THE RELATIONSHIP OF WORK DEMANDS AND RESOURCES TO SUBJECTIVE
WELL-BEING: THE ROLE OF SELF-EFFICACY AND COPING.
By

Nikolaos Dimotakis

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Organizational Behavior - Human Resource Management
2011

ABSTRACT
THE RELATIONSHIP OF WORK DEMANDS AND RESOURCES TO SUBJECTIVE WELLBEING: THE ROLE OF SELF-EFFICACY AND COPING.
By
Nikolaos Dimotakis
The present study proposes to examine the relationship between the demands of
individuals’ work environment and their levels of subjective well-being, as well as the role of
self-efficacy as a mediator of this proposed relationship. Drawing from the demands-control
model and its extensions (Karasek, 1979; Johnson & Hall, 1988; Bakker & Demerouti, 2007), as
well as the self-efficacy component of social-cognitive theory (Bandura, 1997), I suggest a
model that examines the circumstances under which individuals manage to cope, with a greater
or lesser degree of success, with the demands of their work, as well as how the success of these
coping processes relate to individuals’ level of subjective well-being, in combination with the
availability of workplace resources in their job and changes in their daily self-efficacy beliefs.
Finally, I describe a longitudinal field study designed to test this model in a sample of clerical
and administrative employees, and discuss the implications of this model for theory and practice.

For my parents, who showed me the path, and Tracy, who helped me walk it.

iii

ACKNOWLEDGEMENTS

I want to thank my dissertation chair, Remus Ilies, without whose help this dissertation
would not have been possible. My gratitude also goes to Donald E. Conlon, John R. Hollenbeck,
and John M. Schaubroeck who, as members of my dissertation committee, provided invaluable
guidance and assistance.

iv

TABLE OF CONTENTS

List of Tables ..................................................................................................................... vi
List of Figures ..................................................................................................................... x
Introduction ......................................................................................................................... 1
Literature Review................................................................................................................ 7
Hypothesis Development .................................................................................................. 41
Method .............................................................................................................................. 66
Tests of Hypotheses .......................................................................................................... 83
Discussion ......................................................................................................................... 92
Conclusion ...................................................................................................................... 118
Appendices ...................................................................................................................... 119
Tables .............................................................................................................................. 119
Figures............................................................................................................................. 181
References ....................................................................................................................... 219

v

LIST OF TABLES

Table 1: Confirmatory Factor Analysis for the Daily Measurement Variables .......................... 121
Table 2: Variance Components of the Repeated Measures Variables ........................................ 122
Table 3: Means and Standard Deviations for the Between-People Variables ............................ 123
Table 4: Means, Standard Deviations and Correlations for the Within-People Variables ......... 124
Table 5: Relationship between Role Conflict and Well-Being (Hypothesis 1). ......................... 126
Table 6: Relationship between Workload and Well-Being (Hypothesis 1). ............................... 127
Table 7: Relationship between Emotional Demands and Well-Being (Hypothesis 1). .............. 128
Table 8: Relationship between Interpersonal Conflict and Well-Being (Hypothesis 1). ........... 129
Table 9: Relationship between Incivility and Well-Being (Hypothesis 1). ................................ 130
Table 10: Relationship between Workplace Demands and Negative Social Experiences and SelfEfficacy (Hypothesis 2). ............................................................................................................. 131
Table 11: Relationship between Workplace Resources and Well-Being (Hypothesis 3). .......... 132
Table 12: Relationship between Workplace Resources and Self-Efficacy (Hypothesis 3). ....... 133
Table 13: Relationship between Role Conflict Self-Efficacy and Well-Being (Hypothesis 4). . 134
Table 14: Relationship between Workload Self-Efficacy and Well-Being (Hypothesis 4). ...... 135
Table 15: Relationship between Emotional Demands Self-Efficacy and Well-Being (Hypothesis
4). ................................................................................................................................................ 136
Table 16: Relationship between Interpersonal Conflict Self-Efficacy and Well-Being
(Hypothesis 4). ............................................................................................................................ 137
Table 17: Relationship between Incivility Self-Efficacy and Well-Being (Hypothesis 4). ........ 138
Table 18: The Mediating Role of Role Conflict Self-Efficacy in the Relationship between Role
Conflict and Well-Being (Hypothesis 5). ................................................................................... 139
vi

Table 19: The Mediating Role of Workload Self-Efficacy in the Relationship between Workload
and Well-Being (Hypothesis 5). ................................................................................................. 140
Table 20: The Mediating Role of Emotional Demands Self-Efficacy in the Relationship between
Emotional Demands and Well-Being (Hypothesis 5). ................................................................ 141
Table 21: The Mediating Role of Interpersonal Conflict Self-Efficacy in the Relationship
between Interpersonal Conflict and Well-Being (Hypothesis 5). ............................................... 142
Table 22: The Mediating Role of Incivility Self-Efficacy in the Relationship between Incivility
and Well-Being (Hypothesis 5). ................................................................................................. 143
Table 23: The Moderating Role of Job Control in the Relationship between Workplace Demands
and Experiences and Well-Being (Hypothesis 6). ...................................................................... 144
Table 24: The Moderating Role of Workplace Support in the Relationship between Workplace
Demands and Experiences and Self-Efficacy Beliefs (Hypothesis 6). ....................................... 145
Table 25: The Moderating Role of Job Control in the Relationship between Role Conflict and
Well-Being (Hypothesis 6). ........................................................................................................ 146
Table 26: The Moderating Role of Job Control in the Relationship between Workload and WellBeing (Hypothesis 6). ................................................................................................................. 147
Table 27: The Moderating Role of Job Control in the Relationship between Emotional Demands
and Well-Being (Hypothesis 6). ................................................................................................. 148
Table 28: The Moderating Role of Job Control in the Relationship between Interpersonal
Conflict and Well-Being (Hypothesis 6). ................................................................................... 149
Table 29: The Moderating Role of Job Control in the Relationship between Incivility and WellBeing (Hypothesis 6). ................................................................................................................. 150
Table 30: The Moderating Role of Workplace Support in the Relationship between Role Conflict
and Well-Being (Hypothesis 6). ................................................................................................. 151
Table 31: The Moderating Role of Workplace Support in the Relationship between Workload
and Well-Being (Hypothesis 6). ................................................................................................. 152
Table 32: The Moderating Role of Workplace Support in the Relationship between Emotional
Demands and Well-Being (Hypothesis 6). ................................................................................. 153
Table 33: The Moderating Role of Workplace Support in the Relationship between Interpersonal
Conflict and Well-Being (Hypothesis 6). ................................................................................... 154
vii

Table 34: The Moderating Role of Workplace Support in the Relationship between Incivility and
Well-Being (Hypothesis 6). ........................................................................................................ 155
Table 35: The Moderating Role of Prior SE Levels in the Relationship between Workplace
Demands and Experiences and Self-Efficacy (Hypothesis 7). ................................................... 156
Table 36: The Moderating Role of Prior SE Levels in the Relationship between Role Conflict
and Well-Being (Hypothesis 7). ................................................................................................. 157
Table 37: The Moderating Role of Prior SE Levels in the Relationship between Workload and
Well-Being (Hypothesis 7). ........................................................................................................ 158
Table 38: The Moderating Role of Prior SE Levels in the Relationship between Emotional
Demands and Well-Being (Hypothesis 7). ................................................................................. 159
Table 39: The Moderating Role of Prior SE Levels in the Relationship between Interpersonal
Conflict and Well-Being (Hypothesis 7). ................................................................................... 160
Table 40: The Moderating Role of Prior SE Levels in the Relationship between Incivility and
Well-Being (Hypothesis 7). ........................................................................................................ 161
Table 41: The Moderating Role of Coping Success in the Relationship between Workplace
Demands and Experiences and Self-Efficacy (Hypothesis 8). ................................................... 162
Table 42: The Moderating Role of Coping Success in the Relationship between Role Conflict
and Well-Being (Hypothesis 8). ................................................................................................. 163
Table 43: The Moderating Role of Coping Success in the Relationship between Workload and
Well-Being (Hypothesis 8). ........................................................................................................ 164
Table 44: The Moderating Role of Coping Success in the Relationship between Emotional
Demands and Well-Being (Hypothesis 8). ................................................................................. 165
Table 45: The Moderating Role of Coping Success in the Relationship between Interpersonal
Conflict and Well-Being (Hypothesis 8). ................................................................................... 166
Table 46: The Moderating Role of Coping Success in the Relationship between Incivility and
Well-Being (Hypothesis 8). ........................................................................................................ 167
Table 47: The Relationship of Prior Self-Efficacy Levels and Workplace Resources with Coping
Success ........................................................................................................................................ 168
Table 48: The Mediating Role of Coping Success for the Buffering Effects of Control on SelfEfficacy Outcomes (Hypothesis 9). ............................................................................................ 169
viii

Table 49: The Mediating Role of Coping Success for the Buffering Effects of Workplace
Support on Self-Efficacy Outcomes (Hypothesis 9). .................................................................. 170
Table 50: The Mediating Role of Coping Success for the Moderating Effects of Job Control on
Role Conflict (Hypothesis 10). ................................................................................................... 171
Table 51: The Mediating Role of Coping Success for the Buffering Effects of Job Control on
Workload (Hypothesis 10). ......................................................................................................... 172
Table 52: The Mediating Role of Coping Success for the Buffering Effects of Support on
Emotional Demands (Hypothesis 10). ........................................................................................ 173
Table 53: The Mediating Role of Coping Success for the Buffering Effects of Job Control on
Interpersonal Conflict (Hypothesis 10). ...................................................................................... 174
Table 54: The Mediating Role of Coping Success for the Buffering Effects of Job Control on
Incivility (Hypothesis 10). .......................................................................................................... 175
Table 55: The Mediating Role of Coping Success for the Buffering Effects of Workplace
Support on Role Conflict (Hypothesis 10).................................................................................. 176
Table 56: The Mediating Role of Coping Success for the Buffering Effects of Workplace
Support on Workload (Hypothesis 10). ...................................................................................... 177
Table 57: The Mediating Role of Coping Success for the Buffering Effects of Workplace
Support on Emotional Demands (Hypothesis 10). ..................................................................... 178
Table 58: The Mediating Role of Coping Success for the Buffering Effects of Workplace
Support on Interpersonal Conflict (Hypothesis 10). ................................................................... 179
Table 59: The Mediating Role of Coping Success for the Buffering Effects of Workplace
Support on Incivility (Hypothesis 10)......................................................................................... 180

ix

LIST OF FIGURES

Figure 1: Conceptual Representation of Hypothesized Within Person Relationships ................ 182
Figure 2: Conceptual Representation of Hypothesized Between Person Relationships ............. 183
Figure 3: Measurement of Study Variables ................................................................................ 184
Figure 4: The Moderating Effect of Job Control on the Relationship between Emotional
Demands and Emotional Demands Self-Efficacy....................................................................... 185
Figure 5: The Moderating Effect of Control on the Relationship between Interpersonal Conflict
and Interpersonal Conflict Self-Efficacy .................................................................................... 186
Figure 6: The Moderating Effect of Workplace Support on the Relationship between Workload
and Emotional Exhaustion .......................................................................................................... 187
Figure 7: The Moderating Effect of Workplace Support on the Relationship between Emotional
Demands and Emotional Exhaustion .......................................................................................... 188
Figure 8: The Moderating Effect of Workplace Support on the Relationship between Incivility
and Emotional Exhaustion .......................................................................................................... 189
Figure 9: The Moderating Effect of Workplace Support on the Relationship between Workload
and Life Satisfaction ................................................................................................................... 190
Figure 10: The Moderating Effect of Prior Self-Efficacy on the Relationship between Workload
and Experienced Strain ............................................................................................................... 191
Figure 11: The Moderating Effect of Prior Self-Efficacy on the Relationship between Workload
and Positive Affect ...................................................................................................................... 192
Figure 12: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Interpersonal Conflict and Emotional Exhaustion ...................................................................... 193
Figure 13: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Interpersonal Conflict and Affective Distress............................................................................. 194
Figure 14: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Interpersonal Conflict and Life Satisfaction ............................................................................... 195
x

Figure 15: The Moderating Effect of Prior Self-Efficacy on the Relationship between Incivility
and Positive Affect ...................................................................................................................... 196
Figure 16: The Moderating Effect of Prior Self-Efficacy on the Relationship between Incivility
and Life Satisfaction ................................................................................................................... 197
Figure 17: The Moderating Effect of Prior Self-Efficacy on the Relationship between Incivility
and Negative Affect .................................................................................................................... 198
Figure 18: The Moderating Effect of Coping Success on the Relationship between Workload and
Workload Self-Efficacy .............................................................................................................. 199
Figure 19: The Moderating Effect of Coping Success on the Relationship between Emotional
Demands and Emotional Exhaustion .......................................................................................... 200
Figure 20: The Moderating Effect of Coping Success on the Relationship between Interpersonal
Conflict and Emotional Exhaustion ............................................................................................ 201
Figure 21: The Moderating Effect of Coping Success on the Relationship between Interpersonal
Conflict and Positive Affect........................................................................................................ 202
Figure 22: The Moderating Effect of Coping Success on the Relationship between Incivility and
Positive Affect ............................................................................................................................ 203

xi

THE RELATIONSHIP OF WORK DEMANDS AND RESOURCES TO SUBJECTIVE
WELL-BEING: THE MEDIATING ROLE OF SELF-EFFICACY.

Introduction

How individuals function in the workplace has long been a main focus of organizational
behavior, and has been long linked to individual levels of subjective well-being (e.g., Diener,
Suh, Lucas, & Smith, 1999; Csikszentmihalyi, 1990). Such linkages between subjective wellbeing and workplace experiences are not surprising, as, as Judge and Klinger (2007, p. 393)
commented, “…more than half of the nonretired adult population spends most of its waking
hours at work,” thus underlining the importance of workplace experiences as a major influence
in people’s lives. Perhaps as a result, a variety of theoretical models have been put forth to
explain the circumstances under which individuals manage to cope (and even flourish) in and out
of the workplace, or, alternatively, the circumstances under which the stresses and demands of
work result in decreases in subjective well-being and the experience of strain for individuals.
Perhaps the best known and most utilized model of workplace functioning is Karasek’s
(1979) job demands-control model, which argues that adequate control over one’s job enables an
individual to avoid the strain associated with increased job demands. This model has been
expanded to include variables such as social support (Johnson & Hall, 1988) and additional types
of workplace demands and resources (Bakker & Demerouti, 2007; Demerouti, Bakker,
Nachreiner, & Schaufeli, 2001). Such models have much in common with other theoretical
approaches to the relationship between work and individual well-being, such as the personenvironment fit theory of French, Caplan, and Harrison (1982), the commonality being that all
1

these approaches implicitly or explicitly argue that individuals will indeed function better or
worse in the workplace based on the specific circumstances (which can be internal, external, or
both) that individuals find themselves in, and as a result benefit from increased levels of
subjective well-being (or, depending on the focus of the model, reduced levels of experienced
strain). In other words, these models outline characteristics of the worker (such as personality or
experienced states) and the workplace (such as workload and available resources), and explain
how these characteristics interact to determine well-being outcomes.
Indeed, research has often been supportive of this interplay between an individual’s
experiences in the workplace and some stable external or internal characteristics, demonstrating
that these models of workplace functioning can indeed be of value in explaining variance in
between- and within-individual levels of subjective well-being and experienced strain (Karasek,
1979; Landsbergis, 1988; van Vegchel, de Jonge, Söderfeldt, Dormann, & Schaufeli, 2004;
Bakker, Demerouti, & Euwema, 2005; Ilies, Dimotakis, & De Pater, 2010; Bakker, van
Veldhoven, & Xanthopoulou, 2010). Although the demands-control model has represented the
basis for much of the research into strain and subjective well-being over the last decades (van der
Doef & Maes, 1999; Cooper, Dewe, & O’Driscoll, 2001), the focal mediating mechanisms
underlying this model have received substantially less attention in the literature. Specifically,
according to the demands-control model, exposure to increased job demands under conditions of
increased control will not result in increased strain because job control will provide the employee
with in increased capabilities to cope with their work demands and higher personal efficacy
(Karasek, 1979), processes that have not been explicitly examined in the literature to an adequate
extent. Therefore, although workplace and individual factors have been empirically linked to
subjective-well-being, there is less available evidence on whether the beneficial effects of job
2

control (and other resources) actually occur as a result of increased personal self-efficacy beliefs
or through improvements in capabilities to cope, resolve and contend with daily workplace
demands and events on the part of the individual, and whether it is indeed this successful
resolution of workplace demands and events that drives reductions in strain and enhancements in
subjective well-being levels.
Moreover, this coping process is itself a dynamic phenomenon in which environmental
stimuli are appraised and evaluated by the individual, involving a complex and subtle interplay
among individual’s perceptions of their environment, and evaluations of their perceived
capabilities and capacities to cope with these stressors or events (Lazarus & Folkman, 1984;
Izard, 1993; Weiss & Cropanzano, 1996). Although these latter self-evaluations have a
recognized role in the coping process through their influence on appraisal processes (Lazarus &
Folkman, 1984; Folkman, Lazarus, Gruen, & DeLongis, 1986), less attention has been paid
towards the ways by which one’s successes or failures in coping with daily experiences can
inform or affect subsequent self-evaluations (specifically, self-efficacy), even though the role of
success or failure in daily coping would seem to be central to the ways in which these
evaluations are formed (Bandura, 1977; Bandura, 1997), Moreover, as these self-evaluations
have been found to represent an important aspect of individual workplace experience (Siegrist,
2004), an investigation of how they fluctuate as a result of workplace experiences and how they
affect individual functioning as a result could be of value.
Therefore, a comprehensive effort aiming to examine how the successful or unsuccessful
handling of workplace events and demands affects individuals’ self-evaluations and subjective
well-being levels can be of help to the literature by illuminating the interactions among these
important components of daily life, thus providing theoretical and empirical evidence for the
3

specific ways in which various workplace functioning models actually operate. Moreover,
examining these processes and their role in influencing the effects of workplace events on
individuals’ daily lives can provide valuable insights on how work can affect the life experiences
of individuals, thus providing an important contribution to our understanding of how subjective
well-being levels fluctuate as a result of reactions to workplace demands and experiences.
Below, I describe a study intended to examine the effects of workplace experiences by
investigating how the successful resolution of, or coping with, daily events and work demands
affects individual levels of subjective well-being, and how self-efficacy beliefs can serve to
influence and affect the ways in which individuals cope and function in the workplace, as well as
their levels of experienced well-being. Furthermore, I investigate these processes in a
longitudinal manner, to provide a more comprehensive examination of how the consequences of
an individual’s efforts to deal with daily demands and events can affect their functioning on
subsequent days. Such an approach can extend our conceptualization of the effects of work
demands and experiences from within-day only effects to a more nuanced representation in
which the consequences of what the employee experiences on a given workday can carry over to
subsequent days, thus taking into consideration accumulation or spillover processes and their
potentially important effects.
Contributions
My dissertation aims to provide a contribution to the literature in a number of ways. First,
it aims to demonstrate how dealing with the daily demands of individuals’ work environment can
influence their level of experienced subjective-well-being, thus outlining how experiences in this
very important life domain can affect the daily functioning of employees. Second, this study
seeks to illuminate the internal psychological processes underlying the linkages between
4

workplace experiences and subjective well-being by proposing that self-evaluation judgments
(specifically, the self-efficacy beliefs individuals hold with regards to their capabilities to
effectively function in the workplace) represent an important mediating mechanism in the
relationship between work and subjective well-being, and by testing this proposition in a
longitudinal design that includes measurements both at work and at home. Third, it explicitly
examines the success of the coping strategies utilized by employees as a central factor in models
of workplace functioning, and directly tests its importance for individual well-being. Finally, it
examines how workplace resources and fluctuations in self-evaluations can moderate the
relationship among workplace resources and well-being, and how workplace resources and prior
self-efficacy beliefs can influence the coping capabilities of individuals on subsequent days,
therefore outlining and testing an additional linking mechanism that can illuminate the
relationships among self-evaluations, coping, and well-being over time.
These efforts can inform and extend current models of how individuals cope in the
workplace and what this means for their subjective well-being by providing a comprehensive
examination of workplace functioning processes, and by studying how these processes influence
subjective well-being levels within and across days, as well as within- and between-individuals.
The methodology used in this study can also provide a contribution to the literature by answering
the call of Diener, Oishi, and Lucas (2003) for an increase in examinations of well-being that go
beyond cross-sectional, one-time assessments of subjective well-being, and for research into the
processes by which individuals respond to experiences in their environment.
Finally, apart from the potential empirical and theoretical contributions this study can
provide, the findings of this study can also be of interest to practitioners aiming to improve the
workplace experiences and subjective well-being of employees; such efforts can be of potential
5

benefit to organizations through the associations of subjective well-being with important
organizational factors such as employee health (Faragher, Cass, & Cooper, 2005), and
performance (Petty, McGee, & Cavender, 1984; Warr, 1999; Harter, Schmidt, & Keyes, 2003;
Russell, 2008). Similarly, these findings can be of direct benefit to individuals as well, as wellbeing has been recognized as a “necessary, but not sufficient, characteristic of the good society
and the good life” (Diener et al., 2003, p. 405) and is associated with a host of important
individual-level outcomes (Lyubomirsky et al., 2001).
Overview
In order to test my research questions, I will proceed as follows. First, I will review the
pertinent empirical and theoretical literature linking workplace events and demands, subjective
well-being, and self-efficacy. Second, I will present my general model, and outline specific
hypotheses to be tested. Third, I will describe the overall design of the study I aim to use to
empirically test these hypotheses, including the study procedure, measures and analytical
strategies to be used. Fourth, I will describe the results of these analytical strategies, and provide
a detailed examination of the testing of my proposed formal hypotheses. Finally, I will present a
discussion of the implications of my findings for theory and research, as well as the practical
implications for employees and organizations.

6

Literature Review

Subjective Well-Being
Subjective well-being has been a frequent subject of research in psychology and
organizational behavior in the last few decades (Wilson, 1967; Diener et al., 1999; Diener et al.,
2003). Diener (1984) categorized research in subjective well-being in two broad categories,
namely top-down and bottom-up approaches. In top-down approaches, subjective well-being is
considered to be the product of stable individual differences (such as personality traits), which
influence the way in which individuals perceive the world, react to events, and form judgments
about their levels of happiness. On the other hand, bottom-up approaches argue that these
judgments are the results of the cumulative effects of the events, outcomes, and satisfaction in
the various life domains of individuals, thus influencing well-being through the accumulation of
momentary experiences (Diener, 1984; Diener et al., 2003).
Both these approaches have produced important findings that have advanced our
understanding of subjective well-being (Heller, Watson, & Ilies, 2004), shedding light on some
of the “immense number of factors” (Diener, 1984, p. 561) that can have an influence on this
vital phenomenon. The top-down approach has consistently demonstrated the important role that
individual differences can play in influencing subjective well-being levels (Deneve & Cooper,
1998; Judge, Heller, & Mount, 2002; Steel, Schmidt, & Schultz; 2008), while the bottom-up
approach has similarly produced findings that support a relationship between experienced events,
domain (e.g., job or marital) satisfactions, and subjective well-being (Diener, 1984; Suh, Diener,
& Fujita, 1996; Pavot, Diener, & Fujita, 1990; Weiss, Nicholas, & Daus, 1999).
7

Research on subjective well-being, however, has mostly focused on between-individual
differences (Judge et al., 2002), while experiential and episodic approaches have been relatively
neglected (Ilies et al., 2010). In an effort to address this, research on well-being has been recently
enhanced by a within-individual research stream that utilizes episodic, momentary, and
longitudinal conceptualizations in order to investigate the daily lives of employees, aiming to
examine how the events and experiences from individuals’ workplaces can influence and inform
their levels of subjective well-being both in and out of work. These efforts compliment previous
bottom-up processes that demonstrated the relationship between domain satisfactions by directly
and dynamically linking what the individual experiences to how the individual feels, and by
outlining boundary conditions that enhance or diminish this relationship.
Such within-individual approaches that investigate the effects of work experiences and
events on individual functioning are well-positioned to answer the calls for an increased focus on
explaining the specific processes that can link within-and between-person factors and
experienced well-being (Heller et al., 2003; Heller, Watson, & Ilies, 2006). Focusing on work as
a context in which such processes take place, I will review the relevant conceptual and empirical
literature based on two theoretical conceptualizations which are well-positioned to elucidate such
processes. These theoretical efforts consist of (a) the demands-control model (and its expanded
conceptualizations; Karasek, 1979; Johnson & Hall, 1988; Bakker & Demerouti, 2007), and (b)
the self-efficacy component of social cognitive theory (Bandura, 1997). In order to provide clear
linkages between the demands-control model and self-efficacy, I utilize the transactional model
of stress (Lazarus & Folkman, 1984) as a framework for understanding the ways individuals
perceive and react to the demands of their environment, as well as how this can affect their levels
of subjective well-being and experienced strain.
8

The Demands-Control Model and Theoretical Extensions
The demands-control model posits that there is an interactive relationship between the
demands of a job and the control (or decision latitude) that an individual can exercise in
addressing his or her work responsibilities such that when control is low, high job demands will
lead to strain; high control, on the other hand, can result in less negative or even positive
outcomes for an employee facing high job demands (Karasek, 1979; Karasek & Theorell, 1990).
The two factors in the model are thus seen as “the instigators of action (work load demands,
conflicts or other stressors, which place the individual in a motivated or energized state of
“stress”) and the constraints on the alternative resulting actions” (Karasek, 1979, p. 287). When
this energized state fails to result in success in dealing with job demands (a situation that can be
more common when individuals lack the job control they need to be successful), individuals tend
to experience decreased levels of subjective well-being (manifested as increased strain). On the
other hand, when this energized state leads to success in dealing with job demands, then the
accumulation of strain is reduced, and individual learning and growth is expected to increase.
This model was extended by Johnson and Hall (1988), who found that available social
support at work can also attenuate the relationship between high job demands and increased
strain; Ilies et al. (2010) found that perceived organizational support (Eisenberger, Huntington,
Hutchison, & Sowa, 1983) can also represent an important source of support for the employee.
Bakker and colleagues (Demerouti et al., 2001; Bakker & Demerouti, 2007) have argued for a
more comprehensive approach that considers autonomy, support and other buffering mechanisms
as job or personal resources that can help protect the individual from the effects of work
demands in general.

9

The demands-control model has been the basis for much of the research on employee
strain in the last few decades (van der Doef & Maes, 1999; Cooper et al., 2001). Most of this
research, however, has focused mainly on examining the basic propositions of the model, testing
the additive and interactive effects of the demands of an individuals’ workplace and the
resources the individual has on his or her level of subjective well-being, but putting much less
emphasis on examining the processes that could explain these additive or interactive effects. That
is, research examining and testing the mechanisms linking the interaction between demands and
control to experienced strain has been pursued to a much lesser extent. According to Karasek
(1979), job control is expected to mitigate the effects on high job demands because such control
allows individuals to better cope with their work environment; in turn, this enhanced coping can
result in increases in personal efficacy beliefs relative to workplace functioning, providing
valuable outcomes to the individual. That is, when individuals possess the resources they require
to effectively deal with the demands of their workplace, they can be more likely to succeed in
coping with these demands, and this successful coping can result in less accumulated strain and
improved perceptions of their capabilities to deal with future demands. Therefore, the
improvements in functioning under high demands that workplace resources provide for the
individual can result in increased well-being both directly and indirectly, through enhancements
in self-efficacy beliefs. Below, I will describe how these efficacy beliefs can be formed, and why
they are expected to relate to individual levels of subjective well-being.
Self-Efficacy
Perceived self-efficacy “refers to beliefs in one’s capabilities to organize and execute the
courses of action required to produce given attainments” (Bandura, 1997, p. 3; emphasis in the
original). Such beliefs operate as a central factor in human functioning (Bandura, 1986), and
10

their impact on individual outcomes can have the potential to be both positive and negative
(Bandura, 1986; Bandura & Wood, 1989). This centrality of self-efficacy beliefs occurs because
these beliefs can strongly influence the way people perceive their daily experience and their
capabilities to cope (Lazarus & Folkman, 1984; Izard, 1993). According to the transactional
model of stress (Lazarus & Folkman, 1984), exposure to a potential stressor is followed by two
cognitive appraisal processes, and it is the outcomes of these processes that can influence the
behavioral responses individuals will have to the experienced stressor, and ultimately affect
individual levels of well-being and strain. Primary appraisal processes determine whether the
individual will consider the stressor to be benign, threatening, or challenging; on the other hand,
once a stressor is appraised as threatening or challenging, secondary appraisal processes involve
evaluating “what might and can be done” (Lazarus & Folkman, 1984, p. 35). Self-efficacy
beliefs can provide information during both appraisal processes. During primary appraisal,
higher self-efficacy makes it more likely that a stressor would be evaluated as non-threatening.
During the secondary appraisal processes, self-efficacy beliefs can play a potentially more
important role, as the confidence one has in successfully performing the actions that might be
required to resolve the stressor will determine what behaviors are manifested, and the degree of
effort that the individual will feel motivated to exert in said behaviors.
That is, self-efficacy can influence both whether an event or an experience will be
considered as stressful or threatening by an individual, as well as whether the individual will
perceive themselves as capable of dealing with it successfully; these two processes can
collectively relate to individuals’ behavior, functioning, and perceptions of daily experience.
Individuals in a non-efficacious state will perceive more stimuli as potentially threatening, and
will judge themselves less capable of successfully coping with their environment; the individual
11

is thus exposed to a greater amount of potential strain, and is also less likely to undertake the
actions that could successfully address or alleviate the source of this strain.
Self-efficacy beliefs are formed through four main processes (Bandura, 1986). Mastery
experiences refer to the experience of success or failure in a task, which in turn increases and
decreases self-efficacy, respectively. In other words, success or failure at a task directly provides
information to the individual about their capabilities with regards to this task, and thus their selfefficacy beliefs change to reflect their new level of confidence. Vicarious experiences refer to the
experience of someone else’s success or failure, which carries similar effects as mastery
experiences. In this case, the individual uses someone else’s experiences as information,
information that becomes more salient the more similar the target and context under observation
are to the individual and their own context. Social persuasion is a process by which individuals’
self-efficacy beliefs can be influenced by others, both positively and negatively. In this case, the
individual’s social environment can provide positive or negative cues that signal to the individual
that they should or should not be confident in their abilities to deal with the focal actions.
Finally, physiological states reflect the way individuals consider processes such as emotional
arousal and fear judgments when forming self-efficacy judgments; heightened fear, for example,
would result in decreased efficacy beliefs as individuals appraised their emotion as relevant
information for their capabilities in dealing with the current context (Bandura, 1986; Bandura,
1997).
Of these four functions, mastery experiences are the most relevant function in
examinations of daily functioning in the workplace; the workplace represents one of the main
contexts in which individuals can form beliefs about their self-efficacy levels based on their
success in coping with the demands of the work. That is, the experience of dealing with work
12

demands successfully or unsuccessfully represents an archetypal example of mastery experiences
which can then inform individual self-efficacy beliefs about workplace functioning. This
formation of self-efficacy beliefs due to the experience of success or failure in the workplace
represents a process that self-efficacy and work-demands models have in common, and can thus
provide an interface by which these approaches can be theoretically combined.
Nevertheless, social persuasion processes can also be important factors when considering
the social environment in the workplace, which provides opportunities for individuals’
coworkers to have either a positive impact (for example, by providing encouragement and
support) or a negative one (through acts such as bullying or non-constructive criticism).
Similarly, physiological states can also provide self-efficacy information in the workplace, where
the anxiety or negative affect created by workload (for example, see Ilies, Schwind, Wagner,
Johnson, DeRue, & Ilgen, 2007) can reduce individual confidence in successfully dealing with
the demands of the work environment.
The Role of Coping
Coping has been long recognized as an important aspect of individual functioning, and
has important implications for individuals’ levels of strain and subjective well-being (Lazarus &
Folkman, 1984). Coping has been defined as the “constantly changing cognitive and behavioral
efforts” that individuals engage in order to manage the demands of their situation (Lazarus &
Folkman, 1984, p. 141). Despite the important role coping plays for individual well-being,
however, most investigations of coping in the psychology literature have focused on static
examinations of coping, examining the behaviors that individuals engage in on average, thus
limiting our knowledge of how individuals change their coping efforts in reaction to their
environment.
13

Moreover, as mentioned above, most research tends to focus on the types of coping
behaviors that individuals engage in order to contend with the demands of their lives (see, for
example, Jex, Bliese, Buzzell, & Primeau, 2001; Elfering, Grebner, Semmer, KaiserFreiburghaus, Lauper-Del Ponte, & Witschi, 2005; Shoji, Harrigan, Woll, & Miller, 2010). These
efforts aim to distinguish between various types of coping (for example, active, passive, and
avoidance coping) and to examine the differential impact of these various coping types on
individual levels of subjective well-being and experienced strain.
While these efforts have provided important insights on the average differential
effectiveness of various types of coping behaviors, investigations on the actual effects of success
in coping with workplace demands and experiences have been relatively neglected, as have
examinations that conceptualize these processes dynamically instead of statically. The few extant
investigations of coping success, however, have provided some evidence for the role of coping
success and the need to study such processes further in a way that takes their adaptive character
into consideration. For example, Zautra and Wrabetz (1991) demonstrated that coping success
was related to lower levels of psychological distress in a sample of older adults, while the
adaptive and dynamic nature of coping processes has been underlined in conceptual work, as has
the need for investigations that take these characteristics of coping into consideration (Neufeld,
1999).
Below, I will review the empirical literature discussing the links among job demands, job
control, workplace support, self-efficacy, coping, and subjective well-being. Specifically, I will
outline the theoretical and empirical linkages between (a) job demands, workplace resources and
subjective well-being, (b) job demands, workplace resources and self-efficacy, (c) self-efficacy

14

and subjective well-being, and (d) coping and subjective well-being. In each case, I will also
provide a review of the pertinent moderating factors in these processes.
Workplace Demands and Subjective Well-Being
Job demands (defined in a variety of ways, such as high levels of workload, emotional
labor, and role conflict; for example, see Parasuraman & Cleek, 1984; Fillion, Tremblay,
Truchon, Côté, Struthers, and Depuis, 2007; Ilies et al., 2010), have been long linked to
subjective well-being outcomes. While characteristics of the job such as workload are ubiquitous
and an expected part of the job, theoretical and empirical work has long argued and found that
increased levels of any demand can be linked to decreases in subjective well-being. Workload
and role conflict have been found to be among the most commonly reported workplace stressors
(Axelrod & Gavin, 1980; Nandram & Klandermans, 1993), and the emotional demands of an
individual’s workplace have been recently suggested to be another important factor in
investigations of individual well-being (Grandey, 2000). Furthermore, negative social
experiences can represent one more category of work demands that can relate to individual wellbeing (Lim & Cortina, 2005; Ilies et al., 2010).
Conceptually, the effects of these work demands can occur through a number of
pathways. Accumulations of high workload levels can result in overload, taxing the individuals’
capabilities to deal with them effectively (Ilies et al., 2010). The emotional demands of the work
require attitudinal and motivational resources (Grandey, 2000) that might tax individual energy
reserves, while role conflict is associated with hard-to-resolve situations, thus exposing the
individual to accumulating and persistent stressors that could likely result in experienced strain
(Axelrod & Gavin, 1980). Similarly, negative social experiences such as workplace incivility or
interpersonal conflict, apart from their effects as pure workplace stressors, can also impact
15

individuals through their negative effects on the satisfaction of relatedness needs (Baumeister &
Leary, 1995; Ryan & Deci, 2000).
In general, individuals’ exposure to these workplace stressors is expected to be associated
with a physiological state of arousal in which the individual is recruiting resources to deal with
the demands of the situation at hand (Lazarus, 1999), resources that are then unavailable for
other psychological or physiological processes, including the maintenance of subjective wellbeing levels. This draining of personal resources can then manifest as increased strain and
reduced subjective well-being, either directly (through resource depletion, anxiety, or
exhaustion) or indirectly (by reducing the capabilities of individuals to cope with other stressors,
thus leading to accumulations of strain and reductions in subjective well-being.
Empirically, the literature is generally supportive of a negative relationship between the
work demands (conceptualized in various ways, including various types of workplace
experiences and stressors) placed upon the individual and employee well-being (Ganster &
Schaubroeck, 1991; Sonnentag & Frese, 2003). These negative effects of workplace demands on
subjective well-being can even persist even after the individual’s exposure to them has ended,
underlining the persistent character of this relationship (e.g., Repetti, 1993). Furthermore, the
relationship between demands and well-being has been shown to persist even after controlling
for other relevant predictors of subjective well-being such as neuroticism, gender, age, academic
accomplishment, childhood socioeconomic status (de Jonge, Dormann, Jannsen, Dollard,
Landeweerd, & Nijhuis, 2001; Elovainio et al., 2007; Conard & Matthews, 2008). Below, I
provide a short review of the empirical literature discussing these linkages.
In terms of cross-sectional analyses, a variety of large-scale studies has been supportive
of a negative relationship between job demands and subjective well-being (or experienced
16

strain). Specifically, a study conducted as part of the Northern Finland 1966 Birth Cohort Study
found an association between job demands and psychological distress in a sample of 4,293
individuals (Elovainio et al., 2007), while Pelfrene, Vlerick, Kittel, Mak, Kornitzer, and De
Backer (2002) found a positive relationship between job demands and low subjective well-being
(conceptualized as depression) in a sample of 21,419 adult respondents in Belgium. Similar
results were reported by Peeters, Montgomery, Bakker, and Schaufeli (2005) in a sample of
1,264 Dutch adults, who found that job demands (conceptualized as a combination of
quantitative, emotional and mental demands) were associated with decreased subjective wellbeing (conceptualized as burnout). Furthermore, Lang, Thomas, Bliese, and Adler (2007) also
reported a positive and significant relationship between job demands and psychological strain in
a sample of 1,418 army cadets undergoing ROTC training. Karasek, Triantis, and Chaudhry
(1982) found that task demands were significantly and positively associated with reports of
mental strain in a sample of 1,016 male workers in the US, and a similar pattern of results was
reported by Karasek, Gardell, and Lindell (1987), who found that higher levels of workload were
associated with increased levels of mental strain symptoms. Finally, Tummers, van Merode,
Landeweerd, and Candel (2003), in a study of 1,721 nurses nested within 15 hospital
organizations, reported that work demands were significantly associated with increased levels of
strain.
Smaller scale studies have provided similar indications of workplace support for the
relationship between work demands and subjective well-being. Fillion et al. (2007), in an
examination involving 209 palliative care nurses, found that job and emotional demands were
associated with decreased subjective well-being (conceptualized as decreased job satisfaction
and increased emotional distress). Furthermore, Jannsen, Peeters, de Jonge, Houkes, and
17

Tummers (2004), reporting the results of a study of 115 US and 260 Dutch nurses and nurse
assistants found that job demands were associated with decreased subjective well-being (defined
as increased emotional exhaustion). Comparable results were reported by Tse, Flin, and Mearns
(2007) in a study of 186 bus drivers.
Longitudinal studies have provided additional evidence for this relationship, in both
between- and within-people investigations. In a 2-year longitudinal study of 820 truck drivers in
the Netherlands, de Croon, Sluiter, Blonk, Broersen, and Frings-Dresen (2004) found that job
demands were associated with increased experiences of work strain (measured as perceived need
for recovery). Similarly, de Jonge et al., (2001), using a sample of 261 health care professionals,
found that job demands were negatively associated with psychological well-being one year later.
Likewise, Ilies et al., (2007), in a two-week long within-individual examination involving
106 participants, found that on days in which individuals reported increased levels of work
demands (conceptualized as workload), they also reported increased feelings of negative affect at
home (a component of subjective well-being; Diener et al., 2003). A comparable pattern of
results was reported by Repetti (1993) in a within-individual examination of 52 air traffic
controllers; results indicated that days with increased workload were associated with decreased
positive and increased negative mood, and a similar effect was found on days in which
participants reported experiencing more negative interactions with coworkers. Similarly,
Teuchmann, Totterdell, and Parker (1999) reported a significant event-level within-individual
association of job demands with mood and emotional exhaustion. Using a lengthier but sparser
measurement schedule, in which 65 portfolio workers were asked to provide weekly diaries for a
total of 26 weeks, Totterdell, Wood, and Wall (2006) also found a positive association between
work demands and experienced strain.
18

The demands of work are not necessarily represented by a unidimensional construct,
however. Indeed, work demands encompass a variety of different factors that individuals need to
contend with, and investigations focusing on these specific categories of work demands have
been equally supportive of a negative relationship between individual facets or aspects of
workplace demands and subjective well-being. Of these specific categories or aspects, a high
level of workload has been found to be among the most significant predictors of subjective wellbeing and experienced strain. For example, Jin, Yeung, Tang, and Low (2008) identified high
levels of workload as the strongest predictor of the stress sources examined in their study, and
found that workload levels were significantly associated with increased strain (conceptualized as
psychosomatic symptoms) in a sample of 261 teachers in Hong Kong. Similarly, workload was
found to be associated with well-being (measured as life satisfaction) in an investigation
involving a sample of 371 full time workers reported by De Cuyper and De Witte (2006),
although these authors also reported that these results did not replicate in a subsample of 189
temporary workers. Furthermore, Van Emmerik, and Jawahar (2006) reported an association
between workload and negative mood in a sample of 629 dual-earner couples, while Ilies et al.
(2010), in a within-individual examination of 64 clerical and administrative workers, found that
on days when individuals reported higher than usual work demands, they also tended to report
decreased subjective-well-being (defined as increased psychological strain measured at home).
Finally, Lee and Ashforth (1996), in a meta-analytic examination of the correlates of job
burnout, reported a positive relationship between workload and emotional exhaustion (k = 6; N =
1,450; ρ = .65).
Workload is not the only important facet of work demands, however. The emotional
demands of an individual’s job have also been linked to subjective well-being outcomes. For
19

example, in an investigation of 238 full time employees, Brotheridge and Grandey (2002) found
that (surface level) emotional labor was significantly associated with decreased well-being
(operationalized as high burnout). Similarly, Tschan, Rochat, and Zapf (2005) found a
relationship between emotional demands and well-being in a within-people investigation
involving 78 employees in service and non-service professions that provided measures about 848
separate workplace interactions. Likewise, in a 1-year time interval longitudinal study involving
2,255 employees in Sweden, van Vegchel et al. (2004) found that emotional demands were
significantly associated with experienced strain (conceptualized as emotional exhaustion).
Moreover, emotional demands have been found to be independently associated with subjective
well-being when considered concurrently with other types of workplace demands. For example,
Montgomery, Panagopoulou, and Benos (2006) found that emotional demands were associated
with decreased levels of subjective well-being in a sample of 162 doctors in Greece, and these
effects held when controlling for the effects of quantitative job demands, and Ilies, Dimotakis
and Wang (2010) found that high levels of emotional demands and workload were independently
associated with emotional burnout in a three-week within-individual examination involving 120
clerical and administrative workers employed in a public university.
Empirical work has also been supportive of the importance of role demands in predicting
individuals’ subjective well-being. In one of the earlier investigations of such demands, Hamner
and Tosi (1974) reported a significant correlation (r = .27) between role conflict and perceptions
of anxiety in a sample of 61 high-level managers. Similarly, Bedeian and Armenakis (1981)
found that role demands were associated with increased perceptions of workplace tension and
reduced job satisfaction in an investigation of 460 employees of a nursing organization, while
Greenhaus, Bedeian, and Mossholder (1987) found that role conflict was associated with
20

decreased perceptions of the quality of participants’ life in a sample of 336 accountants.
Furthermore, Coverman (1989) provided evidence for an association of role conflict with job
satisfaction in a national probability sample that included 1,515 employed respondents, while
Fried and Tiegs (1993) found that role conflict was positively associated with increased
emotional exhaustion. In general, role conflict has been shown to be an important predictor of
individual well-being outcomes, and recent meta-analytic efforts have been supportive of this
effect (Fischer & Gitelson, 1983; Lee & Ashforth, 1996; Örtqvist & Wincent, 2006). This
relationship between role demands and subjective well-being has been found to persist even
when role demands are considered concurrently with other important workplace demands such as
high levels of workload; for example, Parasuraman and Cleek (1984) found that role conflict was
associated with increased experienced stress and reduced job satisfaction even controlling for
quantitative and qualitative work overload.
Finally, negative social experiences such as interpersonal conflict or workplace incivility
have also been empirically examined as one important category of workplace demands, insofar
as these social experiences represent salient events experienced as part of the job. In this
conceptualization, negative social experiences can comprise a component of the work to the
same extent as high emotional demands or workload. In terms of their effects on subjective wellbeing, the literature is supportive of the significant and negative component of this relationship.
For example, Ilies, Johnson, Judge, and Keeney (2011), in a two-week experience sampling
study involving 49 employees surveyed over a two-week period, found that the experience of
interpersonal conflict at work was associated with increased negative affect within-individuals.
Similarly, Frone (2000) found that interpersonal conflict at work was associated with decreased
job satisfaction and increased feelings of depression in a sample of 319 younger workers, while
21

