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Examining the impact of job burnout on the well-being of human service workers
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1
Examining the Impact of Job Burnout on the Well-being of
Human Service Workers
Erica Leeanne Lizano, MSW, MPA
Dissertation
Dissertation Guidance Committee
Michalle Mor Barak, Ph.D. (Chair)
Bruce Jansson, Ph.D.
Peter Robertson, Ph.D.
2
“ W ork is about a search for daily meaning as well as daily bread, for recognition as well
as cash, for astonishment rather than torpor; in short, for a sort of life rather than a
Monda y throu g h F rid a y sort of d y in g . ”
― Studs Terkel
3
DEDICATION
This dissertation is dedicated to several important key figures in my
life who have given me enduring support, love, and inspiration. I would like to thank my
mother, Rosa Mirian Lizano who taught me to brave through struggle. My grandmother
Doña Betina Lizano, who had the courage and wherewithal to embark on a journey to the
United States in search of a better life. Were it not for the strength and perseverance of
my mother and grandmother, I would not have had the privilege to pursue higher
education. To the most important man in my life, my younger brother, Richard Lizano,
thank you for being one of my biggest cheerleaders and supporters. I would like to thank
my friend, colleague; my sister in arms, the woman who has taught me the true definition
of solidarity, Dr. Brooklyn Levine. Lastly, I would like to dedicate this dissertation to the
Salvadoran community, the community where I learned the value of social justice and
was inspired to become a social worker.
4
ACKNOWLEDGEMENTS
I would like to thank the members of my dissertation committee for guiding and
supporting me through the process of writing my dissertation. To my dissertation chair,
and mentor, Dr. Michalle Mor Barak, thank you for your on-going support during my
doctoral education journey. To Dr. Bruce Jansson, thank you for serving as a nurturing
guide in my doctoral studies from the day I began. To Dr. Peter Robertson, thank you for
joining the social work faculty in this process. Your contribution to my research has been
invaluable.
My path to and through my doctoral education would not have been feasible
without lifelong mentorship. To Dr. Dnika Travis, thank you for the many lessons that
you have imparted upon me on the meaning of being a social worker and a scholar. Your
energy and enthusiasm for social work is contagious and I consider myself privileged to
have you as a mentor. To Dr. Annalisa Enrile, thank you for teaching me to be
courageous when navigating through uncharted waters. To Mr. Gerald Bryant, thank you
for teaching me to unapologetically demand that I be seen not as a “ mi nority student” but
as the scholar that I am. To Rachel Camacho, the first Latina college graduate I ever met,
thank you for teaching me to walk with a purpose and for serving as evidence that I too
could reach my academic goals. To Dr. Roderick Magbual, thank you for planting in me
the seed of interest in graduate education.
5
APPENDIX
Appendix A: Measurement items
6
LIST OF TABLES
Table 1. Study 1 Systematic Review Search Terms
Table 2. Study 1 Summary of Studies Examining the Relationship between
Job Burnout and Worker Well-being
Table 3. Demographic Characteristics of Study Sample
Table 4. Study 2 Correlation Matrix
Table 5. Study 2 Baseline Model Goodness-of-fit Statistics
Table 6. Study 2 Goodness-of-fit Statistics for Constrained and Unconstrained Models By
Organizational Support
Table 7. Study 2 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Supervisory Support
Table 8. Study 2 Goodness-of-fit Statistics for Constrained and Unconstrained Models By
Specialized Child Welfare Training
Table 9. Study 2 Path Coefficients of Full Baseline Model
Table 10. Study 2 Path Coefficients of Multi-Group Path Model of Work Place Demands,
Job burnout, and Job Satisfaction for Low and High Organizational Support Groups
Table 11. Study 2 Path Coefficients for Multi-Group Path Model of Work Place
Demands, Job burnout, and Job Satisfaction for Low and High Supervisory Support
Groups
Table 12. Study 2 Path Coefficients for Multi-Group Path Model of Work Place
Demands, Job burnout, and Job Satisfaction among Those With and Without
Specialized Child Welfare Training
7
Table 13. Study 3 Correlation Matrix
Table 14. Study 3 Baseline Model Fit Statistics
Table 15. Study 3 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Organizational Support
Table 16. Study 3 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Supervisory Support
Table 17. Study 3 Baseline Model Path Coefficients
Table 18. Study 3 Path Coefficients for Multi-Group Path Model of Work Place
Demands, Job burnout, and Job Satisfaction for Low and High Organizational Support
Groups
Table 19. Study 3 Path Coefficients for Multi-Group Path Model of Work Place
Demands, Job burnout, and Job Satisfaction for Low and High Supervisory Support
Groups
8
LIST OF FIGURES
Figure 1. Conceptual Model: The Impact of Job Burnout Dimensions on
Worker Well-being
Figure 2. Conceptual Framework of Job Demands and Resources,
Job Burnout and Job Satisfaction
Figure 3. Conceptual Framework of Job Demands and Resources,
Job Burnout and Psychological Well-being
Figure 4. Study 2 Baseline Model of Job Demands, Burnout, and Job Satisfaction
Figure 5. Study 2 Multi-group Model of High and Low Organizational Support, Job
Demands, Burnout and Job Satisfaction
Figure 6. Study 2 Multiple Sample Model of High and Low Supervisory Support, Job
Demands, Burnout, and Job Satisfaction
Figure 7. Study 2 Multiple Sample Model of Specialized Child Welfare Training, Job
Demands, Burnout, and Job Satisfaction
Figure 8. Study 3 Baseline Model of Job Demands, Burnout, and Psychological Well-
being
Figure 9. Study 3 Multi-group Model of High and Low Organizational Support, Job
Demands, Job Burnout and Psychological Well-being
Figure 10. Study 3 Multiple Sample Model of High and Low Supervisory Support, Job
Demands, Burnout, and Psychological Well-being
9
TABLE OF CONTENTS
LIST OF TABLES PAGE
Table 1: Study 1 Systematic Review Search Terms
Table 2: Study 1 Summary of Studies Examining the Relationship
between Job Burnout and Worker Well-being
Table 3: Demographic Characteristics of Study Sample
Table 4: Study 2 Correlation Matrix
Table 5: Study 2 Baseline Model Goodness-of-fit Statistics
Table 6: Study 2 Goodness-of-fit Statistics for Constrained and
Unconstrained Models By Organizational Support
Table 7: Study 2 Goodness-of-fit Statistics for Constrained and
Unconstrained Models By Supervisory Support
Table 8: Study 2 Goodness-of-fit Statistics for Constrained and
Unconstrained Models By Specialized Child Welfare Training
Table 9: Study 2 Path Coefficients of Full Baseline Model
Table 10: Study 2 Path Coefficients of Multi-Group Path Model of
Work Place Demands, Job burnout, and Job Satisfaction for Low
and High Organizational Support Groups
Table 11: Study 2 Path Coefficients for Multi-Group Path Model of
Work Place Demands, Job burnout, and Job Satisfaction for Low
and High Supervisory Support Groups
Table 12: Study 2 Path Coefficients for Multi-Group Path Model of
Work Place Demands, Job burnout, and Job Satisfaction among
Those With and Without Specialized Child Welfare Training
Table 13: Study 3 Correlation Matrix
Table 14: Study 3 Baseline Model Fit Statistics
Table 15: Study 3 Goodness-of-fit Statistics for Constrained and
Unconstrained Models
By Organizational Support
Table 16: Study 3 Goodness-of-fit Statistics for Constrained and
Unconstrained Models By Supervisory Support
Table 17: Study 3 Baseline Model Path Coefficients
Table 18: Study 3 Path Coefficients for Multi-Group Path Model of
Work Place Demands, Job burnout, and Job Satisfaction for Low
and High Organizational Support Groups
Table 19: Study 3 Path Coefficients for Multi-Group Path Model of
Work Place Demands, Job burnout, and Job Satisfaction for Low
and High Supervisory Support Groups
26
57
112
113
114
115
116
117
118
119
120
121
160
161
162
163
164
165
166
LIST OF FIGURES
Figure 1: Conceptual Model: The Impact of Job Burnout
Dimensions on Worker Well-being
25
10
Figure 2: Conceptual Framework of Job Demands and Resources,
Job Burnout and Job Satisfaction
Figure 3: Conceptual Framework of Job Demands and Resources,
Job Burnout and Psychological Well-being
Figure 4: Study 2 Baseline Model of Job Demands, Burnout, and
Job Satisfaction
Figure 5: Study 2 Multi-group Model of High and Low
Organizational Support, Job Demands, Burnout and Job
Satisfaction
Figure 6: Study 2 Multiple Sample Model of High and Low
Supervisory Support, Job Demands, Burnout, and Job Satisfaction
Figure 7: Study 2 Multiple Sample Model of Specialized Child
Welfare Training, Job Demands, Burnout, and Job Satisfaction
Figure 8: Study 3 Baseline Model of Job Demands, Burnout, and
Psychological Well-being
Figure 9: Study 3 Multi-group Model of High and Low
Organizational
Support, Job Demands, Job Burnout and Psychological Well-being
Figure 10: Study 3 Multiple Sample Model of High and Low
Supervisory Support, Job Demands, Burnout, and Psychological
Well-being
27
28
122
124
126
126
128
167
169
171
ABSTRACT 12
CHAPTER ONE INTRODUCTION, RATIONALE, AND REVIEW OF THE
THREE STUDIES
Introduction
Dissertation Structure
Literature Review
Theoretical frameworks: JD-R Model
References
13
13
15
16
20
29
CHAPTER TWO (STUDY 1):
EXAMINING THE IMPACT OF JOB BURNOUT ON WORKER HEALTH
AND WELL-BEING: A SYSTEMATIC REVIEW AND SYNTHESIS
Introduction
Literature Review
Method
Synthesis of Studies
Discussion and Implications
Study Limitations
References
34
34
36
40
43
47
50
51
11
CHAPTER THREE (STUDY 2): JOB BURNOUT AND AFFECTIVE WELL-
BEING: A LONGITUDINAL STUDY OF BURNOUT AND JOB
SATISFACTION AMONG PUBLIC CHILD WELFARE WORKERS
Introduction
Review of Literature
Methods
Results
Discussion
Implications
Study Limitations
References
65
65
67
76
84
92
96
98
99
CHAPTER FOUR (STUDY 3): BURNOUT AND PSYCHOLOGICAL
WELL-BEING: A LONGITUDINAL STUDY
Introduction
Literature Review
Method
Results
Discussion
Implications
Study Strengths and Limitations
References
130
130
131
139
147
152
157
159
172
CHAPTER 5
INTERGRATION AND IMPLEMENTATION OF FINDINGS FROM THE
THREE STUDIES
Purpose of the Studies
Overall Major Findings
Theory, Practice, and Policy Implications
Implications for Future Research
References
176
176
177
183
185
188
12
Abstract
Presented here is a three-study dissertation with an overarching goal of
contributing to a greater understanding of the impact of job burnout on worker well-being
in the human service sector. Each of the three studies makes a unique contribution to this
overarching goal. Chapter I presents a discussion integrating the logical link among the
three studies, briefly introduces the purpose and description of each, and provides an
overview of the theories driving the three studies. Chapter II (Study 1) is comprised of a
systematic review of literature focusing on the effect of job burnout on worker well-being
in the human service sector. Chapter III (Study 2) presents findings from a test of a
theory-based model of the relationship between job demands and resources, job burnout,
and job satisfaction over time. Chapter IV (Study 3) presents the findings of a test of a
theory-based model of the relationships between job demands and resources, job burnout,
and psychological well-being over time. An integrated discussion of study findings,
conclusions and implications for future social work research and practice are presented in
Chapter V.
13
CHAPTER ONE
INTRODUCTION, RATIONALE, AND REVIEW OF THE THREE STUDIES
Introduction
Though rewarding, working in helping professions can be challenging.
Interpersonal contact is a core characteristic of human service work and also a potential
source of emotional and interpersonal stressors resulting from the demands of providing
care (Maslach, Schaufeli, & Leiter, 2001). Human service work requires that employees
serve clients who are in a state of vulnerability or crisis and this often times makes the
interpersonal exchange emotionally charged (Hasenfeld, 2010). As vehicles for change,
human service workers make great emotional investments when working with
clients/consumers (Hasenfeld, 2010), a process that can lead to feelings of emotional
exhaustion and cynicism (Maslach, 2003). In addition to the emotional demands of
interpersonal exchanges with clients, workplace conditions such as high workloads
(Arrington, 2008; Ballenger et al., 2011; Broome, Knight, Edwards, & Flynn, 2009), risk
of violence when working with clients (Brockmann, 2002; Littlechild, 2005; Shin, 2011)
and low compensation in comparison to other professions (Arrington, 2008; GAO, 2003)
are added stressors to human service work.
Though the number of burnout studies conducted has grown extensively since the
inception of this area of research in the 1970s, several gaps remain in the job burnout
knowledgebase within the human service sector. Previous studies on burnout and
employee well-being have not been systematically reviewed and synthesized. Such a
synthesis can help inform administration and policy decision-making, and aide in guiding
14
future burnout and worker well-being research in the human service sector. A critical
limitation in previous studies on burnout and worker well-being includes a lack of studies
using longitudinal research designs. Burnout is postulated to be a developmental
phenomenon (Maslach, 1998), yet the majority of the studies on burnout and well-being
among human service workers are cross-sectional in nature (Hombrados-Mendieta &
Cosano-Rivas, 2011; Korkeila et al., 2003; Ogresta, Rusac, & Zorec, 2008; Piko, 2006;
Puig et al., 2012). Cross-sectional studies limit the ability to observe the development of
job burnout and its consequences over time. Proposed here is a three-study dissertation
with an overarching goal of contributing to a greater understanding of the impact of job
burnout on worker well-being in the human services sector. Each of the three studies
makes a unique contribution to this overarching goal. Study objectives are as follows:
Study 1: To systematically review and synthesize findings from studies
examining the impact of emotional exhaustion, depersonalization and
personal accomplishment on the psychological/affective, physical, and
behavioral well-being of human service workers.
Study 2: To empirically study the impact of job demands on burnout development
and its subsequent influence on job satisfaction over time. Furthermore, Study 2
explores the influence of three key forms of workplace resources (e.g.
organizational support, supervisory support, and specialized child welfare
training) that influence the relationship between burnout and job satisfaction.
Study 3: To empirically study the impact of job demands on burnout development
and its subsequent influence on psychological well-being over time. Additionally,
15
Study 3 explores the influence of two key forms of workplace resources important
to the work experiences of human service workers (e.g. organizational support,
supervisory support) on the relationship between burnout and psychological well-
being.
Dissertation Structure
This dissertation is presented in multi-manuscript form and consists of three
separate but related manuscripts. This first chapter briefly presents the purpose and
description of each of the three studies, and provides an overview of literature and
theories guiding the studies. Chapter II (Study 1) consists of a systematic review and
synthesis of studies that have examined the impact of job burnout (e.g. emotional
exhaustion, depersonalization, and personal accomplishment) on worker well-being in the
human service sector. Study 1 aims to synthesize the existing literature on burnout and
worker well-being to serve as a benchmark for the current state of knowledge, to help
guide future research in this field, and to help inform management practices designed to
prevent or alleviate burnout and promote the well-being of human service workers.
Chapter III (Study 2) presents findings from a longitudinal study on the influence of job
demands and resources on the development of job burnout, and the subsequent impact of
burnout on job satisfaction.
Study 2 aims to contribute to a deeper understanding of the relationship between
job burnout and affective well-being, specifically job satisfaction. Study 2 examines the
relationships between demands in the workplace as they contribute to job burnout while
taking into consideration how organizational support, supervisory support and having
16
specialized training for human service practice can serve as resources that moderate the
relationship between job burnout and job satisfaction. Chapter IV (Study 3) presents
findings from a longitudinal study of the influence of job demands and resources on the
development of job burnout, and the impact of burnout on the psychological well-being
of workers. Study 3 focuses on elucidating the relationship between job demands in the
workplace, job burnout, and the consequential influence of burnout on the psychological
well-being of human service workers. Furthermore, Study 3 explores the influence of
organizational support and supervisory support as potential resources in the workplace
that may moderate the relationships between job demands, burnout, and psychological
well-being. An integrated discussion of study findings, conclusions and implications for
social work practice and future research is presented in Chapter V.
Literature Review
Job burnout
The human service sector was the birthplace of job burnout research. The use of
the te rm “ burno ut” e mer g e d c oll oquiall y in t he 19 70s t o de sc ribe f e e li n g s of e mot ional
arousal and exhaustion due to work stress (Freudenberger, 1974; Maslach, & Scahufeli,
1993; Schaufeli, Leiter, & Maslach, 2008). In the initial stages of burnout research, it
became evident to practitioners and researchers in the human services sector that the
interpersonal nature of human service work was the core characteristic of the job and also
a source of emotional and interpersonal stressors related to the demands of providing care
(Maslach, Schaufeli, & Leiter, 2001). As interest in job burnout grew during the late 70s
and early 80s so did efforts to define and measure the phenomenon. During this time
17
period Christine Maslach and Susan Jackson developed the Maslach Burnout Inventory
(MBI; 1981), now, the most widely used measure of burnout. The measure consists of
three subscales assessing the three theorized dimensions of emotional exhaustion,
depersonalization, and reduced personal accomplishment (Schaufeli, Leiter, & Maslach,
2009).
Job burnout is theorized to be a response to chronic exposure to stressors at work
(Maslach & Jackson, 1981; Maslach, Schaufeli, & Leiter, 2001). The emotional
exhaustion dimension is considered to be the central dimension of burnout and refers to
feelings of being emotionally depleted. Cynicism, or depersonalization is the
interpersonal dimension of job burnout that develops as protection against feelings of
exhaustion. When the exhaustion becomes too overwhelming for the individual, he or she
detaches from the work and becomes cynical towards clients and co-workers. Lastly,
personal accomplishment or the self-perceived ability to successfully meet job
responsibilities is reduced when experiencing burnout.
Job Burnout and Worker Well-being
Literature on occupational well-being suggests that job burnout places worker
well-being at risk. Well-being in the workplace has increasingly gained attention as
researchers and practitioners have found evidence that work experiences can impact the
health and wellness of employees (Danna & Griffin, 1999; Sparks, Faragher, & Cooper,
2001). The workplace plays an integral role in the daily lives of workers and is a source
of psychosocial stimuli that affect workers through perception, affect, and work
experiences (Levi, 1994). Occupational well-being research is concerned with well-being
18
related to the work domain and is rooted in the broader literature on subjective well-being
-- a bro a d c onst ru c t t ha t i nc ludes a n indi vidual’ s p s y c holo g ic a l and ph y siol og ic a l
responses to and satisfaction with a multitude of domains such as work, family, finances,
and health (Diener, Suh, Lucas, & Smith, 1999).
Worker well-being is a multi-faceted construct and therefore its operational
definition varies widely across studies. Some of the commonly used global measures of
well-being include life satisfaction while domain specific measures include job
satisfaction, anxiety, depression, and psychosomatic symptomatology (e.g. headaches,
back aches, chest pains, sleeping problems; Danna & Griffin, 1999). The well-being
dimension under examination will differ among the three studies presented in this
dissertation. The studies reviewed in Study 1 examined the following three forms of well-
being: 1.) Affective/psychological well-being, 2.) Physical well-being, and 3.) Behavioral
well-being. Studies 2 and 3 focus on affective wellbeing (e.g. job satisfaction) and
psychological well-being (e.g. psychological well-being), respectively.
Job Burnout in the Human Service Sector
Though to the best of our knowledge no data exists on the prevalence rates of job
burnout in the human service sector, there is evidence that suggests that human service
workers may be at greater risk of stress and burnout. When compared to 26 other
occupations, social service work was among the six professions with the worse
experiences of physical health, psychological well-being, and job satisfaction in the
workplace (Johnson, Cooper, Cartwright, Donald, Taylor & Millet, 2005). Findings from
systematic reviews conducted on job burnout and well-being in human service workers
19
help shed some light on burnout among this worker population. In their review of social
worker stress and burnout, Lloyd, King, and Chenoweth (2002) found that the quantity
and quality of research on burnout in social work is weak. Though the authors identify a
lack of rigorous research on stress and burnout research in social work, the evidence that
does exist points to high levels of stress and burnout among social workers (Lloyd, King,
& Chenoweth, 2002). In a similar review of psychiatrists, Fothergill, Edwards, and
Burnard (2004) concluded based on the 65 international studies reviewed that
psychiatrists experience significant levels of stress. The experience of higher levels of
stress has also been found among mental health workers. In their review of mental health
workforce in the U.S. Paris and Hoge (2009) found that among mental health workers
there are high levels of burnout, particularly in the emotional exhaustion dimension of
burnout.
An evidentiary link has been made between burnout and its adverse impact on the
well-being of human service workers. In their longitudinal study on social workers, Kim,
Ji, and Kao (2011) found that those with greater levels of burnout at the inception of the
study subsequently reported greater physical health complaints (e.g. sleep disturbance,
he a da c he s, r e spira tor y a n d g a stroint e sti na l i nf e c ti ons) a y e a r la ter . J ohnson e t al.’ s (2005) study findings suggest that higher levels of burnout lead to sickness-related absence over
time. Job burnout has also been connected to reduced psychological and affective well-
being. In their study of home caregivers of patients with dementia, Takai et al. (2008)
found that greater levels of job burnout resulted in higher levels of depressive symptoms
and reduced levels of quality of life. In their study of Spanish social workers,
20
Hombrados-Mendieta and Cosno-Rivas (2011) found a negative impact of burnout on job
satisfaction and life satisfaction. Similarly, in their study of social workers, Pasupuleti,
Allen, Lambert, & Cluse-Tolar, (2009) found that stress in the workplace resulted in
reduced levels of life satisfaction.
Theory Driven Model of Burnout Development: Job Burnout and Job Demands-
Resources (JD-R) model
This dissertation uses the Job Demands-Resources (JD-R) model as a guiding
framework to explain the development of job burnout in studies 2 and 3. As previously
mentioned, job burnout is theorized to be a response to chronic exposure on the job
stressors. The response to chronic stressors is postulated to lead to burnout (e.g.
emotional exhaustion, depersonalization, and reduced personal accomplishment), which
subsequently impairs personal and social functioning and results in a decline in the
physical and psychological health of the worker (Maslach, 1998). The JD-R model has
been used to explain the interrelationships between demands and resources and their
impact on burnout development. The JD-R model is parsimonious, flexible, and has
received empirical support for its robustness (Bakker & Demerouti, 2007;
Demerouti, Bakker, Nachreiner, & Schaufeli, 2001; Llorens, Bakker, Schaufeli,
Salanova, 2006; Schaufeli, Bakker, & Van Rhenen, 2009).
The JD-R model proposes that all working conditions can be categorized as a
demand or resource irrespective of the occupational field. Job demands include any of the
physical, social, or psychological requirements of the job that call for sustained mental or
physical effort. Resources include the physical, social or psychological aspects of the job
21
that meet one of the following criteria: a) serve a functional role in meeting work goals,
b) reduce the physiological and/or psychological costs of demands, and/or c) promote
personal growth and development (Demerouti, Bakker, Nachreiner, & Schaufeli,
2001). Resources may be drawn from various sources including the overall organization
(e.g. pay, job security), interpersonal relationships (e.g. supervisory and peer social
support), organization of the work (e.g. clarity of work roles, decision making authority),
or at the task level (e.g. task significance; Bakker & Demerouti, 2007).
The JD-R model assumes a dynamic set of interrelationships between demands
and resources and their subsequent impact on both positive (e.g. employee engagement)
and negative (e.g. job burnout) indicators of employee well-being (Bakker et al., 2007).
Person-environment fit theory has been used to help explain the process by which a lack
of equilibrium between work demands and abilities can lead to experiences of stress in
the workplace (French & Caplan, 1972; Caplan, 19 87). A lac k of fit be twe e n a pe rson ’s
abilities and the demands he or she faces as part of work responsibilities can lead to
stress. The mechanisms by which resources influence the development of burnout can be
explained using conservation of resources theory (COR; Wright & Hobfoll, 2004). COR
purports that an inherent motivation exists within individuals to obtain and retain valued
resources (Hobfoll & Freedy, 1993). According to the postulates of COR, if an individual
cannot obtain resources, faces a threat of losing resources or loses the resources that he or
she values, it subsequently leads to feelings of psychological stress (Hobfoll et al., 1993).
Methods
A brief description of the purpose and methods of each of the three studies is
22
described below.
Study One
Study 1 systematically reviews and synthesizes the human service literature on
the effects of job burnout on the affective/psychological, physiological, and behavioral
well-being of human service workers (see Figure 1). The systematic review is driven by
the following research question: What is the impact of the three dimensions of job
burnout (e.g. emotional exhaustion, depersonalization, and personal accomplishment) on
the affective/psychological, physical, and behavioral well-being of human service
workers? Articles for inclusion in the study were identified by using a number of
electronic databases and search engines focused on social work and social sciences (e.g.
Social Work Abstracts, Psych Info, JSTOR, ProQuest, Google Scholar). Furthermore, a
combination of search terms was utilized to search for articles to be included in the study
(See Table 1). Studies meeting the following criteria were included in the systematic
review: 1.) The study examined one or more dimensions of Maslach and coll e a g u e s’
conceptualization of job burnout (e.g. emotional exhaustion, depersonalization, personal
accomplishment) as an independent variable related to a form of employee well-being as
an outcome; 2.) The study was published between the years 1970 and 2013, 3.) The study
focuses on a human service employee population, 4.) The study is quantitative or
qualitative primary research article, 5.) The study has been published in a peer-reviewed
journal, and 6.) The study was published in either English or Spanish.
