor’s degree or beyond; Buchner et al., n.d.; Sheperis, n.d.).

Instrumentation and Materials

The CD-RISC-10 (Campbell-Sills & Stein, 2007) was used to

measure correctional officers’ psychological resilience. Participants

were also asked to complete a demographic questionnaire

consisting of marital status, gender, race/ethnicity, and level of

education (Appendix B).

The CD-RISC-10 was formulated using 10 items from the

original ConnorDavidson Resilience Scale 25 (CD-RISC-25;

Connor & Davidson, 2003). The CD-RISC10 yielded very similar

results as the CD-RISC-25 when measuring the psychological

resilience of various populations, and has been used in studies that

include various forms of trauma, Alzheimer’s caregivers,

adolescents, elders, posttraumatic stress disorder patients,

university students, nurses, social workers, physicians, military

medical personnel, medical students, and missionaries. The CD-

RISC-10 has also been used in functional neuro imaging studies

that included genotyping and neuro imaging to assess for treatment

outcomes and has been deemed to have valid psychometric

properties (Campbell-Sills & Stein, 2007). The CD-RISC-10 can

be completed in approximately 5 minutes and requires participants

possess the ability to read at a fifth-grade level and be at least 10

years of age. The scale itself can screen individuals for high,

intermediate, or low psychological resilience and has been

developed and tested as a predictor of outcome to treatment with

medication or psychotherapy, stress management, and resilience

building (Campbell-Sills & Stein, 2007). The scale has also been

used as a benchmark for measuring resilience treatment and as a

marker for biological changes in the brain (Campbell-Sills & Stein,

2007).

Psychological resilience has been explained as a person’s

ability to maintain adequate levels of functioning, both emotionally

and psychologically, as he or she encounters and deals with

stressful intrusions (Bonanno, 2004). Researchers have posited that

by investigating factors that influence risk and/or a person’s

susceptibility to stressors, it is possible to assess resilience

quantifiably (Connor & Zhang, 2006). Using specific scales that

take into account determinants of resilience (e.g., available

resources, support systems, previous responses and/or coping with

intrusions, etc.), it may be possible to measure subjective factors

that affect resilience in prospective fashion (how a person will

respond to future intrusion) and also a person’s current resilience

(Scali et al., 2012). The CD-RSIC-25 was developed in order to

measure normal psychological resilience in clinical and nonclinical

populations (Connor & Davidson, 2003) and is considered a

multidimensional tool consisting of five distinct areas of

measurement.

Further research and validation of the scales in CD-RISC-25 led to

the formation of the CD-RISC-10 (Campbell-Sills & Stein, 2007).

The CD-RISC-10 has been used in various studies and has been

deemed appropriate for a wide array of epidemiological work

(Notario-Pacheco et al., 2011).

Researchers have determined that the CD-RISC-10 is an

instrument that can be used to measure the psychological resilience

as it pertains to a variety of response and coping styles. According

to Campbell-Sills and Stein (2007), “Overall, the 10 item CDRISC

displays excellent psychometric properties and allows for efficient

measurement of resilience” (p. 1019). Using a calculated

Chronbach’s alpha to measure the internal consistency of the CD-

RISC-10, researchers have concluded that an alpha value of .85

indicated acceptable reliability (Campbell-Sills & Stein, 2007).

Validity analysis has compared the Brief Symptoms Inventory

(BSI) and the Childhood Trauma Questionnaire-Short Form (CTQ-

SF) to the results of the CD-RISC-10 using a sample size of 131

participants (n = 131). Participants who completed the CTQ-SF

yielded a mean of 34.4 (M = 34.4), Standard Deviation of 11.3 (SD

= 11.3), and an overall Range of 25 -79 (R = 25-79). The same

participants who completed the CTQ-SF completed the BSI and

yielded a Mean of 14.8 (M = 14.8), Standard Deviation of 11.9 (SD

= 11.9), and an overall Range of 0-53 (R = 0-53). Confirmatory

factor analysis concluded that the CDRISC-10 could be used to

accurately moderate the relationship between the CTQ-SF and the

BSI (Campbell-Sills & Stein, 2007). Using hierarchical regression

that included the CTQ-SF and CD-RISC-10 on the first step and

then the CTQ-SF x CD-RISC-10 on the second step, researchers

posited that while the main effects model indicated “significance”

(p. 1025), R = .51 R2 = .26 F (2, 127) = 22.76, P < .001, the

regression model on the second step produced results that were

“superior” (p. 1025), R = .56 R2 = .31 F (3, 126) = 19.00, P < .001

(Campbell-Sills & Stein, 2007).

Previous research efforts have used multivariate logistic

regression in order to investigate the relationship(s) between age,

education, trauma history, cancer, current psychiatric diagnosis,

and psychological resilience by using the CD-RISC-10 (Scali et al.,

2012). Studies focused on the psychometric properties of the CD-

RISC-10 have explained that there exists a negative association

between having a psychiatric disorder and having psychological

resilience (Scali et al., 2012). Scali et al. (2012) were successful in

showing that lower levels of resilience were primarily due to

heightened levels of anxiety and not mood disorders; however,

using the CD-RISC-10, they explained that a positive association

between resilience and a history of trauma existed.

