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This study of 805 Finnish teachers working in elementary, secondary, and vocational schools tested 2 interaction hypotheses. On the basis of the job demands–resources model, the authors predicted that job resources act as buffers and diminish the negative relationship between pupil misbehavior and work engagement. In addition, using conservation of resources theory, the authors hypothesized that job resources particularly influence work engagement when teachers are confronted with high levels of pupil misconduct. In line with these hypotheses, moderated structural equation modeling analyses resulted in 14 out of 18 possible 2-way interaction effects. In particular, supervisor support, innovativeness, appreciation, and organizational climate were important job resources that helped teachers cope with demanding interactions with students.
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Job Resources Boost Work Engagement, Particularly When Job Demands
Are High
Arnold B. Bakker
Erasmus University Rotterdam Jari J. Hakanen
Finnish Institute of Occupational Health
Evangelia Demerouti
University of Utrecht and Research Institute of Psychology and
Despoina Xanthopoulou
Erasmus University Rotterdam
This study of 805 Finnish teachers working in elementary, secondary, and vocational schools tested 2
interaction hypotheses. On the basis of the job demands–resources model, the authors predicted that job
resources act as buffers and diminish the negative relationship between pupil misbehavior and work
engagement. In addition, using conservation of resources theory, the authors hypothesized that job
resources particularly influence work engagement when teachers are confronted with high levels of pupil
misconduct. In line with these hypotheses, moderated structural equation modeling analyses resulted in
14 out of 18 possible 2-way interaction effects. In particular, supervisor support, innovativeness,
appreciation, and organizational climate were important job resources that helped teachers cope with
demanding interactions with students.
Keywords: conservation of resources, job demands–resources model, teachers, work engagement
Several studies have shown that disruptive student behavior is
an important predictor of teachers’ strain (e.g., Boyle, Borg, Fal-
zon, & Baglioni, 1995; Evers, Tomic, & Brouwers, 2004; Kin-
nunen & Salo, 1994). For example, Burke, Greenglass, and
Schwarzer (1996), in their longitudinal study of 362 teachers and
school administrators, found that in addition to red tape and lack of
supervisor support, confrontation with disruptive students was an
important predictor of burnout over a 1-year interval. This suggests
that pupil misconduct undermines the work engagement many
idealistic teachers start with (Serow, 1994).
The central aim of the present study was to investigate the role
of job resources in this process. We used the job demands–
resources (JD-R) model (Bakker & Demerouti, 2007; Demerouti,
Bakker, Nachreiner, & Schaufeli, 2001) to examine the potential
buffering role of job resources in the relationship between pupil
misbehavior and work engagement. In addition, we used conser-
vation of resources theory (Hobfoll, 1989, 2002) to test the coping
hypothesis that job resources are particularly relevant when teach-
ers are confronted with high job demands.
What Is Work Engagement?
Engagement is defined as a positive, fulfilling, work-related
state of mind that is characterized by vigor, dedication, and ab-
sorption (Schaufeli & Bakker, 2004; Schaufeli, Salanova,
Gonza´lez-Roma´, & Bakker, 2002). Vigor refers to high levels of
energy and mental resilience while working, the willingness to
invest effort in one’s work, and persistence in the face of difficul-
ties. Dedication refers to a sense of significance, enthusiasm,
inspiration, pride, and challenge. The third dimension of work
engagement is called absorption, which was found to be another
element of engagement in 30 in-depth interviews (Schaufeli et al.,
2001). Absorption is characterized by being fully concentrated and
happily engrossed in one’s work, whereby time passes quickly and
one has difficulties with detaching oneself from work.
Building on the earlier ethnographic work of W. A. Kahn
(1990), who conceptualized engagement at work as “the harness-
ing of organizational members’ selves to their work roles” (p.
694), May, Gilson, and Harter (2004) introduced a three-
dimensional concept of engagement similar to the one described
earlier. Although their labels differ slightly, their operationaliza-
tion is strikingly similar (Schaufeli & Salanova, in press). More
specifically, May et al. distinguished between a physical compo-
nent (e.g., “I exert a lot of energy performing my job”), an
emotional component (e.g., “I really put my heart into my job”),
and a cognitive component (e.g., “Performing my job is so absorb-
ing that I forget about everything else”), which correspond to
Schaufeli and Bakker’s (2004) dimensions of vigor, dedication,
and absorption, respectively.
Several studies have indicated that work engagement has posi-
tive consequences at the individual and organizational levels. For
instance, in their weekly diary study among 54 starting teachers,
Bakker and Bal (2006) found that daily levels of work engagement
were predictive of classroom performance. In addition, Hakanen,
Bakker, and Schaufeli (2006) showed that work engagement has
predictive value for teachers’ organizational commitment (see also
Schaufeli & Bakker, 2004). Work engagement among Finnish
educational staff was positively associated with self-rated health
Arnold B. Bakker and Despoina Xanthopoulou, Department of Work
and Organizational Psychology, Erasmus University Rotterdam, Rotter-
dam, The Netherlands; Jari J. Hakanen, Centre of Expertise for Work
Organizations, Finnish Institute of Occupational Health, Helsinki, Finland;
Evangelia Demerouti, Department of Social and Organizational Psychol-
ogy, University of Utrecht, and Research Institute of Psychology and
Health, Utrecht, The Netherlands.
Correspondence concerning this article should be addressed to Arnold
B. Bakker, Erasmus University Rotterdam, Institute of Psychology, P.O.
Box 1738, T12-47, 3000 DR Rotterdam, The Netherlands. E-mail:
Journal of Educational Psychology Copyright 2007 by the American Psychological Association
2007, Vol. 99, No. 2, 274–284 0022-0663/07/$12.00 DOI: 10.1037/0022-0663.99.2.274
and working ability (Hakanen, 2002). Moreover, in a business
context, Harter, Schmidt, and Hayes (2002) showed that levels of
employee engagement were positively related to business-unit
performance (i.e., customer satisfaction and loyalty, profitability,
productivity, turnover, and safety). Harter et al. concluded that
engagement is “related to meaningful business outcomes at a
magnitude that is important to many organizations” (Harter et al.,
2002, p. 276). Results from in-depth interviews suggest that en-
gaged employees work long hours but that they lack the obsession
to work that is characteristic for workaholics (Schaufeli et al.,
2001). Engaged employees do not neglect their social life outside
work; rather, they enjoy things in their lives other than work. They
also spend time on socializing and hobbies and work as volunteers
(see also Schaufeli & Salanova, in press).
Engagement is measured with the Utrecht Work Engagement
Scale, which includes the three subscales of Vigor, Dedication, and
Absorption. This scale has been validated among Spanish
(Schaufeli, Salanova, et al., 2002), Finnish (Hakanen, 2002), and
Dutch employees (Schaufeli & Bakker, 2004). All investigations
used confirmatory factor analyses and showed that the hypothe-
sized three-factor structure is superior to that of any other alter-
native factor structure. In addition, the internal consistencies of the
three subscales proved to be sufficient in each study.
The JD-R Model
The JD-R model (Bakker & Demerouti, 2007; Bakker, Demer-
outi, De Boer, & Schaufeli, 2003; Bakker, Demerouti, & Verbeke,
2004; Demerouti et al., 2001) is a heuristic model that specifies
how employee well-being may be produced by two specific sets of
working conditions. The first set concerns job demands that rep-
resent characteristics of the job that potentially evoke strain, in
case they exceed the employee’s adaptive capability. More specif-
ically, job demands are those physical, social, or organizational
aspects of the job that require sustained physical and/or psycho-
logical (i.e., cognitive or emotional) effort on the part of the
employee and are therefore associated with certain physiological
and/or psychological costs (e.g., exhaustion; cf. Hockey, 1997).
Although job demands are not necessarily negative, they may turn
into job stressors when meeting those demands requires high effort
from which the employee does not adequately recover (Meijman &
Mulder, 1998).
This is in line with Rudow (1999), who argued that teachers’
cognitive and emotional workload may evoke chronic fatigue and
finally burnout, which may lead to psychosomatic disorders and
complaints as well as restrictions in pedagogical performance.
Indeed, Burke et al. (1996) showed that teachers who were con-
fronted with disruptive students were most likely to report burnout
symptoms 1 year later. In addition, Bakker et al. (2000) and Taris,
Van Horn, Schaufeli, and Schreurs (2004) showed that lack of
reciprocity in teachers’ relationships with students predicts burn-
out. In the relationship with students, teachers’ investments may
include their enthusiasm and effort. These investments are recip-
rocated when students react with gratitude or when there exists a
good classroom atmosphere. Investments are not reciprocated
when students are inattentive, disrespectful, and bored. If this lack
of reciprocity turns into a chronic condition, whereby teachers
continuously give more than they receive in return, it may even-
tually deplete teachers’ emotional resources and, thus, foster the
development of the burnout syndrome and physical health prob-
lems (see also Blase, 1986; Borg & Riding, 1991; Farber, 1991;
Melamed, Shirom, Toker, Berliner, & Shapira, 2006).
The second set of working conditions concerns the extent to
which the job offers resources to individual employees. Job re-
sources are those physical, psychological, social, or organizational
aspects of the job that (a) reduce job demands and the associated
physiological and psychological costs, (b) are functional in achiev-
ing work goals, or (c) stimulate personal growth, learning, and
development (Demerouti et al., 2001). Hence, not only are re-
sources necessary to deal with job demands but they are also
important in their own right (Hobfoll, 2002). Resources may be
located at the following levels: the organization (e.g., salary, career
opportunities), interpersonal and social relations (e.g., supervisor
and coworker support), the organization of work (e.g., role clarity,
participation in decision making), and the task (e.g., performance
feedback, skill variety). In general, job demands and resources are
negatively related because job demands, such as high work pres-
sure and emotionally demanding interactions with students, may
preclude the mobilization of job resources (see Bakker, Demerouti,
Taris, et al., 2003; Demerouti et al., 2001). In a similar vein, high
job resources, such as social support and feedback, may reduce job
An important assumption in the JD-R model is that working
characteristics may evoke two psychologically different processes.
In the first process, demanding aspects of work (i.e., work over-
load) lead to constant overtaxing and, in the long run, to exhaus-
tion (e.g., Lee & Ashforth, 1996; Wright & Cropanzano, 1998).
