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Organizational levers for frontline health care employee well-being in long-term care

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Organizational levers for frontline health care employee well-being in long-term care

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Organizational Levers for Frontline Health Care Employee Well-Being in Long-Term Care
by
Cynthia Elaine Baker

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

August 2022

© Copyright by Cynthia Elaine Baker 2022
All Rights Reserved

The Committee for Cynthia Elaine Baker certifies the approval of this Dissertation

Kim Hirabayashi
Mary McNevin
Bryant Adibe, Committee Chair

Rossier School of Education
University of Southern California
2022

iv
Abstract
This study joins the national conversation about COVID-19-related impacts on the beliefs of
frontline health care employees in long-term care (LTC) communities and how their emotional
exhaustion, fatigue, and burnout at work are associated with their perception of less work
effectiveness. The literature supports an organizational employee well-being strategy that
leverages organizational resources to reduce the harmful effects of direct caregiver chronic
distress and long hours, which are negative contributors to the crisis-level employee turnover in
LTC communities nationally. Qualtrics survey data were collected using items adapted from
validated instruments and two work well-being and effectiveness items for before and during
COVID-19 were developed specifically for this study. Social cognitive theory provided the
theoretical foundation for studying this problem’s effects on frontline employees, provision of
quality care, and health organizations. The current study’s findings revealed that during COVID-
19, participants felt emotionally exhausted, fatigued, burnout and regularly held perceptions of
less work effectiveness. Female gender, more hours, and more years of work in LTC
communities showed demographic differences for emotional exhaustion and burnout and
perceptions of less work effectiveness. When considering organizational levers and supervisor
strategies to support well-being, the only statistically significant finding was that participants
reported there were no organizational policies and procedures and no supervisor strategies
offered and none were most effective for supporting their well-being. Participants also reported
their organization’s offered wellness resources and rewards and incentives and supervisor
strategies focused on support and communication. Recommendations include leveraging three
organizational initiatives: LTC frontline employee accessibility to mental health services, nurse
supervisor leadership training and development, and CNA employee empowerment initiatives.

v
Acknowledgements
I want to thank my dissertation chair, Dr. Bryant Adibe, and committee members, Dr.
Kim Hirabayashi and Dr. Mary McNevin, for their support and encouragement to do my best
work for this important study. Thank you to my family for their understanding and support as I
spent many evenings and weekends immersed in this educational process. Thank you to the
excellent faculty, whose members have trained me as a scholar–practitioner and encouraged me
to learn about myself and my positionality while I fully developed as a human-centered leader.
Thank you to Dr. Dennis Hocevar for your instruction about detailed data analysis and IBM
SPSS. Thank you to my amazing study group and in particular, Nan and Amy. We three spent
many Zoom hours studying and writing side by side. We developed an everlasting personal and
collegial friendship, courageously holding each other arm-in-arm through work and life stressors
that were unusually significant during COVID-19. Finally, thank you to the frontline health care
heroes who participated in this study and provided essential health care to residents before and
throughout COVID-19 pandemic.

vi
Table of Contents
Abstract iv
Acknowledgements v
List of Tables ix
List of Figures xi
Chapter One: Introduction to the Study 1
Context and Background of the Problem 1
Purpose of the Project and Research Questions 2
Importance of the Study 3
Overview of Theoretical Framework and Methodology 4
Definitions 6
Organization of the Dissertation 7
Chapter Two: Literature Review 8
Well-Being 8
Hedonic and Subjective Well-Being 9
Eudemonic and Psychological Well-Being 11
Work Environments Influence Employee Well-Being 14
Work Environment Levers for Well-Being 16
Effective Leaders Support Employee Well-Being 20
Transformational Leadership 21
Obstacles to Well-Being at Work 22
Organizational Change Requires Effort From Employees 23
Workplace Stress Creates Disadvantages for Employee Well-Being 24
High-Stress Environments Elevate Emotional Exhaustion and Lead to
Burnout 26
LTC-Specific Employee Well-Being Challenges During COVID-19 30

vii
LTC Employee Demographics as Predictors of Health and Psychological
Risk 31
Severe Implications for LTC Frontline Health Care Employees 33
Theoretical Foundations 34
Summary 36
Chapter Three: Methodology 37
Research Questions 37
Overview of Design 37
Research Setting 38
The Researcher 38
Data Sources 39
Method 39
Participants 40
Instrumentation 42
Data Collection Procedures 44
Data Analysis 45
Validity and Reliability 46
Ethics 46
Chapter Four: Results and Findings 49
Research Question 1: How Has Burnout, Emotional Exhaustion, and
Fatigue Affected Beliefs About LTC Frontline Health Care Employees’
Effectiveness Throughout the COVID-19 Pandemic? 49
Perceptions of Lower Work Effectiveness 50
Emotional Exhaustion, Fatigue, Burnout, and Less Work Resources 54
Correlational Statistical Analysis 57
Research Question 2: What Demographic Differences, if Any, Exist For
LTC Frontline Health Care Employee Perceptions of Emotional

viii
Exhaustion, Fatigue, Burnout, Less Work Resources, and Perceptions of
Less Work Effectiveness During the COVID-19 Pandemic? 59
Research Question 3: What, if Any, Specific Strategies Have
Organizations and Leaders in LTC Implemented That Support the Well-
Being of Their Frontline Health Care Employees During the COVID-19
Pandemic? 62
Summary 66
Chapter Five: Recommendations 70
Discussion of Findings 70
Recommendations for Practice 73
Recommendation 1: Organizational Support for Frontline Health Care
Employees to Obtain Accessible and Individualized Counseling and
Support Groups 74
Recommendation 2: Organizational Support for Upskilling Supervisors
and Career Trajectories to Develop Transformational Nurse Leaders 75
Recommendation 3: Organizational Empowerment of CNA Direct-Care
Employees 76
Limitations and Delimitations 78
Recommendations for Future Research 79
Conclusion 80
References 81
Appendix A: Qualtrics Survey Protocols 97
Appendix B: Personal Demographics ANOVA Table 104
Appendix C: Work Demographics ANOVA Table 106
Appendix D: Personal Demographics ANOVA Table 107

ix
List of Tables
Table 1: Pleasant Affect, Negative Affect, and Life Satisfaction Across Life Domains 10
Table 2: Sociodemographic Characteristics of Participants 41
Table 3: Item-Total Statistical Analysis for Perceptions of Less Work Effectiveness 51
Table 4: Descriptive Statistics for Perceptions of Less Work Effectiveness 52
Table 5: Item-Total Statistical Analysis for Emotional Exhaustion, Fatigue, Burnout, and
Less Work Resources 55
Table 6: Means, Standard Deviations, and Alphas for Independent and Dependent
Variables 56
Table 7: Strength of Relationships between Perceptions of Less Work Effectiveness,
Emotional Exhaustion, Fatigue, Burnout at Work, and Less Work Resources 58
Table 8: Means, Standard Deviations, and One-Way ANOVA for Work Demographic
Characteristics and Perceptions of Less Work Effectiveness 60
Table 9: Frequencies by Category for Organizational Policies or Practices and Most
Effective 64
Table 10: Frequencies by Category for Supervisor Strategies and Most Effective 66
Table B: Means, Standard Deviations, and One-Way ANOVA for Personal Demographic
Differences and Relationship to Perceptions of Less Work Effectiveness 104
Table C: Means, Standard Deviations, and One-Way ANOVA for Work Demographic
Differences and Relationship to Emotional Exhaustion, Fatigue, Burnout, and
Less Work Resources 106

x
Table D: Means, Standard Deviations, and One-Way ANOVA for Personal Demographic
Differences and Relationship to Emotional Exhaustion, Fatigue, Burnout, and
Less Work 107

xi
List of Figures
Figure 1: Social Cognitive Theory’s Application to the Current Study 36
Figure 2: Perceptions of Less Work Effectiveness Histogram for Frequency Distribution 54
1

Chapter One: Introduction to the Study
The COVID-19 pandemic has created high levels of occupational stress in long-term care
(LTC) nursing homes, leading to a negative impact on the well-being of frontline health care
employees. The purpose of this study was to examine employee beliefs about the impacts of
COVID-19 and identify implemented organizational policies and leadership practices that may
have positively affected the well-being of frontline health care employees in LTC. Greene and
Gibson (2021) identified significant challenges related to COVID-19 for frontline health care
employees, including increased risk of exposure and severe illness from COVID-19, significant
risk of emotional fatigue and psychological distress, and clinically significant mental health
concerns (Carey et al., 2020). Scientific American (Lewis, 2021) analyzed data from the Centers
for Medicare & Medicaid Services (CMS) and U.S. Bureau of Labor Statistics (BLS) and
concluded that in 2020, deaths of nursing home staff members ranked among the highest,
averaging 80 deaths per 100,000 in the United States, making working in nursing homes one of
the most dangerous jobs in 2020. LTC communities also experienced significant direct-care
staffing shortages and high employee turnover, affecting the quality of care for older adult
residents (Dreher et al., 2019). Specifically, the median turnover rate for certified nurse assistants
(CNAs) was 51.5%, representing the most limited likelihood of advancing in their careers
(Denny-Brown et al., 2020). This chapter first provides contextual evidence and background
regarding this problem.
Context and Background of the Problem
The setting for this field study was skilled nursing communities that provide nursing care
and personal care support. The participants for this study were frontline health care staff
members in LTC, including nurse assistants (NAs), CNAs, licensed practical nurses (LPNs), and
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registered nurses (RNs), who were the direct care providers for residents of LTC nursing homes
and the most likely to have unmediated contact with COVID-19 and experience emotional
exhaustion, fatigue, and burnout. Nationally, LTC employs a majority of the workforce with less
education, lower skills, and lower wages.
Nursing facilities employ 1.2 million frontline health care personnel and support workers
nationally (Denny-Brown et al., 2020). Unlike other medical settings, LTC heavily employs NAs
and CNAs (64%), including the majority of less-educated, lower-skilled, and lower-paid
workers. CNAs and NAs typically provide 90% of the hands-on care in nursing homes, including
assistance with bathing, dressing, and eating (Denny-Brown et al., 2020). Direct care positions in
LTC nursing homes are primarily held by people who are female (83%) and do not have a
bachelor’s degree (77%); Black people are disproportionately represented (23.7%), and almost
one third (30.8%) have a household income less than twice the poverty level (Greene & Gibson,
2021). LPNs (22%) and RNs (12%) were included in this study, but they are less prevalent in
this setting as in other medical settings. LPNs and RNs fill the most skilled frontline health care
positions in clinical care, medication prescribing, and nurse leadership (Denny-Brown et al.,
2020).
Purpose of the Project and Research Questions
The purpose of this study was to examine employee beliefs about the impacts of COVID-
19 on their work effectiveness and identify organizational policies and supervisory practices
implemented during the COVID-19 pandemic that may have positively affected the well-being
of frontline health care employees in LTC. The research questions focused on LTC frontline
health care employees’ beliefs about the impacts of emotional exhaustion, fatigue, and burnout
3

on their work effectiveness and the specific strategies, if any, that organizations implemented to
support their well-being during COVID-19.
1. How has burnout, emotional exhaustion, and fatigue affected beliefs about LTC
frontline health care employees’ effectiveness throughout the COVID-19 pandemic?
2. What demographic differences, if any, exist for LTC frontline health care employees’
emotional exhaustion, fatigue, burnout, less work resources, and perceptions of less
work effectiveness during the COVID-19 pandemic?
3. What, if any, specific strategies have organizations and leaders in LTC implemented
that support the well-being of their frontline health care employees during the
COVID-19 pandemic?
Importance of the Study
This study is important because the COVID-19 pandemic has created high levels of
occupational stress for frontline health care workers, resulting in emotional exhaustion, fatigue,
and burnout that caused reduced job satisfaction, high turnover, and crisis-level staffing
shortages in LTC nursing homes (American Health Care Association, 2021; Carey et al., 2020;
Lee-Baggley & Thakrar, 2020). For frontline health care employees with unmediated contact
with COVID-19, pressure factors and demands are at critical levels.
The pandemic is causing significant psychological pressure, cognitive overload, and high
negative emotions for those on the front line of treatment, testing and infection control, and
personal care for sick patients with the virus (Carey et al., 2020). Stress-related demands without
needed resources such as personal protective equipment caused additional pressure factors when
employees experienced compromised health due to COVID-19. Unmet resource demands cause
emotional fatigue, lack of personalization, and low professional satisfaction (Prada-Ospina,
4

2019). Over time among health care professionals, work-related stressors often lead to symptoms
of burnout and may result in moral injury (Lee-Baggley & Thakrar, 2020). COVID-19 illness
and burnout symptoms have caused crisis-level staffing shortages and turnover, affecting LTC
nursing homes’ ability to provide quality care to residents.
The supply of frontline health care individuals who work in LTC is declining just as the
aging population is growing worldwide. In 2020, the Centers for Disease Control and Prevention
(CDC) reported 15,600 nursing homes in the United States with 1.7 million licensed beds
occupied by 1.4 million LTC patients. By 2050, the Administration on Aging (2021) predicted
the 43.1 million adults aged 65 or older in 2012 will almost double to 83.7 million, with 27
million people requiring some kind of LTC nursing or community services. In 2021, the federal
government also reported historic declines in the birth rate, leading to increased concern about
whether there will be enough caregivers to support an aging America (Administration on Aging,
2021). Salsberg and Martiniano (2018) projected a 14.3% increase in demand for frontline LTC
employees by 2026, with more than 260,000 personal care aides, 135,000 RNs, and 113,000
CNAs needed annually to fill new or vacant positions. As the need grows for essential frontline
workers, frontline LTC employees face many obstacles in their day-to-day jobs that are linked to
high turnover rates. High turnover rates affect the quality of care, increase challenging behaviors
among residents, and elevate indicators of poor quality of life (Dreher et al., 2019; Eaton et al.,
2020; Lerner et al., 2014).
Overview of Theoretical Framework and Methodology
The theoretical framework was front and center in justifying the research questions,
problem, and significance of this study and determining the research design and analysis plan.
The theoretical framework is explained by Grant and Osanloo (2014) as much like the design of
5

a house and conceptually, the framework provides a foundation that is evident throughout the
study process. This problem is best studied utilizing social cognitive theory (SCT). SCT explains
human functioning as a reciprocal triad in which the person, behavior, and environmental factors
operate as interactive determinants of one another (Bandura, 1977, 2002, 2004; Manjarres-
Posada et al., 2020). This theory maintains that people are not driven by internal forces or
automatically configured and controlled by external stimuli, but rather by a reciprocal interaction
with organizational facilitators or impediments in their environment (Bandura, 2004). SCT also
provides a human agency component and reciprocal accountability binary between the employee
and the LTC organization that affects resident care and outcomes. All three stakeholders would
benefit from an effective resolution of this problem. SCT’s unique approach to social contextual
pathways recognizes the social origins of human thought and action (Manjarres-Posada et al.,
2020). Because SCT is based on a person, behavior, and environment triad, it can frame most
social science problems.
Although researchers have not used SCT specifically in the LTC environment and it is
not a health care-specific theory, it can be utilized in most fields. Manjarres-Posada et al. (2020)
described SCT as a nondisciplinary theory that provides necessary elements that facilitate the
understanding of human behavior, including inherent aspects of the interactions of the individual
nurse practitioner in the provision of care. Their research is relevant to the current study, because
SCT is applied multidirectionally to the nursing relationship with the patient, targeted healthy
behaviors, and environmental factors (Majarres-Posada et al., 2020). SCT aligns with the
conceptual framework for this study, as discussed in Chapter 2.
The research method for this study was a nonexperimental field study with data collected
via a quantitative survey instrument. Quantitative inquiry involves the process of collecting,
6

analyzing, and interpreting study data (Creswell & Creswell, 2018). The data analysis was
descriptive and correlational. Standardized tools were adapted for emotional exhaustion and
fatigue. Burnout was measured via an established instrument. I developed questions related to
well-being, effectiveness, supervisors or leaders, and organizations for this study with assistance
from a thematic dissertation group. The research methods are presented in detail in Chapter 3.
The following terms appear throughout the dissertation.
Definitions
The World Health Organization (WHO; 2019) defined burnout as a syndrome
conceptualized as resulting from chronic workplace stress that has not been successfully
managed and is characterized by feelings of energy depletion or exhaustion; increased mental
distance from or feelings of negativism or cynicism related to one’s job; and reduced
professional efficacy.
Emotional exhaustion is a state of feeling emotionally worn out and drained as a result of
accumulated stress from personal or work lives or a combination of both. Emotional exhaustion
is one sign of burnout. People experiencing emotional exhaustion often feel like they have no
power or control over what happens in life. They may feel “stuck” or “trapped” in a situation
(Cafasso, 2021).
Fatigue refers to physical or mental exhaustion or both that can be triggered by stress,
medication, overwork, or a mental and physical illness or disease. Fatigue can also trigger
serious mental exhaustion. Persistent fatigue can cause a lack of mental clarity or feeling of
mental “fuzziness,” difficulty concentrating, and in some cases, memory loss (Gale Encyclopedia
of Medicine, 2008).
7

A long-term care nursing home is a place for people who do not need to be in a hospital
but cannot be cared for at home and need to live in a 24-hour care facility. Nursing homes
provide a wide range of health and personal care services based on residents’ medical needs
(U.S. National Library of Medicine, 2021).
Well-being is defined as how well individuals are doing in life, including social, health,
material, and subjective dimensions of well-being (Dodge et al., 2012).
Subjective well-being includes individual beliefs, psychological and mental states, and
behaviors; is a specific facet of well-being that captures how people evaluate their lives; and
reflects an overall evaluation of the quality of a person’s life from their perspective (Diener &
Ryan, 2009).
Organization of the Dissertation
The first chapter describes the current study. The second chapter provides a
comprehensive review of the literature, including definitions of well-being, work environments
and organizational levers that influence employee well-being, and obstacles to well-being such
as organizational change, chronic stress, burnout, and COVID-19-related challenges specific to
frontline health care employees in the LTC sector. I developed a personal conceptual framework
and visual representation using SCT. Chapter 3 contains the research questions, methods, and
settings for the study. Chapter 4 describes the data analysis and findings, and Chapter 5 provides
recommendations based on the current study findings linked to past literature and the conceptual
framework.