Lazuras, Rodafinos, Matsiggos, and Stamatoulakis (2009) found that interpersonal conflict was
associated with decreased physical well-being in a sample of 764 telecommunication employees.
In a within-individual investigation of workplace interactions involving 60 clerical and
administrative employees, Dimotakis, Scott, and Koopman (2010) found that on days in which
employees described their workplace interactions as more negative (a conceptualization that
included interpersonal conflict as a component), employees also reported increased negative
affect and decreased job satisfaction at the end of the workday. Similar effects of interpersonal
conflict experiences on individual well-being have been reported by Harvey, Blouin, and Stout
(2006) and Liu, Spector, and Shi (2007). Finally, Kamarck, Shiffman, Smithline, Goodie, Paty,
Gnys, and Jong (1998) found that interpersonal conflict was associated with increased negative
affect in a sample of 120 individuals.
Although workplace incivility has only recently begun to be examined in the literature,
there is some evidence suggesting that workplace incivility can be another factor with important
implications for well-being outcomes. In a large sample study that included 1,180 public-sector
employees, Cortina, Magley, Williams, and Langhout (2001) found that increased experiences of
workplace incivility were associated with decreased job satisfaction and increased psychological
distress. Furthermore, Lim and Cortina (2005), in a paper reporting the results of two studies
involving a total of 2,258 employees, found that the experience of workplace incivility was
associated with increased job stress, and reduced work and life satisfaction. Similarly, MinerRubino and Cortina (2007), in a study involving 871 women and 831 men, found that incivility
had a zero-order association with reduced psychological well-being and job satisfaction, as well
as with increased job burnout. In their final structural model, where experienced incivility was
entered as a control, incivility was associated with both psychological well-being and job
22

satisfaction, and these effects were invariant by gender. Finally, Lim, Cortina, and Magley
(2008) found that incivility was associated with decreased mental health in a study of 1,158
employees, and these effects held when controlling for general levels of work stress.
Workplace Resources and Subjective Well-Being
In addition to the well-established negative linear relationship between various workplace
demands and subjective well-being, a number of approaches have investigated the positive
effects of various workplace resources on individual well-being. Workplace resources such as
increased job control and perceived social and organizational support have been shown to
enhance employee subjective well-being and reduce experienced strain. These effects have been
found for a variety of workplace resources, among which the most central ones are the amount of
autonomy or discretion an individual has over their job (job control) and the availability of
workplace support (from such sources as coworkers, supervisors, and the organization in
general). In general, these resources can help individuals perceive their work environment as
safer and less threatening, thus reducing the chance that work demands will be appraised as a
stressor (Lazarus & Folkman, 1984). Moreover, workplace resources can relate to intrinsic
human needs such as the need for autonomy or relatedness (Ryan & Deci, 2000), thus directly
enhancing individual well-being through the satisfaction of these aforementioned needs.
The available empirical evidence is strongly supportive of a main effect of workplace
resources on individuals’ subjective well-being. In terms of the relationship between job control
and subjective well-being, Ippolito, Adler, Thomas, Litz, and Hölzl (2005) found a significant
and positive relationship between job control and psychological well-being in a sample of 638
deployed soldiers, while Totterdell et al. (2006) found that job control was associated with
decreased feelings of anxiety in a 26-week study involving 65 portfolio workers. Similarly,
23

Holman and Wall (2002), reporting the results of two cross-sectional and one longitudinal study
of call center employees, found that increased job control was associated with decreased feelings
of anxiety and depression, while a similar relationship between job control and state anxiety was
found by Elsass and Veiga (1997) in a sample of 316 health care workers. Liu et al. (2007)
reported that job control was positively associated with job satisfaction and negatively associated
with feelings of frustrations in both a US and a Chinese sample, while Kamarck et al. (1998)
found that job control was associated with decreased levels of negative affect as well as weakly
related to cardiovascular indexes of strain.
The presence or absence of workplace support has also been found to relate to important
well-being outcomes. In a sample of 3,725 navy personnel, La Rocco and Jones (1978) found
that workplace support was associated with increased job satisfaction and individual self-esteem,
while Schirmer and Lopez (2001) found that supervisor support was related to increased job
satisfaction in a sample of 117 university employees. A similar finding was reported by Karasek
et al. (1982), who found that individuals who reported having higher levels of available social
support tended to also report decreased levels of reported mental strain. In a two-wave
longitudinal study involving 261 health care professionals, de Jonge et al. (2001) found that
perceived workplace support was associated with increased satisfaction with work one year later.
Furthermore, Bourbonnais, Comeau, and Vézina (1999) reported that having higher levels of
available social support was associated with decreased emotional exhaustion and experienced
strain in a nursing sample, while Scheck, Kinicki, and Davy (1997) found that the presence of
instrumental and emotional social support were associated with increased well-being and
reduced strain, respectively, in a sample of 218 employees. Utilizing a more general
conceptualization of well-being, Ganster, Fusilier, and Mayes (1986) found that the availability
24

of social support in the workplace (provided from either coworkers or supervisors) was
associated with a variety of subjective well-being outcomes (including job and life satisfaction
and depression) in a canonical analysis. Similarly, Canivet, Östergren, Lindeberg, Choi, Karasek,
Moghaddassi and Isacsson (2010) found that a lack of social support was associated with
increased feelings of exhaustion in a sample of 5,461 employed individuals in Sweden. Finally,
meta-analytic evidence has provided additional confirmatory evidence for the main effects of
social support availability on subjective well-being (see Viswesvaran, Sanchez, and Fisher,
1999).
In terms of perceived organizational support, in a meta-analytic review of the literature,
Rhoades and Eisenberger (2002) found that perceived organizational support was negatively
related to individual levels of strain (k = 5, N = 874, ρ = -.32) and positively related to job
satisfaction and positive affect experienced at work (k = 21, N = 5,886, ρ = .62, and k = 5, N =
1,420 ρ = .49, respectively). Furthermore, Richardson, Yang, Vandenberg, DeJoy and Wilson
(2007) found that perceived organizational support was associated with enhanced subjective
well-being (defined as decreased depressive symptoms) across two different regional samples,
totaling 1,599 individuals.
Moreover, these workplace resources have been previously found to be independently
associated with subjective well-being in examinations that estimated their effects concurrently.
For example, Parkes, Mendham, and von Rabenau (1994) found that job control (operationalized
as discretion) and social support availability were both positively and independently associated
with employee job satisfaction in a sample of 145 health care workers. This finding provides
additional motivation for a concurrent examination of these workplace resources in order to
provide a more comprehensive view of the factors that can enhance individual well-being.
25

The Moderating Role of Workplace Resources
Apart from the direct effects of workplace resources on employee well-being and strain,
other lines of research have examined whether these resources can indirectly impact individual
outcomes through changes in the relationship between workplace demands and well-being; this
is generally described as the buffer hypothesis. In this hypothesis, resources are thought to
provide a moderating effect, such that individuals high in job control or perceived support are
less likely to report decreases in well-being due to high job demands or negative workplace
experiences. Workplace resources can provide the individual with more options in selecting
potential coping strategies, which can help the individual respond to perceived stressors in a
more effective manner, thus reducing the impact of these stressors on individual levels of wellbeing. For example, job control can provide workload management strategies that employees can
use to manage their work demands (Ilies et al., 2010). Similarly, the availability of social and
organizational support provides more avenues for seeking emotional or instrumental help from
coworkers, supervisors and the organization in general, which the employee can use in coping
with the demands of their environment. Therefore, workplace resources are theoretically
expected to provide a moderating effect on the relationship between work demands and
individual levels of well-being (Karasek, 1979; Johnson & Hall, 1988; Bakker & Demerouti,
2007).
However, evidence for this moderating effect has been mixed (see De Jonge & Kompier,
1997; Van der Doef & Maes, 1999; De Lange, Taris, Kompier, Houtman, & Bongers, 2003).
Some recent support for this contention has been found by Ilies et al. (2010), who demonstrated
that decision latitude and perceived organizational support moderated the effects of workload on
experienced affective distress, such that this relationship was weaker for individuals who
26

reported having higher levels of decision latitude or perceived organizational support, compared
to those who reported having lower levels of decision latitude or perceived organizational
support. Similarly, Bakker et al. (2005), in a study of 1,000 employees of a higher education
organization, found that resources such as autonomy, available social support and a positive
relationship with one’s supervisor reduced the magnitude of the relationship between various
work demands and decreased well-being. These findings are in line with previous work, such as
Landsbergis’ (1988) examination of 771 hospital and nursing home employees, which found that
high workloads combined with low decision latitude were associated with decreased subjective
well-being, a relationship that persisted after controlling for a variety of work and demographic
variables.
Similarly, Van Vegchel et al. (2004) also reported that that job control moderated the
relationship between emotional demands and subjective well-being (measured as emotional
exhaustion), thus providing additional support for an interactive effect between various
conceptualization of work demands and available resources. Likewise, Rau (2004), in a 24-hour
ambulatory assessment of cardiovascular functioning in a sample of 241 employees, found that
individuals with both high job demands and increased decision latitude showed a healthier
cardiovascular response pattern relative to employees occupying low-strain positions who did
have the same characteristics, a finding that she argued indicates that job demands under certain
conditions might be beneficial for the well-being of individuals.
Furthermore, in a longitudinal investigation of 90 blue-collar workers, Frese (1999)
found that the presence of social support moderated the relationship between social stressors and
psychological dysfunction, such that for individuals who reported receiving higher levels of
social support, increased social stressors did not result in increased psychological dysfunction. A
27

similar effect was found in a within-individual investigation by Ilies et al. (2011), who reported
that the relationship between interpersonal conflict and negative affect was weaker for
individuals who reported receiving more social support, compared to individuals who reported
receiving less social support.
The availability of job resources can potentially do more than simply protect employees
from the deleterious effects of work demands. In a recent study of 12,359 employees from 148
organizations, Bakker et al. (2010) reported that when increased levels of job resources are
available to employees, increased job demands can result in positive effects on experienced wellbeing (conceptualized as task satisfaction). Moreover, a variety of additional efforts can provide
some indirect insights on the moderating effect of job resources on the relationship between
work demands and subjective well-being, through examinations of factors associated with the
latter. For example, Bishop, Enkelmann, Tong, Why, Diong, Ang, and Khader (2003) reported
that increased job control was associated with a decreased relationship between job demands and
a objective indicators of health (specifically, cardiovascular functioning), providing evidence for
an indirect moderating effect of job resources through health’s relationship with subjective wellbeing (Peiró, 2006; Wilson, 1967).
Not all empirical results were supportive of a buffering role on the part of workplace
resources; in fact, other studies have previously failed to find a moderating effect of workplace
resources on the relationship between workplace demands and well-being. For example, Spector
(1987), in a study utilizing a sample of 136 university clerical workers, reported no significant
interaction between job stressors and job control in predicting satisfaction and health-related
well-being. Similarly, Daniels and Guppy (1994), in a sample of 224 accountants reported no
moderating effects for job control (conceptualized as autonomy) or social support in the
28

relationship between work demands and psychological well-being outcomes. More research is
therefore needed to understand the role of workplace resources in moderating the relationship
between workplace demands and well-being outcomes, and in influencing individual levels of
well-being in general.
Effects of Workplace Demands and Characteristics on Self-Efficacy
As previously mentioned, individuals’ self-efficacy beliefs can be affected by a variety of
processes, including mastery experiences, social persuasion, and physiological arousal stimuli
(see Bandura, 1997). The experience of dealing with work demands, therefore, can be seen as
likely to provide information relevant to individual self-efficacy beliefs through two main
pathways. First, the degree of success or failure that individuals encounter when dealing with
workplace demands can influence their confidence about their expected future performance.
Failure to properly address work demands because of overload or experienced obstacles can
lower self-efficacy beliefs, with the opposite being true when individuals succeed in addressing
these demands. A supportive work environment can create opportunities for social persuasion, in
which supportive comments or behaviors enhance self-efficacy by creating a sense of safety and
individual worth. Finally, the experience of negative arousal states (such as anxiety, fear, or
distress) that excessive work demands or negative social experiences can create can be
interpreted by individuals as a sign that their abilities do not suffice to successfully cope with
their work environment, thus reducing their perceived efficaciousness (Bandura, 1997).
In general, empirical work has been supportive of the importance of workplace demands
and experiences in informing self-efficacy beliefs. For example, Webster, Beehr, and
Christiansen (2010) found that challenge and hindrance stressors were significantly associated
with self-efficacy levels in a sample of 143 employees from a variety of organizational settings;
29

specifically, challenge stressors predicted self-efficacy positively, and hindrance stressors
predicted self-efficacy negatively. Similarly, Taris, Kompier, De Lange, Schaufeli, and Schreurs
(2003), in study involving 876 Dutch teachers, found that job demands were negatively
associated with individuals’ level of self-efficacy beliefs.
Enhanced self-efficacy has also been linked to the presence of various positive job
characteristics such as social and organizational support mechanisms (Bandura, 2000). For
example, Xanthopoulou, Baker, Heuven, Demerouti, and Schaufeli (2008), in a sample of 44
flight attendants, found that higher levels of colleague support was positively and significantly
associated with increased self-efficacy. In a similar vein, Segrin and Taylor (2007) found that
perceptions of positive relations with others were associated with increased self-efficacy beliefs
in a sample of 703 individuals. A comparable pattern of results was reported by Xanthopoulou,
Bakker, Demerouti, and Schaufeli (2007), using a conceptualization of self-efficacy as part of a
personal resources construct. Their study found that job resources were associated with increased
perceptions of personal resources, and personal resources mediated the relationship between
characteristics of the workplace and experienced well-being (operationalized as engagement and
exhaustion). Further support is given by Martinussen, Richardsen, and Burke (2007) who found
that having higher levels of available social support was associated with increased professional
efficacy in a sample of 205 police officers in Norway. Finally, Taris et al. (2003) found that job
control was significantly associated with self-efficacy beliefs, and a similar finding was reported
by Yoon (2001).
Similarly, adverse changes to the work environment can have a negative impact on selfefficacy beliefs. For example, Parker (2003), in a 3-year quasi-experimental study involving 368
employees, reported that changes to the workplace that resulted in reduced perceptions of job
30

characteristics such as skill utilization and decision making participation were associated with
subsequent decreases in self-efficacy beliefs with regards to employee role breadth. Hecht and
Allen (2005) also found support for the view that a good fit between workplace characteristics
and the preferences or needs of an individual (focusing, in their case, on the temporal ordering of
tasks at work) were associated with increased self-efficacy and affective well-being.
There have, however, been some reports of contradictory findings in investigations of the
relationship between workplace factors and self-efficacy. For example, Parker and Sprigg (1999)
found no relationship between role-breadth self-efficacy and strain in a sample of 268
manufacturing employees in the United Kingdom. Holman and Wall (2002), in a paper reporting
the results of two cross-sectional and one longitudinal study of call-center employees, found no
relationship between workplace demands and stressors and self-efficacy beliefs. As a cautionary
note, however, these authors suggested that the general nature of the self-efficacy measure they
used was probably the result of this non-significant relationship. Jex and Gudanowski (1992)
also reported no significant relationship between workplace stressors and self-efficacy beliefs;
while their measure of was more specific than the measure of Holman and Wall (2002), the
stressors they used (role ambiguity, situational constraints, and hours worked) might not be best
examined in a cross-sectional design, as they may fluctuate significantly across workdays.
Apart from providing some evidence for the importance of considering workplace
characteristics (including workplace demands, work experiences, and characteristics of the
workplace), the above studies indicate that although these workplace characteristics can have an
impact on an individual’s self-efficacy beliefs, investigations focusing on this relationship need
to carefully consider both the required study design to be utilized in researching this relationship,
as well as temporal and measurement considerations.
31

Self-Efficacy and Subjective Well-Being
Self-efficacy beliefs are thought to relate to individual levels of subjective well-being by
increasing the perceived control that the individual has over their environment, context, and
current situation, thus transforming individual’s perceptions and affective reactions. Bandura
(1997, p. 140) states that “perceived efficacy to exercise control over potentially threatening
events plays a central role in anxiety arousal.” In general, therefore, higher levels of efficacy can
result in the individual perceiving their environment as less stressful or threatening, thus
reducing the potential of accumulation strain and resulting in higher individual levels of
subjective well-being (Lazarus & Folkman, 1984).
Previous research has been supportive of a direct link between self-efficacy beliefs and
the experience of increased subjective well-being (Bandura, 1997; Gecas, 1989; Karademas
2007). For example, Karademas (2006) found that self-efficacy beliefs were associated with
subjective well-being (operationalized using life satisfaction and depression as indicators)
experienced one month later. Furthermore, the results of this study indicated that self-efficacy
had both a direct as well as an indirect effect, operating through its association with individual
levels of optimism. In a related study, Karademas (2007) also found that self-efficacy was
associated with positive well-being (operationalized using life satisfaction, vitality and positive
affect as indicators) experienced one month later, while Schwerdtfeger, Konermann, and
Schönhofen (2008) found that occupation-specific self-efficacy was related to psychological
well-being (assessed with subjective reports as well as with physiological responses such as
cardiovascular variables and cortisol levels). Furthermore, Tran, Wright, and Chatters (1991)
reported that self-efficacy beliefs were associated with increased subjective well-being in a

32

sample of older individuals, replicating previous findings (Bortner & Hultsch, 1970; Campbell,
Converse, & Rodgers, 1976).
Self-efficacy has also been found to be negatively associated with indicators of low
subjective well-being such as depression and anxiety (Jex & Gudanowski, 1992). Similarly,
Fillion, et al. (2007) found that self-efficacy had a negative relationship with emotional distress
in a sample of 209 palliative-care nurses, while Holahan, Holahan, and Belk (1984) found that
self-efficacy was associated with lower levels of depression in a sample of older individuals.
Additionally, Evers, Brouwers, and Tomic (2002), utilizing a sample of 490 teachers in the
Netherlands, found that self-efficacy was significantly and negatively related to burnout, further
demonstrating that such beliefs can play a role in subjective well-being processes. Similarly,
Wilk and Moynihan (2005), utilizing a sample of 1,236 call center employees (nested within 429
supervisors), found that higher levels of self-efficacy beliefs were associated with decreased
emotional exhaustion, a component of job burnout and an indicator of low subjective well-being.
Creed, Lehmann, and Hood (2009) found that self-efficacy had a significant zero-order
relationship with psychological well-being (although this relationship became insignificant when
including other core self-evaluation variables as predictors in a multivariate model). Finally,
Fillion et al. (2007) found that self-efficacy was associated with decreased emotional distress in a
sample of 209 palliative-care nurses.
Importantly, these effects can potentially operate through multiple psychological
pathways. For example, Karademas, Kafetsios, and Sideridis (2007) demonstrated that
individuals higher in self-efficacy were less sensitive to threat stimuli, thus showing that
increased self-efficacy might be associated with more positive perceptions of the environment,
and thus a decreased potential to experience strain. Moreover, increased self-efficacy can
33

potentially enable individuals to better cope with the demands of their environment (Jex et al.,
2001). In terms of work-related functioning, a meta-analysis by Judge, Jackson, Shaw, Scott, and
Rich (2007) indicated that self-efficacy was related to at least some aspects of workplace
performance, suggesting that increased levels of this self-evaluation could indicate an increased
capacity to deal with workload and other work demands. This contention would then provide
another pathway through which self-efficacy can relate to subjective well-being and strain,
because of its association with how well individuals can perform (and thus cope with) the
requirements of their work.
In summary, self-efficacy beliefs have been found to be associated with subjective wellbeing, affecting both its positive as well as its negative indicators. Moreover, this relationship
appears to operate through a variety of pathways, further underlining the importance of including
self-efficacy in theoretical and empirical examinations of the predictors of subjective well-being.
Self-Efficacy as a Mediator and Moderator of the Relationship between Workplace
Demands and Experiences and Subjective Well-Being
Apart from investigations of the main effects of self-efficacy, other efforts have focused
on the role of self-efficacy either as a moderator of the relationships between workplace demands
and experiences and subjective well-being, or as a mediator of these relationships. In the latter
approach, self-efficacy is thought to provide an explanation for the relationship between
workplace demands and experiences and subjective-well-being outcomes. That is, excessive
levels of work demands are expected to be associated with lower levels of well-being in part
because the decreases in self-efficacy that can accompany these demands are expected to be
detrimental to individual well-being.

34

Theoretically, an individual’s self-efficacy beliefs can directly relate to the behaviors the
individual is likely to manifest in the workplace, as well as the levels of effort and persistence
that the individual is likely to muster in dealing with work demands (Bandura, 1997). In general,
higher efficacy levels will result in individuals having higher expectancies of success in
resolving workplace demands, which might make these demands seem less stressful or
threatening (via the primary appraisal processes of the transactional stress model), thus reducing
the potential for increased strain. Furthermore, self-efficacy beliefs can provide the individual
with higher levels of motivation, thus increasing the likelihood that workplace demands will be
successfully dealt with. As a result, decreases in self-efficacy can be expected to explain, at least
in part, why increased job demands can be associated with decreased well-being.
This mediating role of self-efficacy on the effects of coping processes was supported by
the results reported by Bandura, Taylor, Williams, Mefford, and Barchas (1985), who found that
experimentally increased perceptions of self-efficacy were associated with decreased adverse
physiological reactions when interacting with a phobic object (a perceived stressor). These
authors argued that increased self-efficacy provided subjects with a perception of increased
control, which in turn enabled individuals to better cope with the demands of the laboratory task
they participated in. The role of self-efficacy for personal well-being was further supported in a
laboratory study by Wiedenfeld, O’Leary, Bandura, Brown, Levine, and Raska (1990), who
reported that self-efficacy beliefs enhanced participant’s immunological system responses,
enabling them to better respond to environmental stressors. Furthermore, this mediating effect of
self-efficacy has also been found to be temporally persistent. For example, Cieslak, Benight, and
Lehman (2008) reported that self-efficacy mediated the effects of negative cognitions on distress
in two separate samples of individuals exposed to traumatic events, and these authors argued for
35

the potential of successful coping with previous events to enable individuals to better cope with
any events they currently face.
Self-efficacy has also been utilized in models of workplace functioning as a moderator of
the relationship between workplace experiences and subjective well-being. According to the
transactional model of stress (Lazarus & Folkman, 1984), highly efficacious individuals are
expected to (a) perceive fewer workplace stimuli as threatening or stressful, and (b) be more
likely to consider themselves capable to successfully deal with stimuli that are actually perceived
as stressful. Therefore, the relationship between workplace demands and experiences and
subjective well-being can be expected to be lower in magnitude for individuals in a higher selfefficacy state.
This moderating role of self-efficacy in the relationship between workplace demands and
experiences and experienced subjective well-being has been previously empirically demonstrated
in the literature. For example, Siu, Spector, Cooper, and Lu (2005) reported that apart from a
direct effect on job satisfaction, self-efficacy beliefs also attenuated the relationship between a
variety of workplace stressors and well-being in a sample of employees in Hong Kong and
Beijing. Likewise, Heuven, Bakker, Schaufeli, and Huisman (2006) demonstrated the
moderating effect of self-efficacy on the relationship between emotional demands in the
workplace and well-being outcomes; in a study of 154 cabin attendants, these authors found that
higher levels of self-efficacy allowed employees to better deal with the emotional demands of
their work, compared to employees with lower levels of self-efficacy. A similar moderating
effect was reported by Jex and Bliese (1999); in analyzing the results of a survey that included
2,273 soldiers, they found that in addition to a zero-order negative association between selfefficacy beliefs and psychological strains, these self-efficacy beliefs also provided a moderating
36

effect on the relationship between work overload, work hours, and psychological strain
experienced, such that the impact of these workplace demands on strain was much weaker for
individuals high in self-efficacy.
Furthermore, in a study of 589 governmental employees going through a period of
organizational change, Jimmieson, Terry, and Callan (2004) found that, in addition to having a
direct effect on current psychological well-being, self-efficacy beliefs moderated the effects of
role ambiguity, quantitative workload and experienced difficulties on psychological well-being
levels assessed two years later, with self-efficacy beliefs demonstrating a buffering effect for
individuals in this sample. Finally, this moderating effect has been also replicated in studies in
other cultural contexts. For example, in a study of 450 enterprise managers in China, Lu, Siu,
and Cooper (2005) reported that self-efficacy moderated the effect of experienced stressors on
physical (although not psychological) strain, such that this relationship was significantly weaker
for individuals who reported higher levels of managerial self-efficacy, compared to individuals
reporting lower levels of managerial self-efficacy.
In general, therefore, the above studies demonstrate that self-efficacy can play an
important role in predicting individual well-being. Self-efficacy, furthermore, can have both
mediating and moderating effects. That is, self-efficacy can both partly explain why exposure to
environmental stimuli such as stressors or work demands can lead to fluctuations in subjective
well-being, as well as affect the strength of the relationship between subjective well-being and its
predictors. As such, it can be thought as both affecting and being affected in turn by individuals’
experience, and the outcomes of these dual processes can have important implications.

37

Coping and Subjective Well-Being
The transactional model of stress (Lazarus & Folkman, 1984) considers coping to be a
central process in the relationship between workplace stressors and individual well-being.
According to this model, coping is considered an adaptive, dynamic process through which
individuals attempt to resolve experienced (or anticipated) stressors or to reduce the impact of
these stressors on their subjective well-being and experienced strain. As such, coping can impact
well-being through two main processes: by directly enhancing well-being levels (for example, by
taking action to remove stressors proactively) and by buffering the individual from the effects of
experienced stressors (for example, by swiftly resolving current workplace demands).
Empirical evidence is generally supportive of the importance of coping in directly
influencing individual levels of subjective well-being, although, as previously mentioned,
investigations have tended to focus more on the types of coping individuals engage in rather than
the success or failure of these efforts. Nevertheless, investigations of coping have provided us
with important findings in terms of the effects of this process on subjective well-being levels for
individuals. For example, in an investigation of 480 individuals, Ben-Zur (2009) reported that
coping was significantly associated with the affective component of subjective well-being.
Furthermore, different coping styles showed opposite patterns of effects, with problem-focused
coping being associated with increased positive and decreased negative affect, while avoidance
coping showed an opposite pattern. Similarly, Weinstein, Brown, and Ryan, (2009) in a series of
studies including laboratory, longitudinal and diary designs, found that approach coping was
positively associated with subjective well-being, and a similar finding was reported by Aryee,
Luk, Keung, and Lo (1999), who found that emotion-focused coping was related to life (but not
job) satisfaction.
38

Other researchers have focused on coping as a moderator or mediator of other subjective
well-being processes. Greenglass and Fiksenbaum (2009) reported that a proactive coping style
was associated with improved psychological functioning, and this coping style also partially
mediated the effects of social support availability on subjective well-being, thus providing some
insight on how personal resources and behaviors relate to each other in predictions of individual
well-being. In terms of the moderating role of coping, Kohn, Hay and Legere (1994) found that
various coping styles had only a modest moderation role on the relationships between hassles
and negative well-being, and these authors suggested that investigations of coping ability might
be more successful than investigations of coping style alone. Parkes (1990), however, found that
direct coping styles moderated the relationship between work demands and psychological strain
such that for individuals high in direct coping, the positive relationship between work demands
and mental strain was weaker compared to individuals low in direct coping. In general, although
coping style has been previously associated with subjective well-being outcomes, there seems to
be a need to move beyond simple investigations of the effects on coping types, and to better
integrate coping into models of workplace functioning.
Summary
This literature review hopefully indicates that workplace demands and experiences, as
well as factors such as job control and availability of workplace support, are important predictors
of individual well-being and self-efficacy beliefs. These self-efficacy beliefs, in turn, are
expected to be significant predictors of individual levels of well-being. Finally, coping can be
seen as representing an important component in models of workplace functioning and subjective
well-being, although there is a need to approach such a factor in a more ordered and careful
manner.
39

Next, I will present a conceptual model linking these factors. I will present the
hypotheses comprising this model, provide theoretical and empirical support for these
hypotheses, and finally discuss a study designed to test this model in a two-week investigation
involving a sample of clerical and administrative workers. As my analyses involve variables at
two levels of analysis (with state or momentary variables comprising the within-individual level
of analyses and trait or averaged state variables comprising the between-individual level of
analysis), I will indicate in each section whether the expected effects lie at the within- or
between-individual level, or alternatively the whether the expected effect implies cross-level
relationships (see Figures 1 and 2 for a summary of the hypothesized relationships).

40

Hypothesis Development

The Relationship of Work Demands and Experiences to Subjective Well-Being.
Work demands have been theoretically linked to decreased subjective well-being and
increased distress in a variety of workplace stress models, including the demands-control model
(Karasek, 1979), the model of person-environment fit (French et al., 1982) and the transactional
model of stress and coping (Lazarus & Folkman, 1984). While a certain level of job demands is
an expected part of any occupation or workplace, as work demands increase, the possibility that
they will begin to tax the individuals’ capabilities to effectively deal with them increases as well.
This is the process by which, for example, workloads can overwhelm employees and become
work overload (Ilies et al., 2010). In general, the higher the job demands experienced by the
individual, the more likely it is that (a) these demands will be perceived as more psychologically
threatening, initiating unfavorable secondary appraisal processes that could lead to strain
(Lazarus & Folkman, 1984), (b) they will exceed an individual’s perceived and actual
capabilities to adequately address them, resulting in a person-environment misfit (French et al.,
1982; Lazarus & Folkman, 1984), and (c) expose the individual to accumulations of stress and
anxiety that can result in reductions of subjective well-being (Karasek & Theorell, 1990). While
workload is the perhaps the most commonly examined job demand under these processes (see,
for example, Ilies et al., 2010), other demands of the workplace such as emotional demands and
role conflict can operate in a similar manner, and might even have a lower threshold for being
perceived as threatening as they might not automatically be considered as a routine part of the
job in the same way as workload.
41

Negative social experiences at work (the most common manifestation of which can be
interpersonal conflict and workplace incivility) can similarly result in reductions in well-being
levels. Insofar as they are perceived as a threat to salient aspects of an individual’s life, their
effects can be appraised and reacted to in a similar fashion as work demands (Lazarus, 1999).
Moreover, interpersonal conflict at work has been conceptually linked to negative affective
reactions, which can in turn result in a reduction of experienced well-being levels (Weiss &
Cropanzano, 1996). These affective reactions can also exert an informative effect on individual
attitudes and judgments (Schwarz & Clore, 1983), thus decreasing individual global satisfaction
and well-being perceptions and providing another pathway through which negative experiences
can impact subjective well-being. Finally, the experience of interpersonal conflict or workplace
incivility can command attitudinal, cognitive and other resources (Beal, Weiss, Barros, &
MacDermid, 2005) in order to be processed, explained, and reacted to by the individual. These
attitudinal and cognitive resources are then no longer available to the individual, and this
reduction in available resources can then further reduce an individual’s capacity to cope with
their environment, ultimately resulting in decreases in subjective well-being.
Nevertheless, a case could be made for the potential of work demands to provide a
beneficial effect on individual subjective well-being. Namely, the presence of work demands can
provide opportunities for personal successes and fulfillment of professional or personal goals,
which could be expected to relate positively to individual subjective well-being. In this case, one
would expect a positive, instead of negative, relationship between work demands and subjective
well-being, and indeed this positive relationship is a point in which I return to in Hypothesis 8.
However, I expect that work demands and negative social experiences will have, on
average, a negative effect, for two main reasons. First, in their role as the instigators of action, all
42

workplace demands require effort and mobilization of resources to engage (Theorell & Karasek,
1990), which can lead to resource depletion and fatigue with some possible negative outcomes
for individual well-being, even if the job demands are ultimately resolved successfully. Second,
the negative event of failing to successfully resolve a certain demand can have a stronger
harmful effect on the individual than the possible positive effects of success could have, due to a
tendency of negative events to have an asymmetrically strong effect on individuals, compared to
positive ones (Fiske & Taylor, 1984; Taylor, 1991). In other words, while work demands have
the potential to provide some benefits towards individual well-being in certain cases, on average,
I expect that workplace events and experiences will have an overall negative effect on individual
well-being.
Empirical approaches have been generally supportive of the net negative effects of
workplace demands and negative social experiences on subjective well-being. For example, Ilies
et al., (2010), in a 14-day ESM study involving 64 individuals, found that increased demands
experienced at work (conceptualized as workload) were associated with two indicators of poor
subjective well-being measured at the end of the day at home (γ = .24 for emotional exhaustion
and .13 for daily strain assessed with the General Health Questionnaire). Other efforts have
demonstrated the negative effects of work demands on the affective component of subjective
well-being (Repetti, 1993; Geurts, Kompier, Roxburgh, & Houtman, 2003; Rau & Triemer,
2004; Ilies et al., 2007).
Similar effects were reported by Dimotakis et al. (2010) with regard to negative social
experiences in the workplace; these authors showed that workplace interactions of a more
negative character (including interpersonal conflict) were associated with increased negative
affect (β = .42). Likewise, Taris, Peeters, LeBlanc, Schreurs, and Schaufeli (2001) found that the
43

experience of injustice in the workplace was associated with decreased well-being in a sample of
teachers (N = 271), and van Eck, Nicolson, and Berkhof (1998) reported that daily unpleasant
events were associated with decreased positive and increased negative affect, corroborating
previous research (DeLongis, Folkman, & Lazarus, 1988; Affleck, Tennen, Urrows, & Higgins,
1994; Clark & Watson, 1998).
Therefore, there is adequate conceptual and empirical evidence to support a main effect
of the daily levels of workplace demands and negative social experiences on individual
subjective well-being levels. Thus, I expect that, within-individuals, increased job demands and
negative experiences in the workplace will be associated with decreased levels of subjective
well-being.

Hypothesis 1a: Higher levels of daily work demands will be associated with lower
levels of subjective well-being.

Hypothesis 1b: More negative social experiences at work will be associated with
lower levels of subjective well-being.

Experiences, Demands and Self-Efficacy
As previously discussed, self-efficacy beliefs are formed through a number of different
pathways (Bandura, 1997), of which mastery experiences, social persuasion, and physiological
states are the most relevant ones for the model proposed in this paper. Furthermore, Stajkovic
(2006), in the context of discussing the core confidence component of self-efficacy, also
described that individuals’ confidence in their capabilities to deal with specific contexts are
44

informed by perceptions of their previous experiences, and their success in dealing with such
contexts in the past. These processes thus both provide support for the view that workplace
demands and experiences can influence individuals’ self-efficacy beliefs. That is, previous
success or failure in dealing with work demands can result in increases and decreases in selfefficacy, respectively. Moreover, the affective and psychological states experienced in dealing
with such demands (whether such coping efforts were successful or not) can also inform selfefficacy judgments, with increased anxiety, or negative affect resulting in decreases in selfefficacy beliefs (Bandura, 1997). Finally, interpersonal conflict and experienced incivility can
provide some degree of negative information to the employee about themselves (for example, in
cases of destructive criticism), which can further reduce self-efficacy beliefs.
Increased job demands can also increase the chances of failure in at least some aspect of
the work, thus reducing individual’s self-efficacy beliefs through another potential pathway.
Specifically, increased job demands can underline areas of concern formerly unknown to the
individual (for example, by identifying a component of one’s tasks that is more complex than
expected, or by realizing that one’s skills in a particular might not be sufficient in the future),
resulting in decreased self-efficacy if one’s success at a task is seen as an unrepeatable or overly
costly endeavor (Bandura, 1982). Furthermore, increased job demands can require individuals to
expend high levels of effort in order to cope with or resolve these demands, and this increased
effort can be interpreted by the employee as a sign of decreased ability and reduced confidence
in the likelihood of being able to produce the same high level of effort required to succeed in
similar difficulties in the future, again resulting in decreases in self-efficacy beliefs (Bandura &
Cervone, 1986).

45

As in the case of the relationship between work demands and subjective well-being,
however, the successful resolution of work demands at work can also result in increased selfefficacy beliefs for individuals, in cases where this resolution provides information to the
individual about potential increased capabilities to function effectively in the workplace (a point
which I explore more fully in Hypothesis 8). Nevertheless, as with job demands, I expect that the
net effect of job demands on self-efficacy will be on average negative, for two main reasons.
First, the asymmetric impact of negative events (Fiske & Taylor, 1984; Taylor, 1991) on
individual experiences and attitudes is expected to result in sharper self-efficacy decreases in the
cases of negative work functioning outcomes, compared to the potential gain in the case of
positive work functioning outcomes. Second, the successful resolution of workplace demands is
expected to represent a mastery experience only in the cases where such resolution is, in some
fashion, novel or exceptional. In other cases, individuals will maintain a stable level of selfefficacy in cases of success, and suffer a lower level of self-efficacy in cases of failure. In other
words, the potential for self-efficacy losses is higher than the potential for gains of self-efficacy
under most circumstances, and thus I expect that the relationship between workplace demands
and negative social experiences and self-efficacy will be negative.
Available empirical evidence is supportive of a net negative relationship between
workplace demands and self-efficacy beliefs. For example, Taris et al. (2003), in a sample
composed of 876 Dutch teachers, found that increased job demands had a negative effect on selfefficacy beliefs, while Jex and Bliese (1999) reported a negative zero-order correlation between
work overload and self-efficacy (r = -.20) in a sample of 2,273 soldiers. Supporting the
relationship between past performance and self-efficacy judgments, Yeo and Neal (2006), as
well as Vancouver and Kendall (2006), found that past performance was positively associated
46

with self-efficacy perceptions, and a similar finding was reported by Locke, Frederick, Lee, and
Bobko (1984), providing empirical support for another pathway through which self-efficacy
beliefs can be formed. Similarly, Mitchell, Hopper, Daniels, George-Falvy, and James (1994)
reported that past performance was associated with self-efficacy beliefs in a laboratory task
(although this association was reported to slightly decrease over time). Finally, a zero-order
association between job demands and self-efficacy was reported by Schaubroeck and Merritt
(1997).
In terms of the effects of workplace experiences, Webster et al. (2010) found a
relationship between negative workplace events (conceptualized as hindrance stressors) and selfefficacy beliefs in a sample of 143 employees. Likewise, Lubbers, Loughlin and Zweig (2005),
found that the experience of interpersonal conflict at work was negatively associated with selfefficacy beliefs in a sample of 195 young workers (β = -.16). Finally, Baron (1988) reported that
receiving destructive criticism (a potentially important negative workplace event associated with
incivility) resulted in decreases in self-efficacy in a sample of 106 undergraduate students.
There is, therefore, enough theoretical and empirical support to suggest negative withinindividual relationships between the daily levels of workplace demands and negative social
experiences experienced and the subsequent formation of lower levels of self-efficacy beliefs.

Hypothesis 2a: Higher levels of daily work demands will be associated with lower
levels of self-efficacy.

Hypothesis 2b: More negative social experiences at work will be associated with
lower levels of self-efficacy.
47

Workplace Resources, Well-Being and Self-Efficacy
The level of workplace resources individuals have available can be another important
predictor of subjective-well-being levels (Cohen & Wills, 1985; Rhoades & Eisenberger, 2002;
Elsass & Veiga, 1997). For both job control and workplace support, one reason for this
association can be that these resources are thought to be able to fulfill intrinsic individual needs,
which, when unmet, can impact subjective well-being levels negatively. Indeed, the acquisition
and retention of control over the circumstances of one’s life has been characterized as an
intrinsic individual motivation (Elsass & Veiga, 1997), an argument that can be extended to
control or discretion over one’s circumstances at work. Moreover, the presence of social and
organizational support in the workplace directly relates to the satisfaction of relatedness needs
(Ryan & Deci, 2000), thus resulting in higher subjective well-being through the satisfaction of
these needs. These theoretical arguments thus posit that individuals who perceive that they have
available workplace support and who are able to exert control over their work environments
should have higher levels of subjective well-being compared to individuals who do not.
The second factor linking the availability of workplace resources to individual well-being
can be the primary appraisal process of the transactional stress model (Lazarus & Folkman,
1984). According to this argument, the presence of workplace resources can lead individuals to
perceive that their environment contains fewer threatening or stressful stimuli. That is,
individuals who possess a variety of workplace stressors can perceive their environment as
generally positive, thus providing an additive effect that can result in stressors such as work
demands being appraised as neutral or benign. This second argument is also supportive of a link
between workplace resources and individual self-efficacy beliefs; when the availability of
48

resources enables the individual to perceive their work environment as less threatening,
employees can have increased levels of confidence their ability to successfully deal with these
demands (Bandura, 1997). On the other hand, more threatening or stressful appraisals of a work
environment create the perception of increased difficulty in dealing with these job demands, thus
resulting in relatively lower levels of self-efficacy.
Empirical results provide support for a positive association between workplace resources
and subjective well-being levels. Ippolito et al. (2005) found such an effect for job control, as did
Holman and Wall (2002) and Liu et al. (2007). Similarly, Totterdell et al. (2006) found a similar
effect for job control within-people, providing further evidence for the importance of job control
as a workplace resource. La Rocco and Jones (1978) reported that workplace support was
another valid work resource that is associated with well-being outcomes, while Karasek et al.
(1982) reported a negative association between the presence of social support and levels of
mental strain. Furthermore, in a large scale study in Sweden, Canivet et al. (2010) linked social
support to reduced feelings of exhaustion (an indicator of low well-being). Finally, meta-analytic
evidence provided by Rhoades and Eisenberger (2002) provides evidence for the importance of
perceived organizational support in predicting individual indicators of well-being such as strain,
job satisfaction, and positive affect experienced at work.
The available empirical evidence would also seem to support a relationship of work
resources such as job control and workplace support to self-efficacy beliefs, although
investigations of this relationship are not very common in the literature. For example, Taris et al.
(2003), in an investigation involving 876 Dutch teachers, found that higher levels of job control
were associated with increased self-efficacy beliefs. Rees and Freeman (2009) reported a
similarly positive association between of social support and self-efficacy beliefs, an association
49

also reported by Saltzman and Holahan (2002) in a longitudinal examination of 300
undergraduate students, and Shen (2009) in a sample of 530 teachers. Furthermore, a zero-order
association between perceived availability of social support and self-efficacy was reported by
Maurer, Weiss, and Barbeite (2003), as well as by Karademas (2006).
In sum, the available theoretical and empirical evidence provides support for a betweenindividual association of workplace resources with average levels of subjective well-being, as
well as an association with average levels of self-efficacy beliefs. Therefore, I hypothesize that:

Hypothesis 3a: Higher levels of available workplace resources will be associated
with higher average levels of subjective well-being.