Exhaustion, in turn, may lead to negative consequences for the
organization, such as absenteeism (Bakker, Demerouti, De Boer,
& Schaufeli, 2003) and impaired in-role performance (Bakker et
al., 2004). In the second process proposed by the JD-R model, job
resources lead to engagement and positive outcomes (Schaufeli &
Bakker, 2004). For instance, Bakker et al.’s (2004) study of human
service professionals (including teachers) showed that job re-
sources lead to dedication and extra-role performance. This is
consistent with Leithwood, Menzies, Jantzi, and Leithwood
(1999), who suggested that schools may develop commitment to
the collectively held goals of the organization by providing teach-
ers with opportunities to become increasingly competent and by
developing shared decision-making possibilities (i.e., job re-
sources). These job resources, in turn, encourage personal invest-
ment in the work and success of the school organization. However,
when schools do not provide or reward teachers with job resources,
the long-term consequence is withdrawal from work and reduced
motivation and commitment (Bakker, Demerouti, & Schaufeli,
2003). This leads to our first hypothesis:
Hypothesis 1: Job resources are positively related to work
Job Resources as Buffers
The JD-R model also postulates that job resources may buffer
the impact of job demands on strain, including burnout. Typically,
the buffering hypothesis explains interactions between job de-
mands (i.e., stressors) and job resources by proposing that the
relationship between job demands and strain is weaker for those
enjoying a high degree of job resources (Caplan, Cobb, French,
Van Harrison, & Pinneau, 1975). Applied to work engagement, the
negative relationship between job demands and work engagement
is weaker for those enjoying high job resources. This hypothesis is
consistent with the demand–control model (Karasek, 1979) and
the effort–reward imbalance model (Siegrist, 1996). The demand–
control model claims that job control or autonomy may buffer the
influence of workload on strain, whereas the effort–reward imbal-
ance model states that rewards (in terms of salary, esteem reward,
and security/career opportunities, i.e., promotion prospects, job
security, and status consistency) may buffer the influence of effort
(extrinsic job demands and intrinsic motivation to meet these
demands) on strain. The JD-R model conceptually integrates and
expands these models by claiming that several different job re-
sources can play the role of buffer for several demanding working
conditions. Which job demands and resources play a role in a
certain organization or occupation depends on the specific job
characteristics that prevail. Whereas the demand–control model
states that autonomy may buffer the impact of work and time
pressure on job strain, the JD-R model expands this view and states
that many different types of job resources may buffer the undesir-
able influence of job demands, including disruptive student behav-
Indeed, in a recent study of over 1,000 teachers at a large
institute for higher education, Bakker, Demerouti, and Euwema
(2005) showed that several job demands influenced burnout only if
teachers possessed few job resources (autonomy, social support,
supervisory coaching, and feedback). In a similar vein, in their
study among four home-care organizations, Bakker, Demerouti,
Taris, et al. (2003) found evidence for the buffering role of job
resources. More specifically, they found that the relationship be-
tween job demands (e.g., workload, physical demands, and patient
harassment) and feelings of exhaustion disappeared when home-
care professionals possessed many resources (e.g., autonomy, op-
portunities for professional development, performance feedback).
The buffer hypothesis is consistent with the work of R. L. Kahn
and Byosiere (1992), who argued that the buffering or interaction
effect can occur between any pair of variables in the stressor–strain
sequence. They claimed that properties of the work situation, as
well as characteristics of the individual, can buffer the effects of a
stressor. The buffering variable can reduce the tendency of orga-
nizational properties to generate specific stressors, can alter the
perceptions and cognitions evoked by such stressors, and can
moderate responses that follow the appraisal process or reduce the
health-damaging consequences of such responses (R. L. Kahn &
Byosiere, 1992, p. 622). Social support is probably the most
well-known situational variable that has been proposed as a po-
tential buffer against job stress (e.g., Haines, Hurlbert, & Zimmer,
1991; Johnson & Hall, 1988; see Van der Doef & Maes, 1999, for
a review). Other characteristics of the work situation that may act
as moderators are (a) the extent to which the onset of a stressor is
predictable (e.g., feedback), (b) the extent to which the reasons for
the presence of a stressor are understandable (e.g., through infor-
mation provided by supervisors), and (c) the extent to which
aspects of the stressor are controllable by the person who must
experience it (e.g., job autonomy; R. L. Kahn & Byosiere, 1992).
In the present study of teachers, we included six job resources
that have been identified as major motivators that either increase
commitment or engagement among teachers or—when lacking—
increase burnout: job control (e.g., De Heus & Diekstra, 1999;
Taris, Schreurs, & van Iersel-van Silfhout, 2001), supervisor sup-
port (e.g., Coladarci, 1992; Friedman, 1999; Leiter & Maslach,
1988; Rosenholtz & Simpson, 1990; Smylie, 1999), information
(Leithwood et al., 1999), organizational climate (e.g., Friedman,
1991; Kremer-Hayon & Kurtz, 1985; Travers & Cooper, 1993),
innovativeness (Rosenholtz, 1989; Smylie, 1999), and apprecia-
tion (Bakker et al., 2005; Van Horn, Schaufeli, & Taris, 2001). On
the basis of this literature, we formulated the following hypothesis:
Hypothesis 2: Job resources buffer the negative relationship
between pupil misbehavior and work engagement. More spe-
cifically, the relationship between pupil misbehavior and
work engagement is weaker for employees with many (vs.
few) resources.
The Salience of Resources Under Stressful Conditions
According to conservation of resources theory (Hobfoll, 1989,
2002), people seek to obtain, retain, and protect that which they
value (e.g., material, social, personal, or energetic resources). The
theory proposes that stress experienced by individuals can be
understood in relation to potential or actual loss of resources. More
specifically, Hobfoll and Shirom (2001) have argued that (a)
individuals must bring in resources to prevent the loss of resources,
(b) individuals with a greater pool of resources are less susceptible
to resource loss, (c) those individuals who do not have access to
strong resource pools are more likely to experience increased loss
(loss spiral), and (d) strong resource pools lead to a greater
likelihood that individuals will seek opportunities to risk resources
for increased resource gains (gain spiral). Hobfoll (2002) has
additionally argued that resource gain itself has only a modest
effect but instead acquires its saliency in the context of resource
We located three studies supporting this latter hypothesis, all of
which referred to occupations outside education. Billings, Folk-
man, Acree, and Moskowitz (2000) studied men who were care-
givers for individuals with AIDS and found that those who used
social support coping maintained their positive emotional states
under conditions of stress. Consequently, these caregivers experi-
enced fewer physical symptoms, thus supporting the importance of
resource gain in the context of loss. Similarly, Riolli and Savicki
(2003) showed that information service workers’ personal re-
sources (optimism and control coping) were particularly beneficial
when work resources were low. Finally, Seers, McGee, Serey, and
Graen (1983) showed that for those employees who had to cope
with high role conflict, job satisfaction was predicted by social
support. However, for those not experiencing stress caused by role
conflict, social support was inconsequential for job satisfaction.
Seers et al. suggested that for persons experiencing low levels of
stress, the use of the social support resource is unnecessary.
However, under stressful conditions, individuals are more likely to
use resources as a coping mechanism or stress-reducing action.
Taken together, conservation of resources theory and these three
studies offer theoretical and empirical support for the notion that
resources are particularly salient in the context of loss. Thus, we
predicted the following:
Hypothesis 3: Job resources particularly influence work en-
gagement (vigor, dedication, and absorption) when teachers
are confronted with high levels of pupil misbehavior. More
specifically, the relationship between job resources and work
engagement is strongest when teachers are exposed to high
(vs. low) pupil misbehavior.
The difference between the buffer and the coping hypotheses is
simply the pattern of the interaction predicted. The method of
testing the statistical significance of interactions, moderated struc-
tural equation modeling (MSEM; Cortina, Chen, & Dunlap, 2001),
reflects no distinction between patterns of interactions. Either of
the two specific patterns can be found by inspecting the complex
association between pupil misbehavior, job resources, and work
Procedure and Participants
The data for this study were obtained as a part of a develop-
mental project in the Education Department of Helsinki, Finland.
In the beginning of 2001, a questionnaire was delivered to all the
schools in the East, Northeast, and Southeast districts of Helsinki.
Teachers were kindly requested to respond to the questionnaire
and to send it anonymously in a prepaid envelope to Jari J.
Hakanen. In total, 805 teachers working in elementary, secondary,
and vocational schools participated in this study (response rate
52%). There was no possibility to send reminders to those who did
not respond to the questionnaire, which explains the moderate
response rate.
Our sample seems representative of the population of Finnish
teachers. The mean age of the teachers in our sample was 41.3
years (SD 10.7), compared with 44 years in the whole of
Finland, and the proportion of female teachers was 81%, compared
with 68% in Finland (Statistics Finland, 2004). In addition, 79% of
the teachers in our sample were working in elementary or lower
secondary schools (67% in Finland), 10% were in upper secondary
schools (11% in Finland), and 11% were in vocational schools
(21% in Finland). The proportion of teachers in vocational schools
was underrepresented in the sample because the Education Depart-
ment of Helsinki mainly runs basic education and is only partly
responsible for vocational education. Participants’ mean teaching
job tenure was 13.5 years (SD 10.1), and they reported that they
worked 37.0 hr per week (SD 8.41) on average. Because the
background variables were only marginally related to the model
variables, they were excluded from all further analyses.
Work engagement was assessed with the Finnish version of the
Utrecht Work Engagement Scale (Schaufeli, Salanova, et al.,
2002). The factorial validity of the Finnish version of this scale has
been demonstrated in previous research (Hakanen, 2002). The
instrument includes three subscales: Vigor, Dedication, and Ab-
sorption. Vigor was assessed with six items (e.g., “At my work, I
feel bursting with energy,” “When I get up in the morning, I feel
like going to work”). Dedication was measured with five items
(e.g., “I am enthusiastic about my job,” “I find the work that I do
full of meaning and purpose”). Absorption was assessed with six
items (e.g., “I am immersed in my work,” “When I am working, I
forget everything else around me”). Items were rated on a 7-point
scale, ranging from 0 never to 6 always. Several studies have
demonstrated the (cross-national) validity, reliability, and stability
of the Utrecht Work Engagement Scale (e.g., Schaufeli & Bakker,
2004; Schaufeli, Martinez, Marques-Pinto, Salanova, & Bakker,
2002; Schaufeli, Salanova, et al., 2002; Storm & Rothman, 2003).