23
Study Two
Study 2 employs a three-wave longitudinal panel design spanning a twelve-month
timeframe to examine the impact of burnout on job satisfaction. The study aims to test the
interrelationships between job demands and resources, job burnout and their subsequent
impact on job satisfaction over time (See Figure 2).
Study 2 tests the following hypotheses:
Hypothesis 1): Job demands (e.g. role conflict, role ambiguity, and
work-family conflict) at wave 1 are positively and significantly related to
emotional exhaustion and depersonalization at wave 2.
Hypothesis 2.): The relationships between job demands at wave 1, burnout at
wave 2 (e.g. emotional exhaustion and depersonalization), and job satisfaction at
wave 3 will be moderated by job resources (e.g. supervisory and organizational
support, specialized child welfare training).
Hypothesis 3.): Emotional exhaustion is significantly and positively associated
with depersonalization.
Hypothesis 4a.): Emotional exhaustion at wave 2 is negatively and significantly
related to job satisfaction at wave 3. Hypothesis 4b.) Depersonalization at wave 2
is negatively and significantly related to job satisfaction at wave 3.
Study Three
Study 3 employs a three-wave longitudinal panel design spanning a twelve-month time
frame to examine the impact of burnout on psychological well-being. The study aims to
24
test the interrelationships between job demands and resources, job burnout and their
subsequent impact on psychological well-being over time (See Figure 3).
Study 3 tests the following hypotheses:
Hypothesis 1a.): Job demands (e.g. role conflict, role ambiguity, and
work-family conflict) at wave 1 are positively and significantly related to
emotional exhaustion and depersonalization at wave 2.
Hypothesis 2a.): The relationships between job demands at wave 1, burnout at
wave 2 (e.g. emotional exhaustion and depersonalization), and psychological
well-being at wave 3 will be moderated by job resources (e.g. supervisory and
organizational support, specialized child welfare training).
Hypothesis 3.): Emotional exhaustion is significantly and positively associated
with depersonalization.
Hypothesis 4a.): Emotional exhaustion at wave 2 is negatively and significantly
related to psychological well-being at wave 3. Hypothesis 4b.) Depersonalization
at wave 2 is negatively and significantly related to psychological well-being at
wave 3.
25
Figure 1
Conceptual Model: The Impact of Job Burnout Dimensions on Worker Well-being
WELL-BEING
Emotional
exhaustion
Personal
accomplishment
Depersonalization
Affective/Psychological
•
Job
sat isfacti on
•
H ap p in ess
•
Well -being
•
M en ta l
h ea lth
•
C oncen trati on
Physical
•
S lee p
d ist ur b an ce
•
Gene r al
hea lth
•
Neck
an d
b ack
p ai n
•
C or onar y
p r oblems
Behavioral
•
S mo k in g
•
Phy sical
a ctivity
•
Dr in k in g
JOB BURNOUT
26
Table 1
Study 1 Systematic Review Search Terms
Job Burnout Related Search
Terms
Employee Well-being
Related Search Terms
Employee Population
Related Search Terms
Job burnout
Emotional exhaustion
Depersonalization
Personal accomplishment
Psychological/Affective/
Cognitive
Job satisfaction
Life satisfaction
Happiness
Well-being
Mental health (e.g.
depression, anxiety)
Concentration
Physiological
Sleep disturbance
Health
Behavioral
Alcohol/drug use
Cigarette smoking
Violence
Child welfare
Social work
Counseling
Mental health
Psychology
Therapy
Nursing
Caregiving
27
Figure 2
Conceptual Framework of Job Demands and Resources, Job Burnout and Job
Satisfaction
Note. Wave 1 variables = job demands and job resources, wave 2 variables = job burnout,
wave 3 variables = job satisfaction.
JOB DEMANDS
JOB BURNOUT
JOB RESOURCES
Role Conflict
Depersonalization
Role Ambiguity
Work-family
Conflict
Supervisory Support
Organizational Support
Emotional
Exhaustion
Job Satisfaction
Specialized Training
28
Figure 3
Conceptual Framework of Job Demands and Resources, Job Burnout and Psychological
Well-being
Note. Wave 1 variables = job demands and job resources, wave 2 variables = job burnout,
wave 3 variables = job satisfaction.
JOB DEMANDS JOB BURNOUT
JOB RESOURCES
Role Conflict
Depersonalization
Role Ambiguity
Work-family
Conflict
Organizational Support
Supervisory Support
Emotional
Exhaustion
Psychological
Well-being
29
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34
CHAPTER TWO (STUDY 1):
EXAMINING THE IMPACT OF JOB BURNOUT ON WORKER HEALTH AND
WELL-BEING: A SYSTEMATIC REVIEW AND SYNTHESIS
Introduction
The purpose of this systematic review is to synthesize findings from empirical
studies examining the impact of job burnout on worker well-being. Job burnout,
described as a response to chronic exposure to workplace strains is marked by feelings of
being emotionally depleted, cynical, and feelings that no matter how much effort you put
into your work there is no progress (Maslach & Jackson, 1981). Though the job burnout
research literature in the human service sector abounds (Boyas & Wind, 2010; Campbell,
Perry, Maertz, Allen, & Griffeth, 2013; Lim, Kim, Kim, Yang, & Lee, 2010; Lloyd,
King, Chenoweth, 2002; Smith, & Clark, 2011; Sprang, Craig, & Clark, 2011) as do
studies that examine its antecedents (Acker, & Lawrence, 2009; Ben-Zur & Michael,
2007; Font, 2012; Hamama, 2012; Kim, 2011; Jourdain & Chênevert, 2010; Lizano &
Mor Barak, 2012), fewer studies have focused on the impact of burnout on worker well-
being. We know from empirical research findings that workers experiencing burnout are
at greater risk of underperforming (Taris, 2006) and of leaving the job (Mor Barak,
Nissly, & Levin, 2001). What can be surmised from job burnout literature is that the
“ burne d- out ” worker is chronically exhausted, disengaged, underperforming (Maslach &
Leiter, 1999) and poses a managerial challenge to administrators.
What has been given less attention in human services research is how this
experience of being burned out impacts the worker in an affective/psychological,
35
physical, and/or behavioral manner. Health and well-being in the workplace encompasses
a broad domain making it a concept that varies widely in definition (Danna & Griffin,
1999). For the purposes of clarity, the conceptual definition of well-being used to guide
thi s s y st e matic r e vi e w is e mbedde d in t he W orld H e a lt h Or g a niz a ti on’s de finiti on of he a lt h a s be in g “ [ a ] state of c ompl e te ph y sica l, m e ntal a nd soc ial we ll -being and not
mer e l y the a bs e nc e o f dise a se ” (W orld H e a lt h Or ga niz a ti on, 1 948). The studies reviewed
here are further distinguished into three broad well-being categories including: 1.)
affective/psychological well-being, 2.) physical well-being, and 3.) behavioral well-
being.
A synthesis of the literature on the relationship between job burnout and worker
well-being can help shed light on some key workforce well-being questions that remain.
A synthesis of findings can provide a greater understanding of the impact of the three
dimensions of job burnout on the affective/psychological, physical, and/or behavioral
aspects of worker well-being. This will further help explain the differential impact that
the burnout dimensions (e.g. emotional exhaustion, depersonalization, and reduced
personal accomplishment) have on the different forms of well-being. This review aims to
aid in expanding our understanding of where the knowledge base currently is regarding
burnout and its effects on worker well-being. A synthesis of the knowledge base will
serve as a tool to guide workforce management efforts made to improve the quality of
work life for human service workers.
36
Literature Review
Job burnout and well-being in the workplace has attracted the attention of
organizational researchers and administrators for two central reasons. The first is the
moral responsibility of organizational leaders to protect the well-being of employees in
the workplace (Burton, 2010). Work is ever present in the lives of most adults. Work is
not merely a source of livelihood but for most workers it is also a source of fulfillment of
intrinsic needs like motivation, belonging, and accomplishment (Warr & Wall, 1975).
The second is the impact of worker well-being on his or her performance which can
subsequently shape service provision and client outcomes (Burton, 2010; Danna &
Griffin, 1999; Ford, Cerasoli, Higgins, & Decesare, 2011; Sparks, Faragher, & Cooper,
2001).
Workplace stress is experienced by many workers, with approximately one-third
(36%) of American workers reporting that they typically feel tense or stressed-out at
work (American Psychological Association, 2011). The prevalence of job stress
underscores the importance of understanding the impact of work strains on workers and
organizations. It is estimated that 43% of adults in the U.S. suffer from adverse health or
psychological symptoms due to experiences of stress (American Psychological
Association, 2007). Though no statistics on the rates of stress and burnout among human
service workers exist, there is evidence to suggest that human service sector workers are
at greater risk of stress and burnout due to the emotive nature of human service work
(Guy, Newman, Mastracci, & Maynard-Moody, 2010; Lloyd, King, Chenoweth, 2002).
When compared to 26 other occupations, social service work was one among the six
37
professions with the worst experiences of physical health, psychological well-being, and
job satisfaction in the workplace (Johnson, Cooper, Cartwright, Donald, Taylor & Millet,
2005).
The impact of burnout on the well-being of workers is a concern for
organizational administrators because its impact goes beyond the individual worker. In
the United States depression is considered to be one of the greatest threats to worker
well-being (Adler et al., 2006). Depression for example, is considered the single most
expensive condition to American employers at an estimated cost of $44 billion dollars a
year in lost productivity (Kessler et al., 2003). In an international study of almost forty
thousand employees, Allen and colleagues found that 16% of study participants
demonstrated signs of mild depression and 7% moderate-to-severe depression suggesting
that almost one-fifth of the sample was afflicted with a mental health issue. The World
Health Organization estimates that 8% of the occurrences of depression can be attributed
to workplace experiences (Burton, 2010). The effects of burnout on the physical health of
workers often times results in worker absence. The cost of an ill employee is exponential
and exceeds the pay for the day(s) missed (Gotzel et al., 2004). Filling time sensitive
positions befittingly elicits great urgency among administrators and managers to fill the
position and responsibilities of a sick worker. This is particularly true for positions that
require timely and speedy responses like those held by child protection workers and
emergency room nurses.
38
Job Burnout Theory and Worker Well-being
The human service sector was the birthplace of job burnout research that emerged
out of an effort to define the syndrome that was afflicting the overworked, exhausted and
distant worker who was once motivated and engaged. Though some heterogeneity in the
de finiti on of burn out ex is ts, M a slac h a nd J a c kson’ s (1981) c onc e ptual a nd ope ra ti ona l
definition of burnout is the most widely used and accepted definition. This systematic
re view is driven b y the th e ore ti c a l post ulate s put f orw a rd b y M a slac h a nd J a c kson’s
(1981) definition of job burnout, which proposes a three-dimension construct comprised
of emotional exhaustion, depersonalization and personal accomplishment. Emotional
exhaustion is the central dimension of burnout; marked by feelings of being depleted
because of chronic exposure to job stress. Feelings of emotional exhaustion then lead to
the worker distancing him or herself from clients becoming cynical and detached. The
third dimension, personal accomplishment, refers to feelings of ineffectiveness in the
workplace regardless of the effort exerted.
Job burnout is a social phenomenon influenced by interpersonal relationships in
the work environment (Maslach, Schaufeli, & Leiter, 2001). Human service employees
serve clients who are in a state of vulnerability or crisis and often times make the
interpersonal exchange an emotionally charged one for the worker (Hasenfeld, 2010).
Establishing an empathic connection between worker and client is a keystone of human
service work. Empathy in this line of work is not merely an implicit expectation. Most
professional human service associations are guided by codes of ethics that explicitly
charge these groups (e.g. social work, marriage and family therapy, addiction counseling)
39
with the responsibility to enter into worker-client exchanges with empathic
understanding, in an effort to try to understand and share the feelings of others. As
vehicles of change, human service workers make great emotional investments when
working with clients/consumers (Guy et al., 2010; Hasenfeld, 2010), a process that can
lead to feelings of emotional exhaustion and depersonalization (Maslach, 2003).
Job burnout poses a risk to the affective/psychological, physical, and behavioral
well-being of workers. The mechanisms by which burnout is theorized to impact worker
well-being are generally described as resulting from a depletion of the burned out
indi vidual’ s pe rsona l re s ourc e s that l e a d to a de c li ne in one’ s a f fe c ti ve , ps y c holog ic a l,
physical, or behavioral state. An expenditure of energetic resources occurs as workers
cope with chronic stress and feelings of exhaustion which then lead to feelings of fatigue
and psychological erosion (Shirom, 1989; Leiter & Maslach, 2001). The depletion of
personal resources felt b y a “ burne d o ut” w ork e r c a n a lso l e a d to physical ailments by
compromising the immune system (Leiter & Maslach, 2001). Additionally, worker
reactions to job burnout can be manifested behaviorally and can include such things as
increased smoking or drinking as coping mechanisms (Maslach, 1978).
This systematic review focuses on empirical studies examining the relationship
between job burnout and multiple domains of well-being and is guided by the following
research question: How do emotional exhaustion, depersonalization, and reduced
personal accomplishment impact worker psychological/affective, physiological, and
behavioral well-being of human service workers (See Figure 1)? This multiple domain
approach to this systematic review is guided by the multi-faceted definition of health and
40
well-being put forward by the World Health Organization that defines health as being a
condition beyond a lack of infirmity but of complete mental, physical and social well-
being (World Health Organization, 1948). The three well-being domains that were
reviewed include: 1.) Affective/psychological well-being, 2.) Physical well-being, and 3.)
Behavioral well-being. Studies exploring affect or feelings, mental health status or mental
illness were categorized under the psychological/affective mental health domain.
The conceptual definition used to designate a study as an affective/psychological
well-being study d ra ws o n P e ter W a rr ’s definition of psychological/affective wellbeing in
the workplace which defines affective well-being as pe ople’ s f e e li n g s a bou t t he ir e ve r y day experiences that can range from negative mental health statuses such as
dissatisfaction, unhappiness, and anxiety to satisfaction and happiness. Studies including
any well-being outcomes operationally defined as a mental health condition, whether or
not it included a formal clinical diagnosis, were included in the affective/psychological
well-being domain. Studies examining job burnout and physical symptoms or health
status measures such as headaches, sleeping patterns, and digestive problems were
categorized within the physical well-being domain. Studies pertaining to behaviors
affecting well-being like smoking, drinking, and exercise were classified as behavioral
well-being studies.
Method
Search Strategy and Selection of Studies
A comprehensive search of peer-reviewed literature was conducted using a variation of
key search terms that allowed for the specification of a job burnout term coupled with an
41
employee well-being and human service worker population term (See Table 1 for the list
of search terms used). First, a comprehensive search of peer-reviewed article abstracts
was conducted. A computerized search of the aforementioned key terms yielded a total of
43 abstracts. Four databases ProQuest, Social Work Abstracts, PsycInfo, and JSTOR and
one search engine, Google scholar were used to carry out the search. Following the
selection of 43 studies based on their abstract, each study article was reviewed in its
entirety to determine if the study met inclusion criteria. The final count of studies after
the review was 17. A summary of the author(s), sample, study design, operationalization
of job burnout, well-being outcome and key findings are summarized and presented in
Table 2.
The study focused on the following inclusion criteria: 1.) The study examined at
least one or all dimensions of job burnout (e.g. emotional exhaustion, depersonalization,
personal accomplishment) as an independent variable related to a form of employee well-
being as an outcome; 2.) The study was published between the years 1970 and 2013, 3.)
The study focused on a human service employee population, 4.) The study was a
quantitative or qualitative primary research article, 5.) The study was published in a peer-
reviewed journal, and 6.) The study was published in English. Two of the studies yielded
by the systematic search had English abstracts and search keywords but were otherwise
written in Spanish. Both of the studies met study inclusion criteria and are included in
this review (Grau, Gil, García, Figueiredo, 2009; Ríos Rísquez, Fernández, & Sánchez
Meca, 2011).
42
Description of Studies
Studies were reviewed and classified based on their research design, dependent
and independent variables, sample type and size, operational definition of burnout and
worker-wellbeing, and statistical analysis approach. The seventeen studies ranged in
publication year from 1988 to 2012. Study sample size ranged from 29 to 406. Of the
studies presented in this review, 41.18% (N=7) of the studies were comprised of a sample
of nurses, four used a social worker sample (23.5%), two a child welfare worker sample
(11.7%), and one study was conducted using each of the following samples: a mix of
health professionals (nurses, doctors, and social workers, 5.88%), rehabilitation
counselors (5.88%), student support service workers (5.88%), and mental health
professionals (5.88%).
Sampling strategies: Study settings represented a range of regions including
Australia, Canada, Spain, South Africa and the United States. The majority of the studies
(N=14) used a cross-sectional research design with only three studies using a longitudinal
approach (Demerouti, et al., 2000; Grau et al., 2009; Kim et al., 2011). All studies
employed quantitative research methods and ranged in statistical analysis from
correlation (Bakir, Ozer, Cetin, & Fedai, 2010; Bhana, 1996; Brewer & Clippard, 2002;
Maslach & Florian, 1988) and t-tests for difference between groups (Jayaratne, Chess, &
Kunkel, 1986) to discriminant analysis (Bennet, 1993), multiple regression (Grau, Gil,
García, & Figueiredo, 2009; Burke, Koyunco, & Fiksenbaum, 2010; Koeske, & Kelly,
1995; Puig et al., 2012; Ríos Rísquez, Godoy Fernández, & Sánchez Meca, 2011) and
structural equation modeling (Demerouti, Bakker, Nachreiner, & Schaufeli, 2000; Glass,
43
McKnight, & Valdimarsdottir, 1993; Hombrados-Mendieta, & Cosano-Rivas, 2011; Kim,
2011; Laschinger, & Grau, 2012; Um, & Harrison, 1998).
Studies varied in their operational definition of burnout. Most studies used one,
two or all three dimensions of the MBI to operationally define burnout. Studies using
only one dimension of the MBI used only emotional exhaustion. Studies using two
dimensions of the MBI used emotional exhaustion and depersonalization. It should be
noted that an alternate burnout measure was used in two studies. The Oldenburg Burnout
Inventory (OLBI) used by Demerouti, Bakker, Nachreiner, & Scaufeli (2000) in their
study of nurses measured two constructs, emotional exhaustion and depersonalization.
The Counselor Burnout Inventory (CBI) used by Puig et al. (2012) included multiple
dimensions of burnout, three of which exhaustion, devaluing client, and incompetence
align with the emotional exhaustion, depersonalization, and personal accomplishment
scales of the MBI. For the purposes of facilitating synthesis only the dimensions that
a li g n with t he M B I ’s e m oti ona l ex ha usti on, de pe rsona li z a ti on a nd pe rsona l
accomplishment scales in the Puig et al. (2012) study were included in this synthesis. The
studies reviewed are abstracted in Table 2.
Synthesis of Studies
Psychological/Affective Well-being
The influence of burnout on the psychological/affective well-being dimension
was the most widely studied among the articles included in this review. Fifteen of the
seventeen studies included a form of psychological or affective well-being measure
ranging from job satisfaction and life satisfaction, to depression and anxiety. Job
44
satisfaction was the most studied affective well-being outcome with a total of eight
articles including it as an dependent variable (Bhana et al., 1996, Brewer, et al., 2002;
Burke et al., 2010; Hombrados-Mendieta et al. , 2011; Jayarante et al., 1996; Koeske,
1995; Maslach et al., 1988; Um et al., 1988). All studies examining job satisfaction as a
well-being outcome used a cross-sectional design. Two studies tested the relationship
between burnout and job satisfaction by using a composite of the MBI and found a
significant negative relationship between them. Among the six studies that separately
tested the various dimensions of burnout, emotional exhaustion was found to have a
significant negative relationship with job satisfaction. The findings are however
inconsistent when the dimensions of cynicism and personal accomplishment were
assessed. The direction of the relationship between cynicism and job satisfaction was
consistently negative in all studies, but statistical significance of the relationship was
inconsistent across studies. Similarly, higher levels of personal accomplishment
consistently had a positive relationship with job satisfaction but the significance of this
relationship varied among studies.
Six studies examined mental health among human service workers (Baker et al.,
2010; Bennet et al., 1994; Glass et al., 1993; Jayaratne, et al., 1996; Lasching-er et al.,
2012; Risquez, et al., 2011). Of the six studies, five used a sample that was either
completely or partially comprised of nurses. Mental health was operationalized in a
number of ways including current mental health status as well as depression and anxiety
symptoms. The two studies that used a composite of burnout found a positive and
significant relationship between burnout, depression (Glass et al., 1993) and anxiety
45
(Bennet et al., 1994). Those that examined the separate dimensions of burnout found a
consistent and significant positive relationship between emotional exhaustion, depression
and anxiety. Depersonalization and personal accomplishment had a positive relationship
with mental health outcomes across studies but the level of significance for the
relationships varied by study.
Five studies investigated other forms of affective well-being that were more
disparate in nature including positive and negative affect, life satisfaction, marital
satisfaction and personal well-ness. Findings from the five studies are described as
follows: Burke et al. (2010) found that all dimensions of burnout significantly predicted
affect with greater levels of emotional exhaustion and cynicism relating to increased
negative affect (e.g. irritability, distress, and nervousness) while greater level of personal
accomplishment related to greater positive affect (e.g. excitement, pride). Demerouti,
Bakker, Nachreiner , a nd S c ha ufe li ’s ( 2000 ) long it udinal st ud y on bur nout a nd li fe satisfaction used the OLBI to operationalize burnout and found a significant and negative
relationship between emotional exhaustion and depersonalization and life satisfaction.
Jayaratne, Ches s a nd Ku nke l’s (1 986) stud y of c h il d we lfa re wor ke rs w a s t he onl y stud y that investigated the impact of burnout on marital satisfaction. Jayaratne et al. (1986)
found that higher levels of emotional exhaustion and depersonalization led to
significantly lower levels of marital satisfaction and higher levels of personal
accomplishment were significantly related to higher levels of marital satisfaction.
Puig et al. (2012) examined the relationship between the CBI and personal well-
ness among mental health professionals. The CBI is comprised of five subscales (e.g.
46
exhaustion, incompetence, negative work, devaluing client, deterioration) with
exhaustion, devaluing client, and incompetence being analogous to the emotional
exhaustion, depersonalization and personal accomplishment dimensions of the MBI. The
investigators in the study conceptually defined well-ness as the integration of mind, body
and spirit and operationalized it into five subscales including the creative self, coping
self, essential self, and physical self. The subscales were comprised of a number of items
with all subscales pertaining to affect with the exception of the physical self (e.g.
Creative Self: Thinking, Emotions, Control, Work, and Positive Humor; Coping Self:
Leisure, Stress Management, Self-Worth, and Realistic Beliefs; Social Self: Friendship
and Love; Essential Self: Spirituality, Gender Identity, Cultural Identity, and Self-Care;
and Physical Self: Nutrition and Exercise). Exhaustion had no significant relationship
with any of the well-ness subscales pertaining to affect, conversely, devaluing of clients
was negatively and significantly related to the creative self. Incompetence was found to
significantly and negatively impact all dimensions of wellness with the exception of the
physical self.
Physical Well-being
Six of the studies included in this review examined the impact of burnout on
physical or somatic symptoms (Burke, et al., 2010; Laschinger et al.; 2012; Grau et al.,
2009; Jayaratne et al.,1996; Kim et al., 2011; Risquez et al., 2011). Studies examining
the impact on physical well-being were largely carried out on nursing samples with only
two studie s usi ng other w orkf orc e sa mpl e s. Kim, J i, and K a o’s ( 2011 ) long i tudi na l st ud y of social workers used a composite measure of burnout (MBI) and found a significant
47
positive relationship between burnout and physical complaints. The rest of the studies did
not use a composite burnout scale. Findings from the remaining five studies consistently
found a significant positive relationship between emotional exhaustion and physical or
somatic problems. Only three of the five studies examined the impact of
depersonalization on physical health and consistently found a significant negative
relationship between burnout and physical health. The relationship between personal
accomplishment and health was investigated in three studies and the relationship was not
found to be significant in either study.
Behavioral Well-being
Two cross-sectional studies included measures of behavioral health as outcomes.
B urke , Ko y unc u, a nd F ik se nba um’s ( 2010) stud y of nu rse s m easured medication use as a
be ha viora l out c ome. M e dica ti on use wa s ope ra ti o na ll y de fine d a s r e sponde nt’s se lf -
reported use of medication such as pain medication and sleeping pills. Burke et a l.’s
(2010) study found a significant and positive relationship between depersonalization and
medic a ti on use . P uig e t a l.’s (2 012) stud y o f me nt a l hea lt h pro f e ssi ona ls m e a sure d
physical wellness, which included nutrition and exercise regimens. The Puig et al. (2012)
study found a significant negative relationship between emotional exhaustion and
nutrition and exercise practices.
Discussion and Implications
This systematic review found 17 studies that investigated the relationship between
job burnout and at least one form of psychological, affective, physiological, or behavioral
well-being as an outcome among human service workers. Study findings all point to the
48
detrimental impact of job burnout on the well-being of workers. More importantly, the
findings from these studies give insight into the differential impact of the job burnout
dimensions on worker well-being. Emotional exhaustion was examined in every study
reviewed and consistently was found to have a negative and significant impact on all the
forms of well-being that were examined. This finding is congruent with job burnout
theory which proposes that emotional exhaustion is the central dimension of burnout
(Maslach et al., 1981). The relationship between depersonalization, personal
accomplishment and well-being were in the anticipated direction but were inconsistently
found to be significant across studies. The lack of consistency in study findings points to
a need to further investigate the dimensions of depersonalization and personal
accomplishment as they relate to worker well-being. Furthermore, it brings attention to
the importance of evaluating the distinct dimensions of burnout separately given their
differential relationships with well-being outcomes. The use of composite burnout scales
may mask nuanced interrelationships between the different burnout dimensions and well-
being.
