TILBURG UNIVERSITY
Testing the Demand-Induced
Strain Compensation Model
Personality and the DISC model & the DISC model in
a new setting.
Masterthesis
13-6-2013
Kim E. R. van Amelsvoort BSc
ANR 883879
First supervisor: dr. Marieke van den Tooren
Second supervisor: dr. Marielle Stel
Abstract
Background. Negative job outcomes (i.e. burnout) are a major concern that has very serious
consequences. The Demand-Induced Strain Compensation (DISC) model proposes a way to
reduce these negative job outcomes. Most information with regard to the DISC model is
derived from samples in health and service sectors, therefore research into other occupational
sectors is needed.
Purpose. This study tests the effect of the triple match principle, extraversion and
conscientiousness on the stress buffer effect, within the profit sector. Hypothesis 1 states that
the stress buffer effect is most likely to occur in case of a triple match, less likely in case of a
double match and least likely in case of a non-match. Hypotheses 2 and 3 state that the stress
buffer effect will appear for people who score high on extraversion and conscientiousness but
not for people who score low on both.
Method. Cross sectional survey data were collected among the staff of ten companies within
the profit sector. 238 people filled in the questionnaire (63% response rate). Data were
analyzed by hierarchical regression analyses.
Results. No significant effects of the triple match principle, extraversion and
conscientiousness on the stress buffer effect were found. Data did not support the hypotheses.
Conclusion. Based on this study it could be concluded that the amount of match does not
influence the stress buffer effect, it could also be concluded that personality should not be
taken into account in relation to the stress buffer effect. Eventually, it could be concluded that
the DISC model is not suitable for the ‘broad’ profit sector.
Key words: Demand-Induced Strain Compensation Model, stress buffer effect, triple match
principle, extraversion, conscientiousness, profit sector
2
Introduction
A survey conducted by CBS (2012) indicates that 30% of the working population in
the Netherlands has to work under great time pressure regularly. This survey also indicates
that 41% of the working population perceives their pace of work as high. Besides this de
Bruin, van Boxmeer, Verwijs and le Blanc (2007) indicate that there has been an everincreasing workload in almost all jobs for the last decades. Working under time pressure, a
high pace of work and a high workload are examples of job demands (Demerouti, Bakker,
Nachreiner, & Schaufeli, 2001). Job demands can be described as those aspects of a job that
require effort (van den Tooren, de Jonge, & Dormann, 2011). Other examples of job demands
are finding solutions for complex problems, lifting heavy objects, dealing with aggressive
clients, shift work and recipient contact (Demerouti et al., 2001; van den Tooren et al., 2011).
There exists a relation between job demands and job outcomes. This means that when
job demands persevere this will lead to the experience of negative job outcomes (van den
Tooren & de Jonge, 2011). Examples of negative job outcomes are neck or back problems,
limb problems, memory functioning problems, mental exhaustion and emotional exhaustion
(i.e. burnout) (van den Tooren & de Jonge, 2011; van den Tooren & de Jonge, 2008).
Moderation
De Jonge and Dormann (2003) mention that negative job outcomes are a major
concern that has very serious consequences and that is still rising. This shows that it is
important to reduce negative job outcomes. The most obvious way to reduce negative job
outcomes is of course by reducing job demands but job demands often cannot be reduced
because they are part of the job.
De Jonge and Dormann (2003) describe job resources as variables that reduce negative
job outcomes that are a result of job demands. This means that job resources moderate the
3
relation between job demands and job outcomes (Demerouti et al., 2010; van den Tooren &
de Jonge, 2011). In fact job resources function as a stress buffer, because of this, the
moderation is called the stress buffer effect (de Jonge & Dormann, 2003). Job resources can
be described as work-related tools (i.e. opportunities, data, people, things) that can be used to
deal with job demands (van den Tooren & de Jonge, 2011). Examples of job resources are job
autonomy, emotional support from colleagues, technical equipment, feedback, rewards, job
control, participation, job security and supervisor support (Demerouti et al., 2001; van den
Tooren et al., 2011).
The stress buffer effect implies that people who are faced with high job demands, but
have a sufficient level of job resources to cope with the demands, will experience fewer
negative job outcomes than people who do not have a sufficient level of job resources (van
den Tooren & de Jonge, 2011), see Figure 1.
The stress buffer effect can be demonstrated with an example of an office worker. The
high workload (a job demand) of an office worker can be reduced by giving him or her a
training in time management (a job resource) by which he or she can cope better with the
workload and will eventually experience fewer negative job outcomes (e.g. mental
exhaustion).
Job demands
Job outcomes
Job resources
Figure 1: The stress buffer effect
4
Although the stress buffer effect is supposed to exist by many researchers, not much
evidence has been found for it (van den Tooren et al., 2011). The Demand-Induced Strain
Compensation (DISC) model could possibly explain why this effect has not been found much
in earlier research (de Jonge & Dormann, 2003).
The aim of the current study could be formulated into three goals. First, this study
wants to test the triple match principle, which is an important principle of the DISC model.
Second, this study wants to test the role of personality, especially of extraversion and
conscientiousness, on the stress buffer effect. Third, this study wants to test the DISC model
in another occupational sector than tested before, namely in the ‘broad’ profit sector.
Demand-Induced Strain Compensation Model
The Demand-Induced Strain Compensation (DISC) Model has been designed “to
explain what aspects of jobs may activate psychological compensation processes of strains, or
balance challenging job demands” (de Jonge & Dormann, 2003, p. 54). Like other job stress
models, the DISC model states that job resources moderate the relation between job demands
and job outcomes, in such a way that people experience fewer negative job outcomes because
of the job resources (van den Tooren et al., 2011).
In contrast to other job stress models, the DISC model is less global and general. The
other job stress models do not describe a specific mechanism that explains in what way job
demands can be compensated by job resources (de Jonge & Dormann, 2003). The DISC
model, however, does describe a specific mechanism. This could explain why the stress buffer
effect has not been found in other models but can be found in the DISC model.
There are a couple of key principles that are unique to the DISC model. These
principles will be explained below. Key principles of the DISC model are the
multidimensionality of concepts, the triple match principle (including double match and nonmatch) and the compensation principle (van den Tooren et al., 2011).
5
The multidimensionality of concepts. Job demands, job resources and job outcomes are
not one-dimensional concepts, they are multidimensional (de Jonge & Dormann, 2003). Job
demands, job resources and job outcomes can be either cognitive, emotional or physical in
nature (de Jonge & Dormann, 2003).
Examples can demonstrate the multidimensionality of concepts. A cognitive job
demand is displaying high levels of concentration and precision, an emotional job demand is
dealing with people who get easily angered and a physical job demand is having to bend and
stretch a lot at work (van de Ven et al., 2008). A similar distinction is possible with job
resources. A cognitive job resource is having the possibility to alternate complex tasks with
simple tasks, an emotional job resource is getting emotional support from others, a physical
job resource is being able to use adequate technical equipment to accomplish physically
strenuous tasks (van de Ven et al., 2008). Negative job outcomes can also be divided into
three categories. An example of a negative cognitive job outcome is having functional
memory problems, a negative emotional job outcome is feeling emotionally exhausted, a
negative physical job outcome is having low back pain (van de Ven et al., 2008).
The triple match principle. The moderating effects of job resources on the relation
between job demands and job outcomes are most likely to occur when job demands, job
resources and job outcomes match (van den Tooren et al., 2011), this means that they are most
likely to occur when they are all of the same kind (for example, when they are all emotional in
nature).