Pupil misbehavior was measured with a six-item scale adapted
from Kyriacou and Sutcliffe (1978). Respondents first read an
overall question (“As a teacher, how great a source of stress are the
following factors to you?”) and were then requested to react to six
specific behaviors or situations, such as “noisy pupils,” “pupils
who show a lack of interest,” and “maintaining class discipline.”
The items were scored on a 5-point scale, ranging from 1 hardly
ever to 5 very often.
Most of the six scales measuring job resources were derived
from the Healthy Organization Barometer (Lindstro¨m, 1997; Lind-
stro¨m, Hottinen, & Bredenberg, 2000). The Healthy Organization
Barometer has been validated in several occupational groups in
Finland. The instrument has been translated into several languages
and has been used in many multinational organizations functioning
in Finland and elsewhere (Lindstro¨m, 1997). Each job resource
was assessed with three items. Here is an example for each job
resource: “In general, how much influence do you have over your
work and things that concern you at work?” (job control); “Does
your supervisor provide help and support when needed?” (super-
visor support); “Is the flow of information at your workplace
between the management and the personnel sufficient?” (informa-
tion); “What is the work climate like in your unit? . . . Encouraging
and supportive of new ideas?” (organizational climate); “How
often do the following aspects occur in your work? . .. We
regularly make improvements in our work” (innovativeness); and
“Do your colleagues appreciate your work?” (appreciation). All
the items that were used to assess the job resources were scored on
a 5-point scale ranging from 1 hardly ever to 5 very often.
Higher scores on these scales refer to more job resources.
Statistical Analyses
To test our hypotheses, we conducted MSEM analyses, using
the AMOS software package (Arbuckle, 1997). The covariance
matrix was analyzed with the maximum-likelihood method. We
preferred MSEM to hierarchical regression analyses because
MSEM allows us to assess and correct for measurement error.
Additionally, MSEM provides measures of fit of the models under
study. To apply MSEM analyses, we followed the procedure
proposed by Mathieu, Tannenbaum, and Salas (1992), as described
by Cortina et al. (2001).
For each hypothesized interaction effect, we tested a model that
included three exogenous variables (pupil misbehavior, each of the
six job resources, and the interaction between pupil misbehavior
and each of the six resources) and three endogenous variables
(vigor, dedication, and absorption). In total, we tested six different
models, one for each possible interaction between pupil misbehav-
ior and the job resources included in the study. Each exogenous
variable had only one indicator that was the standardized (cen-
tered) scale score of the respective variable (Mathieu et al., 1992).
The indicator of the latent interaction variable was the multiplica-
tion of the standardized scale scores of the pupil misbehavior
variable and each job resource tested. For example, the model that
tested the interaction effect of pupil misbehavior and job control
on the three dimensions of work engagement included one pupil
misbehavior variable (whose indicator was the zscore of the pupil
misbehavior scale), one job control variable (whose indicator was
the zscore of the job control scale), and the interaction variable
(whose indicator was the multiplicative result of the zscore of
pupil misbehavior and the zscore of job control).
For the three endogenous latent variables, we followed Bagozzi
and Edwards’s (1998) recommendation to use partial disaggrega-
tion models. To construct item parcels, we performed preliminary
principal components factor analyses for each of the three depen-
dent variables separately. Yuan, Bentler, and Kano (1997) recom-
mended averaging those variables with the same factor structure.
The factor analysis regarding vigor resulted in two distinguished
factors. The first factor included Items 1, 2, and 6, and the second
factor included Items 3, 4, and 5. Thus, instead of including all six
items of the Vigor scale as indicators of the latent vigor factor, we
formed two composites by combining the items that resulted from
the factor analysis. Factor analyses regarding dedication and ab-
sorption resulted in one factor each. In these cases, item parceling
was based on the items’ relative errors. In other words, variables in
each group with roughly equal relative errors were averaged (Yuan
et al., 1997). Thus, we created two composites by combining the
first two and last three items of the Dedication scale; we created
two other composites by combining the first three and the last three
items of the Absorption scale. It is important to note that decisions
on item parceling were also dependent on whether the constructed
composites had acceptable reliabilities.
The models included direct paths from the three exogenous
variables (pupil misbehavior, job resources, and their interactions)
to the three endogenous variables (vigor, dedication, and absorp-
tion). The pupil misbehavior and job resources variables were
allowed to correlate, whereas correlations between pupil misbe-
havior and job resources and the interaction term were expected to
be zero. Furthermore, the residual errors of the three outcome
variables were allowed to correlate. Finally, the paths from the
latent exogenous factors to their indicators were fixed with the
square roots of the scale reliabilities, whereas the error variances of
each indicator were set equal to the product of their variances and
one minus their reliabilities. For more details regarding the calcu-
lation of the reliability score of the interaction term, we refer to
Cortina et al. (2001). Figure 1 graphically represents the model
that was applied for each of the six job resources separately.
The fit of the models was assessed with the chi-square statistic,
the goodness-of-fit index (Hoyle, 1995), and the root-mean-square
error of approximation (MacCallum, Browne, & Sugawara, 1996).
It is suggested that goodness-of-fit values that exceed .90 and
root-mean-square error of approximation values as high as .08 are
indicative of a good fit. A significant interaction effect is evident
when the path coefficient from the interaction variable to the
endogenous variables is statistically significant. The final step for
confirming the significance of an interaction is to test the model
with and without the path from the latent interaction variable to the
Pupil Misbehavior
Vigor 1
Vigor 2
Job Resource Pupil Misbehavior
x Job Resource
Job Resource Cross-product
Dedication 1 Dedication 2
Absorption 2
Absorption 1
Figure 1. The study model is shown. All constrained paths and error variances are marked with C. res. error
residual error.
endogenous variables and to compare the two models on the basis
of the chi-square statistic. Visual examination of the pattern of
interactions was used to assess whether it confirmed Hypothesis 2
or Hypothesis 3. For Hypothesis 2, the buffer hypothesis, the effect
of pupil misbehavior on work engagement was examined within
high and low job resources subgroups. For Hypothesis 3, the
coping hypothesis, the effect of job resources on work engagement
was examined within high and low pupil misbehavior subgroups.
Descriptive Statistics
Table 1 shows the means, standard deviations, correlations, and
internal consistencies of all scales included in this study. The
internal consistencies of the scales are generally good because
Cronbach’s alphas are all well above .70, with one exception
(appreciation has an alpha of .62). The six job resources were
weakly or not at all correlated with pupil misbehavior, and the
intercorrelations between the six job resources were weak to
moderately high.
Direct Effects
Results of the MSEM analyses are presented in Table 2. As
expected, pupil misbehavior was negatively related to each of the
three work engagement dimensions in all the models tested (Serow,
1994). Furthermore, and consistent with Hypothesis 1, all six job
resources (job control, supervisor support, climate, innovativeness,
information, and appreciation) were positively related to vigor, ded-
ication, and absorption (Demerouti et al., 2001; Hobfoll, 2002). Of all
job resources tested, appreciation appeared to be the strongest predic-
tor of all work engagement dimensions (see Table 2).
Interactions Between Pupil Misbehavior and Job
The results of MSEM analyses provided strong support for the
predicted interaction effects. As can be seen in Table 2, five out of
six job resources moderated the effect of pupil misbehavior on
vigor and absorption, whereas four job resources interacted with
pupil misbehavior regarding the dedication dimension of work
engagement. Job control was the only job resource that did not
interact significantly with pupil misbehavior in predicting the
dimensions of engagement. Additionally, information did not have
a moderator effect on the relationship between pupil misbehavior
and dedication. Supervisor support, organizational climate, inno-
vativeness, and appreciation had moderation effects on the rela-
tionship between pupil misbehavior and all three dimensions of
work engagement. Furthermore, all models showed a good fit to
the data (see Table 2).
In cases where MSEM analyses resulted in a significant inter-
action effect, the fit of the model with and without the path from
the latent interaction variable to the endogenous variables was
compared. In all cases, chi-square difference tests showed that the
fit of the models with the path from the latent interaction variable
to the endogenous variables was significantly better than the
models with no such path, thus further supporting these interaction
effects. Taken together, 14 out of 18 interaction terms (78%) had
a significant and unique effect on engagement.
To examine the direction of the effects, we derived graphical
representations of the interaction effects from the simple slope
analyses (Aiken & West, 1991; Frazier, Tix, & Barron, 2004). For
the significant interactions, we inspected plots of the relationship
between pupil misbehavior and work engagement within high and
low job resources subgroups to test Hypothesis 2 (buffering). The
subgroups were built by taking those who scored one standard
deviation below and above the mean on the six resources. For the
high resources group, the slopes ranged from b⫽⫺.42 to b
.56 for vigor, from b⫽⫺.39 to b⫽⫺.45 for dedication, and
from b⫽⫺.45 to b⫽⫺.68 for absorption. In the low job
resources group, the slopes were substantially lower or zero and
ranged from b⫽⫺.03 to b⫽⫺.22 for vigor, from b⫽⫺.01 to
b⫽⫺.21 for dedication, and from b.00 to b⫽⫺.22 for
absorption. All the interactions showed a similar pattern and sup-
ported both our hypotheses. Thus, job resources mitigated the
negative effect of the key job demand in teachers’ profession (i.e.,
pupil misbehavior) on work engagement. For illustrative purposes,
Figures 2A, 2C, and 2E display one significant interaction (buff-
ering) effect for each dimension of work engagement with differ-
ent job resources.
In the last step, plots of work engagement on job resources
within high and low pupil misbehavior subgroups were exam-
ined for the same significant interactions. Job resources were
strongly related to work engagement for those experiencing
high levels of pupil misbehavior (slopes ranged from b.45 to
Table 1
Means, Standard Deviations, Internal Consistencies (Cronbach’s Alphas on the Diagonal), and Correlations Between the Study
Variables (N 805)
Variable MSD 1 2345678910
1. Pupil misbehavior 3.24 0.92 (.86)
2. Job control 3.42 0.78 .17
3. Supervisor support 3.09 1.03 .04 .27
4. Information 3.58 0.67 .04 .23
5. Climate 3.67 0.91 .03 .27
6. Innovativeness 3.19 0.74 .02 .17
7. Appreciation 3.84 0.55 .12
8. Vigor 4.51 0.98 .19
9. Dedication 4.71 1.09 .25
10. Absorption 3.92 1.33 .17
.04 .08
b.63 for vigor, from b.41 to b.69 for dedication, and
from b.29 to b.63 for absorption) and were unrelated or
weakly related for those experiencing low levels of pupil mis-
behavior (slopes ranged from b.12 to b.24 for vigor, from
b.15 to b.23 for dedication, and from b⫽⫺.13 to b
.12 for absorption). These results support Hypothesis 3 by
demonstrating that job resources particularly influence engage-
ment under conditions of high job demands. For illustrative
purposes, Figures 2B, 2D, and 2F display one significant inter-
action (coping) effect for each dimension of work engagement
with different job resources.