8

Chapter Two: Literature Review
Well-Being
For many years, well-being did not appear to have a holistic definition, nor was it an
individualized area of study. The WHO (1978) first referenced well-being at the 1948
International Health Conference as a key word in its definition of health: “A state of complete
physical, mental, and social wellbeing and not merely the absence of disease or infirmity” (p. 1).
Since this definition was published, other definitions of well-being seemed to depend on the
subdomain of social science. Health scholars identified more physical characteristics of well-
being, whereas psychology and occupational psychology scholars focused on the subjective
individual view of well-being. More integrated definitions were needed to justify well-being as a
necessary field of study and practice and to apply it holistically to multiple areas of life.
Danna and Griffin (1999) defined well-being as the state of an individual’s mental,
physical, and general health, in addition to experiences of satisfaction both at and outside of
work. More recently, Nielsen et al. (2017) adopted Danna and Griffin’s broad definition and
added that employee well-being is influenced by the pleasure or displeasure derived from their
job and interactions with colleagues, teammates, and supervisors. Employee well-being features
both psychological outcomes such as low levels of distress, anxiety, and emotional exhaustion
and physiological outcomes such as blood pressure, heart condition, and general physical
exhaustion (Nielsen et al., 2017). Sivanthan et al.’s (2004) definition is also inclusive of health
and psychological aspects of well-being and is composed of physical (e.g., general health,
occupational safety, health-related behaviors) and psychological (e.g., mental illness, stress, self-
efficacy, self-esteem, affective well-being) health at work. Individuals’ beliefs about the quality
of their lives are integral to defining well-being. Hedonic well-being, later known as subjective
9

well-being (SWB), and eudemonic or psychological well-being (PWB) are related and
significant to the current study.
Hedonic and Subjective Well-Being
Hedonic well-being is defined as a person’s well-being derived from pleasure, lowered
by pain, and affected by the pursuit of happiness and pleasant life (R. Ryan & Deci, 2001).
Hedonic well-being is subjective, and scholars have included physical, cognitive, and emotional
pleasure in this definition. Moods and emotions together describe affect, and researcher
Bradburn (1969) determined that affective components of hedonic well-being should be
considered separately. A higher level of hedonic well-being depends on the presence of positive
affect, the absence of negative affect, and the cognitive evaluation of life satisfaction (Bradburn,
1969; Diener et al., 1999). Their three-fold structure of positive affect, negative affect, and life
satisfaction was repeatedly confirmed in studies that followed (Diener et al., 1999, 2018; Diener
& Ryan, 2009; Lucas et al., 1996; Quick & Henderson, 2016; R. Ryan & Deci, 2001).
As shown in Table 1, Diener et al. (1999) hedonic well-being constructs were combined
into the SWB phenomena with components of (not momentary) pleasant affect, unpleasant
affect, and impacts on life satisfaction across life domains.

10

Table 1
Pleasant Affect, Negative Affect, and Life Satisfaction Across Life Domains
Pleasant affect Unpleasant affect Life satisfaction Domain
Joy Guilt and shame Desire to change life Work
Elation Sadness Satisfaction with
current life
Family
Contentment
Pride
Anxiety and worry
Anger
Satisfaction with
past
Leisure
Health
Affection Stress Satisfaction with
future
Finances
Happiness Depression Significant other’s
views of one’s life
Self
Ecstasy Envy Group membership

Note. This table was adapted from Deiner et al. (1999) and shows the components of SWB and
how affect and life satisfaction interact with life dimensions.

SWB includes the individual beliefs, psychological and mental states, and behaviors that
are also crucial to holistic well-being (Diener & Ryan, 2009; Diener et al., 2015, 2018; Dodge et
al., 2012; Tenney et al., 2016). SWB researchers believe that social indicators alone do not
determine the quality of life. People react differently to the same circumstances and evaluate
situations based on their unique expectations, values, and experiences (Diener et al., 1999). SWB
is a specific form of well-being that captures how people evaluate their lives and reflects an
overall evaluation of the quality of a person’s life from their perspective. The descriptor
“subjective” defines the scope of the construct as the extent to which a person believes or feels
that their life is going well. Although this form of well-being is subjective and based on a
11

person’s experience, manifestations of SWB can be measured objectively through verbal and
nonverbal behavior, actions, biology, attention, and memory (Diener & Ryan, 2009; Diener et
al., 2018). Improved well-being via positive affect and life satisfaction significantly improves
several areas of life.
Growing evidence suggests that positive SWB that includes life satisfaction significantly
improves life in the four areas of health and longevity, work and income, social relations, and
societal benefits (Diener & Ryan, 2009; Diener et al., 2015, 2018; Tenney et al., 2016). Diener et
al. (2018) also defined a related term, emotional well-being, as people’s positive moods and
emotions and low levels of negative moods and emotions. The term not only reflects momentary
enjoyment but also movement toward goals that are congruent with a person’s motives. In
addition, emotional well-being is thought to include resilience after bad events and the ability to
express various emotions that are functional and appropriate to the situation (Diener et al., 2018).
A related but distinct form of well-being is eudemonic well-being.
Eudemonic and Psychological Well-Being
Eudemonic well-being centers on meaning and self-realization and conceptualizes well-
being as a person’s ability to fully function (Huppert & So, 2011; Quick & Henderson, 2016; J.
Ryan et al., 2021). Carol Ryff (1989) drew on the works of Aristotle and her professional
training as a lifespan developmental psychologist to develop the now well-studied eudemonic
model named PWB. Ryff sought to challenge prevailing perceptions of well-being that focused
on assessments of feeling good, contentment, and life satisfaction. Instead, PWB is explicitly
concerned with the development and self-realization of the individual, construed as growth and
human fulfillment that are profoundly influenced by the surrounding contexts of people’s lives,
and recognizes that opportunities for self-realization are not equally distributed (Ryff, 1989).
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Eudemonic well-being may be consequential for health by promoting the effective
regulation of multiple physiological systems. Ryff developed six core dimensions of PWB: (a)
self-acceptance of personal strengths and weaknesses; (b) positive relations to others, e.g.,
warmth and empathy; (c) personal growth, e.g., continually developing one’s potential; (d)
meaning and purpose in life; € environmental mastery, e.g., acting on or changing the
environment; and (f) autonomy, e.g., self-determination or independence (Ryff, 1989; Ryff &
Singer, 2008). The authors noted that autonomy is the most culturally Western-based dimension.
PWB seems the most well-rounded well-being model that includes internal thoughts and actions
and relational dimensions that provide a pathway for human growth rather than a state of well-
being (Ryff & Singer, 2008). Other scholars have studied and compared Ryff’s PWB and SWB.
Keyes et al.’s (2002) cross-sectional study first identified contrasting definitions:
“Subjective well-being (SWB) is evaluation of life in terms of satisfaction and balance between
positive and negative affect; psychological well-being (PWB) entails the perception of
engagement with existential challenges of life” (p. 1007). Although both approaches assess well-
being, they address different features of what it means to be well: SWB involves more global
evaluations of affect and life quality, whereas PWB examines perceived thriving vis-à-vis the
existential challenges of life (e.g., pursuing meaningful goals, growing and developing as a
person, establishing quality ties to others). Both perspectives bring to mind Aristotle’s view of
eudaimonia, which although commonly translated as happiness, is more accurately characterized
as striving toward realization of one’s true potential (Keyes et al., 2002). With their differences,
SWB and PWB may be useful jointly. For example, higher SWB may help preserve positive
feelings when PWB is not possible because of a lack of opportunities, lack of resources, or
compromised personal health and vitality. Alternatively, the high demands of striving to make
13