Hypothesis 3b: Higher levels of available workplace resources will be associated
with higher average levels of self-efficacy beliefs.

Self-Evaluations and Subjective Well-Being
Self-efficacy beliefs have been theoretically linked to individual levels of subjective wellbeing (Bandura, 1977), with Warr (2006) arguing that self-efficacy beliefs as they relate to the
present situation are one of the judgments most closely related to the experience of individual
well-being. In essence, these beliefs relate to perceptions of whether one can respond to current
and future situations in a sufficient or satisfactory manner, and as such can influence the
individual’s perceptions about their capability to overcome challenges and maintain an adequate
level of functioning through a number of processes. High self-efficacy can result in more
positive primary appraisals of the external environment (Lazarus & Folkman, 1984), whereby
50

individuals perceive fewer stimuli as threatening to their well-being; these appraisal processes
can result in a positive relationship between self-efficacy and subjective well-being through
individual perceptions of a more positive and less stressful environment. Moreover, decreased
self-efficacy has been argued to relate to more ineffectual modes of coping (Jex and
Gudanowski, 1992), and to decreased perceptions of control (Litt, 1988), thus creating a
perception for the individual of an environment that is more stressful and harder to contend with.
These perceptions in turn can result in a higher potential for the accumulation of strain. In
general then, increased self-efficacy is theoretically expected to relate to increased levels of
subjective well-being.
Empirical evidence is also highly supportive of this effect (Bandura, 1997; Gecas, 1989;
Karademas 2007). For example, Karademas et al. (2007), in a study of 104 undergraduate
students, found both a direct and an indirect (through optimism) effect of self-efficacy on
perceptions of strain. Moreover, Karademas (2006) found that self-efficacy beliefs were
associated with subjective well-being (operationalized using life satisfaction and depression as
indicators) experienced one month later. Similarly, Schwerdtfeger et al. (2008) found that
occupation-specific self-efficacy was positively related to positive affect, and negatively related
to negative affect and burnout in a sample of teachers. Utilizing a national 2,107 sample of older
African-American adults, Tran et al. (1991) reported that self-efficacy beliefs were associated
with increased subjective well-being (β = .26). Finally, in a sample of 8,796 participants from 5
countries, Luszczynska, Gutiérrez-Doña, and Schwarzer (2005) found that self-efficacy was
positively associated with increased positive affect and life satisfaction, and negatively
associated with negative affect, anxiety and depression.

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In terms of other negative indicators of subjective well-being, Fillion et al. (2007) found a
negative relationship between self-efficacy and emotional distress (β = -.26) in a sample of 209
palliative-care nurses. Similarly, in a sample of 490 teachers in the Netherlands, Evers et al.
(2002), found a negative relationship between self-efficacy and various dimensions of burnout.
Finally, Wilk and Moynihan (2005), found a negative relationship between self-efficacy beliefs
and burnout in a sample of 1,236 call center employees.
In view of the theoretical and empirical support for a relationship between self-efficacy
and individual levels of subjective well-being, I propose that, within-individuals, self-efficacy
beliefs will be positively associated with subjective well-being.

Hypothesis 4: Increased self-efficacy beliefs at the end of the workday will be
associated with increased subjective well-being.

The Mediating Role of Self-Efficacy
Thus far, I have advanced arguments for the relationships of (a) workplace demands and
negative social experiences to subjective well-being, (b) available workplace resources to
subjective well-being, (c) workplace demands and negative social experiences to self-efficacy
states, (d) available workplace resources to self-efficacy states and (e) self-efficacy states to
subjective well-being. Drawing again from the linkages between self-efficacy theory (Bandura,
1977; Bandura, 1997), and the demands-control model (Karasek, 1979), I now turn to a
discussion of the mediating role of self-efficacy in the relationships between workplace
experiences and subjective well-being.

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Indeed, the effect of workplace demands and experiences on subjective well-being can be
partially explained through their association with self-efficacy beliefs. That is, increases in work
demands and negative social workplace experiences can negatively affect an individual’s levels
of well-being specifically because these events lead them to doubt their abilities to deal with the
demands of their daily lives, which can then result in decreases in individual levels of selfefficacy beliefs. These decreases, in turn, can have a negative impact on individual levels of
subjective well-being as mentioned above.
In terms of the effects of available workplace resources, I expect self-efficacy to again
mediate the positive impact of resources on individual well-being levels. In this case, the effects
of workplace resources on subjective well-being will be expected to be explained, at least
partially, due to the enhancing of self-efficacy beliefs that workplace resources can affect on
individuals. That is, the availability of organizational and social support and control over one’s
work will be associated with increased well-being specifically because individuals who have
more access to these resources are more likely to hold higher efficacy beliefs (as previously
stated).
The above arguments discuss how self-efficacy can mediate the within-individual
negative effects of workplace demands and negative social experiences, and the betweenindividual positive effects of available workplace resources, on subjective well-being. However,
because subjective well-being is associated with a variety of other factors, such as physiological
health (Judge, Ilies, & Dimotakis, 2010) and recovery activities (Fritz & Sonnentag, 2006), I
only expect self-efficacy to partially mediate these effects (see Figure 1). In short, I propose that:

53

Hypothesis 5: Self-efficacy beliefs will partially mediate the effects of (a)
workplace demands, (b) negative social experiences, and (c) workplace resources on
subjective well-being levels.

The Moderating Role of Workplace Resources on the Relationship between Workplace
Demands and Negative Events and Their Outcomes
Job control (or decision latitude) and workplace support have been hypothesized to
moderate the impact of job demands on individual-level outcomes. In terms of job demands,
increased control can enable individuals to more effectively deal with the requirements of their
environment (see Karasek, 1979; Karasek & Theorell, 1990). Such effectiveness can come from
an increase in the potential options individuals can have to manage their work demands and
energy expenditure, such as the capability to utilize respites to avoid strain (Sonnentag, 2001), or
the utilization of time management strategies designed to help individuals contend better with the
requirements of their workplace (Adams & Jex, 1999). On the other hand, when control is not
available, employees will not have many options available to them in order to successfully cope
with increases in job demands (Karasek, 1979). Karasek and Theorell (1990) offered the
example of the assembly worker whose behavior is severely constrained, leaving them unable to
respond to increases in job demands (such as increases in line assembly speed), and thus
resulting in increased strain that cannot be easily avoided.
The demands-control model has been expanded by Johnson and Hall (1988) to include
the role of workplace support in alleviating the negative effects of job demands. The presence of
social support can provide informational, instrumental and emotional assistance to its recipients
(House, 1981) thus providing them with greater capabilities to deal with the requirements of their
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environment. Receiving social support can thus provide individuals with assistance and
affirmation (Lincoln, 2008), reducing the difficulty or load of their work, and improving their
perceptions of their capabilities in dealing with the demands of the work environment.
Recently, Ilies et al. (2010) examined perceived organizational support (Rhodes &
Eisenberger, 2002) as another potential moderator of the effects of workplace demands and
experiences, with the expectation that the organization can represent another important source of
support for the employee. Perceived organizational support is defined as an “assurance that aid
will be available from the organization when it is needed to carry out one’s job effectively and to
deal with stressful situations” (Rhodes and Eisenberger, 2002, p. 698). Therefore, this source of
support can provide additional help of a more instrumental character that directly relates to the
capabilities of individuals to specifically address workplace demands in a successful fashion.
Empirical evidence supports the moderating effect of social and organizational support
on the effects on workplace demands and experiences, although the evidence for a moderating
effect of job demands is relatively mixed (see De Jonge & Kompier, 1997; De Lange, et al.,
2003; Van der Doef & Maes, 1999). Bakker et al. (2010) found that increased levels of job
resources (which included support and autonomy) moderated the relationship between
experienced workplace demands and well-being in a sample of 12,359 employees. Ilies et al.
(2010) found that both decision latitude and perceived organizational support moderated the
negative effects of workload on affective distress experienced at the end of the workday, such
that these effects were weaker for individuals who reported increased decision latitude and
perceived organizational support. Furthermore, Landsbergis (1988) found that high workloads in
combination with decreased levels of decision latitude were associated with reductions in
subjective well-being in a sample of 771 hospital and nursing home employees, and this
55

relationship that persisted after controlling for a variety of work and demographic variables.
Likewise, Bakker et al. (2005), in a study of 1,000 employees of a higher education organization,
found that workplace resources, including autonomy and social support, reduced the magnitude
of the negative relationship between various work demands and well-being. Van Vegchel et al.
(2004) also reported that job control moderated the relationship between emotional demands and
subjective well-being (measured as emotional exhaustion), while Rau (2004), in a sample of 241
employees, found that having high job demands and high decision latitude was associated with a
healthier physiological response compared to individuals who had high job demands but low
decision latitude. Finally, Karasek et al. (1982) found that for individuals who reported having
greater workplace support, the relationship between workplace stressors and mental strain was
weaker compared to individuals who reported having lower levels support in the workplace.
While investigations of the effects of workplace resources on the effects of workplace
demands on self-efficacy are lacking in the literature, the same theoretical arguments supporting
the moderating effect of resources on subjective well-being can operate on self-efficacy beliefs.
That is, the reduced perception of environmental demands and one’s control over them, as well
as the enhanced capabilities to cope with these environmental demands provided by job control
and available workplace support can also buffer employees from the deleterious effects of job
demands on self-efficacy (see above).
Therefore, based on the available theoretical linkages and empirical evidence, I expect
that workplace support, as well as job control, will have a cross-level moderating effect, such
that the effects of workplace demands and negative social experiences will be weaker for
individuals reporting higher levels of available workplace resources (see Figure 1). In short, I
expect that:
56

Hypothesis 6: Workplace resources will moderate the relationships of workplace
demands and negative social experiences to (a) self-efficacy and (b) subjective wellbeing, such that the negative effects of work demands and negative social experiences
will be weaker for individuals reporting having higher levels of available workplace
resources, compared to individuals reporting having lower levels of available resources.

The Moderating Role of Prior Self-Efficacy on the Relationship between Workplace
Demands and Negative Events and Their Outcomes
Self-efficacy beliefs have been proposed to enhance individuals’ capacities to mobilize
resources, persistence, and effort in dealing with environmental stressors and persevering in the
face of adversity (Bandura, 1997). Thus, self-efficacy can be related to individual levels of
subjective well-being through the secondary appraisal process of the transactional stress model
(Lazarus & Folkman, 1984). According to this argument, the presence of workplace resources
can lead individuals to perceive that stress stimuli experienced as part of the day do not represent
overwhelming stressors that the individual will not be able to successfully cope with, but simply
environmental demands that they can indeed engage and overcome. This perception can then
enable individuals to take the proper actions (such as initiating coping strategies or otherwise
taking action to deal with the situation at hand), thus possibly addressing the stressors and
avoiding the stressors’ effects on individual well-being.
That is, increased self-efficacy can result in individuals being more confident in their
abilities to cope with work demands, thus being more likely to mobilize resources and manifest
behaviors that can help them avoid their negative effects. For example, individuals with high
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self-efficacy are more likely to undertake effective coping strategies (Jex & Bliese, 1999). This
increased capability to deal with workplace demands, in turn, can strengthen individual selfefficacy beliefs even more, creating an upward spiral that is beneficial to the individual
(Bandura, 1997). Finally, individuals with higher levels of self-efficacy beliefs are thought to be
more resilient compared to less efficacious individuals, persisting even in the face of negative
outcomes, thus potentially reducing the effects of workplace demands on future self-efficacy
beliefs (Bandura, 1997).
Indeed, the literature has generally been supportive of this moderating effect of selfefficacy. Heuven et al. (2006) found that higher levels of self-efficacy allowed employees to
better deal with the emotional demands of their work, compared to employees with lower levels
of self-efficacy. Similarly, Siu et al. (2005) reported that self-efficacy beliefs moderated the
relationship between workplace stressors and well-being in a sample of 234 employees in Hong
Kong and Beijing, while Jex and Bliese (1999) found that higher self-efficacy neutralized the
relationship between work overload and psychological strain. Furthermore, in a study of 589
governmental employees going through a period of organizational change, Jimmieson et al.
(2004) found that self-efficacy moderated the effects of a variety of workplace stressors
(including role ambiguity, quantitative workload and experienced job difficulties) on
psychological well-being levels assessed two years later, with self-efficacy reducing the
magnitude of these relationships.
In summary, I expect that, within-individuals, previously formed self-efficacy beliefs will
protect individuals from the effects of currently experienced negative workplace demands and
experiences, such that on days in which individuals experience stressful or negative workplace
events after having experienced high levels of self-efficacy beliefs, the effects of these workplace
58

events will be weaker in magnitude (compared to days in which individuals experience stressful
or negative workplace events after a decrease in their level of self-efficacy beliefs; see Figure 1).

Hypothesis 7: Previously formed levels of self-efficacy beliefs will moderate the
relationship between workplace demands and negative social experiences and (a) selfefficacy beliefs and (b) subjective well-being levels, such that these relationships will be
weaker on days in which individuals encounter these events after experiencing high
levels of prior self-efficacy, compared to days in which individuals encounter these
events after experiencing low levels of prior self-efficacy.

The Moderating Role of Coping, And the Relationships among the Moderators of the
Effects of Workplace Demands and Experiences
The last two hypotheses discussed the expected moderating influences of workplace
resources and prior self-efficacy beliefs on the negative effects of workplace demands and
experiences. The theoretical frameworks supporting these effects, however, implicitly or
explicitly depend on coping and functioning arguments in making these propositions. Coping is a
central factor in the relationship between perceptions of stressors and the experience of strain and
subjective well-being (Lazarus and Folkman, 1984; Lazarus, 1999). Furthermore, the arguments
advanced in the demands-control model (Karasek & Theorell, 1990) as well as the self-efficacy
component of social cognitive theory (Bandura, 1977; Bandura, 1997) discuss that control and
self-efficacy can have valuable buffering effects specifically because they allow individuals to
cope better with their environment by summoning resources and manifesting behaviors that
enable them to better respond to the environmental demands at hand. This increased coping
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success is thus expected to be the most proximal moderator of the relationship between
workplace demands and experiences and their outcomes. Moreover, as the most proximal
moderator, coping success is also expected to mediate the ameliorating effect of work resources
and prior levels of self-efficacy.
In other words, by successfully engaging in coping responses, individuals are able to
better muster the efforts and behaviors that can enable them to deal with the demands of their
work environment effectively (Lazarus & Folkman, 1984). These efforts and behaviors can then
in turn either directly address the work demand itself (for example, by managing to successfully
complete a difficult work assignment) or manage the impact of the stressor (for example, by
ordering tasks such that individuals can better manage their effort expenditure during their
workday). Therefore, coping success can have a within-individual moderating effect on the
effects of workplace demands and negative social experiences, with higher levels of coping
success ameliorating the negative effects of these experienced workplace events.
Moreover, success in coping with work demands can result in increases in self-efficacy
beliefs, as this success represents a mastery experience that increases individual confidence in
one’s capabilities to function successfully in the workplace (Bandura, 1997). In this case,
overcoming higher levels of environmental demands can provide more salient information to the
individual about their capabilities. Furthermore, overcoming work demands can remove negative
psychological and physiological states that are associated with reduced self-efficacy beliefs. In
other words, when individuals successfully cope with a workplace demand, feelings of anxiety or
discomfort can be removed, and their informational effect on self-efficacy is also expected to
diminish. In general then, when individuals are faced with high levels of work demands and
overcome them successfully, their self-efficacy beliefs are expected to increase correspondingly.
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In this case, high coping success will be expected to result in a positive relationship between
workplace demands and self-efficacy beliefs.
A similar effect can be expected for the relationship between workplace demands and
experiences and subjective well-being. Successfully coping with workplace demands can be seen
as a positive affective event (Weiss & Cropanzano, 1996) that can create positive affective
experiences, alleviate negative states, and as such result in increased levels of subjective wellbeing. Success in coping can also satisfy individual needs for competence (Ryan & Deci, 2000),
which provide another mechanism for how coping success can relate to subjective well-being. As
with self-efficacy then, under conditions of high coping success, workplace demands are
expected to relate positively to subjective well-being, while under conditions of low coping
success workplace demands are expected to maintain a negative relationship to subjective wellbeing (see Figure 1).
Furthermore, coping can explain the cross-level moderating effect of workplace resources
and the within-individual moderating effect of previous self-efficacy beliefs on the relationship
between work demands and subjective well-being. That is, for individuals who have high levels
of available workplace resources or previously increased levels of self-efficacy beliefs, the
relationship between work demands and subjective well-being is expected to be weaker, because
these individuals will exhibit more successful coping strategies, and it is these successful coping
strategies that buffer them from the negative impact of workplace demands and negative social
experiences.
As previously mentioned, the literature on coping has tended to focus more on the types
of coping rather than their (objective or subjective) effectiveness. Nevertheless, there is some
empirical research to support that coping success is an important factor in dealing with stressors
61

(Zautra & Wrabetz, 1991). Furthermore, the finding that certain coping strategies are more
effective in enhancing individual well-being (e.g., Ben-Zur, 2009) might be indicative of the
importance of coping success in influencing well-being outcomes, by implicitly capturing the
concept of coping success in such investigations. Furthermore, Greenglass and Fiksenbaum
(2009) described the role of coping style in mediating the effects of social support on subjective
well-being, while Parkes (1990) found that coping style can buffer individual levels of wellbeing from the negative effects of work demands. In all, although coping success has not been
explicitly examined in the literature to an adequate level, to the extent that different coping styles
can be differentially successful in dealing with work demands, these studies can be seen as
indicating that coping can provide a buffering effect for individuals, and this buffering effect can
explain to some extent the beneficial nature of workplace resources such as available workplace
support (see Figure 1).
Therefore, drawing from these initial empirical results and the theoretical arguments
underlying the demands-control model and self-efficacy, I contend that there is sufficient support
to suggest these relationships. Thus, I propose that:

Hypothesis 8: The degree of reported success in coping with workplace demands
and negative social experiences will moderate the relationship of these demands and
experiences to (a) self-efficacy beliefs and (b) subjective well-being levels, such that
workplace demands and experiences will be positively associated with self-efficacy
beliefs and subjective well-being on days in which individuals report higher levels of
coping success, but negatively associated on days in which individuals report lower
levels of coping success.
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Hypothesis 9: Coping success will mediate the moderating effects of (a) available
workplace resources and (b) previous levels of self-efficacy on the relationship between
work demands and negative social experiences and self-efficacy beliefs.

Hypothesis 10: Coping success will mediate the moderating effects of (a)
available workplace resources and (b) previous levels of self-efficacy on the relationship
between work demands and negative social experiences and subjective well-being levels.

Summary of Study Hypotheses and Levels of Analysis
In summary, my study involves the following hypotheses across the various levels of
analysis (see Figure 1 and Figure 2 for a summary of these proposed relationships). In terms of
the within-individual main effects, I expect that higher levels of daily work demands and more
negative social experiences will be associated with (a) lower levels of subjective well-being
experienced at the end of the day, and (b) lower levels of self-efficacy experienced at the end of
the workday. In turn, I expect that higher levels of self-efficacy at the end of the workday will be
associated with increased levels of subjective well-being at the end of the day. Relative to the
between-individual main effects hypothesized, increased availability of workplace resources (job
control and workplace support) is expected to be positively related to average levels of subjective
well-being and to average levels of self-efficacy beliefs.
In terms of the cross-level moderators of the hypothesized within-individual
relationships, I expect that the availability of workplace resources (job control and workplace
support) will moderate the relationship of workplace demands and negative social experiences to
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(a) the level of subjective well-being experienced at the end of the day, and (b) the level of selfefficacy experienced at the end of the workday, such that these relationships will be weaker for
individuals who report having more workplace resources available, relative to individuals who
report having fewer workplace resources available.
Furthermore, regarding the hypothesized same-level moderating effects of the withinindividual relationships discussed above, I expect that on days in which individuals report higher
levels of coping success or in which they have previously formed higher levels of self-efficacy
beliefs, the relationships between workplace demands and experiences and (a) the level of
subjective well-being experienced at the end of the day, and (b) the level of self-efficacy
experienced at the end of the workday, will be weaker, compared to days in which individuals
report lower levels of copings success or have previously formed lower levels of self-efficacy
beliefs.
Relevant to the hypothesized mediating effects, at the within-individual level I expect
that self-efficacy beliefs at the end of the workday will partially mediate the effects of (a)
workplace demands and (b) negative social experiences on subjective well-being experienced at
the end of the day. At the between-individual level, the average level of individual self-efficacy
beliefs is expected to partially mediate the between-individual relationship between workplace
resources and average levels of subjective well-being.
Furthermore, in terms of the expected mediation of cross-level moderating effects, coping
success is hypothesized to mediate the moderating effects of workplace resources on the
relationship between workplace demands and experiences and (a) self-efficacy beliefs
experienced at the end of the workday, and (b) subjective well-being experienced at the end of
the day.
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Finally, relevant to the expected mediation of within-individual moderating effects,
coping success is hypothesized to mediate the moderating effects of previously formed selfefficacy beliefs on the relationship between workplace demands and experiences and (a) selfefficacy beliefs experienced at the end of the workday and (b) subjective well-being experienced
at the end of the day.

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Method

Power Analyses
To estimate the sample size needed for my analyses, I conducted multilevel power
analyses to determine the number of participants needed, as well as the necessary number of
within-individual observations (Snijders and Bosker, 1999). Assuming an average effect size of
.30, and an alpha level of .05, I estimated than the standard error of my coefficients needs to
approach .12 to achieve a power level of .80. To calculate the sample size required for this
standard error, I conducted a power analysis using the Power IN Two-level designs program
(PINT; Snijders and Bosker, 1993). Analyses indicated that achieving this standard error in an
analysis with 2 moderately correlated dependent variables and one cross-level moderator will
require a total of 84 individuals each providing 5 day-level data points (an expected response rate
for my design; see for example Ilies et al. 2010). Therefore, in order to attain this sample size,
while allowing for some individuals to drop out of the study without adversely affecting my
power level, I attempted to enroll 90 individuals in my study.
Sample
My sample was drawn from a pool of mainly administrative and clerical Michigan State
University (MSU) employees who have previously indicated they would be willing to participate
in research studies. Participants were recruited through an e-mail advertisement, which contained
the description of the study and a link to a survey sign-up website, where they were requested to
indicate their agreement to enroll in the study by approving an online consent form. Participation

66

was completely confidential and voluntary, and participants were compensated for their efforts
with a small honorarium (up to $75).
In order to comply with the study design, participants were required to be full-time
employees (full-time in this case being defined as working more than 35 hours a week), and to
have internet access at work and at home. To receive full compensation, participants were
required to complete at least 18 surveys (out of 30 possible); responses between 0 and 17 were
compensated on a prorated basis.
A total of 95 employees signed up for the study. These participants were mostly (81%)
female. Furthermore, they worked an average of 41.87 hours a week (SD = 7.89), were mostly
married (68%), and had an average of 1.64 children (SD = 1.33).
Procedure
After completing an online survey containing perceptions of workplace resources and the
trait measures to be used as controls, participants were asked to fill out 3 daily surveys (two
surveys in the workplace, one survey at home) for a period of 2 weeks, for a total of 10 day-level
possible observations per individual. This 2-week study period is in line with the
recommendations of Wheeler and Reis (1991), and similar to previous research studies (for
example, see Ilies et al. 2010). All surveys were administered online, and individuals were
signaled to fill out a survey through e-mail messages. These signaling e-mails were sent out
during at a fixed time (for the first daily survey; see below) or around randomly assigned 2-hour
blocks around a designated time (for the second and third daily surveys), and each of the daily
surveys required around 5 minutes to complete.
The first daily survey signal was sent at 1:15 pm, and included measures of workplace
demands and experiences. The second daily survey signal was randomly sent within a time block
67

centered around 3:30 pm, and included measures of state self-efficacy and perceived success in
coping with workplace demands and experiences. Finally, the third daily survey was randomly
sent within a time block centered around 7:00 pm, and included measures of current subjective
well-being. Responses from these surveys were combined in order to create day-level data
points; a usable day-level data point will thus consist of three complete surveys. See Figure 3 for
a representation of the variables measured with each daily survey, and a summary of the time
blocks in which these surveys will be administered.
Due to missing data or violations of study protocol, not all participants had enough
complete data points to be included in this study; therefore, the total sample consisted of 77
individuals providing a total of 514 to 517 day-level observations (depending on the specific
variables involved), for a total within-individual response rate of around 66.9% (SD = 2.50 daylevel data points).
Measures
Work demands and interpersonal experiences. I measured work demands using a
multi-dimensional conceptualization, in which the demands of work are considered to consist of
the current level of workload, the level of emotional labor requirements (to capture the emotional
demands of the work), and the role conflict currently experienced (to assess the difficulties
encountered when role requirements clash or create incompatibilities). While work demands
could undoubtedly be considered to include other relevant factors (for example, physical
demands), the conceptualization I used covers the majority of work demands that are involved in
typical white-collar or professional work, and the constructs included are among the most
frequently examined components of work demands examined in the literature (see, for example,
Repetti, 1993; de Jonge, Mulder, & Nijhuis, 1999; Brotheridge & Grandey, 2002; Dwyer &
68

Ganster, 2006). Additionally, I included two measures of negative social experiences
(interpersonal conflict and experienced incivility), in order to assess these common but
undesirable stimuli that individuals are exposed (and need to react) to in their daily work lives.
As such, these interpersonal experiences can be seen to represent an additional category of
workplace demands that individuals might need to contend with as part of their workday. All the
work demand variables were assessed during the first daily survey, which was sent out at 1:15
pm every day. Participants were expected to be at work at the time when they responded to this
survey.
Workload was measured using a modified 9-item version of Jannsen’s (2001) job
demands measure; this measure has been previously used successfully in studies examining the
effects of increased workloads on individual’s well-being and experience (see Ilies et al., 2010;
Ilies et al., 2007). Respondents were asked to use Likert scale responses (ranging from 1 =
strongly disagree to 5 = strongly agree) to indicate their agreement to statements such as
“Today, I have too much work to do in my job” and “Today, I have to work under time
pressure”. The average internal consistency reliability of this scale was .91.
Emotional demands were measured using the surface acting component of Brotheridge
and Lee’s (2003) Emotional Labor Scale, modified to reflect the daily experience of participants.
Among the components of the scale, surface acting most clearly fits the conceptualization of
work demands I am using, and as such is preferred over components such as deep acting. In
responding to this instrument, participants were asked to use Likert scale responses (ranging
from 1 = strongly disagree to 5 = strongly agree) to indicate the extent of their agreement to
statements such as “Today, I have had to resist showing my true feelings,” and “Today, I have

69

been pretending to have emotions I didn’t really have.” The average internal consistency
reliability of this scale was .96.
Role conflict was measured using the scale of Rizzo, House, and Lirtzman (1970),
modified to assess participants’ daily experiences. This scale required participants to use Likert
scale responses (1 = strongly disagree to 5 = strongly agree) to indicate their agreement to a list
of provided statements referring to the role conflict that they have experienced during the
workday, such as “I have to buck rules or policies in order to carry out my assignments,” “I
received incompatible requests from two or more people,” and “I have to work under
incompatible policies and guidelines.” The average internal consistency reliability of this scale
was .93.
In terms of measuring social experiences at work, to assess the levels interpersonal
conflict experiences individuals encounter in the course of their workday I utilized Jehn’s (1995)
conflict scale, modified to assess daily experiences. This instrument required participants to use
Likert scale responses (1 = strongly disagree to 5 = strongly agree) to indicate their agreement
to a list of provided statements about the interpersonal conflict they experienced during the
workday, such as “There is conflict about ideas between me and my coworkers.” and “There are
personality conflicts evident between me and my coworkers.” Responses were aggregated into
an overall scale assessing the degree to which participants experienced interpersonal conflict
throughout the workday. Although this scale was originally intended to differentiate between
task and relationship conflict, the association between these two has been shown to be of a
magnitude that might not support differentiation among the two (Simons & Peterson, 2000; De
Dreu & Weingart, 2003). Because of this potential lack of differentiation, and to avoid
multicollinearity issues in the estimation of my models, I constructed an overall interpersonal
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conflict scale instead of differentiating between task and relationship conflict. The average
internal consistency reliability of this scale was .95.
Finally, workplace incivility was be assessed using the 7-item Workplace Incivility Scale
(Cortina et al., 2001), modified to assess daily experiences. This scale required participants to
use Likert-scale responses (1 = not at all to 5 = extremely) to indicate the extent to which their
coworkers or supervisors have displayed uncivil behaviors toward them during the workday.
Items include “Made demeaning or derogatory remarks toward you,” “Put you down or was
condescending to you,” and “Ignored or excluded you from professional camaraderie.” The
average internal consistency reliability of this scale was .88.
Work and personal resources. To capture the resources available to study participants, I
used constructs representing the most common definitions of workplace resources in the
literature: (a) job control, (b) workplace support (comprised of perceived organizational support,
and perceived availability of social support from coworkers and supervisors). While recent
conceptualizations such as the demands/resources model (Bakker & Demerouti, 2007;
Demerouti et al., 2001) have utilized an expanded inventory of job and personal resources, the
three variables mentioned above are strongly rooted in the literature and represent core
components of the demands/control model and related conceptualizations (Karasek, 1979;
Johnson & Hall, 1988; Karasek & Theorell, 1990). That is, these resources are widely applicable
to most workplaces, have been found to relate to important characteristics of the workplace with
vital implications for organizations and employees, and can thus provide a stronger contribution
relative to more workplace-specific or narrow-band resources (such as, for example, specific
types of technological support or monetary resources that would be more applicable to specific

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occupations). All resource variables were conceptualized as stable constructs, and as such were
only measured once, at the beginning of the study.
Job control was measured using the decision latitude component of the Job Content
Questionnaire (Karasek, Brisson, Kawakami, Houtman, Bongers, & Amick, 1998). Responses
were given by participants utilizing a 5-point Likert scale (1 = strongly disagree to 5 = strongly
agree) to indicate agreement to statements such as “I have a lot of say about what happens on my
job” and “On my job, I have very little freedom to decide how I work” (reverse-coded). The
reliability of this scale was .86.
Perceived organizational support was measured using Eisenberger and colleagues’
(Eisenberger et al., 1986) scale of the same name. As with job control, participants were asked to
use a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) to indicate their
agreement to statements such as “The organization values my contribution to its well-being” and
“The organization strongly considers my goals and values”. The reliability of this scale was .94.
Finally, perceived social support from coworkers and supervisors will be measured with a
form of the Multidimensional Scale of Perceived Social Support (Zimet, Dahlem, Zimet, &
Farley, 1988), modified to relate to the availability or instance of social support in the workplace
received from coworkers and supervisors, as opposed to friends and significant others that were
the initial focus of the instrument. This scale will ask participants to use Likert scale responses
(ranging from 1 = very strongly disagree to 7 = very strongly agree) to indicate their degree of
agreement to statements such as “My coworkers really try to help me”, and “I can count on my
coworkers when things go wrong”. The reliability of this scale was .93, and this scale was
combined with perceived organizational support to create an overall index of available
workplace support.
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Coping success. To measure coping success, I followed a procedure similar to those of
Zautra and Wrabetz (1991), in which participants were presented with a list of 20 coping
strategies from the COPE scale (Carver, Scheier, & Weintraub, 1989), modified to assess daily
behaviors, and were asked to indicate which of these strategies they followed in dealing with the
demands of their workday. Such strategies include “I tried to get advice from someone on what
to do”, “I put aside other activities in order to concentrate on the issues at hand”, and “I took
direct action to get around any problems”. Next, respondents were required to utilize a 5-point
Likert scale (1 = not at all successful to 5 = extremely successful) to indicate the extent to which
the strategies they reported engaging in were successful in helping them cope with their daily
workplace demands. These responses were averaged to create an overall daily workplace coping
success scale, and a variable containing the total number of coping strategies utilized was also
used in the relevant analyses as a control. Coping success was assessed during the second daily
survey, which was randomly signaled during a 2-hour block centered around 3:30 pm.
Participants were expected to be at work at the time when they responded to this survey.
Self-efficacy. To measure self-efficacy, I used a domain-specific scale designed to
conform to Bandura’s (2006) suggestions on the measurement of self-efficacy. As such, this
scale was designed to be specific to the domain of workplace demands, and to moreover be
directly relevant to the work demands examined in this study. The domain of workplace
demands in my study related specifically individuals’ capabilities to respond to and overcome
the demands and pressures exerted to them by their work environment. This scale required
participants to use Likert-scale responses (ranging from 0 = cannot do at all to 10 = perfectly
certain can do), to indicate their confidence in dealing with the workplace demands and social
experiences described above. In this scale, three items referred to each of the work demands
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(workload, emotional demands, role conflict, interpersonal conflict and workplace incivility) for
a total of 15 items. These 5 sub-components of work demands self-efficacy were pilot tested
before the start of the study (see below for results of this pilot-testing). Self-efficacy was
assessed during the second daily survey, which was randomly signaled during a 2-hour block
centered around 3:30 pm. Participants were expected to be at work at the time when they
responded to this survey, and measures provided by participants when they were in other
locations were not be included in the analyses. The average internal consistency reliability of the
self-efficacy subscales was .84, .96, .94, .95, and .94 for emotional demands self-efficacy, role
conflict self-efficacy, interpersonal conflict self-efficacy, workload self-efficacy, and incivility
self-efficacy, respectively.
Subjective well-being. To measure subjective well-being, I followed a multidimensional approach that includes the Diener et al. (1999) conceptualization of subjective wellbeing as comprised of the presence of Positive Affect, the absence of Negative Affect, and a
measure of life satisfaction, as well as additional indicators of (poor) well-being that included
perceived levels of affective distress, experienced strain, and emotional exhaustion (a main
component of occupational burnout; Maslach & Jackson, 1981). Such a multidimensional
approach to the measurement of subjective well-being is appropriate, as subjective well-being
has been described as “broad category of phenomena,” which are distinct yet related in a higherorder fashion (Diener et al., 2003, p. 277). Moreover, this approach captures both positive and
negative aspects of well-being, thus providing a more complete representation of the construct
and more credible data (Diener, 1984). All of these proposed measures of well-being were
modified to reflect currently or daily experienced states as appropriate, and were assessed during

74

the third daily survey, which was randomly signaled during a 2-hour block centered around 7:00
pm. Participants were expected to be at home at the time they responded to this survey.
The Positive Affect and Negative Affect components of subjective well-being were
measured with the 20-item Positive and Negative Affect Schedule (PANAS; Watson & Clark,
1994). For the PANAS, participants were asked to use Likert scale responses (ranging from 1 =
not at all to 5 = extremely) to indicate how accurately twenty adjective mood descriptors
describe the way they feel at the time when they are reporting. For Positive Affect, these
descriptors include “enthusiastic,” “excited,” “proud,” and “determined,” while for Negative
Affect sample descriptors include “upset,” “irritable,” “nervous,” and “hostile.” Across
observations, the average internal consistency reliabilities were .85 and .95 for negative and
positive affect, respectively.
The life satisfaction component was measured with the 5-item Satisfaction with Life
Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985). For this scale, participants were asked
to use Likert scale responses (ranging from 1 = strongly disagree to 7 = strongly agree) to
indicate how accurately each of the five presented statements reflect the way they feel at the time
when they are reporting. The presented statements were modified from the original state to
reflect currently experienced states. Specifically, the five items read as follows: “At this point, in
most ways my life is close to my ideal,” “Currently, the conditions of my life are excellent,” “At
this time, I am satisfied with my life,” “At this point, I have the important things I want in life,”
and “Right now, I feel that if I could live my life over, I would change almost nothing.” The
average internal consistency reliability of the scale was .95.
Experienced strain was measured using the 12-item form of the General Health
Questionnaire (Goldberg, 1992), modified to reflect day-level responses and exclude items that
75

are unsuitable for daily measurement (such as “I lost much sleep over worry”). This instrument
required the participants to use Likert scale responses (ranging from 1 = not at all, to 5 = much
more than usual) to indicate their agreement to statements referring to their experiences of wellbeing on the day they were reporting. These statements include “Today, I have been able to
concentrate on what I’m doing” and “Today, I have been able to enjoy my normal activities”).
The average internal consistency reliability of the scale was .88.
The emotional exhaustion scale was measured using the homonymous 9-item component
of the Maslach Burnout Inventory (Maslach & Jackson, 1981), modified to reflect a same-day
temporal referent. Respondents will be asked to use Likert-scale responses (ranging from 1 =
strongly disagree to 5 = strongly agree) to indicate the degree to which statements like “Today, I
feel emotionally drained” and “Today, I felt too tired to face another day” reflected the way they
felt during the day. The average internal consistency reliability of the scale was .93.
Affective distress was measured with the stress component of the Stress/Arousal
Adjective Checklist (SACL; MacKay, Cox, Burrows, & Lazzerini, 1978). This 10-item scale
required participants to use Likert scale responses (ranging from 1 = not at all to 5 = extremely)
to indicate the extent to which the adjectives provided accurately describe the way respondents
felt during the day. Sample descriptors include “distressed,” “uneasy,” “tense” and “worried”.
The average internal consistency reliability of the scale was .86.
Control variables. A number of trait variables were used as controls, in order to ensure
the robustness of my findings. For control variables, I collected demographics including age,
gender, marital status, number of children, and typical hours worked per week. Moreover, I
collected measures of neuroticism, an important explanatory variable in the investigation of
subjective well-being (Heller et al., 2003), and negative affectivity which relates to stress
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processes and to the experience of daily affect (Watson, 2000). Moreover, in the analyses
involving coping success, total number of coping strategies utilized was also included as a
control. Neuroticism (α = .88) was measured with the 10-item homonymous scale from the
International Personality Item Pool (IPIP; Goldberg, Johnson, Eber, Hogan, Ashton, Cloninger,
& Gough, 2006), and negative affectivity was measured with the PANAS (Watson & Clark,
1994), using instructions appropriate to trait measurement. Finally, at the end of the study,
participants were asked to report, in an open response format, any important events that occurred
in their workplace (such as layoffs, turnover and so on), that might be of importance to my
analyses. The vast majority of events described related to relatively minor events (many of
which, such as increased workload, were already captured by my scales). There was only one
instance of potential layoffs reported in these events, so there did not seem to be any unusual
occurrences in the participants’ work environment during the data collection period that would
unduly bias my results.
Analyses
I used Hierarchical Level Modeling (HLM; Bryk & Raudenbush, 1992) in order to test
the hypothesized day-level relationships between workplace demands and experiences, selfefficacy and subjective well-being, as well as the moderating effects of successful coping,
available resources and previous self-efficacy. In all HLM analyses, I centered the day level
predictor variables relative to the each individual’s mean (group centering) in order to eliminate
confounding sources of variance (such as response biases).
In these HLM analyses, the relevant dependent variable (self-efficacy for Hypothesis 2,
and subjective well-being for Hypotheses 1 and 4) was regressed on the appropriate day-level
variables (as workplace demands and negative experiences for Hypotheses 1 and 2; self-efficacy
77

for Hypothesis 4). To test the cross-level moderating effect of available resources (Hypothesis
6), the resources variables (job control and workplace support) were entered into the second level
of analysis, in order to examine their effects on the slope of the level-1 (or day-level) variables
(controlling for their effect on the β0 intercept). To test the same-level moderating role of prior
levels of self-efficacy (Hypothesis 7) and coping success (Hypothesis 8) on the relationship
between workplace demands and experiences and self-efficacy, the interacting variables as well
as their product term (calculated from group centered variables) were entered into the relevant
HLM models. Finally, to test the hypotheses involving mediation (Hypotheses 5a, 5b, 9 and 10) I
used the series of models prescribed by Baron and Kenny’s (1986) guidelines. In addition, a
series of Sobel tests (Sobel, 1982) were used to test the statistical significance of the mediating
effects; these tests will be conducted using the unbiased z΄ estimators recommended by
MacKinnon, Lockwood, Hoffman, West, and Sheets (2002).
Person-level relationships were tested using OLS regression. Specifically, OLS
regression was used to examine the effects of workplace resources on average levels of
subjective well-being (Hypothesis 3a) and average self-efficacy beliefs (Hypothesis 3b). To test
the hypothesized person-level mediation effect of self-efficacy beliefs on the relationship
between the availability of workplace resources and subjective well-being, I used a series of OLS
regression models as per the Baron and Kenny (1986) guidelines mentioned above, as well as a
Sobel test (Sobel, 1982) to test for the significance of the mediating effect. As this is a singlelevel model, I shall use the regular Sobel z estimator instead of the MacKinnon et al. (2002)
estimators discussed above. The control variables were included in these models to ensure the
robustness of my findings.
Self-Efficacy Scales Pilot Testing
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Before collecting data to test my hypotheses, I conducted a pilot test of the self-efficacy
scales constructed for this study. In this pilot test, the self-efficacy scales, a 10-item work
demands and negative experience scale (composed of 2 sample items from each of the demand
and event factors included in this study; α = .77) and a short 5-item well-being scale (comprised
of items from the General Health Questionnaire; α = .73) were administered through a web
survey to a sample of 202 individuals (66% female, mean age 46.28 years, SD 10.05) employed
full time in a variety of occupations. The self-efficacy subscales demonstrated sufficient levels of
reliability (α = .90 for role conflict self-efficacy, α = .91 for workload self-efficacy, α = .79 for
interpersonal conflict self-efficacy, α = .83 for incivility self-efficacy), with only emotional
demands self-efficacy showing lower levels of reliability (α = .63, α = .67 based on standardized
items).
The self-efficacy scales generally demonstrated relationships with well-being and
workplace demands and experiences in the expected fashion (as expected, the workplace
demands and negative social experiences scale correlated negatively with well-being; r = -.35, p
< .01). All the self-efficacy subscales except for incivility self-efficacy correlated negatively with
the work demands and negative experiences scale, as expected (r = -.12, p < .10 for role conflict
self-efficacy, r = -.22, p < .01 for workload self-efficacy, r = -.18, p < .01 for emotional demand
self-efficacy, r = -.30, p < .01 with interpersonal conflict self-efficacy). In terms of correlations
with well-being, all of the self-efficacy subscales were positively correlated to the well-being
measure (r = .18, p < .05 for role conflict self-efficacy, r = .35, p < .01 for workload selfefficacy, r = .33, p < .01 with interpersonal conflict self-efficacy, and r = .17, p < .05 for
incivility self-efficacy), although the correlation between emotional demand self-efficacy and

79

well-being did not reach significance (r = .11, p < .12), perhaps due to the lower levels of
reliability exhibited by this construct.
Furthermore, a confirmatory factor analysis was supportive of the hypothesized structure
of the self-efficacy component scales. Specifically, a 5 item factor structure fit the data
significantly better than a one factor structure, and also displayed acceptable levels of overall fit
(NFI of .88 vs. .42; NNFI of .89 vs. .34; CFI of .92 vs. .43; GFI of .87 vs. .57; SRMR of .10 vs.
2

.15; RMSEA .10 vs. .24; AIC 70.49 vs. 929.07; ∆χ = 878.57, p < .01). In general, therefore, the
self-efficacy component scales were found to perform adequately in terms of their psychometric
properties, and were judged appropriate to be used in the full dissertation data collection.
Confirmatory Factor Analyses of Daily Measures
A series of confirmatory factor analyses conducted was generally supportive of the
proposed factor structure among my items. In terms of the items measuring daily work demands
and negative social experiences, although a 5 factor structure did not show evidence of excellent
fit, it did fit the data better than a one factor structure (NFI of .84 vs. .39; NNFI of .86 vs. .36;
CFI of .87 vs. .40; GFI of .86 vs. .52; SRMR of .05 vs. .14; RMSEA of .06 vs. .13; AIC of
2

1071.33 vs. 6966.85; ∆χ = 5915.52, p < .01). In terms of the self-efficacy scales, a 5 factor
structure fit the data well, and better than a one factor structure (NFI of .93 vs. .54; NNFI of .92
vs. .47; CFI of .94 vs. .55; GFI of .92 vs. .59; SRMR of .07 vs. .13; RMSEA of .08 vs. .22; AIC
2

of 383.91 vs. 3508.07; ∆χ = 3144.16, p < .01). Finally, in terms of the well-being measures
collected at the end of the day, while the 6 proposed six factor structure did not show evidence of
close fit to the data (likely due to the high number of items included in the CFA), six factors fit
the data better than a one factor structure (NFI of .71 vs. .35; NNFI of .76 vs. .36; CFI of .77 vs.
80

.38; GFI of .80 vs. .51; SRMR of .06 vs. .11; RMSEA of .06 vs. .10; AIC of 2243.96 vs.
2

8310.81; ∆χ = 6096.85, p < .01). See Table 1 for a summary of these analyses.