Other studies that have investigated resilience using the CD-

RISC and confirmatory analysis identified higher order resilience

factors (Yu et al., 2011). Approximately one month after the

devastating 2008 Sichuan earthquake, 2,914 Chinese youth

participants were recruited to complete the CD-RISC,

Multidimensional Scale of Perceived Social Support, Children’s

Depression Inventory, and the Screen for Child Anxiety Related

Emotional Disorders. Yu et al. (2011) used a Cronbach alpha

coefficient to measure the internal consistency and successfully

investigated the hypotheses that higher social support would be

associated with higher CD-RISC scores and higher levels of

anxiety and depression would be associated with lower CD-RISC

scores. The scales had the following reliabilities: positive

correlation between “higher levels of social support” and higher

levels of resilience (0.44), a negative correlation between “higher

levels of anxiety” and resilience (-0.25), and a negative correlation

between “depression” and resilience (-0.38) (Ps < .001; Yu et al.,

2011). The CD-RISC played a vital role in assisting researchers to

determine that differences between gender and age were to be

considered influential demographic factors when investigating

resilience following trauma (Yu et al., 2011).

Goins, Gregg, and Fiske (2012) investigated the resilience

properties of the CDRISC-10 as compared to the CD-RISC in a

population of American Indians. Goins et al. posited that there

existed a unidimensional factor structure between both

measurements and that there were significant positive correlations

between self-efficacy, self-mastery, social support scales and CD-

RISC scores (mean of 75.7 and SD 13.0), and a significant

negative correlation between depression and CD-RISC scores

(mean of 83.0 and SD

13.4). Goins et al. reported that the CD-RISC scores and the CD-

RISC-10 mean score of 33.5 (SD 6.2) resulted in an item

correlation of 0.61 where Cronbach’s alpha ranged from

0.88 to 0.93.

Cosco, Kaushal, Richards, Kuh, and Stafford (2016)

identified a total of 5,909 studies to be used in a systematic review

of measurements pertaining to resilience and concluded that 426

used resilience psychometrics, six of which were included in their

final analysis. Research investigating the psychometric properties

of the CD-RISC-10 as they pertain to older adults (i.e., > 60 years)

determined that the scale possessed adequate levels of internal

consistency, convergent/discriminant validity, and theoretical

construct validity to be used in ongoing research endeavors (Cosco

et al., 2016).

Data Collection and Analysis

This study utilized the Statistical Package for the Social

Science (SPSS) software (v.23), with the alpha value set at .05, to

analyze all data collected. Online participants were administered

the CD-RISC-10 and demographic questionnaire using Facebook,

LinkedIn, Yahoo Focus Groups, and Survey Money Audience.

Participants were given the option of taking part in this study via

U.S. Postal Service and mailed the CD-RISC-10 and descriptive

data questionnaire after they had made contact and expressed

interest via phone, text, e-mail, or written correspondence.

Participants opting to participate via U.S. mail would have been

provided free return mail services. This study utilized two separate

Two-way ANOVA measures to investigate any differences between

group and/or levels that may have existed (Field, 2013). The

independent variables were the marital statuses, levels of

education, races/ethnicities, and genders of correctional officers,

and the dependent variable was correctional officers’ psychological

resilience.

The first Two-way ANOVA was used to investigate a total of

six levels between both variables. The null hypothesis for this Two-

way ANOVA was that there are no differences between the

independent variable levels (Black, Latino, or White; male or

female) and their relationship to correctional officers’

psychological resilience. The alternative hypothesis for this Two-

way ANOVA was that there are differences between the

independent variable levels (Black, Latino, or White; male or

female) and correctional officers’ psychological resilience. In both

the null and alternative hypotheses the researcher used an alpha

value of .05. The researcher used a Two-way ANOVA F-

Distribution in order to analyze the degrees of freedom to

determine the critical value to compare the test statistic to. The

degrees of freedom between groups and within groups were

determined in order to identify the critical F-Value. In order to

identify the degrees of freedom between groups the researcher took

the total number of variables in this Twoway ANOVA (2) minus

one which resulted in a degrees of freedom between groups equal

to one. In order to determine the degrees of freedom within groups

the researcher took the total number of levels (6) minus the total

number of variables (2) which resulted in a degree of freedom

within equal to four.

To determine the total degrees of freedom for this Two-way

ANOVA the researcher added both the degrees of freedom between

groups (1) and the degrees of freedom within groups (4) and

arrived at a total degrees of freedom for this Two-way

ANOVA equal to five. The researcher used the F-Distribution in

order to determine F-

Critical value where the numerator was equal to the degrees of

freedom between groups

(1) and denominator was equal to the degrees of freedom within

groups (4) to arrive at a F-Critical value equal to 4.05. In order to

calculate the sum of squares deviation from the mean for the total

variability the researcher calculated the mean for each variable and

then calculated the grand mean (sum of all the scores in each

variable divided by total scores). Once the researcher calculated

both the mean for each variable and the grand mean, the researcher

then calculated the total sum of squares by squaring the sum of

each score minus the grand mean. In order to calculate the sum of

squares within groups the researcher subtracted the sum of the

squared deviations within each group from the mean of the

variable and added them. In order to find the sum of squares

between groups the researcher took the sum of squares total minus

the sum of squares within. In order to calculate the variance

between groups (mean squared between groups) the researcher

divided the sum of squared between groups by the degrees of

freedom between groups (1). In order to calculate the variance

within groups (mean squared within groups) the researcher divided

the sum of squares within groups by the degrees of freedom within

groups (4).