Studies in this review were overwhelmingly focused on affective psychological
well-being outcomes. Of the 17 studies reviewed, 16 measured at least one form of
affective well-being as an outcome. A dearth of research studies examining the affect of
job burnout on psychological/mental health, cognitive, physical, or behavioral well-being
of human service workers was found. The nursing sector is taking the lead on well-being
and burnout research in the human service sector. The few studies found on
psychological/mental health and physical well-being were conducted using nursing
49
samples. Future studies should seek to examine these well-being outcomes among human
service worker samples in different sectors (e.g. child welfare, substance abuse
counseling, psychiatry) to help shed light on any heterogeneity in burnout levels and
well-being that may exist between human service worker groups. Furthermore, future
studies should investigate the relationship between job burnout and behavioral well-being
giving the limited number of studies (N=2) that included it as an outcome in this review.
This review provides valuable insight into the methodological approaches
pertaining to design, sampling, and measurement being used by researchers investigating
burnout and worker well-being in the human services sectors. Studies in this area of
research are largely cross-sectional in nature and only three studies within this review
employed a longitudinal design. The use of cross-sectional studies in job burnout
research has long been advised against because burnout is theorized to be developmental
in nature (Maslach, et al., 1981). Additionally, cross-sectional studies critically limit any
causal inference that can be made about the relationship between job burnout and its
impact on well-being. Findings from this review point to a gap in longitudinal research
on job burnout and worker well-being. Though there is greater feasibility in carrying out
cross-sectional research due to practical reasons like time and cost limitations,
longitudinal studies are a worthwhile endeavor if we are to gain a better understanding of
the long-term impact of job burnout on worker well-being. The MBI continues to be the
most commonly used scale to measure job burnout and only two of the studies reviewed
used alternate forms of burnout measures.
50
This review provides evidence that job burnout poses a risk to the well-being of
human service workers. More specifically, the evidence points to the dangers of
emotional exhaustion. Any efforts made in workforce management strategies that are
attempting to protect the well-being of human service workers should seek to protect
workers against emotional exhaustion. Emotional exhaustion results from a depletion of
personal resources in workers resulting from continuous exposure to workplace stressors.
Managers and administrators can implement workplace practices that reduce stressors
specific to the work context. Furthermore, managers can focus on providing resources in
the workplace which will aide in mitigating the depletion of personal resources of
workers. Resources can include both emotional resources in the form of social support
and instrumental resources that facilitate meeting work related responsibilities.
Study Limitations
Although this review makes a unique contribution to the knowledgebase by
proving a comprehensive review of the current literature on job burnout and well-being
research in the human service se c tor, th e stud y ’s li mi tations must be noted. This s tud y synthesizes findings on burnout and well-being but does not provide any quantitative
conclusions on the relationships between burnout and well-being. Because this systematic
review does not employ any meta-analytic strategies, it cannot provide inference on the
strength of the relationships found between burnout and worker well-being. This study
draws on published peer-reviewed articles in English and Spanish only limiting the
sample of studies that were included. Using only published studies may introduce bias
given that studies with null findings are less likely to be published.
51
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57
Table 2
Study 1 Summary of Studies Examining the Relationship between Job Burnout and Worker Well-being
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Bakir et
al. (2010)
To investigate the
association between
burnout syndrome and
depressive symptoms
among Turkish
military nurses
Nurses
N= 377
Becks
Depression
Inventory
(BDI)
MBI
(Dimensions
examined
separately)
EE
DP
PA
EE, DP, and the
reverse coded PA are
positively and
significantly
correlated to
depression
Bennet et
al. (1994)
To examine burnout
and its impact on
anxiety, stress and
stigma among
healthcare workers
providing care to
clients with
HIV/AIDS
Health
professionals
(54 nurses,
16 doctors,
14 social
workers)
N= 84
General
Health
Questionnaire
(GHQ-28;
Current mental
health status)
MBI
(Composite)
Higher levels of
burnout are positively
related to anxiety
levels
Bhana et
al. (1996)
To examine the
relationships between
burnout, role dynamics
(role conflict and role
ambiguity), and job
satisfaction among
child-care social
Child
welfare
social
workers
N=29
Job
satisfaction
MBI
(Dimensions
examined
separately)
EE
DP
PA
A significant and
negative correlation
between EE, PA and
job satisfaction
58
Table 2 (Continued)
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Bhana et
al. (1996)
continued
workers
Brewer et
al. (2002)
To measure burnout
and job satisfaction
among a national
sample of Student
Support Services
personnel
Student
support
services
personnel
N= 166
Job
satisfaction
MBI
(Dimensions
examined
separately)
EE
DP
PA
A significant and
negative correlation
between EE, PA and
job satisfaction
Burke et
al. (2010)
To explore the
relationship between
burnout, work
satisfaction and
psychological well-
being
Nurses
N=217
Job
Satisfaction
Positive affect
Negative
affect
Psycho-
somatic
symptoms
Medication
use
Life
satisfaction
MBI
(Dimensions
examined
separately)
EE
DP
PA
A significant and
negative relationship
between EE and job
satisfaction, positive
affect, life satisfaction
A significant and
negative relationship
between EE and
psychosomatic
symptoms
A significant and
negative relationship
between DP and job
satisfaction and life
satisfaction
59
Table 2 (Continued)
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Burke et
al. (2010)
Continued
A significant and
positive relationship
between DP and
psychosomatic symptoms
and medication use
A significant and
positive relationship
between PA and positive
affect
A significant and
negative relationship
between PA and negative
affect
Demerou
-ti et al.
(2000)
To test a theoretically
derived model of
burnout and overall
life satisfaction
Nurses
N=105
Life
satisfaction
Oldenburg
Burnout
Inventory
(OLBI)
EE
DP
A significant and
negative relationship
between EE and life
satisfaction
A significant and
negative relationship
between DP and life
satisfaction
Glass et
al. (1993)
To examine the
relationships between
depression, job
Nurses
N=162
Depression MBI
(Composite)
Burnout mediates the
relationship between a
perceived lack of control
60
Table 2 (Continued)
Citation
Purpose Sample type and
size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Glass et
al. (1993)
continued
burnout and
perceptions of control
and depression
Grau et
al. (2009)
To examine the effects
of burnout on the
health of hospital
workers
Nurses
N=319
Self-reported
health
problems
MBI
(Dimensions
examined
separately)
EE
DP
PA
A significant and
positive relationship
between EE and self-
reported health
problems
A significant and
positive relationship
between DP and self-
reported health
problems
Hombra-
dos
Mendieta
et al.
(2011)
To analyze the effect
of burnout on job and
life satisfaction
Social
Workers
N=107
Life
satisfaction
Job
satisfaction
MBI
(Composite)
A significant and
negative relationship
between burnout and
the outcome variables
of job satisfaction and
life satisfaction
Jayaratne
et al.
(1996)
To examine the impact
of burnout on child
welfare workers and
their
Child
welfare
workers
N=75
Anxiety,
Depression
Somatic
complaints
MBI
(Dimensions
examine d
separately)
A significant and
positive relationship
between EE and
anxiety, depression,
61
Table 2 (Continued)
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Jayaratne
et al.
(1996)
spouses. Job
satisfaction
Marital
satisfaction
1 EE item
DP
PA scales
and somatic
complaints
A significant and
negative relationship
between EE and job
and marital
satisfaction
A negative and
significant relationship
between PA and
anxiety, somatic
complaints
A positive and
significant relationship
between PA and job
and marital
satisfaction
Kim et al.
(2011)
To examine the
relationship between
burnout and physical
health
Social
workers
Time 1
N= 406
Time 2
N=285
Physical
health
complaints
MBI
(Composite)
A positive and
significant relationship
between burnout and
physical health
complaints
Koeske
(1995)
To test a process
model proposing that
overinvolvement
Social
Workers
N=107
Job
satisfaction
MBI
EE
EE completely
mediated the
relationship between
62
Table 2 (Continued)
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Koeske
(1995)
continued
affects job satisfaction
exclusively through its
impact on worker
burnout
overinvolvement on
job satisfaction
Lasching-
er et al.
(2012)
To test a model linking
workplace factors (six
areas of work life,
experiences of
bullying and burnout)
and a personal
dispositional factor
(psychological capital)
to mental and physical
health among new
nurses
Nurses
N=165
Physical
health
Mental health
MBI
EE
DP
A significant and
positive relationship
between EE and poor
physical health
A significant and
positive relationship
between DP and poor
mental health
Maslach
et al.
(1988)
Burnout, job setting
and self-evaluation
among rehabilitation
counselors
Rehabilita
-tion
counselors
N=38
Job
Satisfaction
MBI
(Dimensions
examined
separately)
EE
DP
PA
A significant and
negative relationship
between EE and job
satisfaction
63
Table 2 (Continued)
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Puig et al.
(2012)
To determine the
nature of the
relationship between
job burnout and
personal wellness
Mental health
professionals
N=129
Personal well-
ness: (Five
dimensions:
Essential self
Social self
Creative self
Physical self
Coping self)
Counselor burnout
inventory
(CBI)
Exhaustion
Incompeten-ce
Devaluing
clients
Negative work
environment*
Deterioration
in personal
life*
Exhaustion was
found to significantly
predict exercise and
nutrition
The devaluing client
burnout dimension
was negatively
related to the
creative self
The incompetence
burnout scale is
negatively related to
essential, social,
creative and coping
self dimensions of
wellbeing
Risquez et
al.(2011)
To analyze the
relevance of
individual variables
in the development of
burnout and the
possible effects of
having a hardy
personality as a
protective factor
Nurses
N= 97
General Health
Questionnaire
(GHQ-28)
Psychoso-
matic
symptoms
Anxiety
Depressive
symptoms
MBI (Dimensions
examined
separately)
EE
DP
PA
EE was positively
and significantly
related to
psychosomatic
symptoms, and
anxiety
DP was positively
and significantly
related to
64
Table 2 (Continued)
Citation
Purpose Sample type
and size
Well-being
Outcome (DV)
Burnout
Dimension (IV)
Key finding(s)
Risquez
et
al.(2011)
continu-
ed
against burnout and
its consequences on
workers' health
dysfunction
symptoms
depressive symptoms
Um et
al.
(1998)
To empirically
evaluate a model
delineating the
processes whereby
clinical social workers
experience burnout
and job dissatisfaction
in their workplaces
Clinical
social
workers
N=165
Job diss-
atisfaction
MBI
EE
EE is positively and
significantly related to
job dissatisfaction
*Outcome not included in synthesis.
65
CHAPTER THREE (STUDY 2):
JOB BURNOUT AND AFFECTIVE WELL-BEING:
A LONGITUDINAL STUDY OF BURNOUT AND JOB SATISFACTION AMONG
PUBLIC CHILD WELFARE WORKERS
Introduction
Although the antecedents to job burnout have been studied extensively among
child welfare workers, few of those studies examine the impact of burnout on affective
well- be in g . S a ti sfa c ti on de rive d fr om on e ’s job is a n im porta nt aspe c t of q ua li t y of life and overall affective well-being. For most working people the meaning of work goes
beyond it being a source of income. Work for many individuals provides purpose (Morse
& Weiss, 1955), a sense of identity, meaning, feelings of accomplishment, and
connectedness to others (Cartwright & Holmes, 2006; Chalosfsky, 2003; Kahn, 1974). A
great amount of research has been done to better understand what work conditions lead to
a “ ha pp y ” a nd sa ti sfie d wor ke r a nd wha t t hin g s inhi bit thi s fr om occ urr ing (J udge ,
Piccolo, Podsakoff, Shaw, & Rich, 2010; Lambert, Hogan, & Barton, 2002; Lee &
Cummings, 2008; Loher, Noe, Moeller, & Fitzgerald, 1985). A key finding that has
emerged from this stream of research is that job burnout is a threat to job satisfaction
(Bhana & Haffejee, 1996; Brewer & Clippard, 2002; Burke, Koyunco, & Fiksenbaum,
2010; Hombrados-Mendieta, & Cosano-Rivas, 2011; Koeske & Kelly, 1995; Lee &
Ashforth, 1996; Maslach & Florian, 1988; Um & Harrison, 1998). Job burnout, the
feelings of emotional depletion, cynicism, and a lack of efficacy in the workplace
(Maslach & Jackson, 1981), has been linked to a number of adverse affective
66
consequences including a reduction in job satisfaction (Faragher, Cass, & Cooper, 2005;
Lee & Ashforth, 1996; Lee, Lim, Yang, & Lee, 2011). Workplace experiences that
threaten the affective well-being of child welfare workers, such as job satisfaction, pose a
hazard to child protection organizations as a whole. Job burnout can lead to reduced job
satisfaction which can consequently affect work performance (Judge, Thoresen, Bono, &
Patton, 2001), commitment to the organizations (Gunlu, Aksarayli, & Perçin, 2010;
J e rnig a n, B e gg s, & Kohu t, 2002;; L a ndsm a n, 2001 ;; L a ndsm a n, 2008 ), a nd e mpl o y e e s ’
desire to stay in the organization (DePanfilis, Levy Zlotnik, 2008; Mor Barak, Levin,
Nissly, & Lane, 2006; Mor Barak, Nissly, & Levin, 2001; Strolin-Goltzman, Auerbach,
McGowan, & McCarthy, 2008).
This study tests a series of proposed interrelationships of workplace demands and
resources as predictors of burnout development and the subsequent impact of burnout on
affective well-being (e.g. job satisfaction) using longitudinal data collected from a sample
of public child welfare workers. Though several gaps exist in the human service literature
on job burnout and well-being, this study focuses on two important gaps in knowledge
pertaining to the relationship between burnout and well-being among child welfare
workers. The present study tests the consequences of burnout on affective well-being, an
area of research that has received limited attention in child welfare workforce studies.
Furthermore, the studies on job burnout and job satisfaction that have been conducted
among child welfare workers examining the consequences of burnout rely heavily on
correlational analysis. The use of cross-sectional research designs does not allow for
testing key hypotheses about the temporal order of the interrelationships between
67
workplace experiences, burnout, and worker well-being. Using longitudinal data analysis,
this study tests a series of hypotheses about the temporal order of the relationships
between work demands and resources, burnout, and job satisfaction.
Review of Literature
Child Welfare Workers and Job Satisfaction
No job satisfaction benchmark rates of child welfare workers exist. Nevertheless,
findings from Barth, L lo y d , C hrist, C ha pman, a nd Dic kison ’s ( 2008) na ti o na l st ud y on
job satisfaction among child welfare workers in the United States suggest that, as a
whole, child welfare workers are between undecided about their level of satisfaction and
somewhat satisfied with t he ir jobs. Alt houg h w e c a nnot asc e rta in child we l fa re wor ke rs’ job satisfaction overall, what can be surmised is that the job satisfaction of these workers
has important managerial and administrative implications in child welfare organizations
for two key reasons. First, as a form of affective well-being, job satisfaction is a critical
aspect of worker wellness. Secondly, the affective well-being of workers (e.g. job
satisfaction) has the potential to critically impact worker performance and consequently
organizational outcomes.
Managers and administrators in child welfare organizations have an ethical
responsibility to protect the well-being of their workforce. Workers are the driving force
of child protection services. Child welfare workers are charged with the critical task of
protecting children and promoting their growth and happiness within stable family
settings. The satisfaction of workers with their job should be of importance to
administrators and managers given that it is an important component of overall life
68
satisfaction (Near, Rice, & Hunt, 1978), and the subjective and psychological well-being
(Diener, 1984; Spector, 1997; Warr, 1990) of workers. Job satisfaction is a form of
affective well-being and is a complex emotional reaction to one ’s perception of the
relationship between what one wants from one ’s job and what one perceives it as offering
(Locke, 1969). The general sphere of psychological well-being is concerned with
feelings or affect, within which feelings of satisfaction or dissatisfaction lie (Warr, 1990).
Worker well-being is broadly conceptualized as a multi-domain person-related construct
taking into account the impact of workplace experiences on the physical, emotional,
affective, and psychological wellness of individuals (Danna & Griffin, 1999).
The importance of having satisfied workers goes beyond a concern for their
affective well-being to a concern centered on organizational outcomes. Job satisfaction
can affect several organizational outcomes. In their quantitative and qualitative review of
312 workforce samples, Judge, Thoresen, Bono and Patton (2001) found a moderate
relationship between job satisfaction and performance. Within child welfare workforce
research, the relationship between job satisfaction and performance has not been
examined. The organizational outcomes that have been linked to job satisfaction within
the child welfare workforce literature include organizational commitment and turnover.
Previous child welfare workforce studies have found a positive and significant
relationship between job satisfaction and organizational commitment (Landsman, 2001;
Landsman, 2008), commitment to the child protection field (Landsman, 2001), and
intention to stay on the job (DePanfilis, Levy Zlotnik, 2008; Mor Barak, Levin, Nissly, &
Lane, 2006; Strolin-Goltzman, Auerbach, McGowan, & McCarthy, 2008).
69
It is important to contextualize job satisfaction of child welfare workers within the
broader context of workforce management issues in the public child welfare sector. The
child protection sector has historically faced serious challenges with the recruitment and
retention of qualified workers (Government Accountability Office, 2003; Perry, & Ellett,
2008). At the peak of the retention crisis in the United States, it was estimated that some
public child welfare agencies were seeing as much as a 30-40% annual workforce
turnover among workers with less than two years tenure (Government Accountability
Office, 2003). As the public child welfare sector has become increasingly
deprofessionalized, it has been more difficult to attract and/or retain professionally
educated social workers (Perry et al., 2008). The challenge of attracting and keeping
skilled workers to the field is attributed to the nature of child welfare work which
includes working with families and children with complex needs, carrying the burden of
child safety, poor pay, and high caseloads (Government Accountability Office, 2003).
Because of the challenges in maintaining a stable and qualified workforce, job
burnout and job satisfaction continue to be a concern in the child welfare workforce
(Perry & Ellet, 2008). Efforts have been made to attract and retain professionally trained
child welfare workers because it is believed that they are better equipped to serve clients
and families facing a number of complex problems compared to their non-professionally
trained counterparts (Zlotnik, 2003). Federal funds under Title IV-E have been allocated
for training initiatives that incentivize specialized child welfare training through financial
support for continued education and curriculum development at the baccalaureate and
masters levels. Federal funding for specialized child welfare training is administered by
70
the U .S . C hil dre n’s B ur e a u in t he De pa rtme nt of He a lt h and Human Services (DHHS;
Zlotnik, 2003). The funds have been used largely for specialized agency-university child
welfare training partnerships between public child welfare agencies and schools of social
work (Risley-Curtiss, 2003). Though training content may vary between counties and
states, the focus of specialized child welfare training is on implementing competency-
based curriculum that equips employees for child protection work.
Job Burnout
Job burnout is an individual stress syndrome contextualized within complex social
relationships in the workplace (Maslach & Goldberg, 1998). Burnout consists of three
dimensions including emotional exhaustion, depersonalization and reduced personal
accomplishment that develop in response to chronic exposure to stress in the workplace
(Maslach, 1993; Maslach, 2003 ). J ob bur nout ca use s a de pletion of the indi vidual’ s
emotional resources and personal energy (Leiter & Maslach, 2001).
As a reaction to chronic stress, job burnout can lead to job behaviors including
withdrawal, which diminishes the opportunities to have satisfying work experiences.
Emotional exhaustion is the central dimension of burnout and refers to feelings of being
emotionally depleted due to over-extension. Maslach and Goldberg (1998) suggest that
work overload and personal conflict at work are the central sources of exhaustion.
Emotional exhaustion represents the individual strain dimension of burnout. Cynicism, or
depersonalization, s the interpersonal dimension of burnout that develops as a protection
against feelings of exhaustion. When the exhaustion becomes too overwhelming for the
individual, he or she detaches from the work and becomes cynical and disconnected from
71
clients and co-workers. The third dimension of job burnout, personal accomplishment- is
postulated to be the self-evaluation dimension of the syndrome. Maslach and Goldberg
(1998) propose that that the interrelationship between emotional exhaustion and
depersonalization is a causal one whereby feelings of emotional exhaustion lead to
depersonalization. The third dimension, reduced personal accomplishment, is posited to
develop separately.
Proposed Model of Burnout Development and Its Impact on Job Satisfaction
This study uses the Job Demands-Resources model (JD-R) as a guiding
framework to test the impact of workplace demands and resources on burnout
development and the subsequent impact of burnout on job satisfaction. The JD-R model
has been previously used in empirical studies to explain the effects of job demands and
resources on burnout development and is considered to be parsimonious, flexible, and
robust (Bakker & Demerouti, 2007; Demerouti, Bakker, Nachreiner, & Schaufeli,
2001; Llorens, Bakker, Schaufeli, Salanova, 2006; Schaufeli, Bakker, & Van Rhenen,
2009). It is worthy of note that the JD-R model is used in this study as a guide and not to
test the validity of the model. Proposed in this study is a theory-driven conceptual model
that hypothesizes that workplace demands and resources lead to burnout, which
subsequently leads to reduced affective well-being. The conceptual model was translated
into a testable model where job stress and work-family conflict were modeled as
demands and social support and specialized child welfare training were modeled as
resources (Figure 2). The selection of the demands and resources for inclusion in this
72
study was based on theory and on findings from previous child welfare workforce
studies.
A central postulate of the JD-R model is the assumption that all working
conditions can be categorized as a demand or resource irrespective of the occupational
field. Job demands include any physical, social, or psychological requirements of the job
that call for sustained mental or physical effort. Resources include the physical, social or
psychological aspects of the job that meet one of the following criteria: a) serve a
functional role in meeting work goals, b) reduce the physiological and/or psychological
costs of demands, and/or c) promote personal growth and development
(Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Resources may be drawn from
various sources including the overall organization (e.g. pay, job security), interpersonal
relationships (e.g. supervisory and peer social support), organization of the work (e.g.
clarity of work roles, decision making authority), or at the task level (e.g. task
significance; Bakker & Demerouti, 2007).
The JD-R model assumes a dynamic set of interrelationships between demands
and resources and their subsequent impact on both positive (e.g. employee engagement)
and negative (e.g. job burnout) indicators of employee well-being (Bakker et al., 2007).
The JD-R model suggests that there is differential impact of job demands and resources
on the dimensions of burnout. Person-environment fit theory has been used to help
explain the process by which a lack of equilibrium between work demands and abilities
can lead to stress in the workplace (French & Caplan, 1972; Caplan, 1987). The
mechanisms by which resources influence the development of burnout can be explained
73
using conservation of resources (COR) theory (Wright & Hobfoll, 2004). COR purports
that an inherent motivation exists within individuals to obtain and retain valued resources
(Hobfoll & Freedy, 1993). According to the postulates of COR, if an individual cannot
obtain resources, faces a threat of losing resources or loses the resources that he or she
values, it subsequently leads to feelings of psychological stress (Hobfoll et al., 1993).
Job Demands, Resources, and Job Burnout in the Child Welfare Sector
Demands. Job burnout theory proposes that burnout develops as a result of exposure to
chronic job stress (Maslach & Jackson, 1981; Maslach, 2003). To account for the
influence of job stress on burnout development, the proposed model in this study includes
job stress as an antecedent to burnout. The theoretical postulate that job stress leads to
job burnout has been buttressed by empirical findings in the general workforce literature
(Cordes & Dougherty, 1993; Lee & Ashforth, 1996; Lee, Lim, Yang, & Lee, 2011; Lee,
Seo, Hladkyj, Lovell, & Schwartzmann, 2013; Örtqvist & Wincent, 2006). Similarly,
studies specific to human service workers (Kim & Stoner, 2008; Kirk -‐ Brown & Wallace,
2004; Lee, Lim, Yang, & Lee, 2011; Lloyd, King, & Chenoweth, 2002) and child
welfare workers (Boyas & Wind, 2010; Kim 2011; Lizano & Mor Barak, 2012) have
found a positive relationship between stress and burnout.
Work-family conflict was modeled as a workplace demand in this study. Work-
family conflict refers to the inter-role conflict that occurs when the demands of work and
family are contradictory (Greenhaus & Beutell, 1985, p. 77). Previous studies have
found a positive relationship between work-family conflict and job burnout (Allen, Herst,
Bruck, & Sutton, 2000; Innstrand, Langballe, Espnes, Falkum, & Aasland, 2008). More
74
recently, interest in the impact of WFC on human service workers has grown (Kalliath,
& Kalliath, 2013a; Kalliath, & Kalliath, 2013b; Lambert, Pasupuleti, Cluse-Tolar,
Jennings, & Baker, 2006; Lizano & Mor Barak, 2012). Within child welfare workforce
research work-family conflict has been linked to burnout (Lizano & Mor Barak, 2012),
and turnover (Annie E Casey Foundation, 2003; Levy, Poertner, & Lieberman, 2012;
Nissly, Barak, & Levin, 2005). In order to contribute to the growing examination of the
relationship of WFC and burnout within child welfare workforce research, the conceptual
model tested included work-family conflict as a predictor of job burnout.
Resources. The proposed model included two key resources relevant to child welfare
workers including social support and specialized child welfare training. Social support
was modeled as a resource in the present study and was included because of its influence
on job satisfaction (Baruch-Feldman, Brondolo, Ben-Dayan, & Schwartz, 2002; Lu,
While, & Barriball, 2005) and burnout (Cordes & Dougherty, 1993; Halbesleben, 2006).
This study includes two forms of workplace social support, organizational support and
supervisory support. Both organizational and supervisory support have previously been
studied in human service workforce research and have been found to critically shape
workplace experiences of child protection workers (Collins, Amodeo, & Clay, 2007;
GAO, 2003; Lizano & Mor Barak, 2012; Travis & Mor Barak, 2010; Westbrook, Ellis,
Ellett, 2006).
