1351517463250Engagement_vs.burnout_An_examination_of_the_relationships_between_the_two_concepts_within_the_framework_of_the_.pdf

ESADE WORKING PAPER Nº 234 July 2012
Engagement vs. Burnout: An examination of the
relationships between the two concepts within the
framework of the JDR model
Scott Moodie
Simon L. Dolan
Ronald J. Burke

ESADE Working Papers Series
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ISSN 2014-8135
Depósito Legal: B-3449-2012

Engagement vs. Burnout: An examination of the relationships between the two concepts
within the framework of the JDR model
3
Engagement vs. Burnout: An examination of the relationships between the
two concepts within the framework of the JDR model
Scott Moodie
PhD Candidate in Management Science
ESADE Business School, Ramon Llull University, Spain
Simon L. Dolan
Professor and Future of Work Chair
ESADE Business School, Ramon Llull University, Spain (corresponding author)
Ronald J. Burke
Professor Emeritus, Schulich School of Business, York University (Canada)
and Associate Professor at the Future of Work Chair (ESADE Business School)
July 2012
Abstract
The precise relationship between the positive psychological state of work (i.e.
engagement) and the negative psychological state (i.e. burnout) has been receiving an
increased attention. Some view these as opposite states on the same or similar
continuum, while others take the position that they represent different biobehavioral
spheres. Both states exhibit significant correlations to job demands and resources,
elements of physical and mental wellbeing, and to each other. This study expands our
knowledge of the phenomena of engagement and burnout by analyzing their separate and
joint manifestations. Using a large sample of 2,094 nurses, respondents were segmented
into quadrants that represent a 50/50 (median split) of Engagement and Burnout. The four
resulting quadrants were examined in a series of analyses including logistic regression
and ANOVAs. This configurational approach allowed us to examine both inverse and
concurrent states of Engagement and Burnout. The findings suggested that engagement
and burnout were generally inversely related (67% of the sample) but could be manifested
concurrently at either extreme (33% of the sample). Burnout was chiefly driven by work
demands as both quadrants of low burnout had lower demands and both quadrants of
high burnout had higher demands. Engagement was primarily driven by resources and
affinity. Social support acted independently by aligning with states of burnout. Worker
health was primarily driven by burnout wherein both states of low burnout exhibited better
health and both states of high burnout exhibited poorer health.
Keywords: Engagement, Burnout, JD-R, Affinity, Health, Social Support
Short Title: Exploring the multiple linkages between Work Engagement and Burnout

4
Notes and Acknowledgements
1. A version of this paper has been presented at the Academy of Management
meeting in Boston (August 2012).
2. This work has been supported in part by the MEC (Spanish Ministry of
Education and Science) SEJ2007-67618 and AGAUR - Generalitat de
Catalunya. We also wish to express our gratitude to the Col∙legi Oficial
d'Infermeres de Barcelona for their instrumental assistance.
Corresponding author contact:
Simon L. Dolan
ESADE Business School,
Av. Torre Blanca, 59
Sant Cugat, Spain 08172
simon.dolan@esade.edu
Tel. +34 93 4952052

5
Introduction
Researchers in the fields of organizational psychology and organizational behavior
have examined ways in which positive or negative perceptions and attitudes are
linked to performance at work. The subjective or perceptual measurement of
indicators such as satisfaction and motivation have a long history of use in
organizational research but increasingly have been criticized for being insufficient
to predict performance outcomes on both conceptual or methodological grounds
(Brief & Weiss, 2002; Latham & Pinder, 2005; Wright, 2006; van Saane, Sluiter,
Verbeek, & Frings-Dresen, 2003). They have been replaced by measurements
attempting to capture more objective, work-related states of mind. Two of the latter
include the constructs of burnout and engagement (Bakker, Schaufeli, Leiter, &
Taris, 2008). Burnout is a negative construct contributing to decreased job
satisfaction and organizational commitment, and increasing undesired outcomes
such as turnover and absenteeism (Lee & Ashforth, 1996). Engagement is a
positive indicator characterized by vigor, dedication, and absorption (Schaufeli,
Salanova, González-Romá, & Bakker, 2002). Vigor is characterized by high levels
of energy and mental resilience at work. Dedication is a strong sense of
involvement with one’s work along with a sense of significance, enthusiasm, and
challenge. Absorption occurs when an individual is fully concentrated and happily
engrossed in their work to the extent that time passes quickly and they have
difficulty detaching themselves from their work (Bakker & Demerouti, 2008;
Schaufeli & Bakker, 2004).
Workers that scored high on engagement have been shown to exhibit high energy
and self-efficacy (Schaufeli et al., 2001). The positive nature of work engagement
leads workers to create their own positive feedback in terms of appreciation,
recognition, and success (Bakker & Demerouti, 2008). Bakker and Demerouti
(2008) found that engaged workers carried their enthusiasm and energy with them
outside of the organization and felt a sense of accomplishment at the end of the
work day. Schaufeli & van Rhenen, (2006) reported a strong connection between
positive emotions and engagement. Engagement has also been shown to be
positively related to health (Schaufeli, Taris, & van Rhenen, 2008). Furthermore,