the most of one’s talents may undermine SWB but boost PWB. Using Keyes et al.’s (2002)
contrasting definitions of SWB and PWB, Chen et al. (2013) further concluded that SWB and
PWB are both concerned with the positive aspect of psychological functioning and it is important
to examine both types of well-being to identify commonalities and distinctions. Chen et al.’s
study used a bifactor model to understand the SWB and PWB relationship. The findings
combined SWB and PWB to form a general factor of global well-being (Chen et al., 2013).
Individual self-evaluation and perceptions of well-being are complex, and complexity is central
to its many definitions. More commonly, scholars have studied SWB and PWB as individual
dimensions.
Quick and Henderson (2016) utilized prior definitions from Diener and Seligman (2004)
that defined well-being as “peoples’ positive evaluations of their lives, (which) include positive
emotion, engagement, satisfaction, and meaning” (p. 6). Quick and Henderson and other scholars
expanded the two overarching factors—hedonic (feeling good) and eudemonic (functioning well)
well-being—into multidimensional approaches to defining well-being. J. Ryan et al. (2021)
agreed with Quick and Henderson (2016) that workplace health and well-being interventions
should target and measure the change in two key dimensions: physical and PWB outcomes. This
aligns with the WHO’s (1978) definition of well-being that includes physical and psychological
characterizations of well-being. Researchers have differed, though, regarding the specific facets.
For example, Swarbrick (2006) proposed that well-being consists of a balance among eight
interconnecting dimensions, including: social, emotional, environmental, financial, intellectual,
occupational, physical, and spiritual well-being (Swarbrick, 2006). One group of scholars
recognized that most well-being research has been driven by dimensions and descriptions of
well-being rather than defining it.
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Dodge et al. (2012) defined global well-being as “how well individuals are doing in life,
including social, health, material, and subjective dimensions of well-being” (p. 230). Based on a
review of the prior well-being literature, they adapted a well-being conceptual model in which
resources versus demands affect well-being using a seesaw analogy with well-being at its center,
representing the drive of an individual to return to a set point for well-being. On each end of the
seesaw are resources and challenges that raise or lower individual well-being (Dodge et al.,
2012). The current study used this definition of well-being to acknowledge that employee well-
being is affected by personal, behavioral, and environmental challenges and resources in an
equilibrium. Well-being is not a state of being that remains the same only based on self-
perceptions, but also increases and decreases based on environmental resources and challenges.
Work Environments Influence Employee Well-Being
Well-being is important to organizations and worthy of further study. In 2019, well-being
was the top-ranked trend of organizational importance. Deloitte’s (2020) Annual Human Capital
Survey included 9,000 organization leaders and human resource executives, and 80% responded
that well-being is an important or very important priority for their organization’s success.
Ninety-six percent of respondents agreed that well-being was an organizational responsibility,
and large employers in the United States spent an average of $3.6 million on well-being
programs, at a cost of $762 per employee annually (Deloitte, 2020). To ignite organizational
support for well-being, frameworks have been developed to strengthen the link between
employee perceptions of well-being and organizational performance.
Tenney et al.’s (2016) review of prior research led to the development of a new
framework for strengthening the indirect connection among employee perceptions of well-being,
behavior, and organizational performance (e.g., productivity and profitability). They proposed
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that the path between SWB and performance is indirect, operating through multiple mediators. In
this model, individuals experiencing SWB have low stress, anger, and sadness and frequent
positive feelings, and high job satisfaction. Increased SWB may result in the following
outcomes: (a) better health, (b) lower absenteeism, (c) better self-regulation, (d) stronger
motivation, (e) enhanced creativity, (f) positive relationships, and (g) lower turnover, which can
result in increased individual and organization productivity and profitability (Tenney et al.,
2016). Some researchers have found connections between organizational resources and improved
well-being.
Nielsen et al. (2017) defined organizational resources as “anything perceived by the
individual to help attain his or her goals” (p. 102). Resources in this context enable employees to
complete their tasks and goals, enhance well-being, and increase their capacity to perform well
(e.g., employee effectiveness). Nielsen and colleagues conducted a review of the human
resources management data and organizational psychology literature from 2003 to 2015,
resulting in a meta-analysis of 84 quantitative studies examining which amount of resources at
the individual, group, and organizational levels was most effective in predicting employee well-
being, performance, and psychologically healthy workplaces. They defined psychologically
healthy workplaces as workplaces where resources at the individual, group, leader, and
organizational levels were promoted to ensure employee well-being and performance (Nielsen et
al., 2017, p. 102). These resources were: (a) teamwork structures that can be implemented to
build social capital (group-level resource); (b) autonomy (organization-level resource) that may
be supported by training employees in problem-solving (an individual resource); and (c) leaders
with transformational leadership skills (a leader-level resource). These researchers found no
major differences in effectiveness among individual, group, leader, and organizational levels and
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recommended providing resources at multiple levels depending on employee needs (Nelson et
al., 2017). Work environments have work-related levers to support employee well-being.
Work Environment Levers for Well-Being
When employees had some control and autonomy over how to do their jobs, they were
less exhausted and demonstrated improved well-being (Sonnentag, 2015). Job control helped
employees deal effectively with their job demands and reduce negative outcomes. Job control
and autonomy combined have been consistently associated with lower anxiety and depression,
stress, and burnout and higher job satisfaction, and better employee health. Cooper (2014) and
Day et al. (2017) agreed about the importance of job control.
Day et al. (2017) identified examples of job control that included offering employees
more control over (a) their scheduling and work hours (e.g., flex time), (b) their workspace, and
how they do their job and (c) improving supervisor support help to improve an employee’s sense
of control. Cooper (2014) concluded that workplace control plays a vital role in positive
employee outcomes and well-being. Job control may be defined as primary control or secondary
control. Primary control is defined as the extent a person can affect (act) on the environment or
workplace. Secondary control is how the person can control (think about) their response to the
environment. Having perceptions of control provides more certainty that the severity of an
adverse event can be kept within tolerable limits. Job control is important for buffering the ill-
effects of adverse environmental conditions. Components of job control such as autonomy,
participation in decision making, perceived control, locus of control, self-efficacy, and
empowerment are precursors of positive employee outcomes and well-being, whereas low levels
of job control contribute to both physical illness such as cardiovascular disease and
psychological distress (Cooper, 2014). Autonomy is more than a component of job control.
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Autonomy’s definition is distinguished from job control as referring to control over how,
when, and where job tasks are performed (Day et al., 2017; Sonnentag, 2015). Having autonomy
is associated with improved psychological health. Although autonomy is often studied as one
construct, Cooper (2014) identified types of autonomy including method autonomy (control over
how job tasks are done), schedule autonomy (control over the hours worked), and criteria
autonomy (control over goals and which tasks are done). Although autonomy and job control are
important, researchers’ findings identified social support as also important to work
environments.
Aligned with the contentions of earlier scholars, social support is also a positive factor in
the workplace. Employees who received social support from coworkers and supervisors
experienced better well-being than those who lacked social support (Sonnentag, 2015). Social
support is an important environmental consideration for employee well-being, and researchers
have provided evidence that various kinds of instrumental social and emotional support provide
benefits for health, mental health, and happiness (Sarason et al., 1990). Their study revealed
support for the view that social exchanges affect well-being through negative affect and
psychological symptoms. Social support has strong links to the perception of SWB based on a
multimethod analysis of prior research on well-being (Diener et al., 2018; Kansky & Diener,
2017). Their cross-cultural study identified three key elements of well-being: (a) positive
feelings, (b) social relationships, and (c) social support. Positive feelings are associated with
valuing and engaging in affiliations and the amount of time spent interacting with others.
Individuals with high positive affect are more social and have higher-quality relationships with
others. Happy individuals report having more friends, having closer friends, engaging in more
social activities, and spending more time talking with others compared to their less happy
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counterparts. One caveat is that the link between well-being and sociability matters more in
cultures where sociability is highly valued (Kansky & Diener, 2017). Employees’ perception of
organizational support may have strong impacts on reducing emotional and cognitive burdens.
Perceived organizational support is associated with increased job satisfaction and reduced
stress (Eisenberger et al., 2020). Eisenberger and colleagues conducted a meta-analysis of 317
studies and a qualitative review of the literature on perceived organizational support. Findings
suggest it may be useful in reducing the emotional and cognitive burdens felt by employees
when jobs are stressful or distressing. The strong relationship between fairness (and other
antecedents) and perceived organizational support indicates that organizations can readily
enhance their exchange relationship with employees by providing favorable treatment. In
addition, employee input and transparency during the employee selection process and adaptation
to the new job may help organizations develop high perceptions of organizational support among
employees (Eisenberger et al., 2020). Fairness, employee input, and transparency are useful
organizational supports to reduce emotional and cognitive burdens. A positive work environment
presents opportunities for improved employee well-being.
Positive work climates affect psychological needs and employee well-being. To reduce
the negative impact of controlling work climates, Schultz et al. (2015) recommended manager
autonomy and mindfulness. Schultz and colleagues’ quantitative online survey, completed by
259 employees, indicated that both autonomy support and mindfulness had direct relations with
employee work well-being. Work climates with less autonomy thwarted employees’ basic
psychological needs at work, which partially explained the association of lower autonomy
support at work and decreased work adjustment (Schultz et al., 2015). Strong purpose improves
positive employee adjustment to organizational change.
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Organizations expose people to greater levels of uncertainty and change (Cooper, 2014).
Staying connected to a strong purpose can not only help individuals cope but also improve their
ability to react positively to organizational change when framed by fundamental goals and
anchored in the organization’s mission. An emphasis on well-being requires senior-level vision
and ownership, coherent communication, and individual and organizational strategy
implemented across the organization. Cooper (2014) identified strategies across three stages that
act as predictors of improved employee well-being.
First, at the broad organizational level, are early stage well-being strategies to reach a
wide range of employees. Early stage organization-wide interventions have the most potential to
improve employee well-being via flexible work options, reviews of work planning processes and
job design, scenario planning to reduce uncertainty, and teamwork interventions targeted at
improving interpersonal relationships. Second, mid-stage group-level interventions address
situational or interpersonal factors with skills training such as time management and
assertiveness training. Resilience coaching is also a mid-stage group intervention that is intended
to prepare employees for future uncertainty and challenges, but it risks overemphasizing that
individuals need to “toughen up” versus addressing larger organizational issues. Finally, late-
stage individual interventions are reactive and mainly treat adverse symptoms rather than
addressing root causes. Examples of late-stage individual interventions include counseling and
cognitive behavioral therapy. Such individual support is often provided in large organizations in
the form of employee assistance programs. Typically, this service provides a confidential
gateway to support when employees are experiencing challenges that will benefit from
counseling and other psychological therapies (Cooper, 2014). Direct supervisors can identify
employee needs. Effective leadership is another environmental lever for employee well-being.
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Effective Leaders Support Employee Well-Being
The level of leader effectiveness can positively or negatively affect employee well-being.
Skakon et al. (2010) concluded from a systematic review of 49 studies that leaders may affect
their subordinates’ well-being through different paths. Leaders act as role models for their
subordinates and can model (un)healthy and (un)safe working practices. Leaders’ power to
reward or punish their subordinates assumes considerable importance for employee well-being.
Decision leaders can produce additional stress for their subordinates (e.g., assigning an
abundance of tasks to one employee can result in role overload). Leaders can enhance the quality
of individual work experiences (Skakon et al., 2010). Leaders can increase or reduce employee
well-being depending on the style of leadership.
Leadership styles influence employee stress and affective well-being. Kelloway and
Barling (2010) defined leadership as “a process of social influence that is enacted by designated
individuals who hold formal leadership roles in organizations” (p. 261). Three types of
leadership styles have been described: abusive, laissez-faire, and transformational. Abusive
leadership can lead to emotional exhaustion and burnout (Kelloway & Barling, 2010; Skakon et
al., 2010). Supervision and employee emotional exhaustion were intensified for employees
susceptible to emotional abuse, even when coworker support was high. In contrast, laissez-faire
leadership is a passive management style in which leaders are disengaged and often avoid and
deny responsibility, even in the face of dire situations. Laissez-faire leadership negatively
affects employees’ PWB because it increases workplace stressors (e.g., role conflict, role
ambiguity, conflict with coworkers, bullying at work) and decreases trust in leaders.
Transformational leadership includes four behaviors: idealized influence, inspirational
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motivation, intellectual stimulation, and individualized consideration (Kelloway & Barling,
2010; Kelloway et al., 2012; Skakon et al., 2010).
Transformational Leadership
Transformational leadership is associated with opportunities for positive work
experiences for employees, which result in PWB (Arnold, 2017). A computerized search of
literature from 1980 to 2015 identified 40 empirical research articles that determined the
relationship between transformational leadership and employee PWB (Arnold, 2017).
Transformational leadership is inherently positive because of its focus on four components: (a)
ethical behavior (idealized influence), (b) elevating employees’ motivation (inspirational
motivation), and (c) encouraging and allowing employees to think for themselves (intellectual
stimulation), and (d) demonstrating real concern for individuals’ needs (individualized
consideration). Transformational leaders provide role clarity and meaningful work and enable
employees to develop self-efficacy and trust in their leaders, all of which positively affect
employee well-being. These findings support frameworks that include job resources or demands
as moderators between leader effectiveness and employee well-being (Arnold, 2017) and
employee trust in leaders as a mediator of well-being (Kelloway et al., 2012). Arnold’s study
also identified the need to continue studying leadership style as a job resource or demand that
affects employee well-being.
Transformational leadership style has positive effects on well-being, and other scholars
agreed it helps prevent negative symptoms of low well-being including mental health problems.
Kelloway and Barling (2010) and Kelloway et al. (2012) examined mental health as an indicator
of psychological health and showed that transformational leadership was directly related to
reduced depressive symptoms and indirectly related to employee mental health through its
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positive effects on employees’ sense of community in the workplace. Kelloway et al.’s findings
went further, showing that established trust in a leader is a mediator of employee well-being and
determining how such effects occur, including how different types of leadership behavior exert
an effect on trust and ultimately affect well-being. These findings indicate that transformational
leadership can reduce mental health symptoms and prevent emotional exhaustion and burnout.
Leaders in organizations affect employee well-being, and low well-being is defined as a
workplace issue.
Obstacles to Well-Being at Work
Low employee well-being is a workplace problem. Of 1,500 survey respondents from 46
countries, 86% reported their well-being had declined and 89% reported that their well-being is
challenged at work, underscoring how well-being at work is a significant problem to address
(Moss, 2021). Other studies suggested a significant disconnection between workers’ and
employers’ prioritization of well-being at work. Notably, Deloitte’s (2020) survey identified a
disconnection between employers and workers when prioritizing well-being in work
transformation efforts, especially during COVID-19. Workers’ top three objectives of work
transformation were improving quality, increasing innovation, and improving worker well-being.
Senior executives ranked their top three objectives as improving the customer experience,
increasing innovation, and reducing costs. Employers and workers had a significant discrepancy
in prioritizing improving worker well-being. Employers ranked employee well-being as the
eighth priority in 2021, dropping from the top employer priority in 2019.
Deloitte (2021) also recommended high-level employer strategies to improve worker
well-being at the individual, team, and organizational levels focused on cultural, relational,
physical, and virtual designs. Fostering well-being through inclusive social behaviors and norms;
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management policies, processes, and programs; redesigning the physical workspace; and new
technologies through virtual workspaces are examples of organizational strategies to improve
worker well-being (Deloitte, 2021). These high-level approaches are a starting point for making
employee well-being an organizational priority. Organizational change can promote or reduce
employee well-being.
Organizational Change Requires Effort From Employees
Organizational changes are often unavoidable, but negative employee outcomes from
change are preventable (Day et al., 2017). Organizational change is a job demand that requires
effort and may hurt employee PWB. Organizational change is correlated to lower self-rated
health and higher use of stress-related medications. Day and colleagues (2017) examined the
impact of organizational change on employee burnout among health care professionals in the
middle of an organization-wide change initiative related to health care spending in the Canada
Health District. The scholars also examined whether a positive work environment (involving
high supervisory support and job control) may be associated with more positive outcomes and
mitigated the negative effects of change in the workplace. Study respondents who reported high
levels of supervisor support indicated the support helped them through change-related stressors.
Employees who reported low supervisor support indicated that the lack of support contributed to
their change-related stressors and indicated higher levels of change-related stressors associated
with higher levels of burnout (i.e., higher levels of emotional exhaustion and cynicism and lower
levels of professional efficacy). Positive work environments that are supportive and provide
autonomy are associated with more positive employee outcomes and can buffer negative
outcomes resulting from change (Day et al., 2017). The anticipation stage of organizational
change, when mismanaged, has challenging effects on employees.
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Guidetti et al. (2018) concluded that organizational change processes are often related to
a fear of loss of resources and an increase in job demands that affect well-being. They aimed to
study the consequences of the organizational change process on employee well-being and to
examine understudied employee reactions to anticipated change. The authors concluded that
organizational change was highly correlated with a sense of uncertainty that may lead to a
lessened sense of control over events, psychological discomfort, intention to leave the
organization, and job dissatisfaction (Guidetti et al., 2018). As evidenced by Pollard (2001),
uncertainty reaches the highest levels during the anticipation stage of organizational change,
relating to an increase in cardiovascular diseases, psychological health problems, and arousal of
tension. The stressor–strain relationship has been widely studied during the implementation and
aftermath change phases, whereas only a few studies have been conducted during the
anticipation stage, which represents the more stressful and uncertain phase for employees.
During this period, employees are informed about the incoming change, but often receive little in
the way of specific information formally communicated by management (Pollard, 2001). This
can be a critical juncture because concerns about change are conceptualized as an anticipation of
future loss or threat, specifically determined by the incoming change (Battistelli et al., 2014).
The actual or anticipated loss of significant resources has primacy in the process, leading to
stress, burnout, and impairment of work engagement (Gorgievski & Hobfoll, 2008). The effects
of workplace stress are disadvantageous for employees and organizations.
Workplace Stress Creates Disadvantages for Employee Well-Being
Workplace stress is an enormous problem and is estimated to cost the U.S. economy
more than $500 billion annually (Hellebuyck et al., 2017). Each year, 550 million workdays are
lost due to stress on the job. Stress is defined as the overall process by which employees are met
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with demands and their subsequent physical, cognitive, and emotional reactions to those
demands (Eisenberger et al., 2020; Hellebuyck et al., 2017; Sonnentag, 2015). The negative
consequences of stressors are referred to as strain, which includes affective, physical, or
behavioral reactions to stress (Eisenberger et al., 2020). The demands are correctly referred to as
stressors, whereas the outcomes of reactions to the stressors are often referred to as strains.
Workplace stressors not only affect individuals through strain outcomes but also reduce
employee effectiveness with increased absenteeism and turnover (Eisenberger et al., 2020; Sliter
& Yuan, 2015). Job-related stress is worsened when employees do not receive job-related tools
and resources.
Sonnentag (2015) concluded job conditions that did not provide the necessary day-to-day
tools or resources make a job difficult and sometimes too effortful for employees to accomplish
their tasks, which was more detrimental than high workloads alone. Employees who faced both
high workload and time pressure report poorer job-related well-being and higher levels of
burnout. Other hindrance stressors (e.g., hassles, interruptions, situational constraints,
organizational politics) are related to poor job-related well-being and increased burnout
(Sonnentag, 2015). Stress and adverse effects on employees also include sleep problems.
Deloitte’s (2020) respondents reported that 94% of workers in the United States and United
Kingdom reported feeling stress and one third said their stress level was high to unsustainably
high. Fifty-four percent of workers reported their home life was negatively affected by work at
least once a week. More than 50% reported sleep loss due to high stress levels (Deloitte, 2020).
Stress adversely affects life at home, and extreme chronic and continuous stress situations may
cause burnout syndrome (Prada-Ospina, 2019). This quantitative study of 360 health
professionals examined the role of psychological and social factors in the burnout process.
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Findings from the study included: a significant negative correlation between burnout syndrome
and work satisfaction and stress affects health professionals working in high-stress environments
in a disproportional and inverse way to work satisfaction. The author identified two critical
factors to ensure the well-being of workers: the opportunity to develop their skills and
knowledge in the organization and making sure their contributions generate new ideas that are
considered in the operation or strategy of the organization (Prada-Ospina, 2019). Chronic high-
stress work environments increase the risk of employee burnout.
High-Stress Environments Elevate Emotional Exhaustion and Lead to Burnout
In a Gallup (2020) study, 76% of employees reported experiencing burnout at least
sometimes. The 7,500 full-time employees surveyed identified the top five reasons for burnout,
and they all related to work. (a) unfair treatment, (b) unmanageable workload, (c) lack of role
clarity, (d) lack of communication and support from their manager, and (e) unreasonable time
pressure. When employees strongly agreed they were often treated unfairly at work, they were
2.3 times more likely to experience a high level of burnout (Gallup, 2020). Moss (2021) found
burned-out employees were 2.6 times as likely to be actively seeking a different job, 63% more
likely to take a sick day, and 23% more likely to visit the emergency room. Employee burnout
causes illness and is a global health problem.
Burnout is a global problem, and the WHO (2022) added a new definition and
clarification of burnout, that it is not a medical condition but rather an occupational phenomenon,
to the 11th revision of the International Classification of Diseases. Burnout is defined as “a
syndrome conceptualized as resulting from chronic workplace stress that has not been
successfully managed and is characterized by three dimensions: feelings of energy depletion or
exhaustion; increased mental distance from one’s job, or feelings of negativism or cynicism for
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one’s job; and reduced professional efficacy” (WHO, 2022, QD85 section). Alessani et al.
(2018) defined burnout as a work-related syndrome that results from prolonged exposure to
emotional and interpersonal stressors. The experience of burnout has been consistently
associated with negative individual and organizational outcomes such as anxiety, depression, life
mood disturbances, impaired job performance, turnover, and absenteeism. Guseva et al. (2021)
conducted a systematic review of 248 studies and agreed with the WHO that burnout occurs in
an occupational context and focused on physical and emotional impacts of burnout resulting
from prolonged stress and work-related problems. They defined burnout as: “in a worker,
occupational burnout or occupational physical AND emotional exhaustion state is an exhaustion
due to prolonged exposure to work-related problems” (Guseva et al., 2021, p. 104). Although
Guseva and colleagues provided the most inclusive definition of burnout, the current study relied
on the WHO’s (2019) most frequently used definition, whereas dimensions of burnout, also used
by the WHO, were based on the extensive research of Maslach and colleagues.
Three Dimensions of Burnout
Exhaustion, cynicism, and inefficacy are three dimensions of burnout (Maslach et al.,
2001; Maslach & Leiter, 2008). Exhaustion is the central quality of burnout and most obvious
manifestations of this complex syndrome. Exhaustion prompts actions to distance oneself
emotionally and cognitively from work to cope with work overload. These seminal scholars
identified exhaustion as a necessary criterion for burnout. A work situation with chronic,
overwhelming demands contributes to exhaustion, cynicism, and inefficacy on the job and will
erode one’s sense of effectiveness (Maslach & Leiter, 2008). Burnout includes significant health
risks and has five common elements.
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Five Elements of Burnout
Maslach et al. (2001) identified five common elements of burnout: (a) predominance of
dysphoric symptoms such as mental or emotional exhaustion, fatigue, and depression; (b) an
emphasis on mental and behavioral symptoms more than physical ones; (c) burnout symptoms
are work related; (d) the symptoms manifest in “normal” people who did not suffer from
psychopathology before; and (e) decreased effectiveness and work performance occur because of
negative attitudes and behaviors. Individual manifestations of burnout may not have all five
elements yet still be considered burnout (Maslach et al., 2001). Burnout is a workplace syndrome
and negatively affects employees and organizations.
Employee burnout is caused by work overload, role conflict, role ambiguity, and job
demand (Maslach & Leiter, 2008). Burnout is associated with behaviors such as job withdrawal,
absenteeism, intention to leave, and actual turnover. Burnout results in lower productivity and
reduced work effectiveness, decreased job satisfaction, and a reduced commitment to the job or
organization. Burnout precipitates negative mental health, such as anxiety, depression, and
decreased self-esteem. Burnout co-occurs with depression, but unlike depression, which affects
all areas of life, burnout is found in the context of work. Job resources such as support from
supervisors can help prevent burnout, whereas lack of social support and low autonomy is linked
to burnout (Maslach et al., 2001; Maslach & Leiter, 2008). Although burnout is a workplace
syndrome, it negatively affects all areas of life. The burnout–engagement continuum model
provides a framework for organizations to address burnout.
Burnout–Engagement Continuum at Work
Maslach and Leiter (2008) identified a relationship on a continuum between the positive
experience of work engagement and negative experience of burnout. The burnout–engagement
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continuum conceptualizes an individual’s psychological relationship to their job as a continuum
between the negative experience of burnout and the positive experience of engagement. There
are three interrelated dimensions to this continuum based on Maslach’s original burnout model:
exhaustion–energy, cynicism–involvement, and inefficacy–efficacy. This positive opposite of
burnout is referred to as job engagement, defined as an energetic state of involvement with
personally fulfilling activities that enhance one’s sense of professional efficacy (Maslach &
Leiter, 2008). In addition to the fulfilling state of professional efficacy, fairness in the workplace
is important to employees.
Maslach and Leiter’s (2008) longitudinal study sampled more than 1,000 participants,
and perception of fairness in the workplace was the key workplace incongruity (tipping point)
that determined whether people changed toward burnout or engagement on the continuum. If
people were experiencing problems with fairness in the workplace (such as favoritism,
unjustified inequities, or cheating), they leaned toward burnout over time. In contrast, people
who did not experience a fairness incongruity, the early warning pattern (of either exhaustion or
cynicism) was likely to diminish over time and result in a pattern of engagement. Once people
begin to feel hostile and angry about job inequities and lack faith in organizational processes to
right any wrongs, this may set in motion an increasing cascade of negative reactions to the job.
However, people who feel the workplace is fair and equitable and trust that good solutions will
be found for problems may be able to weather the storm and remain somewhere on the positive
side of the continuum. But when an employee is on the burnout side of the continuum,
organizational supports and preventive individual approaches can get things back on track and
address temporary stress (Maslach & Leiter, 2008). More recent COVID-19 research revealed
chronic distress and compromised well-being in LTC nursing home communities.
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LTC-Specific Employee Well-Being Challenges During COVID-19
Workplace high-stress factors that now include COVID-19 compromise well-being due
to greater demands than the capabilities, resources, and needs of health care employees, who are
emotionally affected and traumatized (Carey et al., 2020). As of June 2022, 937,432 U.S. health
care employees were infected with COVID-19, of whom 2,550 died (CDC, 2022). COVID-19 is
described as a new disease, caused by a novel (or new) coronavirus that had not previously been
seen in humans (CDC, 2019). Although most people who had COVID-19 have experienced mild
symptoms, it can also cause severe illness and even death. Some groups, including older adults
and people who have certain underlying medical conditions, are at increased risk of severe
illness (CDC, 2022). Frontline LTC health care employees are at increased risk of exposure and
illness.
Frontline health care employees working in LTC nursing homes are at significant risk of
exposure to C OVI D‐ 19-infected patients. The Kaiser Family Foundation (KFF; 2021) identified
that LTC employees account for more than a third (38%) of COVID-19 nursing home cases,
though to date, far fewer deaths (3%). This result may be due to the higher risk because LTC
jobs often require close contact with residents. To date, CMS (2022) has reported 34,885
facilities, 1,049,918 cases, and 153,149 deaths in LTC facilities (KFF, 2021).
Health risks from COVID-19 for frontline LTC employees are well documented. Fifty
percent of LTC workers are at increased risk of severe COVID-19 illness and an additional 20%
are potentially at increased risk of mild illness (Carey et al., 2020). These scholars conducted
online interviews with 3,700 participants. Some LTC workers described the situation as
“terrifying,” and safety concerns due to constant adjustment to the new requirements brought
about by COVID-19 left LTC communities with widespread shortages of personal protective
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equipment, increasing workers’ risk of COVID-19 exposure, creating challenges allocating
insufficient resources (e.g., ventilator support), and generating existential stress related to
personal infection, illness, and loss of infected patients, colleagues, or family members (Carey et
al., 2020). Demographic data show added risks for employees working in LTC during COVID-
19.
LTC Employee Demographics as Predictors of Health and Psychological Risk
LTC frontline employee demographics are evidence of additional health risks relating to
COVID-19. Greene and Gibson (2021) collected and analyzed LTC worker demographic data to
identify the increased health risks for LTC workers. The researchers conducted a meta-analysis
of a representative sample of 552 of 52,159 adult respondents working in LTC facilities from the
National Health Interview Survey, which identified the demographics of LTC employees and
their vulnerability to COVID-19. Risk factors include that LTC employees are disproportionately
female (83%), Black (23.7%), and low-income individuals without college degrees (77%). In
addition, employees are found to be highly vulnerable to severe COVID-19 due to health
concerns such as obesity (37.4%), prior smoking history (34.7%), and hypertension (18.9%).
LTC workers’ heightened likelihood of being exposed to COVID-19 in combination with their
demographics are linked to increased risk of severe illness from COVID-19.
Dill and Duffy (2022) described how 1 in 5 Black women are employed in the health care
sector and in this group, they have the highest likelihood of working in LTC (37%) or as a NA,
CNA, or LPN (42%). Fifty percent of Black and Hispanic women in health care earn less than
$15 an hour, and frontline employees who provide personal care experience the highest rates of
workplace-related injuries of any industry in the United States. The researchers’ findings link
Black women’s position in the labor force to the historical legacies of sexism and racism, dating
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back to the division of care work in slavery and domestic service. Their study was based on an
analysis of the probability of Black women working in occupations in the health care industry.
Original data were obtained from the American Community Survey, an annual nationally
representative survey conducted by the U.S. Census Bureau (2019). The researchers
recommended raising wages across the low-wage end of the sector, creating accessible career
ladders, and addressing racism in the pipeline of the health care profession (Dill & Duffy, 2022).
Because of low wages, many LTC workers are financially insecure and most affected by
organizational policies. Greene and Gibson (2021) identified that at least one third of LTC
workers do not have paid sick leave and are not eligible for the 14-day paid sick leave that is
included in the Families First Coronavirus Response Act because nursing homes can exempt
employees from the provisions. LTC workers in several states have protested on this issue and to
obtain more protective equipment, hazard pay, and better staffing (Greene & Gibson, 2021).
Low-income frontline CNAs and LPNs provide direct care to patients and are more likely to be
injured at work.
Overall, health care workers have the highest rates of workplace-related injuries of any
industry in the United States. During the early stages of the COVID-19 pandemic, Scientific
American published an analysis using BLS (2021) and CMS (2021 data that workers in LTC
facilities have the “most dangerous jobs in America” (Lewis, 2021). In the workforce, nurse
aides and nurses are much more likely to experience work-place-related injuries and stress
compared with other health care workers. The BLS (2021) and CMS (2021) reported that in
2020, there were 80 deaths for every 100,000 employees, representing more employee deaths
than loggers and second only to workers in the fishing industry. These issues contribute to
emotional exhaustion, fatigue, burnout, and high turnover in LTC nursing homes.
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Severe Implications for LTC Frontline Health Care Employees
The data related to COVID-19 stressors are staggering. Ginger (2021) surveyed 1,229
employees and 158 CEOs and 70% of employees felt COVID-19 caused the most stress in their
careers. Forty-eight percent of employees experienced high or extreme stress (7% greater than
before COVID-19) and 80% of CEOs believed mental health affects business outcomes.
Although 96% of employers believe they provided sufficient mental health support, in contrast,
only 69% of employees felt similarly. This survey represented different U.S. industries with 100
or more employees and exposed a significant gap between employee versus CEO beliefs that
mental health challenges are accepted in the workplace (35% vs. 74%, respectively). Significant
gaps between employee and organization perceptions are particularly concerning because female
employees are most affected and vulnerable to stress during the pandemic (Ginger, 2021).
Due to COVID-19, female employees feel anxiety over layoff, furlough, burnout, mental
health, childcare, and homeschooling (McKinsey & Company, 2020). Half of employees
consistently felt stressed at work, and one third felt exhausted or burned out. Forty thousand
employees from 47 companies participated in the McKinsey and Company Employee
Experience Survey. The survey questions covered multiple themes (e.g., employee well-being,
work flexibility, remote work, the state of diversity, equity, manager actions, allyship) and
demographic questions (e.g., age, sexual orientation, family status). The enormity of the problem
for individuals and organizations is exacerbated in workplaces with more women (McKinsey &
Company, 2020). Frontline health care workers experience psychological distress and require
psychological support.
Scholars identified elevated emotional and psychosocial distress in health care, especially
health care workers who have unmediated contact with COVID-19 patients (Carey et al., 2020).
34

