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ORIGINAL RESEARCH
published: 17 January 2017
doi: 10.3389/fpsyg.2017.00012
Edited by:
Renato Pisanti,
University Niccolò Cusano, Italy
Reviewed by:
Krystyna Golonka,
Jagiellonian University, Poland
Sara Viotti,
University of Turin, Italy
*Correspondence:
Paul Jimenez
paul.jimenez@uni-graz.at
Specialty section:
This article was submitted to
Organizational Psychology,
a section of the journal
Frontiers in Psychology
Received: 30 September 2016
Accepted: 03 January 2017
Published: 17 January 2017
Citation:
Jimenez P and Dunkl A (2017) The
Buffering Effect of Workplace
Resources on the Relationship
between the Areas of Worklife
and Burnout. Front. Psychol. 8:12.
doi: 10.3389/fpsyg.2017.00012
The Buffering Effect of Workplace
Resources on the Relationship
between the Areas of Worklife and
Burnout
Paul Jimenez*and Anita Dunkl
Department of Psychology, University of Graz, Graz, Austria
Background: Workplace resources are found to play a major role in the stress–
strain relationship. However, usually different types of resources are investigated,
whereas investigating different facets of stress (“stressors”) receive less attention in
research about the relationship between stress, strain and resources. Based upon
recent research, we expected that workplace resources moderate the relationship
between stressors (operationalized with the areas of worklife) and long-term strain
(operationalized with three dimensions of burnout) in the sense that workplace resources
buffer the negative effects of stressors on strain.
Method: Hypotheses were tested in a longitudinal sample of 141 Austrian workers, who
participated two times in an online study over a period of 6 months. Hierarchical multiple
regression analysis was used to test the proposed relationships.
Results: The results imply that workload and reward seem to be the most important
predictors for burnout. Workload is important for emotional exhaustion, whereas
reward is important for cynicism. Value-fit at the workplace plays a significant role for
cynicism, but only if resources at the workplace are high. Further moderating effects
of resources were found for the outcome personal accomplishment. More specifically,
results indicate that having high resources in a high workload environment increases
personal accomplishment after a time interval of 6 months. In addition, employees
experiencing high levels of control but low workplace resources show less personal
accomplishment.
Conclusion: Despite the limiting aspects of the relatively short period of time we can
see that resources can buffer workload effects. This should be taken into consideration
when doing risk assessments in practice as work design should focus on resources
even more when high workload can be found.
Keywords: burnout, longitudinal, strain, stress, workplace resources
INTRODUCTION
Workplace resources have an essential influence on the stress–strain relationship. Previous studies
on buffering effect of resources on the stress–strain relationship mainly used a summarized factor
of stress (e.g., high job demands) to predict negative work-related outcomes such as strain. This
more global view of stress only scratches the surface in research on the stress–strain relationship.
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Jimenez and Dunkl The Buffering Effect of Workplace Resources
However, authors emphasize that different types of stress have to
be analyzed to get a better understanding about stress and strain
(Bakker et al., 2005). Paradoxically, research around the stress–
strain framework tends to investigate the moderating effects
of different types of resources (e.g., social support, feedback,
latitude) more deeply than the effects of different stress factors
(e.g., Xanthopoulou et al., 2007;van den Tooren and de Jonge,
2012). Our study focuses on this complex subject and investigates
the effects of different facets of stress (as we will call it later on
synonymously stressors) and their interaction with workplace
resources on strain.
Stress and Strain at the Workplace
In the long tradition of stress research, the terms stress and
strain are often used interchangeably. A strict way to differentiate
between them was introduced in the norm series of the ISO 10075
(ISO, 2000a,b, 2015). As we can see norms as the current status
of scientific knowledge we therefore refer to these definitions
in this text. The norm ISO 10075-1 (ISO, 2000a, p. 3; s.a.
Demerouti et al., 2002;Zoni and Lucchini, 2012), defines mental
stress and strain as follows: mental stress is the “. . .total of all
assessable influences impinging upon a human being from external
sources and affecting that person mentally” and mental strain is
defined as the “. . .immediate effect of mental stress within the
individual depending on their current condition.” Thus, the norm
summarizes the objective stressors under the term “stress” and
the outcome of these stressors (e.g., the individual evaluation
of these stressors) as “strain.” The consequences of strain can
be further differentiated into short-term and long-term effects
of strain. Short-term effects compass mental fatigue, monotony,
satiation and stress sensations (Demerouti et al., 2002). Long-
term effects of strain result from repeated exposure to strain. One
important chronic reaction to prolonged impairing strain would
be burnout which is now mentioned especially in the upcoming
norm of the ISO 10075-1 (ISO, 2015).
The definition of stress is similar to the definition of “job
demands” (Bakker et al., 2005), as job demands are described
as physical, mental, social, or organizational aspects of the
job that require sustained effort/skills and are associated with
physiological and psychological costs (as in the concept of
Meijman and Mulder, 1998). Bakker et al. (2005) emphasize
that job demands are not necessarily negative and can influence
positive outcomes (e.g., engagement) as well.
Stress is a neutral term and does not bear a negative
(or positive) connotation. In the ISO 10075-1 (ISO, 2000a),
stress is seen as a total value that results by summarizing all
influences at the workplace – whether they have negative effects
or not. However, it is possible to distinguish different stressors
that might have different short-term or long-term outcomes.