Given that specialized child welfare training targets the development of
competencies that serve as preparation for child welfare work (Clark, 2003), it was
modeled as a resource in this study. Within this study, specialized child welfare training
75
consisted of receiving funding to pay for continued social work education in a post
baccalaureate program (Master of Social Work), attending specialized child welfare
focused courses, and completion of a one or two year field internship in public child
welfare. This study aims to test if having specialized training in child welfare affects job
satisfaction among child welfare workers when compared to their non-specially trained
counterparts.
The conceptual model of job demands and resources as predictors of burnout
development and the subsequent impact of burnout on job satisfaction tests the following
hypotheses:
Hypothesis 1): Job demands (e.g. role conflict, role ambiguity, and
work-family conflict) at wave 1 are positively and significantly related to
emotional exhaustion and depersonalization at wave 2.
Hypothesis 2.): The relationships between job demands at wave 1, burnout at
wave 2 (e.g. emotional exhaustion and depersonalization), and job satisfaction at
Time 3 will be moderated by job resources (e.g. supervisory and organizational
support, specialized child welfare training).
Hypothesis 3.): Emotional exhaustion is significantly and positively associated
with depersonalization.
Hypothesis 4a.): Emotional exhaustion at wave 2 is negatively and significantly
related to job satisfaction at wave 3. Hypothesis 4b.) Depersonalization at wave 2
is negatively and significantly related to job satisfaction at wave 3.
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Methods
Study Procedures and Sampling
Data for this three-wave longitudinal panel study were drawn from an availability
sample of 361 workers in an urban public child welfare department in Southern
California that employs approximately 5,000 workers and oversees the welfare of an
estimated 12,000 children and youth. Data were collected over a twelve-month period in
six-month intervals from July 2004 to September 2005. Participants were recruited during
their lunch hour while attending one of 30 required or voluntary training courses offered
at a university-affiliated child welfare-training center. Participants were given
information about the purpose and voluntary nature of the study. Interested participants
enrolled in the study after completing an informed consent process with a trained
research assistant. All participants were required to sign a consent form. A free lunch was
offered as a token of appreciation for participating in the study. Participants completed
the questionnaire in a private training room.
Missing Data
Due to attrition in the study sample, several steps were taken to address missing
data prior to conducting analysis. Missing data within longitudinal studies is
commonplace (Schafer & Graham, 2002). Baseline data was obtained from all 363
respondents, 187 respondents provided data at wave 2, and 133 respondents provided
data at wave 3. In order to address missing data, a full information maximum likelihood
(FIML) estimation strategy was used during analysis. Full information maximum
likelihood estimation uses all available data to make inference and estimate parameters
77
using a likelihood function (Schafer et al., 2002). The use of FIML to estimate a model
with missing data is considered appropriate depending on the mechanism that led to the
missing data. Maximum likelihood estimation approaches are only appropriate for use in
situations where data are missing completely at random (MCAR) or at random (MAR)
(Enders, & Bandalos, 2001; Schafer & Graham, 2002). Data are considered missing at
random if the data are not missing due to the values of the dependent variable of interest
(Schafer & Graham, 2002; Rubin, 1976) Several logistic regression models were tested to
examine if the endogenous variables in the model, job burnout and job satisfaction
predicted missingness). Two dummy variables were created to capture missing data at
wave 2 and wave 3 with the following dummy coding: 0= no missing data, 1= missing
data. The first two logistic regression models tested the relationship between burnout
level at wave 1 and missing data at wave 2 and 3. A second logistic regression model was
conducted to test if level of burnout at wave 2 predicted missing data at wave 3. The
same logistic regression modeling process used in burnout was used to test for the
presence of a significant relationship between job satisfaction and missingness. None of
the logistic regression models yielded any significant results. Additionally, respondents
with missing data were compared to those with no missing data based on several
demographic characteristics including: age, race/ethnicity, gender, educational
background, tenure and position in the organization. No statistically significant
differences were found in any of the demographic characteristics between those with and
those without missing data.
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Measurement
Job Satisfaction. Job satisfaction is conceptually defined in the present study as general
affective reaction to the job and measured using four Likert scale items from Quinn and
S taine s’ ( 1979) Qua li t y o f E mpl o y ment S urve y . I t e ms ar e on a 6 -point Likert scale
response scheme with higher scale scores representing greater job satisfaction. The scale
used has been found to be a valid and reliable measure of job satisfaction and has been
used previously in human service workforce studies (Djukic, Kovner, Budin, & Norm,
2010; Mandell, Stalker, Zeeuw Wright, Frensch, & Harvey, 2012; Mor Barak, Levin,
Nissly, & Lane, 2006; Quinn et al., 1979). The reliability coefficient for the scale in this
study was .89. Job satisfaction scale scores were drawn from time 3 data. Scale items for
job satisfaction items and all other scales used in this study can be found in Appendix A.
Job Burnout. Job burnout is conceptually defined as feelings of emotional exhaustion
and depersonalization in the present study and measured using two of the three subscales
in the Maslach Burnout Inventory- Human Services Survey – (MBI-HSS; Maslach &
Jackson, 1981). The MBI-HSS – is comprised of a 22-item Likert scale that includes
three subscales each measuring the three aspects of burnout: emotional exhaustion (nine
items), depersonalization (five items), and personal accomplishment (eight items).
Subscale items pertaining to the personal accomplishment dimension of burnout were
excluded from the present study on conceptual and empirical grounds. Conceptually, it
has been proposed that personal accomplishment is more accurately conceptualized as a
personal characteristic rather than a symptom of burnout (Cordes & Dougherty, 1993)
and empirically previous study findings suggest that personal accomplishment is not as
79
strongly related to the emotional exhaustion and depersonalization (Lee & Ashforth,
1996; Schaufeli, Bakker, Hoogduin, Schaap, & Klader, 2001). Developed initially for
human service workers, the MBI has been demonstrated to be a valid and reliable
measure of job burnout across occupations, cultures, and languages (MBI; Maslach &
Jackson, 1981; Poghosyan, Aiken, & Sloane, 2009; Worley, Vassar, Wheeler, & Barnes,
2008). The emotional exhaustion scale items used in this study had an overall
C hronb a c h’s r e li a bil it y c oe ff icie nt of .91 a nd the de pe rsona li z a ti on sc a le it e ms had a .81
reliability coefficient. Wave 2 emotional exhaustion and depersonalization scale items
were used in this study
Job stress. Job stress is operationally defined as experiences of role conflict and role
ambiguity in the work setting. Role conflict refers to inconsistent demands at work
(Riz z o, House , a nd L irtz man’ s (1970). Role ambiguity makes reference to a lack of
available information pertaining to the roles and responsibilities in an organization
(Riz z o, House , a nd L irtz man’ s, 1970). Rol e c onfl ict a nd a mbi g uit y w e re m e a sure d usi n g R izz o, House , a nd L irtz man’ s ( 1970) role conflict and ambiguity scales. Eight role
conflict and six role ambiguity items were used to create a composite scale to measure
job stress. Wave 1 role ambiguity and role conflict items were used in this study. Role
a mbi g uit y ha d a C hronb a c h’s alpha coefficient of .83 and role conflict had a reliability
coefficient of .85 in this study.
Work-Family Conflict. Work-family conflict, defined as the interference of work related
roles and responsibilities on the family sphere, is measured using three items from
B e a tt y ’s (1996 ) w ork -family conflict scale. Scale items are rated on a 6-point Likert with
80
a re sponse o f “ 1” c orr e sp onding to “stron g l y disa gre e ” a nd a “ 6” c o rr e spon ding to
“ strong l y a g re e .” G re a t e r sc a le sc o re s r e pre s e nt gre a te r e x pe rie nc e s o f work-family
conflict. The work- fa mi l y sc a le ha d a C hronb a c h ’ s a lpha r e li a bil it y v a lue o f .75 in t his
study. Work-family conflict scale items for use in this study were drawn from wave 1
data.
Organizational and Supervisory Support. Perceived organizational support and
supervisory support were both measured using eight-items developed by Eisenberger,
Huntington, Hutchison, & Sowa (1986). The perceived supervisory and organizational
support scales have been found to be valid and reliable measures of social support in the
workplace (Eisenberger, Fasolo, & Davis-LaMastro, 1990; Eder & Eisenberger, 2008).
Items from both scales are identical with the exception of the use of the words
“ supe rvisor ” a nd “ o r g a ni z a ti on” in ea c h re sp e c ti v e sc a le. I t e m re sponses a r e o n a 6-point
Likert scale, with higher scale scores signifying higher levels of perceived social support.
wave 1 organizational and supervisory support items were used in this study.
S upe rvisor y suppo rt y i e lded a C hronb a c h’s a lpha c oe ff i c ient of .83 a nd o r ganizational
support had a reliability coefficient of .85.
Specialized child welfare training . I n for mation o n re sponde nt’s c ompl e ti o n of
specialized child welfare training was collected through a yes/no self-report questionnaire
item collected during wave 1 of the study.
Covariates. R e sponde nts ’ a g e , se x , e thni c it y /r a c e , orga niz a ti ona l t e nure a n d e duc a ti ona l
ba c k g round w e re d ra wn fr om par ti c ipants’ s e lf -reported answers provided on the baseline
questionnaire. The variables sex, race/ethnicity, and position in the organization were
81
dumm y c ode d in pr e pa ra ti on fo r a na l y sis . The se x va ria ble w a s dum m y c o de d a s “ 0” a nd
“ 1” for m a les a nd f e male s, re spe c ti ve l y . R a c e /ethn icit y wa s dum m y c od e d b y c oll a psin g all those who identified as African American, Latino/a, Asian, American Indian, Native
Ha wa ii a n a nd Othe r into a “ non - C a u c a sian” c a te gor y nume ric a ll y c od e d a s “ 1” .
R e sponde nts i de nti f y in g a s C a uc a sian we r e c ode d a s “ 0” . R e spond e nt pos it ion i n the
orga niz a ti on wa s c ode d a s “ 0” for man a g e rs or su pe rvisor s a nd “ 1 ” f or line-workers.
Analysis Strategy
A series of multi-group path analysis models, a form of structural equation
modeling that simultaneously tests multivariate interrelationships of observed variables
(Bollen, 2005), were performed using IBM SPSS AMOS 18. A multi-group approach
applied to structural equation modeling was used because it permits for invariance to be
tested between groups (Byrne, 2009) and as a result allows for the identification between
group model differences. Prior to analysis, study pa rtic ipants we r e se p a ra t e d int o “ low” a nd “ hi g h” g roups b a se d on their re porte d l e ve ls o f or g a niz a ti ona l and supe rvisor y support. A me dian spli t st ra te g y wa s used to s e pa ra te the stud y sa mpl e int o “ low” a nd a “ hig h ” soc ial support g ro ups. This stra teg y wa s selected over a mean split based on
previous application in similar studies testing the moderating effect of job resources in
the JDR model (Bakker, Demerouti, & Verbeke, 2004) and because it provided a more
even split between the two groups than did a mean split approach.
In preparation for between group comparisons, new variables were created to
separate those with low and high organizational and supervisory support and those with
and without specialized child welfare training. A new variable dividing study participants
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into low and high organizational support groups was created. The study sample was
divid e d int o two g roups ba se d on the sa mpl e ’s m e dian or g a niz a ti ona l sup port sc ore of 25 .
Based on the median split, 51.5% of the participant scores ranged from 8 – 25 and were
c ode d a s be in g in t he “ low or g a niz a ti ona l supp ort g roup ” while those sc o ring 26 – 48
c omprised 48.5% of the s tud y sa mpl e a nd we r e c o de d a s ha vin g “ hi g h or ga niz a ti ona l
support.” The followin g dumm y c odin g sc he m e wa s e mpl o y e d to di sti ngu ish high versus
low organizational support groups: low= 0, high= 1. As a result of the split, 173
respondents were categorized as having low and 163 were categorized as having high
organizational support. Twenty-seven respondents had missing organizational support
data and were excluded from the path model analysis.
The same procedure was conducted to designate low and high supervisor support
g roups b a se d on the sa m ple’ s media n supe rvisor y support sc a le sc o re of 40 . As a re sult ,
54.3% of participants scoring from 8 – 40 we r e c o de d a s ha vin g “ low sup e r visor y support
g roup ” a nd thos e s c orin g 41 – 48 comprised 45.7% of the study sample and were coded
a s ha ving “hi g h supe rvis or y suppo rt.” Dumm y c o ding wa s us e d to i de nti f y the low ve rsus
high supervisory support groups (low= 0, high= 1). After splitting the sample by
supervisory support level 176 respondents were in the low group and 148 were in the
high supervisor support group. Thirty nine respondents had missing supervisory support
data and were excluded from analysis. A variable to distinguish between those who had
received specialized training and those who had not was created where the 235
re sponde nts wi th no s pe c ializ e d tra ini ng we re c od e d a s “ 0” a nd 120 who h a d tra ini ng
83
we re c ode d a s “ 1” . Ei g ht re spond ents did not provide information about specialized child
welfare training and were excluded from analysis.
In preparation for examining differences in workplace experiences of stress and
job burnout by level of social support and specialized child welfare training, a baseline
model that did not test for group differences was analyzed (See Figure 4). Though the
baseline model cannot be compared statistically to the forthcoming models because it is
not nested within the other models due to the lack of social support variables and
specialized training variables, it was analyzed for the purposes of having a conceptual
baseline for comparison. Following the analysis of a baseline model, a two-step model
testing strategy was used for each form of social support and specialized child welfare
training. This two-step approach of comparing a fully constrained and an unconstrained
model is the recommended approach when conducting multi-group structural equation
models (Byrne, 2009). First, a fully constrained model was analyzed as a global test of
invariance in covariance structures between the two groups. This approach requires that a
path model be analyzed simultaneously for the groups and that all paths are constrained
to be equal to each other. The first model was conducted as it is recommended practice
based on the Joreskog tradition in multi-group structural equation modeling (Byrne,
2004). A second multi-group path model with no path constraints and a critical ratio of
differences was analyzed. The second approach allows for paths to vary between groups
and tests if the path parameters are statistically different between groups (Arbuckle, 200).
The second unconstrained model was analyzed because the global test for group
invariance has been found to lead to possible contradictory findings and is overly
84
stringent as a test of group differences (Byrne, 2004). As an alternative to testing only the
overall model covariance structure differences between groups, it is recommended to test
each of the parameters in the model (Byrne, 2004), which was accomplished here in step
number two.
Results
Descriptive Statistics and Correlations
Table 3 presents the demographic characteristics of the study sample. The average
age for the sample was 37. A large proportion of study participants were women (83.4%).
The sample was approximately a third Caucasian (30.7%) and Latino (a)/Hispanic
(29.9%) with the third largest group being African American/Black (21.9%). Tenure
ranged from less than a year to 36 years in the organization with an average tenure of six
years. Approximately two-thirds of the sample reported having a graduate degree (e.g.
MSW, MFT, MA, PhD). A correlation matrix for the study variables of interest is
summarized and presented in Table 4.
Fit statistics
A total of seven path models were conducted to test the central study hypotheses.
The first model conducted was a baseline path model that excluded any social support or
specialized training variables. Then, a constrained and unconstrained model were tested
for organizational support, supervisory support, and specialized child welfare training.
Multiple model fit statistics were used to assess the adequacy of model fit including a
Chi- S qua re test (χ
2
), normative fit index (NFI), comparative fit index (CFI), and the Root
Mean Square Error of Approximation (RMSEA). The standards employed for assessing
85
good model fit follow standard criterion used in SEM and which include a non-
sig nific a nt χ
2
value, a CFI and NFI greater than .90, and an RMSEA equal to or less than
.05 (Kline, 2010).
The ba se li ne model d e mons tra ted a g ood ove ra ll model f it χ
2
(8)= 13.45, p= .09;
CFI = .99, NFI= .98, RMSEA = .04, AIC= 127.46 (Table 5). The baseline model with no
social support variables was found to account for 24% of the variance in job satisfaction.
Constrained and unconstrained models were tested for organizational and supervisory
support. The c onst ra ined orga niz a ti ona l supp ort mode l had g ood ov e ra ll f it , χ
2
(32)=
27.40, p= .70; CFI = 1.00, NFI= .96, RMSEA = .00, AIC= 223.36 (Table 6). The second
non- c onst ra ined mode l o f or g a niz a ti ona l supp ort w a s a na l y z e d a lso y ielde d a g ood fit, χ
2
(16)= 11.07, p= .81; CFI = 1.00, NFI= .98, RMSEA = 0, AIC= 239.01. The constrained
organizational support model accounted for 29% of variance in job satisfaction. The
unconstrained organizational support model accounted for 17% and 42% of variance in
job satisfaction for the low and high organizational support groups, respectively. The
constrained supervisory support path model analysis produced a good fit χ
2
(32)= 29.16,
p= .61; CFI = 1.00, NFI= .96, RMSEA = 0, AIC= 225.17 (Table 7). The unconstrained
supe rvisor y model a lso y ielde d a g ood f it , χ
2
(16)= 14.41, p= .57; CFI = 1.00, NFI= .97,
RMSEA = 0, AIC= 242.41. The constrained supervisor support model accounted for
27% of variance in job satisfaction. The unconstrained model accounted for 34% and
25% of variance in job satisfaction among those with low and high supervisory support,
respectively. The constrained specialized child welfare training model had a good fit
( χ 2= 41.20 ( 32 ), p= .13;; C F I = .98, N F I = .94, R MS EA = .03, AIC= 273.20) (Table 8).
86
The constrained specialized child welfare training model accounted for 25 % of variance
in job satisfaction. The unconstrained child welfare training model accounted for 57 %
and 20% of variance in job satisfaction among those with and without specialized child
welfare training, respectively.
Path Coefficients
Baseline Model- The baseline sample model found no statistically significant impact of
demographic or work variables on job satisfaction (Figure 4, Table 9). Role ambiguity
(b= .31, β = .14, p≤. 01) a nd wor k -family conflict (b= .54, β = .19, p≤. 01) we re the onl y workplace demands that predicted emotional exhaustion at a statistically significant level.
No workplace demands were found to predict depersonalization, although it is worthy of
note that the relationship between work-family conflict and depersonalization yielded a
p-value of .06, only slightly above the critical value of .05. Emotional exhaustion had a
positive significant relationship with depersonalization (b= .24, β = .57, p≤ . 01). None of
the direct paths from workplace demands to job satisfaction were found to be statistically
significant. Emotional exhaustion was the only significant predictor of job satisfaction
(b= - .22, β = - .45, p≤. 01 ).
Organizational Support Model-
Constrained model. The constrained organizational support model path
coefficients are presented in Table 10. Race/ethnicity was the only significant
demographic characteristic that predicted job satisfaction (b= 2.14, β = . 25 , p≤. 05) w it h
non-Caucasian respondents reporting higher job satisfaction. Work-family conflict was
the only job demand that significantly predicted emotional exhaustion (b= .62, β = . 31,
87
p≤. 01). N o job dema nds we re found to pre dict de pe rsona li z a ti on. Emot ion a l ex ha usti on
was found to have a statistically significant relationship with depersonalization (b= .23, β
= .62, p≤. 01). N o st a ti sti c a ll y si g nific a nt re lations hip wa s found be twe e n j ob de mands
and job satisfaction. Emotional exhaustion was the only burnout dimension that predicted
job satisfaction (b= - .22, β = - .50, p≤. 01).
Unconstrained model. The unconstrained organizational support model path
coefficients are presented in Table 10 and Figure 5. When demographic variable paths
were compared between those with low and high organizational support it was found that
all paths for both groups were in the same direction. Race/Ethnicity was a statistically
significant predictor of job satisfaction among those with high organizational support (b=
3.03, β = .25, p≤. 01) but not among those with low (b= 1.16, β = . 11, p≤. 01). T hose who
identified as non-Caucasian had a higher rate of job satisfaction. Based on the critical
ratio for differences test, the difference between Race/Ethnicity path coefficients for the
two groups is not a statistically significant one. The relationship between job demands
and emotional exhaustion differed by group. The relationship between role ambiguity and
emotional exhaustion differed between groups at a statistically significant level. In the
low organizational support group there was no statistically significant relationship found
between role ambiguity and emotional exhaustion. Furthermore, the relationship between
role ambiguity and emotional exhaustion among those with low organizational support
was found to be negative (b= -.07, β = -.14, p ≥.01). Among those who reported having
high organizational support a positive significant relationship was found between role
ambiguity and emotional exhaustion (b= .83, β = .36, p≤. 01). B a s e d on t he critical ratio
88
for differences coefficient, we conclude that the relationship between role ambiguity and
emotional exhaustion is statistically different between the two groups.
Role conflict was found to be a significant predictor of emotional exhaustion
among those with low organizational support (b= .30, β = .21, p≤. 05) but not among those with high organizational support. The critical ratio for differences test however
suggests that the difference in role conflict between groups is not statistically significant
one. No direct paths from job demands to job satisfaction were found to be statistically
significant in either group. No job demands predicted depersonalization in either group.
Emotional exhaustion had a positive and significant relationship with depersonalization
in both the low (b= .23, β = .56, p≤. .01) a nd hi g h ( b= .24, β = .61, p≤. 01) orga niz a ti ona l
support groups. Higher levels of emotional exhaustion predicted lower levels of job
satisfaction among the low (b= - .18, β = - .37, p≤. 05) a nd hi g h ( b= - .27, β = - .56, p≤. 01)
organizational support groups.
Supervisory Support Model-
Constrained model. The constrained supervisory support model path coefficients
are presented in Table 11. None of demographic characteristic variables predicted job
satisfaction. Work-family conflict was the only job demand that predicted emotional
exhaustion (b= .57, β = .21, p≤. 05). N o job dema nds we re p re dictor s of e mot ional
exhaustion. Emotional exhaustion had a positive and significant relationship with
depersonalization (b= .24 , β = .59, p≤. 01). Emoti ona l ex ha usti on wa s a sig n ific a nt
predictor of job satisfaction (b= - .23, β = - .47, p≤. 01) b ut depe rson a li z a ti on wa s not .
89
Unconstrained model. The unconstrained supervisor support model path
coefficients are presented in Table 11 (Figure 6). No demographic characteristic
variables were predictors of job satisfaction. Role conflict and role ambiguity did not
predict emotional exhaustion in either group. Higher levels of work-family conflict
predicted higher levels of emotional exhaustion at a statistically significant level among
those with low supervisory support (b= .96, β = .3 2, p≤. 01) but not among those w it h
high supervisor support (b= .27, β = .10, p > .05). Thoug h the p a th coe ff ici e nts for the
relationship between work-family conflict and emotional exhaustion differed between
groups, the difference was not statistically significant.
Role ambiguity and role conflict were not significant predictors of
depersonalization in either group. Work-family conflict was a predictor of
depersonalization among those with low supervisor support (b= - 25, β = - 19 , p≤. 05) but
not among those with high supervisor support (b= - .06, β = -.05, p >.05). Higher levels of
emotional exhaustion were related to higher levels of depersonalization among those in
the low (b= .28, β = .65, p≤. 01) a nd hig h sup e rvis or suppor t group ( b= .19, β = .50, p≤.
01). Role ambiguity was the only job demand that had a direct statistically significant
relationship with job satisfaction (b= - .23, β = - .2 3, p≤. 05) a mong thos e w it h low
supervisory support but not among those with high supervisory support. Though
different, the difference in the relationship between role ambiguity and job satisfaction
between groups was not statistically significant. Higher levels of emotional exhaustion
predicted lower levels of job satisfaction in both the low (b= - .22, β = - .46, p≤. 01) a nd
90
high (b= - .22, β = - .48, p ≤. 01) supe rvisor y suppo rt g roups. De pe rsona li z a ti on did not predict job satisfaction.
Specialized Child Welfare Training Model
Constrained model. Path model coefficients for both the specialized child welfare
education training are presented in Table 12. No demographic variables predicted job
satisfaction in the constrained specialized child welfare training with the exception of
race/ethnicity (b = 1.86, β = .16, p≤. 05) w it h non -Caucasian respondents reporting higher
job satisfaction. Work-family conflict was the only job demand that had a significant
direct effect on emotional exhaustion (b= .56, β = .21, p≤. 01) a nd de pe rson a li z a ti on ( b= -
.17, β = - .16, p≤. 05). Em oti ona l ex ha usti on wa s a sig nific a nt pr e dictor of
depersonalization (b= .25 , β = .63, p≤. 01). Emoti ona l ex ha usti on pr e dicte d job
satisfaction (b= - .26, β = - .52, p≤. 01) w hil e de pe rs ona li z a ti on did not . Dir e c t paths
between role conflict, role ambiguity, and work-family conflict were tested and none
were found to be statistically significant predictors of job satisfaction.
Unconstrained model. Path coefficients for the unconstrained specialized child welfare
education model are presented in Table 12 (Figure 7). No demographic characteristics
were found to predict job satisfaction among those with no specialized child welfare
education. However, among those with specialized child welfare education, race/ethnicity
and position within the organization were found to be statistically significant predictors
of job satisfaction. Being non-Caucasian with specialized child welfare education
predicted higher levels of job satisfaction (b= 3.16, β = .26, p≤. 05). The c ritica l ra ti o test
of differences suggests that the difference in the relationship between race and job
91
satisfaction between the two groups is not statistically significant. Being a line-worker
among those with specialized child welfare training was negatively related to job
satisfaction (b= - 6.16, β = - .32, p≤. 05) but not a mong those w it hout s pe cialized training.
The difference in relationship between organizational position between the two groups
wa s found to be statis ti c a ll y sig nifi c a nt at a p≤. 05 .
Job demands had differential impact on job burnout between the two groups.
Role ambiguity and role conflict did not predict emotional exhaustion in either group.