Prior to the pandemic, Shanafelt et al. (2016) found that 50% of U.S. physicians experienced
burnout. Now, recent studies showed that burnout, moral injury, and posttraumatic stress
disorder are at the highest levels. Lee-Baggley and Thakrar (2020) reported approximately 41%
of their study respondents identified at least one adverse mental or behavioral health condition,
including 31% reporting anxiety and depressive disorder, 26% reporting trauma and stressor-
related disorder symptoms, 13% reporting the start or increase of substance use, 11% considering
or increasing substance use, and 11% considering suicide. The current study attempted to add to
the prior research literature about the significant effects of fatigue, emotional exhaustion, and
burnout and effects on well-being during the COVID-19 pandemic era. The theoretical
foundation, researcher positionality, and conceptual underpinnings helped frame the current
study.
Theoretical Foundations
Using the SCT triadic model, this study examined frontline health care employees’
perception of their work effectiveness and fatigue, emotional exhaustion, and burnout as
contributors to employee well-being in LTC nursing homes during COVID-19. SCT outlines the
triadic relationship among the LTC employee, behaviors, and the LTC nursing organization and
leadership. When deciding how to study this problem in social science, researchers need to first
identify their worldview or paradigm. The term worldview was coined by Guba (1990, p. 17) and
defined by Creswell and Creswell (2018) as “a basic set of beliefs that guide action” (p. 5).
My worldview is the belief that various influences intersect, are reciprocal in nature, and
play out together. In the context of the current study, the COVID-19 crisis increased employee
burnout, employees quit their jobs, organizations were negatively impacted, and residents did not
receive high-quality care. This philosophy fits a postpositivist worldview. Postpositivists hold a
35

deterministic philosophy described by Creswell and Creswell (2018) to study problems that
reflect the need to identify and assess the causes that influence outcomes. Postpositivist
viewpoints lean toward quantitative or deductive methods. I began by identifying the problem of
study and choosing a theory prior to data collection. Then data analysis was conducted while
weaving theory into my theory of change and positionality. My worldview, theory of change,
and positionality influence each aspect of the study.
My theory of change has less of a set beginning and instead reflects a continuum. In SCT,
change can occur with any of the three points of the triadic model—person, behavior, or
environment—and effects are reciprocal. When working with individuals, there is not a constant
state, because as changes happen environmentally, they affect the person. I believe one
(un)successful change stimulates another wave that facilitates change somewhere in the universe.
As shown in Figure 1, the blue triangle in the center represents the SCT triad reciprocity
among the employee, behavior, and environment. At the top of the triangle is the employee’s
beliefs about their effectiveness, fatigue, emotional exhaustion, and burnout. Well-being is also
centered on the employee. One green arrow identifies how organizational policies and
procedures, and leadership strategies may support employee well-being. A second green arrow
points from the organization and leadership to behavior to indicate how an employee’s use of
organizational and leader resources may contribute to behavioral change.

36

Figure 1
Social Cognitive Theory’s Application to the Current Study

Summary
This comprehensive review of the literature defined well-being and its dimensions and
identified environmental levers including job resources and leadership. The review identified
obstacles for employee well-being including low resources, ineffective leadership, and
organizational change. Setting-specific risks include chronic stress at work, emotional
exhaustion, fatigue, and burnout. The literature substantiates the importance of effective
organizational policies and procedures and supervisor or leader strategies that support employee
well-being. Chapter 3 describes the methodology for the current study.

Behavior
LTC Nursing Organization
Policies and Procedures and
Leadership Strategies that
Support Well-Being
Employee: Work
Effectiveness,
Emotional Exhaustion,
Fatigue, Burnout, Well-
Being
37

Chapter Three: Methodology
The purpose of this study was to examine employee beliefs about the impacts of COVID-
19 and identify implemented organizational policies and leadership practices that may have
positively affected the well-being of frontline health care employees in LTC. This chapter
describes the study design, research setting, method, participants, researcher positionality, data
collection procedures, instrumentation, ethics, and limitations of the study.
Research Questions
The research questions focused on LTC frontline health care employees’ beliefs about the
effects of emotional exhaustion, fatigue, and burnout on their work effectiveness and the specific
strategies, if any, that organizations have implemented to support their well-being.
1. How has burnout, emotional exhaustion, and fatigue affected beliefs about LTC frontline
health care employees’ effectiveness throughout the COVID-19 pandemic?
2. What demographic differences, if any, exist for LTC frontline health care employees’
emotional exhaustion, fatigue, burnout, less work resources, and perceptions of less work
effectiveness during the COVID-19 pandemic?
3. What, if any, specific strategies have organizations and leaders in LTC implemented that
support the well-being of their frontline health care employees during the COVID-19
pandemic?
Overview of Design
I relied on a convenience nonprobability quantitative research field study design. The
research questions were answered utilizing a nonexperimental quantitative correlational survey
research method. Quantitative inquiry involves the process of collecting, analyzing, and
38

interpreting the results of a study (Creswell & Creswell, 2018). Standardized instrumentation
was adapted into an online survey questionnaire in Qualtrics.
Research Setting
The setting for the research study was LTC nursing communities in the United States.
Frontline LTC employees for this study were identified as direct care staff members including
NAs, CNAs, LPNs, and RNs. Demographic data identified additional challenges for LTC health
care employees.
The frontline health care workforce in LTC is 67% NAs or CNAs (BLS, 2021). Fifty
percent of Black NAs and CNAs earn less than $15 an hour. The profession is overwhelmingly
female (90%), and about 54% identify as Black (36%), Hispanic or Latinx (11%), Asian or
Pacific Islander (5%), or another race or ethnicity other than White (5%; Denny-Brown et al.,
2020). Dill and Duffy (2022) identified that 31% of LTC frontline health care employees have a
child younger than age 18 at home and 15% have a child younger than age 5 at home. Nursing
homes also employ a sizable proportion of immigrant workers, with 21% of workers in nursing
homes born outside the United States (Denny-Brown et al., 2020).
The Researcher
I am a 54-year-old, White, female, mother, wife, nana, and professional licensed clinical
social worker (LCSW) living in a Midwestern university town. My profession during the last 18
years has been providing counseling to adults, children, and families. Since 2013, I served as
clinical director and licensed clinical practitioner for a multistate region for a geriatric behavioral
health practice, collaborating with medical teams to provide residents in LTC nursing homes
with mental health assessment and counseling. In addition to institutional review board (IRB)
39

standards of conduct, I am also bound by my LCSW professional licensure to practice ethical
conduct.
Initially, this study was intended to involve qualitative interviews with LTC residents.
But since 2020, dozens of my patients were infected with COVID-19, became extremely ill, and
did not survive COVID-19. In January 2021, one of my clinical employees passed away. Dozens
of my close friends who were caring for sick patients were also infected with COVID-19. In
October 2020, I was sick with COVID-19 symptoms and missed work for 4 weeks. I continued
to experience grief and loss that may have surfaced if interviews had been conducted for this
study. I acknowledge that these personal COVID-19 experiences may reflect similar emotions as
those of LTC employees and may generate bias regarding their lived experiences. I do not
assume my experience was equivalent to the personal challenges and moral injury faced by
frontline health care workers facing COVID-19 danger every day.
Data Sources
The data were collected via an online Qualtrics survey questionnaire that included 27
Likert-style questions that examined the association of LTC employee emotional exhaustion,
fatigue, and burnout and their relationship to work effectiveness. The survey included four open-
ended questions to obtain information about effective organizational policies and procedures and
supervisor strategies that support employee well-being during COVID-19. The survey is
described in this chapter and included in Appendix A.
Method
The field study involved a nonexperimental quantitative descriptive and correlational
survey research method with statistical analysis and interpretation, as dictated by Research
40

Questions 1 and 2. Open-ended survey question responses were coded and categorized as
dictated by Research Question 3.
Participants
The current study featured a convenience nonprobability sample obtained via a
combination of IRB-approved recruitment strategies including email, Facebook, and LinkedIn. I
made appointments to visit two nursing homes and handed out chips and candy bars with a
Qualtrics survey QR code to potential voluntary participants.
After data cleaning, 112 participants had completed 100% of the survey. To test
statistical power, a power analysis using a one-sample Pearson’s correlation test was run in
SPSS. Power refers to the likelihood that the sample size is large enough to reject the null
hypothesis (no relationship or no difference) at p < .05 when population estimates indicate that
the null hypothesis should be rejected (Salkind & Frye, 2020). The research standard is .80
power, and the current (N = 112) sample size had enough statistical power to detect a moderate
correlation of .30 at .90.
To measure the observed power of an independent-sample t-test, the effect size must be
estimated. The effect size measures the difference between groups in standardized units (M = 0,
SD = 1). Salkind and Frye (2020) suggested that .50 is a medium effect size. The larger the effect
size, the more distance and lack of overlap between groups. For the current sample size (N =
112), the observed power was .75, which is slightly lower than the .80 standard. This calculation
was made under the assumption that the sample sizes for the two groups were approximately
equal.
41

As shown in Table 2, the sample was 90% female, 94% White, and featured NAs and
CNAs (n = 29), LPNs (n = 11), and RNs (n = 26). The average age for the participant sample
was 44 years old, and 60% of the participants worked in LTC for 11 or more years.