Rohmert (1984) distinguishes quantifiable and non-quantifiable
stressors. In his view, quantifiable stressors compasses noise,
temperature or air pressure. Non-quantifiable stressors usually
results from working tasks and includes time pressure, monotony
or responsibility.
One classification of stressors is stated in the ISO 10075-
1 (ISO, 2000a, p. 4), which categorizes stress in following
categories: task requirements, physical conditions, social and
organizational factors, and societal factors. The ISO concept
therefore focuses to a system of stressors which can lead to a
variety of possible outcomes, negative but also positive ones.
The main strength of this model lies in the strict distinction
between stressors and the effects. As positive outcomes (e.g.,
practice effects or competence development) are also possible it
is not meaningful to classify stressors as “good” or “bad,” the
consequences of stress are “depending on an individual’s personal
resources and his/her perception of the situation” (Demerouti
et al., 2002, p. 425).
A framework that compasses different stressors which are seen
as potential risk factors especially for burnout can be seen in the
concept of the areas of worklife (Maslach and Leiter, 2008). In
this concept, six domains of the work environment have been
identified that can serve as “organizational risk factors” (Maslach
and Leiter, 2008, p. 500) for negative work-related outcomes, such
as burnout: workload, control, reward, community, fairness, and
values.
The area of workload is described as experiencing qualitative
and quantitative work overload that depletes the person’s capacity
to meet the demands of the job. Control means having sufficient
latitude at work and having possibilities to make important
decisions. Reward refers to financial and non-financial reward
(e.g., recognition from colleagues, supervisors and clients) for the
employees’ work contributions. Community is the overall quality
of social interactions of work. The area of fairness describes
the extent to which decisions at work are perceived as fair.
Finally, values (or value-congruence) describes the match of the
employees’ and organizations’ job goals and expectations (a full
description can be found, e.g., in Maslach and Leiter, 2008).
In all six areas, discrepancies between person and work
environment can occur which are described as mismatch
(Maslach and Leiter, 2008). In other words, these six areas are
able to reveal critical work conditions. On the other hand, they
serve as prevention factors for negative work-related outcomes if
they are evaluated positively (Laschinger et al., 2015;Boamah and
Laschinger, 2016). Especially the area of values is found to have
an essential effect on work-related outcomes such as burnout
(emotional exhaustion, cynicism, and personal accomplishment)
and turnover intention (Leiter and Maslach, 2005, 2009;Leiter
et al., 2009). A conflict between individual and organizational
values leads to less engagement with the tasks, as work is
perceived as personally irrelevant (Leiter and Maslach, 1999).
This reduced involvement depletes the employees’ energy and
contributes to exhaustion and cynicism.
The areas of workload and reward are important predictors
for emotional exhaustion and cynicism, respectively (Leiter and
Maslach, 2009). A lack of (financial or non-financial) reward
leads to feelings of inefficacy and meaninglessness and this in turn
contributes to cynicism (Cartwright and Holmes, 2006). High
workload prevents employees from adequate recovery which is a
critical factor for fatigue and exhaustion (Sonnentag et al., 2010).
Especially the relationship between workload and emotional
exhaustion is rather persistent and stable over time, which means
that high workload at one point is able to predict emotional
exhaustion even after a long period of time (Michielsen et al.,
2004).
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The extent of short-term and long-term outcomes of stress
depends on moderating variables, such as personal or workplace
resources. In the ISO 10075-1 (ISO, 2000a), the current condition
of the individual is highlighted, which is dependent on the
individual’s workplace resources. Next to individual resources,
workplace resources (or “job resources”) have received much
attention in research about outcomes of stress (Karasek, 1979;
Bakker et al., 2005). Indeed, targeting workplace resources is
a sustainable way to prevent negative outcomes of stress as
workplace resources seem to be the precursor of individual
resources such as employees’ self-efficacy, self-esteem, and
optimism (Xanthopoulou et al., 2007).
The Role of Resources at the Workplace
Resources in the working context refer to the physical,
psychological, social, or organizational aspects of the job that
are able to reduce job demands, stimulate personal growth,
learning and development and/or are functional in achieving
work goals (Bakker and Demerouti, 2007). Resources at the
workplace play a major role in the relationship between stress and
strain (Demerouti et al., 2002) and have been studied in a variety
of different frameworks: the demand-control model (Karasek,
1979), the effort-reward imbalance model (Siegrist, 1996), the
job demands-resources (JD-R) model (Bakker and Demerouti,
2007), and the resources/recovery-stress model (Kallus and
Kellmann, 2000;Kallus, 2016). Following the demand-control
model, aspects of job control (e.g., latitude, autonomy) buffer the
effect of stress on strain. In the effort-reward imbalance model,
the important job resource is reward (e.g., salary, promotion,
job security or esteem reward) that may buffer the critical
relationship between stress and strain.
The important role of resources is also illustrated in Hobfoll’s
(1989) conservation of resources (COR) model. This model
proposes that strain is a result of a threat to resources, actual loss
of resources or insufficient gain of additional resources. Any of
these three paths can cause strain and might lead to burnout over
time.