Greater rates of role ambiguity predicted higher levels of depersonalization in those with
specialized child welfare training but not among those without. The critical ratio for
differen c e s w a s st a ti sti c a ll y sig nifi c a nt (p≤. 05) su gg e sti n g that ther e is a st a ti sti c a ll y different relationship between role ambiguity and depersonalization between the two
groups. The relationships between work-family conflict and the dimensions of burnout
were in the same direction among those with and without specialized training, but the
relationships were only significant among those without specialized training.
Nevertheless, the difference between groups in the relationship between work-family
conflict and burnout between the two groups was not a statistically significant one.
Emotional exhaustion was positively related to depersonalization in both specially trained
(b= .17, β = .40, p≤.01) a nd non -specially trained groups (b= .29, β = .71, p ≤.01). H ig h e r
rates of emotional exhaustion were predictive of lower job satisfaction in both specially
(b= - .31, β = - .64, p≤.01 ) a nd non -specially (b= - . 18, β = - .38, p≤.01) tra in e d gro ups.
Depersonalization did not predict job satisfaction in either group.
92
Discussion
The purpose of this study was to investigate the interrelationships between
demands, burnout and job satisfaction across time while taking into account the influence
of resources (e.g. social support and specialized child welfare training) on those
interrelationships.
Job Demands, Job Burnout, and Job Satisfaction
A baseline model was first tested to capture the relationships between workplace
demands, job burnout, and job satisfaction without the influence of workplace resources.
It was hypothesized that job demands (role conflict, role ambiguity, and work-family
conflict) at baseline would predict job burnout six months later. The overall theory-driven
conceptual model tested performed as was hypothesized with some noteworthy
exceptions. All demands had a positive and significant relationship with emotional
exhaustion with the exception of role conflict. This finding is contrary to what was
hypothesized given that the job burnout literature suggests that role conflict, as a form of
job stress, leads to greater levels of burnout (Lee, & Ashforth, 1996; Lee, Lim, Yang, &
Lee, 2011). It is possible that the lack of relationship found between role conflict and job
burnout may be due to factors idiosyncratic to the study sample. The sample of child
welfare workers may not be susceptible to role conflict as an antecedent to burnout.
Another plausible explanation is an empirical one. Job stress is commonly measured in
burnout studies as a composite of role conflict and role ambiguity (Kim & Stoner, 2008;
Thomas & Lankau, 2009). The use of a composite scale may conceal the differential
93
impact of role conflict and role ambiguity on burnout while in this study the two were
tested separately.
Job demands predicted emotional exhaustion but not depersonalization. This
finding contradicts the hypothesized relationship between demands and depersonalization
and suggests that work demands impact depersonalization through emotional exhaustion.
This conjecture would fit with the burnout theory postulate that emotional exhaustion is
the central dimension of burnout (Maslach, Schaufeli, & Leiter, 2001) and that it leads to
depersonalization (Maslach et al., 2001). Job demands had no direct effect on job
satisfaction. No demographic variables predicted job satisfaction suggesting that job
satisfaction in the present study did not vary by age, gender, race, educational
background or position in the organization. Emotional exhaustion at wave 2 was the only
dimension found to predict job satisfaction at wave 3. Unexpectedly, depersonalization
did not predict job satisfaction. A possible explanation for the null relationship found
between depersonalization and job satisfaction is that emotional exhaustion as the
individual strain dimension is more likely to influence well-being outcomes given the
hazard that work strain can pose to wellness. Conversely, depersonalization is a
manifestation of the interpersonal dimension of burnout and may as a result not impact
affective well-being.
Job Demands, Job Burnout, Job Satisfaction and Resources
Findings from the multi-group path models suggest that the type and level of job
resource moderates the relationship between job demands, burnout and job satisfaction.
Job demands had diverging effects on several relationships in the model with the
94
exception of two relationships. The relationship between emotional exhaustion and
depersonalization and emotional exhaustion and job satisfaction were consistent across
all groups and models. This finding suggests that regardless of social support and
specialized training, emotional exhaustion is positively related to depersonalization and
negatively related to job satisfaction.
Organizational Support. When the moderating role of organizational support was
examined, some interesting results emerged. First, role conflict and work-family conflict
predicted emotional exhaustion among those with low organizational support but not
among those with high organizational support. This finding suggests that role conflict is
more likely to lead to emotional exhaustion among those with low organizational support.
Interestingly, role ambiguity predicted emotional exhaustion among those with high
organizational support. This finding was unanticipated given that, based on the JDR-
model, higher levels of resources in the workplace should help mitigate the impact of
demands on burnout development (Bakker & Demerouti, 2007). It is possible that more
organizational support is provided to those who have more ambiguous job duties.
Supervisory support. In the path model analysis that included the moderating effect of
supervisor support it was found that role conflict and role ambiguity at baseline did not
impact either dimension of job burnout significantly in either the low or the high group at
wave 2. When the moderating effect of supervisory support is taken into account, role
conflict and ambiguity do not predict burnout. Work-family conflict led to greater levels
of emotional exhaustion and depersonalization among those who felt less supported by
supervisors.
95
Specialized Child Welfare Training.
When the moderating effect of specialized child welfare training was examined,
differences were found between those with and those without specialized training. It
should be noted that the model that accounted for specialized child welfare training
accounted for the greatest variance explained in job satisfaction when compared to all
other models. Among those with specialized welfare training, the model accounted for
more than half of the variance explained in job satisfaction. Among those with no
specialized child welfare training, greater work-family conflict predicted greater levels of
emotional exhaustion and depersonalization. This finding suggests that those who do not
have specialized child welfare training are at greater risk of succumbing to strains due to
work-family conflict and subsequently experience greater burnout. Among those with
specialized child welfare training, role ambiguity led to greater levels of
depersonalization. This finding suggests that specially trained workers facing ambiguous
work roles might disengage to cope with the ambiguity and develop feelings of
depersonalization.
The relationship between emotional exhaustion and depersonalization was
significant and positive in all models tested. Among those with no specialized child
welfare training the relationship between emotional exhaustion and depersonalization
was stronger than among those with specialized training. This finding suggests that those
with no specialized child welfare training are at greater risk of developing emotional
exhaustion and depersonalization. When the influence of job position on job satisfaction
was examined, it was found that being a front-line worker with specialized child welfare
96
training led to lower rates of satisfaction. This finding suggests that specially trained
child welfare workers may be more satisfied in supervisory or management positions than
working in direct service provision.
When compared across models among those with lower resources, work-family
conflict at baseline predicted greater levels of emotional exhaustion at wave 2. Emotional
exhaustion was positively related to depersonalization across all models. Higher levels of
emotional exhaustion at wave 2 predicted lower levels of job satisfaction in wave 3
across all models while depersonalization did not, suggesting that there is a differential
impact of the burnout dimensions on affective well-being (e.g. job satisfaction).
Implications
Findings from this study point to several avenues of future research on job
burnout and affective well-being. Results from this study call attention to the differential
im pa c t of job burnout’ s d im e nsion s on j ob sa ti sfa c ti on . This finding highlights the
multidimensionality of burnout (Maslach, 1998), which cannot be accurately captured in
composite measures. Researchers conducting job burnout and worker well-being studies
should be cautious when using composite burnout measures as they might suppress
important interrelationships from emerging. This would also further our understanding of
the direction and causality between the burnout dimensions, which is a matter that
continues to present controversial conclusions (Maslach, Schaufeli, & Leiter, 2001).
F uture studi e s shoul d c o nti nue to ex plore the r e la ti onshi p be twe e n job bur nout’s
dimensions and various forms of affective well-being. The benefits of this line of inquiry
are two fold. First, continued exploration of the diffe re nti a l out c omes o f job burn out’s
97
dimensions on worker well-being will aide in clarifying what the consequences of the
burnout dimensions are, given that they appear to be distinct. Second, this will help
expand our knowledge of the types of affective well-being that are vulnerable to job
burnout. Findings from this study suggest that workplace experiences such as the level of
support or training in the workplace influence burnout, which subsequently influences
worker well-being. Though this study takes workplace experiences into consideration, it
does not take into account the overall organizational context. Organizational variables
such as organizational leadership and organizational culture may potentially influence
burnout development and worker well-being and should be examined in future job
burnout studies.
Several implications for social work administration and management practice can
be drawn based on results from this study. When working towards the prevention of
burnout development, a job demand that can be targeted is work-family conflict. Findings
from this study suggest that conflict between work and family responsibilities can cause
emotional exhaustion to begin to form. The implementation of non-traditional work
structures that allow for greater flexibility can be used to help reduce the risk of workers
experiencing conflict between the demands of their personal and professional lives. Some
effective flexible workplace practices include flexible work hours (Baltes, Briggs, Huff,
Wright, & Neuman, 1999; Halpern, 2005), compressed work schedules (Baltes, et al.,
1999), and working remotely (Hunton & Norman, 2010). Furthermore, managers and
administrators crafting workplace interventions that target a reduction of burnout should
be focusing their efforts and protecting workers from emotional depletion. This may
98
include workforce management interventions that protect workers ’ emotional resources
and interventions that will provide workers with added resources that may facilitate the
process of fulfilling their work responsibilities.
Study Limitations
Though this study makes several contributions to the literature on job burnout and
affective well-being in human services, its limitation are worthy of note. In using an
availability sample of workers, there is a risk of potentially having a biased sample.
Participants who either voluntarily joined the study or who were in attendance at
voluntary training sessions during the period of recruitment, may inherently be more
engaged workers. Workers who are burned out or severely stressed might be less inclined
to participate in a voluntary study. Furthermore, the study sample was drawn from a
public child welfare organization in a large urban city. Child protection work within an
organization located in a large metropolis can significantly differ from child protection
work in rural or suburban areas. It is possible that work stressors within organizations in
urban areas might be different from stressors in rural child protection organizations, thus
limiting the generalizability of the study findings to large urban-based child protection
a ge nc ies. Th e stud y ’ s long it udinal de si g n is o ne of it s c e ntra l st re n g ths g ive n that it facilitates testing the temporal order of the hypothesized relationships. Nevertheless, the
short duration of the study limits any inference that can be made about the long-term
effects of burnout on affective well-being.
99
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112
Table 3.
Demographic Characteristics of Study Sample
N (%) M S.D.
Age 37 12
Sex
Male 59 (16.3%)
Female 301 (83.4%)
Race/Ethnicity
Caucasian 111 (30.7%)
Latino(a)/Hispanic 108 (29.9%)
African
American/Black
79 (21.9%)
Asian/Pacific Islander 44 (12.2%)
Other 15 (4.2%)
Tenure
6.16 6.73
Education
BA/BSW 124 (34.3%)
MA/MS/MFT 73 (20.2%)
MSW 155 (42.9)
PhD 3 (.8)
Other 4 (1.1%)
Specialized Public Child Welfare Training
Yes 120 (33 %)
No 235 (65%)
Note. Eight respondents did not indicate if they had specialized
public child welfare training.
113
Table 4
Study 2 Correlation Matrix
Mean
S.D.
Scale
Reliability 1. 2.
3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
1. Age 37 12 N/A 1
2. Race/Ethnicity N/A N/A N/A -.32
**
1
3. Tenure 6.16 6.73 N/A .71
**
-.18
**
1
4. Position N/A N/A N/A -.43
**
.30
**
-.65
**
1
5. Role Conflict 30.45 8.51 .85 .17
**
-.10 .15
**
-.08 1
6. Role Ambiguity 14.11 5.06 .83 -.19
**
-.01 -.18
**
.07 .15
**
1
7. Work-family
Conflict
9.61 3.92 .76 .02 .08
.06
.03 .25
**
.14
**
1
8. Organizational
Support
24.83 8.90 .86 -.26
**
.14
**
-.32
**
.15
**
-.39
**
-.16
**
-.19
**
1
9. Supervisory
Support
37.61 8.43 .90 .06 -.03
-.13
*
.08 -.23
**
-.20
**
-.16
**
.24
**
1
10. Specialized
Training
N/A N/A N/A -.43
**
.19
*
-.36
**
.17 -.07 .13 -.01 .03 .07 1
11. Emotional
Exhaustion
29.73 11.03 .92 -.15
*
-.01
-.17
*
.03 .17
*
.17
*
.21
**
-.10 -.04 .05 1
12. Depersonalization 10.55 4.63 .81 -.17
*
-.05 -.15* .11 .02 .12 .01 -.12 .08 .10 .53
**
1
13. Job Satisfaction 15.43 5.37 .90 .05 .13 .11 .10 -.08 -.19
*
-.11 .20
*
.16 -.12 -.45
**
-.23
*
** p< 0.01 level (2-tailed). * p< 0.05 level (2-tailed).
114
Table 5.
Study 2 Baseline Model Goodness-of-fit
Statistics
Goodness-of-fit Statistics
χ
2
13.45
Degree of freedom (df) 8
χ
2
p-value 0.09
Comparative Fit Index (CFI) 0.99
Normed Fit Index (NFI) 0.98
Root mean square error of approximation
(RMSEA)
0.04
Akaike information criterion
127.46
(AIC)
Variance Explained (r
2
)
Job satisfaction 23.70%
115
Table 6.
Study 2 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Organizational Support
Constrained
Model
Unconstrained
Model
Goodness-of-fit Statistics
χ
2
27.4 11.07
Degree of freedom (df) 32 16
χ
2
p-value .70 .81
Comparative Fit Index (CFI) 1.00 1.00
Normed Fit Index (NFI) .96 0.98
Root mean square error of
approximation (RMSEA) 0 0
Akaike information criterion
(AIC) 223.36 239.01
Variance Explained (r
2
)
Job satisfaction 29%
L=17%, H=42%
Note . “ L ” d e notes low so c ial support gr oup a nd “ H” de notes hi g h soc ial su pport g roup.
116
Table 7.
Study 2 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Supervisory Support
Constrained Model
Multi-group
Analysis
Goodness-of-fit Statistics
χ
2
29.16 14.41
Degree of freedom (df) 32 16
χ
2
p-value .61 .57
Comparative Fit Index (CFI) 1.00 1.00
Normed Fit Index (NFI) .96 .98
Root mean square error of
approximation (RMSEA) 0 0
Akaike information criterion
(AIC) 225.17 242.41
Variance Explained (r
2
)
Job satisfaction 27% L=34%, H=25%
Note . “ L ” d e notes low so c ial support gr oup a nd “ H” de notes hi g h soc ial
support group.
117
Table 8.
Study 2 Goodness-of-fit Statistics for Constrained and Unconstrained
Models By Specialized Child Welfare Training
Constrained
Model
Unconstrained
Model
Goodness-of-fit Statistics
χ
2
41.20 20.01
Degree of freedom (df) 32 16
χ
2
p-value .13 .22
Comparative Fit Index (CFI) .98 .99
Normed Fit Index (NFI) .94 .97
Root mean square error of
approximation (RMSEA) .03 .03
Akaike information criterion
(AIC) 273.20 248.07
Variance Explained (r
2
)
Job satisfaction 35%
Specialized CW
training=57%,
No Specialized
CW training=20%
,
118
Table 9.
Study 2 Path Coefficients of Full Baseline Model
b S.E. β
RC -> EE 0.14 0.1 0.11
RA -> EE 0.31 0.2 .14
*
WFC -> EE 0.04 0.2 .19
**
RC -> DP -0.04 0 -0.07
RA -> DP 0.04 0.1 0.04
WFC -> DP -0.1 0.1 -0.12
EE -> DP 0.24 0 .57
**
Age -> JS -0.01 0.1 -0.01
Race/Ethnicity -> JS 1.52 1 0.13
Tenure -> JS 0.01 0 0.14
Position -> JS 1.27 1.5 0.09
RC -> JS 0.04 0.1 0.07
RA -> JS -0.1 0.1 -0.09
WFC -> JS -0.04 0.1 -0.03
EE -> JS -0.22 0.1 -.45
**
DP -> JS 0.05 0.1 0.04
119
Table 10.
Study 2 Path Coefficients for Multi-Group Path Model of Work Place Demands, Job Burnout, and Job
Satisfaction for Low and High Organizational Support Groups
Constrained
Model
Unconstrained Model
Low Organizational
Support
High Organizational
Support
b S.E. β b S.E. β b S.E. β Critical
Ratio
RC -> EE
.19 .11
.13 .30 .13 .21
*
.18 .17 .13 .54
RA -> EE
.22 .16
.09 -.14 .21 -.07 .83 .25 .36
**
-3.00
WFC -> EE
.62 .21
.20
**
.84 .25 .31
**
.19 .36 .06 1.51
RC -> DP
-.07 .04
-.12 -.04 .05 -.07 -.10 .06 -.18 .76
RA -> DP
.01 .06
.01 .02 .08 .02 -.03 .09 -.03 .37
WFC -> DP
-.14 .08
-.12 -.15 .10 -.13 -.09 .12 -.08 -.32
EE -> DP
.23 .03
.62
**
.23 .04 .56
**
.24 .04 .61
**
-.11
Age -> JS
.03 .05
.05 .02 .08 .05 .03 .07 .06 -.07
Race/Ethnicity -> JS
2.14 .97
.19
*
1.16 1.29 .11 3.03 1.45 .25
*
-.96
Tenure -> JS
.01 .01
.08 .01 .01 .07 .01 .02 .16 -.43
Position -> JS
1.22 1.46
.08 1.04 1.76 .09 2.32 2.50 .15 -.41
RC -> JS
.03 .06
.04 .11 .08 .17 -.04 .09 -.06 1.29
RA -> JS
-.09 .09
-.09 -.13 .12 -.13 -.03 .14 -.03 -.53
WFC -> JS
-.04 .12
-.03 -.12 .16 -.09 .03 .18 .02 -.61
EE -> JS
-.22 .05
-.50
**
-.18 .07 -.37
*
-.27 .07 -.56
**
.91
DP -> JS
.04 .12
.04 .05 .16 .05 .05 .18 .04 .04
120
Table 11.
Study 2 Path Coefficients for Multi-Group Path Model of Work Place Demands, Job Burnout, and Job Satisfaction for Low
and High Supervisory Support Groups
Constrained
Model
Unconstrained Model
Low Supervisory
Support
High Supervisory
Support
Critical
Ratio
b S.E. β b S.E. β b S.E. β
RC -> EE .17 .10 .13
.05 .15 .04 .20 .15 .16
-.71
RA -> EE .27 .17 .11
.21 .21 .10 .35 .27 .15
-.43
WFC -> EE .57 .22 .21*
.96 .31 .32
**
.27 .30 .10
1.59
RC -> DP -.05 .04 -.10
-.09 .05 -.15 -.02 .05 -.04
-.95
RA -> DP .04 .06 .04
-.04 .08 -.04 .14 .09 .16
-1.52
WFC -> DP -.13 .08 -.12
-.25 .12 -.19
*
-.06 .10 -.05
-1.21
EE -> DP .24 .03 .59
**
.28 .04 .65
**
.19 .04 .50
**
1.69
Age -> JS .01 .05 .02 -.06 .07 -.13 .03 .07 .07 -.87
Race/Ethnicity -> JS 1.67 .95 .15 2.05 1.30 .18 1.21 1.37 .11 .44
Tenure -> JS .01 .01 .09 .02 .01 .22 .01 .01 .12 .38
Position -> JS .82 1.42 0.06
.62 1.84 .05 1.78 2.18 .14
-.41
RC -> JS .03 .06 .04
-.08 .08 -.12 .07 .08 .12
-1.32
RA -> JS -.15 0.09 -0.13
-.23 .11 -.23
*
-.03 .15 -.03
-1.09
WFC -> JS -.07 .11 -.06
.09 .18 .07 -.13 .15 -.11
.98
EE -> JS -.23 .05 -.47
**
-.22 .07 -.46
**
-.22 .07 -.48
**
.03
DP -> JS .07 .12 .06
.05 .16 .04 .09 .18 .08
-.19
121
Table 12.
Study 2 Path Coefficients for Multi-Group Path Model of Work Place Demands, Job Burnout, and Job Satisfaction among
Those With and Without Specialized Child Welfare Training
Constrained
Model
Unconstrained Model
Has Specialized Child
Welfare Training
Has No Specialized
Child Welfare Training
Critical
Ratio
b S.E. β b S.E. β b S.E. β
RC -> EE
.16 .10 .12 .03 .16 .03 .23 .13 .18
-.97
RA -> EE
.24 .16 .12 .16 .27 .07 .22 .20 .10
-.15
WFC -> EE
.56 .21 .21
**
.15 .35 .05 .71 .26 .26
**
-1.29
RC -> DP
-.03 .04 -.05 -.05 .06 -.10 -.02 .04 -.03
-.46
RA -> DP
.02 .06 .03 .24 .11 .24
*
-.04 .07 -.05
2.20*
WFC -> DP
-.17 .08 -.16
*
-.12 .14 -.09 -.21 .09 -.18
*
.52
EE -> DP
.25 .03 .63
**
.17 .05 .40
**
.29 .03 .71
**
-2.04*
Age -> JS
-.02 .06 -.05 -.08 .12 -.10 -.03 .06 -.07
-.39
Race/Ethnicity -> JS
1.86 .93 .16
*
3.16 1.33 .26
*
.93 1.23 .08
1.23
Tenure -> JS .01 .01 .08 -.03 .02 -.23 .01 .01 .18 -1.65
Position -> JS
.27 1.47 .02 -6.16 2.55 -.32
*
2.04 1.72 .16
-2.67*
RC -> JS
.06 .05 .09 .15 .07 .25
*
.01 .07 -.01
1.48
RA -> JS
-.08 .09 -.08 .12 .13 .10 -.14 .11 -.14
1.50
WFC -> JS
.04 .11 .03 .14 .16 .10 -.05 .15 -.04
.84
EE -> JS
-.26 .05 -.52
**
-.31 .06 -.64
**
-.18 .07 -.38
**
-1.40
DP -> JS
.11 .11 .09 .01 .15 -.01 .07 .17 .06
-.33
122
Figure 4.
Study 2 Baseline Model of Job Demands, Burnout, and Job Satisfaction
.04
-.45
**
-.12
.04
-.07
.19**
-.09
.14*
.11
.07
.09
.14
.13
- .01
Role
Ambiguity
Emotional
Exhaustion
Job
Satisfaction
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
.57
**
Depersona-
lization
-.03
123
Model fit statistics: Χ
2
= 13.45, df= 8, p=.09; CFI= .99; NFI= .98; RMSEA = .043; AIC=
127.458. The R
2
values for the endogenous variables were as follows: emotional
exhaustion r
2
= 9.2%, depersonalization r
2
= 30.8%, job satisfaction r
2
=23.7%.
124
Figure 5.
Study 2 Multi-group Model of High and Low Organizational Support, Job Demands,
Burnout and Job Satisfaction
Note. Bolded coefficients correspond to the high organizational support group and
italicized coefficients correspond to the low organizational support group.
.56
**
/.61
**
.05/.04
-.37*/-.56
**
-.13/-.08
.02/-.03
-.07/ -.18
.31
**
/.06
-.13/-.03
-.07/.36
**
.21
*
/.13
.17/-.06
.09/.15
.07/.16
.11/.25
*
.05/.06
Role
Ambiguity
Emotional
Exhaustion
Job
Satisfaction
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
Depersona-
lization
-.09/ .02
125
* p≤ .05, **p≤ .01. M ode l fit statis ti c s: Χ
2
= 11.07, df= 16, p=.81; CFI= 1.00; NFI= .98;
RMSEA = .00; AIC= 239.01. Low organizational support group: job satisfaction r
2
= .17.
High organizational support group: job satisfaction r
2
= .42.
126
Figure 6.
Study 2 Multi-group Model of High and Low Supervisory Support, Job Demands,
Burnout, and Job Satisfaction
Note. Bolded coefficients correspond to the high supervisory support group and italicized
c oe ff i c ients c orr e spond t o the low supe rvisor y su pport g roup. * p≤ .05, ** p≤ .01. Model
.65
**
/.50
**
.04/.08
-.46
**
/-.48
**
-.19*/-.05
-.04/.16
- .15/ -.04
.32
**
/.10
-.23
*
/-.03
.10/.15
.04/.16
-.12/.12
.05/.14
.22/.12
.18/.11
-.13/.07
Role
Ambiguity
Emotional
Exhaustion
Job
Satisfaction
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
Depersona-
lization
.07/-.11
127
fit statistics: Χ
2
= 14.41, df= 16, p=.57; CFI= 1.00; NFI= .98; RMSEA = .0; AIC=
242.41. Low organizational support group: job satisfaction r
2
= .34. High supervisory
support group: job satisfaction r
2
= .25.
128
Figure 7.
Study 2 Multiple Sample Model of Specialized Child Welfare Training, Job Demands,
Burnout, and Job Satisfaction
.40
**
/.71
**
- .01/.06
-.64
**
/-.38
**
-.09/-.18*
.24
**
/-.05
-.10/ -.03
.05/.26
**
.10/-.14
.07/.10
.03/.18
.25
*
/-.01
-.32*/.16
-.23/.18
.26
*
/.08
-.10/-.07
Role
Ambiguity
Emotional
Exhaustion
Job
Satisfaction
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
Depersona-
lization
.10/ - .04
129
Note. Bolded coefficients correspond to not having specialized child welfare training and
italicized coefficients correspond to having specialized welfare training . * p ≤ .05, **p≤
.01. Model fit statistics: Χ
2
= 20.01, df= 16, p=.22; CFI= .99; NFI= .97; RMSEA = .03;
AIC= 248.07. Has specialized CW training: job satisfaction r
2
= .57. Does not have
specialized CW training: job satisfaction r
2
= .20.