An example can demonstrate the triple match principle. An office worker who has to
work a lot behind his computer experiences as a result of this symptoms of RSI (repetitive
strain injury). This office worker has high physical job demands and needs physical resources
to lower these demands. An example of a physical resources is a software that obliges people
to take small breaks in which they have to do specific small exercises. As a result of this the
6
negative physical job outcomes will be lowered and the office worker does experience fewer
RSI symptoms.
Double match. A double match means that two variables match, but the third one does
not match. There are two kinds of double match, a double match of common kind and a
double match of extended kind. A double match of common kind means that job demands
and job resources match (they are, for example, both emotional in nature), but job outcomes
do not match (they are, for example, physical in nature) (van den Tooren et al., 2011). A
double match of extended kind means that job resources and job outcomes match (they are,
for example, both cognitive in nature), but job demands do not match (they are, for example,
emotional in nature) or that job demands and job outcomes match (they are, for example, both
physical in nature), but job resources do not match (they are, for example, cognitive in nature)
(van den Tooren et al., 2011). In these situations of double match, the moderating effect of job
resources is less likely to occur than in a situation of triple match (van den Tooren et al.,
2011).
Non-match. In this situation job demands, job resources and job outcomes are all
different in nature (job demands are, for example, physical in nature, job resources are
emotional in nature and job outcomes are cognitive in nature). In this situation the moderating
effect of job resources is least likely to occur (van den Tooren et al., 2011).
The compensation principle. The negative effects of job demands can be compensated
by job resources (de Jonge & Dormann, 2003). Job resources that match job demands are
most likely to counteract negative job outcomes (de Jonge & Dormann, 2003). Based on the
information about the key principles of the DISC model the first hypothesis can be
formulated.
Hypothesis 1: The stress buffer effect of job resources on the relation between job
7
demands and job outcomes is most likely to occur in case of a triple match, less likely to occur
in case of a double match and least likely to occur in case of a non-match.
Personality
This study suggests that there is another factor, besides match, that could have
influence on the stress buffer effect. It could be that the fact that people have access to job
resources does not mean that they really use these resources. It could be that there is a factor
that has influence on whether or not people use job resources, this factor in turn moderates the
stress buffer effect.
Personality could be this moderating factor because personality determines how
people behave (Larsen & Buss, 2008). It could be that, because of their personality, some
people are more inclined to make use of job resources than others. As a result of this it could
be suggested that the stress buffer effect counts for some people but not for all people, see
Figure 2.
Some research already paid attention to personality as a possible moderator on the
stress buffer effect. Van den Tooren and de Jonge (2011) studied if people’s promotion or
prevention focus served as a moderator on the stress buffer effect. They did not find an effect
of these personality variables. There are two possible explanations for this non-significant
result. First, it could be because of a methodological problem because they used dichotomous
variables. Second, they possibly studied personality constructs in relation to the stress buffer
effect that were not as influential as hypothesized. Whereas they studied the prevention and
promotion focus, this study investigates other personality variables that are possibly more
likely to have a moderating effect on the stress buffer effect.
8
Job demands
Job outcomes
Personality
Job resources
Figure 2: Moderating variable stress buffer effect
Especially two markers of the Big Five taxonomy could have a moderating role on the
stress buffer effect. The first one is extraversion. People who are extravert are talkative,
assertive, forward and outspoken. People who are introvert are quiet, bashful and inhibited
(John, Robins, & Pervin, 2010; Larsen & Buss, 2008).
It could be that the stress buffer effect is more present when people are extravert than
when people are introvert. This because extravert people may be more inclined to use
resources or ask people how to use resources because of their more talkative and assertive
nature (John et al., 2010; Larsen & Buss, 2008). People who are introvert are more quiet and
inhibited (John et al., 2010; Larsen & Buss, 2008) and as a result of this they possibly less
often ask how to use job resources or may less often make use of job resources (like talking
about your problems to a colleague or your supervisor). Based on this the second hypothesis
can be formulated.
Hypothesis 2: The stress buffer effect of job resources will appear for extravert people
but not for introvert people.
The second Big Five marker that could possibly have a moderating effect on the stress
buffer effect is conscientiousness. People who score high on conscientiousness are organized,
neat, orderly, practical, prompt and meticulous. People who score low on conscientiousness
9
are disorganized, disorderly, careless, sloppy, impractical and short term oriented (John et al.,
2010; Larsen & Buss, 2008).
It could be supposed that people who score high on conscientiousness may more often
use job resources than people who score low on conscientiousness. This because of the fact
that people who score high on conscientiousness are more organized and practical (John et al.,
2010; Larsen & Buss, 2008). These people may use job resources more often because they
realize that these resources are important to deal with job demands. As a result of their
organized nature they may also use the resources sooner and more consistent. People who
score low on conscientiousness are impractical, disorganized, careless and short term oriented
(John et al., 2010; Larsen & Buss, 2008). Because of their careless and impractical nature they
may not realize that the use of job resources is important, especially when they are important
in the long term (because they are short term oriented). Even if they realize that job resources
are important, for example, because they have some complaints, they probably use the
resources less consistent because of their disorganized nature. Based on this the third
hypothesis can be formulated.
Hypothesis 3: The stress buffer effect of job resources will appear for people who
score high on conscientiousness but not for people who score low on conscientiousness.
Occupational sector
This study is an important contribution to existing research. The sample used in this
study is much more diverse than the samples that were used before. Most information with
regard to the DISC model has been derived from samples in health and service sectors; people
in these sectors mainly deal with emotional job demands (van de Ven et al., 2008). Research
into other occupational sectors and groups was needed according to de Jonge and Dormann
(2006).
Van de Ven et al. (2008) did research into another sector than health and service
10
sectors; they derived data from employees of an information technology (ICT) firm. Although
this is quite a different work area compared to health and service sectors, they found the same
results. Besides the fact that the ICT sector is quite a different sector compared to health and
service sectors more studies are needed, for example, because van de Ven et al. (2008)
mention in their paper that all participants in their study were highly educated ICT employees.
These people have quite the same background (e.g. education) and work in a really specific
sector. Based on this it can be concluded that it is useful to study the DISC model in different
sectors than health and service sectors and in sectors that are more diverse than the ICT
sector.
The current study contributes to the generalizability of the DISC model because this
study tests the DISC model in various companies within the profit sector, the employees in
these companies have quite different backgrounds and the companies function in different
sectors within the profit sector. This sample could be called the ‘broad’ profit sector.
Method
Participants
The staff of ten very diverse companies within the profit sector participated in this
research. The companies that joined this research were a removal firm, a notary office, a
petrochemical company, a cleaning company, a tiling firm, a redecorating company, a
technical company which manufactures solar systems, windows and doors, a technical
company which manufactures lighting systems and electronic devices, a company which
manufactures record devices and a company which creates innovative solutions for
technology.
In total, 380 people were approached. Eventually, 275 people filled in the
questionnaire. After removing the participants that did not finish the questionnaire, 238
11
questionnaires appeared to be useful (63% response rate). 77.3% of the participants were
male, 22.7% were female (184 men and 54 women). The average age of the participants was
41 (SD = 10.28). The participants worked an average number of 41.7 hours a week (SD =
7.49). 80.3% of the participants were married (191 participants) and 68.5% of the participants
had children (163 participants). The tenure of the participants was an average of 11.5 years
(SD = 9.94). Half of the participants were satisfied with their salaries. 53% of the participants
finished higher education or university.
76% of the participants hold the Dutch nationality, 12% hold the Belgian nationality,
9% hold another European nationality. The remaining 3% of the participants hold another
nationality than a European one, these people were born in South-America, North-America,
Asia and Africa.
88.7% of the participants filled in the Dutch version of the questionnaire, 11.3% the
English version. All people who filled in the English version spoke fluently English, although
64.7% had a different native language.