6
engaged workers reported fewer psychosomatic complaints than co-workers who
displayed low levels of engagement (Demerouti, Bakker, De Jonge, Janssen, &
Schaufeli, 2001). Schaufeli & Bakker, (2004) observed that engaged workers
suffered from fewer self-reported headaches, cardiovascular problems, and
stomach aches.
Different approaches to the conceptualization of burnout have at their core low
levels of physical and emotional energy (Shirom, 2005). Burnout represents a
chronic condition that remains stable over time (Taris et al., 2005; Kristensen et
al., 2005; Halbesleben & Demerouti, 2005). Several studies indicated that aspects
of the job environment were stronger predictors of burnout than were personality
factors (Lee & Ashforth, 1996; Schaufeli & Enzmann, 1998). However, research
also suggested that there was a link between emotional exhaustion, as
operationalized within a burnout framework, and family-related factors (Bakker et
al., 2005). This connection between low physical and emotional energy was
primarily dependent upon social aspects of the work environment and was distinct
from chronic states of depression that represented a propensity towards negative
affective states (Shirom, 2005; Schaufeli & Enzmann, 1998). Burnout has been
also linked to a variety of health complaints including circulatory and heart
problems, muscular pains, sleep disturbances, headaches, and gastro-intestinal
problems (Gorter et al., 2000; Kahill, 1988; Westman and Bakker, 2008)
The predominant formulations of burnout and engagement bear a number of
similarities which can create confusion concerning the manner in which they relate
to each other. At the most basic level, constructs evaluating engagement have
been linked to a set of positive emotions (Schuafeli & Van Rhenen, 2006) whereas
burnout constructs wwere closely linked to a set of corresponding negative
emotions (Schaufeli & Enzmann, 1998). Some researchers have positioned
burnout and engagement at opposite ends of a single dimension (Demourouti and
Bakker, n.d). For example, The Oldenburg Burnout Inventory (OLBI; Demerouti et
al., 2001, 2003) is a tool which measures burnout by categorizing respondent’s
levels of exhaustion and disengagement thereby effectively placing burnout and
engagement at opposite ends of the same scale.

7
The Dutch UWES model connected with the pioneering work of Bakker and
Schaufeli conceptualizes engagement according to states of vigor, dedication, and
absorption. The UWES measures of vigor and dedication are regarded as polar
opposites of the most frequently used measure used in burnout research, the
Maslach Burnout Inventory -MBI (Maslach & Jackson 1981). The central
measurers of the MBI are exhaustion and cynicism. However, the UWES ignores
the MBI dimension of reduced personal efficacy and replaces it with the concept of
absorption (Schaufeli & Bakker, 2003). According to Schaufeli & Bakker, (2003),
this modification was made in part because studies had demonstrated that lack of
professional efficacy was less determinate of burnout than exhaustion and
cynicism (Maslach et al., 2001; Shirom, 2002). A second reason for the addition of
absorption to the UWES resulted from qualitative findings suggesting that
engagement was characterized by being immersed and happily engrossed in
one’s work (Schaufi & Bakker, 2003).
Shirom, (2003) argued that vigor (engagement) and burnout were obliquely related
and were thus not positioned at opposite ends of the same continuum. One of his
arguments ass that vigor and burnout are subjective components of different
biobehavioral systems (Watson et al., 1999). By adapting this theory, Shirom,
(2003) posited that burnout may be an antecedent of an internal withdrawal-
oriented behavioral inhibition system whereas vigor is a component of an
approach-oriented behavior facilitation system. This argument presented the
possibility that both burnout and vigor could be operationalized in the same
context since many job situations present both demands and opportunities for
rewards. In this way, demanding situations may evoke burnout, but the anticipated
rewards of completion may simultaneously evoke vigor (Dweck & Legget, 1988).
Joint and Separate Determinants and consequences of Work Engagement and
Burnout.
The origins of both burnout and engagement are multi-factorial and multi-faced
(Shirom, 2005). Possible sources can include individual differences and
personalities, organizational demands and environmental factors, and cultural