130
CHAPTER FOUR (STUDY 3):
BURNOUT AND PSYCHOLOGICAL WELL-BEING: A LONGITUDINAL STUDY
Introduction
An interest in the well-being of workers has propelled much of the job burnout
research within the human services sector. A desire to describe the once engaged worker
who has become emotionally depleted and detached led to some of the first systematic
investi g a ti ons of w ha t w e now r e fe r to a s “ job bur nout” ( F r e ude nb e r g e r, 19 74). J ob
burnout is defined as emotional exhaustion, callousness, and a sense of reduced efficacy
in the workplace (Maslach & Jackson, 1981). Despite a lack of quantifiable benchmarks
for job burnout rates between occupations, there is evidence that suggests that human
service workers are particularly susceptible to job burnout (Johnson, Cooper, Cartwright,
Donald, Taylor & Millet, 2005; Lloyd, King, & Chenoweth, 2002). The nature of human
services is thought to contribute to the greater risk of burnout among this worker
population. Human service work often requires intense interpersonal interactions with
individuals who are in distress or crisis. The continued exposure that human service
workers experience when working with individuals facing severe difficulty can become
stressful and emotionally exhausting (Maslach, 2003).
Despite the extensive study of job burnout among human service workers, a
limited number of studies have examined the influence of job burnout on worker well-
being. The focus of job burnout research within the human service sector has largely been
on examining antecedents of job burnout (Font, 2012; Hamama, 2012; Kim, 2011;
Jourdain & Chênevert, 2010); Lizano & Mor Barak, 2012). Though understanding the
131
predictors of burnout is critical, it is also important to have a better understanding of the
consequences of burnout. The limited research in the human services sector on burnout
consequences has focused primarily on burnout as a predictor of intention to leave (Kim,
& Stoner, 2008; Mor Barak, Levin, Nissly, & Lane, 2006). Burnout is considered to pose
a threat to the affective, psychological and physical well-being of workers (Leiter &
Maslach, 2001). Though burnout is suggested to lead to reduced well-being a number of
gaps in knowledge remain. This study contributes to a greater understanding of the
relationship between job burnout and psychological well-being in several ways. The first,
seeks to disentangle the differential impact of the job burnout dimensions, emotional
exhaustion and depersonalization, and the psychological well-being of human service
workers. Furthermore, this study tests a theory-based model of hypothesized
interrelationships between job demands and resources in the workplace as they lead to the
development of job burnout, and the consequential impact of burnout on psychological
well-being (Figure 3).
Literature Review
Job Burnout in the Human Service Sector
Despite the lack of data that can ascertain the levels of burnout among human
service workers, there is evidence that suggests that individuals in human service
occupations are at higher risk of stress and burnout. In a cross-occupation comparison
among 26 fields of employment, social service work was among the professions with the
lowest health, psychological well-being and job satisfaction ratings (Johnson, Cooper,
Cartwright, Donald, Taylor & Millet, 2005).
132
In their review of research studies examining social worker stress and burnout, Lloyd,
King, and Chenoweth (2002) found that the quantity and quality of research on burnout
in social work is weak. Despite the lack of rigorous research noted by the researchers on
stress and burnout research in social work, the research that has been conducted suggests
that social workers experience high levels of stress and burnout (Lloyd, King, &
Chenoweth, 2002). In a similar review conducted focusing on psychiatrists, Fothergill,
Edwards, and Burnard (2004) conclude based on the 65 international studies reviewed
that psychiatrists experience notably high levels of stress. Mental health workers also
appear to experience high levels of stress. In their review of mental health workers in the
United States, Paris and Hoge (2009) found high levels of burnout among the study
samples, and this was particularly true in the emotional exhaustion dimension of burnout.
Burnout has been linked to reduced worker well-being. In their longitudinal study
on social workers, Kim, Ji, and Kao (2011) found that greater levels of burnout at the
beginning of the study resulted in greater physical health complaints (e.g. sleep
disturbance, headaches, respiratory and gastrointestinal infections) a year later. Johnson
e t al.’ s (2005) stud y findi ng s su gg e st t ha t hi g he r l e ve ls of job burnout l e a d t o si c kne ss -
related absence over time. Job burnout can also lead to reduced psychological and
affective well-being. In their study of home caregivers of patients with dementia, Takai
and colleagues (2008) found that higher levels of job burnout resulted in increased levels
of depressive symptoms and reduced levels of quality of life. In their study of social
workers, Hombrados-Mendieta and Cosno-Rivas (2011) found a negative relationship
between burnout and both job and life satisfaction. In a similar study using a social
133
worker sample, Pasupuleti, Allen, Lambert, & Cluse-Tolar, (2009) found that stress in the
workplace resulted in reduced levels of life satisfaction.
Job burnout
Job burnout refers to the feelings of emotional exhaustion, callousness, and
reduced perception of efficacy that develop from chronic exposure to job stress (Maslach
& Jackson, 1981). Job burnout is considered an occupational hazard that can negatively
impact the affective (Ha, King, & Naeger, 2011; Lee, Lim, Yang, & Lee, 2011),
psychological (Ahola et al., 2005; Armon, Melamed, Toker, Berliner, & Shapira, 2013),
physical (Honkonen et al., 2006; Toppinen-Tanner, Ojajärvi, Väänänen, Kalimo, &
Jäppinen, 2005), and behavioral well-being of workers afflicted with job burnout. Job
burnout is defined as a three-dimensional phenomenon including emotional exhaustion,
depersonalization, and reduced levels of perceived self-efficacy (Maslach et. al., 1981;
Jackson & Schwab, 1986). The three-dimensions of burnout are thought to be related
reactions to workplace stressors (Maslach et al., 1981; Jackson & Schwab, 1986). The
first dimension, emotional exhaustion, refers to feelings of being emotionally depleted
due to excessive psychological and emotional demands elicited by workplace stressors.
Depersonalization, the second dimension of job burnout refers to a callousness and
distance from co-workers and clients that develops due to feelings of emotional
exhaustion. Some manifestations of depersonalization include objectifying clients by
referring to them by a case number and not a name. Depersonalization can also be
exhibited as increased cynicism in workers who in the past demonstrated genuine concern
for client well-being. The third dimension of job burnout is referred to as personal
134
accomplishment, and it includes feelings of reduced efficacy. A burned out worker may
become demotivated due to the chronic stress and emotional exhaustion and may as a
result feel that regardless of the effort put forward, efficacy in the workplace cannot be
reached.
Job Burnout and Psychological Well-being
Well-being in the workplace has caught the attention of researchers and
practitioners because of the relationships that have been found between work experiences
and worker well-being (Danna & Griffin, 1999; Sparks, Faragher, & Cooper, 2001). Job
burnout is a potential threat to psychological well-being of workers. Workplace
experiences for individuals can be critical in shaping their daily lives. Work is an
important source of psychosocial stimuli that can influence workers through affect,
perception, and work occurrences (Levi, 1994). Research and theory focused on
occupational well-being are contextualized within the broader literature on subjective
well-being. Subjective well-being is defined as a broad construct that includes an
indi vidual’ s ps y c holo g ic a l and ph y siol og ic a l re sp onse s to and sa ti sfa c ti on with a
multitude of domains including but not limited to work, family, finances, and health
(Diener, Suh, Lucas, & Smith, 1999). Psychological well-being within the occupational
realm is limited to mental health matters in relation to workplace experiences (Warr &
Wall, 1975).
Theoretical framework of burnout development: Job Demands-Resources (JD-R) model
This dissertation uses the Job Demands-Resources (JD-R) model as a guiding
framework to explain the development of job burnout among human service workers.
135
The JDR-model assumes that working conditions within any occupational field can be
considered a demand or resource depending on the occupational context. Any physical,
social, or psychological work responsibilities that require sustained effort can be
considered a demand. Job resources include any physical, social or psychological feature
of work that either serve a functional role in meeting work responsibilities, reduce the
costs of work demands on the worker, and/or facilitate individual growth and
development (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). According to the
JD-R model, resources can originate from a number of sources within the work
organization (Bakker & Demerouti, 2007). Workers can gain resources from the overall
organization through compensation and access to assets that facilitate meeting their work
responsibilities (e.g. access to work tools, training). Resources in the workplace can also
stem from relationships at work. Co-workers and supervisors within the organization can
serve as a source of support including emotional support and instrumental support. Based
on the JD-R model, the interrelationships between job demands and resources are not
static. According to the assumptions of the JD-R model the greatest risk of burnout
occurs when demands are high and resources are low (Demerouti, Bakker, Nachreiner, &
Schaufeli, 2001). High work demands are thought to lead to strain only when there are
not sufficient resources to meet those demands. High work demands become strenuous
and lead to feelings of exhaustion. A lack of resources in the workplace precludes the
worker from having the ability to meet job demands and leads to withdrawal behavior
that manifests in depersonalization (cynicism).
136
Person-environment (P-E) fit theory can be used to explain the process by which a
lack of balance between work demands and abilities leads to stress (French & Caplan,
1972; Caplan, 1987) and as a result job burnout. The P-E fit theory of stress development
assumes that stress arises as a result of incongruence between the person and the work
environment (Edwards, Caplan, & Van Harrison, 1998). Incongruence between
environmental demands, or work demands, while having few resources to meet those
demands, can lead to experiences of strain and stress. The process by which resources
influence the development of burnout can be explained using conservation of resources
theory (COR; Wright & Hobfoll, 2004). COR posits that there is an inherent motivation
within individuals to obtain and retain resources that they deem valuable (Hobfoll &
Freedy, 1993). According to the postulates of COR, if an individual cannot obtain
resources, faces the risk of losing resources or loses valued resources, he or she can
subsequently experience feelings of psychological distress (Hobfoll et al., 1993).
Job Demands and Resources in the Human Services Sector
As previously mentioned, the JD-R model proposes that the factors deemed as demands
or resources in the workplace are contingent upon the work context. Within this study,
two demands central to human service work are examined. The first demand, job stress,
is defined as experiences of role ambiguity and role conflict at work. The development of
job stress can be explained using role theory. Role within the context of the workplace
includes implicit and explicit duties and responsibilities expected of an individual in a
certain job position. When any implicit or explicit job expectations are either unclear or
discrepant they can lead to experiences of role ambiguity or role conflict in the former
137
and latter cases (Kahn, Wolfe, Quinn, Snoek, & Rosenthal, 1964). Long term exposure to
stress at work can develop into job burnout. Job burnout theory proposes that chronic
exposure to stressors in the workplace begin to deplete the psychological and emotional
resources of the worker leading to feelings of emotional exhaustion, and a distancing
from clients and co-workers as a method of coping (Maslach, 1998; Maslach, Schaufeli,
& Leiter, 2001). Empirical evidence supports the theoretical assumption that a positive
association exists between job stress and burnout (Cordes & Dougherty, 1993; Hogan,
Jenkins, Jiang, & Lambert, 2009; Lee & Ashforth, 1996; Tunc & Kutanis, 2009).
Work-family conflict is the second demand that is examined in this study. Work-
family conflict is defined as an incompatibility experienced when the demands of work
are in conflict with familial or personal responsibilities (Greenhaus & Beutell, 1985).
When workers are exposed continually to contradictory demands between their personal
and work life, feelings of strain and stress can ensue (Allen, Herst, Bruck, & Sutton,
2000; Amstad, Meier, Fasel, Elfering, & Semmer, 2011). As a demand, greater levels of
work-family conflict can lead to increased risk of job burnout developing (Bakker,
Demerouti, & Verbeke, 2004; Maslach, 2005; Schaufeli, Bakker & Van Rhenen, 2009).
Empirical research within the general workforce literature has found that work-family
conflict does predict burnout (Lambert, Hogan, & Altheimer, 2010; Peeters,
Montgomery, Bakker, & Schaufeli, 2005) and findings from comparable studies using
human service samples have been similar (Lizano & Mor Barak, 2012; Nissly, Mor
Barak, & Levin, 2005; Rupert, Stevanovic, & Hunley, 2009).
138
A widely studied resource within human service workforce research is social
support. Instrumental and emotional support in the workplace can play a critical role in
shaping workplace experiences and in aiding workers with the process of coping with
workplace demands (Lee & Ashforth, 1996). Social support in the workplace has the
potential to mitigate the effects that job demands have on the development of job
burnout. The impact of social support on well-being stems from the social support
framework that posits a link between social relationships and well-being (House,
Umberson, Landis, 1988). Empirical evidence suggests that socially supportive work
environments are related to lower levels of job burnout (Halbesleben, 2006; Maslach &
Leiter, 2008).
This study draws on theory and previous empirical findings to put forward the
following hypotheses to be tested:
Hypothesis 1): Job demands (e.g. role conflict, role ambiguity, and
work-family conflict) at wave 1 are positively and significantly related to
emotional exhaustion and depersonalization at wave 2.
Hypothesis 2.): The relationships between job demands at wave 1, burnout at
wave 2 (e.g. emotional exhaustion and depersonalization), and job satisfaction at
Time 3 will be moderated by job resources (e.g. supervisory and organizational
support).
Hypothesis 3.): Emotional exhaustion is significantly and positively associated
with depersonalization.
139
Hypothesis 4a.): Emotional exhaustion at wave 2 is negatively and significantly
related to psychological well-being at wave 3. Hypothesis 4b.) Depersonalization
at wave 2 is negatively and significantly related to psychological well-being at
wave 3.
Hypothesis 4a.): Emotional exhaustion is negatively and significantly related to
psychological well-being. Hypothesis 4b.) Depersonalization is negatively and
significantly related to psychological well-being.
Method
Study Procedures and Sampling
Data for this three-wave longitudinal study were drawn from an availability
sample of 361, workers in an urban public child welfare department in Southern
California that employs approximately 5,000 workers and oversees the welfare of an
estimated 12,000 children and youth. Data were collected over a twelve-month period in
six-month intervals from July 2004 to September 2005. Participants were recruited during
their lunch hour while attending one of 30 required or voluntary training courses offered
at a university-affiliated child welfare-training center. Participants were given
information about the purpose and voluntary nature of the study. Interested participants
enrolled in the study after completing an informed consent process with a trained
research assistant. All participants were required to sign a consent form. A free lunch was
offered as a token of appreciation for participating in the study. Participants completed
the questionnaire in a vacant training room.
Missing Data
140
Due to attrition in the study sample, several steps were taken to address missing
data prior to conducting analysis. Missing data within longitudinal studies is
commonplace (Schafer & Graham, 2002). Baseline data was obtained from all 363
respondents, 187 respondents provided data at wave 2, and 133 respondents provided
data at wave 3. In order to address missing data, a full information maximum likelihood
(FIML) estimation strategy was used during analysis. Full information maximum
likelihood estimation uses all available data to make inference and estimate parameters
using a likelihood function (Schafer et al., 2002). The use of FIML to estimate a model
with missing data is considered appropriate depending on the mechanism that led to the
missing data. Maximum likelihood estimation approaches are only appropriate for use in
situations where data are missing at completely at random (MCAR) or at random (MAR)
(Enders, & Bandalos, 2001; Schafer & Graham, 2002). Data are considered missing at
random if the data are not missing due to the values of the dependent variable of interest
(Schafer & Graham, 2002; Rubin, 1976Several logistic regression models were tested to
examine if the endogenous variables in the model, job burnout and psychological well-
being predicted missingness). Two dummy variables were created to capture missing
data at wave 2 and wave 3 with the following dummy coding: 0= no missing data, 1=
missing data. The first two logistic regression models tested the relationship between
burnout level at wave 1 and missing data at waves 2 and 3. A second logistic regression
model was conducted to test if level of burnout at Time 2 predicted missing data at Time
3. The same logistic regression modeling process used in burnout was used to test for the
presence of a significant relationship between psychological well-being and missingness.
141
None of the logistic regression models yielded any significant results. Additionally,
respondents with missing data were compared to those with no missing data based on
several demographic characteristics including: age, race/ethnicity, gender, educational
background, tenure and position in the organization. No statistically significant
differences were found in any of the demographic characteristics between those with and
those without missing data.
Analysis Strategy
A series of multi-group path analyses, a form of structural equation modeling
that simultaneously tests multivariate interrelationships of observed variables (Bollen,
2005) were performed using IBM SPSS AMOS 18. A multi-group approach applied to
structural equation modeling was used because it permits for invariance to be tested
between groups (Byrne, 2009) and as a result allows for the identification of model
differences between groups. Prior to analysis, study participants were separated into
“ low” a nd “ hig h ” g roups ba se d on their r e porte d le ve ls of or g a niz a ti ona l an d supe rvisor y support. A median split strategy was used to s e pa ra te the stud y sa mpl e int o “ low” a nd a “ hig h ” soc ial support g ro ups. This stra teg y wa s se lec ted ove r a mea n spl it ba se d on
previous application in similar studies testing the moderating effect of job resources in
the JDR model and because it provided a more even split between the two groups.
In preparation for between group comparisons, new variables were created to
separate those with low and high organizational and supervisory support. A new variable
dividing study participants into low and high organizational support groups was created.
The stud y s a mpl e wa s di ve d int o two g roups b a se d on the sa mpl e ’s me dian
142
organizational support score of 25. Based on the median split, 51.5% of the participant
scores ranged from 8 – 25 and were coded as being i n the “ low o r g a niz a ti ona l supp ort
g roup ” while those sc o ring 26 – 48 comprised 48.5% of the study sample and were coded
a s ha ving “hi g h or g a niz a ti ona l supp ort.” The follo wing dumm y c odin g sc h e me w a s
employed to distinguish high versus low organizational support groups: low= 0, high= 1.
As a result of the split, 173 respondents were categorized as having low and 163 were
categorized as high organizational support. Twenty-seven respondents had missing
organizational support data and were excluded from the organizational support path
model analysis. The same procedure was conducted to designate low and high supervisor
support g roups b a se d on the sa mpl e ’s me dian sup e rvisor y support sc a l e sc ore of 40 . As a result, 54.3% of participants scoring from 8 – 40 were c ode d a s h a vin g “ lo w supe rvisor y support g roup ” a nd thos e sc oring 41 – 48 comprised 45.7% of the study sample and were
c ode d a s ha vin g “ hig h su pe rvisor y support.” Dum m y c odin g w a s used to identif y the low
versus high supervisory support groups (low= 0, high= 1). After splitting the sample by
supervisory support level 176 respondents were in the low group and 148 were in the
high supervisor support group. Thirty nine respondents had missing supervisory support
data and were excluded from analysis.
In preparation for examining differences in workplace experiences of stress and
job burnout by level of social support, a baseline model that did not test for group
differences was analyzed. Though the baseline model cannot be compared statistically
because it is not nested within the other models due to the lack of social support variables
it was conducted for the purposes of having a conceptual baseline for comparison.
143
Following the analysis of a baseline model, a two-step model testing an unconstrained
and constrained model strategy was used for each form of social support.. This two-step
approach of comparing a fully constrained and an unconstrained model is the
recommended approach when conducting multi-group structural equation models (Byrne,
2009). First, a fully constrained model was analyzed as a global test of invariance in
covariance structures between the two groups. This approach requires that a path model
be analyzed simultaneously for the groups and that all paths are constrained to be equal to
each other. The first model was conducted as it is recommended practice based on the
Joreskog tradition in multi-group structural equation modeling (Byrne, 2004). A second
multi-group path model with no path constraints and a critical ratio of differences was
analyzed. The second approach allows for paths to vary between groups and tests if the
path parameters are statistically different between groups (Arbuckle, 200). The second
unconstrained model was analyzed because the global test for group invariance has been
found to lead to possible contradictory findings and is overly stringent as a test of group
differences (Byrne, 2004). As an alternative to testing only the overall model covariance
structure differences between groups, it is recommended to test each of the parameters in
the model (Byrne, 2004) which was accomplished here in step number two.
Measurement
Dependent Variable
Psychological Well-being. Psychological well-being is conceptually defined in the
present study as current mental health status and is measured using a shortened version of
the general health questionnaire (GHQ; Goldberg & Blackwell, 1970), a measure of
144
current psychiatric disturbance and disturbance severity. The GHQ-12 is a twelve item
version of the longer GHQ and one that has been found to yield comparable
measurements, is robust in measuring current psychiatric disturbance and has
successfully be used in various cultural and linguistic settings (Goldberg, Gater,
Sartorius, Ustun, Piccinelli, Gureje, & Rutter, 1997). Additionally, the measure has been
used in previous human service workforce studies and has been demonstrated to be a
valid and reliable measure of psychological well-being (Coffey, Dugdill, Tattersall, 2004;
Evans et al., 2006; Kinman & Grant, 2011; Mor Barak, Levin, Nissly, & Lane, 2006).
Items are rated on a 4-point scale with the following response options: 1= much worse
than usual, 2= worse than usual, 3= same as usual and 4= better than usual. A lower score
on the GHQ is indicative of psychological distress. GHQ-12 scale scores were drawn
from time 3 data. C ronba c h’s a lpha f o r the GH Q -12 measure in this study was .85.
Job Burnout. Job burnout is conceptually defined as feelings of emotional exhaustion
and depersonalization in the present study and measured using two of the three subscales
in the Maslach Burnout Inventory- Human Services Survey – (MBI-HSS; Maslach &
Jackson, 1981). The MBI-HSS – is comprised of a 22-item Likert scale that includes
three subscales each measuring the three aspects of burnout: emotional exhaustion (nine
items), depersonalization (five items), and personal accomplishment (eight items).
Subscale items pertaining to the personal accomplishment dimension of burnout were
excluded from the present study on conceptual and empirical grounds. Conceptually, it
has been proposed that personal accomplishment is more accurately conceptualized as a
personal characteristic rather than a symptom of burnout (Cordes & Dougherty, 1993)
145
and empirically previous study findings suggest that personal accomplishment is not as
strongly related to the emotional exhaustion and depersonalization (Lee & Ashforth,
1996; Schaufeli, Bakker, Hoogduin, Schaap, & Klader, 2001). Developed initially for
human service workers, the MBI has demonstrated to be a valid and reliable measure of
job burnout across, occupations, cultures, and languages (MBI; Maslach & Jackson,
1981; Poghosyan, Aiken, & Sloane, 2009; Worley, Vassar, Wheeler, & Barnes, 2008).
Emotional exhaustion and depersonalization scale scores were drawn from wave 2 data.
The emotional exhaustion scale items used in this study had a n ove r a ll C hronb a c h’s
reliability coefficient of .91 and the depersonalization scale items had a .81 reliability
coefficient.
Job stress. Job stress is operationally defined as experiences of role conflict and role
ambiguity in the work setting. Role conflict refers to inconsistent demands at work
(Rizzo, House, and Lirtzman, 1970). Role ambiguity, makes reference to a lack of
available information pertaining to the roles and responsibility in an organization (Rizzo,
House, and Lirtzman 1970). Role conflict and ambiguity were measured using Rizzo,
House, and Lirtzman,1970) role conflict and ambiguity scales. Eight role conflict and six
role ambiguity items were used to create a composite scale to measure job stress. Role
conflict and role ambiguity data were drawn from wave 1. Role ambiguity and role
conflict had a C hronb a c h’s a lpha c o e ff ici e nt of . 83 and .85, respectively.
Work-Family Conflict. Work-family conflict, conceptually defined as the interference
of work related roles and responsibilities on the family sphere, is measured using three
it e ms fr om B e a tt y ’s (199 6) w ork -family conflict scale. Scale items are rated on a 6-point
146
li ke rt w it h a re sponse of “ 1” c or re spondi n g to “str ong l y disa g r e e ” a nd a “ 6 ” c orr e spondi n g to “stron g l y a gre e ” a nd greater scale scores representing greater
experiences of work-family conflict. Work-family conflict scale scores were drawn from
wave 1. The work- fa mi l y sc a le to be use d h a s a C hronb a c h’s a lpha r e li ability value of
.75.
Organizational and Supervisory Support. Organizational and supervisory support were
both measured using eight-items developed by Eisenberger, Huntington, Hutchison, &
Sowa (1986). The perceived organizational and supervisory support scales have been
found to be valid and reliable measures of social support in the workplace (Eisenberger,
Fasolo, & Davis-LaMastro, 1990; Eder & Eisenberger, 2008). Items from both scales are
identica l wit h the e x c e pti on of the use of the wor d s “ supe rvisor ” a nd “ or ga niz a ti on” in
each respective scale. Item responses are on a 6-point Likert scale, with higher scale
scores signifying higher levels of perceived social support. Organizational and
supervisory support scale scores were drawn from wave 1 data. Organizational and
supervisory support had a reliability coefficient of .83 and .85, respectively.
Covariates. R e sponde nts ’ a g e , se x , e thni c it y /r a c e , orga niz a ti ona l t e nure a n d e duc a ti ona l
ba c k g round w e re d ra wn fr om par ti c ipants’ s e lf -reported demographic questionnaire item
responses. The variables sex, race/ethnicity, and position in the organization were dummy
c ode d in pre p a ra ti on fo r a na l y sis . Th e se x va ria bl e wa s dum m y c ode d a s “ 0” a nd “ 1 ” for males and females, respectively. Race/ethnicity was dummy coded by collapsing all those
who identified as African American, Latino/a, Asian, American Indian, Native Hawaiian
a nd Othe r into a “ non - C a uc a sian” c a te g o r y numer i c a ll y c ode d a s “ 1” . R e sp onde nts
147
identif y in g a s C a u c a sian we re c ode d a s “ 0” . R e sp onde nt pos it ion i n the organization was
c ode d a s “ 0 ” for m a na g e r s or supe rvisor s a nd “ 1” f or line -workers. All covariate data
were collected during wave 1 of the study.
Results
Descriptive Statistics and Correlations
Table 3 presents demographic characteristics of the study sample. The average
age for the sample was 37. A large proportion of study participants were women (83.4%).
The sample was approximately a third Caucasian (30.7%) and Latino(a)/Hispanic
(29.9%) with the third largest group being African American/Black (21.9%). Tenure
ranged from less than a year to 36 years in the organization with an average tenure of six
years. Approximately two-thirds of the sample reported having a graduate degree (e.g.