The present study shows that supervisor support, innovative-
ness, information, appreciation, and organizational climate can all
be considered important job resources for teachers because each of
these conditions was able to buffer the negative impact of pupil
misbehavior on work engagement. In line with our hypothesis, a
series of MSEM analyses resulted in 14 out of 18 significant
two-way interactions. Thus, different combinations of job re-
sources and pupil misbehavior explained significant amounts of
the variance in vigor, dedication, and absorption over and above
the main effects. These findings are consistent with earlier research
(among home-care professionals and teachers at a higher education
institution) on the buffer hypothesis in the JD-R model, which
showed conceptually similar results—namely, that several job
resources can buffer the impact of job demands on burnout (Bak-
ker, Demerouti, Taris, et al., 2003; Bakker et al., 2005). Moreover,
we were able to integrate and study simultaneously in one model
many different general as well as profession-specific job demands
and resources that are known from previous studies to influence
teachers’ well-being.
Probably the most innovative theoretical contribution made by
this study is that it shows that job resources are particularly
relevant under highly stressful conditions. Consistent with conser-
vation of resources theory (Hobfoll, 1989, 2002) and previous
research in other domains (Billings et al., 2000; Seers et al., 1983),
the results show that supervisor support, innovativeness, appreci-
ation, and organizational climate particularly influenced teachers’
work engagement when pupil misbehavior was an important job
demand, thus providing support for our coping hypothesis. This
suggests that job resources supply strategies for dealing with the stress
caused by pupil misbehavior. Job resources may be of less concern to
individuals not experiencing a significant amount of stress (cf. Seers
et al., 1983). In the sense of the demand–control–support model, this
represents active jobs that combine the reason and the facilities to
enhance motivation for learning new behavior patterns (Karasek &
Theorell, 1990). At the same time, findings suggest that pupil mis-
conduct was not as detrimental for teachers’ work engagement when
they received support and appreciation from their supervisor and
colleagues and when they worked within a school context that favored
innovativeness and had a supportive climate. This provides clear
support for the buffering hypothesis that has been studied in the
literature somewhat more extensively than the coping hypothesis.
The reason why job resources both have motivational potential
and can act as buffers is most probably different for different
Table 2
Results of Moderated Structural Equation Modeling: Interactions of Pupil Misbehavior and Job Resources (N 805)
Vigor Dedication Absorption Fit
Pupil misbehavior .14 (.03) .22
.21 (.04) .23
.17 (.05) .15
Job control .20 (.03) .34
.26 (.03) .30
.19 (.04) .19
Pupil Misbehavior Job Control .05 (.03) .07 .02 (.04) .03 .04 (.05) .04
20% 17% 7% 102.84 .97 .08
Pupil misbehavior .18 (.03) .28
.25 (.04) .28
.21 (.05) .18
Supervisor support .19 (.03) .29
.30 (.04) .32
.15 (.05) .13
Pupil Misbehavior Supervisor Support .06 (.03) .10
.11 (.04) .13
.15 (.05) .14
18% 21% 7% 103.97 .97 .08
Pupil misbehavior .19 (.03) .29
.27 (.04) .30
.21 (.04) .18
Climate .18 (.03) .29
.24 (.03) .27
.11 (.04) .10
Pupil Misbehavior Climate .08 (.03) .13
.11 (.04) .13
.17 (.05) .16
18% 17% 7% 108.82 .97 .08
Pupil misbehavior .18 (.03) .28
.26 (.04) .29
.21 (.05) .18
Innovativeness .13 (.03) .21
.21 (.03) .25
.09 (.04) .08
Pupil Misbehavior Innovativeness .07 (.03) .13
.09 (.04) .11
.18 (.05) .18
14% 16% 7% 95.21 .97 .08
Pupil misbehavior .19 (.03) .29
.27 (.04) .30
.20 (.05) .18
Information .15 (.03) .24
.20 (.03) .23
.05 (.04) .05
Pupil Misbehavior Information .06 (.03) .10
.06 (.04) .07 .09 (.04) .09
15% 14% 4% 101.45 .97 .08
Pupil misbehavior .15 (.03) .24
.22 (.03) .24
.18 (.04) .17
Appreciation .27 (.03) .50
.45 (.03) .57
.27 (.04) .29
Pupil Misbehavior Appreciation .13 (.03) .20
.21 (.04) .23
.20 (.05) .19
38% 48% 16% 134.21 .96 .09
Note. The df of all models is 17. UPC unstandardized path coefficient; SPC standardized path coefficient; GFI goodness-of-fit index; RMSEA
root-mean-square error of approximation.
resources. For example, supervisor support may alleviate the in-
fluence of job demands on strain because supervisors’ appreciation
and support puts demands in another perspective. Leaders’ appre-
ciation and support may also aid the teachers in coping with their
job demands, facilitate performance, and act as a protector against
ill health (Va¨a¨na¨nen et al., 2003). In contrast, organizational cli-
mate and innovativeness may be crucial for work engagement
because they keep teachers’ work interesting and challenging and
offer them opportunities for self-growth. Appreciation helps main-
tain teachers’ motivation and signals them to continue in a certain
direction (Hackman & Oldham, 1980). Taken together, these find-
ings clearly expand the JD-R model and suggest that teachers
facing demanding working conditions can be helped by offering
them the right resources. Next to the unique contribution of job
demands and resources proposed by the JD-R model (i.e., that job
demands lead to overtaxing and exhaustion and that job resources
lead to work engagement), the present study shows convincingly
that the interaction between job demands and resources adds to the
prediction of work engagement. Thus, not only do job demands
and job resources have unfavorable and favorable effects, respec-
Appreciation + 1 SD
Appreciation - 1 SD
0.000 1.000
Pupil Misbehavior
0.000 1.000
Pupil Misbehavior
0.000 1.000
Pupil Misbehavior
0.000 1.000
0.000 1.000
0.000 1.000
Organizational Climate
Climate + 1 SD
Climate - 1 SD
Innovativeness + 1 SD
Innovativeness - 1 SD
Pupil Misbehavior - 1 SD
Pupil Misbehavior + 1 SD
Pupil Misbehavior - 1 SD
Pupil Misbehavior + 1 SD
Pupil Misbehavior - 1 SD
Pupil Misbehavior + 1 SD
Figure 2. A: The effect of appreciation on the relationship between pupil misbehavior and vigor (cf. buffer
hypothesis). B: Appreciation particularly influences vigor when teachers are confronted with high levels of pupil
misbehavior (cf. coping hypothesis). C: The effect of organizational climate on the relationship between pupil
misbehavior and dedication (cf. buffer hypothesis). D: Organizational climate particularly influences dedication
when teachers are confronted with high levels of pupil misbehavior (cf. coping hypothesis). E: The effect of
innovativeness on the relationship between pupil misbehavior and absorption (cf. buffer hypothesis). F:
Innovativeness particularly influences absorption when teachers are confronted with high levels of pupil
misbehavior (cf. coping hypothesis).
tively, on work engagement (as is the case when studied in
isolation) but also their combination is predictive of the degree of
work engagement. Namely, in 14 out of 18 cases, job control,
supervisor support, information, climate, innovativeness, and ap-
preciation did not result in high levels of work engagement if
teachers did not experience pupil misbehavior. Conceptually, the
current findings replicate Riolli and Savicki’s (2003) study show-
ing that personal resources (optimism and control coping) were
most beneficial when work resources were low.
It is noteworthy that job control (in addition to information) was
unable to buffer the negative relationship between pupil misbe-
havior and work engagement. Previous studies on the demand–
control model (Karasek, 1979) have produced mixed results re-
garding the demand–control interaction effect as well (Van der
Doef & Maes, 1999). Some authors have argued that the lack of
evidence for demand–control interactions can be attributed to the
fact that many researchers study homogeneous groups, leaving
little room for variance on the predictor variables. The current
study clearly investigated a homogeneous group as well but nev-
ertheless showed that several different job resources can play the
role of buffer for demanding working conditions. Which job de-
mands and resources play a role in a certain occupational context
apparently depends upon the specific job characteristics that pre-
vail. Thus, whereas the demand–control model states that auton-
omy buffers the impact of work overload and time pressure on job
strain, the JD-R model challenges this view and states that many
different types of job resources can buffer the undesirable influ-
ence of job demands.
Results of the present study also challenge the idea that specific
job demands and job resources should match in order to show
moderating effects in the prediction of well-being (de Jonge &
Dormann, 2003; Frese, 1999). This line of thinking is referred to
as the matching hypothesis: If the type of available resources (e.g.,
emotional support, appreciation) corresponds to existing stressors
(e.g., pupil misbehavior), then those resources are best able to
mitigate the effects of those stressors, and less strain will result (cf.
Viswesvaran, Sanchez, & Fisher, 1999). According to de Jonge
and Dormann (2006), the discovery of optimal stressor–resource
combinations could help in understanding better how specific
stressors threaten and how specific resources protect employees
from developing strain or even enhance their well-being. However,
the present study does not support the matching hypothesis. For
example, the results show that innovativeness and organizational
climate—variables conceptually unrelated to pupil misconduct—
were able to buffer the negative impact of pupil misbehavior on
work engagement. In other words, we found that buffer effects also
exist when demands and resources do not match, thus raising
doubts regarding the generalizability of the matching hypothesis.
Frese (1999) argued that it is usually difficult to trace significant
interaction effects. It is therefore remarkable that in the present
study, we found evidence for 14 out of 18 interactions (78%).
However, it should be noted that effect sizes for interactions are
usually small, especially in nonexperimental studies (Frazier et al.,
2004). This means that the practical implications of the present
study may be limited: Job resources can buffer only part of the
negative influence of job demands on work engagement. Never-
theless, we believe that the interactions are important from a
theoretical perspective because they shed light on the combination
of different working conditions that may foster work engagement.