In the JD-R model (Bakker and Demerouti, 2007), negative
outcomes of stress can be decreased if job resources are high. In
contrast to Karasek’s (1979) or Siegrist’s (1996) model, the JD-R
model does not limit resources to one aspect (e.g., job control or
reward) but expands the view of resources to a variety of states.
Indeed, examples of job resources can be found on many levels,
such as on the organizational level (e.g., career opportunities,
salary), on the interpersonal level (e.g., social support from
colleagues or supervisor) or on the task/work level (e.g., skill
variety, participation possibilities) (Bakker et al., 2007). When a
sufficient amount of job resources is available, it is even possible
to have positive effects of stress in the sense of challenging jobs
(Bakker et al., 2010). This again is in line with the model in the
ISO 10075-1.
Kallus’ (2016) resources/recovery-stress model assumes that
workplace stress can be especially harmful and lead to negative
outcomes if the relation between stress and recovery/resources
is imbalanced. In his view the terms recovery and resources
are used as nearly interchangeably. If a person experiences high
stress, this stress can lead to strain depending on the person’s
individual resources and depending on the person’s recovery
processes to strengthen resources. In this model, resources are
able to buffer the relation between stress and strain only if they
have been recovered. This view is also shared by Oerlemans and
Bakker (2014), where resources have to be replenished regularly
to show stress-reducing effects. Therefore, the availability and
state of resources must increase to the same extent as stress to
cope successfully with the situation. This is in line with the COR
model, where negative outcomes occur if work demands are high
and resources have not been adequately replenished (Freedy and
Hobfoll, 1994). Especially resources on the task level (latitude
and autonomy) and on the interpersonal level (social support)
have been found to reduce the negative effects of stress on strain
(Halbesleben, 2006;Nahrgang et al., 2011). In the present study,
we conceptualize workplace resources as a combination of task
level and interpersonal level resources.
Theoretical Model and Hypotheses
The research reported in this article used a longitudinal research
design to investigate the relationship between stress, workplace
resources and outcomes of stress. To measure stress, we use the
concept of the areas of worklife (Maslach and Leiter, 2008), which
is a framework that compasses six different stressors (workload,
control, reward, community, fairness, and values). Stress is often
measured as a total value by summarizing many workplace
stressors (e.g., as “demands,” Hakanen et al., 2008;Trépanier et al.,
2014). In our study we want to measure stress deeper in different
facets; therefore, we focus on stressors described in the concept
of the areas of worklife. In addition, we analyze the effects of
stress at two time points (after 6 months), thus testing the causal
relationship between stress and strain.
According to the ISO 10075-1 (ISO, 2000a), the immediate
outcome of stress would be strain. However, we are more
interested in the long-term effects of stress; therefore, the concept
of burnout is used to operationalize the outcome of stress,
which is a result from repeated exposure to strain (ISO, 2000a;
Demerouti et al., 2002).
On basis of the studies conducted by Leiter and Maslach (2005,
2009) regarding the areas of worklife, following hypotheses are
stated:
H1: The area of workload is a significant predictor for
Emotional Exhaustion.
H2: The area of reward is a significant predictor for Cynicism.
H3: The area of values is negatively associated with Emotional
Exhaustion and Cynicism and positively associated with
Personal Accomplishment.
In line with the JD-R model and the resources/recovery-stress
model, we hypothesize that workplace resources are negatively
related to burnout and are able to buffer the negative effect of
stressors (measured with the six areas of worklife) on burnout.
H4: Workplace resources are negatively related to emotional
exhaustion and cynicism and positively related to
personal accomplishment.
H5: Workplace resources moderate the negative relation
between stressors (measured with the areas of
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worklife) and emotional exhaustion/cynicism such
as the relationship is weaker for employees with high
workplace resources.
H6: Workplace resources moderate the positive relation
between stressors (measured with the areas of worklife)
and personal accomplishment such as the relationship is
stronger for employees with high workplace resources.
The main strengths of the present study lie in the differentiated
view of stress by investigating the effects of different stressors
and in the longitudinal design to detect causal relationships. In
addition, moderating effects of workplace resources are tested
cross-sectionally and longitudinally to gain better insight in the
short-term and long-term buffering role of workplace resources
in the stress–strain relationship.
MATERIALS AND METHODS
Participants and Procedure
The data were collected as part of a larger longitudinal study
conducted among Austrian workers. For this study, persons
were recruited from other studies executed at the Department
of Psychology at the University of Graz and were asked for their
consent to contact them again for future studies. The approval of
the ethical commission was obtained before the start of the whole
longitudinal study. The first measurement took place in spring
and the second in autumn. The measurement times were carefully
chosen to avoid holiday seasons. The time interval between the
single measurement points was 6 months. The two measurement
points are referred to as Time 1 (T1) and Time 2 (T2).
At T1, 626 participants filled-in all questionnaires in the
online survey. At T2, 439 participants took part. The final sample
consisted of 141 participants that took part at both measurement
points and also were at the same workplace at both times. Of
these 141 respondents, 61% were female (male: 39%) and their
mean age was 43.7 years (SD =9.04). The majority worked full-
time or more (83.7%), 16.3% worked part-time. The participants
worked in different industrial sectors, mostly from health sector
(19.9%), manufacturing (12.1%), public sector (11.3%), and
general services (9.2%). To analyze a possible drop-out bias,
participants who participated in T1 were compared to those
who participated in both waves. The analysis revealed that both
groups did differ significantly in their experience of workplace
resources (p<0.05). More specifically, workplace resources were
higher in the group that participated in both waves compared to
participants who participated only in T1. For all other variables,
no significant effects were found.