8
factors that interact in specific configurations (Diez-Pinol, Dolan, Sierra, &
Cannings, 2008). To develop a broader and more complete view of the
relationship between work engagement and burnout, it is important to explore
them together to determine the joint influence that antecedents have on separate
and concurrent states of Engagement and Burnout. Thus, this study employs
frequently used measures of Engagement and Burnout and uses a configurational
approach dividing respondents into quartiles based on the presence of Low
Engagement and Low Burnout (LELB), Low Engagement and High Burnout
(LEHB), High Engagement and Low Burnout (HELB), and High Engagement and
High Burnout (HEHB). These quartiles were then examined using personal and
organizational determines nested within the larger framework of the J-DR model
(Bakker & Demerouti, 2007; Demerouti et al., 2001) in an attempt to best predict
the quartiles along with the comparative states of physical and mental health of its
members.
----------------------------------------
(Table 1 about here)
------------------------------------------
Study objectives and research questions
This study expands on our knowledge of the phenomena of Engagement and
Burnout by analyzing their separate and joint manifestations. Thus, as explained
below, the respondents were segmented into quadrants that represented a
50/50, or median split, on both Engagement and Burnout.The four resulting
quadrants include those with A. Low Engagement and Low Burnout (LELB); B.
Low Engagement and High Burnout (LEHB); C. High Engagement and Low
Burnout (HELB); and D. High Engagement and High Burnout (HEHB). This
classification enabled the empirical testing that shows which combination of
antecedents can best predict each manifestation, and what consequences are
exhibited on individual health and wellbeing. This is the essence of what has been
referred to in this study as a configurational approach.

9
More specifically, the following research questions represent the core for the
present study:
1. Are Engagement and Burnout inversely or concurrently related?
2. What is the configuration of individual and organizational variables that predict
states of
A. Low Engagement and Low Burnout?
B. Low Engagement and High Burnout?
C. High Engagement and Low Burnout?
D. High Engagement and High Burnout?
3. What is the effect of each joint configuration of Engagement and Burnout on
Physical and Mental Health?
To address these questions, the study was positioned into the broader J-DR
research model (Bakker & Demerouti, 2007; Demerouti et al., 2001).
Respondents were nurses employed in multiple regions and multiple hospitals in
Spain.. Nurses have been studied extensively due to the worsening of their
respective working conditions and the alarming rates of burnout reported
worldwide (Gilbert et al, 2010, Leiter et al, 2009; Leiter et al, 2010). Studying the
nursing population can be instrumental for comparative reasons and enhance the
external validity of the study.
Personal and organizational factors linked to engagement and burnout were
divided into four categories: Job Demands, Job Resources, Social Support, and
Affinity. Job demands and resources have a long established connection to both
engagement and burnout. The JD-R model proposes that burnout arises from
situations where many demands are made without the provision of sufficient
resources to meet those demands (Demerouti, Bakkar, Nachreiner, & Schaufeli,
2001). The conservation of resources theory suggests that burnout increases
when valued resources are lost, are unable to meet job requirements, or are
insufficient (Hobfoll & Freedy, 1993). Structural equation modeling in the
Schaufeli et al, (2009) study found that increases in demands and decreases in

10
resources predicted burnout and that increases in resources predicted
engagement. This study also concluded that resources and engagement were
reciprocal in that work engagement lead to an increase in resources which
subsequently increased the level of engagement.
A meta-analysis by Crawford et. al (2010) found that demands and burnout were
positively associated and that resources and burnout were negatively associated.
With respect to engagement, they found that resources and engagement were
positively associated but the association between demands and engagement
varied according to the nature of the demand. Demands that were considered to
be hindrances were negatively associated with engagement whereas demands
considered to be challenges had a positive association with engagement. Another
meta-analysis conducted by Halbesleben et al, (2010) found that engagement and
burnout constructs were negatively associated albeit with a few exceptions.
Engagement was positively related to resources and negatively related to
demands with resources having a stronger relationship.
Within the JD-R model, the commonly used measure of social support measures
cooperation among colleagues. For the present study, we replaced this measure
with a measure of social support that assesses support at three levels: supervisor
support, colleague support, and spousal support. A meta-analysis by Halbesleben
(2011) found that work-related social support was more closely associated with the
exhaustion component of burnout than non-work sources of social support.
Shaufeli et al.,(2008) reported that co-worker support was negatively associated
with the reduced professional efficacy dimension of the MBI burnout measure and
positively associated with the dedication dimension of Engagement and that
supervisor support was negatively associated with the exhaustion and cynicism
dimensions of burnout.
Affinity refers to the long-term affective evaluation of an employee to their work
and includes the aspects of Affective Commitment and Job Involvement.
Organizational Commitment and Job Involvement have been found to be
discriminately different constructs from work engagement (Hallberg & Shaufelli,