Another drawback of the study is its cross-sectional nature,
which implies that it is impossible to make causal statements
because of temporal ambiguity. However, the findings are clearly
in line with two theories, namely, the JD-R model (Bakker, De-
merouti, & Schaufeli, 2003; Demerouti et al., 2001) and conser-
vation of resources theory (Hobfoll, 1989, 2002). In addition, it
seems unlikely that work engagement could predict the exact
combinations of job demands and resources (interaction terms)
found in the current study. Finally, this study was based on
self-report questionnaires. Even though employees’ perceptions of
the work environment, as expressed through the questionnaires,
are an important source of information, perceptions do not neces-
sarily reflect objective reality. Therefore, it would be useful if
future research could replicate the findings using a combination of
self-reports and other-ratings of demands and resources.
Practical Implications
We have recently developed several Internet applications of the
JD-R model, in which teachers, secretaries, general practitioners,
and managers who fill in an electronic questionnaire receive online
feedback on their computer screen about the most important de-
mands and resources of their job. This means for teachers that they
receive tailor-made feedback not only about their emotional de-
mands, pupil misbehavior, and so on but also about the availability
of job resources (e.g., supervisor support, innovativeness, appre-
ciation, and organizational climate). An evaluation of one of these
instruments (Bakker, Schaufeli, Bulters, van Rooijen, & ten Broek,
2002) suggests that—at the personal level—the combination of
certain high demands and lack of resources is most predictive of
symptoms of burnout and that the presence of job resources fosters
work engagement, particularly under conditions of high demands.
Thus, the interactions also appear to have practical significance,
even though their contribution to explaining variance in work
engagement for large groups of employees seems limited.
Such information can be used for individual-level job (re)de-
sign, where teachers and school management (or occupational
health professionals, personal coaches, etc.) discuss the possibili-
ties for adjusting the work environment to the needs and abilities
of individual teachers and facilitate the fit between person and
organization. For example, the results of the present study have
been discussed in several seminars and workshops among Finnish
teachers, principals, and administrative staff to encourage the
identification and promotion of the potential and actual job re-
sources at schools and to meet the often inevitable job demands in
the teaching profession.
The general pattern found in the present study suggests that job
resources are rather important to motivate teachers. Because pre-
vious research has suggested that engaged employees are less
inclined to leave the organization (Schaufeli & Bakker, 2004) and
are more willing to help their colleagues when needed (Bakker et
al., 2004), it can be concluded that school organizations may
benefit from an investment in the resources at work.
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and
interpreting interactions. Newbury Park, CA: Sage.
Arbuckle, J. L. (1997). Amos users’ guide Version 4.0. Chicago, IL:
Bagozzi, R. A., & Edwards, J. (1998). A generalized approach for repre-
senting constructs in organizational research. Organizational Research
Methods, 1, 45–87.
Bakker, A. B., & Bal, P. M. (2006). How work engagement influences
performance: A weekly diary study among starting teachers. Manuscript
submitted for publication.
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., De Boer, E., & Schaufeli, W. B. (2003). Job
demands and job resources as predictors of absence duration and fre-
quency. Journal of Vocational Behavior, 62, 341–356.
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., Demerouti, E., & Schaufeli, W. B. (2003). Dual processes at
work in a call centre: An application of the job demands–resources model.
European Journal of Work and Organizational Psychology, 12, 393–417.
Bakker, A. B., Demerouti, E., Taris, T., Schaufeli, W. B., & Schreurs, P.
(2003). A multi-group analysis of the job demands–resources model in
four home care organizations. International Journal of Stress Manage-
ment, 10, 16–38.
Bakker, A. B., Demerouti, E., & Verbeke, W. (2004). Using the job
demands–resources model to predict burnout and performance. Human
Resource Management, 43, 83–104.
Bakker, A. B., Schaufeli, W. B., Bulters, A. J., van Rooijen, A., & ten
Broek, E. (2002). Carrie`re-counseling via Internet. KNMG-project
brengt werkstress en arbeidsvreugde van artsen in beeld [Career coun-
seling through the Internet. KNMG-project reveals doctors’ job stress
and work enjoyment]. Medisch Contact, 12, 454456.
Bakker, A. B., Schaufeli, W. B., Demerouti, E., Janssen, P. P. M., Van der
Hulst, R., & Brouwer, J. (2000). Using equity theory to examine the
difference between burnout and depression. Anxiety, Stress, and Coping,
13, 247–268.
Billings, D. W., Folkman, S., Acree, M., & Moskowitz, J. T. (2000).
Coping and physical health during caregiving. Journal of Personality
and Social Psychology, 79, 131–142.
Blase, J. J. (1986). A qualitative analysis of sources of teacher stress:
Consequences for performance. American Educational Research Jour-
nal, 23, 13–40.
Borg, M. G., & Riding, R. J. (1991). Occupational stress and satisfaction
in teaching. British Educational Research Journal, 17, 263–281.
Boyle, G. J., Borg, M. G., Falzon, J. M., & Baglioni, A. J. (1995). A
structural model of the dimensions of teacher stress. British Journal of
Educational Psychology, 65, 4967.
Burke, R. J., Greenglass, E. R., & Schwarzer, R. (1996). Predicting teacher
burnout over time: Effects of work stress, social support, and self-doubts on
burnout and its consequences. Anxiety, Stress, and Coping, 9, 261–275.
Caplan, R. O., Cobb, S., French, J. R. P., Van Harrison, R., & Pinneau, S. R.
(1975). Job demands and worker health: Main effects and occupational
differences. Washington, DC: U.S. Government Printing Office.
Coladarci, T. (1992). Teachers’ sense of efficacy and commitment to
teaching. Journal of Experimental Education, 60, 323–337.
Cortina, J. M., Chen, G., & Dunlap, W. P. (2001). Testing interaction
effects in LISREL: Examination and illustration of available procedures.
Organizational Research Methods, 4, 324–360.
De Heus, P., & Diekstra, R. F. W. (1999). Do teachers burn out more
easily? A comparison of teachers with other social professions on work
stress and burnout symptoms. In R. Vandenberghe & A. M. Huberman
(Eds.), Understanding and preventing teacher burnout: A sourcebook of
international research and practice (pp. 269–284). New York: Cam-
bridge University Press.
de Jonge, J., & Dormann, C. (2003). The DISC model: Demand-induced
strain compensation mechanisms in job stress. In M. F. Dollard, H. R.
Winefield, & A. H. Winefield (Eds.), Occupational stress in the service
professions (pp. 43–74). London: Taylor & Francis.
de Jonge, J., & Dormann, C. (2006). Stressors, resources, and strain at
work: A longitudinal test of the triple-match principle. Journal of
Applied Psychology, 91, 1359–1374.
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001).
The job demands–resources model of burnout. Journal of Applied Psy-
chology, 86, 499–512.
Evers, W. J. G., Tomic, W., & Brouwers, A. (2004). Burnout among
teachers: Students’ and teachers’ perceptions compared. School Psychol-
ogy International, 25, 131–148.
Farber, B. A. (1991). Crisis in education: Stress and burnout in the
American teacher. San Francisco: Jossey-Bass.
Frazier, P. A., Tix, A. P., & Barron, K. E. (2004). Testing moderation and
mediation effects in counseling psychology. Journal of Counseling
Psychology, 51, 115–134.
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,
Friedman, I. A. (1991). High- and low-burnout schools: School culture aspects
of teacher burnout. Journal of Educational Research, 84, 325–333.
Friedman, I. A. (1999). Turning our schools into a healthier workplace:
Bridging between professional self-efficacy and professional demands.
In R. Vandenberghe & A. M. Huberman (Eds.), Understanding and
preventing teacher burnout: A sourcebook of international research and
practice (pp. 166–175). New York: Cambridge University Press.
Hackman, J. R., & Oldham, G. R. (1980). Work redesign. Reading, MA:
Haines, V. A., Hurlbert, J. S., & Zimmer, C. (1991). Occupational stress,
social support, and the buffer hypothesis. Work & Occupations, 18,
Hakanen, J. J. (2002). Tyo¨uupumuksesta tyo¨n imuun—Positiivisen tyo¨hyvin-
vointika¨sitteen ja—Menetelma¨n suomalaisen version validointi opetusalan
organisaatiossa [From burnout to job engagement—Validation of the Finn-
ish version of an instrument for measuring job engagement (UWES) in an
educational organization]. Tyo¨ ja ihminen, 16, 42–58.
Hakanen, J. J., Bakker, A. B., & Schaufeli, W. B. (2006). Burnout and
work engagement among teachers. Journal of School Psychology, 43,
Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-unit-level relation-
ship between employee satisfaction, employee engagement, and business out-
comes: A meta-analysis. Journal of Applied Psychology, 87, 268–279.
Hobfoll, S. E. (1989). Conservation of resources: A new attempt at con-
ceptualizing stress. American Psychologist, 44, 513–524.
Hobfoll, S. E. (2002). Social and psychological resources and adaptation.
Review of General Psychology, 6, 307–324.
Hobfoll, S. E., & Shirom, A. (2001). Conservation of resources theory:
Applications to stress and management in the workplace. In R. T.
Golembiewski (Ed.), Handbook of organizational behavior (pp. 57–81).
New York: Dekker.
Hockey, G. J. (1997). Compensatory control in the regulation of human
performance under stress and high workload: A cognitive–energetical
framework. Biological Psychology, 45, 73–93.
Hoyle, R. H. (1995). The structural equation modeling approach: Basic
concepts and fundamental issues. In R. H. Hoyle (Ed.), Structural
equation modeling: Concepts, issues and applications (pp. 1–15). Thou-
sand Oaks, CA: Sage.
Johnson, J. V., & Hall, E. M. (1988). Job strain, workplace 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.
Kahn, R. L., & Byosiere, P. (1992). Stress in organizations. In M. D.
Dunnette & L. M. Hough (Eds.), Handbook of industrial and organiza-
tional psychology (Vol. 3, pp. 571–650). Palo Alto, CA: Consulting
Psychologists Press.
Kahn, W. A. (1990). Psychological conditions of personal engagement and
disengagement at work. Academy of Management Journal, 33, 692–724.
Karasek, R. A. (1979). Job demands, job decision latitude and mental
strain: Implications for job redesign. Administrative Science Quarterly,
24, 285–308.
Karasek, R. A., & Theorell, T. (1990). Healthy work: Stress, productivity
and the reconstruction of working life. New York: Basic Books.
Kinnunen, U., & Salo, K. (1994). Teacher stress: An eight-year follow-up
study on teachers’ work, stress, and health. Anxiety, Stress, and Coping,
7, 319–337.