Measures
Areas of Worklife
The Areas of Worklife Scale (AWS; Leiter and Maslach, 1999)
measures six different areas of worklife: (1) workload, (2) control,
(3) reward, (4) community, (5) fairness and (6) values. The
participants are asked to answer 29 items on a 5-point Likert-
Scale ranging from 1 (strongly disagree) to 5 (strongly agree).
One example item for the area of control is “I have professional
autonomy/independence in my work” and one example item for
the area of values is “My values and the organization’s values are
alike.” The German translation by Schulze (see Brom et al., 2015)
was used in this study.
Workplace Resources
The Recovery-Stress-Questionnaire for Work (RESTQ-Work;
Jiménez and Kallus, 2016) assesses different aspects of stress and
recovery activities and states in the past 7 days/nights. In the
present study, the short version of the RESTQ-Work (RESTQ-
Work-27) with 27 items was used. The items can be assigned to a
stress or recovery/resources score. In the present study, only the
workplace resources score without recovery aspects was analyzed
(Jiménez et al., 2016a). The workplace resources score consists
of three sub-dimensions, each measuring another type of work-
related resources (leisure/breaks, psychosocial resources, work-
related resources). The RESTQ-Work-27 allows giving feedback
by using the stress and resources scores. The underlying sub-
dimensions can only be used for screening purposes in the
practical field (Jiménez et al., 2016a). One example item for the
resources score is “In the past 7 days/nights. . . I was able to
relax during my breaks” or “In the past 7 days/nights. . . I had
the chance to work on a variety of tasks.” The answer scale is a
7-point-Likert-Scale ranging from 0 (never) to 6 (always).
Burnout
The Maslach-Burnout-Inventory – General Survey (MBI-GS;
Schaufeli et al., 1996) measures burnout with three dimensions:
emotional exhaustion, cynicism, and personal accomplishment.
In the present study, the German version of the MBI-GS by
Büssing and Glaser (1998) was used. The 16 items can be
answered on a 7-point-Likert-Scale ranging from 0 (never) to 6
(every day).
Analysis
With regard to analyses, we used bivariate correlation and
hierarchical regression analyses. Hierarchical multiple linear
regression analyses were performed for each dependent variable
(emotional exhaustion, cynicism, personal accomplishment) and
were conducted for the cross-sectional sample (at T1) and the
longitudinal sample. In the longitudinal analysis, the dependent
variable at T1 was controlled for all outcomes. To analyze the
interaction between the variables, the interaction terms first were
mean-centered (z-transformed) to minimize multicollinearity
and then entered in the regression analysis. The data was analyzed
using SPSS Version 22.
RESULTS
Descriptive Statistics
Descriptive statistics (means and standard deviations) all study
variables are shown in Table 1. The descriptive statistics were
calculated for both measurement points separately. The data for
workplace resources and the three burnout dimensions were
compared to the data of a representative Austrian sample,
collected in 2015 (Jiménez et al., 2016b). Compared to the
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TABLE 1 | Means (M) and standard deviations (SD) of all study variables.
Variable Time 1 (T1) Time 2 (T2) Austrian representative
sample
Longitudinal sample
(N=141)
All responses
(N=468)
Longitudinal sample
(N=141)
All responses
(N=402)
(N=1200)
M SD M SD M SD M SD M SD
Workload 3.25 0.92 3.35 0.90 3.23 0.96 3.34 0.99 2.76 0.88
Control 3.46 0.89 3.45 0.98 3.30 1.10 3.38 1.03 3.40 1.03
Reward 3.07 0.86 3.07 0.84 2.88 0.83 2.95 0.87 3.32 0.98
Community 3.28 0.87 3.23 0.82 3.52 0.80 3.33 0.88 3.34 0.80
Fairness 2.85 0.93 2.89 0.85 2.77 0.94 2.77 0.90 3.05 0.80
Values 3.45 0.81 3.38 0.84 3.31 0.71 3.31 0.79 3.44 0.81
Workplace resources 2.96 0.98 2.87 0.97 3.08 1.11 3.08 1.09 3.28 1.16
Emotional exhaustion 3.83 1.22 3.95 1.20 3.76 1.24 3.87 1.22 3.23 1.30
Cynicism 3.34 1.26 3.38 1.25 3.36 1.34 3.28 1.33 2.97 1.28
Personal accomplishment 4.66 0.86 4.61 0.84 4.62 0.83 4.61 0.82 4.71 0.83
Note 1: areas of worklife at T2: N =148 (all responses) and N =53 (longitudinal sample).
representative Austrian sample, the study sample showed higher
values in workload, emotional exhaustion and cynicism and
lower values in fairness and workplace resources (see Table 1).
Intercorrelations between variables for T1 and T2 (cross-
sectional and longitudinal) as well as internal consistencies
(Cronbach’s Alpha, α) are shown in Table 2.