81

Variance Components of Study Variables
I conducted a variance components analysis to ensure there was adequate variance at the
within person level to proceed with hypothesis testing. In terms of the work demands and social
experiences scales included in this study, all were found to have sufficient levels of withinperson variance. Specifically, the proportion of variance at the within-person level was found to
range from 22.02% (for role conflict) to 45.26% (for incivility experienced). Similarly, in terms
of the self-efficacy scales, estimates of within-person variance proportions ranged from 21.28%
(for incivility self-efficacy) to 32.49% (for emotional demands self-efficacy). The proportion of
within-person variance in number of coping strategies and coping success was also found to be
adequate (45.95% and 57.18%, respectively). Finally, in terms of the well-being scales, only life
satisfaction showed lower levels of variance at the within-person level (11.59%), with the
within-person variance proportions in the other scales ranging from 18.09% (for emotional
exhaustion) to 44.88% (for affective distress). Overall then, the daily measures in general
showed adequate within-person variance for analyses to proceed as planned. For a summary of
variance components and within-person variance proportions for all scales included in this study,
see Table 2.
Correlations among Study Variables
Table 3 presents the means and standard deviations of, and correlations among, the
between-person variables included in this study. Job control was found to be significantly and
positively associated with overall levels of workplace support, while neuroticism was negatively
associated with both job control and workplace support levels. Negative affectivity was also
found to be negatively associated with workplace support, albeit not with job control
perceptions. There was no association between job control or workplace support with any of the
81

demographic variables (gender, number of children, marital status) or with reports of typical
hours worked per week.
In terms of the within-person correlations, the workplace demands and negative social
experiences scales (role conflict, workload, emotional demands, interpersonal conflict, and
incivility) were found to be generally negatively related to the self-efficacy scales, and positively
related to the strain components of subjective well-being (emotional exhaustion and strain
measured with the General Health Questionnaire). Role conflict and workload were also found to
be positively related to number of coping strategies reported, but not to coping success. The selfefficacy scales were found to be generally positively related to positive affect and life
satisfaction, and negatively related to the strain components of subjective well-being and to
negative affect and affective distress. Finally, the number of different coping strategies utilized
was negatively related to the self-efficacy subscales, while coping success was positively related
to the self-efficacy subscales. Coping success was finally found to be negatively related to
experienced strain, emotional exhaustion, affective distress and negative affect. See Table 4 for
means and standard deviations of, and within-person correlations among, the repeated measures
variables included in this study.

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Tests of Hypotheses

Hypothesis 1
Hypothesis 1 posited that workplace demands and negative social experiences are going
to relate negatively to individual levels of subjective well-being at the within-individual level.
Controlling for demographic variables, hours worked, and negative affectivity and neuroticism,
role conflict and workload were significantly related to emotional exhaustion (standardized γ’ =
.28, p < .01, and γ’ = .22, p < .01, respectively), while emotional demands were found to be
significantly related to both experienced strain and emotional exhaustion (γ’ = .17, p < .01, and
γ’ = .25, p < .01, respectively). In terms of negative social experiences in the workplace, both
interpersonal conflict and incivility were found to be associated with experienced strain (γ’ = .24,
p < .01, and γ’ = .35, p < .01, respectively), emotional exhaustion (γ’ = .23, p < .01, and γ’ = .25,
p < .01, respectively), affective distress (γ’ = .18, p < .01, and γ’ = .13, p < .05, respectively), and
negative affect (γ’ = .16, p < .01, and γ’ = .12, p < .05, respectively). Finally, interpersonal
conflict was found to be negatively related to life satisfaction (γ’ = -.17, p < .05), although
incivility was not. In general then, workplace demands were found to be significantly related to
the strain components of well-being, while negative social experiences were found to also be
related to the negative affective components of well-being (affective distress and negative
affect). However, none of the predictors were found to be related to positive affect, and only
interpersonal conflict was associated with levels of life satisfaction. Hypothesis 1 was thus
partially supported. Please see Tables 5 to 9 for a summary of these analyses.

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Hypothesis 2
Hypothesis 2 referred to the relationship of workplace demands and negative social
experiences to self-efficacy beliefs about these workplace demands and negative social
experiences. All hypothesized relationships were significant and in the expected direction, with
role conflict, workload, emotional demands, interpersonal conflict, and incivility negatively
predicting self-efficacy beliefs related to the same dimensions (γ’ = -.20, p < .05 for role conflict,
γ’ = -.22, p < .01 for workload, γ’ = .24, p < .01 for emotional demands, γ’ = -.31, p < .01 for
interpersonal conflict, and γ’ = -.31, p < .01 for incivility). In other words, individuals exposed to
workplace demands or negative social experiences were more likely to report feeling less
confident in their ability to effectively engage the experienced demand or experience. Overall
then, Hypothesis 2 was fully supported (see Table 10).
Hypothesis 3
Hypothesis 3 argued that workplace resources are going to have a positive relationship
with (a) subjective well-being and (b) self-efficacy beliefs, such that those with higher levels of
resources are going to report higher average levels of well-being and self-efficacy compared to
individuals with lower levels of resources. In terms of individual resources, results indicated that
job control was not associated with subjective well-being or self-efficacy beliefs (p > .10 for all
variables). Available workplace support levels, however, did negatively predict emotional
exhaustion (γ’ = -.43, p < .01) and positively predicted life satisfaction (γ’ = .25, p < .05).
Similarly, available workplace support was positively and significantly related to average levels
of self-efficacy for all subscales (γ’ = .40, p < .01 for role conflict self-efficacy, γ’ = .37, p < .01
for workload self-efficacy, γ’ = .33, p < .01 for emotional demands self-efficacy, γ = .43, p < .01
for interpersonal conflict self-efficacy, and γ’ = .26, p < .05 for incivility self-efficacy). In
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general, then, Hypothesis 3a was partially supported and Hypothesis 3b was fully supported for
workplace support, but not for job control.
Hypothesis 4
Hypothesis 4 concerned the relationship between self-efficacy beliefs and subjective
well-being. Role conflict self-efficacy was found to relate to strain and emotional exhaustion
negatively (γ’ = -.16, p < .01, and γ’ = -.12, p < .05, respectively) and to life satisfaction
positively (γ’ = .14, p < .05). Workload self-efficacy was found to relate to all subjective wellbeing measures except for positive affect (γ’ = -.23, p < .01 for strain, γ’ = -.17, p < .01 for
emotional exhaustion, γ’ = -.16, p < .01 for affective distress, γ’ = -.12, p < .05 for negative
affect, and γ’ = .17, p < .01 for life satisfaction). Emotional demands self-efficacy was found to
be negatively related to strain and emotional exhaustion (γ’ = -.21, p < .01 and γ’ = -.26, p < .01,
respectively), and positively related to life satisfaction (γ’ = .14, p < .05). A similar pattern of
results was found for interpersonal conflict self-efficacy (γ’ = -.23, p < .01 for strain, γ’ = -.17, p
< .05 for emotional exhaustion, γ’ = .23, p < .01 for life satisfaction), while incivility selfefficacy was negatively related to strain (γ’ = -.23, p < .01), emotional exhaustion (γ’ = -.22, p <
.01), and affective distress (γ’ = .12, p < .05), and positively related to life satisfaction (γ’ = .22,
p < .05). In general then, self-efficacy components were found to consistently relate to strain and
emotional exhaustion negatively, and to life satisfaction positively, except for workload and (to a
lesser degree) incivility self-efficacy which were found to predict a wider range of subjective
well-being outcomes. Thus, Hypothesis 4 was partially supported (see Tables 13 to 17 for a
summary of these analyses).

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Hypothesis 5
Hypothesis 5 posited that the effects of workplace demands and negative social
experiences on subjective well-being would be partially mediated by self-efficacy beliefs. Selfefficacy was indeed found to mediate a number of these relationships. In models predicting
subjective well-being from self-efficacy beliefs, controlling for the appropriate demand or social
experience dimension, role conflict self-efficacy partially mediated the effects of role conflict
and workload on experienced strain (z’ for the significance of the mediated effect = 2.47, p < .05
and z’ = 2.87, p < .01, respectively); the decrease in the magnitude of the demand coefficients
once self-efficacy was accounted for, however, was fairly small. In terms of emotional demands,
emotional demands self-efficacy partially mediated the effects of emotional demands on strain
and emotional exhaustion (z’ = 2.63, p < .05). For the negative social experience variables,
interpersonal conflict and incivility self-efficacy mediated the effects of interpersonal conflict
and incivility, respectively, on experienced strain (z’ = 2.07, p < .05 and z’ = 2.09, p < .05).
Apart from these direct mediation effects, however, self-efficacy beliefs were also found
to provide a link for indirect effects of workplace demands and negative social experiences on
subjective well-being. Specifically, workload was found to indirectly relate to emotional
exhaustion, negative affect, and weakly to affective distress through self-efficacy beliefs (z’ =
2.33, p < .01, 2.82, p < .01, and z’ = 1.93, p < .10). Similarly, both role conflict and workload
were indirectly related to life satisfaction through the relevant self-efficacy components (z’ =
2.20, p <.05 and z’ = 2.12, p < .05, respectively). There was some evidence, therefore, for a
partial mediating role of self-efficacy, and for the significance of self-efficacy as a pathway
through which workplace demands can affect subjective well-being. Hypothesis 5 was therefore
partially supported (see Tables 18 to 22 for a summary of these analyses).
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Hypothesis 6
Hypothesis 6 posited that the availability of workplace resources (job control and
workplace support) would moderate the relationship between workplace demands and
experiences and (a) self-efficacy beliefs and (b) subjective well-being. In terms of self-efficacy,
job control was found to moderate the effects of both emotional demands and interpersonal
conflict on the relevant self-efficacy dimensions, such that the negative relationship between
these factors was mitigated with high levels of job control (γ’ = .18, p < .05 and γ’ = .19, p < .05,
respectively; see Figures 4 and 5). While the availability of workplace support did have a main
positive effect on all self-efficacy dimensions, it was not found to moderate the relationship
between workplace demands and negative social experiences and their relevant self-efficacy
dimensions. Hypothesis 6a was thus partially supported for job control, and not supported for
workplace support (see Tables 23 and 24).
In terms of Hypothesis 6b, job control was not found to moderate any of the relationships
between workplace demands and negative social experience and subjective well-being. The
availability of workplace support did provide a significant mitigating effect in the relationship of
workload and emotional demands to emotional exhaustion (γ’ = -.12, p < .05, γ’ = -.09, p < .05,
and γ’ = .09, p < .05, respectively; see Figures 6 & 7). The moderating effect of workplace
support on the workload-life satisfaction and incivility-emotional exhaustion relationships was
also significant, albeit in the opposite direction (γ’ = .09, p < .05 and γ’ = -.10, p < .01,
respectively; see Figures 8 & 9). Overall then, Hypothesis 6b was not supported at all for job
control, and only partly supported in terms of emotional exhaustion for the availability of
workplace support (see Tables 25 to 34).

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Hypothesis 7
Hypothesis 7 related to the moderating effect of prior (previous day) self-efficacy levels
on the relationship between workplace demands and negative social experiences and (a) selfefficacy beliefs, and (b) subjective well-being. In terms of self-efficacy beliefs, no moderating
effect for prior self-efficacy level was found. Interestingly, there was no significant main effect
of previous self-efficacy levels on current levels of these beliefs either. Hypothesis 7a was thus
not supported (see Table 35).
In terms of subjective well-being outcomes, no significant moderating effect of prior selfefficacy beliefs was found on the effects of role conflict or emotional demands. For workload,
prior self-efficacy beliefs moderated the effects of workload on experienced strain (γ’ = -.14, p <
.05; see Figure 10) as well as on positive affect (γ’ = .07, p < .05; see Figure 11), with the
direction of these effects being as hypothesized. A similar moderating role (also in the
hypothesized direction) was found for prior self-efficacy beliefs on the effects of interpersonal
conflicts on emotional exhaustion (γ’ = -.19, p < .01; see Figure 12), affective distress (γ’ = -.07,
p < .05; see Figure 13) and life satisfaction (γ’ = .19, p < .01; see Figure 14). Finally, prior selfefficacy beliefs moderated the effects of incivility on positive affect and life satisfaction (γ’ =
.07, p < .05, and γ’ = .15, p < .05, respectively; see Figures 15 and 16) as hypothesized; there
was, however, a significant moderating effect on negative affect that was in the opposite
direction than expected (γ’ = .13, p < .05; see Figure 17). Overall then, Hypothesis 7b was
partially supported (see Tables 36 to 40).
Hypothesis 8
Hypothesis 8 posited that coping success would moderate the relationship of workplace
demands and negative social experiences to (a) self-efficacy beliefs, and (b) subjective well88

being. In terms of self-efficacy beliefs, coping success was found to significantly moderate the
effects of workload on workload self-efficacy in the expected direction (γ’ = .16, p < .05; see
Figure 18); no other significant moderating effects were found. Hypothesis 8a thus was only
supported for workload, with none of the models concerning the other work demands and social
experiences showing a significant interaction term. Coping success, however, did have a
significant and positive main effect on all self-efficacy outcomes except for emotional demands
self-efficacy (see Table 41 for a summary of these analyses).
In terms of the subjective well-being outcomes, coping success did not significantly
moderate the effects of role conflict, or workload on subjective well-being. It did show a
significant moderating effect for the effects of emotional demands and interpersonal conflict on
emotional exhaustion, albeit this effect was in the opposite direction than expected (γ’ = .11, p <
.05 and γ’ = .14, p < .05, respectively; see Figures 19 and 20). Also in the opposite than expected
direction was the moderating effect of coping success on the relationship between interpersonal
conflict and positive affect (γ’ = -.26, p < .01; see Figure 21). The only effect found in the
expected direction was the moderation of the incivility – positive affect relationship (γ = .10, p <
.05; see Figure 22). Hypothesis 8b was thus not supported (see Tables 42 to 46 for a summary of
these analyses).
Hypothesis 9
Hypothesis 9 posited that coping success will mediate the moderating effects of (a)
workplace resources and (b) prior self-efficacy levels on the relationship of work demands and
negative social experiences to self-efficacy beliefs. Although workplace support did not have any
significant moderating effect, analyses proceeded to investigate whether workplace support
affects self-efficacy though its association with coping success (thus confirming an indirect
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mediated moderation effect). Similarly, although job control and prior efficacy beliefs did not
have a moderating effect on all tested relationships, analyses proceeded to investigate indirect
mediated moderation effects through coping success.
To begin testing for mediation, I investigated the relationship of (a) workplace resources
(job control and workplace support) and (b) previous self-efficacy beliefs on coping success.
Although both job control and workplace support were significantly related to average levels of
coping success (γ’ = .20, p < .05 and γ’ = .26, p < .05, respectively), there was no association
between any of the self-efficacy components and coping success. Hypothesis 9b was thus not
supported, therefore I proceeded to test for mediation only with regard to Hypothesis 9a. Coping
success was again found onto moderate the relationship between workload and workload selfefficacy, and the test of significance for an indirect effect between coping success and workplace
support and job control was at least marginally significant (z’ = 1.82, p < .10 for job control, z’ =
2.09, p < .05 for workplace support). There was, however, a significant relationship between
coping success and self-efficacy for both the job control and workplace support models that can
provide an alternative pathway though which workplace resources can affect self-efficacy beliefs
indirectly. Hypothesis 9a was thus only supported for the relationship between workload and
workload self-efficacy.
Hypothesis 10
Hypothesis 10 posited that coping success will mediate the moderating effects of (a)
workplace resources and (b) prior self-efficacy levels on the relationship between work demands
and negative social experiences and subjective well-being. Based on the relationships between
resources and previous self-efficacy beliefs reported above, Hypothesis 10b was not supported,
and analyses proceeded only with regards to Hypothesis 10a. Results, however, again either did
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not provide support for a buffering effect of coping success that could mediate other moderating
effects, or was in other than the expected direction (as with Hypothesis 8). The only effect that
was in the expected direction was again the moderation of coping success on the incivility positive affect relationship (γ’ = .10, p < .05 for the job control models, γ’ = .10, p < .05 for the
workplace support models). Hypothesis 10 was thus not supported.

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Discussion

Overall, results were supportive of the main effects hypothesized in this study, although
support for the proposed moderators was inconsistent. Workplace demands and negative social
experiences were generally associated with decreased levels of well-being, with these effects
being particularly consistent in terms of experienced strain and emotional exhaustion. Workplace
demands and negative social experiences were also found to consistently and negatively relate to
self-efficacy beliefs, and these self-efficacy beliefs were in turn associated with subjective wellbeing, providing a mediating or indirect effect from workplace demands and negative social
experiences to subjective well-being outside of work. Workplace support was associated with
higher levels of self-efficacy beliefs, lower levels of strain, and higher levels of life satisfaction,
but job control did not predict any of these outcomes. In terms of work demands and experience
effects, the well-being outcomes best predicted by the model were experienced strain and
emotional exhaustion for the work demands variables, and experienced strain, emotional
exhaustion, affective distress and negative affect for the negative social experiences variables. In
terms of the self-efficacy scales, the well-being outcomes predicted most consistently were
strain, emotional exhaustion and life satisfaction. Positive affect was not consistently related to
any of the examined variables.
In terms of the hypothesized moderating effects, results were much less consistent. The
data did not provide any evidence for a moderating role of job control on the relationship of
workplace demands and experiences to well-being, but job control did have a significant effect
on the relationship of emotional demands and interpersonal conflict to self-efficacy beliefs
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relevant to these factors. The availability of workplace support did moderate the effects of
workload and emotional demands on emotional exhaustion, but did not moderate any of the
relationships of workplace demands and experiences to self-efficacy beliefs. Prior self-efficacy
levels showed some evidence for their role as moderators of the relationships contained in the
model, providing a buffering role on the effects of workload, interpersonal conflict, and incivility
on individual well-being; however, previous self-efficacy was not found to moderate the
relationship between work demands and negative social experiences and self-efficacy beliefs
related to these factors. In terms of coping success, although it was found to significantly
moderate the effects of workload on workload self-efficacy, coping success did not have a
significant moderating effect on any of the other relationships examined. Coping success did,
however, have a consistent significant main effect on self-efficacy beliefs, as well as on two
components of well-being (experienced strain and affective distress).
Implications for Theory
The implications of these results for theory mainly relate to the basic theories utilized as a
background for this model (the demands/control model, self-efficacy theory, and the
transactional model of stress), although other theoretical frameworks can also be potentially
informed by this study.

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Demands/Control/Support Model. In general, results were not supportive of the
moderating hypotheses of the demands/control model, with job resources providing inconsistent
moderating effects on the relationship of work demands and negative experiences to subjective
well-being (although the relationship perhaps closest conceptually to the original predictions of
this model, namely that between workload and emotional exhaustion, was indeed moderated by
workplace support).
The factors included in the demands/control model, did however demonstrate some
consistent main effects, with both workplace demands and negative social experiences predicting
well-being (mostly the components related to strain or low well-being) at the end of the day, and
workplace support also had direct effects on well-being. These findings thus provide little
support for the buffering hypothesis of the demands/control model (except as mentioned above),
but do support the direct effects propositions of the model.
Different workplace events also were found to differentially relate to well-being
outcomes, with work demands (role conflict, workload, and emotional demands) being only
related to strain and emotional exhaustion, and with negative social experiences being related to
strain, emotional exhaustion, affective distress and negative affect. This potential for differential
effects is not currently well explained by the theory, but does indicate that the various workplace
stressors can potentially affect different aspects of well-being. It is possible that social
experiences in the workplace show greater affective responses because they pose a threat to the
continuing satisfaction of different needs compared to work demands (relatedness versus
competence; see Ryan & Deci, 2000). Alternatively, the satisfaction of the various needs can
directly relate to affective versus lack-of-strain indicators of well-being, such that the failure to

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satisfy relatedness needs increases affective distress as well as strain, while failure to satisfy
competence needs on results in increases in levels of experienced strain.
Moreover, there might be a deeper difference in the way work demands and negative
social experiences are conceptualized. Negative experiences might be functionally much closer
to affective events (see Weiss & Cropanzano, 1996) compared to workplace demands, in that
they begin and end more quickly and with greater distinctiveness relative to their “beginning”
and “end.” On the other hand, workplace demands could represent more of an ongoing
situational characteristic that, while potentially affecting the individual adversely in terms of
stress, do not invoke a strong affective response (or one that is much closer to moods rather than
affect or discrete emotions; see Thayer, 1996).This would imply that models of workplace
functioning need to consider these two categories of workplace features more carefully and with
greater discretion between the two, or utilize separate conceptual models to explain their effects
(for examples, see Spector & Fox, 2002; Weiss & Cropanzano, 1996).
These differential predictions also have implications for the aspects of well-being
investigated by models of workplace functioning. In other words, the fact that different aspects
of well-being are not all predicted by the same workplace events might mean that the various
dimensions considered part of well-being do not represent as tight a nomological net as
previously thought. This implies that, for example, a low level of experienced strain is not
necessarily associated with high levels of the positive indicators of well-being such as life
satisfaction or high levels of positive affect. The direct implication of this for the demands/
control model is that expanding it to include more diverse aspects of well-being might be
empirically or theoretically appropriate, and that future work needs to consider indicators of low
and high well-being in a more separated fashion (for an example, see Karademas 2007).
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This study also did not find any evidence for a main or moderating effect of job control,
although there was some evidence for the importance of workplace support for individual wellbeing. While this provides some additional evidence for the support component of the
demands/support aspect of the model, the fact that job control failed to predict any of the
outcomes of interest does raise some interesting points. A potential implication is that the effects
of job control are more subject to moderating influences on the part of contextual or individual
factors. For example, Schaubroeck and colleagues (Schaubroeck et al., 2000; Schaubroeck et al.,
2001) found that job support was only beneficial for individuals with high levels of self-efficacy;
a similar or related moderated effect could also have occurred in this research context. This
would indicate that although the effects of workplace support might be applicable to a greater
variety of individuals and situations, the utility of job control is more narrow or specific.
Another possibility is that, while the main or moderating effects of workplace support
might be linear in nature, with higher levels of workplace support providing consistently higher
levels of utility to the individual, the effects of job control are more related to reaching a specific
threshold to at which the individual benefits, with further increases in job control being of minor
importance; indeed, the data presented by Karasek (1977) when introducing the demands/control
model are fully compatible with this possibility. In this study, a set of exploratory analysis did
1

not clearly demonstrate the existence of such non-linear effects , although the lack of significant

1

No significant curvilinear effects were found in the models predicting well-being from
workplace resources (workplace support and job control). In predicting self-efficacy, there was
only one instance of a significant curvilinear effect, for the relationship between interpersonal
conflict self-efficacy and workplace support (γ = -.19, p < .05). There was also a significant
curvilinear effect in the moderating role of job control in the relationship between interpersonal
conflict and interpersonal conflict self-efficacy (γ = -.17, p < .01), and in the relationship
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and consistent non-linear effects could be due to a lack of power at the higher level of analysis
since this study was not optimized to test such effects.
Finally, the underlying needs satisfied by these workplace resources might fluctuate
between people to a varying extent. If the need for autonomy (which provides some theoretical
basis on why job control is beneficial to individuals) fluctuates more between people than the
need for relatedness (which provides a similar theoretical basis for the effects of the social
components of workplace support), this could indicate that job control is only important for a
narrower subset of the population, compared to the availability of workplace support. Selfdetermination theory does acknowledge the potential for different need orientations (see Black &
Deci, 2000; Deci & Ryan, 1995); a joint investigation of the phenomena involved in the demands
control model and self-determination theory could shed some light into how these two
frameworks might jointly predict well-being outcomes.
Self-Efficacy. The fact that daily fluctuations in self-efficacy were also found to be
predicted by work demands, and in turn predictive of individual well-being, implies that selfefficacy should be more closely considered as a construct central to workplace functioning.
These results further underline the importance of self-efficacy beliefs for a host of individuallevel outcomes, and provide some evidence for how self-efficacy beliefs are formed as a result of
workplace factors.

between workload and affective distress (γ = -.18, p < .05). Finally, in terms of the non-linear
moderating effects of workplace support, there was a curvilinear moderating effect for the
relationship between role conflict and negative affect (γ = -.17, p < .05), for the relationship
between emotional demands and positive affect (γ = -.14, p < .05), and for the relationship
between workload and emotional exhaustion (γ = .20, p < .01).
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Specifically, the results were generally supportive of the role of workplace demands and
negative social experiences in negatively affecting self-efficacy beliefs. Individuals exposed to
high levels of work demands tended to report reduced levels of these beliefs, most likely due to
these demands leading to experienced difficulties or to what could be perceived as unsustainably
high levels of effort. In other words, when individuals experienced workplace demands that were
higher than normal, this likely resulted in them experiencing some momentary fatigue, distress,
or concern about the level of effort required to cope, which then negatively affected their beliefs
in their capabilities to successfully cope with future demands. These effects are in line with the
mechanisms proposed by Bandura (1997) on self-efficacy belief formation, and add some
additional empirical evidence to this literature.
Furthermore, the availability of workplace support was significantly associated with all
measured components of workplace self-efficacy. The availability of workplace support can be
seen as a safety net that individuals perceive in the workplace, thus feeling that help will be
provided if needed and accordingly increasing their confidence in successfully meeting future
challenges. Moreover, as Bandura (1997) argued, higher levels of workplace support can be
associated with increased social persuasion processes, whereby individuals are provided with
encouragement and positive views on their own capabilities by others around them, leading to
increased self-efficacy.
Moreover, this last finding can provide a linkage between models of workplace
investigating the relationships between demands, resources, and well-being and self-efficacy
frameworks, by providing a pathway through which workplace resources can enhance or benefit
individual well-being. That is, this linkage can shed light on potential mechanisms through

98

which workplace resources provide benefits to employees, thus improving the theoretical clarity
of these models.
In terms of predicting state levels of self-efficacy beliefs, the fact that prior self-efficacy
levels failed to predict current self-efficacy beliefs in the models presented (with the exception of
incivility self-efficacy) in this study invokes some interesting considerations. A likely possibility
is that self-efficacy beliefs could be even more malleable than previously thought, and that
individuals rapidly revised them to reflect current workplace realities. This can have implications
for state versus trait conceptualizations of this construct, because if self-efficacy beliefs are
indeed rapidly revised as a result of individual experience then perhaps general trait self-efficacy
conceptualizations (for example, see Chen, Gully, & Eden, 2001) might not adequately capture
the nature of this construct. There is, however, the possibility that the failure of self-efficacy
beliefs to persist across days could be an artifact of group centering and regression to the mean
effects; in other words, individuals who experienced high levels of self-efficacy (relative to their
average level) were likely to persist in such beliefs the following day, but also likely to naturally
revert to their default level of self-efficacy beliefs, with these two effects cancelling each other
out for an overall null relationship. Therefore, while the questions generated by these null effects
are interesting, more research is needed to fully understand what they would mean for theories of
self-efficacy.
This study also found a relationship between self-efficacy and individual levels of
subjective well-being. These results have implications for a variety of models of workplace
functioning, well-being, and stress, by positioning self-efficacy as an important predictor of
individual outcomes of this nature. In fact, self-efficacy beliefs were generally a more consistent
predictor of well-being than workplace demands and experiences, although this could be due to
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the increased temporal distance between the measurements of demands, self-efficacy, and wellbeing rather than a stronger association of well-being with self-efficacy beliefs. Still, the results
of this study do point to the importance of self-efficacy in predicting well-being (particularly
experienced strain, emotional exhaustion, and life satisfaction), something that can be of use to a
number of well-being frameworks, by positing self-efficacy as a mediator of the effects of
workplace features, characteristics, or episodes, on subjective well-being.
Self-efficacy beliefs did not, however, show a significant relationship with positive
affect, and their relationship with other affective indicators of well-being (specifically, affective
distress and negative affect) were somewhat inconsistent. Similar to the varying effects of
workplace demands in predicting different well-being dimensions, these results provide more
support to the idea that more attention needs to be paid to the specific aspects of well-being
being examined by each particular theoretical framework or empirical study, and to their
relationship with specific aspects of workplace self-efficacy beliefs.
In terms of self-efficacy measurement issues, this study can also be seen as demonstrating
the feasibility of constructing targeted self-efficacy scales that focus on specific workplace
demands and negative social experiences. With minor alterations to the scale construction
process, it seems it would be relatively simple to devise self-efficacy scales that relate to a
variety of other workplace factors (such as interactions with customers, or to the completion of
specific tasks), thus facilitating targeted research efforts. In short, this study demonstrated that
Bandura’s (2006) self-efficacy scale construction guidelines, when paired with existing
constructs measuring workplace factors, can result in scales of sufficient predictive validity and
good psychometric properties in a simple and expedient fashion.
Transactional Stress Model. Coping, one of the basic components of the transactional
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stress model (Lazarus & Folkman, 1984), was found to be an important predictor of subjective
well-being in this study. These findings thus provide support for the central tenets of the
transactional stress model, as well as potentially relating to the importance of fulfillment of
competence needs discussed by Ryan & Deci (2000). The conceptualization of coping used,
however, focused on general coping success rather than the discrete coping strategies often
utilized in stress research (for example, see Carver et al., 1989). The primary implication of this
for the transactional stress model is that, in dealing with workplace stressors, it might matter less
what strategies people utilize and more how well these strategies are utilized. That is, any coping
strategy followed can be of benefit to the individual, as long as this strategy is successful in
avoiding or alleviating the stressor at hand, in contrast to previous views that some coping
strategies are by their nature more successful than others.
This contention was further supported by a series of tests estimating differences in
average success of each strategy measured in this study; although some differences achieved
statistical significance, these effects were of minor practical importance. Nevertheless, there are
some alternative explanations to consider. First, the coping strategies selected for this study were
those that would be most applicable to (and effective in) an organizational setting; this might
have resulted in reduced variance in their means level of success due to the fact that they were
all, to some extent, appropriate for the context. If more maladaptive or counterproductive coping
strategies (such as venting or workplace disengagement) were included this could reveal
differences in average coping success between these strategies and the ones included in my
study. However, apart from purely maladaptive coping strategies such as alcohol or drug abuse,
there would probably be little theoretical reason to expect average success differences between
the coping strategies examined in this study and any alternative ones excluded.
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Second, individuals could be repeatedly selecting strategies that have served them well in
the past (or fit best to their disposition or occupation), thus increasing coping strategy success
levels beyond what would be expected. This alternative explanation, however, would still mean
that coping success, not coping type, is a more appropriate predictor of individual well-being, as
that would imply differences in coping strategies followed between individuals (in line with
previous research), but less differences in how well these strategies can counteract the effects of
workplace stressors (supporting the importance of coping success for well-being).
Finally, the design of this study did not include frequency assessments of coping
strategies followed (as would be the case in most traditional coping research), which makes a
direct empirical comparison between traditional operationalizations and my coping success
construct impossible with the existing data. These results, however, do provide some initial
evidence for the importance of coping success that can inform and extend future work on the
transactional stress model and related frameworks.
Coping success did, however, emerge as an overall important component of workplace
functioning, as it was positively associated with increased levels of self-efficacy beliefs in
addition to the subjective well-being effects discussed above. In general, when individuals
perceived greater success in coping with workplace demands and negative social experiences,
they also reported higher levels of self-efficacy beliefs across all dimensions (except for
emotional demands self-efficacy, for which this effect did not achieve significance). This
provides support for Bandura’s (1997) assertion of mastery experiences as a source of selfefficacy, and represents an empirical synthesis of self-efficacy theory and the transactional
model of stress. The implications of this are that both self-efficacy and coping success emerge as
important variables in considering how individuals experience and react to social occurrences
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and stressors in their workplace, and can thus inform future research on workplace events, stress,
or well-being.
Furthermore, average coping success was positively associated with the availability of
workplace resources (workplace support and job control), providing a potential pathway that can
explain the previously reported relationships of these workplace resources with well-being. That
is, workplace resources could benefit the individual in part because they allow them to manifest
coping strategies in a more successful fashion, thus counteracting the negative effects of
workplace stressors and other negative events.
Similar to workplace resources, however, coping success was not found to play a
significant moderating role in the relationship of workplace demands and negative social
experiences to subjective well-being (with the exception of the relationship between workload
and workload self-efficacy, where coping success manifested the hypothesized moderating
effect). The implications of this finding is that coping success can be better thought of as
counteracting the effects of workplace stressors (that is, exerting an effect on well-being of the
opposite sign relative to stressors) rather than providing a buffering effect to the individual (or
affecting the magnitude of the relationship of stressors and self-efficacy to well-being outcomes).
While this initial investigation on coping success is not sufficient to fully address the issue of
main versus moderated effects of coping, it can inform future research that seeks to explicitly test
these two potential mechanisms of action.
Moreover, as with workplace demands and negative social experiences and self-efficacy
beliefs, coping success was mostly associated with the experienced strain and affective distress
components of subjective well-being, with no significant relationship being found with positive
or negative affect and life satisfaction. This again underlines the importance of considering sub103

components of subjective well-being separately in constructing theoretical arguments about their
relationship with workplace events and experiences, and of the potential mediators or moderators
of this relationship.
However, in informing theory on stress and coping care must be taken to not equalize
coping success with improvements in well-being, as this would introduce tautology concerns in
the literature. In this study, coping success was conceptualized as success in dealing with the
workplace stressor at hand, not with the resulting strain or stress. In other words, the construct of
coping success focuses on the effectiveness of the behaviors that individuals use in engaging,
removing, or otherwise avoiding workplace demands and negative social experiences, not with
the ways in which individuals manage the experienced distress or other reductions in their wellbeing that have come about as a results of workplace experiences. This is not to say that the latter
is not an important topic of investigation, but rather to differentiate behaviors aimed at stressors
versus behaviors aimed at the stressors’ effects.
Implications for Practice
The results of this study can also have important implications for practice. Organizations
that seek to improve employee subjective well-being can do so through interventions or
programs in a variety of areas. First, these programs can aim to increase available workplace
resources, which can include workplace such as work redesign programs to increase job control,
or leadership initiatives to increase the amount of workplace support that is available to
employees. Furthermore, organizations can implement programs designed to improve individual
levels of self-efficacy through, for example, improved training in time management or conflict
resolution. This can help individuals feel more confident in their ability to successfully resolve a
wider variety of workplace events, thus increasing their self-efficacy beliefs. Finally, other
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training approaches can directly aim to improve employee coping skills, providing employees
with more options they can use and better proficiency at implementing these options.
When attempting to enhance individual levels of resources, however, organizations must
ensure that this does not turn into into a zero-sum game in which some employees benefit from
increased workplace resources at the expense of other employees. The workplace resource for
which this is perhaps most likely to be a concern is job control, in which increased control for
some employees might result in decreased control for others (by, for example, enhancing an
employee’s control over the job by reducing the control of their supervisor over them). The best
way to avoid this is to look for aspects of the work that employees specifically desire control
over in order to function best at the workplace, and that at the same time represent a task burden
or hassle for their superiors (or, at the very least, are not central to superiors’ task performance or
workplace functioning). In other words, workplace interventions that seek to identify and transfer
control over the aspects of the job that are beneficial to one party and harmful (or at least neutral)
to others are most likely to be successful in enhancing workplace resources for employees
without reducing workplace resources for others.
The relationship between the coping success construct included in this study and
individual levels of self-efficacy and well-being can further inform interventions aimed at
increasing employee self-efficacy or well-being by underlining the importance of the ultimate
effectiveness of coping, rather than the specific coping strategy selected in terms of predicting
important individual outcomes (although see the discussion above for an overview of alternative
explanations). Although there is probably still value in educating employees about different
coping strategies, helping employees refine and improve on the strategies that they are more

105

comfortable with or that are more applicable to their situation could represent a reliable way to
enhance employee well-being.
Although there is still some theoretical uncertainty on the exact way the three factors
mentioned above (workplace resources, self-efficacy, and coping) operate in terms of main or
moderated effects, such a question is arguably of less concern when considering practical
applications (compared to theoretical and empirical efforts). That is, in terms of workplace
interventions or other programs designed to improve employee well-being or increase selfefficacy, the question of moderating versus main effects is less important than it is in academic
terms. This means that organizations can provide a benefit to their employees by taking measures
designed to make more workplace resources available to them (or by helping increase their
coping capabilities and self-efficacy levels), with the exact nature of the mechanism by which
these benefits accrue being of secondary importance.
Furthermore, these results indicate that organizations can improve employee well-being
by directly addressing the negative impact of work demands and negative workplace
experiences. While some demands such as workload might perhaps not be directly addressable
(see below), other demands such as role conflict could be potentially targeted by improved
communication and lines of command, clearer goal-setting, and a more accessible code of
conduct or set of rules that employees could apply; reducing these “non-essential” demands
would be expected to result in improvements in employee well-being without unduly affecting
organizational effectiveness and functioning.
Workload could be harder to directly reduce because workload fluctuations would imply
that eliminating high workload levels would require introducing substantial slack into the
workday at considerable cost to the organization. Nevertheless, organizations can still have some
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options when attempting to manipulate workload levels to protect employee well-being.
Specifically, job design efforts could seek to identify optimal levels of workload for each
occupation or class of employee, with the focus then being shifted towards keeping deviations
from that optimal workload level to a minimum Moreover, organizations can incorporate
examinations of person-workload fit into their selection mechanisms, thus selecting for
individuals that are best matched for the levels of workload (or workload fluctuations) that are
typical of the position at hand. Alternatively, employees could be assigned tasks that best fit their
current psychological and physiological state, ensuring (to the extent that this is possible) that no
single employee is exposed to high levels of workload over a prolonged period of time. Finally,
workload levels (or fluctuations of workload) could be managed by the introduction of work
teams or closely collaborating groups that provide helping and other supportive behaviors to
their overwhelmed members, thus creating slack within the group that can be allocated to
specific tasks as needed.
On the other hand, the findings of this study showing a negative relationship between
negative social experiences (interpersonal conflict and incivility) and subjective well-being point
to the importance of establishing and maintaining a safe and positive work climate. Establishing
an organizational climate in which civility is strongly encouraged could be particularly helpful;
eliminating conflict is not always possible, and doing so could also have important negative
organizational implications (see Jehn, 1995). Because incivility does not seem to have any
potential benefits to the organizations and is generally established as an undesirable norm in
most cases of human interaction, interventions designed to reduce instances of incivility by
educating employees on its costs or by providing rewards for civil behavior could be very
successful and ultimately result in increased levels of employee well-being.
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Limitations
As with any research, this study has a number of limitations that need to be
acknowledged. First, all the variables included in this study were assessed using self-reported
measures, which might create some concerns about common methods bias (see Podsakoff,
MacKenzie, Lee, & Podsakoff, 2003). However, these concerns could be somewhat alleviated by
the fact that the independent, mediator, and dependent variables were all separated in time, by
placing them in different measurement occasions as typical with such designs (for an example,
see Ilies et al., 2010). Furthermore, the nature of some of the constructs (such as self-efficacy)
included in this study is such that self-reports are likely the only feasible measurement option
available. However, some common methods variance concerns do remain, and this is a limitation
of this study that needs to be acknowledged.
First, it is possible that the collection of the study data exerted a reactive effect on
participants (see Ilies et al., 2010), thus changing their attitudes, affect, or behavior in the
workplace. This concern is perhaps most prominent when considering the coping success
measure, due to two potential mechanisms. Participants could have been made aware of coping
behaviors they could (or should) be doing, but were not, such as directly working to address a
workplace demand or to confront an uncivil supervisor. This discrepancy between potential and
actual behavior could create some distress or personal feelings of failure, thus affecting
participants’ well-being or self-efficacy beliefs beyond the effects that would be expected in the
workplace alone. The second, albeit less likely, potential reactive effect for the coping success
measure is providing participants with options they would have not otherwise considered, either
in general or at the particular point of time of the measurement. For example, participants could
have sought emotional support that they would otherwise not have, or were moved to shift
108

attention and effort away from some tasks in favor of others. Although the impact of any reactive
effect exerted by the data collection on the results of this study is unclear, the potential for such
impact exists.
Second, the workplace demands and negative social experiences included in this study
were by necessity chosen to represent those most commonly or frequently encountered in the
average workplace. Attempting to capture the most common events, however, necessitates that
other, perhaps most contextually applicable events are left unexplored. That is, this study did not
try to investigate some potential workplace demands that are especially salient for some
workplaces or occupations. For example, the most salient workplace demand for some
employees might be the need to fulfill specific sales quotas; this “sales quota” demand would not
necessarily map well into the network of demands included in this study.
A similar criticism can also be applied to the selection of workplace resources included in
the study; while the resources examined were chosen to be the ones with the widest applicability
and theoretical background to support their effects, this still comes at the cost of leaving other,
potentially more salient, resources unexamined. For example, operational resources such as
material support might be more important than job control or social and organizational support
availability in some workplaces or occupation.
In a related vein, all demands and negative experiences were weighed equally for all
individuals in this study, but it is entire possible that some of these were more important than
others either at the level of the individual or the organization. For example, some employees or
workplace might be more accepting of or tolerant of incivility or conflict; for them, conflict
would exert a smaller influence on well-being levels, thus potentially affecting the results of this
study.
109