11
2006). Affective commitment is one of the dimensions of organizational
commitment as proposed by Allen & Meyer (1990). Affective organizational
commitment is more closely related to job characteristics than to personal factors
and therefore related to extrinsic circumstances of the work (Morrow, 1983,
Hallberg & Shaufeli, 2006). Organizational commitment has been found to be
inversely associated with the cynicism and reduced professional efficacy
dimensions of burnout and positively associated with the dedication and
absorption dimensions of work engagement (Schaufeli et al., 2008).
Job involvement has been defined as a ‘cognitive belief state of psychological
identiﬁcation’ with one’s job (Kanungo, 1982, p. 80). This relatively stable attitude
(Kunel et al., 2009) is different from short-term states of engagement which can
change from day to day (Dalal, Brummel, Wee, & Thomas, 2008). Job Involvement
has been shown to have a direct positive effect on Engagement among nurses
(Kunel et al., 2009). Griffen et al, (2010) found that job involvement was positively
related to the emotional exhaustion dimension of burnout.
Present states of physical and mental health were evaluated by assessing general
physical health, anxiety and depression. As noted above, both engagement and
burnout are measures of employee wellbeing and both have been extensively
linked to health. It is common for people suffering from stress to engage in
behaviors such as smoking, alcohol abuse, or eating unhealthy food that may
alleviate short term effects, but have long-term negative health consequences
(Scwarzer & Fuchs, 1995). Several studies have confirmed that health is closely
correlated with burnout. (Kahill, 1988; Soderfeldt et al., 2000). Engagement is
linked to positive emotions and better health (Bakker et al., 2008). While there is a
need for further research on the specific paths between engagement and health, a
recent study found that patients who demonstrated positive affect had a reduction
in 10-year incidents of coronary heart disease (Davidson et al., 2010). A summary
of the general hypothesized relationships of these categories with regards to
Engagement and Burnout can be found in Table 2

12
---------------------------------
---------------------------------
Sample Methods and procedures
Respondents
Nurses must be registered and qualified within a regional association to practice
nursing n Spain.. This study was carried out with the support of these associations
in selected regions in Spain. An online survey was prepared, pre-tested and pre-
validated, and sent to the regional associations for distribution among their
members. The total recipient number could not be determined but 2,115 surveys
were completed online. Of these, 21 surveys were removed from the dataset due
to spurious data or omissions leaving 2094 complete responses. The majority of
responses were received from the provinces of Catalunya and Gipuzkoa. The
respondents were 90.3% female, had a mean age of 39 years and had worked as
a nurse for an average number of 16 years. Of these, 72% reported living with a
partner and 85% of respondents worked full time as a nurse.
Measures
The central measures of the study were the shortened (Schaufeli et al., 2006)
Utrecht Work Engagement Scale (UWES) developed by Schaufeli and Bakker
(2003) and the Shirom-Melamed Burnout Measure (SMBM, Shirom et al., 2005).
The UWES is based upon a three dimension model of engagement which includes
vigor, dedication, and absorption (Schaufeli et al., 2002) whereas the SMBM
assesses the depletion of an individual’s energetic resources at work by
measuring the three dimensions of physical fatigue, emotional exhaustion, and
cognitive weariness.

13
Job Demands and Resources were investigated by employing measures used in
the Job Demands – Resources (JD-R) model of Bakker et al. (2003) which has
been employed in many other studies on engagement (i.e. Xanthopoulou et al.,
2007a, b) and burnout (Bakker et al., 2004). While the model seems to be dynamic
and in a continued state of evolution ( Demerouti & Bakker, 2011), some core
components were present across various versions of it. For example, job demands
refer to physical, psychological, social, or organizational aspects of the job that
require sustained psychological or physical effort (Bakker et al, 2004). This model
examines job demands according to three categories: workload, emotional
demands, and work-home conflict.
Job Resources refer to physical, psychological, social, or organizational aspects of
the job that are necessary to achieve goals, reduce job demands, and stimulate
personal growth and development (Bakker et al., 2004). Of the original JD-R
measures, the scales for Autonomy and Self Development Opportunities were
used. The JD-R measure of Social Support that measures a single factor of social
support was replaced with the scale of Dolan et al (1992a, 1992b) which assesses
support along the axes of Supervisor Support, Colleague Support, and Spousal
Support.
Affinity towards work was assessed using measures of Affective Commitment and
Job Involvement. The inclusion of these variables permits an assessment of
perceived affiliation and identification with the work and workplace. Affective
Commitment was assessed using the measures of Meyer, Allen and Smith, 1993.
Job Involvement was assessed using a 4 item version from Frone and Rice (1987)
which was based on the original measure by Kanungo (1982).
Employee health and wellbeing was measured by assessing General Health,
Anxiety, and Depression. General health was assessed through a single item
which asked respondents to evaluate their general state of health varying from
very poor and very good (Benyamini & Idler, 1999). The single-item construct has
been found to be a valid predictor of all-cause morbidity and mortality (DeSalvo et
al., 2006a) and has demonstrated comparable reliability and validity when