In order to calculate the F-Value for the data set the

researcher divided the variance between groups (mean squared

between groups) by the variance within groups (mean squared

within groups). The researcher then compare the F-Value to the F-

Critical value in order to determine whether or not to reject the null

hypothesis that stated that there were no differences between the

independent variable levels (Black, Latino, or White and male or

female) and their relationship to correctional officers’

psychological resilience.

This second Two-way ANOVA also investigated a total of six

levels between two variables. The null hypothesis for this Two-way

ANOVA is that there were no differences between the independent

variable levels (GED or high school diploma, AA or AS, Bachelors

of Arts [BA] or bachelor’s degree or beyond) and their relationship

to correctional officers’ psychological resilience. The alternative

hypothesis for this Twoway ANOVA was that there were

differences between the independent variable levels (GED or high

school diploma, AA or AS, bachelor’s degree or beyond, and

married or not married] and correctional officers’ psychological

resilience. In both the null and alternative hypotheses the

researcher used an alpha value of .05. The researcher used a Two-

way ANOVA F- Distribution in order to analyze the degrees of

freedom to determine the critical value from which to compare the

test statistic. The degrees of freedom between groups and within

groups were determined in order to identify the critical F-Value. In

order to identify the degrees of freedom between groups the

researcher took the total number of variables in this Two-way

ANOVA (2) and subtracted one which results in a degrees of

freedom between groups equal to one. In order to determine the

degrees of freedom within groups the researcher took the total

number of levels (6) minus the total number of variables (2) which

resulted in a degree of freedom within equal to four. To determine

the total degrees of freedom for this Twoway ANOVA the

researcher added both the degrees of freedom between groups (1)

and the degrees of freedom within groups (4) to arrive at a total

degrees of freedom for this Two-way ANOVA equal to 5. The

researcher used the F-Distribution in order to determine F-Critical

value where the numerator was equal to the degrees of freedom

between groups (1) and denominator was equal to the degrees of

freedom within groups (4) to arrive at a F-Critical value equal to

4.05. In order to calculate the sum of squares deviation from the

mean for the total variability the researcher calculated the mean for

each variable and then calculated the grand mean (sum of all the

scores in each variable divided by total scores).

Once the researcher calculated both the mean for each

variable and the grand mean the researcher then calculated the total

sum of squares by squaring the sum of each score minus the grand

mean. In order to calculate the sum of squares within groups the

researcher subtracted the sum of the squared deviations within each

group from the mean of the variable and added them. In order to

find the sum of squares between groups the researcher took the

sum of squares total minus the sum of squares within. In order to

calculate the variance between groups (mean squared between

groups) the researcher divided the sum of squared between groups

by the degrees of freedom between groups (1). In order to calculate

the variance within groups (mean squared within groups) the

researcher divided the sum of squares within groups by the degrees

of freedom within groups (4). In order to calculate the F-Value for

the data set the researcher divided the variance between groups

(mean squared between groups) by the variance within groups

(mean squared within groups). The researcher then compared the

F-Value to the FCritical value in order to determine whether or not

to reject the null hypothesis that stated that there were no

differences between the independent variable levels (GED or high

school diploma, AA or AS, bachelor’s degree or beyond, and

married or not married) and their relationship to correctional

officers’ psychological resilience.

Research Questions and Hypotheses

RQ1- Are there differences in psychological resilience

between levels of education among correctional officers?

(DV-Psychological resilience, IV- Educational level)

H01 = There will be no difference in psychological resilience

between levels of education among correctional officers.

H11 = Correctional officers with higher levels of education

will have higher psychological resilience scores.

RQ2- Are there differences in psychological resilience

between different marital statuses among correctional officers?

(DV-Psychological resilience, IV- Marital status)

H02 = There will be no differences in psychological

resilience between different marital statuses among

correctional officers.

H12 = There will be significant differences in psychological

resilience between different marital statuses among

correctional officers.

RQ3- Are there differences in psychological resilience

between races/ethnicities among correctional officers?

(DV-Psychological resilience, IV- Race/Ethnicity)

H03 = There will be no differences in psychological

resilience between races/ethnicities among correctional

officers.

H13 = There will be significant differences in psychological

resilience between races/ethnicities among correctional

officers.

RQ4- Are there differences in psychological resilience

between genders among correctional officers?

H04 = There will be no significant differences in

psychological resilience between genders among correctional

officers.

H14 = There will be significant differences in psychological

resilience between genders among correctional officers.

Threats to Validity

Creswell (2014) explained two primary existent threats to

validity that exist in quantitative research; internal and/or external

factors that may affect the validity of analyses. Internal threats to

this study consisted of the implementation of the CD-RISC10

measurement and the demographic factors that were being

examined; specifically, it would have been impossible to examine

the extent to which one demographic factor solely influences

resilience. This study focused on four specific demographic

factors; however, because of the unique interplay that may have

existed between these variables it was difficult to assume that one

was not acting simultaneously with another to influence

correctional officers’ psychological resilience. Internal threats to

this study’s validity were also present when examining the manner

in which correctional officers were trained via their respective

programs. The TDCJ and the CDCR have independent and

distinguished training programs that are meant to prepare

correctional officers for the scope of work duties that they perform.