Third, the sample of participants involved in this study represented a generally limited
part of the total breadth of the workforce, in that the sample was mainly composed of clerical,
administrative, and technical workers. This limitation of the sample can somewhat limit the
generalizability of these results to other occupations, such as those of a more physical (for
example, manufacturing plant workers) or creative (such as graphical designers or architects)
nature. The occupations involved in this study do, however, represent a sizable component of the
workforce; therefore, the generalizability issues of this study might not be so severe in that the
study findings can generalize to a practically significant number of employed individuals.
Another criticism related to the sample is that the individuals involved in this study were
not randomly selected, but rather chose to self-select into this study. While none of the
demographic, control, or other variables seemed to be outside the norm for similar samples, and
of course such self-selection is a typical feature of field studies, the study sample could still be
subject to some selection biases. Similarly, there was the potential for self-selection withinpeople, as participants decided to complete or skip measurements on specific days (or even
specific measurements within a study day). Such self-selection effects might not always be
avoidable, however, because participants can hardly be randomly selected and then compelled to
join the study, or forced to complete specific surveys. Moreover the effect of between- or withinperson selection biases could also operate to make the effects presented in this study more rather
than less conservative, as it is possible that individuals who experience a wider range or
workplace demands or negative social experiences would refuse to participate due to constraints
imposed by these demands and experiences, and similar processes could also operate at the
within-individual level (e.g. with participants skipping surveys during times of high workplace
demands or during times of experienced distress). Nevertheless, it is hard to completely dismiss
110

the possibility that some self-selection effects did take place, and as a result these need to be
acknowledged as a limitation of this study.
Finally, the measures utilized to assess workplace demands and negative social
experiences, while psychometrically sound and generally suitable for a design such as the one
used in this study, undoubtedly cannot adequately capture all the richness involved in workplace
demand experiences or the complex nature of human conflict and uncivil interactions. Even if
such predictors perform well in explaining variance in the outcomes of interest, there are
elements of the nature of these events that remain unexplained by these quantitative measures, a
factor that represents another limitation of this work.
Future Directions
This study can also serve to generate a number of future avenues of research. Future
direction can be guided by two main motivations related to this study; the need to further
investigate some of the empirical results reported, and the need to improve on the limitations
associated with the current study design.
Extending the findings of this study. In terms of further investigations into the results
presented herein, there are a few areas that can provide particularly interesting contributions.
First, there would be value in a closer investigation of the relationships between the different
aspects of well-being, including indicators of strain, positive affective responses, negative
affective responses, and domain satisfactions (such as job and life satisfaction measures). Such
an investigation can provide an important contribution to well-being theories as well as to a
variety of models of workplace functioning that take well-being into consideration by aiming to
uncover and explain the underlying structure and nomological net around these well-being
components.
111

Future research could also specifically focus on some of the interactions reported in this
study. Perhaps the most impactful of these is the moderating effect of coping success in the
relationship between workload and workload self-efficacy, but there would be value in focusing
on the moderating effects of previous self-efficacy as well. The former is important in that
workload is the one workplace demand that is most applicable to all occupations, and one that is
costliest to reduce in the work environment as mentioned above. Moreover, workload selfefficacy beliefs were found in turn to be linked to well-being levels as well as influencing future
workplace functioning, further underlining the importance of this finding. These factors can be
therefore combined to inform a model in which success in addressing the demands of the work
increases self-efficacy beliefs, which in turn improves workplace functioning on subsequent
days. Other future work can focus on similar interactions to create cross-level and temporally
sophisticated models of workplace functioning.
Alternatively, future research could focus on these moderated effects that were found to
be significant but opposite to the hypothesized direction. For example, the moderating effects of
coping success were not always supportive of the study hypotheses; indeed, in three cases,
coping success was found to moderate the relationship of emotional demands and interpersonal
conflict to emotional exhaustion and positive affect in the opposite than expected direction. In
terms of positive affect, the pattern of results suggests that it is possible that this reversed
moderating effect could be due to the cost of increasing one’s coping effort, but this possibility
does not hold for the other two interactions. Instead, it could be that deviations from the optimal
situation (in which there are few demands and negative social experiences and at the same time
the individual feels that whatever minor issues remain are well handled) could create individual
concerns, worries, or doubts that translate into reduced well-being. If that is the case, future
112

research can investigate some potential mediators of these moderated effects such as perceptions
of workplace climate, psychological safety, feelings of psychological contract violation, or other
attitudes, feelings, or stressors that could be triggered due to increased negative perceptions of
the workplace.
Moreover, the findings of this study relative to how individuals experience and respond
to their work environment have the potential to inform future work based on other theoretical
frameworks. A theoretical framework that is perhaps most directly applicable is Hofboll’s
Conservation of Resources theory (COR; Hofboll, 1989). COR states that individuals “strive to
retain, protect, and build resources and that what is threatening to them is the potential or actual
loss of these valued resources” (Hoboll, 1989, p. 513). Using this framework, workplace selfefficacy beliefs can be conceptualized as an important “resource” for individuals, which can be
protected, gained, or lost in the workplace depending on how successfully individuals cope with
the workplace demands at hand. This synthesis can help explain individual behavior and wellbeing in terms of self-efficacy gains or losses, based on the interplay between workplace
demands, factors such as the availability of workplace support, and coping responses.
Furthermore, while this study explicitly focused on how workplace functioning affects
individual well-being, future research could also seek to examine a variety of other important
organizational outcomes using a framework similar to the one presented herein. For example,
some studies could investigate whether coping success leads to improved task or job
performance, or if coping success refers only to the individual’s efforts to avoid experiencing
distress. Similarly, other efforts could seek to investigate how factors related to workplace
functioning affect voluntary behaviors such as organizational citizenship or negative workplace
behaviors (Organ, 1988; Dimotakis, Ilies, & Mount, 2008). By examining a wider range of
113

outcomes of importance to individuals and organizations, such efforts could stand to provide a
more well-rounded understanding of the way employees experience and react to the daily
occurrences of their workplace.
Future studies could also examine self-efficacy beliefs across different temporal frames,
and more clearly focus on the events and episodes that precede fluctuations in self-efficacy. This
approach would provide a closer look at how self-efficacy judgments are formed, and provide an
explanation for how they persist or fluctuate according to individual experiences. For example,
an Experience Sampling Methodology study involving frequent measurement (see Dimotakis,
Ilies, & Judge, in press) could investigate how long the positive or negative effects of discrete
workplace experiences (for example, achieving task success or failure) persist across time, and
whether other intervening events could affect increases or decreases in the temporal persistence
of such effects.
Moreover, while as previously mentioned exploratory analyses conducted in this study
failed to find a consistent pattern of non-linear effects for workplace support and job control,
future work could explicitly seek to address the possibility of such effects using studies
specifically designed and optimized for testing non-linear relationships. By investigating nonlinear effects, this line of research could provide an alternative explanation for the sometimes
mixed support that the demands/control/support model has received in the literature, and thus
contribute to both theory and practice.
Finally, future studies could expand on the findings presented herein relative to the
positive effects of coping success on subjective well-being and self-efficacy. Specifically, an
investigation that explicitly compares and contrasts the effects of coping success versus coping
styles could shed some light on the findings of this study and contribute to a variety of models of
114

stress and well-being that include coping responses. Furthermore, future work could investigate
the relative benefits of coping success on individual well-being as well as the organizational
outcomes discussed above, thereby uncovering any differential relationships of success in
different coping styles with organizational and individual outcomes (for example, by
demonstrating that success in seeking emotional support is beneficial in terms of individual
subjective well-being levels, but not for organizationally important outcomes such as task or job
performance).
Addressing limitations. Other avenues of research could attempt to address some of the
limitations inherent in the design of this study. First, future research approaches could attempt to
address the common methods variance concerns mentioned in the limitations section by
replicating the findings of this study using other sources of ratings or data collection methods,
thus going beyond self-reported measures. For example, self-reported data on experienced
positive or negative affect could be validated by collecting spouse or peer reports, and selfreports of experienced strain or emotional exhaustion could be improved upon by collecting
physiological measures (such as cortisol samples or cardiovascular measures). Similarly,
workplace demands such as workload can be measured using more objective techniques (such as
utilizing measures of actual tasks needing completion on a particular workday). These
approaches can thus help address some of the common methods bias concerns included in this
study, as well as providing a more comprehensive investigation of these well-being phenomena.
Similarly, generalizability concerns can also be assuaged by future research by
conducting similar studies on a wider range of occupations. While the technological approach
utilized will probably need to be adjusted to best fit the context (for a discussion of various
technological approaches and how they can be adjusted to the work context at hand, see
115

Dimotakis et al., in press), examining other samples can help ensure that the findings of this
study generalize beyond clerical and administrative workers to a larger segment of the
workforce.
Expanding future investigations into other contexts can also provide a prime opportunity
to extend current research into more targeted work demands and sources of workplace resources.
In other words, future research can use initial investigations into the work context to uncover
these resources or demands that are particularly applicable or salient to that organization or
occupation, and focus their work accordingly. While this might decrease the potential
generalizability of the findings, such research efforts that pay close attention to the context at
hand can provide a clear and concise picture of workplace functioning for their particular
context, adding detail and nuance to the theoretical conclusions that can be drawn from them.
Beyond examining more contextually applicable resources or demands, other research
approaches can instead take a more qualitative approach towards workplace functioning, using
the appropriate data collection techniques to attempt to gain a richer understanding of how
employees experience workplace demands and negative social experiences, and what resources
or strategies they use to effectively cope with them. This can extend our understanding beyond
the conclusions reached by the various quantitative approaches implemented so far, and perhaps
reveal new avenues of research or potential mediating processes that can then be investigated
further.
Finally, future research can instead seek to investigate workplace experiences that can
enhance individual well-being or help individuals function better, thus examining the “flip-side”
of the demand experiences that have been the focus of investigations up to this point (see Ilies,
Keeney, & Scott, 2011, for an exception). Similarly, other approaches can investigate the effects
116

of chronic demands or pressures experienced by the individual, either from their work or family
domains, thus providing a counterpoint to the well-being enhancing resources included in models
of workplace functioning. In other words, future investigations could focus on the reverse side of
the demands/control model and other similar conceptualization, by investigating the beneficial
influences of positive workplace events, and how chronic stressors or demands can affect these
influences and individual well-being in general.

117

Conclusion

This study proposed and tested a model by which workplace demands and negative social
experiences affect individual well-being partly through variations in self-efficacy beliefs. It also
posited a series of moderators of these relationships, as well as a proximal order for the effects of
these moderators. The former arguments were mostly supported by this study, but support for the
latter was mixed. In general though, this study proposed and found that self-efficacy beliefs and
success in individual coping efforts are important variables in understanding workplace
functioning in general and the relationship between workplace demands and negative social
experiences and individual well-being, findings that can provide contributions for both theory
and practice.

118

APPENDICES

119

APPENDIX A

TABLES

120

Table 1: Confirmatory Factor Analysis for the Daily Measurement Variables
x

2

df

NFI

NNFI

CFI

GFI

SRMR

RMSEA

AIC

Demands Measures
5 Factors
2105.33
517
.84
.86
.87
.86
.05
.06
1071.33
1 Factor
8020.85
527
.39
.36
.40
.52
.14
.13
6966.85
Self-Efficacy Measures
.93
.92
.94
.92
.07
.08
383.91
5 Factors
543.91
80
1 Factor
3688.07
90
.54
.47
.55
.59
.13
.22
3508.07
Well-Being Measures
6 Factors
5073.96
1415
.71
.76
.77
.80
.06
.06
2243.96
1 Factor
11170.81
1430
.35
.36
.38
.51
.11
.10
8310.81
Notes: All estimates derived from within-individual CFAs. NFI= Normed Fit Index. NNFI = Non-Normed Fit Index. CFI =
Comparative Fit Index. GFI = Goodness-of-fit Index. SRMR = Standardized Root Mean Residual. RMSEA = Root Mean Square
Error of Approximation. AIC = Akaike Information Criterion

121

Table 2: Variance Components of the Repeated Measures Variables
Between-Person
Within-People
Variance Component
Variance Component
1. Role Conflict
0.66
0.19
2. Workload
0.50
0.23
3. Emotional Demands
0.81
0.35
4. Interpersonal Conflict
0.23
0.17
5. Incivility
0.07
0.06
6. Role Conflict SE
307.27
118.54
7. Workload SE
360.12
130.79
8. Emotional Demands SE
276.59
133.10
9. Interpersonal Conflict SE
345.37
98.88
10. Incivility SE
323.33
87.40
11. Experienced Strain
0.09
0.09
12. Emotional Exhaustion
0.76
0.17
13. Affective Distress
0.30
0.24
14. Negative Affect
0.08
0.06
15. Positive Affect
0.49
0.29
16. Life Satisfaction
2.26
0.30
17. # of Coping Strategies
20.76
17.65
18. Coping Success
0.29
0.39
Notes: SE = Self-Efficacy. All variance components estimated from null HLM models.

122

% Variance Within People
22.02%
31.39%
30.58%
42.53%
45.26%
27.84%
26.64%
32.49%
22.26%
21.28%
48.92%
18.09%
44.88%
43.88%
37.02%
11.59%
45.95%
57.18%

Table 3: Means and Standard Deviations for the Between-People Variables
M
SD
1
2
3
4
5
6
7
1. Gender
1.81
0.39
2. Number of Children
1.66
1.33
.14
3. Hours Worked
41.89
7.93
.19
.08
4. Workplace Support
3.49
0.64
.04
.13
-.08
5. Job Control
3.73
0.58 -.07
.17
.20
.36**
6. Neuroticism
2.28
0.63
.05
-.11
-.10
-.43** -.32**
7. NA
1.33
0.44 -.04
.02
-.01
-.22*
.05
.57**
**
8. Marital Status
0.68
0.47 -.10
-.07
.28
.09
.13
.03
.07
Notes: N = 96. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work
Hours relates to mean hours worked per week. Marital Status was coded as 1 = not married, 2 = married.
Trait NA = Trait Negative Affect. * p < .05 ** p < .01

123

Table 4: Means, Standard Deviations and Correlations for the Within-People Variables
M
SD
1
2
3
4
5
6
7
8
9
10
1. Role Conflict
1.87
0.43
2. Workload
3.06
0.48 .38**
3. Emotional Demands
1.81
0.60 .49** .20**
4. Interpersonal Conflict
1.37
0.41 .27** .22** .41**
5. Incivility
1.14
0.25 .27** .11*
.29** .20
6. Role Conflict SE
82.71 10.89 -.16* -.07
-.21** -.13* -.13*
**
**
7. Workload SE
80.94 11.44 -.21
-.21
-.18** -.12** -.08*
.38**
8. Emotional Demands SE
82.96 11.54 -.23** -.10** -.24** -.20** -.13*
.47** .28**
9. Interpersonal Conflict SE
83.89
9.94 -.20* -.09
-.25** -.26** -.06
.53** .31** .53**
10. Incivility SE
85.63
9.35 -.17* -.10* -.22** -.27** -.17
.40** .35** .43** .62**
**
**
11. Experienced Strain
1.83
0.30 .08
.06
.18
.17
.10
-.17** -.23** -.26** -.21** -.25**
12. Emotional Exhaustion
2.38
0.41 .28** .19** .25** .17** .14** -.12* -.16** -.24** -.16* -.22**
13. Affective Distress
1.92
0.49 .02
.01
.10
.13*
.06
-.08
-.16** -.12* -.05
-.11*
14. Negative Affect
1.19
0.25 .04
.01
.09
.13*
.07
-.04
-.13* -.14* -.03
-.14*
*
*
**
*
15. Positive Affect
2.37
0.53 -.03
.04
-.06
-.17
.07
.13
.18
.09
.16
.17*
16. Life Satisfaction
4.73
0.54 -.07
-.02
-.12** -.13* -.07
.11** .17** .17** .12*
.16**
17. # of Coping Strategies
9.10
4.20 .14*
.11*
.03
.14
.06
-.15** -.21** -.17** -.15* -.07
18. Coping Success
3.37
0.63 .05
.00
-.13
-.12
-.12
.15*
.17** .04
.17*
.24**
Notes: N = 514-517. Within-people correlations were estimated from coefficients derived from univariate fixed-effect HLM models,
which were then standardized using within-individual standard deviation estimates. * p < .05 ** p < .01

124

Table 4 (cont’d).
11

12

13

14

15

16

17

12. Emotional Exhaustion
.37**
13. Affective Distress
.59** .42**
14. Negative Affect
.48** .34** .72**
15. Positive Affect
-.26** -.16** -.29** -.03
16. Life Satisfaction
-.43** -.23** -.47** -.32** .26**
17. # of Coping Strategies
-.02
.07
.02
.03
.07
-.02
**
*
*
*
18. Coping Success
-.17
-.13
-.12
-.10
.04
.02
.09
Notes: N = 514-517. Within-people correlations were estimated from coefficients derived
from univariate fixed-effect HLM models, which were then standardized using withinindividual standard deviation estimates. * p < .05 ** p < .01

125

Table 5: Relationship between Role Conflict and Well-Being (Hypothesis 1).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85
57.25
2.44
28.95
1.95
39.45
1.21
49.08
2.36
31.82
4.66
35.32
**
.06
.98
.00
.03
-.03
-.45
-.07
-1.00
Gender
.03
.37
.18
2.82
Children #
.03
.51
-.12
-1.69
.06
.93
-.05
-.88
.08
.81
-.09
-.98
Work Hours
.01
.21
-.03
-.39
.06
1.04
-.02
-.24
.00
.03
-.07
-.93
**
**
**
**
Neuroticism
.36
3.04
.31
2.90
.29
3.51
-.05
-.60
-.34
-3.96
-.45
-4.38**
**
*
Trait NA
.02
.17
.04
.34
.27
2.78
.61
2.54
.08
.97
-.11
-1.29
*
-.05
-.74
.02
.44
.02
.24
.17
1.82
Marital Status
.08
1.07
.20
2.00
**
Role Conflict
.05
.92
.28
4.93
.01
.12
.01
.20
.01
.17
-.03
-.62
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. * p < .05 ** p < .01

126

Table 6: Relationship between Workload and Well-Being (Hypothesis 1).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85
57.18
2.43
28.94
1.95
39.49
1.21
49.25
2.36
31.80
4.66
35.24
**
.06
1.03
-.01
-.22
-.06
-1.02
-.07
-.95
Gender
.02
.28
.20
3.11
Children #
.04
.57
-.11
-1.69
.10
1.41
-.04
-.63
.06
.58
-.09
-.99
Work Hours
.02
.41
-.05
-.56
.06
1.11
-.01
-.14
.00
-.02
-.09
-1.06
**
**
**
**
Neuroticism
.35
3.14
.31
3.12
.33
4.14
-.04
-.49
-.37
-4.39
-.43
-4.12**
**
*
Trait NA
.02
.20
.04
.33
.26
2.71
.61
2.57
.07
.92
-.11
-1.23
*
-.08
-1.14
.02
.30
.01
.10
.17
1.82
Marital Status
.07
1.00
.20
2.06
**
Workload
.06
1.12
.22
3.74
.01
.10
.00
-.09
.10
1.80
.06
1.08
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. * p < .05 ** p < .01

127

Table 7: Relationship between Emotional Demands and Well-Being (Hypothesis 1).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85
57.15
2.44
28.94
1.95
39.52
1.21
49.07
2.36
31.71
4.66
35.31
**
.06
.92
-.01
-.19
.01
.10
-.08
-1.00
Gender
.03
.39
.18
2.79
Children #
.01
.23
-.12
-1.74
.08
1.10
-.06
-1.01
.06
.62
-.09
-1.02
Work Hours
.02
.44
-.03
-.34
.08
1.48
-.01
-.17
.01
.10
-.08
-1.01
**
**
**
**
Neuroticism
.35
3.06
.31
2.95
.30
3.60
-.05
-.57
-.38
-4.71
-.45
-4.29**
**
*
Trait NA
.00
-.03
.05
.35
.28
2.79
.63
2.60
.12
1.67
-.11
-1.30
Marital Status
.08
1.07
.18
1.79
-.05
-.80
.04
.65
.04
.53
.17
1.85
**
**
Em. Demands
.17
3.17
.25
4.46
.10
1.55
.11
1.64
-.03
-.50
-.04
-.61
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Em. Demands =
Emotional Demands. * p < .05 ** p < .01

128

Table 8: Relationship between Interpersonal Conflict and Well-Being (Hypothesis 1).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.61
25.53
2.13
17.72
1.65
17.54
1.08
22.15
2.34
21.99
4.92
23.84
**
.05
.93
-.03
-.55
-.04
-.63
-.08
-1.00
Gender
-.02
-.26
.24
3.39
Children #
.03
.49
-.12
-2.01
.10
1.37
-.01
-.22
.07
.70
-.09
-.92
Work Hours
.01
.27
-.03
-.46
.07
1.63
.00
-.06
.01
.17
-.08
-1.02
**
*
**
**
Neuroticism
.28
3.07
.27
2.66
.27
3.43
-.05
-.68
-.34
-3.97
-.42
-3.95**
**
**
Trait NA
.06
.72
.09
.66
.29
2.88
.63
2.77
.08
1.02
-.11
-1.29
*
-.10
-1.58
-.03
-.49
.01
.08
.19
2.13
Marital Status
.02
.25
.20
2.02
**
**
**
**
In. Conflict
.24
3.83
.23
4.62
.18
3.94
.16
3.90
.01
.32
-.17
-2.04*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict =
Interpersonal Conflict. * p < .05 ** p < .01

129

Table 9: Relationship between Incivility and Well-Being (Hypothesis 1).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.38
12.46
1.97
15.38
1.66
13.52
1.07
18.31
2.56
16.35
4.96
18.70
**
.06
.92
-.02
-.39
-.02
-.24
-.08
-1.04
Gender
-.01
-.22
.18
2.82
Children #
.07
1.20
-.08
-1.27
.08
1.11
-.04
-.60
.06
.58
-.11
-1.28
Work Hours
.04
.90
-.03
-.41
.08
1.69
.00
-.02
.00
.01
-.07
-.89
**
**
**
*
Neuroticism
.33
3.40
.32
3.28
.28
3.44
-.06
-.76
-.33
-3.91
-.42
-3.96**
**
*
Trait NA
.06
.70
.04
.29
.30
3.07
.65
2.69
.07
.95
-.13
-1.43
Marital Status
.02
.37
.18
1.88
-.06
-.94
.01
.20
.04
.43
.19
2.17**
Incivility
.35
4.29**
.25
5.88**
.13
2.44*
.12
2.59*
-.09
-1.66
-.13
-1.41
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. * p < .05 ** p < .01

130

Table 10: Relationship between Workplace Demands and Negative Social Experiences and Self-Efficacy (Hypothesis 2).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
Intercept
80.97
44.16
79.67
39.68
82.11
47.28
91.98
32.85
96.42
18.41
Gender
-.09
-1.28
-.13
-1.68
-.13
-1.90
-.12
-1.54
-.09
-.97
Children #
-.04
-.46
.01
.10
.08
1.20
.09
1.13
.09
1.36
Hours Worked
.08
.80
.13
1.50
.00
-.04
.04
.47
.00
.02
**
*
**
Neuroticism
-.32
-2.73
-.18
-1.57
-.30
-2.70
-.37
-3.59
-.34
-2.84**
Trait NA
.15
1.64
.07
.71
.07
.82
.18
1.92
.20
1.99*
Marital Status
-.13
-1.44
-.20
-2.19*
-.15
-1.71
-.16
-1.87
-.19
-1.94
*
**
**
**
Demand/Experience
-.20
-2.47
-.22
-5.00
-.24
-3.42
-.31
-5.70
-.31
-2.90**
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean
hours worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect.
Demand/Experience relates to the relevant domain being examined (e.g. Role Conflict for Role Conflict Self-Efficacy). Em.
Demands = Emotional Demands. In. Conflict = Interpersonal Conflict. * p < .05 ** p < .01

131

Table 11: Relationship between Workplace Resources and Well-Being (Hypothesis 3).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85
58.36
2.44
32.28
1.95
40.38
1.21
49.96
2.36
31.89
4.65
37.10
**
Gender
.03
.41
.23
3.70
.07
1.03
-.02
-.39
-.05
-.76
-.09
-1.26
Children #
.05
.82
-.08
-1.19
.09
1.35
-.04
-.65
.06
.59
-.13
-1.48
.04
.71
-.09
-1.17
.08
1.36
.01
.18
.02
.23
-.06
-.80
Hours Worked
*
*
**
Neuroticism
.26
2.25
.16
1.90
.22
2.57
-.08
-.99
-.29
-3.00
-.31
-2.75**
Trait NA
.05
.58
.05
.52
.30
2.82**
.66
2.77**
.07
.97
-.14
-1.31
Marital Status
.09
1.18
.16
1.68
-.05
-.82
.05
.78
.02
.20
.19
2.32*
Job Control
-.14
-1.24
.04
.34
-.08
-1.19
-.11
-1.65
.03
.37
.10
1.05
**
W. Support
-.07
-.78
-.43
-4.76
-.12
-1.33
.03
.27
.09
.91
.25
2.48*
Notes: N = 77. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. W. Support =
Workplace Support. * p < .05 ** p < .01

132

Table 12: Relationship between Workplace Resources and Self-Efficacy (Hypothesis 3).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
Intercept
80.92
48.85
79.70
42.75
82.11
50.88
81.68
48.48
83.31
46.99
*
Gender
-.12
-1.40
-.17
-2.09
-.14
-1.88
-.13
-1.39
-.12
-1.26
Children #
-.08
-1.15
.01
.14
.05
.82
.02
.23
.05
.82
Hours Worked
.11
1.33
.16
1.90
.05
.49
.05
.59
.03
.28
Neuroticism
-.13
-1.06
-.02
-.19
-.16
-1.39
-.20
-1.61
-.21
-1.49
Trait NA
.12
1.34
.06
.64
.08
.92
.18
1.91
.18
1.80
*
Marital Status
-.07
-.84
-.17
-2.03
-.11
-1.28
-.15
-1.75
-.19
-1.95
Job Control
.07
.75
-.05
-.53
-.01
-.13
.02
.26
.06
.41
**
**
**
**
W. Support
.40
4.03
.37
4.12
.33
3.47
.43
3.86
.26
2.40*
Notes: N = 77. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. W. Support =
Workplace Support. Em. Demands = Emotional Demands. In. Conflict = Interpersonal Conflict. * p < .05 ** p < .01

133

Table 13: Relationship between Role Conflict Self-Efficacy and Well-Being (Hypothesis 4).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
56.57
2.42
28.77
1.94
39.43
1.21
49.66
2.37
31.96
4.69
35.64
**
.06
.90
-.03
-.45
-.02
-.32
-.07
-.94
Gender
.04
.56
.19
2.86
Children #
.04
.56
-.12
-1.68
.08
1.08
-.05
-.83
.07
.69
-.10
-1.12
Work Hours
.01
.16
-.05
-.63
.06
1.22
.00
.01
-.01
-.09
-.06
-.72
**
**
**
**
Neuroticism
.33
3.02
.31
2.91
.30
3.50
-.05
-.56
-.36
-4.08
-.45
-4.25**
**
**
Trait NA
.03
.30
.06
.41
.28
2.91
.65
2.70
.09
1.16
-.12
-1.44
*
-.04
-.66
.02
.29
.02
.23
.16
1.69
Marital Status
.09
1.26
.23
2.27
**
*
R. Conflict SE
-.16
-3.20
-.12
-2.53
-.08
-1.89
-.05
-1.07
.06
1.15
.14
2.68*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. R. Conflict SE = Role
Conflict Self-Efficacy. * p < .05 ** p < .01

134

Table 14: Relationship between Workload Self-Efficacy and Well-Being (Hypothesis 4).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.26
2.44
28.97
1.95
39.52
1.21
48.53
2.36
31.88
4.66
35.30
**
.06
1.03
.02
.33
-.04
-.66
-.08
-1.02
Gender
.03
.43
.19
2.87
Children #
.03
.43
-.12
-1.73
.07
1.01
-.05
-.84
.10
.97
-.10
-1.09
Work Hours
.02
.48
-.03
-.38
.08
1.63
.03
.40
.00
-.05
-.09
-1.09
**
**
**
**
Neuroticism
.32
3.01
.31
2.91
.29
3.52
-.05
-.61
-.35
-3.98
-.44
-4.19**
**
*
Trait NA
.03
.31
.05
.36
.28
2.80
.59
2.51
.09
1.19
-.11
-1.29
*
-.05
-.71
.05
.86
.01
.16
.18
1.92
Marital Status
.08
1.09
.21
2.11
**
**
**
*
Workload SE
-.23
-3.99
-.17
-3.25
-.16
-3.89
-.12
-1.99
.06
1.14
.17
2.86**
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Workload SE =
Workload Self-Efficacy. * p < .05 ** p < .01

135

Table 15: Relationship between Emotional Demands Self-Efficacy and Well-Being (Hypothesis 4).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.37
2.44
29.02
1.95
39.38
1.21
48.78
2.36
31.93
4.66
35.26
**
.07
1.20
.00
-.06
-.03
-.46
-.07
-.95
Gender
.04
.54
.20
3.02
Children #
.04
.66
-.13
-1.89
.07
1.01
-.06
-1.07
.08
.81
-.10
-1.12
Work Hours
-.01
-.18
-.03
-.39
.05
.81
-.03
-.31
-.01
-.10
-.08
-1.05
**
**
**
**
Neuroticism
.36
3.33
.33
3.16
.30
3.71
-.04
-.47
-.35
-3.98
-.44
-4.23**
**
**
Trait NA
.00
.02
.05
.34
.27
2.92
.60
2.80
.08
1.04
-.11
-1.24
*
-.04
-.56
.05
.86
.02
.23
.18
1.92
Marital Status
.08
1.16
.22
2.21
**
**
E. Demands SE
-.21
-3.76
-.26
-4.33
-.07
-1.50
-.08
-1.25
.09
1.64
.14
2.07*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. E. Demands SE =
Emotional Demands Self-Efficacy. * p < .05 ** p < .01

136

Table 16: Relationship between Interpersonal Conflict Self-Efficacy and Well-Being (Hypothesis 4).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.16
2.44
28.98
1.95
39.20
1.21
49.03
2.36
31.71
4.66
35.37
**
.06
.95
-.01
-.23
-.03
-.41
-.08
-1.02
Gender
.04
.48
.19
2.87
Children #
.03
.41
-.12
-1.71
.07
1.05
-.05
-.86
.07
.68
-.10
-1.07
Work Hours
.02
.35
-.04
-.42
.07
1.43
.00
-.05
-.03
-.53
-.08
-.98
**
**
**
**
Neuroticism
.35
3.14
.32
2.97
.30
3.60
-.05
-.53
-.34
-3.86
-.45
-4.37**
**
*
Trait NA
.02
.25
.05
.35
.28
2.80
.64
2.64
.08
1.06
-.11
-1.25
*
-.05
-.73
.03
.57
.04
.44
.17
1.82
Marital Status
.08
1.16
.21
2.11
**
*
In. Conflict SE
-.23
-3.66
-.17
-2.63
-.08
-1.23
-.02
-.30
.07
1.25
.23
3.21**
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict SE =
Interpersonal Conflict Self-Efficacy. * p < .05 ** p < .01

137

Table 17: Relationship between Incivility Self-Efficacy and Well-Being (Hypothesis 4).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.10
2.44
28.96
1.95
39.57
1.21
48.65
2.36
31.85
4.66
35.32
**
.06
.94
.02
.28
-.02
-.37
-.09
-1.14
Gender
.04
.64
.20
2.91
Children #
.02
.32
-.12
-1.75
.07
1.04
-.04
-.60
.07
.65
-.09
-1.05
Work Hours
.02
.47
-.04
-.46
.07
1.43
.00
.03
-.01
-.15
-.08
-.98
**
**
**
**
Neuroticism
.34
3.32
.32
3.03
.30
3.54
-.06
-.67
-.35
-4.01
-.45
-4.33**
**
*
Trait NA
.02
.21
.04
.32
.28
2.80
.63
2.81
.08
1.09
-.11
-1.23
*
-.05
-.76
.06
1.17
.02
.21
.16
1.72
Marital Status
.10
1.37
.21
2.09
**
**
*
Incivility SE
-.23
-4.02
-.22
-3.74
-.12
-2.15
-.12
-1.41
.03
.65
.22
2.71**
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Incivility SE =
Incivility Self-Efficacy. * p < .05 ** p < .01

138

Table 18: The Mediating Role of Role Conflict Self-Efficacy in the Relationship between Role Conflict and Well-Being
(Hypothesis 5).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
56.59
2.42
28.75
1.94
39.44
1.21
49.64
2.37
31.94
4.69
35.65
**
Gender
.04
.50
.18
2.82
.05
.89
-.01
-.21
-.02
-.27
-.07
-.94
Children #
.03
.53
-.12
-1.66
.07
1.00
-.05
-.84
.07
.71
-.10
-1.05
Work Hours
.01
.12
-.05
-.62
.05
.89
-.01
-.09
-.01
-.13
-.05
-.68
**
**
**
**
Neuroticism
.34
3.01
.31
2.86
.29
3.49
-.05
-.61
-.36
-4.07
-.45
-4.34**
Trait NA
.62
2.61*
.09
1.14
-.12
-1.45
.02
.26
.05
.39
.28
2.88**
Marital Status
-.05
-.75
-.01
-.18
.02
.26
.15
1.65
.09
1.21
.21
2.14*
**
Role Conflict
.04
.74
.26
4.69
.00
-.07
.01
.25
.03
.64
-.01
-.31
**
R. Conflict SE
-.15
-3.03
-.08
-1.77
-.08
-1.76
-.03
-.70
.06
1.20
.14
2.54*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. R. Conflict SE = Role
Conflict Self-Efficacy. * p < .05 ** p < .01

139

Table 19: The Mediating Role of Workload Self-Efficacy in the Relationship between Workload and Well-Being (Hypothesis
5).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.15
2.43
28.96
1.95
39.56
1.21
48.53
2.36
31.86
4.66
35.23
Gender
.03
.35
.21
3.28**
.06
1.02
.01
.24
-.07
-1.15
-.07
-.94
*
Children #
.03
.45
-.14
-2.18
.10
1.35
-.04
-.66
.08
.92
-.09
-1.02
Work Hours
.03
.54
-.02
-.29
.07
1.19
.03
.37
-.02
-.39
-.09
-1.06
**
**
**
**
Neuroticism
.33
3.04
.28
2.87
.32
4.11
-.05
-.54
-.37
-4.36
-.44
-4.13**
Trait NA
.03
.29
.06
.44
.26
2.76**
.57
2.48*
.08
1.06
-.11
-1.20
*
Marital Status
.07
1.01
.21
2.25
-.07
-1.11
.03
.59
.01
.08
.17
1.86
**
*
Workload
.01
.31
.19
3.30
-.02
-.47
-.02
-.34
.12
2.11
.11
1.85
**
**
**
*
Workload SE
-.22
-3.89
-.13
-2.74
-.16
-3.74
-.13
-2.12
.08
1.67
.14
2.40*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Workload SE =
Workload Self-Efficacy. * p < .05 ** p < .01

140

Table 20: The Mediating Role of Emotional Demands Self-Efficacy in the Relationship between Emotional Demands and WellBeing (Hypothesis 5).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.30
2.44
28.99
1.95
39.46
1.21
48.72
2.36
31.81
4.66
35.24
Gender
.03
.43
.17
2.70**
.06
1.02
-.01
-.16
.00
.05
-.07
-.91
Children #
.03
.49
-.14
-1.90
.08
1.14
-.07
-1.14
.07
.65
-.11
-1.23
Work Hours
-.01
-.24
-.04
-.39
.05
.94
-.03
-.37
.00
-.04
-.08
-1.04
**
**
**
**
Neuroticism
.36
3.36
.33
3.16
.31
3.79
-.04
-.49
-.38
-4.55
-.44
-4.15**
Trait NA
-.01
-.11
.03
.27
.27
2.86**
.60
2.78**
.11
1.48
-.11
-1.22
Marital Status
.08
1.13
.18
1.89
-.04
-.68
.05
.89
.04
.57
.18
1.96
*
**
E. Demands
.12
2.31
.19
3.48
.07
1.16
.07
1.06
.02
.35
-.01
-.23
**
**
E. Demands SE
-.18
-3.56
-.20
-3.85
-.07
-1.40
-.08
-1.30
.10
1.67
.12
2.13**
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. E. Demands =
Emotional Demands. E. Demands SE = Emotional Demands Self-Efficacy. * p < .05 ** p < .01

141

Table 21: The Mediating Role of Interpersonal Conflict Self-Efficacy in the Relationship between Interpersonal Conflict and
Well-Being (Hypothesis 5).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
56.96
2.44
28.91
1.95
39.19
1.21
48.88
2.36
31.72
4.66
35.35
Gender
.06
.86
.23
3.32**
.06
.90
-.02
-.31
-.03
-.46
-.08
-1.08
Children #
.04
.62
-.11
-1.72
.08
1.16
-.03
-.49
.07
.66
-.10
-1.15
Work Hours
.01
.23
-.02
-.26
.08
1.69
.01
.13
-.04
-.63
-.08
-1.01
**
**
**
**
Neuroticism
.34
3.13
.31
2.79
.30
3.53
-.05
-.60
-.36
-4.06
-.44
-4.14*
Trait NA
.02
.24
.07
.46
.28
2.79**
.66
2.79**
.08
1.02
-.11
-1.31
*
Marital Status
.09
1.24
.22
2.28
-.06
-.84
.02
.32
.03
.41
.18
2.01*
In. Conflict
.16
2.42*
.18
2.86**
.12
1.66
.15
2.56**
.09
1.98*
-.13
-1.43
*
In. Conflict SE
-.17
-2.37
-.11
-1.56
-.03
-.43
.01
.16
.09
1.70
.13
1.82*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict =
Interpersonal Conflict. In. Conflict SE = Interpersonal Conflict Self-Efficacy. * p < .05 ** p < .01

142

Table 22: The Mediating Role of Incivility Self-Efficacy in the Relationship between Incivility and Well-Being (Hypothesis 5).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.84
57.16
2.44
28.92
1.94
39.58
1.21
48.48
2.36
31.81
4.66
35.31
**
.07
1.07
.03
.59
-.01
-.19
-.09
-1.18
Gender
.05
.75
.19
2.87
Children #
.01
.18
-.10
-1.45
.07
1.04
-.07
-1.11
.05
.53
-.11
-1.27
Work Hours
.02
.37
-.03
-.40
.07
1.38
-.01
-.09
.00
.02
-.07
-.90
**
**
**
**
Neuroticism
.34
3.22
.35
3.49
.29
3.49
-.09
-1.05
-.34
-4.00
-.43
-4.09**
**
**
Trait NA
.02
.29
.03
.21
.28
2.86
.65
2.97
.09
1.26
-.12
-1.38
*
-.05
-.69
.08
1.54
.02
.28
.17
1.94
Marital Status
.11
1.58
.19
2.02
**
Incivility
.08
.91
.34
4.99
.12
1.02
-.04
-.45
-.11
-1.19
.01
.04
**
**
-.20
-3.08
-.13
-1.93
-.15
-1.52
.03
.53
.26
2.87**
Incivility SE
-.26
-3.85
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Incivility SE =
Incivility Self-Efficacy. * p < .05 ** p < .01

143

Table 23: The Moderating Role of Job Control in the Relationship between Workplace Demands and Experiences and WellBeing (Hypothesis 6).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
γ’
t
γ’
t
γ’
γ’
t
γ’
t
γ’
Intercept
81.02
44.89
79.65
39.65
82.14
47.46
81.64
43.72
83.21
45.00
Gender
-.09
-1.19
-.11
-1.47
-.12
-1.71
-.16
-2.20*
-.11
-1.24
Children #
-.05
-.59
.00
-.06
.08
1.08
.08
1.10
.09
1.25
Work Hours
.04
.43
.13
1.35
-.01
-.10
.02
.24
-.02
-.13
*
*
**
-.19
-1.51
-.27
-2.38
-.36
-3.31
-.25
-1.92
Neuroticism
-.24
-2.04
Trait NA
.10
1.09
.07
.70
.06
.63
.18
1.73
.17
1.67
*
*
Marital Status
-.15
-1.67
-.19
-2.07
-.15
-1.68
-.22
-2.46
-.24
-2.52*
*
**
**
**
Demand/ Experience
-.20
-2.56
-.20
-4.47
-.22
-3.40
-.32
-4.80
-.27
-2.35*
Job Control Main Effects
.19
2.06*
.02
.21
.07
.72
.10
.98
.14
.95
**
**
Job Control Slope Effects
.02
.21
-.06
-1.10
.18
2.39
.19
2.08
.13
.61
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Demand/Experience
relates to the relevant domain being examined (e.g. Role Conflict for Role Conflict Self-Efficacy). Em. Demands = Emotional
Demands. In. Conflict = Interpersonal Conflict. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope effects
relates to the cross-level moderating effects of Job Control on the level-1 Demand/Experience slopes predicting Self-Efficacy.
*
p < .05 ** p < .01

144

Table 24: The Moderating Role of Workplace Support in the Relationship between Workplace Demands and Experiences and
Self-Efficacy Beliefs (Hypothesis 6).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
γ’
t
γ’
t
γ’
γ’
t
γ’
t
γ’
Intercept
80.86
48.57
79.66
42.46
82.12
50.67
81.66
48.11
83.22
46.39
Gender
-.13
-1.53
-.15
-1.73
-.14
-1.95
-.18
-2.34*
-.14
-1.47
Children #
-.08
-1.00
-.02
-.24
.05
.83
.06
.79
.07
1.12
.04
.45
.09
1.29
.04
.39
Work Hours
.12
1.43
.17
2.06*
*
Neuroticism
-.14
-1.20
-.04
-.33
-.16
-1.43
-.24
-2.26
-.19
-1.55
Trait NA
.14
1.66
.07
.77
.07
.89
.21
2.42*
.20
2.23*
Marital Status
-.07
-.81
-.15
-1.74
-.11
-1.31
-.15
-1.91
-.20
-2.06*
*
**
**
**
Demand/ Experience
-.20
-2.65
-.20
-4.71
-.22
-3.65
-.28
-4.53
-.27
-2.18*
W. Support Main Effects
.43
4.42**
.35
3.86**
.33
3.52**
.42
3.88**
.28
2.50*
W. Support Slope Effects
-.03
-.27
-.02
-.50
.15
1.73
.10
1.43
.00
-.02
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Demand/Experience
relates to the relevant domain being examined (e.g. Role Conflict for Role Conflict Self-Efficacy). Em. Demands = Emotional
Demands. In. Conflict = Interpersonal Conflict. W. Support = Workplace Support. Main Effects relates to the effect of Workplace
Support on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Workplace Support on the level-1
Demand/Experience slopes predicting Self-Efficacy. * p < .05 ** p < .01

