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ORIGINAL ARTICLE
The influence of psychosocial work characteristics on the needfor recovery from work: a prospective study among computerworkers
Ruben A. Kraaijeveld • Maaike A. Huysmans •
Marco J. M. Hoozemans • Allard J. Van der Beek •
Erwin M. Spekle
Received: 1 May 2012 / Accepted: 5 February 2013
� Springer-Verlag Berlin Heidelberg 2013
Abstract
Purpose To investigate the influence of high job
demands, low job control, and high social support on need
for recovery (NFR) among computer workers.
Methods Data was obtained from a longitudinal cohort
study, including 5 consecutive measurements, with an
in-between period of 6 months. General estimating equa-
tions analyses were performed to assess the risk for high NFR
6 months later. Odds ratios (ORs) for high NFR were cal-
culated for high job demands, low job control and low social
support, separately. Likewise, ORs were calculated for
combinations of job demands and job control, as well as for
combinations of job demands, job control and social support.
Results High job demands resulted in an increased risk
for high NFR 6 months later, particularly in older workers.
Low social support showed also an increased risk for future
high NFR, but this was not the case for low job control.
Furthermore, a combination of high job demands and low
job control, as well as a combination of high job demands,
low job control and low social support demonstrated an
increased risk for future high NFR where older workers
showed higher risks.
Conclusion This study demonstrated that adverse psy-
chosocial work characteristics predicted future NFR among
computer workers.
Keywords Need for recovery � Psychosocial work
characteristics � Computer work �Job demand-control-support model
Introduction
Throughout the years, multiple studies have demonstrated
that psychosocial work characteristics can play an impor-
tant factor in the development of work-related health
problems and impaired psychological well-being (Choi
et al. 2011; Kuper and Marmot 2003; Netterstrom et al.
2006; van den Heuvel et al. 2005). In most studies, psy-
chosocial work characteristics have been described in
terms of job demands, job control or decision latitude, and
social support. These terms are derived from the job
demand-control-support (JDCS) model (Johnson and Hall
1988; Johnson et al. 1989), which is an extension of the
earlier postulated job demand-control (JDC) model by
Karasek (1979). According to the JDCS model, jobs with
high demands, low control and low social support are the
most harmful for workers’ health (Johnson and Hall 1988).
These jobs have shown to result in an increased risk of
several health problems, such as cardiovascular diseases
(Netterstrom et al. 2006), depression (Sanne et al. 2005),
low back and neck pain (Macfarlane et al. 2009), neck and
upper limb symptoms (Bongers et al. 2006) and psycho-
logical distress (Choi et al. 2011).
R. A. Kraaijeveld � M. A. Huysmans (&) � A. J. Van der Beek
Department of Public and Occupational Health, EMGO?
Institute for Health and Care Research, VU University Medical
Center, PO Box 7057, 1007, MB, Amsterdam, The Netherlands
e-mail: [email protected]
M. A. Huysmans � M. J. M. Hoozemans �A. J. Van der Beek � E. M. Spekle
Body@Work, Research Center on Physical Activity, Work and
Health, Amsterdam, The Netherlands
M. J. M. Hoozemans � E. M. Spekle
Research Institute MOVE, Faculty of Human Movement
Sciences, VU University Amsterdam, Amsterdam, The
Netherlands
E. M. Spekle
Arbo Unie OHS, Utrecht, The Netherlands
123
Int Arch Occup Environ Health
DOI 10.1007/s00420-013-0852-2
It has been hypothesized that work-related health
problems are preceded by a higher need for recovery
(NFR), which can be seen as an intermediate variable
between psychosocial work characteristics and work-rela-
ted health problems (Sluiter et al. 2003). The concept of
NFR has been deduced from the effort-recuperation model
by Meijman and Mulder (1998) and refers to the extent of
recuperating from work-induced effort. This need for
recovery can be observed particularly during the last hours
of work and immediately after work. It is characterised by
temporary feelings of overload, irritability, social with-
drawal, lack of energy and reduced performance (van
Veldhoven and Broersen 2003).
Different studies have indeed shown that workers with
high NFR are at risk of adverse health effects. Sluiter et al.
(2003) concluded that NFR has a strong prognostic value
regarding subjective health complaints in different occu-
pational groups. A high NFR was also found to be a pre-
dictor for cardiovascular disease in a working population
(van Amelsvoort et al. 2003). Furthermore, Spekle et al.
(2012) found that, of several risk factors, NFR was the
strongest predictor for neck and upper limb symptoms in a
population of computer workers. Finally, in a study by De
Croon et al. (2003), NFR predicted future sickness absence
in truck drivers. Aforementioned studies showed that NFR
can be seen as a precursor of a variety of health problems.
Therefore, monitoring NFR might be useful to early
identify those at risk of work-related health problems.
Only few studies have addressed the relation between
adverse psychosocial work characteristics and NFR. Cross-
sectional studies showed indeed that high job demands, low
control and low social support were associated with high
NFR (Kiss et al. 2008; Sluiter et al. 2001; van der Hulst
et al. 2006). De Raeve et al. (2007) concluded in a pro-
spective study that an increase in job demands, as well as a
decrease in decision latitude, predicted a subsequent
increase in NFR. Another prospective study by Sluiter et al.