Criminal activity among inmate populations are similar systematic

differences pertinent to responding to stressful situations may

differ between systems. Participant selection and instrumentation

may have also threatened the validity of this study due to

unforeseeable factors that might have influenced a participant’s

desire and/or willingness to take part in this study.

In reviewing the potential external threats to validity (i.e. the

generalizability of this study’s results) it is apparent that

information derived from this study will be applicable in a general

manner. Due to the volunteer bias associated with this type of

quantitative research and the two correctional systems (i.e. TDCJ

and CDCR) where participants will be drawn from results may not

be applicable to all U.S. correctional officers.

Ethical Protection of Human Participants

Ethical Considerations

All participants used in any capacity during this study had the

opportunity to withdraw at any time. All participation was on a

volunteer basis and ethical considerations were a primary focus

that were maintained throughout this study’s entirety. Informed

consent is necessary when conducting any research on human

participants. All volunteers taking part in this study were required

to ensure their understanding of how data collection would occur.

Participants understood their right to withdraw at any time during

this study, the efforts that were taken to ensure their confidentiality,

and all the individuals who had access to participant information.

At no time did this study implement or utilize any participant

information, any unapproved method for analyses, and/or

dissemination practices that were not fully approved by the

Walden University Internal Review Board prior to inception. The

Walden University Internal Review Board approval number for

this study is 09-26-16-0233590.

All participation data was collected, stored, and protected in a

confidential and anonymous fashion in accordance with well-

established practices (Creswell, 2014). Participant information was

stored online by utilizing a Survey Monkey password protected

website and all password protected files was stored on one primary

device. All participation data was stored online or in locked files.

At no time was there be any information stored that could have

been used to identify volunteer participants. The only individuals

who had access to this study’s participant information were this

writer, this writer’s dissertation chair and committee member.

Summary

This study was designed in order to investigate the potential

relationships between demographic factors and correctional

officers’ psychological resilience. Online participants were

administered the CD-RISC-10 and demographic questionnaire

using Facebook, LinkedIn, Yahoo Focus Groups, and Survey

Money Audience. Participants had the option of taking part in this

study via U.S. Postal Service and would have been mailed the CD-

RISC-10 and demographic questionnaire after they had made

contact and expressed interest via phone, text, e-mail, or written

correspondence and provided implied informed consent. This study

utilized two separate two-way ANOVAs to investigate any

differences between groups and levels that may have existed.

Independent variables investigated in this study were the marital

statuses, levels of education, races/ethnicities, and genders of

correctional officers, and the dependent variable was correctional

officers’ psychological resilience. Included in this chapter were the

research design, rationale for using the design, data collection

instruments used in the study, methods for conducting data

analyses, internal and external threats to validity, and ethical

considerations. Chapter 4 includes the data analyses results.

Chapter 4: Results

Introduction

The purpose of this study was to investigate whether or not

there was a relationship between correctional officers’

psychological resilience and four specific demographic factors.

Quantitative methodology was used to investigate the independent

variables of marital statuses, levels of education, races/ethnicities,

and genders of correctional officers, and the dependent variable of

correctional officers’ psychological resilience. Two separate two-

way ANOVAs were used to investigate between and within levels.

The first two-way ANOVA was used to investigate a total of six

levels between both variables. The null hypothesis for the first two-

way ANOVA was that there were no differences between the

independent variable levels (Black, Latino, or White; male or

female) and their relationship to correctional officers’

psychological resilience. The alternative hypothesis for the first

two-way ANOVA was that there were differences between the

independent variable levels (Black, Latino, or White; male or

female) and correctional officers’ psychological resilience. The

second two-way ANOVA also investigated a total of six levels

between two variables. The null hypothesis for the second two-way

ANOVA was that there were no differences between the

independent variable levels (GED or high school diploma, AA or

AS, BA or bachelor’s degree or beyond; married or not married)

and their relationship to correctional officers’ psychological

resilience. The alternative hypothesis for the second two-way

ANOVA was that there were differences between the independent

variable levels (GED or high school diploma, AA or AS, bachelor’s

degree or beyond, and married or not married) and correctional

officers’ psychological resilience. SPSS software (v.23) was used

for analyses and computation. This chapter includes the descriptive

characteristics of the sample, a discussion on data collection

methods used, data analyses, and the results of the study as they

relate to the research questions and hypotheses.

Descriptive Characteristics

All responses included in this research study were checked

for consent, survey completion, and demographic questionnaire

completion. A time frame of approximately 3 weeks was necessary

to gain a sufficient number of participants to conduct this study. A

total of 59 participants attempted to complete the CD-RISC-10 and

demographic questionnaire; however, six participants did not

respond to all 10 items on CD-RISC-10 and one participant did not

respond to all items on the demographic questionnaire. All seven

participants who failed to respond either to all items included in the

CD-RISC-10 or to all questions included on the demographic

questionnaire were excluded from this study.

A total of 52 participants completed all items on both the CD-

RISC-10 and demographic questionnaire, and their responses

where used during analysis. The overall sample that was used for

this study consisted of 27 (51.92%) men and 25 (48.08%) women

(Table 1). The sample for this study included 31 (59.62%)

participants who identified themselves as married and 21 (40.38%)

participants who identified as not married. Data related to

races/ethnicities were derived from 16 (30.77%) participants who

identified as Latino, 13 (25.00%) who identified as Black, and 23

(44.23%) participants who identified as White. Data related to

levels of education were collected from 31 (59.62%) participants

who reported that their highest level of education was a GED or

high school diploma, 14 (26.92%) participants who reported their

highest level of education was an AA or AS, and seven (13.46%)

participants who reported t that their highest level of education was

a BA or Bachelors of Science (BS) or beyond.