145

Table 25: The Moderating Role of Job Control in the Relationship between Role Conflict and Well-Being (Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 58.47
2.44 28.93
1.95 40.19
1.21 49.69
2.36 31.83
4.66 35.99
**
Gender
.02
.30
.18
2.78
.05
.91
-.01
-.09
-.03
-.41
-.07
-.91
Children #
.05
.77
-.11 -1.53
.08 1.08
-.04
-.70
.07
.74
-.11 -1.21
Work Hours
.04
.71
-.02
-.24
.08 1.38
.00
-.05
-.01
-.15
-.10 -1.23
.28
2.75
.25 3.04**
-.08 -1.04
-.32
.67
.17
1.84
Neuroticism
.30
2.51*
**
*
**
Trait NA
.05
.58
.06
.50
.30 3.12
.63 2.68
.06 -3.36
-.27 -3.42**
Marital Status
.09
1.21
.20
1.97
-.04
-.54
.04
.64
.02
.76
-.16 -1.65
Role Conflict
.04
.78
.28
4.89**
.01
.12
.01
.25
.00
.19
.42
1.71
Job Control Main Effects
-.17 -1.33
-.08
-.59
-.12 -1.69
-.10 -1.59
.07
.08
-.01
-.59
Job Control Slope Effects
.05
.39
.00
-.05
-.01
-.07
-.05
-.47
.04
.61
-.01
-.28
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Main Effects relates to
the effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Job Control on the level1 Role Conflict slopes predicting Well-Being. * p < .05 ** p < .01

146

Table 26: The Moderating Role of Job Control in the Relationship between Workload and Well-Being (Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 58.40
2.44 28.94
1.95 40.21
1.21 49.77
2.36 31.74
4.66 35.96
**
Gender
.01
.19
.18
2.89
.07 1.14
-.02
-.28
-.08 -1.39
-.07
-.86
Children #
.06
.84
-.11 -1.58
.11 1.43
-.04
-.54
.06
.58
-.11 -1.24
Work Hours
.05
.92
-.03
-.31
.08 1.32
.00
.05
.00
.08
-.11 -1.31
.30
3.29**
.28 3.56**
-.08 -1.03
-.33 -3.59**
-.38
1.88
Neuroticism
.29
2.64*
**
**
Trait NA
.06
.67
.04
.37
.29 3.16
.64 2.74
.04
.53
-.15 -3.32**
*
Marital Status
.09
1.16
.20
1.98
-.06
-.87
.03
.56
-.01
-.12
.16 -1.62
Workload
.06
1.15
.20
3.27**
.03
.60
.01
.20
.07
1.22
.06
1.75
Job Control Main Effects
-.17 -1.39
-.06
-.49
-.11 -1.56
-.10 -1.62
.06
.62
.18
.96
Job Control Slope Effects
.00
.04
-.01
-.11
-.12 -1.34
-.08 -1.02
.09
1.23
-.06 -1.15
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Main Effects relates to
the effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Job Control on the level1 Workload slopes predicting Well-Being. * p < .05 ** p < .01

147

Table 27: The Moderating Role of Job Control in the Relationship between Emotional Demands and Well-Being (Hypothesis
6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 58.39
2.44 28.95
1.95 40.25
1.21 49.66
2.36 31.74
4.66 35.98
Gender
.02
.32
.18
2.75**
.05
.84
-.02
-.30
.00
-.02
-.07
-.91
-.05
-.73
.06
.59
-.11 -1.25
Children #
.03
.49
-.12 -1.60
.09 1.26
Work Hours
.05
.90
-.02
-.23
.10 1.84
.01
.08
.00
-.07
-.11 -1.29
*
**
**
**
Neuroticism
.30
2.55
.29
2.86
.26 3.11
-.09 -1.04
-.35 -3.85
-.38 -3.36**
Trait NA
.04
.40
.06
.49
.30 3.14**
.65 2.74**
.11
1.44
-.15 -1.66
Marital Status
.10
1.23
.18
1.78
-.04
-.60
.04
.80
.03
.34
.16
1.74
**
**
Em. Demands
.17
3.30
.24
4.41
.09 1.45
.11 1.61
-.02
-.39
-.04
-.58
Job Control Main Effects
-.16 -1.32
-.07
-.53
-.13 -1.76
-.11 -1.68
.05
.50
.18
1.87
Job Control Slope Effects
-.01
-.10
-.04
-.90
-.05
-.54
-.02
-.25
.08
1.69
.02
.28
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Em. Demands =
Emotional Demands. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level
moderating effects of Job Control on the level-1 Emotional Demand slopes predicting Well-Being. * p < .05 ** p < .01

148

Table 28: The Moderating Role of Job Control in the Relationship between Interpersonal Conflict and Well-Being (Hypothesis
6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 58.29
2.44 28.96
1.95 40.17
1.21 49.48
2.36 31.83
4.66 35.93
Gender
.04
.54
.22
3.32**
.06
.91
-.02
-.39
-.04
-.62
-.08 -1.04
-.01
-.08
.07
.64
-.11 -1.33
Children #
.05
.83
-.11 -1.60
.09 1.27
Work Hours
.05
.87
-.01
-.09
.10 1.83
.03
.47
.00
.01
-.10 -1.30
*
*
**
**
Neuroticism
.28
2.56
.28
2.53
.25 3.00
-.09 -1.13
-.32 -3.51
-.37 -3.14**
Trait NA
.06
.69
.09
.62
.31 3.16**
.69 3.06**
.06
.80
-.16 -1.69
*
Marital Status
.10
1.28
.22
2.21
-.04
-.62
.02
.34
.00
.02
.17
1.94
*
*
*
*
In. Conflict
.18
2.42
.17
2.62
.10 1.55
.15 2.28
.08
2.01
-.16 -1.65
Job Control Main Effects
-.17 -1.42
-.09
-.67
-.13 -1.79
-.13 -1.93
.06
.63
.18
1.89
Job Control Slope Effects
.02
.13
.07
.79
.14
.88
.08
.58
-.11 -1.24
-.01
-.10
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict =
Interpersonal Conflict. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level
moderating effect of Job Control on the level-1 Interpersonal Conflict slopes predicting Well-Being. * p < .05 ** p < .01

149

Table 29: The Moderating Role of Job Control in the Relationship between Incivility and Well-Being (Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 58.47
2.44 29.02
1.95 40.24
1.21 49.61
2.36 31.81
4.66 35.92
**
Gender
.03
.36
.20
2.96
.06
.92
-.03
-.43
-.02
-.34
-.08 -1.00
Children #
.05
.75
-.09 -1.30
.09 1.23
-.07 -1.18
.05
.53
-.13 -1.57
Work Hours
.05
.91
-.02
-.27
.09 1.71
.02
.21
.00
.02
-.10 -1.15
.29
2.78**
.25 3.05**
-.09 -1.12
-.30 -3.17**
-.35 -3.05**
Neuroticism
.28
2.54*
Trait NA
.06
.68
.07
.51
.31 3.16**
.67 2.90**
.07
.93
-.17 -1.79
*
Marital Status
.10
1.28
.21
2.11
-.04
-.55
.05
.84
.01
.09
.18
2.07**
Incivility
.24
2.45*
.21
5.42**
.13 1.55
.02
.32
-.07 -1.29
-.11 -1.16
Job Control Main Effects
-.17 -1.41
-.08
-.61
-.13 -1.78
-.11 -1.67
.07
.74
.19
1.98*
Job Control Slope Effects
-.07
-.24
-.06 -1.10
.22
.99
-.01
-.13
.04
.39
-.14
-.95
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict =
Interpersonal Conflict. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level
moderating effect of Job Control on the level-1 Incivility slopes predicting Well-Being. * p < .05 ** p < .01

150

Table 30: The Moderating Role of Workplace Support in the Relationship between Role Conflict and Well-Being (Hypothesis
6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 58.47
2.44 28.93
1.95 40.19
1.21 49.69
2.36 31.83
4.66 35.99
Gender
.02
.30
.18
2.78**
.05
.91
-.01
-.09
-.03
-.41
-.07
-.91
-.04
-.70
.07
.74
-.11 -1.21
Children #
.05
.77
-.11 -1.53
.08 1.08
Work Hours
.04
.71
-.02
-.24
.08 1.38
.00
-.05
-.01
-.15
-.10 -1.23
Neuroticism
.30
2.51*
.28
2.75
.25 3.04**
-.08 -1.04
-.32
.67
.17
1.84
Trait NA
.05
.58
.06
.50
.30 3.12**
.63 2.68*
.06 -3.36**
-.27 -3.42**
Marital Status
.09
1.21
.20
1.97
-.04
-.54
.04
.64
.02
.76
-.16 -1.65
**
Role Conflict
.04
.78
.28
4.89
.01
.12
.01
.25
.00
.19
.42
1.71
W. Support Main Effects
-.17 -1.33
-.08
-.59
-.12 -1.69
-.10 -1.59
.07
.08
-.01
-.59
W. Support Slope Effects
.05
.39
.00
-.05
-.01
-.07
-.05
-.47
.04
.61
-.01
-.28
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. W. Support =
Workplace Support. Main Effects relates to the effect of Workplace Support on the level-1 intercept. Slope effects relates to the crosslevel moderating effect of Workplace Support on the level-1 Role Conflict slopes predicting Well-Being. * p < .05 ** p < .01

151

Table 31: The Moderating Role of Workplace Support in the Relationship between Workload and Well-Being (Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 57.14
2.44 32.25
1.95 39.89
1.21 49.34
2.36 31.83
4.65 36.82
**
Gender
.03
.32
.22
3.47
.09 1.47
-.02
-.25
-.09 -1.47
-.09 -1.29
Children #
.06
.88
-.08 -1.27
.12 1.73
-.04
-.64
.05
.49
-.12 -1.35
Work Hours
.01
.17
-.08 -1.12
.04
.73
-.01
-.12
.02
.32
-.05
-.64
.17
2.22*
.26 3.28**
-.04
-.52
-.31 -3.39**
-.34 -3.20**
Neuroticism
.31
2.68*
Trait NA
.02
.23
.04
.47
.27 2.57*
.62 2.62*
.05
.77
-.11 -1.09
Marital Status
.05
.73
.15
1.73
-.09 -1.42
.02
.39
.01
.09
.20
2.41*
Workload
.04
.78
.22
3.66**
.02
.31
.03
.53
.08
1.34
.07
1.19
**
W. Support Main Effects
-.11 -1.14
-.42 -4.59
-.14 -1.83
.00
-.02
.10
.98
.27
3.07**
W. Support Slope Effects
.12
1.37
-.12 -2.41*
-.03
-.41
-.15 -1.93
.04
.53
-.10 -2.08*
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. W. Support =
Workplace Support. Main Effects relates to the effect of Workplace Support on the level-1 intercept. Slope effects relates to the crosslevel moderating effect of Workplace Support on the level-1 Workload slopes predicting Well-Being. * p < .05 ** p < .01

152

Table 32: The Moderating Role of Workplace Support in the Relationship between Emotional Demands and Well-Being
(Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 57.18
2.44 32.27
1.95 39.93
1.21 49.23
2.36 31.79
4.65 36.85
Gender
.04
.49
.22
3.51**
.07 1.08
-.01
-.21
.00
-.02
-.10 -1.35
-.06
-.94
.05
.53
-.12 -1.38
Children #
.03
.42
-.08 -1.22
.09 1.38
Work Hours
.01
.23
-.08 -1.05
.06 1.20
-.01
-.15
.02
.24
-.05
-.61
*
**
**
Neuroticism
.31
2.59
.15
1.84
.25 2.85
-.05
-.61
-.34 -3.82
-.34 -3.21**
Trait NA
.00
.04
.06
.58
.28 2.54*
.63 2.61*
.12
1.88
-.12 -1.12
Marital Status
.07
.97
.15
1.63
-.07 -1.15
.04
.62
.05
.73
.20
2.42**
**
**
Em. Demands
.16
3.06
.23
4.25
.09 1.37
.09 1.41
-.02
-.35
-.05
-.74
W. Support Main Effects
-.11 -1.14
-.42 -4.61**
-.14 -1.74
.00
.00
.10
1.02
.27
3.09*
W. Support Slope Effects
-.09 -1.44
-.09 -2.47*
-.04
-.65
-.10 -1.40
.03
.48
-.02
-.31
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Em. Demands =
Emotional Demands. W. Support = Workplace Support. Main Effects relates to the effect of Workplace Support on the level-1
intercept. Slope effects relates to the cross-level moderating effect of Workplace Support on the level-1 Emotional Demands slopes
predicting Well-Being. * p < .05 ** p < .01

153

Table 33: The Moderating Role of Workplace Support in the Relationship between Interpersonal Conflict and Well-Being
(Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 57.15
2.45 32.20
1.95 39.82
1.21 48.99
2.36 31.90
4.65 36.76
Gender
.05
.68
.26
4.31**
.07 1.19
-.02
-.32
-.05
-.78
-.11 -1.56
-.01
-.14
.06
.60
-.13 -1.47
Children #
.05
.76
-.07 -1.16
.10 1.44
Work Hours
.01
.14
-.06
-.79
.07 1.23
.02
.27
.02
.33
-.04
-.60
*
**
**
Neuroticism
.30
2.64
.13
1.56
.24 2.71
-.06
-.74
-.31 -3.25
-.31 -2.93**
Trait NA
.02
.23
.08
.79
.28 2.57*
.67 2.91**
.08
1.10
-.12 -1.17
Marital Status
.07
.97
.17
1.93
-.08 -1.19
.00
.04
.02
.25
.22
2.78**
*
**
*
In. Conflict
.19
2.56
.19
2.85
.11 1.45
.14 2.19
.06
1.22
-.16 -1.85
W. Support Main Effects
-.11 -1.20
-.42 -4.65**
-.14 -1.79
-.01
-.05
.10
1.01
.29
3.29**
W. Support Slope Effects
.09
1.05
-.02
-.35
.00
-.01
-.10 -1.36
-.03
-.71
.01
.08
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict =
Interpersonal Conflict. W. Support = Workplace Support. Main Effects relates to the effect of Workplace Support on the level-1
intercept. Slope effects relates to the cross-level moderating effect of Workplace Support on the level-1 Interpersonal Conflict slopes
predicting Well-Being. * p < .05 ** p < .01

154

Table 34: The Moderating Role of Workplace Support in the Relationship between Incivility and Well-Being (Hypothesis 6).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 57.25
2.45 32.32
1.95 39.92
1.21 49.14
2.36 31.89
4.65 36.72
*
Gender
.04
.49
.23
3.71
.07 1.17
-.03
-.42
-.03
-.48
-.11 -1.51
Children #
.04
.64
-.07 -1.03
.09 1.32
-.09 -1.46
.04
.45
-.15 -1.79
Work Hours
.01
.16
-.08 -1.09
.06 1.09
.00
-.01
.02
.36
-.03
-.41
.16
1.97
.24 2.78**
-.05
-.70
-.28 -3.14**
-.28 -2.79**
Neuroticism
.30
2.61*
Trait NA
.02
.21
.05
.55
.28 2.55*
.64 2.75**
.09
1.34
-.14 -1.29
Marital Status
.07
1.00
.16
1.80
-.07 -1.07
.04
.63
.03
.35
.23
3.00**
Incivility
.32
2.50*
.21
4.64**
.16 1.50
.05
.61
-.11 -1.79
-.12 -1.17
**
W. Support Main Effects
-.11 -1.15
-.42 -4.62
-.14 -1.77
.01
.06
.12
1.22
.30
3.46**
W. Support Slope Effects
.43
1.69
.09
2.59*
.19 1.09
.13
.99
-.10
-.99
-.08
-.91
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. W. Support =
Workplace Support. Main Effects relates to the effect of Workplace Support on the level-1 intercept. Slope effects relates to the crosslevel moderating effect of Workplace Support on the level-1 Incivility slopes predicting Well-Being. * p < .05 ** p < .01

155

Table 35: The Moderating Role of Prior SE Levels in the Relationship between Workplace Demands and Experiences and
Self-Efficacy (Hypothesis 7).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
γ’
t
γ’
t
γ’
γ’
t
γ’
t
γ’
Intercept
81.31
39.97
80.67
35.91
82.08
43.06
82.64
40.83
82.99
41.55
Gender
-.07
-.89
-.09
-1.12
-.09
-1.15
-.12
-1.36
-.09
-1.04
Children #
-.07
-.80
.02
.29
.05
.64
.07
.78
.11
1.59
Work Hours
.18
2.00*
.19
2.05*
.00
-.05
.09
.95
.03
.33
*
**
*
Neuroticism
-.35
-2.61
-.11
-.85
-.33
-3.03
-.39
-3.29
-.34
-2.47*
Trait NA
.17
1.75
.00
.01
.15
1.68
.21
2.15
.15
1.39
*
*
Marital Status
-.11
-1.21
-.21
-2.19
-.18
-2.05
-.18
-1.82
-.24
-2.47*
**
**
**
Demand/ Experience
-.10
-1.80
-.25
-5.25
-.15
-2.73
-.33
-3.62
-.14
-1.09
Prior SE level
.00
.06
.09
1.18
.08
1.07
.07
1.48
.13
2.00*
Interaction Term
.11
1.97
-.08
-1.12
.02
.47
.02
.28
-.09
-.96
Notes: N = 394-398. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean
hours worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect.
Demand/Experience relates to the relevant domain being examined (e.g. Role Conflict for Role Conflict Self-Efficacy). SE = Self
Efficacy. Em. Demands = Emotional Demands. In. Conflict = Interpersonal Conflict. Interaction term relates to the interaction
between the relevant Demand/Experience and associated Self-Efficacy domain (e.g. Role Conflict interacting with prior levels of
Role Conflict Self Efficacy). * p < .05 ** p < .01

156

Table 36: The Moderating Role of Prior SE Levels in the Relationship between Role Conflict and Well-Being (Hypothesis 7).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.87 50.40
2.48
27.98
1.98 35.89
1.22 45.57
2.32 29.22
4.66 33.36
*
Gender
-.03
-.40
.18
2.43
.00
.06
-.04
-.61
-.05
-.76
-.05
-.67
Children #
.06
.90
-.12
-1.63
.06
.80
-.04
-.61
.10
.93
-.09
-.92
Work Hours
.07
1.22
-.02
-.23
.09 1.48
.04
.51
.00
-.06
-.04
-.54
.38
3.51**
.35 3.93**
.00
-.03
-.34
-3.85**
-.45
-4.19**
Neuroticism
.43
3.54**
Trait NA
.01
.13
.00
.00
.24 2.80**
.56 2.57*
.07
.77
-.15
-1.74
*
Marital Status
.07
.95
.25
2.51
-.04
-.52
.00
.01
-.01
-.16
.13
1.34
Role Conflict
.02
.20
.35
3.96**
.01
.19
.03
.36
.08
1.61
-.04
-.76
Prior SE Level
-.04
-.56
.04
.82
.00
.02
-.03
-.46
.09
1.55
.12
1.94
Interaction Term
-.03
-.52
.05
.63
-.03
-.45
-.09 -1.71
.02
.51
.06
1.24
Notes: N = 394-398. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. SE = Self Efficacy.
Interaction term relates to the interaction between Role Conflict and prior levels of Role Conflict Self-Efficacy. * p < .05 ** p < .01

157

Table 37: The Moderating Role of Prior SE Levels in the Relationship between Workload and Well-Being (Hypothesis 7).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.87 51.01
2.47
27.47
1.97 36.87
1.21 48.63
2.32 29.22
4.66 33.47
Gender
.03
.34
.19
2.59
.01
.15
-.06
-.82
-.08 -1.15
-.06
-.68
Children #
.03
.44
-.11
-1.56
.06
.83
-.05
-.78
.09
.86
-.10 -1.13
Work Hours
.03
.56
-.02
-.29
.08 1.88
.03
.42
-.02
-.32
-.07
-.81
.36
3.54**
.38 4.78**
.00
-.05
-.38 -4.40**
-.43 -4.11**
Neuroticism
.40
3.10**
Trait NA
.00
.01
.00
.03
.21 2.62**
.54 2.73**
.07
.77
-.14 -1.66
*
Marital Status
.13
1.74
.26
2.55
-.04
-.63
.00
.01
-.02
-.23
.17
1.78
Workload
.06
1.19
.25
4.09**
.03
.59
.02
.37
.09
1.62
.10
1.66
Prior SE Level
-.09
-1.35
-.06
-1.26
.11 1.72
.05
.56
-.04
-.99
.03
.42
Interaction Term
-.14
-2.23*
-.08
-1.43
-.10 -1.84
-.08
-.95
.07
2.48*
.11
1.16
Notes: N = 394-398. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. SE = Self Efficacy.
Interaction term relates to the interaction between Workload and prior levels of Workload Self-Efficacy. * p < .05 ** p < .01

158

Table 38: The Moderating Role of Prior SE Levels in the Relationship between Emotional Demands and Well-Being
(Hypothesis 7).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.86 50.92
2.47
27.97
1.98 36.31
1.20 50.54
2.32 29.28
4.67 33.73
Gender
-.06
-.60
.18
2.57*
.01
.17
-.09 -1.47
-.05
-.69
-.04
-.53
.77
-.04
-.81
.10
.92
-.09
-.95
Children #
.01
.15
-.12
-1.66
.06
Work Hours
.07
1.21
-.02
-.24
.09 1.71
.01
.16
.00
-.04
-.05
-.57
**
**
**
**
Neuroticism
.40
3.09
.38
3.58
.33 3.76
.04
.52
-.37 -4.22
-.45
-4.13**
Trait NA
-.04
-.36
.02
.19
.24 2.79**
.35 3.03**
.09
1.10
-.14
-1.59
*
Marital Status
.06
.81
.23
2.28
-.03
-.45
.01
.12
-.02
-.19
.15
1.57
**
Em. Demands
.10
1.45
.18
2.95
.11 1.54
.10 1.33
.04
.81
-.01
-.16
Prior SE Level
-.06
-1.02
-.04
-.91
.01
.21
.03
.57
.04
.68
.08
1.08
Interaction Term
.01
.26
.04
.52
.02
.47
-.14
-.72
-.06 -1.31
-.06
-1.42
Notes: N = 394-398. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. Em. Demands =
Emotional Demands. SE = Self Efficacy. Interaction term relates to the interaction between Emotional Demands and prior levels of
Emotional Demands Self-Efficacy. * p < .05 ** p < .01

159

Table 39: The Moderating Role of Prior SE Levels in the Relationship between Interpersonal Conflict and Well-Being
(Hypothesis 7).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.87
50.91
2.47
27.71
1.98 35.30
1.21 45.72
2.32 29.25
4.68 33.55
Gender
.02
.24
.21
2.72**
.03
.40
-.04
-.62
-.06
-.82
-.05
-.55
-.02
-.30
.10
.93
-.10
-1.11
Children #
.02
.29
-.14
-1.88
.09 1.14
Work Hours
.06
.99
.02
.33
.12 2.33*
.04
.62
.00
.04
-.03
-.42
*
**
*
**
Neuroticism
.45
3.53
.35
3.23
.35 4.02
.00
.06
-.35
-3.91
-.46
-4.14**
Trait NA
-.01
-.07
.05
.34
.23 2.66**
.55 2.48*
.07
.87
-.12
-1.43
*
Marital Status
.14
1.74
.28
2.68
-.03
-.45
.01
.15
-.02
-.21
.14
1.51
*
**
In. Conflict
.20
2.63
.21
3.19
.10 1.20
.12 1.41
.08
1.43
-.05
-.70
Prior SE Level
-.09
-1.23
-.01
-.15
-.02
-.33
.00
.04
.02
.52
.03
.57
**
**
Interaction Term
.01
.13
-.19
-3.81
-.07 -2.08
-.05
-.84
.07
1.67
.19
4.60**
Notes: N = 394-398. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. In. Conflict =
Interpersonal Conflict. SE = Self Efficacy. Interaction term relates to the interaction between Interpersonal Conflict and prior levels of
Interpersonal Conflict Self-Efficacy. * p < .05 ** p < .01

160

Table 40: The Moderating Role of Prior SE Levels in the Relationship between Incivility and Well-Being (Hypothesis 7).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.87 50.75
2.46
27.67
1.98 35.40
1.21 45.34
2.32 29.36
4.65 33.12
*
Gender
-.02
-.24
.19
2.48
.02
.25
-.03
-.57
-.04
-.55
-.05
-.65
Children #
.02
.28
-.12
-1.61
.05
.65
-.08 -1.29
.10
.96
-.10
-1.11
Work Hours
.04
.67
.00
-.05
.10 1.99*
.03
.41
-.01
-.15
-.04
-.48
.35
3.31**
.34 3.84**
-.02
-.32
-.35 -3.89**
-.48
-4.45
Neuroticism
.45
3.44**
Trait NA
-.01
-.11
.02
.18
.25 2.95**
.61 2.99**
.07
.87
-.11
-1.25
*
Marital Status
.12
1.43
.27
2.62
-.01
-.11
.05
.88
-.01
-.14
.14
1.55
Incivility
.22
1.79
.12
1.95
.04
.60
-.04
-.66
-.04
-.88
-.04
-.51
Prior SE Level
-.13
-1.78
-.07
-1.37
-.04
-.59
.00
-.05
.06
1.35
.13
2.04
Interaction Term
-.08
-.93
.01
.09
.02
.31
.13 2.23*
.07
2.35*
.15
2.25*
Notes: N = 394-398. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. SE = Self Efficacy.
Interaction term relates to the interaction between Incivility and prior levels of Incivility Self-Efficacy. * p < .05 ** p < .01

161

Table 41: The Moderating Role of Coping Success in the Relationship between Workplace Demands and Experiences and SelfEfficacy (Hypothesis 8).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
γ’
t
γ’
t
γ’
γ’
t
γ’
t
γ’
Intercept
80.67
42.84
78.69
38.92
81.53
46.40
81.44
42.89
83.12
43.52
-.11
-1.49
-.13
-1.75
Gender
-.12
-1.64
-.10
-1.35
-.16
-2.28*
Children #
-.02
-.22
.07
.93
.09
1.39
.12
1.47
.08
1.21
Work Hours
.08
.89
.12
1.51
.01
.09
.03
.28
.01
.13
Neuroticism
-.32
-2.77**
-.15
-1.34
-.28
-2.56*
-.41
-3.78**
-.33
-2.79**
Trait NA
.10
1.08
.04
.53
.02
.28
.20
1.94
.23
2.63*
-.14
-1.66
-.19
-2.10*
-.16
-1.75
Marital Status
-.07
-.79
-.19
-2.26*
*
*
**
*
# of Coping Strategies
-.13
-2.23
-.19
-2.67
-.18
-2.90
-.12
-2.25
-.04
-.67
*
**
**
**
Demand/ Experience
-.16
-2.28
-.20
-4.04
-.23
-2.88
-.24
-3.18
-.22
-2.27*
Coping Success
.18
3.41**
.31
4.51**
.03
.54
.17
2.46*
.21
3.38**
*
Interaction Term
.07
.75
.16
3.53
-.03
-.39
.09
.98
-.02
-.09
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean
hours worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping
Strategies = the number of different copings strategies utilized. Demand/Experience relates to the relevant domain being examined
(e.g. Role Conflict for Role Conflict Self-Efficacy). Em. Demands = Emotional Demands. In. Conflict = Interpersonal Conflict.
Interaction term relates to the interaction between the relevant Demand/Experience and Coping Success (e.g. Role Conflict
interacting coping success when predicting Role Conflict Self Efficacy). * p < .05 ** p < .01

162

Table 42: The Moderating Role of Coping Success in the Relationship between Role Conflict and Well-Being (Hypothesis 8).
Experienced
Emotional
Affective
Negative
Positive
Life
Strain
Exhaustion
Distress
Affect
Affect
Satisfaction
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 55.85
2.45 28.86
1.94 37.85
1.19 59.87
2.38 31.57
4.66 35.12
Gender
.02
.27
.21
3.05**
.04
.59
-.05
-.95
-.04
-.56
-.09
-1.17
Children #
.00
.01
-.10
-1.39
.10
1.44
.01
.34
.10
1.12
-.10
-1.06
Work Hours
.00
.05
-.04
-.42
.03
.53
-.01
-.15
.05
.95
-.08
-.95
Neuroticism
.33
3.35**
.28
2.53*
.31
3.63
.01
.21
-.35
-3.85**
-.43
-4.19**
Trait NA
.01
.07
.04
.32
.20
1.78
.28
2.79**
.05
.55
-.10
-1.09
Marital Status
.09
1.27
.14
1.41
-.12
-1.86
-.08
-1.65
.03
.35
.16
1.77
# of Coping Strategies
.01
.21
.05
.75
.04
.64
.04
.61
.03
.40
-.02
-.32
*
Role Conflict
.04
.71
.38
4.13
.01
.17
.04
.63
.04
.91
-.06
-1.25
Coping Success
-.17
-3.59*
-.05
-.86
-.13
-2.38*
-.01
-.13
.03
.57
.04
.84
Interaction Term
.06
.91
.00
-.03
.01
.19
.02
.19
-.10
-1.83
.06
.61
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Interaction term relates to the interaction between Role Conflict and Coping
Success. * p < .05 ** p < .01

163

Table 43: The Moderating Role of Coping Success in the Relationship between Workload and Well-Being (Hypothesis 8).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.07
2.45 29.33
1.95 38.15
1.20 57.20
2.38 31.76
4.66 35.23
**
Gender
.00
.05
.21
3.51
.09 1.50
-.04
-.77
-.11 -1.68
-.07
-.94
Children #
.04
.62
-.07
-1.14
.10 1.48
.01
.24
.06
.59
-.10 -1.11
Work Hours
.01
.13
-.07
-1.13
.09 1.81
.00
.06
.00
-.01
-.06
-.74
.27
3.02**
.31 3.67**
-.01
-.11
-.33 -3.62**
-.41 -3.85**
Neuroticism
.34
3.60*
Trait NA
.03
.36
.03
.24
.27 2.16*
.34 2.92**
.03
.37
-.11 -1.16
Marital Status
.06
.80
.13
1.51
-.12 -1.89
-.07 -1.57
.00
.01
.18
1.96
# of Coping Strategies
.04
.60
.04
.57
.04
.71
.01
.23
.02
.30
-.03
-.57
**
Workload
.06
1.24
.20
3.25
.00
-.06
-.01
-.16
.07
1.37
.04
.66
Coping Success
-.17 -3.16*
-.09
-1.39
-.13 -2.15*
-.01
-.15
.05
.96
.05
.99
Interaction Term
-.05 -1.00
.04
1.30
-.08
-.90
.05
.77
.05
.71
.08
1.18
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Interaction term relates to the interaction between workload and Coping Success.
*
p < .05 ** p < .01

164

Table 44: The Moderating Role of Coping Success in the Relationship between Emotional Demands and Well-Being
(Hypothesis 8).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 55.42
2.46
29.27
1.94 38.34
1.19 58.90
2.38 31.39
4.66 35.20
Gender
.04
.67
.25
3.79**
.05
.80
-.06 -1.00
-.02
-.31
-.09 -1.25
.00
-.08
.10
1.04
-.10 -1.08
Children #
-.03
-.50
-.09
-1.39
.10 1.37
Work Hours
.04
.72
-.05
-.67
.07 1.46
-.01
-.17
.04
.70
-.08 -1.02
**
*
*
**
Neuroticism
.35
3.46
.26
2.39
.29 3.40
-.02
-.35
-.40 -4.69
-.40 -3.93**
Trait NA
.02
.23
.05
.39
.25 2.09*
.38 3.21**
.09
1.32
-.12 -1.39
Marital Status
.11
1.48
.18
1.86
-.11 -1.64
-.08 -1.73
.04
.52
.15
1.69
# of Coping Strategies
.02
.39
.07
1.07
.05
.81
-.01
-.24
.06
1.03
-.03
-.45
Em. Demands
.15
2.51*
.25
3.80**
.09 1.18
.10 1.64
-.02
-.46
-.07
-.75
Coping Success
-.15 -3.00**
-.08
-1.17
-.12 -2.09*
.00
-.03
.03
.55
.03
.77
Interaction Term
.05
.73
.11
2.49*
-.02
-.29
-.04
-.75
-.14 -1.91
-.06
-.66
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Em. Demands = Emotional Demands. Interaction term relates to the interaction
between Emotional Demands and Coping Success. * p < .05 ** p < .01

165

Table 45: The Moderating Role of Coping Success in the Relationship between Interpersonal Conflict and Well-Being
(Hypothesis 8).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 55.90
2.45 29.48
1.95 37.68
1.20 55.50
2.37 31.52
4.66 35.51
Gender
.01
.14
.22
3.47**
.07 1.04
-.06 -1.05
-.06
-.91
-.10 -1.42
.01
.13
.09
.88
-.11 -1.32
Children #
.02
.37
-.04
-.64
.10 1.36
Work Hours
.04
.85
-.06
-.85
.08 1.64
.01
.12
-.01
-.14
-.09 -1.05
Neuroticism
.33
3.74**
.29
2.70**
.29 3.26**
-.01
-.19
-.36 -4.14**
-.41 -4.00**
Trait NA
.04
.48
.02
.16
.27 2.13*
.38 2.73**
.06
.67
-.12 -1.32
Marital Status
.06
.90
.12
1.37
-.11 -1.55
-.06 -1.29
.01
.18
.18
2.08*
# of Coping Strategies
.01
.14
.01
.19
.02
.35
-.01
-.14
.08
1.30
-.01
-.21
In. Conflict
.14
1.63
.17
2.23*
.09 1.06
.10 1.26
.05
1.00
-.11 -1.03
Coping Success
-.21 -3.63**
-.09
-1.43
-.10 -1.71
-.01
-.15
.06
1.00
.04
.87
Interaction Term
.07
.78
.14
2.12*
-.01
-.27
.05
.76
-.26 -4.16**
.05
.54
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. In. Conflict = Interpersonal Conflict. Interaction term relates to the interaction
between Interpersonal Conflict and Coping Success. * p < .05 ** p < .01

166

Table 46: The Moderating Role of Coping Success in the Relationship between Incivility and Well-Being (Hypothesis 8).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.43
2.46 29.51
1.95 37.80
1.20 54.37
2.38 31.40
4.63 34.37
.08 1.22
-.04
-.74
-.04
-.60
-.11 -1.41
Gender
.05
.65
.21
3.22**
Children #
.01
.10
-.05
-.86
.10 1.35
-.02
-.46
.06
.57
-.11 -1.26
Work Hours
.03
.55
-.06
-.85
.08 1.62
.00
-.08
.01
.18
-.08 -1.07
**
**
**
**
Neuroticism
.32
3.44
.29
2.73
.28 3.12
-.03
-.49
-.38 -4.61
-.41 -3.65**
*
**
Trait NA
.05
.61
.02
.20
.28 2.26
.39 3.15
.08
.98
-.11 -1.21
-.05 -1.14
.02
.19
.14
1.59
Marital Status
.08
1.14
.14
1.52
-.10 -1.51
# of Coping Strategies
.01
.13
.03
.42
.02
.30
-.01
-.20
.05
.71
-.01
-.15
Incivility
.18
2.64*
.21
4.01*
.10 1.25
.01
.10
-.06 -1.36
-.24 -1.51
Coping Success
-.17 -3.22**
-.08
-1.23
-.11 -1.64
.01
.17
.03
.50
.05
.95
*
Interaction Term
.04
.69
.01
.36
.03
.82
-.03
-.95
.10
2.48
-.10
-.39
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Interaction term relates to the interaction between Incivility and Coping Success.
*
p < .05 ** p < .01

167

Table 47: The Relationship of Prior Self-Efficacy Levels and Workplace Resources with Coping Success
Model 1
γ’
t
3.36 58.39
.05
.92
.01
.10
-.07 -1.15
-.25 -3.17**
.02
.35
-.10 -1.30
.10 1.53
.20 2.02*

Model 2
γ’
3.36
.03
.01
-.01
-.22
.08
-.05
.10

t
58.45
.44
.14
-.10
-2.62*
1.07
-.74
1.57

Model 3

Model 4

Model 5

Model 6

Model 7

γ’
t
3.34 51.48
.02
.36
.08 1.18
.02
.30
-.30 -2.93**
.06
.59
-.10 -1.17
.13 1.56

γ’
t
3.33 51.86
.03
.49
.08 1.13
.02
.43
-.29 -2.88**
.03
.36
-.09 -1.13
.12 1.51

γ’
t
3.33 51.84
.03
.62
.09 1.37
.03
.54
-.29 -2.91**
.03
.30
-.10 -1.18
.11 1.26

γ’
t
3.33 51.63
.03
.45
.08 1.26
.02
.34
-.29 -2.82*
.03
.33
-.10 -1.22
.14 1.62

γ’
t
3.33 51.36
.02
.42
.10 1.43
.02
.30
-.28 -2.75**
.03
.27
-.11 -1.34
.11 1.32

Intercept
Gender
Children #
Work Hours
Neuroticism
Trait NA
Marital Status
# of Cop. Strategies
Job Control
Workplace Support
.26 2.55*
Pr. R. Conflict SE
-.02
-.27
Pr. Workload SE
.10
.98
Pr. E. Demands SE
-.05
-.52
Pr. In.Conflict SE
.07
.67
Pr. Incivility SE
-.04
-.45
Notes: N = 77 for Models 1-2, N = 394-398 for Models 3-7. Gender was coded as 1 = male, 2 = female. Children # = Number of
Children. Work Hours relates to mean hours worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA =
Trait Negative Affect. # of Coping Strategies = the number of different copings strategies utilized. Pr. = Previous. R. Conflict SE =
Role Conflict Self-Efficacy. E. Demands SE = Emotional Demands Self-Efficacy. In. Conflict SE = Interpersonal Conflict SE. All
models have Coping Success as the dependent variable. * p < .05 ** p < .01

168

Table 48: The Mediating Role of Coping Success for the Buffering Effects of Control on Self-Efficacy Outcomes (Hypothesis
9).
Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Self-Efficacy Role Conflict
Workload
Em. Demands
In. Conflict
Incivility
γ’
t
γ’
t
γ’
γ’
t
γ’
t
γ’
Intercept
80.70
43.45
78.69
38.94
81.56
46.43
81.39
43.02
83.09
43.12
Gender
-.11
-1.51
-.10
-1.33
-.15
-2.00*
-.10
-1.29
-.10
-1.26
Children #
-.03
-.38
.05
.74
.08
1.20
.11
1.53
.05
.70
Work Hours
.05
.50
.13
1.57
.00
-.04
.01
.05
-.02
-.22
-.17
-1.43
-.24
-2.11*
-.33
-2.97*
-.24
-2.00*
Neuroticism
-.23
-2.02*
Trait NA
.04
.49
.06
.71
.00
-.04
.16
1.48
.16
1.99*
Marital Status
-.10
-1.05
-.18
-2.18*
-.14
-1.61
-.21
-2.34*
-.13
-1.42
*
**
**
*
# of Coping Strategies
-.13
-2.22
-.20
-2.78
-.18
-2.87
-.12
-2.19
-.06
-1.15
Demand or Experience
-.17
-2.30*
-.18
-3.39**
-.21
-2.91**
-.26
-3.57**
-.17
-1.74
*
Job Control Main Effect
.21
2.42
-.02
-.24
.12
1.26
.16
1.65
.26
1.93
Job Control Slope Effect
-.02
-.30
-.12
-2.21*
.16
1.79
.17
1.39
.27
2.00*
Coping Success
.19
3.45**
.32
4.57**
.03
.47
.16
2.28*
.23
4.09**
**
Interaction Term
.07
.74
.14
3.68
-.05
-.59
.08
.99
-.08
-.40
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Em. Demands = Emotional Demands. In. Conflict = Interpersonal Conflict.
Demand/Experience relates to the relevant domain being examined (e.g. Role Conflict for Role Conflict Self-Efficacy). Main Effects
relates to the effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Job Control on
the level-1 Demand/Experience slopes predicting Self-Efficacy. Interaction term relates to the interaction between the relevant
Demand/Experience and Coping Success (e.g. Role Conflict interacting with Coping Success when predicting Role Conflict SelfEfficacy). * p < .05 ** p < .01

169

Table 49: The Mediating Role of Coping Success for the Buffering Effects of Workplace Support on Self-Efficacy Outcomes
(Hypothesis 9).
Self-Efficacy Role Conflict
γ’
t
80.65
46.73
-.13
-1.69
-.07
-.90
.12
1.45
-.16
-1.41
.11
1.14
-.02
-.24
-.12
-2.10*
-.17
-2.25*
.39
3.82**

Self-Efficacy Workload
γ’
t
78.74
41.53
-.15
-1.82
.04
.56
.15
2.08*
-.03
-.22
.03
.33
-.16
-2.02*
-.18
-2.56*
-.19
-3.80**
.30
3.04**

Self-Efficacy Em. Demands
γ’
γ’
81.54
49.27
-.17
-2.25*
.06
1.00
.04
.41
-.16
-1.45
.03
.28
-.11
-1.29
-.18
-2.83**
-.22
-3.07**
.30
3.18**

Self-Efficacy In. Conflict
t
γ’
81.41
47.50
-.12
-1.47
.08
1.18
.08
.88
-.24
-2.20*
.21
1.95
-.16
-2.01*
-.12
-2.15*
-.24
-3.58**
.43
3.80**

Self-Efficacy Incivility
t
γ’
83.05
45.86
-.16
-1.94
.08
1.20
.02
.23
-.21
-1.80
.21
2.54*
-.17
-1.81
-.03
-.52
-.20
-1.63
.24
2.10*

Intercept
Gender
Children #
Work Hours
Neuroticism
Trait NA
Marital Status
# of Coping Strategies
Demand or Experience
W. Support Main Effect
W. Support Slope
-.03
-.41
-.02
-.39
.10
1.61
.02
.21
.39
1.82
Effect
Coping Success
.16
2.95**
.30
4.31**
.02
.38
.15
2.12*
.18
2.79**
**
Interaction Term
.06
.62
.15
3.36
-.04
-.44
.07
.74
.05
.74
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Em. Demands = Emotional Demands. In. Conflict = Interpersonal Conflict.
Demand/Experience relates to the relevant domain being examined (e.g. Role Conflict for Role Conflict Self-Efficacy). W. Support =
Workplace Support. Main Effects relates to the effect of Workplace Support on the level-1 intercept. Slope effects relates to the crosslevel moderating effects of Workplace Support on the level-1 Demand/Experience slopes predicting Self-Efficacy. Interaction term
relates to the interaction between the relevant Demand/Experience and Coping Success (e.g. Role Conflict interacting with Coping
Success when predicting Role Conflict Self-Efficacy). * p < .05 ** p < .01

170

Table 50: The Mediating Role of Coping Success for the Moderating Effects of Job Control on Role Conflict (Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.82
2.45 28.84
1.94 38.55
1.19 61.58
2.38 31.56
4.66 35.95
**
Gender
.01
.19
.20
2.98
.03
.41
-.06
-1.26
-.03
-.48
-.06
-.76
Children #
.02
.32
-.09
-1.29
.11
1.57
.03
.62
.09
.92
-.11
-1.25
Work Hours
.03
.55
-.03
-.33
.06
.88
.01
.15
.04
.66
-.09
-1.07
.27
2.53*
.28
3.40**
-.02
-.31
-.30
-3.14**
-.37
-3.31**
Neuroticism
.28
2.98**
Trait NA
.03
.37
.05
.40
.22
2.10*
.30
3.11**
.02
.23
-.13
-1.31
Marital Status
.11
1.38
.15
1.40
-.11
-1.69
-.06
-1.39
.02
.21
.16
1.78
# of Coping Strategies
.01
.19
.06
.78
.05
.67
.04
.63
.02
.38
-.03
-.40
Role Conflict
.03
.49
.38
4.13
.01
.32
.04
.71
.04
.85
-.07
-1.36
Job Control Main Effects
-.14 -1.23
-.03
-.25
-.11
-1.73
-.11
-2.26*
.11
1.38
.19
2.23*
Job Control Slope Effects
.06
.59
.03
.50
-.06
-.95
-.09
-.88
.02
.28
-.01
-.55
**
*
Coping Success
-.17 -3.58
-.05
-.89
-.14
-2.44
-.02
-.25
.03
.57
.04
.88
Interaction Term
.06
.98
-.01
-.09
.02
.20
.02
.17
-.10
-1.74
.04
.45
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope
effects relates to the cross-level moderating effects of Job Control on the level-1 Role Conflict slopes predicting Well-Being.
Interaction term relates to the interaction between Role Conflict and Coping Success. * p < .05 ** p < .01