MSW, MFT, MA, PhD). A correlation matrix for the study variables of interest is
summarized and presented in Table 13.
Fit Statistics
A total of five path models were conducted to test the central study hypotheses.
The first model conducted was full sample path model that excluded any social support
variables. One constrained and one unconstrained model was tested for organizational
and supervisory support. Multiple model fit statistics were used to assess the adequacy of
model fit including a Chi- S qua re test ( χ
2
), normative fit index (NFI), comparative fit
index (CFI), and the Root Mean Square Error of Approximation (RMSEA). The
standards employed for assessing good model fit follow standard criterion used in SEM
148
and which include a non- sig nific a nt χ
2
value, a CFI and NFI greater than .90, and an
RMSEA equal to or less than .05 (Kline, 2010).
The ba se li ne model d e mons tra ted a g ood ove ra ll model f it χ 2 (8) = 14.30, p= .07;
CFI = .99, NFI= .98, RMSEA = .05, AIC= 128.30 (Table 14, Figure 8). The baseline
model with no social support variables was found to account for 21% of the variance in
psychological well-being. Constrained and unconstrained models were tested for
organizational and supervisory support. The constrained organizational support model
ha d g ood ov e r a ll fit, χ 2 ( 32)= 27.90, p= .68; CFI = 1.00, NFI= .96, RMSEA = .00, AIC=
223.87 (Table 15, Figure 9). The second non-constrained model of organizational support
a lso y ielde d a g ood f it , χ
2
(16)= 10.99, p= .81; CFI = 1.00, NFI= .98, RMSEA = 0, AIC=
238.98. The constrained organizational support model accounted for 27% of variance in
psychological well-being. The unconstrained organizational support model accounted for
20% and 30% of variance in psychological well-being for the low and high
organizational support groups, respectively. The constrained supervisory support path
model analysis produced a good fi t χ
2
(32)= 42.88, p= .09; CFI = .98, NFI= .94, RMSEA
= .03, AIC= 238.88 (Table 6, Figure 10). The unconstrained supervisory model also
y i e lded a g ood f it , χ
2
(16) = 14.76, p= .54; CFI = 1.00, NFI= .98, RMSEA = 0, AIC=
242.41. The constrained supervisor support model accounted for 20% of variance in
psychological well-being. The unconstrained model accounted for 22% and 48% of
variance in psychological well-being among those with low and high supervisory support,
respectively.
Path Coefficients
149
Baseline Model. The baseline model found no statistically significant impact of
demographic or work variables on psychological well-being (Table 17). Role conflict (b=
.14, β = .11, p≤. 05) a nd wor k -family conflict (b= .58, β = .20, p≤. 01) w e r e the onl y workplace demands that predicted emotional exhaustion at a statistically significant level.
Work-family conflict predicted depersonalization (b= - .15, β = - .13, p≤. 05 ). E m otional
exhaustion had a positive significant relationship with depersonalization (b = .24, β = .58,
p≤. 01). N one of the dir e c t paths fr om wor kpla c e de mands to ps y c holog i c a l we ll -being
were found to be statistically significant. Emotional exhaustion was the only significant
predictor of psychological well-being (b= - .21, β = - .45, p≤. 01).
Organizational Support Model
Constrained model. The constrained organizational support model path
coefficients are presented in Table 18 and pictorially depicted in Figure 9. No
demographic or work variables were found to have a statistically significant relationship
with psychological well-being. Work-family conflict was the only job demand that
significantly predicted emotional exhaustion (b = .67, β = .22, p≤. 01). N o job demands
were found to predict depersonalization. Emotional exhaustion was found to have a
statistically significant relationship with depersonalization (b= .24, β = .63, p≤. 01). N o
statistically significant direct relationship was found between job demands and
psychological well-being. Emotional exhaustion was the only burnout dimension that
predicted psychological well-being (b= - .20, β = - .52, p≤. 01).
Unconstrained model. The unconstrained organizational support model path
coefficients are presented in Table 18. When demographic variable paths were compared
150
between those with low and high organizational support it was found that all paths for
both groups were in the same direction. No demographic variables were found to be
predictors of psychological well-being in either group. Those who identified as non-
Caucasian had a higher rate of job satisfaction. The relationship between job demands
and emotional exhaustion differed by group. Role conflict (b= .31, β = .2 1, p≤. 05) a nd
work-family conflict (b= .90, β = .3 1, p≤. 01) w e r e sig nific a nt pr e dictor s of e mot ional
exhaustion among those with low organizational support. Role ambiguity was a predictor
of emotional exhaustion among those with high organizational support (b= .82, β = .36,
p≤. 01). N o job dema nds we re found to si g nific a nt l y pre di c t depe rsona li z a ti on in either group. Emotional exhaustion was found to be significantly related to depersonalization in
both the low (b= .23, β = .5 6, p≤. 01) a nd hig h ( b= .24, β = . 62, p≤. 01) supe rvisor y support groups. Neither job demands nor job burnout were found to be significant
predictors of psychological well-being. Among those with high organizational support,
no demands were found to have a direct relationship with psychological well-being.
Emotional exhaustion was found to predict psychological well-being among those with
high organizational support (b= -.26, β = - .54, p≤. 01).
Supervisory Support Model-
Constrained model. The constrained supervisory support model path coefficients
are presented in Table 19. None of demographic characteristic variables were found to
predict psychological well-being. Work-family conflict was the only job demand found to
predict emotional exhaustion (b = .63, β = .21, p≤. 01). N o job demands were found to be
predictors of depersonalization. Emotional exhaustion had a positive and significant
151
relationship with depersonalization (b= .24, β = .57, p≤. 01). Emoti ona l exha usti on wa s
found to be a significant predictor of psychological well-being (b= - .22, β = - .45, p≤. 01)
but depersonalization was not.
Unconstrained model. The unconstrained supervisor support model path
coefficients are presented in Table 19 and a pictorial depiction of the path model is
presented in Figure 10. No demographic characteristic variables were found to be
predictors of psychological well-being with the exception of job position. Among those
with low supervisory support, job position predicted psychological well-being (b = 3.97, β
= .31, p≤. 05). This sugg ests that line workers with low supervisory support report higher
psychological well-being. Work-family conflict predicted emotional exhaustion (b= 1.13,
β = .37, p≤. 01) a nd de p e rsona li z a ti on ( b= - .25, β = - .19, p≤. 05) a mon g th ose with l ow
supervisory support but not among those with high organizational support (b= .23, β = .09). Higher levels of emotional exhaustion were related to higher levels of
depersonalization in both low (b= .28, β = .66, p≤. 01) a nd hi g h ( b= .19, β = .49, p≤. 01)
supervisory support groups. Role conflict and role ambiguity did not predict
psychological well-being in either group. Neither job demands or job burnout predicted
psychological well-being among those with low supervisory support. Among those with
high supervisory support, higher levels of work-family conflict (b= - .34, β = - .26, p≤. 01)
and emotional exhaustion (b= - .31, β = - .62, p≤. 0 1) w e r e foun d to l e a d to lowe r le ve ls of
psychological well-being. The high support group was also found to have a positive
relationship between depersonalization and psychological well-being (b = . 45, β = .34, p≤.
01).
152
Discussion
There has been limited examination of the impact of burnout on the
psychological well-being of workers in human service workforce studies. This study was
carried out with the purpose of gaining a better understanding of the complex
relationships that exist between job demands and resources, job burnout and
psychological well-being over time. Overall, findings from this study suggest that
demands at baseline have a differential impact on the burnout dimensions six months
later. While the burnout dimensions at wave 2 have a differential impact on the
psychological well-being of workers at wave 3. Furthermore, the complex
interrelationships between demands, job burnout, and psychological well-being are
impacted by social support in the workplace.
Job Demands and Job Burnout. Based on the results of the model tested with no social
support moderators, the relationships between job demands and job burnout were largely
as anticipated. Greater levels of role conflict at baseline predicted higher levels of
emotional exhaustion six months later, which is a finding congruent with previous
burnout studies (Lee & Ashforth, 1996; Kim, 2011; Tunc & Kutanis, 2009).
Unexpectedly, role ambiguity did not predict either dimension of job burnout (e.g.
emotional exhaustion and depersonalization), which was an unanticipated finding. Role
ambiguity is conceptualized as a workplace stressor and is considered to be an antecedent
to job burnout (Rizzo, House, Lirtzman, 1970; Lee, & Ashforth, 1996). In previous
empirical studies including a meta-analysis of burnout among psychiatric nurses,
153
(Melchior, Bourns, Schmitz, and Wittich, 1997), similar results have been found where
role conflict did correlate significantly with burnout while role ambiguity did not.
No job demands predicted depersonalization, a finding that is incongruent with
the JD-R model of burnout development (Demerouti, Bakker, Nachreiner, & Schaufeli,
2001). It may be possible that the job demands tested in this study are not predictors of
depersonalization, or that the job demands tested impact depersonalization through
emotional exhaustion. Though some debate exists regarding the interrelationships
between the burnout dimensions (Maslach, Schaufeli, & Leiter, 2001) findings from this
study support a theory of burnout development where there is a sequential relationship
from emotional exhaustion to depersonalization. Furthermore, emotional exhaustion at
wave 2 was the only burnout dimension that predicted psychological well-being at wave
3, a finding that was unforeseen. The null relationship between depersonalization and
psychological well-being points to the possibility that the dimensions of burnout have
differential impact on worker well-being outcomes.
Job Demands, Job Burnout, and Social Support. Study results indicate that the
relationships between job demands and the dimensions of burnout are more complex
when organizational support is accounted for. Overall, study findings point to null
relationships between demographic characteristics of workers and psychological well-
being. Findings also highlight the inconsistent and differential impact of job stress (e.g.
role conflict and role ambiguity) on the dimensions of burnout. When controlling for
social support in the workplace, role conflict did not predict either dimension of burnout,
while role ambiguity did predict burnout depending on the level of social support.
154
Interestingly, higher levels of role ambiguity baseline led to greater levels of emotional
exhaustion six months later only among those with high organizational support. This
finding suggests that those with higher levels of organizational support are more
susceptible to having higher levels of emotional exhaustion. The finding is
counterintuitive given that there is theoretical (Cohen, & Wills, 1985; Cohen, & McKay,
1984) and empirical support for social support as a buffer against stressors (Bakker,
Demerouti, & Euwema, 2005; Xanthopoulou et al., 2007). However, results from this
study suggest that organizational and supervisory social support may not buffer against
workplace stressors and burnout. Similarly, results in other studies have found that
higher social support within organizations is not always linked to more positive employee
outcomes (Boyas, Wind, &, 2010; Catalan, Burgess, Pergami, Hulme, Gazzard, &
Phillips, 1996). A plausible explanation is that formal support from the organization or
supervisors is given to those who organizational leaders believe are having a difficult
time coping with workplace stressors. Thus, managers and administrators might respond
to employees who appear stressed and burned out by providing them more social support
than their counterparts exhibiting lower level of stress and burnout.
The impact of work-family conflict was consistent across the models tested.
Work-family conflict is a predictor of emotional exhaustion and not depersonalization.
The negative impact of work-family conflict at baseline on emotional exhaustion six
months later was higher among those with lower levels of social support. This finding
suggests that increased work-family conflict leads to increased emotional exhaustion
among human service workers but the negative impact of work-family conflict is present
155
only among those with low levels of social support. Study results support the
hypothesized moderating effect of social support on the relationship between work-
family conflict and burnout. When the relationship between job demands and job burnout
was examined, no job demands were found to predict depersonalization. This finding
stands in contrast to job burnout theory, which postulates a relationship between job
stressors (e.g. job demands) and job burnout dimensions, including depersonalization
(Maslach, 2003). Findings from this study however, do suggest that there is a strong
association between emotional exhaustion and depersonalization. This finding points to
some alternate explanations that may be able to elucidate this unanticipated finding. Job
burnout theory is not completely clear on the interrelationships between the job burnout
dimensions with several explanations of how the dimensions influence each other
(Maslach, Schaufeli, & Leiter, 2001). One central, and popular theory on how the
dimensions are interrelated is one whereby emotional exhaustion leads to
depersonalization. This study lends support to the notion that greater job demands lead to
greater emotional exhaustion, which subsequently leads to higher levels of
depersonalization. This suggests that depersonalization is a function of emotional
exhaustion and not the direct influence of job demands.
Predicting Psychological Well-Being. No demographic characteristics were related to
psychological well-being, suggesting that worker well-being does not significantly differ
based on age, gender, tenure or position within the organization. One exception to the
overall null relationships found between demographic characteristics and psychological
well-being was the significant relationship found between race/ethnicity and
156
psychological well-being among those with high organizational support. Higher levels of
psychological well-being were found among non-Caucasian respondents with high
organizational support.
Job demands did not directly impact psychological well-being with one exception.
Work-family conflict at baseline influenced psychological well-being at wave 3 among
those with high supervisory support. This finding suggests that social support may not
buffer against the relationship between work-family conflict and psychological well-
being. The relationship between emotional exhaustion and psychological well-being was
consistent among the various models tested. Higher levels of emotional exhaustion led to
lower levels of psychological well-being a finding congruent with job burnout theory
postulates (Leiter, & Maslach, 2001; Maslach, C., & Leiter, 2006) and with previous
empirical studies (Asai, 2007 ). Results for the relationship between depersonalization
and psychological well-being were contrary to what was hypothesized. Depersonalization
did not predict psychological well-being, a finding that is incongruent with job burnout
theory (Maslach, 2001b) which purports a negative relationship between job burnout and
worker well-being. This finding provides evidence for a differential impact of job
burnout dimensions on psychological well-being. A plausible explanation is that
depersonalization, or detachment would not contribute to psychological well-being. One
exception was found when the relationship between reduced depersonalization and
psychological well-being was examined among those with high supervisory support. In
this case, higher levels of depersonalization were positively related to greater
157
psychological well-being. This finding stands in opposition of job burnout theory, which
suggests that higher levels of job burnout lead to lower psychological well-being.
In summary, findings from this study suggest that work-family conflict is
contributes to the development of emotional exhaustion. Emotional exhaustion is a
hazard to psychological well-being while depersonalization is not. Though social support
in the workplace does moderate the relationship between job demands, burnout, and
psychological well-being, this relationship was not consistent. For many, higher levels
of social support did result in more positive well-being outcomes but not all. In some
cases, depending on the source of support, higher levels of social support were associated
with poorer psychological well-being outcomes.
Implications
Findings from this study point to several managerial and administrative practice
implications. First, this study consistently found that work-family conflict leads to higher
levels of emotional exhaustion across the models tested. This finding suggests that
workers who feel that their work responsibilities are in conflict with their familial
responsibilities begin to feel emotionally depleted as they attempt to meet competing
demands. Organizational administrators and managers can strive to create a work
environment that integrates greater levels of flexibility, allowing workers to have a more
effective balance between familial and work responsibilities. Some flexible work
practices that have been found to be effective in reducing work-family conflict include
flex hours (Kelly, Moen, & Tranby, 2011), telecommuting options (Golden, Veiga, &
Simsek, 2006), and compressed work schedules (Lingard, Brown, Bradley, Bailey, &
158
Townsend, 2007). The finding that emotionally exhausted workers have lower levels of
psychological well-being points to the importance of targeting emotional exhaustion
among workers. Workplace interventions seeking to ameliorate, or buffer against
emotional exhaustion among workers should be explored. As this study has found, social
support alone may not be sufficient to protect against emotional exhaustion.
Though this study contributes to a better understanding of job burnout and
psychological well-being, several questions remain to be answered. Future studies should
continue to examine the differential impact of the burnout dimensions on worker well-
being. A possibility is that emotional exhaustion, as the affective dimension, influences
well-being while depersonalization, the interpersonal dimension of job burnout, may have
consequences associated with workplace behaviors like quality of service provision,
interaction with clients and co-workers. Future longitudinal studies on burnout and
psychological well-being should be carried out for a period of time longer than a year.
Longer longitudinal studies will provide a clearer perspective of job burnout
development. Organizational factors such as leadership and climate can significantly
influence work conditions that may subsequently lead to the development of burnout.
Though organizational leadership and organizational climate are key in shaping the work
experiences of human service workers, organizational leadership and climate variables
are not captured in the present study. Future studies can take a more holistic look at job
burnout development and its consequential influence on worker well-being by examining
the influence of organizational leadership and climate on burnout development.
159
Study Strengths and Limitations
The present study was successful in contributing to a greater understanding of the
relationship between job burnout and the psychological well-being of human service
wor ke rs, but shoul d be c onsi de re d withi n the c ont e x t of it s li mi tations . The stud y ’s
longitudinal design helps elucidate the relationship between burnout and psychological
well-being. Nevertheless, it should be noted that though longitudinal, the study took place
over a short period of time. One year is a limited amount of time to capture change in job
burnout. The sampling strategy employed in the study presents limitations i n the stud y ’s
generalizability. The study makes use of an availability sample, which may potentially
bias the study sample. Additionally, the sample was drawn from a large public child
welfare organization that may subsequently limit the ability to generalize workplace
experiences of workers in the sample to workers within contexts in non-urban areas.
That being said, this study is marked by unique strengths. The present study employs a
longitudinal design that allows for quantitative analysis that goes beyond a correlational
one. Several burnout and employee well-being studies in the human services sector have
examined only correlational relationships. This study tests a proposed conceptual model
that provides insight into the complex relationships that exist between the job burnout
dimensions and psychological well-being over time. The analysis of the burnout
dimensions separately and not as a composite also serves as a strength in this study
because this approach allows for a closer look at the nuanced relationships that exist
between emotional exhaustion, depersonalization, and worker well-being.
160
Table 13.
Study 3 Correlation Matrix
Mean
S.D.
Scale
Reliability 1. 2.
3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
1. Age 37 12 N/A 1
2. Race/Ethnicity N/A N/A N/A -.32
**
1
3. Tenure 6.16 6.73 N/A .71
**
-.18
**
1
4. Position N/A N/A N/A -.43
**
.30
**
-.65
**
1
5. Role Conflict 30.45 8.51 .85 .17
**
-.10 .15
**
-.08 1
6. Role Ambiguity 14.11 5.06 .83 -.19
**
-.01 -.18
**
.07 .15
**
1
7. Work-family
Conflict
9.61 3.92 .76 .02 .08
.06
.03 .25
**
.14
**
1
8. Organizational
Support
24.83 8.90 .86 -.26
**
.14
**
-.32
**
.15
**
-.39
**
-.16
**
-.19
**
1
9. Supervisory
Support
37.61 8.43 .90 .06 -.03
-.13
*
.08 -.23
**
-.20
**
-.16
**
.24
**
1
10. Specialized
Training
N/A N/A N/A -.43
**
.19
*
-.36
**
.17 -.07 .13 -.01 .03 .07 1
11. Emotional
Exhaustion
29.73 11.03 .92 -.15
*
-.01
-.17
*
.03 .17
*
.17
*
.21
**
-.10 -.04 .05 1
12. Depersonalization 10.55 4.63 .81 -.17
*
-.05 -.15* .11 .02 .12 .01 -.12 .08 .10 .53
**
1
13. Psychological
Well-being
34.84 5.20 .85
-.03 .09 .01 .13 -.14 -.08 -.17 .22
*
.04 -.15 -.37
**
-.09
** p< 0.01 level (2-tailed). * p< 0.05 level (2-tailed).
161
Table 14.
Study 3 Baseline Model Fit Statistics
Goodness-of-fit Statistics
χ
2
14.30
Degree of freedom (df) 8
χ
2
p-value .07
Comparative Fit Index (CFI) .99
Normed Fit Index (NFI) .98
Root mean square error of approximation
(RMSEA)
.05
Akaike information criterion
128.30
(AIC)
Variance Explained (r
2
)
Psychological well-being 21%
162
Table 15.
Study 3 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Organizational Support
Constrained
Model
Unconstrained
Model
Goodness-of-fit Statistics
χ
2
27.9 10.99
Degree of freedom (df) 32 16
χ
2
p-value .68 .81
Comparative Fit Index (CFI) 1.00 1.00
Normed Fit Index (NFI) .96 0.98
Root mean square error of
approximation (RMSEA) 0 0
Akaike information criterion
(AIC) 223.87 238.98
Variance Explained (r
2
)
Psychological well-being 27%
L=20%, H=30%
Note . “ L ” d e notes low so c ial support gr oup a nd “ H” de notes hi g h soc ial su pport g roup.
163
Table 16.
Study 3 Goodness-of-fit Statistics for Constrained and Unconstrained Models
By Supervisory Support
Constrained Model
Multi-group
Analysis
Goodness-of-fit Statistics
χ
2
42.88 14.76
Degree of freedom (df) 32 16
χ
2
p-value .09 .54
Comparative Fit Index (CFI) .98 1.00
Normed Fit Index (NFI) .94 .98
Root mean square error of
approximation (RMSEA) .03 0
Akaike information criterion
(AIC) 238.88 242.41
Variance Explained (r
2
)
Psychological Well-being 20% L=22%, H=48%
Note . “ L ” d e notes low so c ial support gr oup a nd “ H” de notes hi g h soc ial
support group.
164
Table 17.
Study 3 Baseline Model Path Coefficients
b S.E. β
RC -> EE .14 .10 .11
*
RA -> EE .32 .16 .14
WFC -> EE .58 .21 .20
**
RC -> DP -.04 .04 -.07
RA -> DP .04 .06 .04
WFC -> DP -.15 .08 -.13
*
EE -> DP .24 .03 .58
**
Age -> PWB .01 .05 .02
Race/Ethnicity -> PWB 1.27 .98 .11
Tenure -> PWB .01 .01 .11
Position -> PWB 1.81 1.48 .14
RC -> PWB -.05 .05 -.08
RA -> PWB .02 .09 .01
WFC -> PWB -.06 .12 -.04
EE -> PWB -.21 .05 -.45
**
DP -> PWB .19 .12 .17
** p< 0.01 level (2-tailed). * p< 0.05 level (2-tailed).
165
Table 18.
Study 3 Path Coefficients for Multi-Group Path Model of Work Place Demands, Job burnout, and Job
Satisfaction for Low and High Organizational Support Groups
Constrained
Model
Unconstrained Model
Low Organizational
Support
High Organizational
Support
b S.E. β b S.E. β b S.E. β Critical
Ratio
RC -> EE
.17 .11 .12
.31 .14 .22
*
.13 .17 .09 .78
RA -> EE
.22 .16 .09
-.15 .21 -.07 .82 .26 .36
**
-2.96
*
WFC -> EE
.67 .21 .22
**
.90 .25 .33
**
.22 .36 .07 1.55
RC -> DP
-.07 .04 -.12
-.04 .05 -.07 -.10 .06 -.18 .80
RA -> DP
.02 .06 .02
.02 .08 .02 -.01 .09 -.02 .26
WFC -> DP
-.15 .08 -.13
-.15 .10 -.13 -.11 .12 -.09 -.25
EE -> DP
.24 .03 .63
**
.23 .04 .57
**
.24 .04 .62
**
-.22
Age -> PWB
.03 .05 .07
.04 .08 .07 .03 .07 .01 .02
Race/Ethnicity -> PWB
1.65 .97 .16
1.27 1.40 .11 2.35 1.33 .23 -.56
Tenure -> PWB
.01 .01 .13
.01 .01 .05 .01 .01 .16 -.39
Position -> PWB
2.39 1.48 .19
1.49 1.90 .11 3.54 2.29 .27 -.68
RC -> PWB
-.02 .06 -.03
-.10 .09 -.14 .04 .08 .06 -1.15
RA -> PWB
0.02 0.09 .02
-.02 .13 -.02 .12 .13 .13 -.78
WFC -> PWB
0.00 0.12 -.002
-.29 .17 -.21 .09 .16 .08 -1.63
EE -> PWB
-0.20 0.05 -.52
**
-.13 .08 -.26 -.22 .07 -.54
**
.82
DP -> PWB
0.16 0.13 .16
.13 .18 .10 .17 .17 .16 -.16
** p< 0.01 level (2-tailed). * p< 0.05 level (2-tailed).
166
Table 19.
Study 3 Path Coefficients for Multi-Group Path Model of Work Place Demands, Job burnout, and Job Satisfaction for Low
and High Supervisory Support Groups
Constrained
Model
Unconstrained Model
Low Supervisory
Support
High Supervisory
Support
Critical
Ratio
b S.E. β b S.E. β b S.E. β
RC -> EE
.14 .11 .10
.01
.15 .01 .16 .15 0.12 -.68
RA -> EE
.28 .17 .13 .21 .21 .10 .45 .27 0.19 -.71
WFC -> EE
.63 .22 .21
**
1.13 .32 .37
**
.23 .30 0.09 2.06
*
RC -> DP
-.05 .04 -.09 -.09 .05 -.15 -.01 .05 -.02 -1.08
RA -> DP
.04 .06 .05 -.04 .08 -.04 .13 .09 .14 -1.38
WFC -> DP
-.14 .08 -.11 -.25 .12 -.19
*
-.06 .10 -.06 -1.21
EE -> DP
.24 .03 .57
**
.28 .04 .66
**
.19 .04 .49
**
1.75
Age -> PWB .02 .05 .05 -.03 .08 -.07 .04 .07 .09 -.71
Race/Ethnicity -> PWB 1.24 .99 .11 .31 1.36 .03 1.60 1.26 .14 -.70
Tenure -> PWB .01 .01 .07 .02 .01 .34 .01 .01 .08 .91
Position -> PWB
1.82 1.49 .13 3.97 1.91 .31
*
1.58 2.00 .11 .86
RC -> PWB
-.04 .06 -.06 -.07 .08 -.12 -.11 .07 -.18 .35
RA -> PWB
-.02 .09 -.02 -.15 .12 -.16 .16 .14 .13 -1.72
WFC -> PWB
-.09 .12 -.06 .26 .19 .19 -.34 .14 -.26
**
2.57
*
EE -> PWB
-.22 .05 -.45
**
-.13 .08 -.30 -.31 .06 -.62
**
1.79
DP -> PWB
.21 .13 .18 -.03 .17 -.03 .45 .16 .34
**
-2.06
*
167
Figure 8.