Procedure
Participants had to fill in the questionnaire once. The study was a cross-sectional
survey study.
There were two possibilities to fill in the questionnaire; participants could fill in a
digital or a paper version. Participants who did not have the opportunity to fill in the digital
version received a paper version. 84% of the participants filled in the digital version of the
questionnaire, 16% of the participants filled in the paper version.
In case of the digital version, the staff of the companies received an e-mail about the
research. A couple of days later they received another e-mail with a link to the questionnaire.
They could fill in the questionnaire online, via Qualtrics. They were given two weeks to fill in
the questionnaire. After one week they received a reminder by e-mail with a link to the
12
questionnaire.
In case of the paper version, the executive of the possible participants gave them
general information about the research. Everyone received a questionnaire and people were
asked to return the questionnaires in a closed envelope in a special box within two weeks.
Participants could fill in a Dutch or an English version of the questionnaire depending
on their native language.
Measures
First, participants had to answer a couple of questions about demographic variables.
The demographic variables include their age, gender, nationality, native language, married
state, number of children, level of education, satisfaction with salary, working hours, tenure
and function. The demographic variables were measured by one-item scales.
Second, the personality characteristics that were used in this research were measured
using the Big Five Inventory (Denissen, Geenen, van Aken, Gosling, & Potter, 2008), people
had to rate 16 statements about extraversion and conscientiousness. People had to rate their
agreement with the statements on a 5-point Likert scale, ranging from 1 (strongly disagree) to
5 (strongly agree). An example statement with regard to conscientiousness is ‘I make plans
and follow them through’. An example statement with regard to extraversion is ‘I have an
assertive personality’. The reliability of the scale for conscientiousness was α = 0.734. The
reliability of the scale for extraversion was α = 0.839.
Then, the participants had to answer an adapted version of the DISQ 2.1 questionnaire
(de Jonge et al., 2009). This questionnaire measures the degree in which people have job
demands and job resources within their job. People had to rate their agreement with 32
statements on a 5-point Likert scale, ranging from 1 (never or very rarely) to 5 (very often or
always). An example question with regard to job demands is ‘I have to make complex
decisions at work’. An example question with regard to job resources is ‘I am able to stop
13
emotionally charged interactions with others for a while’. The reliability of the scale for
cognitive demands was α = 0.773, the reliability of the scale for emotional demands was α =
0.834, the reliability of the scale for physical demands was α = 0.948. The reliability of the
scale for cognitive resources was α = 0.646, the reliability of the scale for emotional resources
was α = 0.762, the reliability of the scale for physical resources was α = 0.903.
Finally, participants had to answer a couple of questions with regard to job outcomes.
The outcomes that were used were cognitive, emotional and physical job outcomes. Cognitive
job outcomes were measured using an adapted version of the scale developed by Chalder et
al. (1993). People had to rate their agreement with 6 items on a 5-point Likert scale, ranging
from 1 (totally disagree) to 5 (totally agree). An example statement with regard to cognitive
outcomes is ‘I make slips of the tongue when speaking’. The reliability of the scale for
cognitive outcomes was α = 0.748. Emotional job outcomes were measured by an index of
emotional exhaustion, namely the Utrechtse Burnout Scale (Schaufeli & van Dierendonck,
2000). Emotional outcomes were measured by 5 items that were scored on a 7-point Likert
scale, ranging from 1 (never) to 7 (always). An example statement is ‘I feel mentally
exhausted because of my job’. The reliability of the scale for emotional outcomes was α =
0.904. Last, physical job outcomes were measured by the scale of Hildebrandt and Douwes
(1991). The participants were asked if they had experienced physical complaints like neck and
back problems during the last six months. Physical outcomes were measured by 4 items that
were scored on a 3-point Likert scale. Possible responses were 1 (No), 2 (Sometimes) and 3
(Yes). An example question is ‘Did you experience pain in your neck and shoulders during
the last six months?’. The reliability of the scale for physical outcomes was α = 0.766. The
precise questionnaire can be found in Appendix A.
Data analysis
14
All three hypotheses were tested at a level of significance of α = 0,05. All results were
analyzed as two-tailed tests. The data were analyzed with the SPSS computer program. Job
demands, job resources, extraversion and conscientiousness were standardized.
The independent variables in this study were cognitive, emotional and physical job
demands, cognitive, emotional and physical job resources and conscientiousness and
extraversion. The dependent variables in this study were negative cognitive, emotional and
physical job outcomes.
Hypothesis 1 was tested by six hierarchical regression analyses. There were six
hierarchical regression analyses because there were three outcome measures (cognitive,
physical and emotional) and two conditions (match and non-match). There was a regression
analysis for every outcome in every condition. Testing both the match and the non-match
conditions is a standard procedure when testing the DISC model (de Jonge & Dormann,
2003). In both conditions, the control variables were first entered after this the standardized
main effects of job demands and job resources were also entered. After this the two-way
interactions between job demands and job resources were entered, at this point the two
conditions differ.
In the match condition the matching variables were looked at, this means that the
interaction between cognitive demands and cognitive resources was entered as well as the
interaction between emotional demands and emotional resources and the interaction between
physical demands and physical resources.
In the non-match condition variables that do not match were looked at. This means
that the interaction between cognitive demands and emotional resources was entered as well
as the interaction between cognitive demands and physical resources, the interaction between
emotional demands and cognitive resources, the interaction between emotional demands and
physical resources, the interaction between physical demands and cognitive resources and
15
finally the interaction between physical demands and emotional resources.
It was decided, based on the amount of times the different kinds of match appeared, if
Hypothesis 1 was supported. When triple match appeared more often than double match and
when double match appeared more often than non-match Hypothesis 1 was supported.
Hypotheses 2 and 3 were also tested using hierarchical regression analyses. The
procedures for both hypotheses were the same, but in the second hypothesis extraversion was
used, in the third hypothesis conscientiousness was used. These hypotheses were also tested
by six hierarchical regression analyses. In the match as well as the non-match condition the
control variables were first entered, after this the main effects of demands, resources, and
extraversion and conscientiousness were entered. After this the two-way interactions were
entered as explained above, but there were also entered 2-way interactions with extraversion
and conscientiousness. Finally, the three-way interactions between demands, resources, and
extraversion and conscientiousness were entered.
It was decided, based on the number of significant 3-way interactions with personality,
if Hypothesis 2 and Hypothesis 3 were supported. Hypothesis 2 and Hypothesis 3 were
supported when there were more significant than non-significant 3-way interactions with
personality.
Results
Correlations hypotheses
Before the hypotheses were tested it was important to know what demographic
variables correlated with the dependent variables. Three dependent variables were taken into
account, namely negative cognitive outcomes, negative emotional outcomes and negative
physical outcomes. Variables that correlated with the dependent variables were entered as
covariates in the regression analyses. Table 1 (Appendix B) contains the correlations between
16
covariates and the dependent variables.
First, correlations with cognitive outcomes were taken into account. No demographic
variables correlated with cognitive outcomes (see Table 1). Based on this it was decided that
no covariates were entered in regression analyses with cognitive outcomes as dependent
variable.
Second, correlations with emotional outcomes were taken into account. Two variables
correlated with emotional outcomes, namely having children (r= -.14, p= .04) and satisfaction
with salary (r= -.19, p= .00), see Table 1. These demographic variables were entered as
covariates in regression analyses with emotional outcomes as dependent variable.
Finally, correlations with physical outcomes were taken into account. Two variables
correlated with physical outcomes, namely level of education (r= -.16, p= .02) and
satisfaction with salary (r= -.20, p= .00), see Table 1. These demographic variables were
entered as covariates in regression analyses with physical outcomes as dependent variable.