Kremer-Hayon, L., & Kurtz, H. (1985). The relation of personal and
environmental variables to teacher burnout. Teaching and Teacher Ed-
ucation, 1, 243–249.
Kyriacou, C., & Sutcliffe, J. (1978). Teacher stress: Prevalence, sources, and
symptoms. British Journal of Educational Psychology, 48, 159–167.
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, 123–133.
Leiter, M. P., & Maslach, C. (1988). The impact of interpersonal environ-
ment on burnout and organizational commitment. Journal of Organiza-
tional Behavior, 9, 297–308.
Leithwood, K. A., Menzies, T., Jantzi, D., & Leithwood, J. (1999). Teacher
burnout: A critical challenge for leaders of restructuring schools. In
A. M. Huberman (Ed.), Understanding and preventing teacher burnout:
A sourcebook of international research and practice (pp. 85–114). New
York: Cambridge University Press.
Lindstro¨m, K. (1997). Assessing and promoting healthy work organiza-
tions. In P. Seppa¨la¨, T. Luopaja¨rvi, C. Nygard, & M. Mattila (Eds.),
From experience to innovation (pp. 504–506). Helsinki, Finland: Finn-
ish Institute of Occupational Health.
Lindstro¨m, K., Hottinen, V., & Bredenberg, K. (2000). Tyo¨ilmapiiri-ja
hyvinvointibarometri [The Healthy Organization Barometer]. Helsinki,
Finland: Tyo¨terveyslaitos, Psykologian osasto.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power
analysis and determination of sample size for covariance structure mod-
eling. Psychological Methods, 1, 130–149.
Mathieu, J. E., Tannenbaum, S. I., & Salas, E. (1992). Influences of
individual and situational characteristics on measures of training effec-
tiveness. Academy of Management Journal, 35, 828847.
May, D. R., Gilson, R. L., & Harter, L. M. (2004). The psychological
conditions of meaningfulness, safety and availability and the engage-
ment of the human spirit at work. Journal of Occupational and Orga-
nizational Psychology, 77, 11–37.
Meijman, T. F., & Mulder, G. (1998). Psychological aspects of workload. In
P. J. D. Drenth & H. Thierry (Eds.), Handbook of work and organizational
psychology (Vol. 2, pp. 5–33). Hove, England: Psychology Press.
Melamed, S., Shirom, A., Toker, S., Berliner, S., & Shapira, I. (2006).
Burnout and risk of cardiovascular disease: Evidence, possible causal
paths, and promising research directions. Psychological Bulletin, 132,
Riolli, L., & Savicki, V. (2003). Optimism and coping as moderators of the
relationship between work resources and burnout in information service
workers. International Journal of Stress Management, 10, 235–252.
Rosenholtz, S. J. (1989). Teacher’s workplace: The social organiztion of
schools. New York: Longman.
Rosenholtz, S. J., & Simpson, C. (1990). Workplace conditions and the rise
and fall of teachers’ commitment. Sociology of Education, 63, 241–257.
Rudow, B. (1999). Stress and burnout in the teaching profession: European
studies, issues, and research perspectives. In R. Vandenberghe & A. M.
Huberman (Eds.), Understanding and preventing teacher burnout: A
sourcebook of international research and practice (pp. 38–58). New
York: Cambridge University Press.
Schaufeli, W. 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, 293–315.
Schaufeli, W. B., Martinez., I. M., Marques-Pinto, A. M., Salanova, M., &
Bakker, A. B. (2002). Burnout and engagement in university students: A
cross-national study. Journal of Cross-Cultural Psychology, 33, 464
Schaufeli, W. B., & Salanova, M. (in press). Work engagement: An emerging
psychological concept and its implications for organizations. In S. W.
Gilliland, D. D. Steiner, & D. P. Skarlicki (Eds.), Research in social issues
in management. Greenwich, CT: Information Age Publishers.
Schaufeli, W. B., Salanova, M., Gonza´lez-Roma´, V., & Bakker, A. B. (2002).
The measurement of engagement and burnout: A two sample confirmatory
factor analytic approach. Journal of Happiness Studies, 3, 71–92.
Schaufeli, W. B., Taris, T., Le Blanc, P., Peeters, M., Bakker, A. B., & de
Jonge, J. (2001). Maakt arbeid gezond? Op zoek naar de bevlogen
werknemer [Does work make healthy? The quest for the engaged
worker]. De Psycholoog, 36, 422–428.
Seers, A., McGee, G. W., Serey, T. T., & Graen, G. B. (1983). The
interaction of job stress and social support: A strong inference investi-
gation. Academy of Management Journal, 26, 273–284.
Serow, R. C. (1994). Called to teach: A study of highly motivated preservice
teachers. Journal of Research and Development in Education, 27, 65–72.
Siegrist, J. (1996). Adverse health effects of high effort–low reward con-
ditions. Journal of Occupational Health Psychology, 1, 27–41.
Smylie, M. A. (1999). Teacher stress in a time of reform. In R. Vanden-
berghe & A. M. Huberman (Eds.), Understanding and preventing
teacher burnout: A sourcebook of international research and practice
(pp. 5984). New York: Cambridge University Press.
Statistics Finland. (2004). Oppilaitostilastot 2003 [Educational institutes
2003] (Koulutus No. 5). Helsinki, Finland: Author.
Storm, K., & Rothman, I. (2003). A psychometric analysis of the Utrecht
Work Engagement Scale in the South African police service. South
African Journal of Industrial Psychology, 29, 62–70.
Taris, T. W., Schreurs, P. J. G., & van Iersel-van Silfhout, I. J. (2001). Job
stress, job strain, and psychological withdrawal among Dutch university
staff: Towards a dual-process model for the effects of occupational
stress. Work & Stress, 15, 283–296.
Taris, T. W., Van Horn, J. E., Schaufeli, W. B., & Schreurs, P. J. G. (2004).
Inequity, burnout and psychological withdrawal among teachers: A
dynamic exchange model. Anxiety, Stress, and Coping, 17, 103–122.
Travers, C. J., & Cooper, C. L. (1993). Mental health, job satisfaction and
occupational stress among UK teachers. Work & Stress, 7, 203–219.
Va¨a¨na¨nen, A., Toppinen-Tanner, S., Kalimo, R., Mutanen, P., Vahtera, J.,
& Peiro, J. M. (2003). Job characteristics, physical and psychological
symptoms, and social support as antecedents of sickness absence among
men and women in the private industrial sector. Social Science and
Medicine, 57, 807–824.
Van der Doef, M., & 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 Horn, J. E., Schaufeli, W. B., Taris, T. (2001). Lack of reciprocity
among Dutch teachers: Validation of reciprocity indices and their rela-
tion to stress and well-being. Work & Stress, 15, 191–213.
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.
Wright, T. A., & Cropanzano, R. (1998). Emotional exhaustion as a
predictor of job performance and voluntary turnover. Journal of Applied
Psychology, 83, 486493.
Yuan, K. H., Bentler, P. M., & Kano, Y. (1997). On averaging variables in
a confirmatory factor analysis model. Behaviormetrika, 24, 71–83.
Received October 31, 2005
Revision received January 23, 2007
Accepted January 23, 2007
... Despite the relevance of the topic, due to the increasingly international character of the work context in many organizations, it is worth considering that the mentioned interaction processes tend to be discussed as side theme in more generally focused studies (Rattrie and Kittler, 2014). The present study aims to address this gap, anchored in the hypothesis that company policies, in a business expatriation context, allow for conditional job resources (Biswas et al., 2021) to be provided (or not), by purposefully allocating resources to maintain and improve expatriates' working conditions, therefore playing a qualifying role in maintaining or improving employee willingness and psychological contracts under contexts perceived as being of high job demand (Bakker et al., 2007;Demerouti and Bakker, 2011). To address its goal, the study considers interaction effects, as proposed by the job demandsresources (JD-R) model (Bakker et al., 2007;Demerouti and Bakker, 2011;Rattrie and Kittler, 2014;Bakker and Demerouti, 2017), as lens to understand how expatriation-related company policies are enacted as resource pathway to ensure expatriate willingnessunderstood as the likelihood of an individual accepting an expatriation job offer (Mol et al., 2009)as well as the impact of this in terms of the psychological contract maintained with employer organizations. ...
... The present study aims to address this gap, anchored in the hypothesis that company policies, in a business expatriation context, allow for conditional job resources (Biswas et al., 2021) to be provided (or not), by purposefully allocating resources to maintain and improve expatriates' working conditions, therefore playing a qualifying role in maintaining or improving employee willingness and psychological contracts under contexts perceived as being of high job demand (Bakker et al., 2007;Demerouti and Bakker, 2011). To address its goal, the study considers interaction effects, as proposed by the job demandsresources (JD-R) model (Bakker et al., 2007;Demerouti and Bakker, 2011;Rattrie and Kittler, 2014;Bakker and Demerouti, 2017), as lens to understand how expatriation-related company policies are enacted as resource pathway to ensure expatriate willingnessunderstood as the likelihood of an individual accepting an expatriation job offer (Mol et al., 2009)as well as the impact of this in terms of the psychological contract maintained with employer organizations. With this approach, the possibility to add developments or amendments to the JD-R model that may foster its use in international work contexts, namely for less cited countries and economies, such as Portugal, with significant MNC segmentation and heterogeneity (Amador and Cabral, 2014;Forte and Moreira, 2018;Silva et al., 2018;Cabral et al., 2020), was considered as subsidiary research goal. ...
... In addition to this, employment-related resource gains are suggested to be more important in the context of perceived resource losses (Halbesleben et al., 2014). As proposed by the JD-R model (Bakker et al., 2007;Demerouti and Bakker, 2011;Rattrie and Kittler, 2014;Bakker and Demerouti, 2017), job resources (such as autonomy, organizational support or job security) play an important role in preventing performance impairment, also acting as antecedents to motivation-related outcomes such as improved commitment, willingness and dedication. Two key additive effects are proposed in the JD-R model. ...