171

Table 51: The Mediating Role of Coping Success for the Buffering Effects of Job Control on Workload (Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.86 57.04
2.45 29.24
1.95 38.63
1.20 58.62
2.38 31.78
4.66 36.02
**
Gender
.00
-.03
.21
3.49
.08
1.30
-.05
-.95
-.10 -1.65
-.07
-.89
Children #
.06
.89
-.07
-1.13
.11
1.53
.02
.44
.05
.48
-.13 -1.49
Work Hours
.03
.69
-.07
-1.10
.10
1.96
.02
.43
-.01
-.17
-.08 -1.06
.28
3.03**
.28
3.31**
-.03
-.59
-.30 -3.13**
-.34 -3.00**
Neuroticism
.28
3.24**
Trait NA
.07
.84
.02
.24
.29
2.36*
.36
3.18**
.01
.14
-.15 -1.56
Marital Status
.08
.99
.13
1.47
-.11
-1.70
-.06
-1.25
-.01
-.08
.16
1.90
# of Coping Strategies
.04
.56
.03
.55
.04
.59
.01
.17
.02
.35
-.04
-.67
**
Workload
.05
1.13
.21
3.17
.01
.16
.00
-.05
.07
1.26
.05
.88
Job Control Main Effects
-.15 -1.39
.00
.01
-.08
-1.22
-.09
-2.09*
.09
.90
.18
2.15*
Job Control Slope Effects
.01
.21
-.02
-.40
-.09
-1.27
-.08
-1.13
.03
.56
-.05 -1.19
**
*
Coping Success
-.17 -3.15
-.08
-1.34
-.12
-2.19
-.01
-.15
.05
.86
.05
1.08
Interaction Term
-.05
-.95
.04
1.25
-.08
-.88
.05
.71
.05
.74
.08
1.13
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope
effects relates to the cross-level moderating effects of Job Control on the level-1 Workload slopes predicting Well-Being. Interaction
term relates to the interaction between Workload and Coping Success. * p < .05 ** p < .01

172

Table 52: The Mediating Role of Coping Success for the Buffering Effects of Support on Emotional Demands (Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.33
2.45 29.10
1.94 39.04
1.19 60.75
2.38 31.44
4.66 35.97
**
Gender
.04
.55
.25 3.79
.04
.64
-.07 -1.24
-.02
-.36
-.09 -1.19
Children #
-.01
-.20
-.09 -1.34
.12
1.53
.01
.31
.09
.89
-.11 -1.35
Work Hours
.05 1.06
-.06
-.69
.09
1.72
.01
.23
.03
.49
-.11 -1.34
.26
2.58*
.26 3.05**
-.06
-.85
-.38 -4.15**
-.33 -2.97**
Neuroticism
.31 3.24**
Trait NA
.05
.58
.04
.35
.27
2.37*
.40 3.53**
.08 1.14
-.17 -1.80
Marital Status
.12 1.48
.18
1.78
-.10 -1.55
-.07 -1.47
.04
.49
.14 1.60
Em. Demands
.02
.40
.07
1.07
.05
.83
-.01
-.22
.07 1.07
-.02
-.27
*
**
# of Coping Strategies
.15 2.61
.25 3.82
.09
1.14
.09
1.64
-.01
-.28
-.06
-.72
Job Control Main Effects
-.12 -1.05
.01
.12
-.10 -1.46
-.10 -2.20*
.03
.33
.17 2.07*
Job Control Slope Effects
-.07
-.81
-.03
-.83
-.10 -1.14
-.06
-.72
.07 1.41
-.03
-.92
**
*
Coping Success
-.15 -3.03
-.07 -1.12
-.12 -2.08
.00
-.05
.03
.51
.03
.67
Interaction Term
.03
.42
.11
2.15*
-.03
-.51
-.04
-.85
-.14 -1.93
-.08
-.92
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean
hours worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping
Strategies = the number of different copings strategies utilized. Em. Demands = Emotional Demands. Main Effects relates to the
effect of Job Control on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Job Control on the level-1
Emotional Demands slopes predicting Well-Being. Interaction term relates to the interaction between Emotional Demands and
Coping Success. * p < .05 ** p < .01

173

Table 53: The Mediating Role of Coping Success for the Buffering Effects of Job Control on Interpersonal Conflict
(Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.74
2.45 29.41
1.95 38.14
1.20 56.69
2.37 31.57
4.66 36.20
**
Gender
.00
-.04
.22
3.38
.06
.91
-.07 -1.24
-.06
-.96
-.09 -1.27
Children #
.03
.44
-.04
-.64
.11 1.48
.02
.43
.08
.79
-.13 -1.55
Work Hours
.07
1.48
-.07
-.97
.10 1.89
.02
.46
-.03
-.46
-.11 -1.31
.30
2.80**
.26 2.94**
-.04
-.72
-.31 -3.49**
-.36 -3.23**
Neuroticism
.29
3.38**
Trait NA
.06
.78
.01
.10
.29 2.35*
.40 2.97**
.03
.34
-.15 -1.63
Marital Status
.08
1.08
.12
1.28
-.10 -1.40
-.05 -1.10
.00
.02
.17
2.00*
.30
-.01
-.21
.09
1.37
.00
.00
# of Coping Strategies
.00
.04
.01
.21
.02
In. Conflict
.11
1.28
.14
1.82
.08
.98
.10 1.27
.06
1.30
-.09
-.84
Job Control Main Effects
-.12 -1.18
.01
.05
-.10 -1.50
-.10 -2.15*
.12
1.29
.17
2.02*
Job Control Slope Effects
.20
1.56
.09
1.06
.15 1.02
.09
.73
-.15 -1.40
-.09 -1.59
**
Coping Success
-.20 -3.51
-.09 -1.46
-.10 -1.62
-.01
-.12
.07
1.09
.03
.62
Interaction Term
.09
.96
.15
2.10*
.00
-.01
.06
.80
-.25 -4.34**
.00
.03
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. In. Conflict = Interpersonal Conflict. Main Effects relates to the effect of Job
Control on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Job Control on the level-1 Interpersonal
Conflict slopes predicting Well-Being. Interaction term relates to the interaction between Interpersonal Conflict and Coping Success.
*
p < .05 ** p < .01

174

Table 54: The Mediating Role of Coping Success for the Buffering Effects of Job Control on Incivility (Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.86 57.72
2.46 29.49
1.95 38.45
1.20 55.47
2.38 31.44
4.63 35.20
**
Gender
.04
.61
.22
3.32
.07 1.10
-.05
-.88
-.03
-.54
-.09 -1.22
Children #
.04
.59
-.05
-.74
.11 1.51
.00
-.10
.05
.47
-.13 -1.48
Work Hours
.06
1.28
-.06
-.89
.10 1.88
.01
.23
.00
-.02
-.10 -1.28
.27
2.48*
.25 2.84**
-.05
-.93
-.33 -3.69**
-.36 -2.87**
Neuroticism
.26
3.09**
Trait NA
.09
1.22
.03
.29
.30 2.51*
.40 3.34**
.05
.65
-.15 -1.52
Marital Status
.09
1.11
.14
1.48
-.09 -1.37
-.04
-.96
.00
.06
.14
1.62
# of Coping Strategies
.00
.06
.03
.40
.02
.32
-.01
-.20
.05
.72
.00
-.05
**
**
Incivility
.18
2.77
.21
3.78
.13 1.34
.01
.17
-.07 -1.20
-.27 -1.66
Job Control Main Effects
-.16 -1.41
-.01
-.10
-.10 -1.50
-.10 -2.27*
.10
1.10
.16
1.83
Job Control Slope Effects
-.21 -1.61
-.11 -1.82
.10
.53
-.07
-.70
-.02
-.18
-.37 -2.39*
**
Coping Success
-.17 -3.24
-.08 -1.15
-.10 -1.63
.01
.14
.03
.46
.05
.95
Interaction Term
.02
.35
.01
.29
.03
.49
-.04 -1.27
.10
2.41*
-.09
-.33
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Main Effects relates to the effect of Job Control on the level-1 intercept. Slope
effects relates to the cross-level moderating effects of Job Control on the level-1 Incivility slopes predicting Well-Being. Interaction
term relates to the interaction between Incivility and Coping Success. * p < .05 ** p < .01

175

Table 55: The Mediating Role of Coping Success for the Buffering Effects of Workplace Support on Role Conflict (Hypothesis
10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.72
2.46 32.29
1.94 38.46
1.19 60.39
2.38 31.68
4.65 36.46
Gender
.03
.35
.22
3.45**
.05
.75
-.05 -1.00
-.04
-.69
-.09 -1.28
.02
.46
.09
.99
-.12 -1.25
Children #
.03
.44
-.05
-.68
.11 1.71
Work Hours
.00
-.07
-.08 -1.06
.03
.45
-.01
-.18
.06
1.01
-.03
-.40
*
**
**
Neuroticism
.27
2.55
.13
1.57
.26 3.01
-.01
-.11
-.31 -3.23
-.34 -3.23**
Trait NA
-.01
-.08
.03
.35
.18 1.57
.28 2.66*
.05
.69
-.08
-.73
*
Marital Status
.06
.89
.09
1.02
-.14 -2.26
-.08 -1.97
.04
.50
.20
2.32*
# of Coping Strategies
.02
.29
.06
.80
.05
.72
.05
.77
.02
.34
-.02
-.38
Role Conflict
.04
.90
.39
4.32**
.01
.12
.03
.48
.05
.99
-.07 -1.45
W. Support Main Effects
-.17 -1.98*
-.42 -4.67**
-.16 -2.07*
-.07 -1.31
.10
1.13
.27
3.00**
W. Support Slope Effects
.07
.99
-.07 -1.23
-.07 -1.13
-.12 -1.62
.02
.31
-.01
-.26
**
*
Coping Success
-.17 -3.58
-.04
-.83
-.14 -2.42
-.01
-.09
.03
.60
.04
.84
Interaction Term
.06
.95
.01
.07
.04
.48
.04
.42
-.11 -1.85
.04
.44
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. W. Support = Workplace Support. Main Effects relates to the effect of
Workplace Support on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Workplace Support on the
level-1 Role Conflict slopes predicting Well-Being. Interaction term relates to the interaction between Role Conflict and Coping
Success. * p < .05 ** p < .01

176

Table 56: The Mediating Role of Coping Success for the Buffering Effects of Workplace Support on Workload (Hypothesis
10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.75
2.46 32.97
1.95 38.40
1.20 56.56
2.38 31.84
4.65 36.43
Gender
.01
.16
.23
3.69**
.10 1.52
-.05
-.82
-.12 -1.90
-.10 -1.31
.02
.34
.05
.50
-.14 -1.54
Children #
.07
1.08
-.03
-.51
.13 1.84
Work Hours
.00
-.07
-.11 -1.72
.07 1.36
.00
-.02
.01
.17
-.02
-.27
**
*
**
**
Neuroticism
.27
2.82
.15
2.07
.26 3.07
-.02
-.32
-.28 -2.94
-.30 -2.80**
Trait NA
.02
.24
.03
.36
.25 1.87
.34 2.77**
.03
.45
-.11
-.96
*
Marital Status
.02
.30
.09
1.18
-.14 -2.25
-.07 -1.66
.01
.17
.21
2.56*
# of Coping Strategies
.03
.56
.05
.79
.05
.80
.02
.37
.01
.23
-.03
-.53
Workload
.04
.83
.22
3.72**
.01
.14
.01
.26
.07
1.28
.06
.94
*
**
W. Support Main Effects
-.19 -2.21
-.39 -4.64
-.14 -1.68
-.05
-.86
.13
1.33
.27
3.01**
W. Support Slope Effects
.10
1.47
-.15 -3.40**
-.07
-.88
-.16 -2.05*
.04
.57
-.08 -1.75
**
*
Coping Success
-.16 -3.03
-.08 -1.31
-.13 -2.16
-.02
-.21
.05
.96
.04
.85
Interaction Term
-.05
-.99
.04
1.12
-.08
-.92
.05
.71
.06
.80
.08
1.14
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. W. Support = Workplace Support. Main Effects relates to the effect of
Workplace Support on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Workplace Support on the
level-1 Workload slopes predicting Well-Being. Interaction term relates to the interaction between Workload and Coping Success.
*
p < .05 ** p < .01

177

Table 57: The Mediating Role of Coping Success for the Buffering Effects of Workplace Support on Emotional Demands
(Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.37
2.46 32.88
1.93 39.04
1.19 59.52
2.38 31.50
4.65 36.36
Gender
.05
.75
.27
4.26**
.06
.99
-.06 -1.11
-.03
-.42
-.12 -1.58
.01
.21
.09
.97
-.14 -1.64
Children #
-.01
-.11
-.04
-.66
.12 1.74
Work Hours
.02
.40
-.10 -1.39
.06 1.17
-.01
-.15
.04
.75
-.05
-.63
**
*
**
Neuroticism
.29
2.72
.11
1.38
.23 2.67
-.04
-.52
-.36 -3.85
-.28 -2.67*
Trait NA
.03
.26
.05
.56
.23 1.87
.37 3.08**
.09
1.31
-.12 -1.19
*
*
Marital Status
.08
1.14
.13
1.54
-.14 -2.17
-.09 -2.18
.05
.63
.19
2.35*
# of Coping Strategies
.02
.41
.07
1.06
.05
.82
-.01
-.26
.07
1.05
-.03
-.51
Em. Demands
.15
2.60*
.24
3.69**
.09 1.08
.07 1.27
-.03
-.64
-.06
-.71
W. Support Main Effects
-.15 -1.71
-.41 -4.63
-.15 -1.94
-.04
-.72
.10
1.00
.27
3.04**
W. Support Slope Effects
-.06 -1.26
-.08 -2.03*
-.06
-.96
-.18 -2.80**
-.05
-.96
.02
.75
**
*
Coping Success
-.15 -2.99
-.06
-.99
-.12 -2.05
.00
-.04
.03
.56
.03
.75
**
Interaction Term
.04
.74
.11
2.79
-.01
-.18
-.02
-.53
-.11 -1.96
-.04
-.62
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. Em. Demands = Emotional Demands. W. Support = Workplace Support.Main
Effects relates to the effect of Workplace Support on the level-1 intercept. Slope effects relates to the cross-level moderating effects of
Workplace Support on the level-1 Emotional Demands slopes predicting Well-Being. Interaction term relates to the interaction
between Emotional Demands and Coping Success. * p < .05 ** p < .01

178

Table 58: The Mediating Role of Coping Success for the Buffering Effects of Workplace Support on Interpersonal Conflict
(Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.85 56.54
2.46 33.00
1.95 38.12
1.20 55.40
2.37 31.85
4.66 36.72
Gender
.02
.32
.24
4.10**
.08 1.23
-.06 -1.03
-.07 -1.05
-.12 -1.77
.01
.22
.08
.79
-.14 -1.78
Children #
.04
.69
.02
.29
.12 1.69
Work Hours
.03
.56
-.09
-1.40
.07 1.37
.01
.10
.00
-.04
-.06
-.76
**
**
Neuroticism
.27
2.82
.15
1.79
.23 2.59
-.02
-.36
-.31 -3.21
-.31 -2.95**
Trait NA
.04
.43
.04
.41
.26 1.94
.38 2.66*
.05
.71
-.13 -1.25
*
Marital Status
.04
.54
.06
.76
-.13 -1.99
-.06 -1.43
.03
.34
.22
2.80**
# of Coping Strategies
.01
.23
.02
.32
.02
.38
-.01
-.15
.09
1.35
-.01
-.09
In. Conflict
.15
1.81
.20
2.53*
.10 1.12
.10 1.32
.03
.52
-.13 -1.31
W. Support Main Effects
-.17 -1.99*
-.42
-4.80**
-.15 -1.86
-.03
-.50
.11
1.01
.27
3.05**
W. Support Slope Effects
.11
1.04
-.05
-.60
-.02
-.14
-.01
-.16
-.07 -1.10
-.07 -1.20
**
Coping Success
-.20 -3.48
-.07
-1.23
-.10 -1.62
-.01
-.13
.06
1.02
.03
.60
*
**
Interaction Term
.12
.89
.27
2.46
-.01
-.19
.09
.79
-.38 -3.81
.03
.23
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. In. Conflict = Interpersonal Conflict. W. Support = Workplace Support. Main
Effects relates to the effect of Workplace Support on the level-1 intercept. Slope effects relates to the cross-level moderating effects of
Workplace Support on the level-1 Interpersonal Conflict slopes predicting Well-Being. Interaction term relates to the interaction
between Interpersonal Conflict and Coping Success. * p < .05 ** p < .01

179

Table 59: The Mediating Role of Coping Success for the Buffering Effects of Workplace Support on Incivility (Hypothesis 10).
Experienced
Strain

Emotional
Exhaustion

Affective
Distress

Negative
Affect

Positive
Affect

Life
Satisfaction

γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
γ’
t
Intercept
1.86 57.27
2.46 33.20
1.95 38.32
1.20 54.30
2.38 31.53
4.62 35.50
**
Gender
.06
.84
.24
3.87
.09 1.44
-.04
-.76
-.05
-.74
-.13 -1.83
Children #
.03
.57
-.02
-.29
.12 1.69
-.02
-.37
.05
.51
-.15 -1.82
Work Hours
.01
.23
-.10 -1.48
.06 1.28
-.01
-.10
.02
.31
-.05
-.78
.13
1.68
.22 2.48**
-.04
-.60
-.33 -3.50**
-.29 -2.56*
Neuroticism
.24
2.61*
Trait NA
.06
.62
.03
.40
.27 2.04*
.39 3.00**
.07
1.01
-.12 -1.10
Marital Status
.05
.71
.10
1.18
-.12 -1.91
-.06 -1.30
.03
.34
.18
2.34*
# of Coping Strategies
.01
.21
.04
.56
.02
.29
-.01
-.21
.05
.71
-.02
-.29
*
**
Incivility
.22
2.41
.25
3.86
.14 1.23
.03
.36
-.07 -1.09
-.25 -1.46
W. Support Main Effects
-.20 -2.31*
-.40 -4.74**
-.15 -1.84
-.03
-.41
.11
1.15
.30
3.42**
W. Support Slope Effects
.02
.14
.14
1.94
.06
.33
.05
.42
-.03
-.41
.05
.25
**
Coping Success
-.16 -3.15
-.07 -1.07
-.10 -1.58
.02
.21
.03
.48
.05
.94
Interaction Term
.05
.82
.00
-.08
.03
.63
-.04
-.98
.10
2.44*
-.11
-.44
Notes: N = 514-517. Gender was coded as 1 = male, 2 = female. Children # = Number of Children. Work Hours relates to mean hours
worked per week. Marital Status was coded as 1 = not married, 2 = married. Trait NA = Trait Negative Affect. # of Coping Strategies
= the number of different copings strategies utilized. W. Support = Workplace Support. Main Effects relates to the effect of
Workplace Support on the level-1 intercept. Slope effects relates to the cross-level moderating effects of Workplace Support on the
level-1 Incivility slopes predicting Well-Being. Interaction term relates to the interaction between Incivility and Coping Success.
*
p < .05 ** p < .01

180

APPENDIX B

FIGURES

181

Figure 1: Conceptual Representation of Hypothesized Within Person Relationships

182

Figure 2: Conceptual Representation of Hypothesized Between Person Relationships

183

Figure 3: Measurement of Study Variables

184

Figure 4: The Moderating Effect of Job Control on the Relationship between Emotional
Demands and Emotional Demands Self-Efficacy

100

Emotional Demands
Self-Efficacy

95
90
85
80
75
70
65
60

Low Emotional Demands
Low Control

High Emotional Demands
High Control

Notes: Low Emotional Demands refers to one within-person standard deviation below the
mean on emotional demands. High Emotional Demands refers to one standard within-person
deviation above the mean on Emotional Demands. Low Control refers to one between-person
standard deviation below the mean on Job Control. High Control refers to one between-person
standard deviation above the mean on Job Control.

185

Figure 5: The Moderating Effect of Job Control on the Relationship between Interpersonal
Conflict and Interpersonal Conflict Self-Efficacy

100

Interpersonal Conflict
Self-Efficacy

95
90
85
80
75
70
65
60

Low Interpersonal Conflict
Low Control

High Interpersonal Conflict
High Control

Notes: Low Emotional Demands refers to one within-person standard deviation below the
mean on emotional demands. High Emotional Demands refers to one standard within-person
deviation above the mean on Emotional Demands. Low Control refers to one between-person
standard deviation below the mean on Job Control. High Control refers to one between-person
standard deviation above the mean on Job Control.

186

Figure 6: The Moderating Effect of Workplace Support on the Relationship between
Workload and Emotional Exhaustion

Emotional Exhaustion

3.1

2.7

2.3

1.9

1.5

Low Workload

High Workload

Low Support

High Support

Notes: Low Workload refers to one within-person standard deviation below the mean on
Workload. High Workload refers to one standard within-person deviation above the mean on
Workload. Low Support refers to one between-person standard deviation below the mean on
Workplace Support. High Support refers to one between-person standard deviation above the
mean on Workplace Support.

187

Figure 7: The Moderating Effect of Workplace Support on the Relationship between
Emotional Demands and Emotional Exhaustion

Emotional Exhaustion

3.1

2.7

2.3

1.9

1.5

Low Emotional Demands

High Emotional Demands

Low Support

High Support

Notes: Low Emotional Demands refers to one within-person standard deviation below the
mean on emotional demands. High Emotional Demands refers to one standard within-person
deviation above the mean on Emotional Demands. Low Support refers to one between-person
standard deviation below the mean on Workplace Support. High Support refers to one betweenperson standard deviation above the mean on Workplace Support.

188

Figure 8: The Moderating Effect of Workplace Support on the Relationship between
Incivility and Emotional Exhaustion

Emotional Exhaustion

3.1

2.7

2.3

1.9

1.5

Low Incivility

High Incivility

Low Support

High Support

Notes: Low Incivility refers to one within-person standard deviation below the mean on
Incivility. High Emotional Demands refers to one standard within-person deviation above the
mean on Incivility. Low Support refers to one between-person standard deviation below the
mean on Workplace Support. High Support refers to one between-person standard deviation
above the mean on Workplace Support.

189

Figure 9: The Moderating Effect of Workplace Support on the Relationship between
Workload and Life Satisfaction

4.8

Life Satisfaction

4.4

4

3.6

3.2

Low Workload

High Workload

Low Support

High Support

Notes: Low Workload refers to one within-person standard deviation below the mean on
Workload. High Workload refers to one standard within-person deviation above the mean on
Workload. Low Support refers to one between-person standard deviation below the mean on
Workplace Support. High Support refers to one between-person standard deviation above the
mean on Workplace Support.

190

Figure 10: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Workload and Experienced Strain

2.2

Experienced Strain

2.1

2

1.9

1.8

1.7

1.6

Low Workload

High Workload

High Previous SE

Low Previous SE

Notes: Low Workload refers to one within-person standard deviation below the mean on
Workload. High Workload refers to one standard within-person deviation above the mean on
Workload. High Previous SE refers to one within-person standard deviation above the mean on
Workload Self-Efficacy. Low Previous SE refers to one within-person standard deviation below
the mean on Workload Self-Efficacy.

191

Figure 11: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Workload and Positive Affect

2.5

Positive Affect

2.4

2.3

2.2

2.1

2

Low Workload

High Workload

High Previous SE

Low Previous SE

Notes: Low Workload refers to one within-person standard deviation below the mean on
Workload. High Workload refers to one standard within-person deviation above the mean on
Workload. High Previous SE refers to one within-person standard deviation above the mean on
Workload Self-Efficacy. Low Previous SE refers to one within-person standard deviation below
the mean on Workload Self-Efficacy.

192

Figure 12: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Interpersonal Conflict and Emotional Exhaustion

3.1

Emotional Exhaustion

2.7

2.3

1.9

1.5

Low Interpersonal Conflict
High Previous SE

High Interpersonal Conflict
Low Previous SE

Notes: Low Interpersonal Conflict refers to one within-person standard deviation below
the mean on Interpersonal Conflict. High Interpersonal Conflict refers to one standard withinperson deviation above the mean on Interpersonal Conflict. High Previous SE refers to one
within-person standard deviation above the mean on Interpersonal Conflict Self-Efficacy. Low
Previous SE refers to one within-person standard deviation below the mean on Interpersonal
Conflict Self-Efficacy.

193

Figure 13: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Interpersonal Conflict and Affective Distress

2.1

Affective Distress

2.05

2

1.95

1.9

1.85

1.8

Low Interpersonal Conflict
High Previous SE

High Interpersonal Conflict
Low Previous SE

Notes: Low Interpersonal Conflict refers to one within-person standard deviation below
the mean on Interpersonal Conflict. High Interpersonal Conflict refers to one standard withinperson deviation above the mean on Interpersonal Conflict. High Previous SE refers to one
within-person standard deviation above the mean on Interpersonal Conflict Self-Efficacy. Low
Previous SE refers to one within-person standard deviation below the mean on Interpersonal
Conflict Self-Efficacy.

194

Figure 14: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Interpersonal Conflict and Life Satisfaction

4.8
4.75

Life Satisfaction

4.7
4.65
4.6
4.55
4.5
4.45
4.4

Low Interpersonal Conflict
High Previous SE

High Interpersonal Conflict
Low Previous SE

Notes: Low Interpersonal Conflict refers to one within-person standard deviation below
the mean on Interpersonal Conflict. High Interpersonal Conflict refers to one standard withinperson deviation above the mean on Interpersonal Conflict. High Previous SE refers to one
within-person standard deviation above the mean on Interpersonal Conflict Self-Efficacy. Low
Previous SE refers to one within-person standard deviation below the mean on Interpersonal
Conflict Self-Efficacy.

195

Figure 15: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Incivility and Positive Affect

2.5

Positive Affect

2.4

2.3

2.2

2.1

2

Low Incivility

High Incivility

High Previous SE

Low Previous SE

Notes: Low Incivility refers to one within-person standard deviation below the mean on
Interpersonal Conflict. High Incivility refers to one standard within-person deviation above the
mean on Interpersonal Conflict. High Previous SE refers to one within-person standard deviation
above the mean on Incivility Self-Efficacy. Low Previous SE refers to one within-person
standard deviation below the mean on Incivility Self-Efficacy.

196

Figure 16: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Incivility and Life Satisfaction

4.9

Life Satisfaction

4.8

4.7

4.6

4.5

4.4

4.3

Low Incivility

High Incivility

High Previous SE

Low Previous SE

Notes: Low Incivility refers to one within-person standard deviation below the mean on
Interpersonal Conflict. High Incivility refers to one standard within-person deviation above the
mean on Interpersonal Conflict. High Previous SE refers to one within-person standard deviation
above the mean on Incivility Self-Efficacy. Low Previous SE refers to one within-person
standard deviation below the mean on Incivility Self-Efficacy.

197

Figure 17: The Moderating Effect of Prior Self-Efficacy on the Relationship between
Incivility and Negative Affect

1.3

Negative Affect

1.25

1.2

1.15

1.1

1.05

1

Low Incivility

High Incivility

High Previous SE

Low Previous SE

Notes: Low Incivility refers to one within-person standard deviation below the mean on
Interpersonal Conflict. High Incivility refers to one standard within-person deviation above the
mean on Interpersonal Conflict. High Previous SE refers to one within-person standard deviation
above the mean on Incivility Self-Efficacy. Low Previous SE refers to one within-person
standard deviation below the mean on Incivility Self-Efficacy.

198

Figure 18: The Moderating Effect of Coping Success on the Relationship between
Workload and Workload Self-Efficacy

100

Workload Self-Efficacy

95
90
85
80
75
70
65
60

Low Workload

High Workload

High Coping Success

Low Coping Success

Notes: Low Workload refers to one within-person standard deviation below the mean on
Workload. High Workload refers to one standard within-person deviation above the mean on
Workload. High Coping Success refers to one within-person standard deviation above the mean
on Coping Success. Low Coping Success refers to one within-person standard deviation below
the mean on Coping Success.

199

Figure 19: The Moderating Effect of Coping Success on the Relationship between
Emotional Demands and Emotional Exhaustion

2.6

Emotional Exhaustion

2.5

2.4

2.3

2.2

2.1

Low Emotional Demands

High Emotional Demands

High Coping Success

Low Coping Success

Notes: Low Emotional Demands refers to one within-person standard deviation below the
mean on Emotional Demands. High Emotional Demands refers to one standard within-person
deviation above the mean on Emotional Demands. High Coping Success refers to one withinperson standard deviation above the mean on Coping Success. Low Coping Success refers to one
within-person standard deviation below the mean on Coping Success.

200

Figure 20: The Moderating Effect of Coping Success on the Relationship between
Interpersonal Conflict and Emotional Exhaustion

2.6

Emotional Exhaustion

2.5

2.4

2.3

2.2

2.1

Low Interpersonal Conflict
High Coping Success

High Interpersonal Conflict
Low Coping Success

Notes: Low Interpersonal Conflict refers to one within-person standard deviation below
the mean on Interpersonal Conflict. High Interpersonal Conflict refers to one standard withinperson deviation above the mean on Interpersonal Conflict. High Coping Success refers to one
within-person standard deviation above the mean on Coping Success. Low Coping Success
refers to one within-person standard deviation below the mean on Coping Success.

201

Figure 21: The Moderating Effect of Coping Success on the Relationship between
Interpersonal Conflict and Positive Affect

2.6

Positive Affect

2.5

2.4

2.3

2.2

2.1

2

Low Interpersonal Conflict
High Coping Success

High Interpersonal Conflict
Low Coping Success

Notes: Low Interpersonal Conflict refers to one within-person standard deviation below
the mean on Interpersonal Conflict. High Interpersonal Conflict refers to one standard withinperson deviation above the mean on Interpersonal Conflict. High Coping Success refers to one
within-person standard deviation above the mean on Coping Success. Low Coping Success
refers to one within-person standard deviation below the mean on Coping Success.

202

Figure 22: The Moderating Effect of Coping Success on the Relationship between Incivility
and Positive Affect

2.6

Positive Affect

2.5

2.4

2.3

2.2

2.1

2

Low Incivility

High Incivility

High Coping Success

Low Coping Success

Notes: Low Incivility refers to one within-person standard deviation below the mean on
Incivility. High Incivility refers to one standard within-person deviation above the mean on
Interpersonal Conflict. High Coping Success refers to one within-person standard deviation
above the mean on Coping Success. Low Coping Success refers to one within-person standard
deviation below the mean on Coping Success.

203

APPENDIX C

MEASURES COLLECTED WITH THE 1ST DAILY SURVEY.

204

Work Demands (Janssen, 2001).
Please use a number from this scale to indicate your agreement to the following phrases
that describe your situation at work, as it applies for today:
1
Strongly
Disagree
1.
2.
3.
4.
5.
6.
7.
8.
9.

2

3

4

Disagree

Neutral

Agree

5
Strongly
Agree

I have to work fast.
I have too much work to do.
I have to work extra hard to finish a task.
I have to work under time pressure.
I can do my work in comfort.
I can take my time in doing my work.
I have to deal with a work backlog.
I have problems with the high pace of work.
The workload is high.

Role Conflict (Rizzo et al., 1970).
Please use a number from this scale to indicate your agreement to the following phrases
that describe your situation at work, as it applies for today:
1
Very Slightly or
Not at all
1.
2.
3.
4.
5.
6.
7.
8.

2
Somewhat

3
Moderately

4
Very much

5
Extremely

I have to do things that should be done differently.
I have to work under incompatible policies and guidelines.
I have to buck rules or policies in order to carry out my assignments.
I have to work with two or more groups who operate quite differently.
I received incompatible requests from two or more people.
I do things that are apt to be accepted by one person and not accepted by others.
I work on things that I think are unnecessary.
I have to work under vague directives or instructions.

Emotional Demands (Brotheridge & Lee, 2003).
Please use a number from this scale to indicate your agreement to the following phrases
that describe your situation at work, as it applies for today:
1
Very Slightly or
Not at all

2
Somewhat

3
Moderately

205

4
Very much

5
Extremely
much

1. I have to resist expressing my true feelings.
2. I have to pretend to have emotions I don’t really have.
3. I have to hide my true feelings about a situation.
Interpersonal Conflict (Jehn, 1995).
Please use a number from this scale to indicate your agreement to the following phrases
that describe your interactions with your coworkers, as they apply for today:
1
Very Slightly or
Not at all
1.
2.
3.
4.
5.
6.
7.

2
Somewhat

3
Moderately

4
Very much

5
Extremely
much

There is friction between me and my coworkers.
There are personality conflicts evident between me and my coworkers.
There is emotional conflict between me and my coworkers.
My coworkers and I disagree about opinions regarding the work being done.
There is conflict about ideas between me and my coworkers.
There is conflict between me and my coworkers about the work we do.
There are differences of opinion between me and my coworkers.

Workplace Incivility Scale (Cortina & Weingart, 2001).
Please use a number from this scale to answer the following questions about your
experiences at work today.
1
Very Slightly or
Not at all

2
Somewhat

3
Moderately

4
Very much

5
Extremely

Did any of your superiors or coworkers:
1.
2.
3.
4.
5.
6.
7.

Put you down or was condescending to you?
Paid little attention to your statement or showed little interest in your opinion?
Made demeaning or derogatory remarks about you?
Addressed you in unprofessional terms, either publicly or privately?
Ignored or excluded you from professional camaraderie?
Doubted your judgment on a matter over which you have responsibility?
Made unwanted attempts to draw you into a discussion of personal matters?

206

APPENDIX D

MEASURES COLLECTED WITH THE 2ND DAILY SURVEY.

207

Self-efficacy.
Please use a number from this scale to indicate how confident you feel right now in your
ability to accomplish the following during your daily life.
1

5

10

Cannot do at all

Might be able to do

Perfectly certain I can do

1. Handling the volume of the work.
2. Dealing with the pace of the workday.
3. Successfully completing the tasks I have to perform.
4. Displaying the emotions I have to display as part of my work duties.
5. Regulating my emotional expressions in order to complete my work.
6. Keeping my true feelings hidden.
7. Dealing with contradicting instructions.
8. Juggling conflicting guidelines or policies.
9. Successfully fulfilling non-compatible responsibilities.
10. Resolving conflicts about the work at hand.
11. Resolving personality conflicts between you and your coworkers.
12. Handling frictions in the workplace.
13. Managing others’ unprofessional behavior in the workplace.
14. Dealing with uncivil situations.
15. Handling others’ potentially offensive comments and remarks.

Coping Efforts (Carver et al., 1986).
Please indicate whether you performed the following actions today when trying to deal with
any problems, obstacles, and challenges in your workplace.
1

2

Did not do

Did

1. I asked people who have had similar experiences what they did.
2. I tried to get advice from someone about what to do.
3. I talked to someone to find out more about the situation.
4. I talked to someone who could do something concrete about the problem.
5. I talked to someone about how I feel.
6. I tried to get emotional support from coworkers or my supervisor.
7. I discussed my feelings with someone.
8. I got sympathy and understanding from someone.
9. I took additional action to try to get rid of any problems.
10. I concentrated my efforts on doing something about the work issues.
11. I did what had to be done, one step at a time.
208

12. I took direct action to get around any problems.
13. I tried to come up with a strategy about what to do.
14. I made a plan of action.
15. I thought hard about what steps to take.
16. I thought about how I might best handle the problem.
17. I put aside other activities in order to concentrate on the issues at hand.
18. I focused on dealing with the current problems, and if necessary let other things slide a
little.
19. I kept myself from getting distracted by other thoughts or activities.
20. I tried hard to prevent other things from interfering with my efforts.

Coping Success.
Please use a number from the scale below to indicate how successful the actions described
above were in helping you deal with the demands of your workplace today.
1

2

3

4

5

Not at all
successful

Somewhat
successful

Moderately
successful

Very
successful

Extremely
Successful

1. Coping Action #1.
2. Coping Action #2.
3. Coping Action #3.
4. Coping Action #4.
5. Coping Action #5.
6. Coping Action #6.
7. Coping Action #7.
8. Coping Action #8.
9. Coping Action #9.
10. Coping Action #10.
11. Coping Action #11.

209

APPENDIX E

MEASURES COLLECTED WITH THE 3RD DAILY SURVEY.

210

Positive and Negative Affect (Watson & Clark, 1994).
Using this scale, rate the following items below as to how you feel right now.
1

2

3

4

5

Very Slightly or
Not at all

Somewhat

Moderately

Very much

Extremely
much

1.
2.
3.
4.
5.

Interested
Distressed
Excited
Upset
Strong

6.
7.
8.
9.
10.

Guilty
Scared
Hostile
Enthusiastic
Proud

11.
12.
13.
14.
15.

Irritable
Alert
Ashamed
Inspired
Nervous

16.
17.
18.
19.
20.

Determined
Attentive
Jittery
Active
Afraid

Satisfaction with Life Scale (Diener et al., 1985).
Below are five statements with which you may agree or disagree. Using the 1-7 scale below,
please indicate your agreement to the following statements, as they apply right now. Please
be open and honest in your responding.
1
Strongly
Disagree
1.
2.
3.
4.
5.

2
Disagree

3
Slightly
Disagree

4
Neutral

5
Slightly
Agree

6
Agree

7
Strongly
Agree

At this point, in most ways my life is close to my ideal.
Currently, the conditions of my life are excellent.
At this time, I am satisfied with my life.
At this point, I have the important things I want in life.
Right now, I feel that if I could live my life over, I would change almost nothing.

Affective Distress (Mackay et al., 1978).
Please use a number from this scale to indicate the extent to which each adjective describes
your mood right now. There are no right or wrong answers; please respond honestly and
openly, about your mood at the present moment.
1

2

3

4

5

Very Slightly or
Not at all

Somewhat

Moderately

Very much

Extremely
much

1. Calm
2. Contented
3. Comfortable

4. Uneasy
5. Worried
6. Uptight
211

7. Tense
8. Relaxed
9. Bothered

General Health Questionnaire (Goldberg, 1992).
Please read the questions below and each of the four possible answers, as they apply for
today. Choose the response that best applies to you.
1

3

4

Not at all

1.
2.
3.
4.
5.
6.
7.
8.

2
Less than usual

Same as usual

More than usual

Have you been able to concentrate on what you’re doing?
Have you felt that you are playing a useful part in things?
Have you felt capable of making decisions about things?
Did you feel constantly under strain?
Have you been able to enjoy your normal activities?
Were you feeling unhappy or depressed?
Have you been thinking of yourself as a worthless person?
Were feeling reasonably happy, all things considered?

Emotional exhaustion scale (Maslach & Jackson, 1981).
Please indicate your agreement to the following statements, as they apply for right now:
1
Strongly
Disagree
1.
2.
3.
4.
5.
6.
7.
8.
9.

2

3

4

Disagree

Neutral

Agree

5
Strongly
Agree

I feel emotionally drained from my work.
I feel used up at the end of the workday.
I feel fatigued when I get up in the morning and have to face another day on the job.
Working with people all day is really a strain for me.
I feel burned out from my work.
I feel frustrated by my job.
I feel I’m working too hard on my job.
Working with people directly put too much stress on me.
I feel like I’m at the end of my rope.

Work environment changes and catastrophic events.
Below, please summarize any important events that occurred at your work environment in
the last two weeks. Please include events that related to either you or your coworkers (for
example, include any downsizing, promotions, turnover, important health issues and so
on).
Event #1: ________________________________________
Event #2: ________________________________________
Event #3: ________________________________________
212

APPENDIX F

MEASURES COLLECTED ONCE AT THE BEGINNING OF THE STUDY.

213

Perceived social support (Zimet et al., 1990).
Please indicate your agreement with the following statements, using the scale below:
1
Strongly
Disagree

2

3

4

5

Disagree

Neutral

Agree

Strongly Agree

1. My coworkers really care about my feelings.
2. I can count on my coworkers when things go wrong.
3. I get the emotional help and support I need from my coworkers.
4. My coworkers are a real source of comfort to me.
5. My coworkers really try to help me.
6. I can talk about my problems with my coworkers.
7. My supervisors really care about my feelings.
8. I can count on my supervisor when things go wrong.
9. I get the emotional help and support I need from my supervisor.
10. My supervisor is a real source of comfort to me.
11. My supervisor really tries to help me.
12. I can talk about my problems with my supervisor.

Decision Latitude (Karasek et al., 1998).
Please indicate your agreement with the following statements, using the scale below:
1
Strongly
Disagree
1.
2.
3.
4.
5.
6.
7.
8.
9.

2

3

4

5

Disagree

Neutral

Agree

Strongly Agree

My job requires that I learn new things
My job involves a lot of repetitive work
My job requires me to be creative
My job allows me to make a lot of decisions on my own
My job requires a high level of skill
On my job, I have very little freedom to decide how I work
I get to do a variety of different things on my job
I have a lot of say about what happens on my job
I have an opportunity to develop my own special abilities

214

Perceived organizational support. (Eisenberger et al., 1986).
Please indicate your agreement with the following statements, using the scale below:
1
Strongly
Disagree
1.
2.
3.
4.
5.
6.
7.
8.

2

3

4

5

Disagree

Neutral

Agree

Strongly Agree

The organization values my contribution to its well-being.
The organization fails to appreciate any extra effort from me (reverse coded).
The organization would ignore any complaint from me (reverse coded).
The organization really cares about my well-being.
Even if I did the best job possible, the organization would fail to notice (reverse coded).
The organization cares about my general satisfaction at work.
The organization shows very little concern for me (reverse coded).
The organization takes pride in my accomplishments at work.

Negative Affectivity (Watson & Clark, 1994).
Using this scale, rate the following items below as to how you feel in general.
1
Very Slightly or
Not at all
1.
2.
3.
4.
5.

2
Somewhat

3
Moderately

Distressed
Upset
Guilty
Scared
Hostile

4
Very much

5
Extremely
much

6. Irritable
7. Ashamed
8. Nervous
9. Jittery
10. Afraid

Neuroticism (Goldberg et al., 2006).
Please indicate your agreement with the following statements, using the scale below:
1
Strongly
Disagree
1.
2.
3.
4.
5.

2

3

4

5

Disagree

Neutral

Agree

Strongly Agree

I often feel blue.
I dislike myself.
I am often down in the dumps.
I have frequent mood swings.
I panic easily.

6. I rarely get irritated.
7. I seldom feel blue.
8. I feel comfortable with myself.
9. I am not easily bothered by things.
10. I am very pleased with myself.