Demand-Induced Strain Compensation Model
To test Hypothesis 1 the information of Table 2 and Table 3 was taken into account.
Table 2 (Appendix B) contains regression analyses of the three dependent variables in the
match condition, Table 3 (Appendix B) contains regression analyses of the three dependent
variables in the non-match condition.
Based on three regression analyses in the match condition (see Table 2) it could be
concluded that there were no triple matches, out of three possible triple matches. There was
one double match of common kind out of six possible double matches of common kind,
namely an interaction between physical demands and physical resources in the prediction of
emotional outcomes (b= -.19, p= .03). This significant interaction showed that when physical
demands became higher, people with higher physical resources experienced fewer negative
emotional outcomes compared to people with low physical resources, see Graph 1 (Appendix
17
C).
The three regression analyses in the non-match condition (see Table 3) showed three
double matches of extended kind out of twelve possible double matches of extended kind. The
first double match of extended kind was, an interaction between physical demands and
cognitive resources in the prediction of cognitive outcomes (b= .22, p= .00). This significant
interaction did not show a stress buffer effect, this because the relation was not negative. In
this situation it was shown that when the physical demands of a job became higher, people
with high cognitive resources experienced more negative cognitive outcomes compared to
people with low cognitive resources, see Graph 2 (Appendix C). The second double match of
extended kind was the interaction between physical demands and emotional resources in the
prediction of emotional outcomes (b= -.14, p= .04). This significant relation showed that
when physical demands became higher, people with high emotional resources showed fewer
negative emotional outcomes compared to people with low emotional resources, see Graph 3
(Appendix C). The last double match of extended kind was the interaction between emotional
demands and physical resources in the prediction of physical outcomes (b= .21, p= .02). This
significant interaction did not show a stress buffer effect, because the relation was positive. It
was shown that when emotional demands of a job became higher, people with high physical
resources experienced more negative physical outcomes than people with low physical
resources, see Graph 4 (Appendix C).
One significant non-match out of six possible non-matches was found, namely an
interaction between emotional demands and physical resources in the prediction of cognitive
outcomes (b= -.21, p= .02). This significant relation showed that when emotional demands
became higher, people with high physical resources experienced fewer negative cognitive
outcomes compared to people who had low physical resources, see Graph 5 (Appendix C).
Altogether, no triple matches were found, while three triple matches would have been
18
possible, 0% of triple matches was significant. One double match of common kind was found,
while six double matches of common kind would have been possible. One double match of
extended kind that was in line with the stress buffer effect was found. Twelve double matches
of extended kind would have been possible. In total 11% of double matches was significant.
One significant non-match was found out of six possible non-matches, 17% of non-matches
was significant.
Based on regression analyses described above it could be concluded that Hypothesis 1,
the stress buffer effect of job resources on the relation between job demands and job outcomes
is most likely to occur in case of a triple match, less likely to occur in case of a double match
and least likely to occur in case of a non-match, was not confirmed.
The effect of personality on the stress buffer effect was tested. First, the effect of
extraversion on the stress buffer effect was tested. Table 4 (see Appendix B) contains
regression analyses of three dependent variables in the match condition, Table 5 (see
Appendix B) contains regression analyses of three dependent variables in the non-match
condition. Table 4 and Table 5 were used to test Hypothesis 2.
Based on three-way interaction in both the match condition and the non-match
condition it could be concluded that there were no significant three-way interactions with
extraversion. This means that extraversion does not have an effect on whether or not people
use resources. Based on this it could be concluded that extraversion does not moderate the
stress buffer effect.
Based on the regression analyses described above it could be concluded that
Hypothesis 2, the stress buffer effect of job resources will appear for extravert people but not
for introvert people, was not confirmed.
Second, the effect of conscientiousness on the stress buffer effect was tested. Table 6
(see Appendix B) contains regression analyses of three dependent variables in the match
19
condition, Table 7 (see Appendix B) contains regression analyses of three dependent variables
in the non-match condition. Table 6 and Table 7 were used to test Hypothesis 3.
The three-way interaction in both the match condition and the non-match condition
showed that there were no significant three-way interactions with conscientiousness. This
means that conscientiousness does not have an effect on whether or not people use resources.
Based on abovementioned it could be concluded that conscientiousness does not moderate the
stress buffer effect.
Based on the regression analyses described above it could be concluded that
Hypothesis 3, the stress buffer effect of job resources will appear for people who score high
on conscientiousness but not for people who score low on conscientiousness, was not
confirmed.
Discussion
The aim of the current study could be formulated into three goals. First, this study
wanted to test the triple match principle. Second, this study wanted to test the role of
personality, especially of extraversion and conscientiousness, on the stress buffer effect.
Third, this study wanted to test the DISC model in another occupational sector than tested
before, namely in the ‘broad’ profit sector.
A couple of positive points with regard to this study could be mentioned. First, this
study was quite unique. So far, in most cases, the DISC model had been tested within health
and service sectors only, whereas this study tested the DISC model within the profit sector.
Because of this, this study could give people a notion of the usability of the DISC model
outside health and service sectors. Second, the environments in which the participants worked
were all within the profit sector, although of quite different kinds. Because of this, results
apply to multiple environments and not only to people who worked in a specific sector, like in
the study of van de Ven et al. (2008). A last strong point of this study was that this study was
20
also quite unique in proposing that personality could moderate the stress buffer effect.
Three hypothesis were used to test the DISC model and the effect of personality. It
was presupposed that the stress buffer effect of job resources on the relation between job
demands and job outcomes was most likely to occur in case of a triple match, less likely to
occur in case of a double match and least likely to occur in case of a non-match. The other
two presuppositions stated that the stress buffer effect of job resources would appear for
extravert people and for people who score high on conscientiousness, but not for introvert
people and for people who score low on conscientiousness.
Demand-Induced Strain Compensation Model
Results of six hierarchical regression analyses revealed no clear differences between
the conditions of match, so between triple match, double match and non-match. This was in
contrast with the studies of de Jonge and Dormann (2003) and van den Tooren et al. (2001)
and contrary to expectations. Based on this study it could be concluded that match did not
influence the stress buffer effect of job resources on the relation between job demands and job
resources. This was in contrast with Hypothesis 1.
There could be a methodological explanation for this result. The sample size of this
study was possibly too small to test the DISC model in a proper way. This had to do with the
fact that quite complex hierarchical regression analyses were needed to test the DISC model;
because of the complexity and the size of the regression analyses it was really hard to find an
effect.
Another explanation was related to the sector in which the DISC model was tested.
The DISC model was originally designed for health and service sectors (de Jonge &
Dormann, 2006) and was once studied in a really specific profit sector, namely the ICT sector
(van de Ven et al., 2008). This study wanted to test the DISC model in a more broad and
general profit sector, and did not find support for the DISC model in this sector. Based on this
21
study, within these specific companies, it could be concluded that the DISC is not useful in
the ‘broad’ profit sector but maybe only in specific sectors within the profit sector.
Hypotheses 2 and 3 tested the effect of personality on the stress buffer effect. Contrary
to expectations, results of this study did not show an effect of both personality variables,
extraversion and conscientiousness, on the appearance of the stress buffer effect.
In this situation the same methodological explanation as mentioned above, the small
sample size, could explain this result. The small sample size was even a bigger problem,
because hierarchical regression analyses became more complex because of the three-way
interactions that were used to test Hypothesis 2 and Hypothesis 3.
There might be two other explanations for these results that had to do with the content.
First, van den Tooren and de Jonge (2011) also did not found an effect of personality on the
stress buffer effect. In this study other personality variables than in the study of van den
Tooren and de Jonge (2011) were tested, but the effect of personality on the stress buffer
effect was again not found. This possibly shows that there exists no relation between
personality and the stress buffer effect.