Table 1

Summary of Sample Characteristics (n = 52)

Characteristics

Percentage*

Gender

Male

51.92%

Female

48.08%

Marital Status

59.62%

Married

Not Married

40.38%

Education Level

GED or High School

Diploma

59.62%

Associates of Arts (A.A.) or

Associates of Science (A.S.)

26.92%

Bachelors and Arts (B.A.)

or Bachelors of Science

(B.S.)

or beyond

13.46%

Race/Ethnicity

Latino

30.77%

Black

25.00%

White

44.23%

Data Collection

All data for this study were collected via the Internet with the

use of Facebook, Yahoo Focus Groups, Survey Monkey Audience,

and LinkedIn. No participants requested any information be sent to

them via U.S. Postal Services. The CD-RISC-10 (Campbell-Sills &

Stein, 2007) was the instrument used to collect data pertinent to

correctional officers’ psychological resilience, and a demographic

questionnaire was used to collect data pertinent to correctional

officers’ marital statuses, educational levels, races/ethnicities, and

genders. Prior to data collection, all participants who completed the

CD-RISC-10 and demographic questionnaire were provided

information about the types of questions, the approximate time it

would take to respond to CD-RISC-10 and questionnaire prompts,

and the purpose for conducting this research.

Data Analysis

Prior to examining whether there were any significant

relationship(s) between demographic factors and correctional

officers’ psychological resilience, the mean scores associated with

each demographic variable were calculated. Univariate tests were

used to identify any significant differences in psychological

resilience mean scores that existed between independent variable

levels and are represented in Table 1 and Table 2. The independent

variable gender yielded no significant differences between the

psychological resilience mean scores of males and females.

Overall, male correctional officers reported a slightly higher level

of psychological resilience (M = 30.421) than female correctional

officers (M = 28.770). Examining the resiliency means of male and

female correctional officers and their respective race/ethnicity

(Black, Latino, or White) yielded that Latino females reported the

highest resiliency (M = 32.500), followed by Latino males (M =

31.300), White males (M = 30.462), Black males (M = 29.500),

Black females (M = 27.111), and White females (M = 26.700).

Correctional officers’ races/ethnicities and genders resiliency

means can be seen in Table 2.

Table 2

Means: Correctional Officers’ Races/Ethnicities & Genders

Source

LF LM

WF WM

BF BM

M M

Resilience

32.500 31.300

26.700 30.462

27.111 29.500

Note. LF-Latino Females; LM-Latino Males; WF-White Females;

WM-White Males; BF-Black Females; BM-Black Males.

Overall married correctional officers reported a slightly

higher level of psychological resilience (M = 29.065) than

correctional officers who were not married (M = 30.585); however,

the differences in means were not large enough to be considered

significant. Examining the resiliency means of married and not

married correctional officers and their respective educational levels

(AA, AS, or BA, BS, and beyond) yielded that correctional officers

who were not married with an educational level of BA, BS, or

beyond reported the highest resiliency (M = 33.000); followed by

correctional officers who were married with an educational level of

AA or AS (M = 30.556), correctional officers who were not

married with an educational level of GED or high school diploma

(M = 30.154), correctional officers who were not married with an

educational level of AA or AS (M = 28.600), correctional officers

who were married with an educational level of a GED or high

school diploma (M = 28.389), and correctional officers who were

married with an educational level of BA, BS, or beyond (M =

28.250). Correctional officers’ marital statuses and levels of

education resiliency means can be seen in Table 3.

Table 3

Means: Correctional Officers’ Marital Statuses & Levels of

Education

Source M/B

NM/B

M/A NM/A

M/HS NM/HS

M M

Resilience 28.250

33.00

30.556 28.600

28.389 30.154

Note. M/B- Married with a B.A. or B.S. and Beyond; NM/B- Not

Married with a B.A. or

B.S. and Beyond; M/A- Married with A.A. or A.S.; NM/A- Not

Married with A.A. or A.S.; M/HS- Married with a high school

diploma or G.E.D.; NM/HS- Not Married with a high school

diploma or G.E.D.

Results of the Study

Research Questions and Hypotheses

The first two-way ANOVA was conducted with the

independent variables of correctional officers’ marital status

(married or not married) and educational level (AA, AS, or BA,

BS, and beyond), and the dependent variable of correctional

officers’ psychological resilience. The second two-way ANOVA

was conducted with the independent variables of correctional

officers’ gender (male or female) and race/ethnicity

(Black, Latino, or White), and the dependent variable of

correctional officers’ psychological resilience. Using G*Power

3.1.9.2 analysis for conducting this rwo-way

ANOVA (fixed effects, special, main effects and interactions with a

statistical power of .80, Alpha of .05, and a medium effect size of

.40), a total sample size of 52 participants was appropriate for

drawing significant differences between two variables (marital

status and educational level) and within a total of six levels

(married or not married; GED or high school diploma, or AA, AS,

or BA, BS, and beyond; Buchner et al., n.d.; Sheperis, n.d.).