Table 2
Sociodemographic Characteristics of Participants
Demographic n
Age 106
30 or younger 19
31 to 45 37
46 to 60 38
61 or older 12
Gender 109
Female 99
Male 10
Ethnicity 106
Hispanic or Latinx 4
Non-Hispanic or Latinx 102
Race 104
White 98
Person of color 6
Years worked in LTC 112
2 years or less 16
3 to 5 years 16
6 to 10 years 15
11 to 20 years 27
21 or more years 38

42

Instrumentation
The survey instrument featured 27 questions and was administered online using
Qualtrics. The survey instrument contained work-related (three items) and personal (nine items)
demographic questions. Eleven Likert-style questions were chosen from four existing
instruments measuring emotional exhaustion and burnout (two items), fatigue (four items),
effectiveness (five items), and less work resources (two items) variables. Other questions were
developed and agreed on by the thematic dissertation group, including two Likert-style questions
measuring the level of effectiveness and well-being before and during the pandemic and four
open-ended questions that identified organization policies (two items) and supervisor strategies
(two items) for employee well-being during COVID-19.
Two questions measuring the emotional exhaustion and burnout variables were adopted
from the Maslach Burnout Inventory-2 (MBI-2). The fatigue variable relied on four questions
adapted from the Fatigue Assessment Scale-10. Employee effectiveness items were adapted from
the Perceived Stress Scale-10 (PSS-10). In addition to the PSS-10, effectiveness was measured
with two questions from the Q12 Employee Engagement Survey.
Maslach Burnout Inventory
The MBI is designed to assess the three components of burnout syndrome: emotional
exhaustion, depersonalization, and reduced personal accomplishment. It features 22 items
divided into three subscales: psychological, social, and physical (Maslach et al., 1996). Since its
creation, there has been support for use of a less time-consuming inventory (West et al., 2009,
2012). West et al. (2009) completed a factor analysis of the 22-item survey. The single questions
with the highest factor loading on emotional exhaustion (“I feel burned out from my work”) and
depersonalization (“I have become more callous toward people since I took this job”) are
43

contained in the MBI-2, which was used for this study. When the two questions are compared to
the full MBI, Spearman correlations between the single emotional exhaustion question and full
domain without that question ranged from .76 to .83. Spearman correlations between the single
depersonalization question and full domain without that question ranged from .61 to .72. West et
al. (2012) found concurrent validity of the two items relative to the full MBI.
Fatigue Assessment Scale
To measure fatigue, three of 10 questions from the FAS-10, which has a Cronbach’s
alpha of .87 (Michielsen et al., 2004), were used for this survey. The factor analysis they
performed showed each question measured one factor, fatigue, and individual question reliability
ranged from .60 to .77: (a) “Mentally, I feel exhausted” (.74); (b) “Physically, I feel exhausted”
(.77); (c) “I have enough energy for everyday life” (.63); and (d) “When I am doing something, I
concentrate quite well” (.57; Michielsen et al., 2020).
Perceived Stress Scale
One of two scales the current survey used to measure the employee effectiveness variable
was the PSS. The PSS is a self-reported questionnaire that was designed to measure “the degree
to which individuals appraise situations in their lives as stressful” (Cohen et al., 1983, p. 385).
The PSS has 14-, 10-, and 4-question versions and is the most widely used psychological
instrument for measuring the perception of stress. The PSS-10 had a Cronbach’s alpha range of
.74 to .91 in 12 studies testing its psychometrics (Lee, 2012). The PSS-10 questions are listed by
Cohen and Mermelstein (2014) and include three questions to measure effectiveness. Two of the
three questions were modified to add “at work,” with thematic dissertation group agreement. The
questions are: (a) In the last month, how often have you felt that you were unable to control the
important things in your life?; (b) In the last month, how often have you felt confident in your
44

ability to handle problems at work?; and (c) In the last month, how often have you felt
difficulties at work were piling up so high you could not overcome them? Each participant’s
answers were based on a 5-point Likert style scale: 1 = never, 2 = sometimes, 3 = regularly, 4 =
often, and 5 = always. Cronbach’s alpha was lower than previously reported due to fewer
questions and because two questions were modified.
Q12 Employee Engagement Survey
The second scale measuring the less work resources variable featured two questions
adapted from the Q12 Employee Engagement Survey (Gallup, 2021). This survey’s Cronbach’s
alpha was .91 when studied in its entirety (Harter & Schmidt, 2002; Harter et al., 2009). Two
items—“I have the materials and equipment I need to do my job right” and “My supervisor or
someone at work seems to care about me as a person”—were used to measure less work
resources in this study. Each answer is based on a 5 point-Likert scale: 1 = strongly disagree, 2 =
disagree, 3 = neither agree nor disagree, 4 = agree, or 5 = strongly agree. The first item is the
strongest indicator of job stress from the survey. This element measures both physical resource
needs and potential barriers between the employer and employee. The second item assesses the
likelihood that employees will experiment with new ideas, will share information and support
each other in their work and personal lives, are prepared to give their manager and organization
the benefit of the doubt, and feel more equipped to strike a balance between their work and
personal lives (Gallup, 2021).
Data Collection Procedures
Following approval from the USC Office for the Protection of Research Subjects,
recruiting participants from LTC communities was done in three steps. First, a corporate LTC
group sent an email containing a letter describing the study and the Qualtrics link and QR code
45

to 14 LTC communities for participants to complete the Qualtrics survey. Each group was asked
to post the survey information in employee work areas, such as nursing stations and break rooms.
Next, to ensure participant anonymity and confidentiality, I provided written information about
the importance of the study and explained that it is voluntary. The survey was open for 7 weeks
between January 17 and March 3, 2022. Participants could take the survey confidentially at the
facility or anonymously if they preferred to use the link and complete the survey after work. I did
not request names or personally identifying information from participants.
In addition to emailing the survey to LTC communities, I went to two LTC communities
with study information and snacks with the QR code attached and left them in nursing stations
and break areas. Third, I submitted and had an LTC story published about the study by Pioneer
Network on Facebook and LinkedIn.
Data Analysis
Prior to data analysis, I uploaded the Qualtrics survey responses to SPSS and cleaned the
data, removing blank responses. Six scale items were positively scaled, so for consistency, items
8, 9, 11, 13, 14, 15, and 16 were reverse coded. Because items were all negatively scaled, two
variables were renamed: work effectiveness (perceptions of less work effectiveness) and work
resources (less work resources). Internal consistency and reliability were calculated in SPSS to
determine Cronbach’s alpha for each item. Once the items for the dependent variable (perception
of less work effectiveness) and independent variables (emotional exhaustion, fatigue, burnout,
and less work resources) were combined using SPSS to obtain the highest internal consistency
and reliability, the means and standard deviations were calculated for all variables. Descriptive
statistics were determined for dependent and independent variables with means, standard
deviations, skewness, and kurtosis. All variables resulted in a near-normal curve. Next, Pearson’s
46

correlations were calculated in SPSS to test the research hypothesis that emotional exhaustion,
fatigue, burnout, and less work resources are associated with employee perception of less work
effectiveness. Statistical power analysis confirmed the sample was large enough to support the
statistical results, and Cohen’s effect size was used to estimate statistical power based on effect
size. Analyses of variance were run for demographics to compare means to the dependent and
independent variables and within groups. Post hoc t-tests were run for groups of three or more.
Most important, statistical significance was set to be less than .05.
Validity and Reliability
The survey contents were constructed based on the research questions and study variables
and adopted or adapted from existing instruments. Validity and reliability statistics are provided
in the Instrumentation section for items from established instruments. Two Likert-style items and
four open-ended items that were developed by the thematic dissertation group were not tested.
Due to time constraints, I conducted interrater reliability checks and pilot tests (n = 10) prior to
survey administration. The survey raters, who were not in the study sample, were asked to
answer the following questions before closing the survey: (a) How much time did it take to
complete the survey?; (b) Please list any items that are unclear; and (c) In what ways could the
survey be improved? Interrater testing was used to check the clarity of each question and make
sure instructions were standardized and consistent (Salkind & Frye, 2020).
Ethics
This research study was reviewed and approved by the University of Southern California
IRB. I used documents from the IRB document library with samples and recommendations for
communicating to participants about voluntary informed consent and anonymity. Consent
information was included in a written description of the study with notification that consent
47

would be assumed when they begin the survey and could be withdrawn at any time before the
conclusion of the survey. To ensure confidentiality and anonymity, the Qualtrics software did not
retain any identifiable information about the participants, and they were not asked for individual
identifying information beyond the generalizable demographic and survey responses collected
from the entire sample. Despite assurances about confidentiality and anonymity, participants
may not be comfortable giving honest opinions to open-ended questions that were asked in the
survey.
This was a field study about LTC health care professionals’ personal views of work
effectiveness, their supervisor, and their workplace. Another possible harm was that participants
may not trust that their information was anonymous and have concern or reticence about
participating or revealing negative information about their supervisor or organization and fear
retaliation. For example, during the data collection stage of this study, a charge nurse disclosed
that she had completed the survey because she trusts me. She disclosed that she had refused to
complete prior surveys at work because her colleague was fired from their organization for her
feedback on an employee survey. The nurse’s disclosure was a real-life confirmation of the
challenges of fear of retaliation and reduced psychological safety. When conducting research, I
utilized IRB document samples to provide written assurance of participant anonymity of their
personal information; that data storage in Qualtrics does not retain any identifying information;
the autonomous process of data collection, access to the data, storage, and analysis; and how
results may be reported. Supervisors and organizations are in positions of power and privilege,
and I may have also been seen as a person of power and privilege.
Researchers may be seen as holding power and privilege by nature of collecting and
analyzing data from and about others (Robinson & Firth Leonard, 2019). I am an LCSW and
48

behavioral health expert who provided behavioral health services to residents in LTC
communities. To reduce opportunities for power dynamics and coercion, I made thoughtful
changes that delineated my visit from patient care delivery visits. I dressed casually, did not see
patients for sessions, announced the purpose of my visit, handed out snacks, and verbalized
information about the study.

49

Chapter Four: Results and Findings
The purpose of this study was to examine LTC frontline health care employees’ beliefs
about the impacts of COVID-19 and identify organizational and leadership practices
implemented during the COVID-19 pandemic that may have positively affected the well-being
of frontline health care employees in LTC. The first research question focused on the LTC
frontline health care employees’ beliefs about the impacts of emotional exhaustion, fatigue,
burnout, and less work resources on their perceptions of less work effectiveness. The second
research question focused on demographic differences, if any, exist for LTC frontline health care
employees’ emotional exhaustion, fatigue, burnout, less work resources, and perceptions of less
work effectiveness. The third research question was addressed with open-ended questions to
identify specific organizational policies and direct supervisor strategies, if any, that were
implemented to support employee well-being during COVID-19. The study utilized SCT in a
deductive quantitative survey design. This chapter provides results and findings from data
analysis for each research question.
Research Question 1: How Has Burnout, Emotional Exhaustion, and Fatigue Affected
Beliefs About LTC Frontline Health Care Employees’ Effectiveness Throughout the
COVID-19 Pandemic?
This section begins by addressing Research Question 1 with the objective of testing the
hypothesis that emotional exhaustion, fatigue, burnout, and less work resources are associated
with perceptions of less work effectiveness. Dependent variables are the outcome or results
under the influence of the independent variable (Creswell & Creswell, 2018). For Research
Question 1, perceptions of less work effectiveness was the dependent variable. Emotional
exhaustion, fatigue, burnout, and less work resources were the independent variables. The
50

findings section provides tables and figures that examine with 95% certainty the evidence that
the dependent variable, e.g., level of work effectiveness, was associated with LTC frontline
health care employees’ beliefs about their level of exhaustion, fatigue, and burnout at work. I
first tested reliability and descriptive statistics of items designed to measure the dependent
variable of lack of work effectiveness.
Perceptions of Lower Work Effectiveness
The survey instrument contained four items that measured less work effectiveness: (a) In
the last month, how often have you felt confident in your ability to handle your problems at
work? (reverse scored); and (b) In the last month, how often have you felt difficulties at work
were piling up so high that you could not overcome them? These scales ranged from 1 (never) to
5 (always). (c) How do you compare your current effectiveness in your work relative to before
the pandemic?; and (d) How do you compare your current well-being at work relative to before
the pandemic? These questions were reverse scored so the scales ranged from 1 (significantly
less) to 5 (significantly more).
To help determine which items to combine for perceptions of less work effectiveness, I
tested internal consistency and frequencies in SPSS statistical software.
Reliability
The most common measure of internal consistency and reliability is Cronbach’s alpha.
Item reliability scores closest to 1.0 indicate the strongest reliability, with .70 as the research
standard (Salkind & Frye, 2020). As shown in Table 3, the combined items almost reached the
research standard for good reliability with an alpha of .69, meaning that there was slightly more
than 30% error. When reviewing the four items and identifying changes in internal consistency
and reliability, removing any item would decrease internal consistency and reliability, thus
51

further supporting the reliability of these four items as measures of perceptions of less work
effectiveness.

Table 3
Item-Total Statistical Analysis for Perceptions of Less Work Effectiveness
M SD Corrected r α if item deleted
In the last month, how often have you felt
confident about your ability to handle
your problems at work? (reversed)
2.33 .89 .48 .62
In the last month, how often have you felt
difficulties at work were piling up so
high that you could not overcome
them?
3.28 1.07 .42 .67
How do you compare your current
effectiveness in your work relative to
before the pandemic? (reversed)
3.75 1.07 .47 .63
How do you compare your current well-
being at work relative to before the
pandemic? (reversed)
4.06 .90 .54 .58

52

Descriptive Frequencies
Descriptive statistical analysis was subsequently run for the perceptions of less work
effectiveness variable using SPSS. Descriptive statistics are one way to organize and describe
data from the collected sampling group (Salkind & Frye, 2020). For descriptive analysis, the
average mean is used as a measure of central tendency and standard deviation was used to
measure variability Creswell & Creswell, 2018). The mean is a measure of central tendency,
sometimes called average, that represents an entire group of scores. The mean is calculated using
the sum of all the values in a group divided by the number of values in that group (Salkind &
Frye, 2020). As shown in Table 4, the mean is 3.35 and the SD is 0.70. The SD is the average
unit of distance from the mean. SD is the most frequently used measure of variability from the
mean. The larger the SD, the larger the dispersion or average distance from the mean (Salkind &
Frye, 2019).

Table 4
Descriptive Statistics for Perceptions of Less Work Effectiveness
N
Valid 112
Missing 0
M 3.35
Mdn 3.50
SD 0.70
Skewness -0.39
Kurtosis 0.63

53

Also shown in Table 4, the mean and median are nearly identical, and in Figure 2, a
histogram and frequency polygon line represent an approximate normal bell curve and one peak.
The left and right sides of a normal curve are symmetric or mirror images. A perfectly symmetric
normal curve rarely happens in practice, so skewness and kurtosis statistics are needed. The
skewness of a normal distribution is indicated by a skewness statistic, and zero is a perfectly
normal distribution. A range in the skewness of plus or minus 1.0 is an approximate normal
distribution. As shown in Table 4, the skewness (-0.39) falls in this range, so the distribution is
approximately normal.
The kurtosis is the extent to which a distribution is flat (negative kurtosis) or peaked
(positive kurtosis). Zero is a perfectly normal distribution, and the kurtosis (0.63) shows a
positive value less than 1.0, so the distribution is normal. These results confirm the applicability
of parametric statistics with confidence in the significance level (p < .05).

54

Figure 2
Perceptions of Less Work Effectiveness Histogram for Frequency Distribution

Emotional Exhaustion, Fatigue, Burnout, and Less Work Resources
I added items from the survey instrument for each independent variable hypothesized to
be associated with perceptions of less work effectiveness. As shown in Table 5, the emotional
exhaustion independent variable contained two items with an alpha of .69. The fatigue variable
contained three items with an alpha of .59, burnout contained two questions from the MBI-2 with
an alpha of .60, and I combined two items from a Gallup instrument called less work resources
with an alpha of .53. Three of the four independent variables had lower alpha than .70, and low
reliability may be because the sample responses were largely from a homogenous sampling of
frontline health care employees in LTC.

55

Table 5
Item-Total Statistical Analysis for Emotional Exhaustion, Fatigue, Burnout, and Less Work
Resources
M SD Corrected r α if item deleted
Emotional exhaustion
Mentally, I feel exhausted. 3.37 1.23 .46 --
In the last month, how often have you felt
that you were unable to control the
important things in your life?
3.17 1.13 .46 --
Fatigue
When I am doing something, I can
concentrate quite well. (reverse coded)
3.19 1.05 .35 .56
Physically, I feel exhausted. 3.33 1.19 .35 .58
I have enough energy for everyday life.
(reverse coded)
3.59 1.41 .53 .33
Burnout at work
I feel burned out from my work. 5.13 1.65 .42 --
I have become more callous toward people
since I took this job.
3.54 1.97 .42 --
Less work resources
I have the materials and equipment I need to
do my work right. (reverse coded)
2.79 1.16 .35 --
My supervisor or someone at work seem to
care about me as a person. (reverse coded)
2.47 1.20 .35 --

As shown in Table 6, means, standard deviations, and alphas were calculated in SPSS for
less work effectiveness (M = 3.35, SD = .699), emotional exhaustion (M = 3.27, SD = 1.03),
fatigue (M = 3.37, SD = 0.78), burnout (M = 4.33, SD = 1.52), and less work resources (M =
2.63, SD = .977). As discussed in Chapter 3, after reverse coding several items for consistency,
the scales measure each variable from left to right. In light of the scale midpoints, the
participants had regularly experienced emotional exhaustion, regularly experienced fatigue,
56

experienced burnout at work a few times a month or more, sometimes perceived less work
resources, and regularly perceived of less work effectiveness.