14
compared to other multi-item measures used by health professionals (DeSalvo et
al., 2006b). Mental health was measured via the anxiety and depression scales
developed by Dolan and Arsenault (1983). The variables used in the study,
including their respective psychometric properties are presented in Table 3.
--------------------------------
-------------------------------
Analysis Strategy
The data was analyzed in stages which included zero-item correlations and
ANOVAs to determine their independence and suitability for predicting states of
Engagement and Burnout. The Engagement and Burnout scores were binned
using a 50/50 median split and then merged to reflect four distinct groups
representing Low Engagement and Low Burnout, Low Engagement and High
Burnout, High Engagement and Low Burnout, and High Engagement and High
Burnout. A series of Binary Logistic Regression analyses were undertaken to
determine the relative influence of the independent variables as predictors of each
state of Engagement and Burnout after controlling for Age, Gender, and Part
Time/Full Time work status. Explained variance was measured with the
Nagelkerke Pseudo R2
score. A series of ANOVA analyses were then conducted
to determine whether the independent variables demonstrated a significant
difference within each group when compared to the remaining population.
Results
The purpose of this study was to identify whether the states of Engagement and
Burnout are manifested inversely or can be manifested concurrently. An effort
was also made to illustrate these conditions by identifying the primary antecedents
of each condition. In addition, levels of physical and mental health found among
each configuration were analyzed.

15
Segmentation of respondents according to levels of Engagement and Burnout
revealed that 67% of the population experienced states of either Low
Engagement and High Burnout or High Engagement and Low Burnout. The
remaining 33% of the population experienced states of either Low Engagement
and Low Burnout or High Engagement and High Burnout. Thus while the majority
of workers exhibited “one or the other” dominant states, a sizable percentage of
workers were functioning in one of the extremes.
------------------------------------------
(Tables 4 and 5 about here)
------------------------------------------
The group defined by states of Low Engagement and Low Burnout was best
predicted by all three Demands and Job Involvement (see results of Logistic
Regression in Table 4). Results of the ANOVA analysis (see Table 5) indicated
that when compared to the remaining population, these nurses exhibited
significantly lower Demands and Affinity and had higher levels of Colleague
Support. These nurses demonstrated better overall health on all measures. This
group has been labeled ‘Loafers’ to indicate their relative lack of demands, normal
levels of resources and support and their apathy towards the work.
The group defineded by states of Low Engagement and High Burnout was best
predicted by Emotional Demands, Work Interfering with Home, Self Development
Opportunities, Colleague and Spousal Support, and the two measures of Affinity.
Results of the ANOVA analysis indicated that this group of nurses demonstrated
significantly higher Demands, lower Resources, lower Social Support, and lower
Affinity. They reported a significantly poorer level of health on all measures. This
group has been labeled ‘Slaves’, to indicate their increased demands and lack of
resources, support or personal affinity to the work.
The group defined by states of High Engagement and Low Burnout was predicted
using all variables except for Autonomy. The ANOVA results revealed that,
compared to the remaining population, this group exhibited significantly lower
Demands, higher Resources, higher Social Support, and higher Affinity. They also
demonstrated significantly better health on all measures. This group has been

16
labeled ‘Apprentices’ to indicate their lower demands and higher levels of
resources, support, and affinity to the work.
Finally, the group defined by states of High Engagement and High Burnout was
best predicted by all measures of Demands, Self Development, Supervisor
Support and Job Involvement. The results of the ANOVA analysis indicate that
these workers experience higher Demands, higher Self Development
Opportunities, lower Social Support, and higher Affinity than their colleagues. They
were also marked by comparatively lower health on all measure when compared
to their colleagues. We have termed as ‘Lone Rangers’ to reflect their higher
demands, resources, and affinity to the work but lack of social support.
Discussion
The findings suggested that engagement and burnout were generally inversely
related but could be manifested concurrently at either extreme. The explained
variance of the dominant quadrants is very satisfactory assuming individual level
of analysis (LEHB R2
=.36, HELB R2
=.35), but the extreme quadrants are lower
(LELB R2
=.17, HEHB R2
=.12). This suggests that the primary determinants of
these states are external to the working conditions. This may reflect personality
types or social and cultural factors that influence their participation in the work
environment or their ability to manage resources, demands, or social relationships.
Results show that burnout was chiefly driven by work demands as both quadrants
of low burnout had lower demands and both quadrants of high burnout had higher
demands. This supports the findings of other studies (Xanthopoulou et al, 2007).
Engagement was found to be primarily driven by resources and affinity. The
relationship between resources and engagement has been amply documented in
other studies (Bakker et al, 2007, Crawford et al, 2010). While both job
involvement and organizational commitment have been independently examined
along with burnout and engagement, this is the first time that they have been
combined as dimensions of a single construct we called affinity. This provides