Second, it could be mentioned that there are possibly factors other than personality
that may have an effect on the stress buffer effect. A factor that could possibly influence the
stress buffer effect is recovery during detachment from work. De Jonge, Spoor, Dormann,
Sonnentag and van den Tooren (2012) studied recovery during detachment from work in
relation to the DISC model. They state that, in the long term, less or no recovery during
detachment from work will lead to health problems. Based on this study it would be
interesting to study recovery during detachment from work in relation to the stress buffer
effect and to look at its effects.
Limitations
22
A first limitation is the design used in this study. A longitudinal design, in general,
gives more reliable results, because data have not been based on one moment, compared to
the cross-sectional design that has been used in this study.
Second, the small sample size in this study can be a limitation. The small sample size
is especially a limitation because of the fact that the model has been tested with two- and
three-way interactions, whereas these quite complex analyses need a big sample size.
Although the sample size is quite small, it should have been possible to find an effect because
of the simple design that was used in this study.
Finally, a common method variance would possibly appear because self-report surveys
were used. It would have been better to use more objective measures. However, Spector
(2006) mentioned in his study that common method variance is not necessarily linked to selfreport surveys and that common method variance should not be seen as a big problem.
Theoretical implications
First, this study did not found any support for the triple match principle, which is a
really important principle of the DISC model. However, this result is in contrast with the
results of van den Ven et al. (2008), who studied the DISC model in a specific profit sector. In
general, the usability of the DISC model in the profit sector could be doubted based on this
study and it could be concluded that more research is needed because van de Ven et al. did
find support for the triple match principle.
Second, results of this study show partial support for the stress buffer effect. In 11% of
the cases support for the stress buffer effect has been found, in the other cases no support has
been found. The stress buffer effect is an important principle of the DISC model, so partial
support for an important principle of the DISC model has been found.
Third, this study mentioned personality as a variable that could have influence on the
stress buffer effect. However, this study did not find any support for the moderating role of
23
personality (i.e. extraversion and conscientiousness) on the stress buffer effect. Because of
this it could be concluded that personality does not have an effect on the stress buffer effect,
especially when combined with the study of van den Tooren et al. (2011) in which no support
for personality has been found either.
Practical implications
First, employers in the profit sector can doubt, because of the results with regard to the
triple match principle, whether every aspect of the DISC model should be taken into account
to reduce the negative outcomes their employees’ experience. Employers in the profit sector
could possibly just give resources in a random way, because the partial support for the stress
buffer effect demonstrates that resources can have an effect, but it does not have to be taken
into account if these resources match with demands and outcomes.
Second, the results of this study on personality suggest that employees with different
personality characteristics react the same to resources that are provided to them. As a result of
this it can be concluded that employers do not have to take into account the personalities of
their employees when they provide resources to them.
Follow-up
It could be interesting to test if there is, indeed, no support for the DISC model in the
‘broad’ profit sector. This follow-up study should especially need a bigger sample size
because the sample size could be a factor that had a big influence on this study. It would also
be interesting to study separately different branches within the profit sector. This because of
the fact that van de Ven et al. (2008) did find support for the DISC model within one branch
of the profit sector (the ICT sector) but this study did not find support for the DISC model
when looked at the ‘broad’ profit sector. Maybe the DISC model only works within specific
sectors.
24
It is also interesting to look for other characteristics that could possibly influence the
stress buffer effect, like the recovery during detachment from work that was mentioned by de
Jonge et al. (2012). Future research could test if the stress buffer effect appears more often
among people who have a good recovery during detachment from work than among people
who do not have a good recovery during detachment from work.
Finally, it was mentioned that the most obvious way to reduce negative job outcomes
was by reducing job demands. It was also mentioned that job demands often could not be
reduced because they were part of a job (de Jonge & Dormann, 2003). This study did not find
much support for the fact that job resources could reduce negative job outcomes. Because of
this it is maybe interesting to look for a possibility to reduce the negative job outcomes
directly by reducing job demands. Reducing job demands could be done by hiring some extra
people, but this is expensive. CBS (2013) mentioned that the costs of absence through
absenteeism in the Netherlands were 3.95% of the total labor costs; this high absenteeism rate
could be caused by high job demands. It could be interesting to study what is more expensive,
hiring some extra people or paying the costs of absenteeism due to high job demands.
Conclusion
This study shows that there is no significant effect of the amount of match on the
appearance of the stress buffer effect. This means that there is no support for an important
principle of the DISC model. It was also shown that there was no effect of personality (i.e.
extraversion and conscientiousness) on the appearance of the stress buffer effect. This means
that personality should not be taken into account in relation to the DISC model. Finally, it
could be concluded, based on this study, that there is no support for the DISC model within
the ‘broad’ profit sector. Based on the results of this study it would be interesting to look at
the usability of the DISC model within the profit sector and to look at the DISC model and its
principles in general.
25
References
CBS (2013). Kosten ziekteverzuim. Retrieved on 28-4-2013 from: www.cbs.nl/nlNL/menu/methoden/toelichtingen/alfabet/k/kosten-ziektenverzuim.htm
CBS (2012). Workload back at 1996 level. Retrieved on 14-11-2012 from:
fttp://www.cbs.nl/NR/rdonlyres/72775143-715C-4692
A70CF61109E2F23B/0/pb02e136.pdf
Chalder, T., Berelowits, G., Pawlikowska, T., Watts, L., Wessely, S., Wright, D., & Wallace,
E.P. (1993). Development of a fatique scale. Journal of Psychosomatic Research, 37,
147-153.
De Bruin, R., van Boxmeer, F., Verwijs, C., & Le Blanc, P. (2007). Het demand-induced
strain compensation (DISC) model nader onderzocht: Resultaten van een
internetstudie in verschillende bedrijfssectoren. Gedrag & Organisatie, 20, 239-258.
De Jonge, J., & Dormann, C. (2006). Stressors, resources, and strains at work: A longitudinal
test of the triple match principle. Journal of Applied Psychology, 91(5), 1359-1374.
De Jonge, J., & Dormann, C. (2003). The DISC model: demand-induced strain
compensation mechanisms in job stress. Londen: Taylor & Francis.
De Jonge, J., Dormann, C., van Vegchel, N., von Nordheim, T., Dollard, M., Cotton, S., &
van den Tooren, M. (2009). The DISC questionnaire 2.1. Eindhoven: Eindhoven
University of Technology.
De Jonge, J., Spoor, E.M.B., Dormann, C., Sonnentag, S., & van den Tooren, M. (2012). Take
a break?!: Off-job recovery, job demands, and job resources as predictors of health,
active learning, and creativity. European Journal of Work and Organizational
Psychology, 21(3), 321-348.
Demerouti, E., Bakker, A.B., Nachreiner, F., & Schaufeli, W.B. (2001). The job demandsresources model of burnout. Journal of Applied Psychology, 86(3), 499-512.
26
Denissen, J.J.A., Geenen, R., van Aken, M.A.G., Gosling, S.D., & Potter, J. (2008).
Development and validation of a Dutch translation of the big five inventory (BFI).
Journal of Personality Assessment, 90, 152-157.
John, O.P., Robins, R.W., Pervin, L.A. (2010). Handbook of personality: Theory and
research. New York: The Guilford Press.
Hildebrandt, V.H., & Douwes, M. (1991). Lichamelijke Belasting en Arbeid: Vragenlijst
Bewegingsapparaat. Voorburg: Dictoraat-Generaal van de Arbeid.
Larsen, R.J., Buss, D.M. (2009). Personality psychology: Domains of knowledge about
human nature. Europe: McGraw – Hill Education.