Table 6
Means, Standard Deviations, and Alphas for Independent and Dependent Variables
M SD α
Emotional exhaustion 3.26 1.03 .69
Fatigue 3.36 0.78 .59
Burnout at work 4.33 1.53 .60
Less work resources 2.63 0.97 .53
Less work effectiveness 3.35 0.69 .69

57

Correlational Statistical Analysis
Once reliability and descriptive statistical evidence was shown for both the dependent
and independent variables, SPSS statistical software was used to calculate the relationships
between the variables with Pearson’s correlation (Salkind & Frye, 2020). For this study,
Pearson’s correlation coefficient was used to measure the correlations of emotional exhaustion,
fatigue, burnout, and less work resources effects and their associations with less work
effectiveness. A Pearson’s correlation ranges between -1.0 and +1.0, and the further from 0, the
stronger the relationship. Zero means there is no relationship between the variables, and the null
hypothesis is r = 0 (Salkind & Frye, 2019). The correlation coefficients are shown for each
variable for the 112 respondents in Table 7. According to Salkind and Frye’s (2020) numerical
index, the higher the numerical value of the correlation, the stronger the relationship: moderate
(.30), moderate to strong (.40), and strong (.50 to 1.0). Negative correlations indicate an inverse
relationship, and a positive correlation indicates a direct relationship. SPSS computed the
correlations for each variable against the other variables.

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Table 7
Strength of Relationships between Perceptions of Less Work Effectiveness, Emotional
Exhaustion, Fatigue, Burnout at Work, and Less Work Resources
1 2 3 4
1. Emotional exhaustion
2. Fatigue .62*
3. Burnout at work .62* .45*
4. Less work resources .34* .36* .36*
5. Less work effectiveness .68* .61* .51* .33*

Note. N = 112.
*p < .05 (2-tailed).

Statistical significance levels less than .05 mean that the relationship between two
variables is not due to chance (Salkind & Frye, 2020). The level of significance was set to p <
.05 with 95% confidence that the relationship between two variables is not due to chance. Also,
as shown in Table 7, the results of the Pearson’s tests indicated relationships between
perceptions of less work effectiveness and the independent variables.
Despite reliability less than .70 for each independent variable, the size of the correlation
supported all four hypotheses in this study. As shown in Table 6, perceptions of less work
effectiveness, the dependent variable for each hypothesis, had a strong statistical relationship
with emotional exhaustion (.68), a strong relationship with fatigue (.61), a strong relationship
with burnout (.50), and a moderate association with less work resources (.34), supporting the
59

hypothesis that these variables had significant associations with perceptions of less work
effectiveness.
Research Question 2: What Demographic Differences, if Any, Exist For LTC Frontline
Health Care Employee Perceptions of Emotional Exhaustion, Fatigue, Burnout, Less Work
Resources, and Perceptions of Less Work Effectiveness During the COVID-19 Pandemic?
Demographic variables were categorized into work and personal demographics to test the
associations between the variables. An analysis of variance (ANOVA) was computed using
SPSS. ANOVA is a collection of statistical models that test the statistical difference between two
or more means (Salkind & Frye, 2020). For data analysis, ANOVA was used to test participant
demographic means between groups and each participant’s demographic association with less
work effectiveness. ANOVA is an F-test named after founder R. A. Fisher. This test is needed
when more than one level of a group is tested. An F ratio was provided, and the relationship
between variables was tested for statistical significance at p < .05.
As shown in Table 8, number of years worked, F(4, 107) = 5.63, p < .001, and number of
hours worked, F(2, 107) = 3.52, p = .03, were associated with less work effectiveness.
Participants who had worked for 2 years or less (M = 2.67) reported more work effectiveness
than all other groups. The other significant between-group difference was between working less
than 2 years and working 3 to 5 years (M = 3.60), showing an increased perception of less work
effectiveness. The data showed significant differences between working 39 hours or less (3.20)
and 60 hours or more (M = 3.73), showing that increasing hours may reduce work effectiveness.

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Table 8
Means, Standard Deviations, and One-Way ANOVA for Work Demographic Characteristics and
Perceptions of Less Work Effectiveness
Demographic n M SD F p
License 66 3.25 0.74 1.41 .25
CNA 29 3.08 0.86
LPN 11 3.43 0.48
RN 26 3.37 0.66
Years worked 112 3.35 0.69 5.63* < .001
2 or less 16 2.67
a
0.75
3–5 16 3.60
b
0.61
6–10 15 3.45
b
0.57
11–20 27 3.35
b
0.52
21 or more 38 3.50
b
0.71
Hours worked 110 3.37 0.69 3.52* .03
39 or less 15 3.20
a
0.50
40–59 76 3.31 0.73
60 or more 19 3.73
b
0.51

Note. Significant ANOVA results with three or more groups were followed with a Fisher’s least
significant differences test. Differing groups are indicated by differing superscripts.

Except for gender, F(1, 107) = 5.03, p = .02, personal demographics did not show
statistically significant evidence of associations with less work effectiveness. As shown in Table
B (see Appendix B), women (M = 3.41) reported more work ineffectiveness than men (M =
2.90). Although only marginally significant (p < .10) perceived less work effectiveness was
associated with greater education. Participants with a high school diploma or equivalent
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sometimes experienced less work effectiveness (M = 2.92) and all other education levels
regularly experienced less work effectiveness (M = 3.33).
Next, ANOVA tests were run to compare means between work demographic groups to
obtain statistical evidence of work demographics’ associations with emotional exhaustion,
fatigue, burnout, and less work resources. As shown in Table C, participants’ number of years
worked had a statistically significant association with emotional exhaustion, F(4, 107) = 2.73, p
= .03, and burnout at work, F(4, 107) = 3.66, p = .008. When comparing means between groups,
participants who worked 2 years or less (M = 2.56) sometimes experienced emotional
exhaustion, compared to participants working 3 to 5 years (M = 3.50) who regularly experienced
emotional exhaustion. Within groups, burnout was reported once a week for participants working
6 to 10 years (M = 4.96) and once a month or less for those working 2 years or less (M = 3.21).
Hours worked were associated with emotional exhaustion, F(2, 107) = 5.18, p = .01;
fatigue, F(2, 107) = 4.98, p = .01; and burnout at work, F(2, 107) = 3.80, p = .02. As shown in
Table C (see Appendix C), findings also indicated that the number of hours worked affected
emotional exhaustion. Participants working 39 hours or less (M = 2.93) experienced less
exhaustion compared to those working 60 or more hours (M = 3.92). Hours worked and fatigue
had similar findings. Participants working 39 hours or less (M = 3.22) had significantly less
fatigue than participants working 60 or more hours (M = 3.87). For hours worked and burnout at
work, the findings were slightly different, with employees working 60 or more hours reporting
burnout a few times a month (M = 5.21) and employees working 40 to 59 hours reporting
burnout once a month or less (M = 4.17).
The final stage for demographic tests were ANOVAs run in SPSS to identify associations
between participant personal demographics and emotional exhaustion, fatigue, burnout at work,
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and less work resources. As shown in Table D (see Appendix D), education level was associated
with emotional exhaustion, F(4, 104) = 1.73, p = .16, and was the only personal demographic
associated with emotional exhaustion, fatigue, burnout, and less work resources. Although
education (p > .10) was not statistically significant, when comparing means between education
groups, the largest difference was between participants with a master’s degree (M = 3.38)
reporting regularly experiencing emotional exhaustion and participants who attended some
college or trade school (M = 2.92) reporting sometimes feeling emotionally exhausted.
Research Question 3: What, if Any, Specific Strategies Have Organizations and Leaders in
LTC Implemented That Support the Well-Being of Their Frontline Health Care Employees
During the COVID-19 Pandemic?
This findings section features data analysis and results from participant responses to four
open-ended items: (a) What policies or practices, if any, did your organization implement that
you felt supported your well-being during the pandemic? (b) Which of these did you feel was
most effective? (c) What strategies, if any, did your direct supervisor implement that you feel
supported your well-being during the pandemic? (d) Which of these did you feel was most
effective?
The participant sample responded to two open-ended questions about organizational
policies and procedures and supervisor strategies. Each item contained a follow-up question
regarding which strategy they felt was most effective. For data management and analysis, the
four responses collected from the Qualtrics survey were uploaded to ATLAS.ti statistical coding
software. Six a priori or precoding categories were named based on the literature from Chapter 2:
COVID-19 safety, COVID-19 paid time off, flexible scheduling, wellness resources, rewards
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and incentives, and social support. Each participant’s response was open coded and then
assigned to a category.
Once open coding was complete, 171 individual codes were placed into one of 13
individual categories. Five categories were added to the a priori coding for the organizational
items: (a) none, NA, or nothing; (b) food; (c) social gatherings; (d) all were effective; and (e)
none were effective. After open coding, three categories were added for supervisor strategies: (a)
communication, (b) support, and (c) time off. Responses were placed in categories, I analyzed
the findings, and ATLAS.ti statistical software was employed to run frequencies.
The most frequent responses for organizational policy and procedures that supported their
well-being were none, NA, or nothing. One respondent gave context to these responses,
“Nothing new. I ultimately have more work that no one else can do,” citing the CDC infection
control requirements. Twenty-two participants reported wellness-related resources were
provided: “Gave us information for mental health support and bought a couple of large massage
chairs … we broke in,” “offered a counselor,” “PTSD support group,” and “how to cope with
stress.” Other participants reported interventions with positive intentions: “Wellness committee,
but ineffective” or “ I feel like they tried to help, but it is hard to fully understand the impact of
what happened unless you worked hand on directly in it. … We were offered counseling later
into it.” Fourteen participants reported monetary incentives: “Double versus time and a half …
but only beneficial if you pick up extra hours/shifts,” “$1.00 an hour pay raise,” and “cards, gift
bags, bonus incentives to pick up extra hours … food … mental health.” Participants also
reported social gatherings such as “potlucks.” Frequent responses to the most effective
organizational policy and procedure during COVID-19 were none, NA, or nothing. Participants
also reported “morale is low,” “survivor of the fittest,” “don’t trust,” or “I can’t answer this
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question.” Participants shared incentives and rewards were effective such as “time off,” “double
time pay,” “all hands-on deck and acknowledgment of a job well done.” One participant
reported: “Bonus pay was a temp fix to a long-term problem. The stress … has basically ruined
everyday life for people.” Wellness resources were noted, such as “Employee Assistance
Program,” “support group was helpful,” and “counseling.” COVID-19 safety resources were
mentioned by participants, such as “helping with PPE” and “hand hygiene.” Other interventions
were reported: “relief fund selling PTO,” “activities for staff that didn’t have to do with work,”
and “agency workers helped but call off … like almost daily.” One participant reported: “There
is new anxiety and stress level that was not there before.” Table 9 shows a summary of the most
frequent responses to organizational items.

Table 9
Frequencies by Category for Organizational Policies or Practices and Most Effective
Organizational policy or
practice
Number of
respondents
Number of respondents
(most effective)
None, NA, or nothing 57 68
Wellness resources 22 7
Rewards and incentives 14 6
Food 7 1
Social gatherings 6 2

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Similar to organizational items, none, NA, or nothing was the most reported for
supervisor strategies. A few respondents added more context: “I can’t think of any”; “None. I
have been given many more tasks with 0 more assistance since the pandemic”; “I couldn’t take a
break with anyone, felt like I was in jail”; and “Our supervisors could have done a better job of
making a personal connection.” Participants who reported supervisor strategies that were helpful
to them seemed most focused on communication strategies: “phone calls,” “conversation,”
“asked about my wellbeing,” “setting time aside to talk to me,” “open door policy to vent our
frustrations out,” and “pay increases for direct staff.”
Some participants reported that no strategy was most effective, whereas a small number
reported effective strategies that mostly focused on communication and support from their
supervisors. Responses included: “weekly COVID calls,” “support and communication,”
“recognition,” “SUPPORT,” “listening,” “venting sessions, open door,” “ALWAYS HAD MY
BACK,” “allowed me time for talking, venting and crying,” “checking in on me,” and “able to
talk about things when they get overwhelming.” Responses also included COVID-19 safety:
“masks, gowns, gloves and goggles,” “weekly Covid testing,” “showed us how to wear our PPE
to properly prevent spreading … but, we still had people testing positive none of the strategies
worked,” and “safety for staff.” Other responses included “teamwork,” “bonuses,” “rewards and
recognition,” “counseling,” “time off,” and “food.” Table 10 shows the most frequent responses
by category for most effective supervisor strategies.

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Table 10
Frequencies by Category for Supervisor Strategies and Most Effective
Supervisor strategy Number of
respondents
Number of respondents
(most effective)
None, NA, or nothing 66 76
Support 10 3
Communication 9 3
COVID-19 safety 7 4
Flexible scheduling 7 4
Time off 5 4

Summary
The findings from this chapter addressed the three research questions. For Research
Question 1, the findings support the hypothesis that frontline health care employees’ emotional
exhaustion, fatigue, burnout, and less work resources were positively correlated with their
perceptions of less work effectiveness. Based on statistical analysis, participants’ perception of
less work effectiveness showed a strong statistical relationship to emotional exhaustion (r = .68),
fatigue (r = .61), burnout (r = .51), and a moderate statistical relationship to less work resources
(r = .33). Using a 5-point Likert scale, 1 (never) to 5 (always), descriptive statistics of less work
effectiveness showed that participants regularly felt perceptions of less work effectiveness (M =
3.35). The item-total statistical analysis showed that participants regularly experienced emotional
exhaustion (M = 3.27), regularly experienced fatigue (M = 3.37), and sometimes had less work
resources (M = 2.63). Burnout was measured using a 7-point Likert scale, 1 (never) to 7 (every
day). Participants reported they experienced burnout a few times a month or more (M = 4.33).
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Demographic variables were categorized into work and personal demographics for data analysis
to address Research Question 2.
To address Research Question 2, this study analyzed demographic differences, if any, in
participant perceptions of less work effectiveness, emotional exhaustion, fatigue, burnout, and
less work resources. First, ANOVAs were performed for work demographics. The participants’
number of hours worked each week, F(2, 107) = 3.52, p = .03, and the number of years worked
in LTC communities, F(4, 107) = 5.73, p < .001, showed a statistical relationship with
perceptions of less work effectiveness. Perceptions of less work effectiveness were impacted by
the number of hours participants worked each week. On average, participants who worked 60 or
more hours (M = 3.73) experienced less work effectiveness than people who worked 39 hours or
less (M = 3.20). Although participants regularly felt less work effectiveness on average, frontline
employees who had worked in LTC for 2 years or less (M = 2.67) only sometimes felt they were
not effective at work, whereas participants who worked 3 to 5 years (M = 3.60) regularly felt less
work effectiveness.
Next, ANOVA findings indicate that work demographics were also associated with
emotional exhaustion, fatigue, and burnout. Participants’ number of hours worked per week was
associated with emotional exhaustion (M = 3.28), fatigue (M = 3.38), and burnout (M = 4.35).
Participants who worked 60 or more hours experienced higher levels of emotional exhaustion (M
= 3.92), fatigue (M = 3.87), and burnout (M = 5.21). The number of years worked in LTC on
average was associated with emotional exhaustion (M = 3.26) and burnout (M = 4.33). In
participant groups, findings were similar for both emotional exhaustion and burnout. Participants
working 2 years or less on average experienced less emotional exhaustion (M = 2.56) and
burnout (M = 3.21) than all other years worked, including participants who worked 3 to 5 years,
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who reported feeling emotional exhaustion regularly (M = 3.50) and experiencing burnout (M =
4.90) a few times a month. Gender differences were associated with perceptions of less work
effectiveness.
Gender differences were the only personal demographic that showed statistically
significant evidence of an association with participants’ perception of less work effectiveness (p
= .02). When comparing female and male participants, on average, men (M = 2.90) reported
perceptions of more work effectiveness than women (M = 3.41). Female participants regularly
experienced perceptions of less work effectiveness, and men sometimes felt ineffective at work.
Gender differences were marginally associated with burnout (p = .06). Female participants
reported higher levels of burnout (M = 4.41) on average, a few times a month, whereas male
participants felt burnout (M = 3.50) once a month or less. Although education differences were
marginally statistically significant for emotional exhaustion (p = .16), when comparing means
between education groups, the largest differences were between participants with a master’s
degree (M = 3.38), who reported more regularly experiencing emotional exhaustion, and
participants who attended some college or trade school (M = 2.92), who reported sometimes
feeling emotionally exhausted. After analyzing demographic differences to address Research
Question 2, four open ended items were coded, placed in categories, and analyzed in response to
Research Question 3.
The findings from Research Question 3 involved data from two open-ended survey
questions about organizational policies and procedures and supervisor strategies. Each item
contained a follow-up question regarding which strategy was most effective. Overall, the most
frequent finding, discussed in Chapter 5, was that participants most frequently reported “none,
NA, or nothing” as interventions that supported their well-being during COVID-19. Participants
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added context: “moral [sic] is low,” “don’t trust,” and “I can’t answer this question.” In contrast,
participants also reported policies and practices they felt were most effective that were provided
by their organization included wellness resources (“Employee Assistance Programs,” “support
group was helpful,” and “counseling”) and COVID-19 safety resources (“helping with PPE” and
“hand hygiene”).
Regarding supervisor strategies that supported their well-being, the most frequent
responses were “none, NA, or nothing.” A few participants added more context: “I can’t think of
any”; “None. I have been given more tasks … since the pandemic”; “I couldn’t take a break with
anyone, felt like I was in jail”; and “our supervisors could have done a better job making a
personal connection.” Participants also reported supervisor strategies they felt were most
effective: (a) supervisor support (“checking in on me,” “listening,” “venting sessions,”
“ALWAYS HAD MY BACK,” communication, “weekly COVID calls,” “phone calls,” and
“support and communication”) and (b) COVID-19 safety (“weekly COVID testing,” “showed us
how to wear our PPE to prevent spreading … but none of the strategies worked,” “masks, gowns,
gloves, goggles”). The findings from Chapter 4 are linked to the literature and grounded in SCT
to identify three organizational recommendations in Chapter 5.