RQ1- Are there differences in psychological resilience

between levels of education among correctional officers? (DV-

psychological resilience, IV- educational level)

H01 = There will be no difference in psychological resilience

between levels of education among correctional officers.

H11 = Correctional officers with higher levels of education

will have higher psychological resilience scores.

Correctional officers’ levels of education were included as a

factor in a two-way ANOVA to investigate the relationship

between this demographic factor and correctional officers’

psychological resilience. The F value of .197 was less than the F-

Critical value of 4.05 and resulted in a failure to reject the null

hypothesis. The P-value (.822) was greater than .05, which

indicated that the finding was not significant. Subset psychological

resiliency means increased with higher educational levels among

correctional officers (GED or high school diploma [M = 29.13];

AA, AS, or BA, BS, and beyond [M = 29.86]; BA, BS, and beyond

[M = 30.29]) and are represented in Table 4; however, the increases

were not large enough to be considered significant.

Table 4

Means, Std. Error, and F Statistics: Correctional Officers’

Educational Levels

Source GED or HS A.A. or A.S. B.A. or B.S. or Beyond ANOVA

test

M Std. M Std. M Std. F(df)

Resilience

29.13 4.493 29.86 6.666

30.29

3.904

.197

(1,4)

Note. Significance was indicated as follows: +p < .10; p < .05; p <

.01.

RQ2- Are there differences in psychological resilience

between different marital statuses among correctional officers?

(DV-psychological resilience, IV- marital status) H02 = There will

be no differences in psychological resilience between different

marital statuses among correctional officers.

H12 = There will be significant differences in psychological

resilience between different marital statuses among

correctional officers.

Correctional officers’ marital statuses were included as a

factor in a two-way ANOVA to investigate the relationship

between this demographic factor and correctional officers’

psychological resilience. The F value of .776 was less than the F-

Critical value of 4.05 and resulted in a failure to reject the null

hypothesis. The P-value (.383) was greater than .05, which

indicated that the finding was not significant. Overall, correctional

officers who were not married reported a slightly higher level of

psychological resilience (M = 30.585) than correctional officers

who were married (M = 29.065) as represented in Table 5;

however, the differences were not large enough to be considered

significant.

Table 5

Means, Std. Error, and F Statistics: Correctional Officers’ Marital

Statuses

Source Married Not Married ANOVA

test

M Std. M Std. F(df)

Resilience 29.065 1.099 30.585 1.330 .776

(1,4)

Note. Significance was indicated as follows: +p < .10; p < .05; p <

.01.

The second two-way ANOVA was conducted with the

independent variables of correctional officers’ gender (male or

female) and race/ethnicity (Black, Latino, or

White), and the dependent variable of correctional officers’

psychological resilience. Using G*Power 3.1.9.2 analysis for

conducting this two-way ANOVA (fixed effects, special, main

effects and interactions with a statistical power of .80, Alpha of

.05, and a medium effect size of .40), a total sample size of 52

participants was appropriate for drawing significant differences

between two variables (gender and race/ethnicity) and within a

total of siz levels (male or female; Black, Latino, or White;

Buchner et al., n.d.; Sheperis, n.d.). Consequently, 27 (51.92%)

participants were male, 25 (48.08%) participants were female, 13

(25.00%) participants were Black, 16 (30.77%) were Latino, and

23 (44.23%) participants were White.

RQ3- Are there differences in psychological resilience

between races/ethnicities among correctional officers?

(DV-Psychological resilience, IV- Race/Ethnicity)

H03 = There will be no differences in psychological

resilience between races/ethnicities among correctional

officers.

H13 = There will be significant differences in psychological

resilience between races/ethnicities among correctional

officers.

Correctional officers’ races/ethnicities were included as a

factor in a Two-way ANOVA to investigate the relationship

between this demographic factor and correctional officers’

psychological resilience. The F value of 2.638 was less than the F-

Critical value of 4.05 and resulted in a failure to reject the null

hypothesis. The P-value (.082) was greater than .05 which

indicates that the finding is not significant. Subset psychological

resiliency means were not significantly different between

correctional officers’ races/ethnicities [Black (M = 27.85); White

(M = 28.83); Latino (M = 31.75)] and are represented in Table 6.

Table 6

Means, Std. Error, and F Statistics: Correctional Officers’

Educational Levels

Source Black White Latino ANOVA

test

M Std. M Std. M Std. F(df)

Resilience 27.85 1.440 28.83 1.088 31.75 1.238 .082

(1,4)

Note. Significance was indicated as follows: +p < .10; p < .05; p <

.01.

100

RQ4- Are there differences in psychological resilience

between genders among correctional officers?

H04 = There will be no significant differences in

psychological resilience between genders among correctional

officers.

H14 = There will be significant differences in psychological

resilience between genders among correctional officers.

Correctional officers’ genders were included as a factor in a Two-

way ANOVA to investigate the relationship between this

demographic factor and correctional officers’ psychological

resilience. The F value of 1.326 is less than the F-Critical value of

4.05 and resulted in a failure to reject the null hypothesis. The P-

value (.256) was greater than .05 which indicates that the finding is

not significant. Overall male correctional officers reported a

slightly higher level of psychological resilience (M = 30.421) than

correctional officers who were not married (M = 28.770) as

101

represented in Table 7; however, the differences were not large

enough to be considered significant

Table 7

Means, Std. Error, and F Statistics: Correctional Officers’ Marital

Statuses

Source Male Female ANOVA

test

M Std. M Std. F(df)

Resilience 30.421 1.044 38.770 .982 .256

(1,4)

Note. Significance was indicated as follows: +p < .10; p < .05; p <

.01.