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Purpose Managerial discourses tend to portray work-related mobility practices in a positive light, presenting mobility assignments as a place of stimulus and differentiation. A conception of mobility as an opportunity, may contrast, in specific economies and business settings, with lived personal experiences. This article reports the results of a three-year study, aimed to question how multinational companies (MNCs) located in a small and developing European economy (Portugal) are building talent pools for expatriate assignments. Interaction effects, as proposed by the job demands-resources (JD-R) theory, are considered as lens to understand the interplay of company expatriate policies, willingness profiles and psychological contracts of expatriates. By using a Portuguese sample, the study examines whether prior findings in mature economies and consolidated MNCs can be generalized to less developed international business settings. Design/methodology/approach A three-year study, encompassing 24 expatriate cases observed in five multinational firms born or located in Portugal. Two techniques of empirical data collection were used: statistical sources and documental analysis and in-depth interviews. A total of 37 interviews were conducted, both in-person and remotely, of which 13 were with company managers and representatives, and 24 with expatriates (as defined and referred like this by the companies under study). Findings Heterogeneous company policies, ranging from juvenile, functionalist to more dynamic and flow-based approaches, are presented as qualifying resources of willingness levels and psychological contracts of expatriates. Observed interaction effects between policies, willingness and psychological contracts, empirically mirrored in three profiles (conformist, protean and disrupted expatriates) suggest that incentive effects (emanating from company policies) and job demand-resource balance, factored as terms of social and economic trade, are non-linear and asymmetric, influencing firm propensity to succeed while using international work to support company expansion goals. As job resources, expatriate policies are presented as operating as pull or push factors: functionalist HR approaches seem to act as push factors generating more conformist or compelled willingness profiles. Research limitations/implications Generalization of study's outcomes has limitations. Future studies are encouraged to use comparative and longitudinal research designs. Furthermore, future research should include business expatriates with entry-level positions, and increase the number of interviewees, as results can also be considered as limited by sample size. Practical implications It is suggested that further strategic work is needed to present expatriation development value, formally screen and consider willingness level as selection criteria, and enlarge the pool (from internal to external) of candidates, in peripheral economic settings such as Portugal. A shift to more dynamic and job resource-dense policies are suggested as beneficial, as pathway to optimize social and economic value from expatriation assignments and work experiences. Originality/value By putting the interplay between macro and micro-level processes into perspective, the study provides empirical evidence on how company expatriate policies have come to promote unforeseen differentiation of employee willingness and psychological contracts at the heart of MNCs. This is particularly relevant in developing economies such as Portugal, challenging the need to build talent pools for international work assignments. Empirical data illustrating company policies interactive effects with different willingness profiles and psychological contracts of expatriates is provided.
... Informed by the Job Demands-Resources (JD-R) model, scattered research has examined how teachers' work demands and resources impact their psychological wellbeing with respect to motivational and impairment pathways (e.g., Bakker et al., 2007;Hakanen et al., 2006). However, as studies based on the JD-R framework have to date primarily examined the influence of external demands and resources concerning job settings (e.g., workload, school climate), the effects of teachers' internal psychological resources (e.g., motivation, personality factors) on their well-being remains scarce. ...
... The benefits of individuals' psychological resources for better adapting to challenging work contexts should then translate into better occupational well-being, as suggested by studies based on the JD-R framework showing greater personal motivation in employees to contribute to lower burnout (e.g., self-efficacy; Xanthopoulou et al., 2007) and greater psychological resilience to correspond with stronger work engagement (e.g., Salmela-Aro & Upadyaya, 2018). 1 Research with teachers based on the JD-R model shows long-term job demands (e.g., work overload, student misbehavior) to contribute to greater burnout (Hakanen et al., 2006) and lower work engagement . In contrast, greater job resources (e.g., autonomy, supervisor support, positive climate) have been found to promote higher levels of work-related engagement and well-being in teachers (e.g., work commitment, Bakker et al., 2007;job satisfaction, Veldman et al., 2016). In occupational settings, psychological needs satisfaction (e.g., autonomy, feedback promoting competency) and self-efficacy have been consistently found to serve as adaptive psychological resources that bolster work engagement in employees (for a review, see Schaufeli & Taris, 2014). ...
... Accordingly, this inconsistent result might be explained by having not examined potential moderating variables such as the extent of student misbehaviors or occupational support. More specifically, greater psychological benefits of teachers' social goals should be observed then among teachers who are at greater risk of burnout due to high levels of student misbehavior (see Aldrup et al., 2018), or teachers who are lacking administrative support (see Bakker et al., 2007). Prior studies addressing specific workload and emotional demands consistently show high job demands combined with low job resources (e.g., autonomy, social support) to contribute to the highest burnout levels among employees (e.g., Bakker et al., 2005), with the buffering effect of personal resources (e.g., self-efficacy, optimism) expected to be most evident in such circumstances . ...
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Positive teacher-student relationships are recognized as critical social resources for promoting dyadic well-being and adaptive instruction. However, there is scarce research on the relationship between teachers’ motivation for connecting with students and teachers’ psychological adjustment. To explore the relationship, this study applied the job demands-resources model to investigate how teachers’ social goal orientations corresponded with their well-being, job satisfaction, and school commitment, with burnout and work engagement as mediating variables. Whereas teachers’ social mastery-approach goals (attempting to improve student relationship-building competencies) were expected to serve as beneficial psychological resources, their social work-avoidance goals (putting minimum effort into student relationships) were hypothesized to function as would detrimental occupational demands. Findings from mediational structural equation modeling of questionnaire responses from Canadian K-12 teachers (N = 154) showed teachers with stronger social mastery-approach goals to be more engaged and, in turn, report greater well-being, job satisfaction, and school commitment. In contrast, teachers with stronger social work-avoidance goals reported less work engagement that was further associated with lower well-being and job satisfaction, as well as greater burnout and, in turn, poorer job satisfaction. Implications concerning teachers’ interpersonal appraisals and psychological health initiatives were discussed.
... In the motivational process, it is assumed that job resources have motivational potential and lead to high work engagement, low cynicism, and excellent performance. Job resources enable employees to achieve their work goals and to manage the psychological and physical demands of the job; they also foster employee growth and learning and development and help buffer the detrimental effects of job demands (Bakker et al., 2007). ...
... However, in contrast to previous studies (Van den Broeck et al., 2016), we did not find this direct effect. Instead, in line with Hypothesis 4 and the assumptions of the JD-R theory, we found the so-called "buffer effect" (Bakker & Demerouti, 2007;Bakker et al., 2005), which states that a high level of resources reduces the impact of job demands on strain. Autonomy moderates the positive effect of work overload on exhaustion such that this effect is weaker for high (vs. ...
Based on a longitudinal survey of K-12 teachers in Switzerland (N = 533), a conditional effects model was used to analyze the relationships between teachers' work overload, prolonging working hours as a coping strategy, autonomy, and exhaustion. The findings showed that the effect of work overload on exhaustion was fully mediated by prolonging working hours. Autonomy moderated the longitudinal effects of work overload on exhaustion. Simple slope analyses demonstrated that autonomy buffered the negative effects of work overload on exhaustion.
... In addition, GLTs not only lose the autonomy and choice about whether to submit a proposal, but also may not have access to the appropriate resources to have their proposals reviewed. Increased work requirements are not always accompanied by an increase in resources, which has led some GLTs to be reluctant to write funding proposals and fulfill this requirement only passively [50]. Our findings do indicate that universities have offered some support for teachers' funding applications by inviting experts who have succeeded in obtaining NSSFC funding in the past. ...
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Abstract: The academic evaluation of teachers of languages other than English (LOTEs) has been extensively researched, especially from the perspective of academic publications. However, little attention has been paid to another key performance indicator in teacher assessment, namely, external research funding. Focusing on German language teachers (GLTs), this paper adopts a mixed methods approach to investigate the assessment requirements for LOTE teachers in terms of external research funding and the factors that may impact their accomplishments. Based on Bronfenbrenner’s ecological systems theory and conservation of resources theory, we analyzed policy documents from the universities under investigation, examined “German or Germany-related” funding approvals, and conducted semi-structured interviews with eight GLTs to explore the environmental factors (individual context, institutional context, social context, chronological context) that may influence the survival of GLTs in terms of the requirements for external research funding. The findings indicate that factors from each ecological context interact with one another and have a combined influence on GLTs’ external research funding application activity. Moreover, there is an imbalance between the academic demands faced by GLTs and the resource support that is available to them. This imbalance may affect the survival and development of GLTs and is likely to have a continuing influence throughout their career. The study concludes by offering some suggestions at different levels to facilitate the sustainable professional development of GLTs.
... PZ sa zapájajú do vedenia školy, komunikujú a spolupracujú s rodičmi a sú súčinní s odbornými zamestnancami pri riešení učebných a výchovných problémov žiakov. Okrem spomínaných činností, PZ podľa ďalších prieskumov (Bakker, et al. 2007; ...
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Milé čitateľky a milí čitatelia, predkladáme Vám záverečnú správu z prieskumu „Duševné zdravie pedagogických zamestnancov“ (ďalej už len Duševné zdravie PZ). Zamerali sme sa na pohľad pedagogických zamestnancov MŠ, ZŠ a SŠ. Duševné zdravie je stavom organizmu, kedy prebiehajú všetky duševné pochody optimálnym spôsobom, umožňuje správne odrážať vonkajšiu realitu, primerane a pohotovo reagovať na všetky podnety a mať zároveň pocit uspokojenia zo svojej činnosti. WHO (2020) definuje duševné zdravie ako stav, keď je človek spokojný so svojím životom, využíva svoje schopnosti a svoj potenciál, zdravým spôsobom zvláda bežný životný stres, rieši problémy, vytvára a udržiava zdravé vzťahy. Vnímaná pohoda posilňuje odolnosť a sebavedomie, ktoré sú potrebné na úspešné zapojenie sa do spoločnosti, profesionálneho života a vzťahov. Pandémia COVID-19 mala podľa WHO (2021) významný negatívny vplyv na neustále zhoršujúce sa duševné zdravie všetkých profesií. Negatívne vplývala aj na duševné zdravie PZ, ktorí boli vystavení novým výzvam realizácie edukačného procesu v online prostredí, čo u mnohých aktérov edukácie spôsobovalo stres, vyčerpanie a tým zhoršenie úrovne duševného zdravia. Z pohľadu učiteľov je jedným z najvýraznejších efektov pandémie a obdobia DV najmä zhoršenie duševnej pohody („wellbeing“) a celkového psychického stavu. Koncept duševného zdravia a predovšetkým prevencia duševného zdravia u učiteľov sa preto stáva významnou oblasťou, na ktorú je potrebné sa zamerať. V zmysle uvedených myšlienok, analyzujúc viaceré prieskumy realizované v našich podmienkach a v zahraničí, sme považovali za nevyhnutné zamerať sa aj na mapovanie aktuálnej situácie u PZ na Slovensku. Vzhľadom na prebiehajúci vojenský konflikt na Ukrajine sme sa rozhodli v rámci prieskumu zamerať aj na oblasť možných nových zdrojov pracovných záťaží pre PZ súvisiacich so spomínanou situáciou. S prebiehajúcim konfliktom môžu vznikať pre PZ nové výzvy, ktorým musia čeliť (napr. začleňovanie ukrajinských detí/žiakov/učiteľov do slovenských škôl a i.). V kontexte vyššie uvedených myšlienok bolo zámerom prieskumu zistiť aktuálny stav duševného zdravia PZ, priniesť nové informácie o stave jednotlivých významných komponentov (symptómy stresu, najfrekventovanejšie zdroje stresu, wellbeing, nové záťažové situácie súvisiace s vojnovým konfliktom, existujúca podpora duševného zdravia) duševného zdravia PZ a poskytnúť podnety na tvorbu vzdelávacích programov, resp. obsahu vzdelávacích programov, individuálne a skupinové poradenstvo.