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Chapter Five: Recommendations
The purpose of this study was first, to examine employee beliefs about the impacts of
COVID-19 on their perceptions of less work effectiveness and associations to emotional
exhaustion, fatigue, burnout, and less work resources. Second, it explored what demographic
differences exist, if any, in perceptions of less work effectiveness, emotional exhaustion, fatigue,
burnout, and less work resources. Third, it identified what effective organizational policies and
supervisory strategies, if any, were implemented during the COVID-19 pandemic that may have
positively affected the well-being of frontline health care employees in LTC.
In this concluding chapter, I discuss the current study’s findings and link them to prior
literature. Following a discussion of the findings, I offer three recommendations for practice,
limitations and delimitations of the current study, recommendations for future research, and a
conclusion.
Discussion of Findings
Frontline health care employees have historically experienced elevated levels of
emotional exhaustion, fatigue, and burnout that affect their work effectiveness and turnover
(American Health Care Association, 2021; Carey et al., 2020; Lee-Baggley & Thakrar, 2020).
Carey et al. (2020) identified the cognitive load and psychological distress related to personal
infection, illness, and loss of infected patients, colleagues, and family members leading to
burnout. Baggley and Thakrar (2020) found psychological risks, with approximately 41% of
frontline workers experiencing at least one adverse mental health condition. The current study’s
findings reveal that during COVID-19, participants felt emotionally exhausted, fatigued, and
burned out and had perceptions of less work effectiveness. Female gender, more hours worked,
and more years of work in LTC communities were associated with more emotional exhaustion
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and burnout and perceptions of less work effectiveness. When considering organizational levers
and supervisor strategies to support well-being, a significant finding was that participants
reported no organizational policies and procedures and no supervisor strategies were effective for
supporting their well-being. A small number of participants reported their organizations offered
wellness resources and rewards and incentives. Supervisor strategies focused on support and
communication. A wide range of well-being interventions was initiated by the U.S. health system
during the COVID-19 pandemic.
The U.S. health system implemented policies and procedures in an attempt to reduce
burnout and increase employee well-being during the first year of the COVID-19 pandemic. To
identify the most frequently implemented interventions for burnout reduction and well-being
interventions for frontline health care employees, Zerden et al.’s (2021) scoping review of 20
U.S.-based articles from 11 states ranked the top interventions. In 80% of the articles, more than
one intervention was deployed, pointing to the need for multiple interventions and not a single
strategy. In Zerden et al.’s study, the eight most deployed strategies in order of frequency were
enhanced communication (70%); wellness initiatives (70%); individual counseling or support
and group or unit counseling and support (50%); provision of goods and services (40%); peer
support (30%); access to adequate personal protective equipment and supplies (25%); and
expanded workplace flexibility and role shifting (15%). Other findings indicated that burnout
interventions typically included multipronged strategies that targeted multiple systems to address
the health care workforce’s needs at the individual, organizational, and community levels
(Zerden et al., 2021).
During COVID-19, LTC nursing homes experienced frequent changes in national and
state safety regulations in an attempt to reduce the frontline health care employees’ and
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residents’ risk of COVID-19 exposure and illness. LTC organizations could not control
regulatory changes and seemed slow to respond. Pre-COVID-19 literature concluded that health
care employee burnout can result from unplanned organizational change. Day et al. (2017)
identified that organizational change was often unavoidable, but negative outcomes for
employees were preventable. Day et al.’s study examined the impact of organization-wide
change on health care professional burnout at work and found that unplanned change was
correlated to lower self-rated health and higher usage of stress-related medications. They also
examined organizational levers such as a positive work environment involving high supervisory
support and employee job control. A high level of supervisor support indicated improved
change-related stressors and reduced burnout. Guidetti et al. (2018) concluded that uncertainty
during organizational change led to a lessened sense of job control, more psychological
discomfort, job dissatisfaction, and intent to leave. Cooper (2014) concluded that reducing
uncertainty from organizational change means employees stay connected to a strong purpose
framed by fundamental goals and anchored in the organization’s mission. Eisenberger et al.
(2020) identified that perceived organizational support included fairness, employee input, and
transparency, which contribute to a positive work environment, reduced stress, increased job
satisfaction, and improved well-being.
Organizational levers for employee support were more critical than ever during COVID-
19. Although few of the current study’s participants identified effective interventions, the prior
literature highlight the importance of interventions: (a) burnout interventions such as mental
health services as a strategy to protect frontline employees and promote health care workers’
health and wellness, (b) importance of supervisors who are supportive and communicative, and
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(c) LTC organizational approaches that communicate change and ensure direct-care staff
members feel empowered.
The recommendations are based on the current study findings, peer-reviewed literature,
and theoretical underpinnings of SCT. I seek to inform and leverage LTC organizations’ limited
resources in a movement toward improved work culture for employee retention in LTC.
Recommendations include: (a) employee access to mental health services, (b) leadership training
(upskilling) and career trajectories for nurse leaders and supervisors, and (c) organization-wide
culture change with LTC frontline health care caregiver empowerment.
Recommendations for Practice
The level of each intervention is focused on a widening scope—individual, supervisor,
and larger work environment—and will require organizational stakeholder leverage and support
to be successfully implemented. Recommendations in this section focus on leveraging
organizational resources that may improve employee, resident, and organizational outcomes by
reducing the effects of emotional exhaustion, fatigue, and burnout on employee perceptions of
work effectiveness. maximize employee well-being, improve the quality of care for residents in
LTC nursing homes, and reduce frontline health care staff turnover. They include organizational
support for employees to obtain accessible and individualized mental health services;
organizational support for upskilling supervisors and career trajectories to develop
transformational nurse leaders; and organizational empowerment of CNA direct-care employees.
The first recommendation, access to counseling and support groups, has proven efficacy from
prior studies for addressing symptoms of psychological distress and burnout and improving
perceptions of work effectiveness, and it is a common strategy to support employee well-being.
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Recommendation 1: Organizational Support for Frontline Health Care Employees to
Obtain Accessible and Individualized Counseling and Support Groups
The prior literature shows that mental health counseling is an effective intervention to
reduce psychological distress and support employee well-being. When considering the individual
impacts of COVID-19, individual counseling has shown proven efficacy. Prior studies in other
health care sectors identified individual counseling and support groups as an essential
organizational support intervention during COVID-19 (Zerden et al., 2021). Access to individual
counseling and support groups was a well-documented and effective intervention for frontline
health care employees during the pandemic throughout the United States (Albott et al., 2020;
Feinstein et al., 2020; Gonzalez et al., 2020; Griffin et al., 2020; Kaslow et al., 2020; Lombardi
et al., 2020; Meier et al., 2020; Miotto et al., 2020; Ripp et al., 2020; Zerden et al., 2021).
Findings from the literature support counseling as a burnout resource and organizational support.
If mental health support were accessible and barriers were reduced or removed, the crisis-level
distress and continued emotional harm and long-term trauma from COVID-19 could be reduced
(Kaslow et al., 2020). Mental health resources could include individual and group counseling,
coaching, and 24-hour hotlines that could be implemented depending on the resources and size
of the LTC organization. Common implementation strategies are employee assistance programs,
partnerships with local mental health practices, contracts with a tele-mental health service, and
digital self-help apps (Zerden et al., 2021). Leaders and supervisors are also critically important
for encouragement and normalizing of help seeking to reduce the societal stigma of seeking
mental health support. Prior literature concluded that leaders and supervisors are also
instrumental in reducing employee strain levels and employees’ intent to stay at an organization
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(Kaslow et al., 2020). The second recommendation is an effort to upskill and train nurse
supervisors and leaders.
Recommendation 2: Organizational Support for Upskilling Supervisors and Career
Trajectories to Develop Transformational Nurse Leaders
Participants in the current study reported supervisor strategies that were most effective
focused on communication and support. Most supervisors in LTC nursing homes are RNs, and
despite more than 1.3 million nursing home residents in the United States, only 7% of RNs work
in nursing home facilities (BLS, 2021). RNs are often the most highly trained clinical health
providers LTC facilities at a given time, but they often receive no training for management and
leadership.
Prior literature indicated the value of supportive leadership and its relevance to reducing
employee burnout and improving perceptions of work effectiveness. Transformational leaders
have four behavioral attributes: idealized influence, inspirational motivation, intellectual
stimulation, and individualized consideration, which can help reduce frontline employee mental
health symptoms and prevent emotional exhaustion and burnout (Arnold, 2017).
Transformational leadership has positive effects on well-being, and other scholars agreed it helps
prevent negative symptoms of low well-being including mental health problems (Kelloway &
Barling, 2010; Kelloway et al., 2012).
Kelloway et al.’s (2012) findings go further by showing established trust in a leader as a
mediator of employee well-being, how such effects occur, and how distinct types of leadership
behavior exert an effect on trust and ultimately affect well-being. One strategy from the literature
for continuing education for nurse supervisors is a nurse residency program (NRP; Cline et al.,
2017). Nurses need to be effective communicators among the interdisciplinary care team,
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residents, and their families and must respond effectively to changes in residents’ status or
condition because collaborating providers, such as physicians, often are not readily available in
LTC (Cadmus et al., 2016; Neller et al., 2021). An NRP is one way to enhance novice nurses’
knowledge and skills in LTC supervisor-specific roles and responsibilities, provide career
trajectories for RNs, develop transformational nurse leaders, impact frontline health care
employee burnout, improve employee retention, and improve quality of care.
NRPs are common and found to be effective in post-acute and hospital settings, but they
are new in LTC, and the earliest known LTC program is based on Cadmus et al. (2016) and a
recently created NRP for LTC communities in Utah (Neller et al. 2021). An NRP involves
distance learning education designed to extend and supplement nurses’ base education by
including geriatric care content and competencies with an added mentoring and consultation
component. In addition to filling knowledge and skill gaps, effective nursing leadership
development can have several short-term impacts: It can be implemented strategically and
differently depending on the LTC organization’s commitment level and staffing needs, improve
RN recruitment and retention, and develop nurse leaders who effectively communicate and
support their frontline health care staff. Because this is a training and mentoring program, an
LTC-based NRP would need to feature a flexible time frame for completion, from 2 to 4 months.
The program requires a nurse facilitator and volunteer mentors, so developing stakeholder
partnerships and joining a consortium of LTC communities would be a cost-saving strategy
(Neller et al., 2021).
Recommendation 3: Organizational Empowerment of CNA Direct-Care Employees
This recommendation addresses the current study’s findings about the relationship of
number of work hours and emotional exhaustion, burnout, and perceptions of less work
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effectiveness. Prior literature showed that organizations that promote an employee empowerment
approach can improve work effectiveness and reduce employee turnover. For example, LTC
nursing homes involving NAs in resident care planning have reported lower turnover rates
(Probst et al., 2010). Based on a nationally representative sample of nursing homes and 2,897
CNAs, Probst et al. revealed a positive association between job satisfaction and organizational
climate, supervisor behavior, having sufficient time for tasks, being valued, and hourly earnings.
The empowered work team approach had positive effects on CNA empowerment, performance,
satisfaction, resident care, and choices and improved procedures, coordination, and cooperation
with other staff members.
Quantitative data also revealed a lower likelihood that CNAs exposed to the empowered
work teams would quit or be fired (Probst et al., 2010). The positive relationship between
empowerment and retention is consistent with other literature on the relationship between being
valued, job satisfaction, aligning schedules, encouraging teamwork, and CNA input (Berridge et
al., 2018; Bowers et al., 2016; Eaton et al., 2020).
There is a significant link between organizational culture of empowerment and job
satisfaction, intent to stay, and turnover (Berridge et al., 2018; Eaton et al., 2020). Utilizing data
from the 2009–2010 National Nursing Home Survey, Berridge et al.’s (2018) multivariate
ordered logistic regression of data from 2,034 nursing home administrators identified that staff
empowerment scores were positively related to higher retention rates. Moderate empowerment
scores resulted in a 44% greater likelihood of having higher retention, and high empowerment
scores indicated a 64% greater likelihood of having higher retention. Bowers et al. (2016) found
that value of staffing practices about retention speaks to the importance of CNA involvement;
inclusion; being involved in, informed, and at the table as part of a team; being valued; and job
78

satisfaction. More than 2,000 nursing home administrators identified the two most effective staff
empowerment practices were when CNAs were aware when a resident’s care plan had changed
and when they worked together to cover each other’s shifts. Strategically, LTC facilities begin
empowerment initiatives with improved communication across functions for improved
collaborative patient care and by training the nursing supervisors (e.g., Recommendation 2). It
seems a real day-to-day change in LTC work environment, flexible scheduling practices, and
increased involvement in resident care planning will improve the quality of care and value in the
organization.
Limitations and Delimitations
Limitations of quantitative research include reliability, internal validity, external validity,
replication, and generalizability. First, the development of a new survey instrument that
measured three constructs—emotional exhaustion, fatigue, and burnout—had inherent
challenges. With the exception of an alpha of .70 for the dependent variable of perceptions of
less work effectiveness, the instrument’s independent variables did not reach the research
standard for reliability. Although, the majority of Likert-style questions were adapted from prior
instruments and two items were adopted from the MBI-2 to ensure the reliability of each
variable, the newly constructed survey was not tested due to time constraints and lack of
experience with survey development. Prior to data collection, I completed a 10-person interrater
analysis of the questionnaire.
Participant sampling and sample size are two limitations to external validity and
replication. First, the participant sample was 88% White, whereas national demographics
indicate about 50% non-White individuals provide direct care in LTC nursing homes (Denny-
Brown et al., 2020). During exploratory demographic statistical analysis, a more diverse sample
79

may have identified more statistically significant personal demographic findings associated with
emotional exhaustion, fatigue, burnout, and perceptions of work effectiveness. The sample size
(N = 112) showed statistical power and effect sizes that met but did not exceed research
standards. I identified two delimitations related to SCT and discarding incomplete survey
responses during data cleanup.
The first delimitation identified here is that the current study’s conceptual framework, as
shown in Chapter 2, did not focus on all three elements of the SCT triad: person, behavior, and
environment. The collected data addressed two constructs, the employee and the organization.
The findings and connections to SCT may have seemed more complete with an additional
research question regarding employees’ behaviors or actions they had taken to improve their
well-being during the COVID-19 pandemic. The second delimitation was the choice following
data collection to discard incomplete surveys. I reviewed each incomplete survey, and, in most
instances, the participant did not fill in the open-ended questions, so they were removed from the
sample to obtain a clean dataset.
Recommendations for Future Research
I recommend the current study be replicated while recruiting from a wider geographic
area, where a larger and racially more diverse participant sample may be more available. Also,
during future research with this less empowered direct-care provider group, researchers should
add interviews or focus groups with volunteer participants following completion of the survey.
Whether the sample size is larger than 112, a mixed-methods approach will provide additional
context as to participants’ beliefs about how emotional exhaustion, fatigue, and burnout
contribute to employee perception of less work effectiveness. Follow-up interviews would also
clarify the benefits of organizational and supervisor strategies that did or did not support their
80

well-being. Also, because of the staffing crisis in LTC and the multiple generations of workers in
the workforce, consideration of what attracts and affirms decisions to stay in the LTC sector
using a multigenerational approach may help organizations and leaders develop healthy work
cultures and add benefits that are aligned with employee values. They should consider what
attracts these groups to LTC nursing communities as a career in the face of the staffing crisis that
looms throughout the United States.
Conclusion
Professionals on the front lines in LTC communities provide direct care for the world’s
most medically challenged and aging adults. The literature prior to COVID-19 painted the
picture of an already struggling LTC system that has historically experienced turnover and
staffing shortages and was caught largely unprepared for the COVID-19 pandemic.
LTC community administrators and chief leaders have expressed concern about the
frontline health care staffing crisis. Readers are encouraged to consider the findings of the
current study and find pathways to culture change and recovery. Millions of aging adults require
medical care in LTC communities. To ameliorate the staffing and turnover crisis, it is important
to strategically align the work culture and leverage organizational resources with the values of
the frontline health care workforce.