Schaufeli, W.B., & van Dierendonck, D. (2000). Utrechtse burnout schaal (UBOS):
Handleiding. Lisse: Swets & Zeitlinger.
Spector, P.E. (2006). Method variance in organizational research: Truth or urban legend?
Organizational Research Methods, 9(2), 221-232.
Van den Tooren, M., & de Jonge, J. (2011). Job resources and regulatory focus as
moderators of short-term stressor-strain relations: A daily diary study. Journal of
Personnel Psychology, 10 (3), 97-106.
Van den Tooren, M., de Jonge, J., & Dorman, C. (2011). The demand-induced strain
compensation model: Background, key principles, theoretical underpinnings, and
extended empirical evidence. In A. Caetano, Silva, S., & Chambel, M.J. (Eds.), New
challenges and interventions in the psychosocial work environment. Munich:
Rainer Hampp.
Van den Tooren, M., & de Jonge, J. (2008). Managing job stress in nursing: What kind of
resources do we need? Journal of Advanced Nursing, 63(1),75-84.
Van de Ven, B., Vlerick, P., & de Jonge, J. (2008). The interplay of job demands, job
27
resources and cognitive outcomes in informatics. Stress and Health, 24, 375-382.
28
Appendix A
- Questionnaire Thank you for participating in this study. Filling in this questionnaire will take about 10
minutes. Your answers to this questionnaire are anonymous. Choose the answer that fits
the best to your specific situation. There are no right or wrong answers.
The questionnaire will start with some general questions. Fill in or mark the answer that
is most suitable to your situation.
1. What is your gender?
o male
o female
2. What is your age?
………………..
3. What is your nationality?
………………..
4. What is your civil status?
o Single and living at home (not with your partner)
o Single and living at your own
o Having a relationship but living at home (not with your partner)
o Having a relationship but not living together
o Living together or married
o Divorced
o Widow or widower
5. Do you have children?
o No
o Yes, how many? ……. Children.
6. What is the highest level of education you have finished?
o Primary/ elementary/ grammar school
o High school
o Practical education, namely: …………….
o Higher education, namely: ……………
o University
o No finished education
o Something else, namely: ……………
29
7. How satisfied are you with your salary?
Very
dissatisfied
1
Dissatisfied
Neutral
Satisfied
Very satisfied
2
3
4
5
8. How many hours do you work in a week?
………………..
9. In which function do you work at this moment?
………………..
10. How long do you work in this company?
………………..
The following questions will be somewhat more specific about your work. Please mark
the answer that is most suitable to your situation.
Never or
very
rarely
Rarely
Occasionaly
Often
Very
often
or
always
1. I have to make complex
decisions at work.
1
2
3
4
5
2. I need to display high levels of
concentration and precision at
work.
1
2
3
4
5
3. I have to solve work-related
problems within a limited time
frame.
1
2
3
4
5
4. I have to remember many
things simultaneously.
1
2
3
4
5
5. I have to do a lot of mentally
taxing work.
1
2
3
4
5
6. I have to deal with people (e.g.
clients, colleagues or supervisors)
who have unrealistic
expectations.
1
2
3
4
5
30
7. I have to control my emotions
to complete tasks within a limited
time frame.
1
2
3
4
5
8. I have to deal with people (e.g.
clients, colleagues or supervisors)
whose problems touch me
emotionally.
1
2
3
4
5
9. I have to deal with people (e.g.
clients, colleagues or supervisors)
who get easily angered towards
me.
1
2
3
4
5
10. I have to do a lot of
emotionally draining work
1
2
3
4
5
11. I have to display emotions
(e.g. towards clients, colleagues
or supervisors) that are
inconsistent with my feelings.
1
2
3
4
5
12. I have to perform a lot of
physically strenuous tasks to
carry out my job.
1
2
3
4
5
13. I have to bend and/or to
stretch a lot at work
1
2
3
4
5
14. I have to work in
uncomfortable or impractical
postures to do my work.
1
2
3
4
5
15. I have to lift or move heavy
persons or objects (more than 10
kg).
1
2
3
4
5
16. I have to perform physical
activity in a quick and
continuous fashion.
1
2
3
4
5
17. I have the opportunity to take
a mental break when tasks
require a lot of concentration.
1
2
3
4
5
18. I have the opportunity to
vary complex tasks with simple
1
2
3
4
5
31
tasks.
19. I receive information from
others (e.g. colleagues or
supervisors) in solving complex
tasks.
1
2
3
4
5
20. I am able to use my
knowledge and intellectual skills
to solve complex tasks.
1
2
3
4
5
21. I have access to useful
information (from computers,
books, records, colleagues and
operating instructions) to solve
complex tasks.
1
2
3
4
5
22. I have the opportunity to
determine my own work method.
1
2
3
4
5
23. I am able to stop emotionallyladen interactions with others for
a while whenever I want.
1
2
3
4
5
24. I feel esteemed at work by
others (e.g. clients, colleagues or
supervisors).
1
2
3
4
5
25. I get emotional support from
others (e.g. clients, colleagues or
supervisors) when a threatening
situation at work occurs.
1
2
3
4
5
26. I have the opportunity to
express my emotions after a
threatening situation occurs,
without experiencing negative
consequences (e.g. from
supervisors, colleagues or
clients).
1
2
3
4
5
27. Other people (e.g. clients,
colleagues or supervisors) will be
a listening ear for me when I face
a threatening situation.
1
2
3
4
5
28. I am able to plan my work in
1
2
3
4
5
32
a way that physical tasks require
no more physical exertion than I
can manage.
29. I am able to use adequate
technical equipment to
accomplish physically strenuous
tasks.
1
2
3
4
5
30. I am able to decide what
posture I will use to perform
physically strenuous tasks.
1
2
3
4
5
31. I am able to take a physical
break when things get physically
strenuous.
1
2
3
4
5
32. I receive physical help from
others (e.g. clients, colleagues or
supervisors) in lifting or moving
heavy persons or objects.
1
2
3
4
5
The following questions will be somewhat more about yourself.
Mark the answer that suits the best to your situation.
Disagree Disagree
very
much
Neutral
Agree
Agree
very
much
1. When I work I do a thorough
job.
1
2
3
4
5
2. I will persevere until the task is
finished.
1
2
3
4
5
3. I tend to be disorganized.
1
2
3
4
5
4. I tend to be lazy.
1
2
3
4
5
5. I am a reliable worker.
1
2
3
4
5
6. I do things efficiently.
1
2
3
4
5
7. I make plans and follow
through them.
1
2
3
4
5
33
8. I am easily distracted.
1
2
3
4
5
9. I can be somewhat careless
1
2
3
4
5
10. I tend to be quiet.
1
2
3
4
5
11. I generate a lot of
enthousiasm.
1
2
3
4
5
12. I am outgoing and sociable.
1
2
3
4
5
13. I am reserved.
1
2
3
4
5
14. I am sometimes shy/ inhibited.
1
2
3
4
5
15. I am full of energy.
1
2
3
4
5
16. I have an assertive
personality.
1
2
3
4
5
Neutral
Agree
Totally
agree
Now there will be again some questions about your work.
Choose the answer that fits the best to your situation.
Totally Disagree
disagree
1. I have difficulties in
concentrating.
1
2
3
4
5
2. I have difficulties in thinking
bright.
1
2
3
4
5
3. I make slips of the tongue when
speaking.
1
2
3
4
5
4. It is difficult for me to find the
correct word.
1
2
3
4
5
5. My memory is good.
1
2
3
4
5
6. I have lost interest in the things I
used to do.
1
2
3
4
5
34
There will be again some questions about your functioning at work.
Encircle the most suitable answer.
Never
Almost
never
Regularly
Often
Very
often
Always
2
Now
and
then
3
1. I feel mentally
exhausted because of
my work.