Summary

The analyses indicated that there are no significant

differences in psychological resilience between correctional

officers’ educational levels, marital statuses, races/ethnicities, and

genders among correctional officers. Chapter 5 presents a summary

of the results and findings of this study. Included in chapter 5 is an

102

interpretation of this study’s findings, a discussion of this study’s

limitations and social implications, and recommendations for

future research.

103

Chapter 5: Discussion, Conclusions, and

Recommendations

Introduction

This study’s purpose was to investigate the potential

relationship between correctional officers’ psychological resilience

and four specific demographic factors. Quantitative research

methodologies were utilized to gather and analyze data collected

via online survey and demographic questionnaire. The online

survey included the CDRISC-10, which assessed the psychological

resilience of participants, and the demographic questionnaire,

which retrieved data about participants’ genders, marital statuses,

races/ethnicities, and educational levels. The targeted data were

collected, and I have provided a detailed account of the findings in

this chapter. In this chapter, I also explain limitations of this study’s

design as well as recommendations for future research efforts.

Interpretation of Findings

This study provides information about relationships between

four demographic factors and correctional officers’ psychological

104

resilience. The statistical analyses in this study indicated that there

were no significant relationships between correctional officers’

levels of education and their psychological resilience, correction

officers’ marital statuses and their psychological resilience,

correctional officers’ races/ethnicities and their psychological

resilience, or correctional officers’ genders and their psychological

resilience.

Level of Education

Grounded in previous literature, this study included the

hypothesis that correctional officers with higher levels of education

would have higher psychological resilience scores. Previous

research efforts focused on academic success and progression as

influenced by psychological resilience had identified the vital role

of personal adaptability (Jimerson et al., 1999). Studies have

suggested that the way individuals respond to and/or cope with

stressful intrusions are key when examining their ability to

maintain effective levels of resilience, and that studying the types

105

of stressors may be less important than focusing on individuals’

responses and/or coping styles (Allan et al.,

2013; Jimerson et al., 1999).

While research identified a significant correlation between

academic success and psychological resilience in first year

university students (Allan et al., 2013), this study’s analyses

showed that differences between correctional officers’ levels of

education and their psychological resiliency means were not

significant. The responses and/or coping styles that assisted

correctional officers to achieve academic success may not be as

effective when dealing with stressful intrusions that occur inside

prison walls. The lack of significant differences between

correctional officers’ levels of education and their psychological

resilience may suggest that the type of stress that correctional

officers face calls for different responses and/or coping strategies.

106

Marital Status

On the foundation that marriage may provide added social

support, I formulated this study’s hypothesis. The hypothesis that

there would be significant differences in psychological resilience

between different marital statuses (married or not married) among

correctional officers was not supported by this study. Previous

research efforts posited that the reciprocal nature of correctional

officers’ psychological resilience and interpersonal relationship

functioning may have provided added insight into the role of the

marital status demographics (Snyder & Lopez, 2009). The

dissolution of marriages has been linked historically with external

stressors, such as work-related stress (Bolger et al., 1989; Repetti,

1989; Schulz et al., 2004). This study’s analyses showed that

differences between correctional officers’ marital statuses and their

psychological resiliency were not significant. Psychological

resilience may not maintain a reciprocal nature when paired with

correctional officers’ interpersonal relationship functioning. While

107

the work-related stressors correctional officers endure may

influence the dissolution of marriages, correctional officers’ marital

statuses had no significant impact on their ability to respond to

and/or cope with work related stress.

Race/Ethnicity

The hypothesis that there would be significant differences in

psychological resilience between races/ethnicities among

correctional officers was not supported by this study. Previous

research posited that race/ethnic discrimination affected

psychological resilience as these factors may contribute to the

depletion of psychological reserves due to chronic exposure or

exposure to a major traumatic discriminatory episode (Pascoe &

Smart Richman, 2009; Williams & Mohammed, 2009). This study

showed that there were no significant differences between the

races/ethnicities entailed in this research as they pertained to

correctional officers’ psychological resilience. Correctional officers

belonging to minority races/ethnicities may be exposed to greater

108

discriminatory acts and have experienced depletions of

psychological reserves; however, in this study their psychological

resilience maintained similar levels to White participants, who are

not considered minorities.

Gender

The hypothesis that there would be significant differences in

psychological resilience between genders among correctional

officers was not supported by this study. Previous literature that

focused on discrimination between genders and psychological

resilience suggested the prevalence in the development of

ineffective coping strategies in those who had been subjected to

gender discrimination (Borrell et al., 2010). The difference

between correctional officers’ genders and their psychological

resiliency means were not significant. Previous literature also

suggested that exposure to chronic discrimination and/or a major

discriminatory event resulted in deficiencies when responding to

and/or coping with psychological stress (Borrell et al., 2010; Luo

109

et al., 2012). This study’s results suggested male and female

correctional officers who participated in this study scored similar

levels of psychological resilience, which may be indicative of their

similar abilities to respond to and/or cope with stress (Campbell-

Sills

& Stein, 2007; Notario-Pacheco et al., 2011).