... Job resources propose the job in terms of motivation to achieve work goals. 37 However, job demands require physical and emotional strength to remove the barriers which cause hindrance in job requirements. Tims et al 38 acknowledged four dimensions of job crafting: increasing structural job resources, increasing social job resources, increasing challenging job demands, and decreasing hindering job demands. ...
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Purpose: Researchers have a wide-ranging consensus on the negative side of presenteeism that leads to productivity loss; however, little is known about its flipside that has undertaken motivational factors as potential antecedents. This implicit gap is addressed by exploring a new perspective of presenteeism and proposing employees' calling as its precursor with the help of self-determination theory (SDT). The mediating mechanism is explicated with job crafting by considering it a sensemaking strategy that offers a plausible explanation of the positive association between an employee's calling and presenteeism. This research is an attempt to explore the positive side of presenteeism and generalize the presenteeism findings in another sector apart from the medical field, as this phenomenon is gaining widespread acceptance in HR literature. Methods: The data were collected from 274 employees from the textile sector, and the hypotheses were tested using SmartPLS software. We collected time-lagged data from the textile sector employees of Pakistan. The individual-level data have been collected to test the relationship between calling, job crafting, and presenteeism. Results: The results indicate the positive association between calling and presenteeism through direct and indirect paths. However, the mediating mechanism through two dimensions of job crafting, crafting challenging job demands and crafting social job resources, was not supported. Conclusion: Drawing on SDT, we contribute to the literature by identifying calling as an antecedent of presenteeism. We propose and test the direct and indirect relationships between calling, job crafting, and presenteeism. Future researchers might attempt to test this model in different sectors like multinational companies, educational institutions, healthcare, retail, etc. The proposed relationships also lend themselves to be explicated with other mediators.
Purpose The purpose of this study is to explore the role of “overtime norms” as a mediator between performance-driven work climates and employee burnout. This study also examines in-role performance and work engagement as moderators between high-performance climates and burnout. Design/methodology/approach A snowball sample of 214 full-time working adults from the United States participated via an online survey. Data were analyzed using SmartPLS and conditional process analysis. Findings Results from conditional process analyses suggest (1) performance-driven climates are positively related to burnout, (2) overtime norms mediate the relationship between performance-driven climates and burnout, and (3) in-role performance and work engagement moderate that relationship such that highly competent and engaged employees are less prone to stress and burnout. Practical implications These results highlight the dangers of performance-driven work climates on employee well-being. Trends toward extended work hours which can be exacerbated by technological advancements inevitably come at a cost. Managers and organizations should be careful not to prioritize work life over non-work life. Originality/value This study contributes to the literature by identifying overtime norms as a mediator in the performance-driven work climate–burnout relationship. This study also identifies in-role performance and work engagement as resources that can reduce burnout.
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Evidence suggests that perceived school culture is the most powerful predictor of teachers’ work performance. However, studies to date have paid little attention to the potential mechanisms behind this association. On the basis of the job demands–resources (JD–R) model, the present study explored the mediating role of affective empathy and the moderating role of job tenure in the association between perceived school culture and teachers’ work engagement. 647 primary and secondary school teachers completed questionnaires measuring perceived school culture, affective empathy, and work engagement. After gender and educational level were included as covariates, the results showed that perceived school culture positively correlated with teachers’ work engagement, and more importantly, this association was partially mediated by affective empathy. In addition, job tenure significantly moderated the direct association between perceived school culture and work engagement. Specifically, there was a stronger association between perceived school culture and work engagement for teachers with shorter job tenure than those with longer job tenure. The findings suggested the direct effect of perceived school culture on work engagement, and the indirect effect of perceived school culture on work engagement through the mediating role of affective empathy. These findings enrich our understanding of how perceived school culture associates with work engagement, and highlight the moderating role of job tenure in the direct association between perceived school culture and work engagement.
This study aimed to investigate the relationship between job stress, burnout, and intention to leave, moderated by empathic concern and perspective-taking. The data were collected via the Maslach Burnout Inventory-Human Services Survey (MBI-HSS), Interpersonal Reactivity Index (IRI) measuring perspective-taking and empathic concern, Spielberger's Professional Stress Questionnaire, and a questionnaire measuring intention to leave. Medical doctors, nurses, and psychologists working in addiction facilities were surveyed. The results showed that, independently, job stress increases burnout and intention to leave. In addition, either cognitive or emotional factors of empathy prevent burnout and intention to leave; however, the preventing effect of each is reduced when they interact. Moreover, perspective-taking enhances the effect of job stress on intention to leave. This twofold effect of empathy for burnout and intention to leave provides practical implications for health-care professionals.
İşletmelerin performansını artırmada, çalışanların olumlu tutum ve davranışlarının önemli rol oynadığı bilinmektedir. Çalışanlarda olumlu tutum ve davranışların gelişmesi, örgütsel faktörlere bağlı olduğu kadar kişisel faktörlere de bağlı olabilmektedir. Örgütsel ve kişisel başarıda kilit unsurlardan birisi olan işe adanmışlık davranışı, önemi giderek artan, olumlu örgütsel tutum ve davranışlardan birisidir. İşe adanmışlık davranışına yol açabilecek öncülleri belirleyebilmenin, onu etkileyecek örgütsel ve bireysel faktörleri ortaya koyabilmenin işletme performansına katkı sunacağı düşünülmektedir. Bu çalışmanın amacı: işe adanmışlığı etkileyebilecek örgütsel destek ve bireylerin kişilik özellikleri arasındaki ilişkileri bir model çerçevesinde test etmektir. Örgütsel davranış araştırmalarında belirli bir kültür ve çevre dahilinde araştırmaları gerçekleştirmek daha tutarlı sonuçların elde edilmesine yol açabilmektedir. Bu bilgiler ışığında Malatya Organize Sanayi bölgesinde faaliyet gösteren, iki tekstil işletmesinin 421 çalışanından veriler toplanmış ve analiz edilmiştir. Analizler sonucunda örgütsel desteğin işe adanmışlık üzerinde pozitif açıklayıcı etkisinin olduğu ve bu iki değişken arasındaki ilişkide kişiliğin kısmi araçlık rolüne sahip olduğu sonucuna ulaşılmıştır.
This study began with the premise that people can use varying degrees of their selves. physically. cognitively. and emotionally. in work role performances. which has implications for both their work and experi­ ences. Two qualitative. theory-generating studies of summer camp counselors and members of an architecture firm were conducted to explore the conditions at work in which people personally engage. or express and employ their personal selves. and disengage. or withdraw and defend their personal selves. This article describes and illustrates three psychological conditions-meaningfulness. safety. and availabil­ ity-and their individual and contextual sources. These psychological conditions are linked to existing theoretical concepts. and directions for future research are described. People occupy roles at work; they are the occupants of the houses that roles provide. These events are relatively well understood; researchers have focused on "role sending" and "receiving" (Katz & Kahn. 1978). role sets (Merton. 1957). role taking and socialization (Van Maanen. 1976), and on how people and their roles shape each other (Graen. 1976). Researchers have given less attention to how people occupy roles to varying degrees-to how fully they are psychologically present during particular moments of role performances. People can use varying degrees of their selves. physically, cognitively, and emotionally. in the roles they perform. even as they main­ tain the integrity of the boundaries between who they are and the roles they occupy. Presumably, the more people draw on their selves to perform their roles within those boundaries. the more stirring are their performances and the more content they are with the fit of the costumes they don. The research reported here was designed to generate a theoretical frame­ work within which to understand these "self-in-role" processes and to sug­ gest directions for future research. My specific concern was the moments in which people bring themselves into or remove themselves from particular task behaviors, My guiding assumption was that people are constantly bring­ ing in and leaving out various depths of their selves during the course of The guidance and support of David Berg, Richard Hackman, and Seymour Sarason in the research described here are gratefully acknowledged. I also greatly appreciated the personal engagements of this journal's two anonymous reviewers in their roles, as well as the comments on an earlier draft of Tim Hall, Kathy Kram, and Vicky Parker.
Six organizational conditions of schools, identified from a review of the social-psychological literature on job design, are found to affect the job commitment of 1,213 teachers from 78 elementary schools throughout Tennessee. The authors divide organizational qualities into those that impinge on the tasks of defining boundaries and implementing the professional teaching task and those that directly affect the core instructional role of the teacher. They find that novice teachers' commitment is influenced more by organizational supports for the management of boundary issues, while experienced teachers are influenced more by organizational qualities that affect the core instructional tasks. They also find that midcareer teachers have a lower commitment to their jobs and place a greater emphasis on task autonomy than do either novices or veterans.
This study examined the antecedents of job strain (emotional exhaustion, health complaints) and withdrawal behaviour (e.g. lowered organizational commitment) among a cross-sectional sample of 131 academic staff members of the law department of a large Dutch university. Conservation of resources theory (Hobfoll, 1989) provided the theoretical background for this study. Strains and withdrawal behaviours were expected to be most prominent among those who reported having few resources and/or who reported high job demands. Structural equation modelling revealed that this was indeed the case. As predicted, differential patterns of effects emerged for job demands and job resources. Analysis of the effects of four job-specific stressors revealed that especially the structural aspects of a staff member's teaching task (e.g. the number of students in their classes) contributed strongly to perceived job demands. Theoretical and practical implications of the study are discussed.