17
insight into the long-term attitude toward the work and the identification that
workers feel with their job which may be a useful construct in future studies. The
relationship of affinity to engagement can be partially explained in the conceptual
similarity of these attitudinal states with the UWES construct of dedication which
asks respondents several questions related to their identification with their work.
Findings pertaining to the influence of social support on burnout and engagement
provided an interesting insight. Social support has historically been considered a
resource as evidenced by its inclusion as a resource in the JD-R model.
Nonetheless, findings in this study do not confirm this assertion. Social support
did not behave like the other resources which were associated with states of
engagement. Instead, social support acted independently by aligning with states of
burnout. Both states of low burnout evidenced higher social support whereas both
states of high burnout evidenced lower social support. This suggests that social
support should perhaps be regarded as a distinct construct not to be considered
as a traditional resource.
Worker health was primarily influenced by burnout wherein both states of low
burnout exhibited better health and both states of high burnout exhibited poorer
health. While there has been an abundance of research linking engagement to
positive health (Kanste 2011) and burnout to negative health (Ahola, 2007,
Shirom, 2009), the findings of this study suggest that burnout is the greater
determinant of health. However, our measures of burnout, anxiety, and depression
were highly correlated which may be indicative of an inherent susceptibility of this
type of psychometric research to common method variance. The difficulty of
effectively isolating these phenomena has been noted by Shirom (2003).
Practical Implications
There are a number of practical implications that follow from this study. There has
been a recent debate about the relative merits of focusing on positive states of
engagement or negative states of burnout. Our study suggests that these states

18
are not mutually exclusive and that focusing too strongly on either state may
distract from a more fundamental need to create a positive and balanced work
environment. The strongest predictors in this study were demands and self
development opportunities. If management would focus on balancing demands
and resources and follow that by fostering social support and encouraging affinity
through training and recruitment, the result should be positive regardless of
whether it is measured according to burnout or engagement. We are not
suggesting that measuring either engagement or burnout is irrelevant. To the
contrary, they are both useful measures for assessing an employee’s current state
as reflective of the work environment. However, if the objective is to improve
working conditions and enhance employee wellbeing, it would at times be more
appropriate to directly assess demands and resources and find ways to optimize
their balance. Beyond that, it is in the best interest of companies and managers to
continually seek ways to foster social support and feelings of affinity to the work
and workplace.
Strengths and Limitations
The purpose of this study was to use a straightforward configurational approach to
classify the inverse and concurrent manifestations of engagement and burnout.
The recent growth in popularity of the concept of work engagement and the JD-R
model testify to the importance of these constructs and their relationships. Much of
the current research on this topic considers engagement and burnout to be linear
dimensions and focuses on building structural models of the precise relationships
between variables. That approach is to be encouraged, but there is also a need to
jointly deconstruct dimensions and relationships in a tactile manner that can inform
future structural models. While the majority of respondents fell in the expected
categories of HELB and LEHB, the 33% that exhibited one of the concurrent states
strongly suggests that new approaches to the study of these variables should be
considered. The secondary benefit of this approach is that these findings (Table 5)
can be submitted directly to managers to provide an easily understood approach
for assessments and interventions.

19
This quantitative simplification is useful in understanding the underlying nature of
the dimensions, but it is also prone to numerous susceptibilities. The study was
conducted at a single point in time using purely psychometric sources. It is
therefore prone to common method variance (Podsakoff et al., 2003). Further, the
variables of burnout, anxiety and depression have been previously noted to exhibit
multicolinearity (Shirom, 2003). While the sample size was rather large for this
type of studies (N=2094), the findings may not be generalizable beyond nurses
working in Spain.
Future Research Direction
This study presents the first step towards the classification of specific joint states
of work engagement and burnout. By demonstrating that the clusters have unique
compositions of antecedents, it would be useful to study whether the
contemporary structural models of variables interact differently in each of the four
quadrants. It would also be useful to examine whether the extreme quadrants
(HEHB, LELB) are influenced by other variables which could include individual
personality types, social functioning ability, values, clear instructions, job control or
compensation, among others. One of the primary goals of future research should
be the identification of paths between the quadrants, or more specifically, to
identify paths to HELB from the other three quadrants. If we can increase the
accuracy of the worker classification and the paths between groups, we will be
able to provide managers with specific tools for maximizing the well-being and
productivity of their workers.