Cross-Sectional Sample
To test the proposed hypotheses, hierarchical multiple linear
regression analyses were conducted for the cross-sectional
sample (at T1) and the longitudinal sample. In Table 3,
the results for T1 are depicted. In the first step, the areas
of worklife were stepped into the equation, which was
significant for all models (1R2emotional exhaustion =0.55;
1R2cynicism =0.57, 1R2personal accomplishment =0.37).
The second step included workplace resources, which
significantly accounted for an additional variance for all
outcomes (1R2emotional exhaustion =0.04; 1R2cynicism =0.05,
1R2personal accomplishment =0.07). The third step included
the interaction terms, which were non-significant for all
models.
Out of the areas of worklife, the areas of reward and values
showed to be the most important predictors for all three
dimensions of burnout. The area of workload was significant
for the criteria emotional exhaustion and cynicism. Workplace
resources were negatively related to emotional exhaustion and
cynicism and positively related to personal accomplishment. As
for the interactions between the areas of worklife and workplace
resources, only the interaction between workload and workplace
resources was significant for the outcome variable emotional
exhaustion. More specifically, the buffering effect of resources
seems to work better in an environment with low workload, as
low workload combined with high resources has the lowest level
of emotional exhaustion (Figure 1).
The standardized regression coefficients (β) as well as p-values
and 1R2are presented in Table 3.
Longitudinal Sample
Table 4 present the four steps of the analyses. The dependent
variables at T1 were stepped into the equation first. This step
was significant for all models (1R2emotional exhaustion =0.54;
1R2cynicism =0.43, 1R2personal accomplishment =0.44). This step
was followed by the six areas of worklife (step 2). The
first step accounted for an additional variance for cynicism
(1R2cynicism =0.06). The third step included workplace
resources, which was non-significant for all outcomes. In the
fourth and last step, the interaction terms were included. This
step was not significant for all outcomes.
Workload showed to be the most important predictor for
emotional exhaustion at T2 and reward was an important
predictor for cynicism at T2 (hypotheses 1 and 2). The other
areas of worklife did not show significant results with all three
dimensions of burnout at T2. Contrary to hypothesis 3, resources
at the workplace did not show any direct relationships with all
three outcome variables.
Out of all interactions, only one was significant: the interaction
between workload and workplace resources was significant
for personal accomplishment. More specifically, high workload
paired with high workplace resources at T1 lead to higher
personal accomplishment at T2 (Figure 2). As for emotional
exhaustion and cynicism, none of the proposed interactions
showed significant results.
The standardized regression coefficients (β) as well as p-values
and 1R2are presented in Table 4.
DISCUSSION
This study explored the relationship between stressors, workplace
resources and burnout as the long-term outcome of stress. We
investigated which stressors are linked to burnout and if resources
are able to buffer the negative effect of stress facets on burnout.
The six areas of worklife (Maslach and Leiter, 2008) were used