Study 3 Baseline Model of Job Demands, Burnout, and Psychological Well-being
Model fit statistics: Χ
2
= 14.30, df= 8, p=.07; CFI= .99; NFI= .98; RMSEA = .05; AIC=
128.30. Psychological well-being r
2
=21%.
.17
-.45
**
-.13
*
.04
-.07
.20
**
.01
.14
.11*
-.08
.14
.11
.11
.02
Role
Ambiguity
Emotional
Exhaustion
Psychological
Well-being
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
.58
**
Depersona-
lization
-.04
168
Figure 9.
Study 3 Multi-group Model of High and Low Organizational Support, Job Demands, Job
Burnout and Psychological Well-being
.56
**
/.62
**
.05/.10
-.26*/-.54
**
-.13/-.09
.02/-.02
-.07/ -.18
.31
**
/.07
-.02/.13
-.07/.36
**
.21
*
/.09
-.14/.06
.11/.27
.05/.16
.11/.23
*
.07/.01
Role
Ambiguity
Emotional
Exhaustion
Psychological
Well-being
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
Depersona-
lization
-.21/ .08
169
Note. Bolded coefficients correspond to the high organizational support group and
italicized coefficients correspond to the low organizational support group.
* p≤ .05, **p≤ .01. Model fit statistics: Χ
2
= 10.99, df= 16, p=.81; CFI= 1.00; NFI= .98;
RMSEA = .00; AIC= 238.98. Low organizational support group: psychological well-
being r
2
= .20. High organizational support group: psychological well-being r
2
= .30.
170
Figure 10.
Study 3 Multiple Sample Model of High and Low Supervisory Support, Job Demands,
Burnout, and Psychological Well-being
Note. Bolded coefficients correspond to the high supervisory support group and italicized
c oe ff i c ients c orr e spond t o the low supe rvisor y su pport g roup. * p≤ .05, ** p≤ .01. Model
..66
**
/.49
**
-.03/.34
**
-.30/-.62
**
-.19*/-.06
-.04/.14
- .15/ -.02
.37
**
/.09
-.16/.13
.10/.19
.04/.01
-.12/-.18
.31
*
/.11
.34/.08
.03/.14
-.07/.09
Role
Ambiguity
Emotional
Exhaustion
Psychological
Well-being
Work-family
Conflict
Role
Conflict
Race/
Ethnicity
Age
Tenure
Position
Depersona-
lization
.19/-.26
**
**
171
fit statistics: Χ
2
= 14.76, df= 16, p=.54; CFI= 1.00; NFI= .98; RMSEA = .0; AIC=
242.41. Low organizational support group: psychological well-being r
2
= .22. High
supervisory support group psychological well-being r
2
= .48.
172
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176
CHAPTER 5
INTERGRATION AND IMPLEMENTATION OF FINDINGS FROM THE THREE
STUDIES
Purpose of the Studies
Though the human service sector serves as the birthplace for job burnout research
(Schaufeli & Maslach, 1993) and its antecedents have been widely studied, a dearth of
research examining the impact of burnout on human service worker well-being exists.
Leaders within human service organizations should be concerned about the effects of job
burnout on worker well-being for two primary reasons. First, managers and
administrators within organizations have an ethical responsibility to protect employees
from workplace hazards. Secondly, worker well- b e ing c a n dire c tl y in flue nc e wor ke rs’ on-the-job performance and as a result can subsequently influence organizational
performance. The studies on burnout and worker well-being that have been conducted
have left several gaps in knowledge and the goal of this dissertation is to address some of
those key gaps. First, a systemic review and synthesis of research findings on burnout and
psychological, physical, and behavioral well-being among human service workers has not
been carried out. A systematic review of literature provides a summary of the current
state of knowledge on job burnout and worker well-being and helps inform future
research studies. Without a systematic review of literature on burnout and well-being, it
is unclear if burnout and its different dimensions have an effect on worker well-being.
Furthermore it remains unclear if the burnout dimensions have similar or dissimilar
ramifications on psychological, physical and behavioral well-being. The few studies that
177
have been conducted are limited primarily by their designs. Most studies on burnout and
worker well-being in the human services sector are cross-sectional in nature which
disallows the testing of the temporal order of events leading to burnout a n d bur nout’s
influence on worker well-being. Given that such knowledge would contribute to a better
understanding of job burnout and worker well-being, this multi-manuscript dissertation
first presents a systematic review of the job burnout and worker well-being literature.
Next, it examines the interrelationships between job demands and resources, job burnout,
a nd bur nout’s e f fe c t on a ff e c ti ve a nd ps y c holo g ic a l we ll -being over the span of a year.
Major findings drawn from the three studies presented in this dissertation are summarized
below followed by a discussion of the implications of study findings on theory, practice,
policy and methodological recommendations for future research.
Overall Major Findings
Major Findings: Study 1
Based on the search strategy employed, and inclusion criteria set forth, the
systematic review conducted yielded 17 studies that investigated the relationship between
job burnout and at least one form of affective/psychological, physical, or behavioral well-
being. The number of studies points to the sparse amount of research being published on
this topic. The findings from the included studies indicate that job burnout is a hazard to
worker well-being. When the differential impact of the burnout dimensions on well-being
was examined, it was found that emotional exhaustion was negatively related to worker
well-being on a consistent basis regardless of the form of well-being being studied.
Furthermore, emotional exhaustion was measured in every single study and in some was
178
the sole burnout dimension studied. Depersonalization and personal accomplishment
were not as widely studied as emotional exhaustion. When studied, a negative
relationship was found between depersonalization and well-being outcomes, while a
positive relationship between personal accomplishment and well-being was found.
Interestingly, though the relationships found between depersonalization, personal
accomplishment and worker well-being were in the hypothesized direction the
significance of these relationships was inconsistent across studies. This finding suggests
that while emotional exhaustion is a direct threat to worker well-being, the relationship
between the burnout dimensions of depersonalization and personal accomplishment were
not as clear. A possible explanation might be that depersonalization and reduced personal
accomplishment develop as protection against emotional exhaustion and as a result
protect some forms of well-being (e.g. affective well-being) but not others (e.g.
psychological and physical well-being).
Study methodologies and sample strategies provided some interesting insight into
the current state of job burnout research in the human service sector. Though burnout is
conceptually and operationally defined as separate dimensions, not all studies examined
the impact of each dimension on well-being separately. A number of studies made use of
composite scales of burnout, precluding the ability to examine any nuanced differences
that may exist between the different job burnout dimensions and their consequences on
well-being. The great majority of the studies were cross-sectional with only three studies
using longitudinal study designs. A great proportion of study samples were in nursing
with those studies carried out largely by nursing scholars. The most widely studied well-
179
being outcome was affective well-being and more specifically, job satisfaction as the
form of affective well-being. Very few studies focused on physical and behavioral well-
being as outcomes.
Major Findings: Study 2
Study 2 tested the interrelationships across time between job demands, job
burnout and affective well-being (e.g. job satisfaction) among a sample of public child
welfare workers. Study 2 results suggest that job satisfaction is not influenced by age,
race/ethnicity, tenure or position. When the influence of workplace resources on job
demands, burnout and job satisfaction was tested, subtleties emerged that lend support to
the hypothesis that the relationship between job demands and job burnout is dependent on
the level of resources in the workplace. Before continuing with a discussion of the
models tested, it should be noted that two relationships remained consistent regardless of
level of resources. First, the association between emotional exhaustion and
depersonalization was positive and significant irrelevant of job resource levels. Second,
emotional exhaustion at wave 2 significantly predicted lower job satisfaction at wave 3
regardless of level of resources.
Three forms of workplace resources were tested in the study models including
organizational support, supervisor support, and specialized child welfare training. When
the relationships between job demands, burnout and job satisfaction were examined
without accounting for the level of resources, most of the study findings were as
hypothesized. In the baseline model within Study 2, work-family conflict and role
ambiguity at baseline predicted emotional exhaustion six months later. No job demands
180
predicted depersonalization. Findings from Study 2 suggest that demands at baseline
impact depersonalization through emotional exhaustion six months later. Emotional
exhaustion was the only burnout dimension that predicted job satisfaction.
To assess for the moderating effect of organizational support on the relationships
between job demands, burnout, and job satisfaction, a comparison of path model
coefficients was conducted between those reporting high and low levels of support. The
model that accounted for organizational support explained more variance in job
satisfaction than did the model with no social support accounted for (low organizational
support r
2
= 17% and high organizational support group r
2=
42% vs. baseline model
r
2
=23.7%). The path model that included organizational support yielded no significant
relationships between demographic characteristics and job satisfaction with the exception
of race. Non-Caucasian respondents with high organizational support reported higher
levels of job satisfaction. Respondents in the low levels of organizational support
category were more vulnerable to demands predicting emotional exhaustion. Emotional
exhaustion was significantly and positively associated with depersonalization irrelevant
of level of support. Higher levels of emotional exhaustion at wave 2 predicted lower
levels of job satisfaction at wave 3 irrelevant of the level of organizational support
received.
The model including supervisory support was superior in explaining variance in
job satisfaction (low supervisory support r
2
=34%, high supervisory support r
2
= 25 %)
when compared to the baseline model (r
2
= 23.7%). No demographic variables predicted
job satisfaction in the supervisory support model. Those categorized as having low
181
supervisory support appeared to be more vulnerable to having job demands predict
burnout as evidenced by the greater number of significant paths between demands and
burnout among this group. Emotional exhaustion and depersonalization were positively
and significantly associated in both groups. Higher levels of emotional exhaustion at
wave 2 predicted lower levels of job satisfaction at wave 3 in both supervisory support
groups, while depersonalization was not found to be a significant predictor of job
satisfaction in either group.
The model including specialized child welfare training was more effective in
explaining variance in job satisfaction among those with specialized child welfare
training (has no specialized child welfare training r
2
=20%, has specialized child welfare
training r
2
= 57%) when compared to the baseline model (r
2
= 23.7%). No demographic
variables predicted job satisfaction in the specialized child welfare training model with
the exception of position within the organization. Workers with specialized child welfare
training in front-line positions were less likely to be satisfied with their jobs. Respondents
with specialized child welfare training were more vulnerable to job stress (e.g. role
conflict and role ambiguity). Respondents with no specialized child welfare training were
more likely to have their experiences of work-family conflict at baseline predict
emotional exhaustion six months later. Emotional exhaustion and depersonalization were
positively and significantly associated in both groups. When the standardized beta
coefficients of the paths between emotional exhaustion and depersonalization are
compared between groups, it appears that the relationship between emotional exhaustion
a nd de pe rson a li z a ti on is strong e r a mon g those w it h no spe c ializ e d tra ini ng (β= .71) a s
182
c ompar e d to t hose with s pe c ializ e d tra ini ng (β= .41). Higher levels of emotional
exhaustion at wave 2 predicted lower levels of job satisfaction at wave 3 in both groups.
However, the relationship between emotional exhaustion and depersonalization was a lot
stronger among those with specialized child we lfa re tra ini n g (β= -.64) than among those
without specialized child welfare training
(β= -.38).
Major Findings: Study 3
Study 3 tested a baseline model of the interrelationships between job demands, burnout
and psychological well-being among a sample of public child welfare workers over one
year. Results from the baseline model tested in Study 3 suggest that psychological well-
being is not influenced by age, race/ethnicity, tenure or position. Role conflict and work-
family conflict were the only job demands at wave 1 that predicted emotional exhaustion
six months later in the baseline model. No job demands predicted depersonalization.
Emotional exhaustion and depersonalization had a positive and significant association.
Higher levels of emotional exhaustion predicted lower levels of psychological well-
being.
To assess for the moderating effects of organizational and supervisory support on
the relationships between job demands, burnout and pscychological well-being, a
comparison of path model coefficients was conducted between those with low and high
levels of social support. The model that accounted for organizational support explained
the same variance in psychological well-being as the baseline model among those with
low organizational support but explained more variance among those with high
183
organizational support (low organizational support r
2
= 20% and high organizational
support group r
2=
30% vs. baseline model r
2
=21%). The path model that included
organizational support yielded no significant paths between demographic characteristics
and psychological well-being with the exception of race/ethnicity. Non-Caucasian
respondents with high organizational support reported higher levels of psychological
well-being. Emotional exhaustion was significantly and positively associated with
depersonalization irrelevant of level of organizational support. Higher levels of emotional
exhaustion at wave 2 predicted lower levels of psychological well-being six months later
regardless of level of organizational support.
No demographic variables predicted psychological well-being in the supervisory
support model. Those categorized as having low supervisory support appeared to be more
vulnerable to having job demands predict burnout as evidenced by the greater number of
significant paths between demands and burnout among this group. Emotional exhaustion
and depersonalization were positively and significantly associated between both groups.
Higher levels of emotional exhaustion at wave 2 predicted lower levels of psychological
well-being six months later in both supervisory support groups. Higher levels of
emotional exhaustion and depersonalization predicted lower levels of psychological well-
being among those with high levels of supervisory support but not among those with low
levels of supervisory support.
Theory, Practice, and Policy Implications
The overarching findings from the three studies point to an important implication
for burnout theory. Studies 2 and 3 lend support to the possibility that job demands
184
influence depersonalization through emotional exhaustion. The sequence of relationships
between the dimensions of burnout remains a topic of debate (Maslach, Schaufeli, &
Leiter, 2001). Several theories have been provided for interrelationships between the
burnout dimensions. Findings from this study lend support to the assumption that
emotional exhaustion is the key dimension of burnout and that depersonalization results
in response to emotional exhaustion.
As mentioned above, findings from all three studies confirm that emotional
exhaustion is the central dimension of burnout. More importantly, emotional exhaustion
is hazardous to the affective/psychological, physical, and behavioral well-being of
workers. This central finding points to some important managerial and administrative
practice implications. Any workplace interventions at the management or organizational
policy level designed to mitigate the negative impact of burnout on worker well-being
should target emotional exhaustion. Management practices or administrative policies in
the workplace geared toward reducing burnout should seek to promote the protection of
wor ke rs’ p e rsona l re sour c e s or pr ovide tool s that i nc re a s e wor k e rs’ p e rsona l re sourc e s. A
depletion of personal resources is the central mechanism by which emotional exhaustion
develops and thus any effort to prevent the development job burnout should target the
depletion of personal resources.
Study 2 yielded findings that may have implications for the specialized training of
child welfare workers. First, the study findings suggest that there is a negative
relationship between front-line child welfare work and job satisfaction among those with
specialized child welfare training. It may be possible that individuals who have sought
185
specialized child welfare training feel that their specialized skill sets are not being used to
their full capacity in front-line work. Individuals with specialized training might be less
satisfied with line work. Managers within child welfare organizations should consider
what might be done to create job responsibilities that promote job satisfaction among
specially trained workers. Some possibilities include hybrid positions where specially
trained workers carry a lower caseload in order to work on other special projects where
leadership and management skills can be utilized. This might include supervising interns,
working on short-term administrative projects for organizational development, or training
of new child welfare workers. Specially trained workers were also more susceptible to
having job stress (role conflict and role ambiguity) predict emotional exhaustion. It
appears that those with advanced training are less likely to be able to cope with
conflicting job demands or with unclear job expectations. Specially trained workers
might feel that they have a deeper understanding of the requirements of child welfare
work and may as a result have a difficult time tolerating incompatible or unclear
demands. Managers and administrators in child welfare organizations should aim to move
towards clearer definitions of work expectations and take a critical evaluation of any
expectations that may be contradictory at the risk of promoting job dissatisfaction among
highly skilled workers.
Implications for Future Research
Systematic Review
Findings from the systematic review conducted in Study 1 of this dissertation
points to the importance of continued research focusing on job burnout and worker well-
186
being. First, an expansion of studies examining the impact of burnout on physical well-
being among human se rv ice wor ke rs is c ritica l. B urnou t’s potential c onse q ue nc e s on
physical well-being can potentially impact organizations through worker absenteeism due
to sickness, and through healthcare costs associated with burnout induced physical
ailments. Future studies should also begin to explore how burnout influences behavioral
well-being. The general workforce literature suggests that maladaptive behaviors can
develop as a coping mechanism against burnout (Maslach, 1978). Such behaviors include
smoking, drinking, lack of exercise, and overeating (Gorter, Eijkman, & Hoogstraten,
2000; Moustou, Panagopoulou, Montgomery, & Benos, 2010). The review of literature
also suggests that study findings on the relationship between depersonalization, personal
accomplishment and worker well-being are mixed. Further examinations of the
differential impact of burnout dimensions on psychological, physical and behavioral
well-being are needed.
A great proportion of the studies included in the systematic review employed
cross-sectional designs. This finding underscores the importance of continuing to expand
the use of longitudinal research design approaches when studying the relationship
between job burnout and worker well-being. The developmental nature of burnout
(Maslach, 1998) makes it difficult to capture the complex interrelationships between
burnout and worker well-being when using cross-sectional design approaches. Though
conducting longitudinal designs can be logistically more difficult than conducting cross-
sectional studies, it is critical that research in the burnout and worker well-being field
move toward the increased use of longitudinal study designs.
187
Longitudinal Empirical Studies
The longitudinal design of studies 2 and 3 serve as a primary strength of the
studies. The longitudinal research design of the latter two studies in this dissertation
permitted the testing of hypotheses about the temporal order of complex
interrelationships between job demands, job burnout and worker well-being (e.g.
affective and psychological well-being) while taking into consideration the influence of
workplace resources. Nevertheless, the study was notably short covering only a one-year
period of time between baseline and the final observation carried out in wave 3. Future
longitudinal studies should continue using panel study designs but for longer durations of
time. Studies lasting two, five or even ten years can more effectively capture the
development of burnout across time and its impact on worker well-being.
The differential impact of job demands on the dimensions of burnout and the
distinct influence of the burnout dimensions on worker well-being found in studies 2 and
3 highlight the importance of refraining from using composite burnout measures in
burnout research. To fully understand the heterogeneous influence of emotional
exhaustion and depersonalization on worker well-being, job burnout dimensions must not
be aggregated when measured. Future scholars investigating the relationships between
the dimensions of job burnout and worker well-being should continue the separate
mea sure ment of bu rnout’ s di mensions and a bstain fr om us ing c ompos it e burn out sca les.
188
References
Gorter, R. C., Eijkman, M. A., & Hoogstraten, J. (2000). Burnout and health among
Dutch dentists. European journal of oral sciences, 108(4), 261-267.
Maslach, C. (1978). Job burnout: How people cope. Public Welfare, 36(2), 56-58.
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual review of
psychology, 52(1), 397-422.
Maslach, C. (1998). A multidimensional theory of burnout. In C. L. Cooper (Ed.)
Theories of organizational stress (pp. 68-85). New York, NY: Oxford
University Press, Inc.
Moustou, I., Panagopoulou, E., Montgomery, A. J., & Benos, A. (2010). Burnout
Predicts Health Behaviors in Ambulance Workers. Open Occupational Health
& Safety Journal, 2, 16-18.
Schaufeli, W. B., & Maslach, C. (1993). Historical and conceptual development of
burnout. Professional burnout: Recent developments in theory and research,
1-16.
189
APPENDIX A
Measurement items
Scale items requiring reverse coding are marked with an asterisk (*).
Role ambiguity
Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role conflict and ambiguity in
complex organizations. Administrative Science Quarterly, 15(2), 150-163.
1.* I have clear planned goals and objectives for my job.
2.* I know that I have divided my time properly.
3.* I know what my responsibilities are.
4.* I know exactly what is expected of me.
5.* I feel certain about how much authority I have on the job.
6.* Explanation is clear of what has to be done.
Role conflict
Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role conflict and ambiguity in
complex organizations. Administrative Science Quarterly, 15(2), 150-163.
1. I have to do things that should be done differently under different
conditions.
2. I receive an assignment without the manpower to complete it.
3. I have to buck a rule or policy in order to carry out an assignment.
4. I work with two or more groups who operate quite differently.
5. I receive incompatible requests from two or more people.
6. I do things that are apt to be accepted by one person and not by others.
190
7. I receive an assignment without adequate resources and materials to execute
it.
8. I work on unnecessary things.
Work-family conflict
Beatty, C. A. (1996). The stress of managerial and professional women: Is the price
too high? Journal of Organizational Behavior, 17, 233 – 251.
1. My job keeps me away from my family too much.
2. My time off does not match other family members schedules well.
3.* I have a good balance between my job and my family life.
Perceived supervisory support
Kottke, J. L., Sharafinski, C. E. (1988). Measuring perceived supervisory
and organizational support. Educational & Psychological Measurement,
48(4), pp. 1075-1079.
1. My supervisor values my contribution to the wellbeing of the organization.
2.* My supervisor fails to appreciate any extra effort from me.
3.* My supervisor would ignore any complaint from me.
4. My supervisor really cares about my wellbeing.
5.* Even if I did the best job possible, my supervisor would fail to notice.
6. My supervisor cares about my general satisfaction at work.
7.* My supervisor shows very little concern for me.
8. My supervisor takes pride in my accomplishments at work.
191
Perceived organizational support
Kottke, J. L., Sharafinski, C. E. (1988). Measuring perceived supervisory
and organizational support. Educational & Psychological Measurement,
48(4), pp. 1075-1079.
1. This organization [DCFS] values my contribution to its wellbeing.
2.* DCFS fails to appreciate any extra effort from me.
3.* DCFS would ignore any complaint from me.
4. DCFS really cares about my wellbeing.
5.* Even if I did the best job possible, DCFS would fail to notice.
6. DCFS cares about my general satisfaction at work.
7.* DCFS shows very little concern for me
8. DCFS takes pride in my accomplishments at work.
Emotional exhaustion
Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout.
Journal of Occupational Behavior, 2, 99 – 113.
1. I feel emotionally drained from my work.
2. I feel used up at the end of the workday.
3. I feel fatigued when i get up and have to face another day on the job.
4. Working with people all day is really a strain for me.
5. I feel burned out from my work.
6. I feel frustrated by my job.
7. I feel I'm working too hard on my job.
192
8. Working with people directly puts too much stress on me.
9. I feel like I'm at the end of my rope.
Depersonalization
Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout.
Journal of Occupational Behavior, 2, 99 – 113.
1. I feel I treat some clients as if they were impersonal objects.
2. I've become more callous toward people since I took this job.
3. I worry that this job is hardening me emotionally.
4. I don't really care what happens to some clients.
5. I feel clients blame me for some of their problems.
General Health Questionnaire- 12 (GHQ; Current mental health status)
Goldberg, D. P. (1972). The detection of psychiatric illness by questionnaire.
Maudsley Monograph No. 21. Oxford University Press: Oxford.
1. Been able to concentrate on whatever you are doing.
2. Recently lost much sleep over worry.
3. Recently felt you were playing a useful part in things.
4. Recently felt capable of making decisions about things.
5. Recently felt constantly under strain.
6. Recently felt you could not overcome your difficulties.
7. Recently been able to enjoy your normal day-to-day activities.
8. Recently been able to face up to problems.
9. Recently been feeling unhappy or depressed.
193
10. Recently been losing confidence in yourself.
11. Recently been thinking of self as worthless possession.
12. Recently been feeling reasonable happy, all things considered.
Job satisfaction
Quinn, R. P., & Staines, G. L. (1979). The 1977 quality of employment survey. Ann
Arbor, MI: Survey Research Center, Institute for Social Research, University
of Michigan.
1. All in all, I am satisfied with my job.
2. If a good friend was interested in working in a job like mine for DCFS, I would
recommend that job.
3. Knowing what I know now about my job, if I have it to do over again, I would
still have pursued that job.
4. In general, I would say that my job measured up to the sort of job I have
wanted when I took it.
Abstract (if available)
Abstract
Presented here is a three‐study dissertation with an overarching goal of contributing to a greater understanding of the impact of job burnout on worker well‐being in the human service sector. Each of the three studies makes a unique contribution to this overarching goal. Chapter I presents a discussion integrating the logical link among the three studies, briefly introduces the purpose and description of each, and provides an overview of the theories driving the three studies. Chapter II (Study 1) is comprised of a systematic review of literature focusing on the effect of job burnout on worker well‐being in the human service sector. Chapter III (Study 2) presents findings from a test of a theory‐based model of the relationship between job demands and resources, job burnout, and job satisfaction over time. Chapter IV (Study 3) presents the findings of a test of a theory‐based model of the relationships between job demands and resources, job burnout, and psychological well‐being over time. An integrated discussion of study findings, conclusions and implications for future social work research and practice are presented in Chapter V.
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University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Lizano, Erica Leeanne
(author)
Core Title
Examining the impact of job burnout on the well-being of human service workers
School
School of Social Work
Degree
Doctor of Philosophy
Degree Program
Social Work
Publication Date
05/02/2014
Defense Date
03/13/2014
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
child welfare workers,human service workers,job burnout,job satisfaction,job stress,Mental Health,OAI-PMH Harvest,well-being
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application/pdf
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Language
English
Contributor
Electronically uploaded by the author
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Advisor
Mor Barak, Michàlle E. (
committee chair
), Jansson, Bruce (
committee member
), Robertson, Peter John (
committee member
)
Creator Email
erica.lizano@gmail.com,lizano@usc.edu
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https://doi.org/10.25549/usctheses-c3-410644
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Lizano, Erica Leeanne
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Tags
child welfare workers
human service workers
job burnout
job satisfaction
job stress
well-being