81

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97

Appendix A: Qualtrics Survey Protocols
Your participation in this survey is important to understanding how the COVID-19 pandemic
affects frontline health care employees’ well-being in long-term care nursing homes and to
identify which organizational strategies implemented during COVID-19 are most successful in
improving employee well-being.

Question Response options
(if close-ended)
Concept
measured
Instrument
adopted or
adapted
Citation
1. How long have
you been
working in long
term care
nursing homes?
Less than 1 year,
1–2 years, 3–5
years, 6–10
years, 11–20
years, 21+ years
Demographic Created for
this study

2. What is your
current level of
health care
practice license
or certification?
Nurse assistant,
certified nurse
assistant,
licensed
practical nurse,
registered nurse,
other
Demographic Created for
this study

3. What is the
average number
of hours you
work each
week?
Less than 20
hours, 20–39
hours, 40–59
hours, 60 hours
or more
Demographic Created for
this study

4. I feel burned
out from my
work.
7-point Likert
scale: never, a
few times a year
or less, once a
month or less, a
few times a
month, once a
week; a few
Burnout Maslach
Burnout
Inventory-2
West et al. (2012)
98

times a week,
every day
5. I have become
more callous
toward people
since I took this
job.
7-point Likert
scale: never, a
few times a year
or less, once a
month or less, a
few times a
month, once a
week; a few
times a week,
every day
Burnout Maslach
Burnout
Inventory-2
West et al. (2012)
6. Mentally, I feel
exhausted.
5-point Likert
scale: never,
sometimes,
regularly, often,
always
Emotional
exhaustion
Fatigue
Assessment
Scale
Michielsen et al.
(2004)
7. Physically, I
feel exhausted.
5-point Likert
scale: never,
sometimes,
regularly, often,
always
Fatigue Fatigue
Assessment
Scale
Michielsen et al.
(2004)
8. I have enough
energy for
everyday life.
5-point Likert
scale: never,
sometimes,
regularly, often,
always
Fatigue Fatigue
Assessment
Scale
Michielsen et al.
(2004)
9. When I am
doing
something, I can
concentrate
quite well.
5 point-Likert
scale: never,
sometimes,
regularly, often,
always
Fatigue Fatigue
Assessment
Scale
Michielsen et al.
(2004)
10. In the last
month, how
often have you
felt that you
were unable to
control the
important things
in your life?
5-point Likert
scale: never,
almost never,
sometimes,
fairly often,
very often
Emotional
exhaustion
Perceived
Stress Scale
Cohen et al. (2014)
99

11. In the last
month, how
often have you
felt confident
about your
ability to handle
your problems
at work?
5-point Likert
scale: never,
almost never,
sometimes,
fairly often,
very often
Work
effectiveness
Perceived
Stress Scale
(“at work”
added for
context)
Cohen et al. (2014)
12. In the last
month, how
often have you
felt difficulties
at work were
piling up so
high that you
could not
overcome them?
5-point Likert
scale: never,
almost never,
sometimes,
fairly often,
very often
Work
effectiveness
Perceived
Stress Scale
(“at work”
added for
context)
Cohen et al. (2014)
13. I have the
materials and
equipment I
need to do my
work right.
5-point Likert
scale: strongly
disagree,
disagree, neither
agree nor
disagree, agree,
strongly agree
Work
resources
Q12
Employee
Engagement
Survey
Gallup. (2021)
14. My supervisor
or someone at
work seems to
care about me
as a person.
5-point-Likert
scale: strongly
disagree,
disagree, neither
agree nor
disagree, agree,
strongly agree
Work
resources
Q12
Employee
Engagement
Survey
Gallup. (2021)
15. How do you
compare your
current
effectiveness in
your work
relative to
before the
pandemic?
5-point Likert
scale:
significantly
less effective,
somewhat less
effective, same
level of
effectiveness,
somewhat more
effective, and
significantly
more effective
Work
effectiveness
before and
after
COVID-19
Developed for
this study
with
thematic
dissertation
group
consensus

100

16. How do you
compare your
current well-
being at work
relative to
before the
pandemic?
5-point Likert
scale:
significantly
less, somewhat
less, same level,
somewhat more,
and
significantly
more
Well-being
before and
during
COVID-19
Question
developed
for this
study with
thematic
dissertation
group
consensus

17. What policies
or practices, if
any, did your
organization
implement that
you felt
supported your
well-being
during the
pandemic?
Which of these
did you feel was
most effective?
Open ended Organizationa
l support
for
employee
well-being
Question
developed
for this
study with
thematic
dissertation
group
consensus

18. What
strategies, if
any, did your
direct
supervisor
implement that
you feel
supported your
well-being
during the
pandemic?
Which of these
did you feel was
most effective?
Open ended Supervisor or
leader
strategies
for
employee
well-being
Question
developed
for this
study with
thematic
dissertation
group
consensus

19. What is your
highest level of
education?
Terminal degree
(doctorate),
master’s degree,
bachelor’s
degree,
associate
degree, some
college, trade or
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
Toor (2020)
101

technical
school, high
school diploma
or equivalent,
prefer not to
answer
20.What is your
marital status?
Divorced,
domestic
partnership,
never married,
now married,
separated,
widowed, prefer
not to answer
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
Toor (2020)
21.What is your
gender?
Female, male,
prefer to
describe _____,
prefer not to
answer
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
U.S. Census Bureau
(2021)
22.What is your
ethnicity?
Hispanic or
Latino, non-
Hispanic or
non-Latino,
prefer not to
answer
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
U.S. Census Bureau
(2022a)
23. What is your
race? (Select all
that apply)
American Indian
or Alaska
Native, Asian,
Black, or
African
American,
Native
Hawaiian or
other Pacific
Islander, White,
prefer to
describe _____,
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
U.S. Census Bureau
(2022b)
102

prefer not to
answer
24. In what year
were you born?
Enter year:
________,
prefer not to
answer
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus

25. What is your
current
household
income?
Less than $25,000,
$25,000–
49,999,
$50,000–
$99,999,
$100,000–
$199,000,
$200,000 or
more, prefer not
to answer
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
Toor (2020)
26. Including
yourself, how
many people
live in your
household?
Fill in the blank:
__________
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
Toor (2020)
27. How many
dependents do
you have in
your household?
[If participants
state 0, then
skip to end of
survey.
Depending on
the number of
dependents
stated, a follow-
up question is
asked: How old
is Dependent 1?
Fill in the blank:
__________
[After last
dependent’s age
is entered,
respondent may
choose: No
more
dependents]
Demographic Question
developed
for this
study with
thematic
dissertation
group
consensus
Toor (2020)
103

This continues
until there are
no more
dependents.]

104

Appendix B: Personal Demographics ANOVA Table
Table B
Means, Standard Deviations, and One-Way ANOVA for Personal Demographic Differences and
Relationship to Perceptions of Less Work Effectiveness
Demographic n M SD F p
Marital status 104 3.35 0.69 2.25 .08
Domestic partnership 6 3.62 0.72
Never married 16 3.03 0.90
Now married 67 3.35 0.62
Separated, divorced, or widowed 15 3.61 0.63
Gender 109 3.27 1.04 5.03* .02
Female 99 3.38 1.04
Male 10 2.95 1.03
Household income 99 3.38 0.07 1.25 .29
Less than $25,000 8 3.34 1.07
$25,000–$49,000 15 3.06 0.85
$50,000–$99,000 31 3.45 0.63
$100,000–$199,000 33 3.52 0.57
$200,000 or more 12 3.29 0.63
Race 104 3.36 0.70 00.11 .74
White 98 3.35 0.72
Person of color 6 3.45 0.70
Education 107 3.33 0.69 1.99 .10
Master’s degree 21 3.44 0.66
Bachelor’s degree 30 3.51 0.63
Associate degree 21 3.35 0.67
Some college or trade school 22 3.21 0.75
High school diploma or equivalent 13 2.92 0.73
Age 106 3.38 0.69 2.30 .08
30 or younger 19 3.21 0.77
31–45 37 3.31 0.65
46–60 38 3.61 0.61
61 or older 12 3.18 0.82
Household members 112 3.35 0.06 0.30 .82
2 or fewer 49 3.41 0.71
3 or 4 40 3.30 0.71
5 or 6 18 3.37 0.58
7 or more 5 3.15 0.87
Dependents in household 109 3.34 0.69 0.09 .91
None 46 3.32 0.70
105

1 or 2 47 3.35 0.76
3–5 16 3.40 0.12
Age range of dependents 64 3.36 0.69 1.98 .13
0–5 12 3.66 0.63
6–12 26 3.38 0.60
13–18 14 3.37 0.69
19 or older 12 3.00 0.83

106
Appendix C: Work Demographics ANOVA Table
Table C
Means, Standard Deviations, and One-Way ANOVA for Work Demographic Differences and Relationship to Emotional Exhaustion,
Fatigue, Burnout, and Less Work Resources
Emotional exhaustion Fatigue Burnout at work Lack of work resources
n M SD F p M SD F p M SD F p M SD F p
License 66 3.21 1.08 0.94 .39 3.37 0.85 1.23 .29 4.31 1.50 0.09 .29 2.78 1.09 .57 .57
CNA 29 3.01 1.03 3.19 3.60 4.32 1.63 2.78 1.09
LPN 11 3.45 0.96 3.60 0.71 4.13 1.58 2.82 1.21
RN 26 3.34 1.17 3.47 0.83 4.38 1.50 2.63 0.92
Years worked 112 3.26 1.03 2.73* .03 3.51 0.78 1.35 .25 4.33 1.52 3.66* .008 2.63 0.97 1.32 .35
2 or less 16 2.56
a
1.10 3.04 0.91 3.21
a
1.72 2.25 0.93
3–5 16 3.50
b
0.77 3.54 0.70 4.90
b
1.55 2.87 0.90
6–10 15 3.30
b
0.97 3.31 0.76 4.96
b
1.23 2.80 0.95
11–20 27 3.18
b
1.02 3.28 0.72 4.27
b
1.44 2.74 1.01
21 or more 38 3.48
b
1.03 3.51 0.78 4.34
b
1.39 2.55 0.99
Hours worked 110 3.28 1.02 5.18* .01 3.38 0.78 4.98* .01 4.35 1.51 3.80* .02 2.64 0.98 0.30 .74
39 or less 15 2.93
a
0.84 3.22
a
0.72 4.23
a
1.55 2.73 0.97
40–59 76 3.19 1.05 3.28 0.78 4.17
a
1.48 2.59 0.98
60 or more 19 3.92
b
0.80 3.87
b
0.64 5.21
b
1.39 2.76 1.03

Note. Significant ANOVA results with three or more groups were followed with a Fisher’s least significant differences test. Differing
groups are indicated by differing subscripts.

107
Appendix D: Personal Demographics ANOVA Table
Table D
Means, Standard Deviations, and One-Way ANOVA for Personal Demographic Differences and Relationship to Emotional
Exhaustion, Fatigue, Burnout, and Less Work Resources
Demographic Emotional exhaustion Fatigue Burnout at work Lack of work resources
n M SD F p M SD F p M SD F p M SD F p
Marital status 104 3.27 1.04 0.38 .76 3.48 0.89 0.97 .40 4.35 1.49 0.34 .79 2.57 0.92 0.30 .92
Domestic partnership 6 3.25 0.88 3.77 0.62 4.41 1.88 2.33 0.98
Never married 16 3.15 1.01 3.39 0.91 4.31 1.57 2.62 0.95
Now married 67 3.25 1.00 3.27 0.73 4.43 1.46 2.55 0.87
Separated, divorced,
or widowed
15 3.53 1.30 3.48 0.89 4.00 1.45 2.73 1.14
Gender 109 3.27 1.04 1.06 .30 3.35 0.77 1.21 .27 4.33 1.51 3.39 .06 2.61 0.96 0.04 .83
Female 99 3.38 1.04 3.38 0.77 4.41 1.52 2.61 0.98
Male 10 2.95 1.03 3.10 0.81 3.50 1.05 2.55 0.68
Household income 99 3.26 1.02 1.41 .23 3.36 0.80 0.96 .43 4.26 1.53 1.54 .19 2.60 0.93 1.41 .23
Less than $25,000 8 2.62 1.50 3.04 1.09 3.81 2.32 3.00 1.69
$25,000–$49,000 15 3.10 0.82 3.24 0.96 3.83 1.71 2.50 0.88
$50,000–$99,000 31 3.40 1.05 3.51 0.71 4.43 1.21 2.79 0.95
$100,000–$199,000 33 3.43 0.89 3.42 0.81 4.63 1.38 2.54 0.75
$200,000 or more 12 3.04 1.11 3.13 0.50 3.66 1.68 2.16 0.65
Race 104 3.25 1.05 1.46 .23 3.35 0.77 0.37 .54 4.29 1.52 1.75 .18 2.58 0.93 1.85 .17
White 98 2.75 1.03 3.36 0.78 4.34 1.51 2.55 0.92
Person of color 6 2.75 1.03 3.16 0.69 3.50 1.58 3.08 0.91
Education 107 3.24 1.04 1.73 .16 3.36 0.85 0.94 .42 4.35 1.66 0.97 .40 2.60 0.96 1.44 .23
Master’s degree 21 3.38

0.97 3.34 0.62 4.38 1.38 2.35 0.69
Bachelor’s degree 30 3.46 0.92 3.47 0.70 4.65 1.34 2.60 0.73
Associate degree 21 3.33 1.24 3.49 0.94 4.45 1.70 2.95 1.12
Some college or trade
school
35 2.92

1.00 3.19 0.85 4.01 1.66 2.54 1.12
Age 106 3.27 1.00 1.38 .25 3.41 0.75 1.47 .22 4.32 1.53 0.55 .64 2.65 0.96 0.46 .71

108
30 or younger 19 3.05 1.03 3.19 0.70 4.21 1.68 2.42 0.82
31–45 37 3.20 0.94 3.36 0.87 4.56 1.67 2.71 1.07
46–60 38 3.52 0.96 3.60 0.57 4.23 1.26 2.68 0.94
61 or older 12 3.27 1.00 3.33 0.86 4.00 1.74 2.75 0.96
Household members 112 3.26 1.03 0.71 .54 3.36 1.03 0.24 .86 4.33 1.52 0.65 .58 2.63 0.97 0.62 .59
2 or fewer 49 3.36 1.02 3.43 0.75 4.50 1.42 2.64 1.00
3 or 4 40 3.16 0.93 3.30 0.85 4.33 1.63 2.53 0.96
5 or 6 18 3.11 1.25 3.37 0.77 3.84 1.61 2.88 1.02
7 or more 5 3.70 1.15 3.26 0.64 4.00 1.45 2.40 0.65
Dependents 109 3.26 1.03 0.24 .78 3.37 0.79 0.29 .74 4.35 1.53 0.35 .70 2.61 0.96 1.94 .15
None 46 3.32 0.98 3.42 0.70 4.50 1.42 2.58 0.96
1 or 2 47 3.18 1.10 3.31 0.92 4.23 1.63 2.48 0.94
3–5 16 3.31 1.07 3.43 0.62 4.31 1.56 3.03 0.95
Age of dependents 64 3.20 1.08 0.62 .60 3.34 0.84 0.64 .59 4.21 1.61 2.27 .089 2.63 0.96 0.12 .94
0–5 12 3.50 0.88 3.61 0.69 5.16 1.73 2.54 0.89
6–12 26 3.25 1.18 3.35 0.77 4.13 1.57 2.71 1.03
13–18 14 3.12 1.14 3.23 0.72 3.57 1.42 2.64 0.74
19 or older 12 3.12 1.00 3.16 1.22 4.20 1.54 2.54 1.19

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Asset Metadata

Creator Baker, Cynthia Elaine (author)

Core Title Organizational levers for frontline health care employee well-being in long-term care

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2022-08

Publication Date 08/04/2022

Defense Date 08/02/2022

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Burnout,COVID-19,emotional exhaustion,employee well-being,fatigue,frontline health care employee,long-term care nursing home,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Adibe, Bryant (committee chair), Hirabayashi, Kim (committee member), McNevin, Mary (committee member)

Creator Email cebaker@usc.edu,renewagility@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC111376141

Unique identifier UC111376141

Legacy Identifier etd-BakerCynth-11102

Document Type Dissertation

Format application/pdf (imt)

Rights Baker, Cynthia Elaine

Type texts

Source 20220805-usctheses-batch-970 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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Repository Name University of Southern California Digital Library

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Repository Email cisadmin@lib.usc.edu