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TABLE 2 | Correlations and internal consistencies (Cronbach’s alpha) between all study variables (Time 1 and Time 2; N=141).
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Time 1 (T1)
(1) Workload 0.85
(2) Control −0.33∗∗∗ 0.80
(3) Reward −0.39∗∗∗ 0.36∗∗∗ 0.83
(4) Community −0.32∗∗∗ 0.27∗∗∗ 0.41∗∗∗ 0.88
(5) Fairness −0.29∗∗∗ 0.43∗∗∗ 0.45∗∗∗ 0.50∗∗∗ 0.89
(6) Values −0.28∗∗∗ 0.39∗∗∗ 0.49∗∗∗ 0.45∗∗∗ 0.74∗∗∗ 0.81
(7) Workplace
resources
−0.44∗∗∗ 0.55∗∗∗ 0.63∗∗∗ 0.53∗∗∗ 0.51∗∗∗ 0.45∗∗∗ 0.87
(8) Emotional
exhaustion
0.65∗∗∗ −0.45∗∗∗ −0.57∗∗∗ −0.27∗∗∗ −0.38∗∗∗ −0.40∗∗∗ −0.61∗∗∗ 0.91
(9) Cynicism 0.53∗∗∗ −0.47∗∗∗ −0.70∗∗∗ −0.46∗∗∗ −0.56∗∗∗ −0.59∗∗∗ −0.67∗∗∗ 0.71∗∗∗ 0.86
(10) Personal
accomplishment
−0.25∗∗∗ 0.48∗∗∗ 0.62∗∗∗ 0.33∗∗∗ 0.44∗∗∗ 0.50∗∗∗ 0.65∗∗∗ −0.52∗∗∗ −0.67∗∗∗ 0.86
Time 2 (T2)
(11) Workload 0.65∗∗∗ −0.13 −0.02 −0.03 −0.06 0.00 −0.02 0.31∗0.21 0.06 0.86
(12) Control −0.17 0.60∗∗∗ 0.13 0.23 0.29∗0.29∗0.50∗∗∗ −0.30∗−0.36∗∗ 0.39∗∗ −0.37∗∗ 0.89
(13) Reward −0.10 0.23 0.53∗∗∗ 0.04 0.33∗0.37∗∗ 0.30∗−0.17 −0.36∗∗ 0.33∗−0.14 0.34∗0.73
(14)
Community
−0.13 0.26 0.10 0.67∗∗∗ 0.37∗∗ 0.41∗∗ 0.45∗∗∗ 0.05 −0.14 0.32∗−0.20 0.41∗∗ 0.22 0.89
(15) Fairness −0.15 0.42∗∗ 0.40∗∗ 0.33∗0.81∗∗∗ 0.62∗∗∗ 0.47∗∗∗ −0.27 −0.56∗∗∗ 0.54∗∗∗ −0.23 0.53∗∗∗ 0.45∗∗∗ 0.42∗∗ 0.88
(16) Values −0.09 0.34∗0.14 0.20 0.56∗∗∗ 0.66∗∗∗ 0.29∗−0.03 −0.46∗∗∗ 0.30∗−0.30∗0.55∗∗∗ 0.44∗∗ 0.42∗∗ 0.68∗∗∗ 0.72
(17)
Workplace
resources
−0.36∗∗∗ 0.41∗∗∗ 0.53∗∗∗ 0.44∗∗∗ 0.46∗∗∗ 0.43∗∗∗ 0.75∗∗∗ −0.57∗∗∗ −0.52∗∗∗ 0.56∗∗∗ −0.17 0.76∗∗∗ 0.39∗∗ 0.55∗∗∗ 0.52∗∗∗ 0.49∗∗∗ 0.91
(18) Emotional
exhaustion
0.58∗∗∗ −0.37∗∗∗ −0.47∗∗∗ −0.24∗∗∗ −0.38∗∗∗ −0.38∗∗∗ −0.47∗∗∗ 0.73∗∗∗ 0.55∗∗∗ −0.40∗∗∗ 0.66∗∗∗ −0.48∗∗∗ −0.38∗−0.22 −0.29∗−0.38∗∗ −0.60∗∗∗ 0.91
(19) Cynicism 0.39∗∗∗ −0.36∗∗∗ −0.56∗∗∗ −0.30∗∗∗ −0.49∗∗∗ −0.53∗∗∗ −0.52∗∗∗ 0.60∗∗∗ 0.66∗∗∗ −0.48∗∗∗ 0.41∗∗ −0.67∗∗∗ −0.59∗∗∗ −0.37∗∗ −0.59∗∗∗ −0.66∗∗∗ −0.68∗∗∗ 0.73∗∗∗ 0.92
(20) Personal
accomplishment
−0.17∗0.30∗∗∗ 0.45∗∗∗ 0.20∗0.30∗∗∗ 0.35∗∗∗ 0.45∗∗∗ −0.35∗∗∗ −0.40∗∗∗ 0.67∗∗∗ −0.12 0.65∗∗∗ 0.49∗∗∗ 0.48∗∗∗ 0.52∗∗∗ 0.52∗∗∗ 0.68∗∗∗ −0.47∗∗∗ −0.62∗∗∗ 0.84
∗p<0.05, ∗∗p<0.01, ∗∗∗ p<0.001; Cronbach’s alpha (α) in the diagonal; areas of worklife at T2: N =53.
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TABLE 3 | Cross-sectional, hierarchical multiple regression analysis for all predicted variables at Time 1 (T1).
Emotional exhaustion T1 Cynicism T1 Personal accomplishment T1
Step and variable βp1R2βp1R2βp1R2
Step 1: Areas of worklife 0.55∗∗∗ 0.57∗∗∗ 0.37∗∗∗
Workload T1 0.50∗∗∗ <0.001 0.16∗∗∗ <0.001 −0.02 0.663
Control T1 −0.01 0.829 −0.02 0.555 0.06 0.184
Reward T1 −0.16∗∗∗ <0.001 −0.27∗∗∗ <0.001 0.23∗∗∗ <0.001
Community T1 0.00 0.985 −0.01 0.853 −0.03 0.465
Fairness T1 0.07 0.131 −0.01 0.898 −0.10∗0.050
Values T1 −0.10∗0.017 −0.25∗∗∗ <0.001 0.22∗∗∗ <0.001
Step 2: 0.04∗∗∗ 0.05∗∗∗ 0.07∗∗∗
Workplace resources T1 −0.26∗∗∗ <0.001 −0.32∗∗∗ <0.001 0.39∗∗∗ <0.001
Step 3: 0.01 0.00 0.01
Workload T1 ×Workplace resources T1 0.08∗0.032 0.02 0.627 0.04 0.363
Control T1 ×Workplace resources T1 −0.01 0.835 −0.02 0.725 −0.05 0.284
Reward T1 ×Workplace resources T1 0.05 0.216 −0.01 0.869 0.00 0.952
Community T1 ×Workplace resources T1 0.01 0.895 −0.00 0.961 −0.03 0.582
Fairness T1 ×Workplace resources T1 −0.00 0.951 −0.01 0.773 −0.01 0.817
Values T1 ×Workplace resources T1 0.02 0.707 0.06 0.210 0.02 0.663
The (standardized) beta values (β) are the coefficients from the finale stage of the analysis; ∗p<0.05, ∗∗p<0.01, ∗∗∗ p<0.001.
to operationalize stressors. Our hypotheses could be partially
verified.