20
Table 1
Configurational segmentation of sample (N = 2094)
Engagement
Low High
Burnout
Low
(LELB)
N = 342 (16.3%)
(HELB)
N = 731 (34.9%)
High
(LEHB)
N = 666 (31.6%)
(HEHB)
N = 355 (17.0%)

21
Table 2
Summary of expected relationships of Engagement and Burnout with study
constructs
Engagement Burnout
Demands - +
Resources + -
Affinity + -
Mental Health + -
Physical Health + -
Note: + = positive relationship; - = negative relationship

Table 3
Means (M), Standard Deviations (SD), Internal Consistencies (Cronbach's α) and Zero-Order Correlations of the Study
Variables (N = 2094)
Variable M SD Items Range α 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. Engagement 5.00 1.22 9 1-7 .91 -
2. Burnout 3.35 1.41 12 1-7 .95 -.50
**
-
3. Work Overload 3.69 .88 4 1-5 .86 -.03 .35
**
-
4. Emotional Demands 3.09 .82 6 1-5 .85 -.19
**
.50
**
.51
**
-
5. Work Int. w/ Home 2.21 .81 3 1-5 .77 -.13
**
.47
**
.31
**
.40
**
-
6. Self Dev. Opp. 3.69 .72 3 1-5 .67 .48
**
-.39
**
-.12
**
-.20
**
-.19
**
-
7. Autonomy 3.35 .95 3 1-5 .86 .32
**
-.31
**
-.21
**
-.22
**
-.19
**
.50
**
-
8. Supervisor Support 2.56 .83 4 1-4 .92 .29
**
-.34
**
-.19
**
-.23
**
-.17
**
.36
**
.39
**
-
9. Colleague Support 2.86 .67 4 1-4 .87 .25
**
-.32
**
-.13
**
-.23
**
-.19
**
.30
**
.29
**
.36
**
-
10. Spousal Support 3.34 .68 4 1-4 .88 .14
**
-.17
**
-.04
*
-.11
**
-.12
**
.11
**
.10
**
.17
**
.21
**
-
11. Affective Commitment 4.12 1.34 6 1-7 .84 .43
**
-.30
**
-.12
**
-.16
**
-.10
**
.38
**
.30
**
.34
**
.21
**
.05
*
-
12. Job Involvement 3.99 1.17 4 1-7 .70 .37
**
-.03 .07
**
.06
*
.23
**
.19
**
.08
**
.11
**
.02 -.05
*
.39
**
-
13. Anxiety .54 .38 4 0-1 .77 -.26
**
.58
**
.27
**
.39
**
.42
**
-.25
**
-.25
**
-.19
**
-.20
**
-.13
**
-.12
**
.09
**
-
14. Depression .41 .33 4 0-1 .67 -.33
**
.65
**
.21
**
.37
**
.37
**
-.32
**
-.25
**
-.22
**
-.22
**
-.14
**
-.19
**
.03 .63
**
-
15. Physical Health 3.10 .79 1 1-4 n.a. .24
**
-.50
**
-.13
**
-.23
**
-.25
**
.18
**
.17
**
.15
**
.18
**
.18
**
.07
**
-.08
**
-.37
**
-.40
**
Note: * p < .05; ** p < .01; *** p <.001.

23
Table 4
Binary Logistic Regression of Engagement and Burnout Quartiles on the
Study Variables (β-values) (N= 2094)
LELB LEHB HELB HEHB
Demands
1. Work Overload -.43*** .00 .17* .20*
2. Emotional Demands -.37*** .56*** -.52*** .35***
3. Work Int. w/ Home -.48*** .57*** -.61*** .23**
Resources
4. Self Development -.17 -.75*** .72*** .39***
5. Autonomy -.06 -.08 .10 - .02
Social Support
6. Supervisor Support -.04 -.04 .23** - .21*
7. Colleague Support .14 -.26** .21* -.03
8. Spousal Support -.12 -.20* .30** -.06
Affinity
9. Affective Commitment -.08 -.29*** .32*** .03
10. Job Involvement -.33*** -.30*** .29*** .32***
Explained Variance (R2
) .17 .36 .35 .12
Note: * p < .05; ** p < .01; *** p < .001.
Explained Variance is measured with the Nagelkerke Pseudo R2