215

APPENDIX G

SUMMARY OF HYPOTHESES

216

Hypothesis 1a: Higher levels of daily work demands will be associated with lower levels of
subjective well-being.
Hypothesis 1b: More negative social experiences at work will be associated with lower levels of
subjective well-being.
Hypothesis 2a: Higher levels of daily work demands will be associated with lower levels of selfefficacy.
Hypothesis 2b: More negative social experiences at work will be associated with lower levels of
self-efficacy.
Hypothesis 3a: Higher levels of available workplace resources will be associated with higher
average levels of subjective well-being.
Hypothesis 3b: Higher levels of available workplace resources will be associated with higher
average levels of self-efficacy beliefs.
Hypothesis 4: Increased self-efficacy beliefs at the end of the workday will be associated with
increased subjective well-being.
Hypothesis 5: Self-efficacy beliefs will partially mediate the effects of (a) workplace demands,
(b) negative social experiences, and (c) workplace resources on subjective well-being levels.
Hypothesis 6: Workplace resources will moderate the relationships of workplace demands and
negative social experiences to (a) self-efficacy and (b) subjective well-being, such that the
negative effects of work demands and negative social experiences will be weaker for individuals
reporting having higher levels of available workplace resources, compared to individuals
reporting having lower levels of available resources.

217

Hypothesis 7: Previously formed levels of self-efficacy beliefs will moderate the relationship
between workplace demands and negative social experiences and (a) self-efficacy beliefs and (b)
subjective well-being levels, such that these relationships will be weaker on days in which
individuals encounter these events after experiencing high levels of prior self-efficacy, compared
to days in which individuals encounter these events after experiencing low levels of prior selfefficacy.
Hypothesis 8: The degree of reported success in coping with workplace demands and negative
social experiences will moderate the relationship of these demands and experiences to (a) selfefficacy beliefs and (b) subjective well-being levels, such that workplace demands and
experiences will be positively associated with self-efficacy beliefs and subjective well-being on
days in which individuals report higher levels of coping success, but negatively associated on
days in which individuals report lower levels of coping success.
Hypothesis 9: Coping success will mediate the moderating effects of (a) available workplace
resources and (b) previous levels of self-efficacy on the relationship between work demands and
negative social experiences and self-efficacy beliefs.
Hypothesis 10: Coping success will mediate the moderating effects of (a) available workplace
resources and (b) previous levels of self-efficacy on the relationship between work demands and
negative social experiences and subjective well-being levels.

218

REFERENCES

219

REFERENCES

Adams, G. A., & Jex, S. M. (1999). Relationships between time management, control, workfamily conflict and strain. Journal of Occupational Health Psychology, 4, 72-77.
Affleck, G., Tennen, H., Urrows, S., & Higgins, P. (1994). Person and contextual features of
daily stress reactivity: Individual differences in relations of undesirable daily events with
mood disturbance and chronic pain intensity. Journal of Personality and Social
Psychology, 66, 329-340.
Aryee, S., Luk, V., Leung, A., & Lo, S. (1999). Role stressors, interrole conflict, and well-being:
The moderating influence of spousal support and coping behaviors among employed
parents in Hong Kong. Journal of Vocational Behavior, 54, 259-278.
Axelrod, W. L., & Gavin, J. F. (1980). Stress and strain in blue-collar and white-collar
management staff. Journal of Vocational Behavior, 17, 41-49.
Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice Hall.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122147.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.
Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (1997). Self-efficacy: The exercise of control, New York, NY: Freeman.
Bandura, A. (2000). Cultivate self-efficacy for personal and organizational effectiveness. In:
E.A. Locke, (Ed.), The Blackwell Handbook of Principles of Organizational Behavior.
(pp. 120-136). Oxford, UK: Blackwell.
Bandura, A. (2006). Self-efficacy beliefs of adolescents. Greenwich, CT: Information Age
Publishing.
Bandura, A., & Cervone, D. (1986). Differential engagement of self-reactive influences in
cognitive motivation. Organizational Behavior and Human Decision Processes, 38, 92113.
Bandura, A., Taylor, C. B., Williams, S. L., Mefford, I. N., & Barchas, J. D. (1985).
Catecholamine secretion as a function of perceived coping self-efficacy. Journal of
Consulting and Clinical Psychology, 53, 406-414.
Bandura, A., & Wood, R. (1989). Effect of perceived controllability and performance standards
on self-regulation of complex decision making. Journal of Personality and Social
Psychology, 56, 805-814.

220

Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art.
Journal of Managerial Psychology, 22, 309-328.
Bakker, A. B., Demerouti, E., & Euwema, M. C. (2005). Job resources buffer the impact of job
demands on burnout. Journal of Occupational Health Psychology, 10, 170-180.
Bakker, A., B., van Veldhoven, M., & Xanthopoulou, D. (2010). Beyond the demands-control
model: Thriving on high job demands and resources. Journal of Personnel Psychology, 9,
3-16.
Baron, R. A. (1988). Negative effects of destructive criticism: Impact on conflict, self-efficacy,
and task performance. Journal of Applied Psychology, 73, 199-207.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social
psychological research: Conceptual, strategic and statistical considerations. Journal of
Personality and Social Psychology, 51, 1173-1182.
Baumeister, R., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments
as a fundamental human motivation. Psychological Bulletin, 117, 497-529.
Beal, D. J., Weiss, H. M., Barros, E., & MacDermid, S. M. (2005). An episodic process model of
affective influences on performance. Journal of Applied Psychology, 90, 1054-1068.
Bedeian, A. G., & Armenakis, A. A. (1981). A path-analytic study of the consequences of role
conflict and ambiguity. Academy of Management Journal, 24, 417-424.
Ben-Zur, H. (2009). Coping styles and affect. International Journal of Stress Management, 16,
87-101.
Bishop, G. D., Enkelmann, H. C., Tong, E. M. W., Why, Y. P., Diong, S. M., Ang, J., & Khader,
M. (2003). Job demands, decisional control, and cardiovascular responses. Journal of
Occupational Health Psychology, 2, 146-156.
Black, A. E., & Deci, E. L. (2000). The effects of instructors' autonomy support and students'
autonomous motivation on learning organic chemistry: A self-determination theory
perspective. Science Education, 84, 740-756.
Bortner, R. W., & Hultsch, D. F. (1970). A multivariate analysis of correlates of life satisfaction
in adulthood. Journal of Gerontology, 25, 41-47.
Bourbonnais, R., Comeau, M., & Vézina, M. (1999). Job strain and evolution of mental health
among nurses. Journal of Occupational Health Psychology, 4, 95-107.
Brotheridge, C. M., & Grandey, A. A. (2002). Emotional labor and burnout: Comparing two
perspectives of “people work”. Journal of Vocational Behavior, 60, 17-39.
Brotheridge, C. M., & Lee, R. T. (2003). Development and validation of an emotional labor
scale. Journal of Occupational and Organizational Psychology, 76, 365-379.
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data
analysis methods. Newbury Park, CA: Sage Publications.
Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life:
Perceptions, evaluations, and satisfactions. New York, NY: Russell Sage Foundation.

221

Canivet, C., Östergren, P., Lindeberg, S. I., Choi, B., Karasek, R., Moghaddassi, M., & Isacsson,
S. (2010). Conflict between the work and family domains and exhaustion among
vocationally active men and women, Social Science & Medicine, 70, 1237-1245
Carver, C. S., Scheier, M. F., & Weintraub, J. K. (1989). Assessing coping strategies: A
theoretically based approach. Journal of Personality and Social Psychology, 56, 267-283.
Chen, G., Gully, S. M., & Eden, D. (2001). Validation of a new generalized self-efficacy scale.
Organizational Research Methods, 4, 62-83.
Cieslak, R., Benight, C. C., & Lehman, V. C. (2008). Coping self-efficacy mediates the effects of
negative cognitions on posttraumatic distress. Behaviour Research and Therapy, 46, 788798.
Clark, L. A., & Watson, D. (1988). Mood and the mundane: Relations between daily life events
and self-reported mood. Journal of Personality and Social Psychology, 54, 296-308.
Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis.
Psychological Bulletin, 98, 310-357.
Conard, M. A., & Matthews, R. A. (2008). Modeling the stress process: Personality eclipses
dysfunctional cognitions and workload in predicting stress. Personality and Individual
Differences, 44, 171-181.
Cooper, C. L., Dewe, P. J., & O'Driscoll, M. P. (2001). Organizational Stress: A Review and
Critique of Theory, Research, and Applications. Thousand Oaks, CA: Sage.
Cortina, L. M., Magley, V. J., Williams, J. H., & Langhout, R. D. (2001). Incivility in the
workplace: Incidence and impact. Journal of Occupational Health Psychology, 6, 64-80.
Coverman, S. (1989). Role overload, role conflict, and stress: Addressing consequences of
multiple role demands. Social Forces, 67, 965-982.
Creed, P. A., Lehmann, K., & Hood, M. (2009). The relationship between core self-evaluations,
employment commitment and well-being in the unemployed. Personality and Individual
Differences, 47, 310-315.
Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York, NY:
Harper and Row.
Daniels, K., & Guppy, A. (1994). Occupational stress, social support, job control, and
psychological well-being. Human Relations, 47, 1523-1544.
De Croon, E. M., Sluiter, J. K., Blonk, R. W. B., Broersen, J. P. J., & Frings-Dresen, M. H. W.
(2004). Stressful work, psychological job strain, and turnover: A 2-year prospective
cohort study of truck drivers. Journal of Applied Psychology, 89, 442-454.
De Cuyper, N., & De Witte, H. (2006). Autonomy and workload among temporary workers:
Their effects on job satisfaction, organizational commitment, life satisfaction and selfrated performance. International Journal of Stress Management, 13, 441-469.
De Dreu, C. K. W., & Weingart, L. R. (2003). Task versus relationship conflict, team
performance, and team member satisfaction: A meta-analysis. Journal of Applied
Psychology, 88, 741-749.
222

De Jonge, J., Dormann, C., Jannsen, P. P. M., Dollard, M. F., Landeweerd, J. A., & Nijhuis, F. J.
N. (2001). Testing reciprocal relationships between job characteristics and psychological
well-being: A cross lagged structural equation model. Journal of Occupational and
Organizational Psychology, 74, 29-46.
De Jonge, J., & Kompier, M. A. J. (1997). A critical examination of the demand-control-support
model from a work psychological perspective. International Journal of Stress
Management, 4, 235-258.
De Jonge, J., Mulder, M. J. G. P., & Nijhuis, F. J. N. (1999). The incorporation of different
demands concepts in the job demands-control model: Effects on health care
professionals. Social Science and Medicine, 48, 1149-1160.
De Lange, A. H., Taris, T. W., Kompier, M. A., Houtman, I. L., & Bongers, P. M. (2003). “The
very best of the millennium": Longitudinal research and the demand-control-(support)
model. Journal of Occupational Health Psychology, 8, 282-305.
Deci, E. L., & Ryan, R. M. (1995). Human autonomy: The basis for true self-esteem. In M.
Kernis (Ed.), Efficacy, agency, and self-esteem (pp. 31-49). New York: Plenum
Publishing Co.
DeLongis, A., Folkman, S., & Lazarus, R. S. (1988). The impact of daily stress on health and
mood: Psychological and social resources as mediators. Journal of Personality and Social
Psychology, 54, 486-495.
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demandsresources model of burnout. Journal of Applied Psychology, 86, 499-512.
Deneve, K. M., & Cooper, H. (1998). The happy personality: A meta-analysis of 137 personality
traits and subjective well-being. Psychological Bulletin, 124, 197-229.
Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542-575.
Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale.
Journal of Personality Assessment, 49, 71-75.
Diener, E., Oishi, S., & Lucas, R. E. (2003). Personality, culture, and subjective well-being:
Emotional and cognitive evaluations of life. Annual Review of Psychology, 54, 403-425.
Diener, E., Suh, M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades
of progress. Psychological Bulletin, 125, 276-302.
Dimotakis, N., Ilies, R., & Judge, T. A. (in press). Experience Sampling Methodology. In R.
Landis and J. M. Cortina (eds.), Frontiers of Methodology in Organizational Research.
Dimotakis, N., Ilies, R., & Mount, M. (2008). Intentional Negative Behaviors at Work. In J.
Martocchio, H. Liao & A. Joshi (eds.), Research in Personnel and Human Resources
Management, 27 (pp. 247-277). Bingley, UK: Emerald Group Publishing
Dimotakis, N., Scott, B. A. and Koopman, J. (2011). An experience sampling investigation of
workplace interactions, affective states, and employee well-being. Journal of
Organizational Behavior, 32, 572–588.
Dwyer, D. J., & Ganster, D. C. (2006). The effects of job demands and control on employee
attendance and satisfaction. Journal of Organizational Behavior, 12, 595-608.
223

Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. (1986). Perceived organizational
support. Journal of Applied Psychology, 71, 500-507.
Elfering, A., Grebner, S., Semmer, N. K., Kaiser-Freiburghaus, D., Lauper-Del Ponte, S., &
Witschi, I. (2005). Chronic job stressors and job control: Effects on event-related coping
success and well-being. Journal of Occupational and Organizational Psychology, 78,
237-252.
Elovainio, M., Kivimäki, M., Ek, E., Vahtera, J., Honkonen, T., Taanila, A., Veijola, J., &
Järvelin, M. R. (2007). The effect of pre-employment factors on job control, job strain
and psychological distress: A 31-year longitudinal study. Social Science & Medicine, 65,
187-199.
Elsass, P. M., & Veiga, J. F. (1997). Job control and job strain: A test of three models. Journal of
Occupational Health Psychology, 2, 195-211.
Evers, W. J., Brouwers, A., & Tomic, W. (2002). Burnout and self-efficacy: A study of teachers’
beliefs when implementing an innovative educational system in the Netherlands. British
Journal of Educational Psychology, 72, 227-243.
Faragher, E. B., Cass, M., & Cooper, C. L. (2005). The relationship between job satisfaction and
health: a meta-analysis. Occupational and Environmental Medicine, 62, 105-112.
Fillion, L., Tremblay, I., Truchon, M., Côté, D., Struthers, C. W., & Depuis, R. (2007). Nurses
providing palliative care: Empirical evidence for an integrative occupational stressmodel. International Journal of Stress Management, 14, 1-25.
Fischer, C. D., & Gitelson, R. (1983). A meta-analysis of the correlates of role conflict and
ambiguity. Journal of Applied Psychology, 68, 320-333.
Fiske, S. T., & Taylor, S. E. (1984). Social cognition. Reading, MA: Addison-Wesley.
Folkman, S., Lazarus, R. S., Gruen, R., & DeLongis, A. (1986). Appraisal, coping, health status,
and psychological symptoms. Journal of Personality and Social Psychology, 50, 571579.
French, J. R., Caplan, R. D., & Harrison, R. V. (1982). The mechanisms of job stress and strain.
Chichester, England: Wiley.
Frese, M. (1999). Social support as a moderator of the relationship between work stressors and
psychological dysfunctioning: A longitudinal study with objective measures. Journal of
Occupational Health Psychology, 4, 179-192.
Fried, Y., & Tiegs, R. B. (1993). The main effect model versus buffering model of shop steward
social support: A study of rank-and-file auto workers in the U.S.A. Journal of
Organizational Behavior, 14, 481-493.
Fritz, C., & Sonnentag, S. (2006). Recovery, well-being, and performance-related outcomes: The
role of work load and vacation experiences. Journal of Applied Psychology, 91, 936-945.
Frone, M. R. (2000). Interpersonal conflict at work and psychological outcomes: Testing a model
among young workers. Journal of Occupational Health Psychology, 5, 246-255.
Ganster, D. C., Fusilier, M. R., & Mayes, B. T. (1986). Role of social support in the experience
of stress at work. Journal of Applied Psychology, 71, 102-110.
224

Ganster, D. C., & Schaubroeck, J. (1991). Work stress and employee health. Journal of
Management, 17, 235-271.
Gecas, V. (1989). The social psychology of self-efficacy. Annual Review of Sociology, 15, 291316.
Geurts, S. A. E., Kompier, M. A. J., Roxburgh, S., & Houtman, I. L. D. (2003). Does work-home
interference mediate the relationship between workload and well-being? Journal of
Vocational Behavior, 63, 532-559.
Goldberg, D. (1992). General Health Questionnaire (GHQ-12). Windsor, United Kingdom:
NFER-Nelson.
Goldberg, L. R., Johnson, J. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., &
Gough, H. C. (2006). The international personality item pool and the future of publicdomain personality measures. Journal of Research in Personality, 40, 84-96.
Grandey, A. A. (2000). Emotion regulation in the workplace: A new way to conceptualize
emotional labor. Journal of Occupational Health Psychology, 5, 95-110.
Greenglass, E. R., & Fiksenbaum, L. (2009). Proactive coping, positive affect, and well-being:
Testing for mediation using path analysis. European Psychologist, 14, 29-39.
Greenhaus, J. H., Bedeian, A. G., & Mossholder, K. W. (1987). Work experiences, job
performance, and feelings of personal and family well-being. Journal of Vocational
Behavior, 31, 200-215.
Hamner, W. C., & Tosi, H. L. (1974). Relationship of role conflict and role ambiguity to job
involvement measures. Journal of Applied Psychology, 59, 497-499.
Harter, J. K., Schmidt, F. L., & Keyes, C. L. M. (2003). Well-being in the workplace and its
relationship to business outcomes: A review of the Gallup studies. In C. L. M. Keyes & J.
Haidt, (Eds.). Flourishing: The Positive Person and the Good Life, (pp. 205-224).
Washington, DC: American Psychological Association.
Harvey, S., Blouin, C., & Stout, D. (2006). Proactive personality as a moderator of outcomes for
young workers experiencing conflict at work. Personality and Individual Differences, 40,
1063-1074.
Hecht, T. D., & Allen, N. J. (2005). Exploring links between polychronicity and well-being
from the perspective of person-job fit: Does it matter if you prefer to do only one thing at
a time? Organizational Behavior and Human Decision Processes, 98, 155-178.
Heller, D., Watson, D., & Ilies, R. (2004). The role of person vs. situation in life satisfaction: A
critical examination. Psychological Bulletin, 130, 574-600.
Heller, D., Watson, D., & Ilies, R. (2006). The dynamic process of life satisfaction. Journal of
Personality, 74, 1421-1450.
Heuven, E., Bakker, A. B., Schaufeli, W. B., & Huisman, N. (2006). The role of self-efficacy in
performing emotion work. Journal of Vocational Behavior, 69, 222-235.
Hofboll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress.
American Psychologist, 44, 513-524.
225

Holahan, C. K., Holahan, C. J., & Belk, S. (1984). Adjustment in aging: The roles of life stress,
hassles, and self-efficacy. Health Psychology, 3, 315-328.
Holman, D. J., & Wall, T. D. (2002). Work characteristics, learning-related outcomes, and strain:
A test of competing direct effects, mediated, and moderated models. Journal of
Occupational Health Psychology, 7, 283-301.
House, G. S. (1981). Work stress and social support. Reading, MA: Addison-Wesley.
Ilies, R., Dimotakis, N., & De Pater, I. E. (2010). Psychological and physiological reactions to
high workloads: Implications for well-being. Personnel Psychology, 63, 407-436.
Ilies, R., Dimotakis, N., & Wang, L. (2010). Job demands and strain: persistent effects and
moderating processes. Part of the symposium: Job Demands and Worker Well-Being, J.
Diefendorff, & A. Gabriel (Chairs), presented at the 2010 Society for Industrial and
Organizational Psychology National Conference, Atlanta, GA.
Ilies, R., Johnson, M. D., Judge, T. A. and Keeney, J. (2011). A within-individual study of
interpersonal conflict as a work stressor: Dispositional and situational moderators.
Journal of Organizational Behavior, 32, 44-64.
Ilies, R., Keeney, J., & Scott, B. A. (2011) Work-family interpersonal capitalization: Sharing
positive work events at home. Organizational Behavior and Human Decision Processes,
114, 115-126
Ilies, R., Schwind, K. M., Wagner, D. T., Johnson, M. D., DeRue, D. S., & Ilgen, D. R. (2007).
When can employees have a family life? The effects of daily workload and affect on
work-family conflict and social behaviors at home. Journal of Applied Psychology, 92,
1368-1379.
Ippolito, J., Adler, A. B., Thomas, J. L., Litz, B., & Hölzl, R. (2005). Extending and applying the
demand-control model: The role of soldier’s coping on a peacekeeping deployment.
Journal of Occupational Health Psychology, 10, 452-464.
Izard, C. E. (1993). Four systems for emotion activation: Cognitive and non-cognitive processes.
Psychological Review, 100, 60-69.
Jannsen, P. P. M. (2001). Fairness perceptions as a moderator in the curvilinear relationships
between job demands, and job performance and job satisfaction. Academy of
Management Journal, 44, 1039-1050.
Jannsen, P. P. M., Peeters, M. C. W., de Jonge, J., Houkes, I., Tummers, G. E. R. (2004).
Specific relationships between job demands, job resources and psychological outcomes
and the mediating role of negative work-home interference. Journal of Vocational
Behavior, 65, 411-429.
Jehn, K. A. (1995). A multimethod examination of the benefits and detriments of intragroup
conflict. Administrative Science Quarterly, 40, 256-282.
Jex, S. M., & Bliese, P. D. (1999). Efficacy beliefs as a moderator of the impact of work-related
stressors: A multilevel study. Journal of Applied Psychology, 84, 349-361.

226

Jex, S. M., Bliese, P. D., Buzzell, S., & Primeau, J. (2001). The impact of self-efficacy on
stressor-strain relations: Coping style as an exploratory mechanism. Journal of Applied
Psychology, 86, 401-409.
Jex, S. M., & Gudanowski, D. (1992). Efficacy beliefs and work stress: An exploratory study.
Journal of Organizational Behavior, 13, 509-517.
Jimmieson, N. L., Terry, D. J., & Callan, V. J. (2004). A longitudinal study of employee
adaptation to organizational change: The role of change-related information and changerelated self-efficacy. Journal of Occupational Health Psychology, 9, 11-27.
Jin, P., Yeung, A. S., Tang, T. O., & Low, R. (2008). Identifying teachers at risk in Hong Kong:
Psychosomatic symptoms and sources of stress. Journal of Psychosomatic Research, 65,
357-362.
Johnson, J. V., & Hall, E. M. (1988). Job strain, work place social support, and cardiovascular
disease: A cross-sectional study of a random sample of the Swedish working population.
American Journal of Public Health, 78, 1336-1342.
Judge, T. A., Heller, D., & Mount, M. K. (2002). Five-factor model of personality and job
satisfaction: A meta-analysis. Journal of Applied Psychology, 87, 530-541.
Judge, T. A., Ilies, R., & Dimotakis, N. (2010). Are health and happiness the product of wisdom?
The relationship of general mental ability to educational and occupational attainment,
health, and well-being. Journal of Applied Psychology, 95, 454-468.
Judge, T. A., Jackson, C., Shaw, J. C., Scott, B. A., & Rich, B. L. (2007). Self-efficacy and
work-related performance: The integral role of individual differences. Journal of Applied
Psychology, 92, 107-127.
Judge, T. A., & Klinger, R. (2007). Job satisfaction: Subjective well-being at work. In M. Eid &
R. Larsen (Eds.), The Science of Subjective Well-Being (pp. 393-413). New York, NY:
Guilford Publications.
Kamarck, T. W., Shiffman, S. M, Smithline, L., Goodie, J. L., Paty, J. A., Gnys, M., & Jong, J.
Y. K. (1998). Effects of task strain, social conflict and emotional activation on
ambulatory cardiovascular activity: Daily life consequences of recruiting stress in a
multiethnic adult sample. Health Psychology, 17, 17-29.
Karademas, E. C. (2006). Self-efficacy, social support and well-being: The mediating role of
optimism. Personality and Individual Differences, 40, 1281-1290.
Karademas, E. C. (2007). Positive and negative aspects of well-being: Common and specific
predictors. Personality and Individual Differences, 43, 277-287.
Karademas, E. C., Kafetsios, K., & Sideridis, G. D. (2007). Optimism, self-efficacy and
information processing of threat- and well-being-related stimuli. Stress and Health, 23,
285-294.
Karasek, R. (1979). Job demands, job decision latitude, and mental strain: Implications for job
redesign. Administrative Science Quarterly, 24, 285-308.
Karasek, R., Brisson, C., Kawakami, N., Houtman, I., Bongers, P., & Amick, B. (1998). The Job
Content Questionnaire (JCQ): An instrument for internationally comparative assessments
227

of psychosocial job characteristics. Journal of Occupational Health Psychology, 3, 322355.
Karasek, R., Gardell, B., & Lindell, J. (1987). Work and non-work correlates of illness and
behaviour in male and female Swedish white-collar workers. Journal of Organizational
Behavior, 8, 187-207.
Karasek, R., & Theorell, T. (1990). Healthy work: Stress, productivity and the reconstruction of
working life. New York, NY: Basic Books.
Karasek, R., Triantis, K. P., & Chaudry, S. S. (1982). Coworker and supervisor support as
moderators of associations between task characteristics and mental strain. Journal of
Occupational Behavior, 3, 181-200.
Kohn, P. M., Hay, B. D., & Legere, J. J. (1994). Hassles, coping style, and negative well-being.
Personality and Individual Differences, 17, 169-179.
La Rocco, J. M., & Jones, A. P. (1978). Co-worker and leader support as moderators of stressstrain relationships in work situations. Journal of Applied Psychology, 63, 629-634.
Landsbergis, P. A. (1988). Occupational stress among health care workers: A test of the job
demands-control model. Journal of Organizational Behavior, 9, 217-239.
Lang, J., Thomas, J. L., Bliese, P. D., & Adler, A. B. (2007). Job demands and job performance:
The mediating effect of psychological and physical strain and the moderating effect of
role clarity. Journal of Occupational Health Psychology, 12, 116-124.
Lazarus, R. S. (1999). Stress and emotion: A new synthesis. New York, NY: Springer.
Lazarus, R. S., & Folkman, S. (1984). Stress, Appraisal, and Coping. New York, NY: Springer.
Lazuras, L., Rodafinos, A., Matsiggos, G., & Stamatoulakis, A. (2009). Perceived occupational
stress, affective, and physical well-being among telecommunication employees in
Greece. Social Science & Medicine, 6, 1075-1081.
Lee, R. T., & Ashforth, B. E. (1996). A meta-analytic examination of the correlates of the three
dimensions of burnout. Journal of Applied Psychology, 81, 123-133.
Lim, S., & Cortina, L. M. (2005). Interpersonal mistreatment in the workplace: The interface and
impact of general incivility and sexual harassment. Journal of Applied Psychology, 90,
483-496.
Lim, S., Cortina, L. M., & Magley, V. J. (2008). Personal and workgroup incivility: Impact on
work and health outcomes. Journal of Applied Psychology, 93, 95-107.
Lincoln, K. D. (2008). Personality, negative interactions, and mental health. Social Service
Review, 82, 223-252.
Litt, M. D. (1988). Cognitive mediators of stressful experience: Self-efficacy and perceived
control. Cognitive Therapy and Research, 12, 241-260.
Liu, C., Spector, P. E., & Shi, L. (2007). Cross-national job stress: a quantitative and qualitative
study. Journal of Organizational Behavior, 28, 209-239.
Locke, E. A., Frederick, E., Lee, C., & Bobko, P. (1984). The effect of self-efficacy, goals, and
task strategies on task performance. Journal of Applied Psychology, 69, 241-251.
228

Lu, C., Siu, O., & Cooper, C. L. (2005). Managers’ occupational stress in China: the role of selfefficacy. Personality and Individual Differences, 38, 569-578.
Lubbers, R., Loughlin, C., & Zweig, D. (2005). Young workers’ job self-efficacy and affect:
Pathways to health and performance. Journal of Vocational Behavior, 67, 199-214.
Luszczynska, A., Gutiérrez-Doña, B., & Schwarzer, R. (2005). General self-efficacy in various
domains of human functioning: Evidence from five countries. International Journal of
Psychology, 40, 80-89.
Lyubomirsky, S. (2001). Why are some people happier than others?: The role of cognitive and
motivational processes in well-being. American Psychologist, 56, 239-249.
MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A
comparison of methods to test mediation and other intervening variable effects.
Psychological Methods, 7, 83-104.
Martinussen, M., Richardsen, A. M., & Burke, R. J. (2007). Job demands, job resources, and
burnout among police officers. Journal of Criminal Justice, 35, 239-249.
Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of
Occupational Behavior, 2, 99-113.
Maurer, T. J., Weiss, E. M., & Barbeite, F. G. (2003). A model of involvement in work-related
learning and development activity: The effects of individual, situational, motivational,
and age variables. Journal of Applied Psychology, 88, 707-724.
MacKay, C., Cox, T., Burrows, G., & Lazzerini, T. (1978). An inventory for the measurement of
self-reported stress and arousal. British Journal of Social and Clinical Psychology, 17,
283-284.
Miner-Rubino, K., & Cortina, L. M. (2007). Beyond targets: Consequences of vicarious
exposure to misogyny at work. Journal of Applied Psychology, 92, 1254-1269.
Mitchell, T. R., Hopper, H., Daniels, D., George-Falvy, J., & James, L. R. (1994). Predicting
self-efficacy and performance during skill acquisition. Journal of Applied Psychology,
79, 506-517.
Montgomery, A. J., Panagopoulou, E., & Benos, A. (2006). Work-family interference as a
mediator between job demands and job burnout among doctors. Stress and Health, 22,
203-212.
Nandram, S. S., & Klandermans, B. (2006). Stress experienced by active members of trade
unions. Journal of Organizational Behavior, 14, 415-431.
Neufeld, R. W. J. (1999). Dynamic differentials of stress and coping. Psychological Review, 106,
385-397.
Organ, D. W. (1988). Organizational citizenship behavior: The good soldier syndrome.
Lexington, MA: Lexington Books.
Örtqvist, D., & Wincent, J. (2006). Prominent consequences of role stress: A meta-analytic
review. International Journal of Stress Management, 13, 399-422.
Parasuraman, S., & Cleek, M. A. (1984). Coping behaviors and managers’ affective reactions to
role stressors. Journal of Vocational Behavior, 24, 179-193.
229

Parker, S. K. (2003). Longitudinal effects of lean production on employee outcomes and the
mediating role of work characteristics. Journal of Applied Psychology, 88, 620-634.
Parker, S. K., & Sprigg, C. A. (1999). Minimizing strain and maximizing learning: The role of
job demands, job control, and proactive personality. Journal of Applied Psychology, 6,
925-939.
Parkes, K. R. (1990). Coping, negative affectivity, and the work environment: Additive and
interactive predictors of mental health. Journal of Applied Psychology, 75, 399-409.
Parkes, K. R., Mendham, C. A., & von Rabenau, C. (1994). Social support and the demanddiscretion model of job stress: Tests of additive and interactive effects in two samples.
Journal of Vocational Behavior, 44, 91-113.
Pavot, W., Diener, E., & Fujita, F. (1990). Extraversion and happiness. Personality and
Individual Differences, 11, 1299-1306.
Peeters, M. C. W., Montgomery, A. J., Bakker, A. B., & Schaufeli, W. B. (2005). International
Journal of Stress Management. 12, 43-61.
Peiró, A. (2006). Happiness, satisfaction and socio-economic conditions: Some international
evidence. The Journal of Socio-Economics, 35, 348-365.
Pelfrene, E., Vlerick, P., Kittel, F., Mak, R. P., Kornitzer, M., & De Backer, G. (2002).
Psychosocial work environment and psychological well-being: Assessment of the
buffering effects in the job demands-control (-support) model in BELSTRESS. Stress and
Health, 18, 43-56.
Petty, M. M., McGee, G. W., & Cavender, J. W. (1984). A meta-analysis of the relationships
between individual job satisfaction and individual performance. Academy of Management
Review, 9, 712-721.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method
biases in behavioral research: A critical review of the literature and recommended
remedies. Journal of Applied Psychology, 88, 879-903.
Rau, R. (2004). Job strain or healthy work: A question of task design. Journal of Occupational
Health Psychology, 9, 322-338.
Rau, R., & Triemer, A. (2004). Overtime in relation to blood pressure and mood during work,
leisure, and night time. Social Indicators Research, 67, 51-73.
Rees, T., & Freeman, P. (2009). Social support moderates the relationship between stressors and
task performance through self-efficacy. Journal of Social and Clinical Psychology, 28,
244-263.
Repetti, R. L. (1993). Short-term effects of occupational stressors on daily mood and health
complaints. Health Psychology, 12, 125-131.
Rhoades, L., & Eisenberger, R. (2002). Perceived organizational support: A review of the
literature. Journal of Applied Psychology, 87, 698-714.
Richardson, H. A., Yang, J., Vandenberg, R. J., DeJoy, D. M., & Wilson, M. G. (2008).
Perceived organizational support’s’ role in stressor-strain relationships. Journal of
Managerial Psychology, 23, 789-810.
230

Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role conflict and ambiguity in complex
organizations. Administrative Science Quarterly, 15, 150-163.
Russell, J. E. A. (2008). Promoting subjective well-being at work. Journal of Career Assessment,
16, 117-131.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic
motivation. American Psychologist, 55, 68-78.
Saltzman, K. M., & Holahan, C. J. (2002). Social support, self-efficacy and depressive
symptoms: An integrative model. Journal of Social & Clinical Psychology, 21, 309-322.
Schaubroeck, J. & Merritt, D. (1997). Divergent effects of job control on coping with work
stressors: The key role of self-efficacy. Academy of Management Journal, 40, 738-754.
Schaubroeck, J., & Jones, J. R., & Xie, J. L (2001). Individual differences in utilizing control to
cope with job demands: Effects on susceptibility to infectious disease. Journal of
Applied Psychology, 86, 265-278.
Schaubroeck, J., Lam, S. S. K., & Xie, J. L. (2000). Collective efficacy versus self-efficacy in
coping responses to stressors and control: A cross-cultural study. Journal of Applied
Psychology, 85, 512-525.
Scheck, C. L., Kinicki, A. J., & Davy, J. A. (1997). Testing the mediating processes between
work stressors and subjective well-being. Journal of Vocational Behavior, 50, 96-123.
Schirmer, L. L., & Lopez, F. G. (2001). Probing the social support and work strain relationship
among adult workers: Contributions of adult attachment orientations. Journal of
Vocational Behavior, 59, 17-33.
Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being:
Informative and directive functions of affective states. Journal of Personality and Social
Psychology, 45, 513-523.
Schwerdtfeger, A., Konermann, L., & Schönhofen, K. (2008). Self-efficacy as a healthprotective resource in teachers? A biopsychological approach. Health Psychology, 27,
358-368.
Segrin, C., & Taylor, M. (2007). Positive interpersonal relationships mediate the association
between social skills and psychological well-being. Personality and Individual
Differences, 43, 637-646.
Shen, Y. E. (2009). Relationships between self-efficacy, social support and stress coping
strategies in Chinese primary and secondary school teachers. Stress and Health, 25, 129138.
Shoji, K., Harrigan, J. A., Woll, S. B, & Miller, S. A. (2010). Interactions among situations,
neuroticism, and appraisals in coping strategy choice. Personality and Individual
Differences, 48, 270-276.
Siegrist, J. (2004). Psychosocial work environment and health: New evidence. Journal of
Epidemiology and Community Health, 58, 888.
Simons, T., & Peterson, R. (2000). Task conflict and relationship conflict in top management
teams: The pivotal role of intragroup trust. Journal of Applied Psychology, 85, 102-111.
231

Siu, O. L., Spector, P. E., Cooper, C. L., & Lu, C. (2005). Work stress, self-efficacy, Chinese
work values, and work well-being in Hong Kong and Beijing. International Journal of
Stress Management, 12, 274-288.
Snijders, T. A. B., & Bosker, R. J. (1993). Standard errors and sample sizes for two-level
research. Journal of Educational Statistics, 18, 237-259.
Snijders, T. A. B., & Bosker, R. J. (1999). Multilevel Analysis: An Introduction to Basic and
Advanced Multilevel Modeling. London, England: Sage Publishers.
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation
models. In S. Leinhardt (Ed.), Sociological Methodology (pp. 290-312). Washington, DC:
American Sociological Association.
Sonnentag, S. (2001). Work, recovery activities, and individual well-being: A diary study.
Journal of Occupational Health Psychology, 6, 196-210.
Sonnentag, S. & Frese, M. (2003). Stress in organizations. In W. C. Borman, D. R. Ilgen, & R. J.
Klimoski (Eds.), Comprehensive handbook of psychology, Volume 12: Industrial and
organizational psychology (pp. 453-491). Hoboken: Wiley.
Spector, P. E. (1987). Interactive effects of perceived control and job stressors on affective
reactions and health outcomes for clerical workers. Work & Stress, 1, 155-162.
Spector, P.E., & Fox, S. (2002). An emotion-centered model of voluntary work behavior: Some
parallels between counterproductive work behavior and organizational citizenship
behavior. Human Resource Management Review, 12, 269-292.
Stajkovic, A. D. (2006). Development of a core confidence-higher order construct. Journal of
Applied Psychology, 91, 1208-1224.
Steel, P., Schmidt, J., & Shultz, J. (2008). Refining the relationship between personality and
subjective well-being. Psychological Bulletin, 134, 138-161.
Suh, E., Diener, E., & Fujita, F. (1996). Events and subjective well-being: Only recent events
matter. Journal of Personality and Social Psychology, 70, 1091-1102.
Taris, T. W., Kompier, M. A. J., De Lange, A. H., Schaufeli, W. B., & Schreurs, P. J. G. (2003).
Learning new behaviour patterns: A longitudinal test of Karasek's active learning
hypothesis among Dutch teachers. Work & Stress, 17, 1-20.
Taris, T. W., Peeters, M. C. W., Le Blanc, P. M., Schreurs, P. J. G., & Schaufeli, W. B. (2001).
From inequity to burnout: The role of job stress. Journal of Occupational Health
Psychology, 6, 303-323.
Taylor, S. E. (1991). Asymmetrical effects of positive and negative events: The mobilizationminimization hypothesis. Psychological Bulletin, 110, 67-85.
Teuchmann, K., Totterdell, P., & Parker, S. K. (1999). Rushed, unhappy, and drained: An
experience sampling study of relations between time pressure, perceived control, mood,
and emotional exhaustion in a group of accountants. Journal of Occupational Health
Psychology, 4, 37-54.
Thayer, R. E. (1996). The origin of everyday moods: Managing energy, tension, and stress. New
York: Oxford University Press.
232

Totterdell, P., Wood, S., & Wall, T. (2006). An intra-individual test of the demands-control
model: A weekly diary study of psychological strain in portfolio workers. Journal of
Occupational and Organizational Psychology, 79, 63-84.
Tran, T. V., Wright, R. Jr., & Chatters, L. (1991). Health, stress, psychological resources, and
subjective well-being among older blacks. Psychology and Aging, 6, 100-108.
Tschan, F., Rochat, S., & Zapf, D. (2005). It’s not only clients: Studying emotion work with
clients and co-workers with an event-sampling approach. Journal of Occupational and
Organizational Psychology, 78, 195-220.
Tse, J. L. M., Flin, R., & Mearns, K. (2007). Facets of job effort in bus driver health:
Deconstructing “effort” in the effort-reward imbalance model. Journal of Occupational
Health Psychology, 12, 48-62.
Tummers, G., van Merode, F., Landeweerd, A., & Candel, M. (2003). Individual-level and
group-level relationships between organizational characteristics, work characteristics, and
psychological work reactions in nursing work: A multilevel study. International Journal
of Stress Management, 10, 111-136.
Van der Doef, M. P., & Maes, S. (1999). The job demand-control(-support) model and
psychological well-being: A review of 20 years of empirical research. Work & Stress, 13,
87-114.
Van Eck, M., Nicolson, N. A., & Berkhof, J. (1998). Effects of stressful daily events on mood
states: Relationship to global perceived stress. Journal of Personality and Social
Psychology, 75, 1572-1585.
Van Emmerik, I. J. H., & Jawahar, I. M. (2006). The independent relationships of objective and
subjective workload with couples’ mood. Human Relations, 59, 1371-1392.
Van Vegchel, N., de Jonge, J., Söderfeldt, M., Dormann, C., & Shaufeli, W. (2004). Quantitative
versus emotional demands among Swedish human service employees: Moderating effects
of job control and social support. International Journal of Stress Management, 11, 21-40.
Vancouver, J. B., & Kendall, L. N. (2006). When self-efficacy negatively relates to motivation
and performance in a learning context. Journal of Applied Psychology, 91, 1146-1153.
Viswesvaran, C., Sanchez, J. I., & Fisher, J. (1999). The role of social support in the process of
work stress: A meta-analysis. Journal of Vocational Behavior, 54, 314-334.
Warr, P. (1999). Well-being and the workplace. In D. Kahneman, E. Diener and N. Schwarz
(Eds.), Well-Being: The Foundations of Hedonic Psychology (pp. 392-412). New York,
NY: Russell Sage Foundation.
Warr, P. (2006). Differential activation of judgments in employee well-being. Journal of
Occupational and Organizational Psychology, 79, 225-244.
Watson, D. (2000). Mood and Temperament. New York, NY: Guilford.
Watson, D., & Clark, L. A. (1994). The PANAS-X: Manual for the positive and negative affect
schedule-expanded form. Iowa City, IA: University of Iowa.

233

Webster, J. R., Beehr, T. A., & Christiansen, N. D. (2010). Toward a better understanding of the
effects of hindrance and challenge stressors on work behavior. Journal of Vocational
Behavior, 76, 68-77.
Weinstein, N., Brown, K. W., & Ryan, R. M. (2009). A multi-method examination of the effects
of mindfulness on stress attribution, coping, and emotional well-being. Journal of
Research in Personality, 43, 374-385.
Weiss, H. M., & Cropanzano, R. (1996). Affective events theory: A theoretical discussion of the
structure, causes, and consequences of affective experiences at work. Research in
Organizational Behavior, 18, 1-74.
Weiss, H. M., Nicholas J. P., & Daus, C. S. (1999). An examination of the joint effects of
affective experiences and job beliefs on job satisfaction and variations in affective
experiences over time. Organizational Behavior and Human Decision Processes, 78, 124.
Wheeler, L., & Reis, H. T. (1991). Self-recording of everyday life events: Origins, types, and
uses. Journal of Personality, 59, 339-354.
Wiedenfeld, S. A., O’Leary, A., Bandura, A., Brown, S., Levine, S., & Raska, K. (1990). Impact
of perceived self-efficacy in coping with stressors on components of the immune system.
Journal of Personality and Social Psychology, 59, 1082-1094.
Wilk, S. L., & Moynihan, L. M. (2005). Display rule “regulators”: The relationship between
supervisors and worker emotional exhaustion. Journal of Applied Psychology, 90, 917927.
Wilson, W. R. (1967). Correlates of avowed happiness. Psychological Bulletin, 67, 294-306.
Xanthopoulou, D., Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2007). The role of
personal resources in the job demands-resources model. International Journal of Stress
Management, 14, 121-141.
Xanthopoulou, D., Bakker, A. B., Heuven, E., Demerouti, E., & Schaufeli, W. B. (2008).
Working in the sky: A diary study of work engagement among flight attendants. Journal
of Occupational Health Psychology, 13, 345-356.
Yeo, G. B., & Neal, A. (2006). An examination of the dynamic relationship between selfefficacy and performance across levels of analysis and levels of specificity. Journal of
Applied Psychology, 91, 1088-1101.
Yoon, J. (2001). The role of structure and motivation for workplace empowerment: The case of
Korean employees. Social Psychology Quarterly, 64, 195-206.
Zautra, A. J., & Wrabetz, A. B. (1991). Coping success and its relationship to psychological
distress for older adults. Journal of Personality and Social Psychology, 61, 801-810.
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale
of perceived social support. Journal of Personality Assessment, 52, 30-41.

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