1
4
5
6
7
2. Working the whole
day is very hard for
me.
1
2
3
4
5
6
7
3. I feel 'burned out'
because of my work.
1
2
3
4
5
6
7
4. I feel used up at the
end of a working day.
1
2
3
4
5
6
7
5. I feel tired at the
beginning of the day
when I know I have to
work for a whole day.
1
2
3
4
5
6
7
The following questions will be about your physical health.
Choose the answer that is most suitable to your situation.
Did you experience the last six month pain
in…
1. Your neck and shoulders?
No
Sometimes
Yes
1
2
3
2. The middle part of your back?
1
2
3
3. The lower part of your back?
1
2
3
4. Your limbs (legs and arms)?
1
2
3
Do you have any comments or questions about the questionnaire?
Thank you very much for participating in this study!
35
Appendix B
- Tables –
Table 1
Correlations for the covariates with the dependent variables.
Item
1
2
3
4
5
6
7
1.
Gender
2.
Civil status
-.01
3.
Having children
.29**
-.44**
4.
Level of education
.16*
-.02
.14*
5.
Satisfaction with
salary
0.06
-.05
.11
.08
6.
Cognitive outcomes
-.01
-.06
.03
-.04
-.13
7.
Emotional outcomes
-.11
-.01
-.14*
-.07
-.19**
.40**
-.06
8.
Physical outcomes
Note. *p < .05; **p < .01
-.02
-.09
-.16*
-.20**
.23**
36
.46**
8
Table 2
Regression model Hypothesis 1 match
Match
DV 1:
Cognitive
outcomes
DV 2:
Emotional
outcomes
DV 3:
Physical
outcomes
B
SE
B
SE
B
SE
-.01
.07
.50
.32
1.05**
.40
Having children
-
-
.01
.14
-
-
Satisfaction with
salary
-
-
-.16*
.08
-.24**
.08
Level of education
-
-
-
-
-.05
.05
Cognitive demands
-.15
.08
.19**
.07
.08
.08
Emotional demands
.12
.08
.13
.07
-.04
.08
Physical demands
.02
.08
.34**
.07
.24**
.08
Cognitive resources
-.06
.09
-.01
.08
.06
.09
Emotional resources
-.06
.09
-.01
.08
-.10
.06
Physical resources
-.05
.09
-.13
.08
-.02*
.07
Cognitive demands x
cognitive resources
-.04
.06
-.02
.06
-.09
.06
Emotional demands
x emotional
resources
-.07
.07
.04
.06
-.02
.07
.08
-.15
.09
Constant
-.09
.09
-.18**
Physical demands x
physical resources
Note. *p < .05; **p < .01
B: unstandardized Beta
SE: standard error
–: no covariate in this regression analysis
37
Table 3
Regression model Hypothesis 1 non-match
Non-Match
DV 1:
Cognitive
outcomes
DV 2:
Emotional
outcomes
DV 3:
Physical
outcomes
B
SE
B
SE
B
SE
.05
.07
.53
.32
.95*
.40
Having children
-
-
.03
.14
-
-
Satisfaction with
salary
-
-
-.18*
.08
-.24**
.08
Level of education
-
-
-
-
-.03
.05
Cognitive demands
-.12
.08
.22*
.07
.11
.08
Emotional demands
.13
.08
.14
.07
-.04
.08
Physical demands
.12
.08
.34**
.07
.28**
.09
Cognitive resources
-.10
.09
-.03
.09
.05
.09
Emotional resources
-.06
.09
-.05
.08
-.16
.09
Physical resources
.03
.08
-.03
.08
-.07
.08
Cognitive demands x
emotional resources
-.03
.07
.06
.07
.09
.07
Cognitive demands x
physical resources
.11
.09
-.01
.08
.05
.09
Emotional demands
x cognitive resources
.03
.07
.02
.07
-.10
.07
Emotional demands
x physical resources
-.21*
.09
-.08
.08
.21**
.09
Physical demands x
cognitive resources
.22**
.07
.06
.07
.11
.07
Physical demands x
emotional resources
-.13
.07
-.14*
.07
-.02
.07
Constant
38
Note. *p < .05; **p < .01
B: unstandardized Beta
SE: standard error
–: no covariate in this regression analysis
39
Table 4
Regression model Hypothesis 2 match
Match
DV 1:
Cognitive
outcomes
DV 2:
Emotional
outcomes
DV 3:
Physical
outcomes
B
SE
B
SE
B
SE
-.37
.07
.35
.31
1.06
.09
Having children
-
-
.07
.14
-
-
Satisfaction with
salary
-
-
-.14
.08
-.24
.09
Level of education
-
-
-
-
-.04
.05
Cognitive demands
-.14
.08
.21*
.07
.08
.08
Emotional demands
.18*
.08
.14
.07
-.05
.08
Physical demands
.04
.08
.36**
.07
.26**
.09
Cognitive resources
-.06
.09
.02
.08
.05
.09
Emotional resources
.01
.09
-.01
.08
-.08
.09
Physical resources
-.01
.09
-.13
.08
-.20*
.09
-.31**
.07
-.12
.07
.07
.07
Cognitive demands x
cognitive resources
.00
.06
.00
.06
-.09
.06
Emotional demands
x emotional
resources
-.08
.07
-.02
.07
-.03
.07
Physical demands x
physical resources
.02
.10
-.22*
.09
-.23*
.10
Cognitive demands x
extraversion
-.05
.08
-.06
.07
-.09
.08
Emotional demands
x extraversion
.08
.08
.04
.07
.05
.08
Constant
Extraversion
40
Physical demands x
extraversion
-.13
.09
-.08
.08
-.17
.09
Cognitive resources
x extraversion
.04
.10
-.30**
.10
-.28**
.10
Emotional resources
x extraversion
.11
.08
.12
.07
.10
.08
Physical resources x
extraversion
-.04
.08
-.02
.07
-.03
.08
Cognitive demands x
cognitive resources x
extraversion
.06
.07
-.01
.07
-.04
.07
Emotional demands
x emotional
resources x
extraversion
-.03
.07
-.02
.06
-.10
.07
Physical demands x
physical resources x
extraversion
.03
.09
-.03
.08
-.08
.09
Note. *p < .05; **p < .01
B: unstandardized Beta
SE: standard error
–: no covariate in this regression analysis
41
Table 5
Regression model Hypothesis 2 non-match
Non-Match
DV 1:
Cognitive
outcomes
DV 2:
Emotional
outcomes
DV 3:
Physical
outcomes
B
SE
B
SE
B
SE
.01
.08
.36
.32
.91*
.42
Having children
-
-
.02
.15
-
-
Satisfaction with
salary
-
-
-.14
.08
-.22*
.09
Level of education
-
-
-
-
-.04
.05
Cognitive demands
-.13
.08
.25**
.07
.13
.08
Emotional demands
.17*
.08
.12
.08
-.07
.08
Physical demands
.12
.08
.35**
.08
.28**
.09
Cognitive resources
-.10
.09
.01
.09
.07
.09
Emotional resources
.01
.09
-.06
.08
-.19*
.09
Physical resources
.02
.08
-0.2
.08
-.06
.09
-.26**
.08
-.17*
.08
.01
.08
Cognitive demands x
emotional resources
.03
.08
-.01
.07
.03
.08
Cognitive demands x
physical resources
.08
.09
.02
.09
.08
.10
Emotional demands
x cognitive resources
.00
.08
.00
.08
-.08
.08
Emotional demands
x physical resources
-.18*
.09
-.08
.08
-.25**
.09
Physical demands x
cognitive resources
.19*
.08
.04
.07
.07
.08
Constant
Extraversion
42
Physical demands x
emotional resources
-.07
.08
-.11
.07
.03
.08
Cognitive demands x
extraversion
-.07
.08
-.04
.08
-.06