24
Table 5
Synoptic ANOVA analysis for each quadrant compared to the remaining
population (N= 2094)
Low Engagement High Engagement
Low
Burnout
‘Loafers’
N = 342 (16.3%)
↓ Work Overload *** Demands: ↓
↓ Emotional Demands ***
↓ Work Int. w/ Home ***
Resources: Avg.
Social Support: ~↑
↑ Colleague Support *
↓ Affective Commitment ** Affinity: ↓
↓ Job Involvement ***
↓ Anxiety ***
Wellbeing: ↑ ↓ Depression ***
↑ Health ***
‘Apprentices’
N = 731 (34.9%)
↓ Work Overload *** Demands: ↓
↓ Emotional Demands ***
↓ Work Int. w/ Home ***
↑ Self Development *** Resources: ↑
↑ Autonomy ***
↑ Supervisor Support *** Social Support: ↑
↑ Colleague Support ***
↑ Spousal Support ***
↑ Affective Commitment *** Affinity: ↑
↑ Job Involvement ***
↓ Anxiety ***
Wellbeing: ↑ ↓ Depression ***
↑ Health ***
High
Burnout
‘Slaves’
N = 666 (31.6%)
↑ Work Overload *** Demands: ↑
↑Emotional Demands ***
↑Work Int. Home ***
↓ Self Development *** Resources: ↓
↓ Autonomy ***
↓ Supervisor Support *** Social Support: ↓
↓ Colleague Support ***
↓ Spousal Support ***
↓ Affective Commitment *** Affinity: ↓
↓ Job Involvement ***
↑ Anxiety ***
Wellbeing: ↓ ↑ Depression ***
↓ Health ***
‘Lone Rangers’
N = 355 (17.0%)
↑ Work Overload *** Demands: ↑
↑ Emotional Demands ***
↑ Work Int. w/ Home ***
↑ Self Development * Resources: ~↑
↓ Supervisor Support ** Social Support: ↓
↓ Colleague Support *
↓ Spousal Support *
↑ Affective Commitment * Affinity: ↑
↑ Job Involvement ***
↑ Anxiety ***
Wellbeing: ↓ ↑ Depression ***
↓ Health ***
Notes:
(A) Levels of Significance: * p < .05; ** p < .01; *** p < .001
(B) Arrows: ↑ indicates significantly greater levels than the remaining population; ↓indicates
significantly lesser levels than remaining population

25
References
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emerging concept in occupational health psychology. Work Stress, 22(3), 187-200.
doi:10.1080/02678370802393649
Bakker, A.B., & Demerouti, E. (2008). Towards a model of work engagement.
Career Development International, 13(3), 209–223. Emerald, 60/62 Toller Lane,
Bradford, West Yorkshire, BD 8 9 BY, UK,.
Brief, A. P., & Weiss, H. M. (2002). Organizational behavior: affect in the
workplace. Annual review of psychology, 53, 279-307.
doi:10.1146/annurev.psych.53.100901.135156
Demerouti, E., Bakker, A., De Jonge, J., Janssen, P., & Schaufeli, W. (2001).
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Scandinavian Journal of Work, Environment & Health, 27(4), 279-286.
Diez-Pinol, M., Dolan, S. L., Sierra, V., & Cannings, K. (2008). Personal and
organizational determinants of well-being at work: The case of Swedish
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610. doi:10.1108/09526860810900754
Latham, G. P., & Pinder, C. C. (2005). Work motivation theory and research at the
dawn of the twenty-first century. Annual review of psychology, 56, 485-516.
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Lee, R. T., & Ashforth, B. E. (1996). A meta-analytic examination of the correlates
of the three dimensions of job burnout. Journal of Applied Psychology, 81(2), 123.
Schaufeli, W.B., Salanova, M., González-Romá, V., & Bakker, A. B. (2002). The
measurement of engagement and burnout: A two sample confirmatory factor
analytic approach. Journal of Happiness studies, 3(1), 71–92. Springer.

26
Schaufeli, W., Taris, T., Le Blanc, P., Peeters, M., Bakker, A., & De Jonge, J.
(2001). Maakt arbeid gezond? Op zoek naar de bevlogen werknemer (“Does work
make happy? In search of the engaged worker”). De Psycholoog, 36, 422-428.
Schaufeli, Wilmar B., & Bakker, A. B. (2004). Job demands, job resources, and
their relationship with burnout and engagement: a multi-sample study. Journal of
Organizational Behavior, 25(3), 293-315. doi:10.1002/job.248
Schaufeli, Wilmar B., & Van Rhenen, W. (2006). Over de rol van positieve en
negatieve emoties bij het welbevinden van managers: Een studie met de Job-
related Affective Well-being Scale (JAWS) [About the role of positive and negative
emotions in managers‘ well-being: A study using the Jobrelated Affect. Gedrag &
Organisatie, 19, 223-244.
Schaufeli, Wilmar B., Taris, T. W., & van Rhenen, W. (2008). Workaholism,
Burnout, and Work Engagement: Three of a Kind or Three Different Kinds of
Employee Well-being? Applied Psychology, 57(2), 173-203. doi:10.1111/j.1464-
0597.2007.00285.x
Wright, T. a. (2006). The emergence of job satisfaction in organizational behavior:
A historical overview of the dawn of job attitude research. Journal of Management
History, 12(3), 262-277. doi:10.1108/17511340610670179
van Saane, N., Sluiter, J. K., Verbeek, H. A. M., & Frings-Dresen, M. H. W. (2003).
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review. Occupational Medicine, 53(3), 191-200. doi:10.1093/occmed/kqg038

27

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