Limitations of the Study

Prior to the implementation of this study, limitations were

identified and included factors pertinent to the generalizability of

this study’s findings, correctional officers’ potential lack of Internet

access, and the self-report nature of the CD-RISC-10 and

demographic questionnaire utilized to gather participant data. I

analyzed data gathered from 52 participants from two correctional

officer organizations that included the CDCR and the TDCJ. A

major limitation to this study is that it did not involve investigating

differences in psychological resilience between correctional

officers who work for the CDCR versus correctional officers who

110

work for the TDCJ. The relatively small sample size and two

organizations that participants were drawn from has limited this

study’s generalizability. Furthermore, this study only included data

drawn from correctional officers who work in the United States,

and the data produced may not be applicable to correctional

officers working outside of the country. Another limitation

pertinent to the utilization of information yielded from this study is

that it may only be applicable to correctional officers who work

face-to-face with inmates and not those employed in positions that

do not require direct interaction with inmates.

Correctional officers who did not have the necessary access

or the ability to gain access to an online medium utilized in this

study’s data collection (e.g., Facebook,

Survey Monkey Audience, Yahoo Focus Groups, LinkedIn) could

participate via U.S. Postal Service mail correspondence; however,

no participant chose this option. Due to the lack of participants

111

utilizing the U.S. Postal Service option, my ability to analyze data

from those officers who did not have Internet access was limited.

A limitation of this study was its small sample size, which

could have resulted in a sampling bias error. This study’s sample

size may have resulted in a systematic distortion in measuring the

true frequency of any phenomenon due to potential selection bias

and limited random sampling of TDCJ and CDCR correctional

officers. Participant recruitment and data collection occurred over a

relatively short amount of time (approximately 3 weeks), which

could have potentially limited participation from correctional

officers and potentially resulted in sampling process errors.

Individuals who took longer than the approximate 3 weeks to

decide to participate were excluded as this study had already

achieved adequate participation to conduct univariate tests.

Recommendations for Future Research

One recommendation for future research efforts that are

concerned with psychological resilience between different marital

112

statuses may include interpersonal relationships and interpersonal

functioning. Focusing on investigating correctional officers’

interpersonal relationships and functioning could provide

important information pertaining to the role that healthy support

systems occupy in psychological resilience. A longitudinal type

study is recommended to gain further insight into the way

correctional officers’ psychological resilience may fluctuate in

alignment with their perceived interpersonal functioning and/or

marital satisfaction.

Research is also needed to gain a better understanding of the

roles that cultural norms and socioeconomic statuses play in

correctional officers’ utilization of coping strategies and their

reluctance to access mental health services following traumatic

events (Grych et al., 2015). Literature has yet to adequately explain

cultural norms and their influences on acceptable forms of

expression pertaining to stress and coping (Grych et al., 2015).

While people in some cultures are more likely to seek mental

113

health services should they feel it warranted, others may find it

taboo and unaccepted. The organization, delivery, and financing of

services may also contribute to potential correlation between

psychological resilience, socioeconomic statuses, and

access/utilization of mental health services. Groups with limited

social resources and unequal access to mental health services due

to their minority statuses may have greater difficulty responding to

and/or coping with work-related stress.

Implications for Social Change

This study was focused on investigating potential

relationships between correctional officers’ psychological

resilience and four demographic factors. This study found that

there were no significant differences among levels of education,

genders, marital statuses, and races/ethnicities and correctional

officers’ psychological resilience. The social implication drawn

from this study is that demographic factors should not be

considered when determining whether correctional officers are

114

psychologically resilient to perform the respective scope of work.

The information gained from this study implies that the

development of programs that improve correctional officers’

resilience and prevent the onset of psychopathology should be

focused on factors other than races/ethnicities, genders, marital

statuses, and levels of education.

Social change entails an alteration or transformation of

culture and social institutions over a period. This study’s

implication for social change is rooted in a foundation of equality

between various demographics that include races/ethnicities,

genders, marital statuses, and levels of education. It provides

further evidence in support of a nonbiased mechanism that

contributes to growth and strength by recognizing the value in

diversity. The interaction of various demographic factors, such as

those investigated in this study, provides a platform from which to

acknowledge the interdependence needed to grow and strengthen

institutions such as our criminal justice system. This study provides

115

evidence in support of the insignificant differences that exist

between races/ethnicities, genders, marital statuses, and levels of

education as they pertain to correctional officers’ ability to perform

their job duties. It supports the notion that the high turnover rate

facing correctional institutions is not rooted in correctional

officers’ demographics, but may be more attributable to systematic

issues that ultimately affect us all.

Conclusion

I conducted this study seeking to investigate the roles of

gender, race/ethnicity, level of education, and marital status on

correctional officers’ psychological resilience. My motivation was

to identify whether one demographic factor (or a combination of

demographic factors) would have a greater association with

psychological resilience than others. I used the stress-vulnerability

model to help me identify the point at which correctional officers

displayed difficulty responding to and/or coping with adversity.

With this research, I sought to provide insight into demographic

116

factors that might have contributed to a correctional officer’s

ability to effectively respond to and/or cope with high stress

demands.

This study provided inconclusive evidence that any of the

four demographic factors had a relationship to correctional

officer’s psychological resilience and reaffirms the need to

promote equality among levels of educations, genders,

races/ethnicities, and marital statuses when considering candidates’

ability to perform correctional officers scope of work.

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