As stated in hypothesis 1, workload is a significant predictor
for emotional exhaustion. The relationship between workload
on emotional exhaustion is also evident after 6 months, which
supports the assumption that high workload causes emotional
exhaustion in the long run. High workload has been repeatedly
associated with emotional exhaustion (Maslach et al., 2001;Leiter
and Maslach, 2009). Constant high workload creates a work
environment where employees don’t have time to recover from
work demands. This depletes the employees’ capacity to meet
work demands and creates long-lasting fatigue and exhaustion.
Interestingly, high workload seems to be negatively related to
cynicism, indicating that working in an environment with high
workload, cynicism is low. However, this effect is no longer visible
after 6 months.
The area of reward is related to all dimensions of burnout,
but seems to be a strong preventive factor for cynicism even
after 6 months. This supports our second hypothesis as well
as the findings of Maslach and Leiter (2008). A lack of reward
contributes to feelings of inefficacy and meaninglessness which
can be precursors for cynicism.
In past research, values showed to be one of the strongest
predictors to prevent burnout as it directly affects emotional
exhaustion, cynicism, and personal accomplishment (Leiter and
Maslach, 2009). In the present study, we could replicate this
assumption only in the cross-sectional analysis. Longitudinally,
values are not related to burnout after 6 months, therefore
hypothesis 3 was only supported in the cross-sectional sample.
Regarding workplace resources, we expected workplace
resources to be an important predictor for all three burnout
dimensions (hypothesis 4), which was supported in the cross-
sectional analyses. However, the direct, positive effect of
workplace resources on burnout is not found after 6 months.
Furthermore, we expected workplace resources to be a buffer
between stressors and burnout (hypotheses 5 and 6). We found
a moderating effect of resources for the relationship between
workload and emotional exhaustion. In a work environment
with low workload, employees can access their resources more
easily and thus the buffering effect of resources can take place.
However, this effect was very small and was not replicated in the
longitudinal sample. The JD-R model (Bakker and Demerouti,
2007), and the resources/recovery-stress model (Kallus, 2016)
state that the negative relationship between stress and strain
should be weaker if workplace resources are high. However, this
buffering effect can only take place if workplace resources are
strengthened parallel with increasing stress. In other words, very
high stress demands a high recovery of resources to keep the
FIGURE 1 | Two-way interaction between workload (T1) and workplace
resources (T1) on emotional exhaustion (T1).
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TABLE 4 | Hierarchical multiple regression analysis for all predicted variables (T1–T2).
Emotional exhaustion Time 2 Cynicism Time 2 Personal accomplishment Time 2
Step and variable βp1R2βp1R2βp1R2
Step 1 0.54∗∗∗ 0.43∗∗∗ 0.44∗∗∗
Dependent variable T1 0.52∗∗∗ <0.001 0.37∗∗∗ 0.001 0.65∗∗∗ <0.001
Step 2: Areas of worklife 0.03 0.06∗0.01
Workload T1 0.17∗0.038 0.03 0.730 0.04 0.646
Control T1 −0.02 0.828 0.04 0.628 −0.09 0.264
Reward T1 −0.08 0.356 −0.19∗0.041 0.08 0.380
Community T1 0.02 0.755 0.11 0.163 −0.05 0.566
Fairness T1 −0.06 0.505 −0.08 0.421 −0.04 0.712
Values T1 0.02 0.821 −0.08 0.445 0.03 0.779
Step 3: 0.00 0.01 0.00
Workplace resources T1 −0.02 0.825 −0.16 0.125 0.15 0.196
Step 4: 0.02 0.04 0.05
Workload T1 ×Workplace resources T1 0.08 0.334 0.00 0.983 0.22∗∗ 0.010
Control T1 ×Workplace resources T1 −0.02 0.849 0.05 0.541 0.04 0.686
Reward T1 ×Workplace resources T1 0.09 0.344 0.17 0.094 −0.02 0.840
Community T1 ×Workplace resources T1 0.14 0.087 0.11 0.220 −0.12 0.162
Fairness T1 ×Workplace resources T1 −0.18 0.126 −0.15 0.225 0.12 0.344
Values T1 ×Workplace resources T1 −0.02 0.877 −0.16 0.192 0.15 0.251
The (standardized) beta values (β) are the coefficients from the finale stage of the analysis; ∗p<0.05, ∗∗p<0.01, ∗∗∗ p<0.001.
balance (Kallus, 2016). In a work environment with long-lasting
stress, workplace resources might be difficult to utilize or might
even be depleted to an extent that they cannot be replenished
anymore (see also Freedy and Hobfoll, 1994).
In line with hypothesis 6, we found a moderating effect
of resources for workload on personal accomplishment. More
specifically, high workload seems to be able to enhance personal
accomplishment if workplace resources are high. This is in
line with the JD-R model, where working in a high workload
environment does not have harmful effects when workplace
resources are high. In our study, workplace resources even
show a beneficial effect, as working in a high workload
environment contributes to personal accomplishment when
workplace resources are high. The demand-control model
(Karasek, 1979) categorizes high demands paired with high
resources as “active jobs” and these are characterized with high
engagement.
The effects found in the present study are small and do
not fully support the buffering effect of workplace resources
between stressors and burnout. However, the findings should
not be neglected. In the present sample, the participants had
much higher values in workload and burnout and lower values
in workplace resources compared to the Austrian norm sample.