.08
Emotional demands
x extraversion
.06
.07
.06
.07
.07
.08
Physical demands x
extraversion
-.07
.10
-.10
.09
-.28**
.10
Cognitive resources
x extraversion
.07
.11
-.25*
.10
-.28*
.11
Emotional resources
x extraversion
.10
.08
.11
.07
.07
.08
Physical resources x
extraversion
.02
.08
.06
.08
.08
.09
Cognitive demands x
emotional resources
x extraversion
-.05
.07
.08
.07
.07
.08
Cognitive demands x
physical resources x
extraversion
-.02
.09
-.12
.08
-.01
.09
Emotional demands
x cognitive resources
x extraversion
.05
.08
-.03
.08
-.07
.08
Emotional demands
x physical resources
x extraversion
.08
.08
.11
.07
.01
.08
Physical demands x
cognitive resources x
extraversion
.01
.08
-.04
.08
-.05
.08
.02
.07
-.04
Physical demands x
emotional resources
x extraversion
Note. *p < .05; **p < .01
B: unstandardized Beta
SE: standard error
–: no covariate in this regression analysis
.07
-.07
.07
43
Table 6
Regression model Hypothesis 3 match
Match
DV 1:
Cognitive
outcomes
DV 2:
Emotional
outcomes
DV 3:
Physical
outcomes
B
SE
B
SE
B
SE
5.93**
1.03
-.07
1.08
1.75
1.15
Having children
-
-
-.03
.15
-
-
Satisfaction with
salary
-
-
-.15
.08
-.28**
.09
Level of education
-
-
-
-
-.07
.05
Cognitive demands
.02
.14
.46**
.14
.29
.16
Emotional demands
.03
.12
.14
.12
-.13
.13
Physical demands
.09
.08
.31**
.08
.27**
.10
Cognitive resources
-.27
.16
-.07
.17
.17
.18
Emotional resources
-.05
.12
.03
.13
-.17
.14
Physical resources
.03
.08
-.14
.09
-.15
.09
Conscientiousness
-1.28**
.18
-.34
.18
-.30
.19
Cognitive demands x
cognitive resources
.01
.07
-.04
.07
-.12
.08
Emotional demands
x emotional
resources
-.03
.06
.03
.06
-.05
.07
Physical demands x
physical resources
-.05
.11
-.22*
.11
-.17
.12
Cognitive demands x
conscientiousness
-.02
.08
.03
.08
.03
.08
Emotional demands
x conscientiousness
.01
.09
.06
.09
.13
.09
Constant
44
Physical demands x
conscientiousness
-.07
.09
.00
.09
-.08
.09
Cognitive resources
x conscientiousness
.03
.08
-.05
.08
-.03
.09
Emotional resources
x conscientiousness
-.01
.09
-.00
.09
-.05
.09
Physical resources x
conscientiousness
-.01
.10
-.00
.10
.05
.11
Cognitive demands x
cognitive resources x
conscientiousness
.11
.06
-.00
.06
-.11
.07
Emotional demands
x emotional
resources x
conscientiousness
-.06
.08
-.02
.08
-.05
.08
Physical demands x
physical resources x
conscientiousness
.01
.10
-.05
.10
-.05
.10
Note. *p < .05; **p < .01
B: unstandardized Beta
SE: standard error
–: no covariate in this regression analysis
45
Table 7
Regression model Hypothesis 3 non-match
Non-Match
DV 1:
Cognitive
outcomes
DV 2:
Emotional
outcomes
DV 3:
Physical
outcomes
B
SE
B
SE
B
SE
.07
.08
.35
.33
.98*
.42
Having children
-
-
-.02
.15
-
-
Satisfaction with
salary
-
-
-.12
.08
-.23*
.09
Level of education
-
-
-
-
-.03
.05
Cognitive demands
-.01
.08
.28**
.09
.18
.09
Emotional demands
.05
.08
.10
.08
-.09
.08
Physical demands
.13
.09
.30**
.09
.36**
.10
Cognitive resources
-.18*
.09
-.03
.09
.04
.10
Emotional resources
-.02
.08
-.03
.09
-.17
.09
Physical resources
.04
.08
-.06
.09
-.01
.09
Conscientiousness
-.48**
.08
-.15
.08
-.19*
.08
Cognitive demands x
emotional resources
-.02
.08
-.01
.09
-.03
.09
Cognitive demands x
physical resources
.08
.09
.09
.10
.06
.10
Emotional demands
x cognitive resources
.07
.07
.01
.08
-.04
.08
Emotional demands
x physical resources
-.16
.08
-.13
.09
-.25**
.09
Physical demands x
cognitive resources
.17*
.08
.01
.08
.11
.09
Constant
46
Physical demands x
emotional resources
-.10
.07
-.05
.08
-.01
.08
Cognitive demands x
conscientiousness
-.03
.07
.02
.08
.04
.08
Emotional demands
x conscientiousness
.03
.09
.12
.09
.20*
.10
Physical demands x
conscientiousness
-.05
.10
-.02
.10
-.18
.10
Cognitive resources
x conscientiousness
.06
.08
-.06
.09
-.05
.09
Emotional resources
x conscientiousness
-.03
.09
.03
.10
-.08
.10
Physical resources x
conscientiousness
-.01
.12
.04
.12
.16
.13
Cognitive demands x
emotional resources
x conscientiousness
.03
.09
-.06
.09
.09
.10
Cognitive demands x
physical resources x
conscientiousness
.06
.10
-.02
.11
-.18
.11
Emotional demands
x cognitive resources
x conscientiousness
.04
.09
.03
.09
-.15
.10
Emotional demands
x physical resources
x conscientiousness
-.20
.11
-.06
.12
.04
.12
Physical demands x
cognitive resources x
conscientiousness
-.05
.08
.01
.08
.04
.08
.15
.09
-.00
Physical demands x
emotional resources
x conscientiousness
Note. *p < .05; **p < .01
B: unstandardized Beta
SE: standard error
–: no covariate in this regression analysis
.09
-.09
.10
47
Appendix C
- Graphs -
Graph 1
2-way interaction of physical demands and physical resources in the prediction of emotional
outcomes
1,4
Emotional outcomes
1,2
1
0,8
Low PR
High PR
0,6
0,4
0,2
0
Low PD
High PD
Note. PD: physical demands
PH: physical resources
48
Graph 2
2-way interaction of physical demands and cognitive resources in the prediction of cognitive
outcomes
0,4
0,3
Cognitive outcomes
0,2
0,1
0
-0,1
Low CR
Low PD
High PD
-0,2
-0,3
-0,4
-0,5
Note. PD: physical demands
CR: cognitive resources
49
High CR
Graph 3
2-way interaction of physical demands and emotional resources in the prediction of emotional
outcomes
1,2
Emotional outcomes
1
0,8
Low ER
0,6
High ER
0,4
0,2
0
Low PD
High PD
Note. PD: physical demands
ER: emotional resources
50
Graph 4
2-way interaction of emotional demands and physical resources in the prediction of physical
outcomes
1,4
Physical outcomes
1,2
1
0,8
Low PR
0,6
High PR
0,4
0,2
0
Low ED
High ED
Note. ED: emotional demands
PR: physical resources
51
Graph 5
2-way interaction of emotional demands and physical resources in the prediction of cognitive
outcomes
0,4
Cognitive outcomes
0,3
0,2
0,1
Low PR
0
Low ED
High ED
-0,1
-0,2
-0,3
-0,4
Note. ED: emotional demands
PR: physical resources
52
High PR