For workload and burnout, we have a “ceiling effect” where
significant differences are difficult to detect. Therefore, we suggest
interpreting the results in the direction of a buffering effect of
workplace resources, although we must point out that this result
has to be interpreted with high caution.
In the study of Maslach and Leiter (2008), employees
experiencing problems with fairness at the workplace were
especially vulnerable to develop burnout over time. Interestingly,
our analyses revealed a negative relation between fairness and
personal accomplishment at T1, indicating that high fairness at
the workplace is associated with lower personal accomplishment.
In the simple bivariate correlation, the relationship is positive,
though. As we used multiple regression analysis, confounding
effects of predictor variables are considered and gives a
better representation of the relationship between predictor and
outcome. The effect is very small and no longer apparent
after 6 months, though. Nevertheless, future studies should be
conducted to shed light on this unexpected result.
The area of community was not related to burnout at T2,
although research provides evidence that social support at work
is related to a lower burnout-risk (e.g., Halbesleben, 2006). The
same applies for control. Aspects of control (e.g., autonomy,
participation possibilities, latitude) were not directly related to
FIGURE 2 | Two-way interaction between workload (T1) and workplace
resources (T1) on personal accomplishment (T2).
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Jimenez and Dunkl The Buffering Effect of Workplace Resources
burnout in our study. In their mediation model of job burnout,
Leiter and Maslach (2005,2009) showed that community and
control are not directly related to burnout but show indirect
relations through values (for community) and through workload
(for control). Therefore, all areas of worklife play important roles
for burnout, either directly or indirectly through mediation.
Methodological Issues
An important point of this study lies in the investigation of
different types of stress (stressors) instead of using one global
indicator of stress. By analyzing different stressors together with
different types of resources, the complex interaction between
stressors and resources could be investigated much more deeply.
In the present study, we used a global indicator of resources as
the questionnaire used in this study (RESTQ-Work-27; Jiménez
et al., 2016a) only allows building a global score of resources.
In future studies, different types of stressors and resources
should be assessed to get a deeper understanding in the complex
interactions at the workplace.
Same-source bias is a possible limitation of the study. We
collected data at different points in time, a practice suggested by
Podsakoff and Organ (1986) to reduce the effects of common
method bias. Nevertheless, it is possible to take objective
indicators for work environment for the analyses (e.g., sickness
absences, accident statistics), but these are usually difficult to
obtain as companies are hesitant to hand over sensitive data.
As the online survey was declared as “stress study” and open
for every interested person, a self-selection bias could occur.
Comparing the values of the study sample with a representative
sample of Austrian workers, the study sample consists of persons
with more burnout and higher stress. This “ceiling effect” has not
just drawbacks but also “advantages” in the more conservative
sense of research: It is even more difficult to detect significant
effects if a ceiling effect is present.
A reason for not finding more longitudinal effects may lie in
the time interval of 6 months. It seems plausible to assume that
for a health indicator such as burnout, which is considered as
relatively stable, permanent changes are not easily achieved but
require an exposure over a longer time interval. This assumption
is supported by other analyses where effects over a period of
1 year were found (Maslach and Leiter, 2008). Non-significant
results also could be due to lack of power because of our small
sample size. We therefore emphasize that some coefficients are
not significant yet substantial in absolute value, so we do not
claim that there is no effect in this case.
Practical Implications and Conclusion
The findings in the presented study show small effects
for the buffering effect of workplace resources on the
relationship between stress and the long-term consequence,
burnout. In the cross-sectional sample, workplace resources
seem to be important prevention factors for burnout, but
moderating effects with stressors are still weak. As for the
longitudinal effects, more data are needed to investigate this
relationship further. Our study includes effects after half a
year, but extending the research for longer time periods is
needed.
Nevertheless, we stress that workplace resources are
important and so it has to be looked on short- and long term
effects of resources. In the practical field of risk assessment,
assessing workplace resources together with stressors is
sometimes overlooked but important to develop sustainable
interventions. The stress-strain chain which is the base of
risk analysis and the design of workplaces (ISO, 2000b)
has to include the stressors as well as buffering aspects
especially (Portuné, 2012;Zoni and Lucchini, 2012). For the
risk of burnout – which is seen as a long-term impairing
effect of stressors (Demerouti et al., 2002;ISO, 2015) –
especially the time aspect must be considered in combination
with different stressors. Looking at workplaces with high
workload for sure the rule of work design means that at first
the work environment has to be changed (Portuné, 2012).
Especially for these workplaces possible workplace resources
should be taken into account when workplace design is
considered.
ETHICS STATEMENT
This study was carried out in accordance with the
recommendations of the guidelines of the Ethics commission
of the University of Graz with written informed consent from
all subjects. All subjects gave written informed consent in
accordance with the Declaration of Helsinki. The protocol was
approved by the Ethics commission of the University of Graz
from 02.03.2012.
AUTHOR CONTRIBUTIONS
PJ and AD designed the study; conducted research and analyzed
the data; AD and PJ wrote and edited the article.
FUNDING
This publication was printed with the financial support of the
University of Graz.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2017 Jimenez and Dunkl. This is an open-access article distributed
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