(2003) also demonstrated that high job demands predicted
high NFR. However, both of these prospective studies did
not address the influence of combinations of job demands,
job control and social support on future NFR.
Since NFR is a precursor of different work-related
health problems, and little is known about the influence of
combinations of adverse psychosocial work characteristics
on this precursor, more longitudinal research is needed.
Therefore, the aim of the present study was to investigate
the influence of adverse psychosocial work characteristics,
in terms of job demands, job control and social support, on
future NFR. Three main research questions will be
addressed. Firstly, do high job demands, low job control
and low social support separately predict high NFR? Sec-
ondly, does a combination of high job demands and low job
control predict high NFR? Thirdly, does a combination of
high job demands, low job control and low social support
predict high NFR?
Methods
Study design & participants
For this study, data were obtained from a longitudinal cohort
study, with a 24-months follow-up, which was set-up to
investigate the predictive validity of a questionnaire with
respect to neck and upper limb symptoms in computer
workers (Spekle et al. 2012). From 2004 until 2006, com-
puter workers of a Dutch occupational health service were
contacted per e-mail 5 times consecutively, with an
in-between period of 6 months, for filling out an internet-
based questionnaire. The population consisted of office staff
(45 %), occupational health physicians (20 %), health care
professionals & consultants (25 %) and managers (10 %),
who all used a computer for at least 2 h a day. The educa-
tional level of this population was primarily intermediate to
higher vocational or university education. The study design,
protocols, procedures and informed consent form of the
study were approved by the Ethics Committee of the Faculty
of Human Movements Sciences of the VU University
Amsterdam, and all participants electronically provided
informed consent before filling out the questionnaire.
Assessment of psychosocial work characteristics
and NFR
The internet-based questionnaire primarily concerned
exposure to risk factors for neck, shoulder and arm
symptoms (Spekle et al. 2009). For developing this ques-
tionnaire, the JDCS model was used as a theoretical
framework and questions were constructed or based on a
literature review on risk factors for neck and upper limb
symptoms. Furthermore, a substantial part of the questions
on psychosocial work characteristics was derived from the
Dutch Musculoskeletal Questionnaire (Hildebrandt et al.
2001) with response categories limited to ‘yes’ or ‘no’,
instead of the usually used Job Content Questionnaire of
Karasek (1979) which uses a four-point Likert scale. The
psychometric properties of the questionnaire used in the
present study were previously tested and results indicated
an acceptable reliability, concurrent validity and homoge-
neity (Spekle et al. 2009).
Variables of interest were obtained from the psychoso-
cial work characteristics scales of this questionnaire. The
scales ‘recovery time’, ‘work pace and load’, ‘decision
latitude’ and ‘work relations’ were used to asses NFR, job
demands, job control and social support, respectively
(https://www.rsiquickscan.com/research/questionnaire.pdf).
Int Arch Occup Environ Health
123
The ‘recovery time’ scale consisted of 6 items such as ‘do you
feel mentally exhausted by your work?’ and ‘do you feel at the
end of your tether?’ Responses (‘yes’ or ‘no’) to items were
summed up to a total score of a maximum of 6, where a higher
score meant more recovery is needed. Although this scale has
not been widely used for assessing NFR, items represent
fatigue effects of work-induced efforts. In addition, items of
this scale are similar to the items of the exhaustion scale of the
Maslach Burnout Inventory-General Survey (MBI-GS)
(Schaufeli et al. 1996) and the ‘need for recovery scale’ from
the Dutch Questionnaire on the Experience and Evaluation of
Work [(Dutch abbreviation: VBBA (van Veldhoven and
Broersen 2003))]. In previous studies, our NFR scale was
found to be internally consistent, reliable and showed pre-
dictive validity with respect to arm, shoulder and neck
symptoms (Spekle et al. 2009, 2012).
The ‘work pace and load’ scale consisted of 8 items with
questions, such as ‘do you regularly work under time
pressure?’ and ‘is your work often too tiring for you?’ The
‘decision latitude’ scale consisted of 9 items with ques-
tions, such as ‘can you choose when you take breaks?’ and
‘do you decide yourself when you carry out a task?’ Fur-
thermore, ‘work relations’ is a 7-item scale, with questions,
such as ‘do you find the general atmosphere at work good?’
and ‘does your direct supervisor support you enough in
your work?’ Responses (‘yes’ or ‘no’) to the items were
summed up to generate a total score for ‘work pace and
load’, ‘decision latitude’ and ‘work relations’, ranging
from 0 to 8, 9 and 7, respectively. All items were asked or
recoded in such a way that a higher score meant an unfa-
vourable psychosocial work characteristic. In addition, the
questionnaire contained also questions about gender, age,
prevalence of neck and upper limb symptoms, working
hours, work posture and movements, work tasks, work
environment factors, furniture, computer work station
attributes, and eyesight.
Statistical analyses
To investigate the influence of adverse psychosocial work
characteristics on future NFR, generalized estimating
equations (GEE) analyses were performed. With these
analyses, the relation between longitudinally measured
variables can be estimated using all longitudinal data
simultaneously while adjusting for within-person correla-
tions caused by repeated measurements on each subject
(Twisk et al. 2005). In addition, data of all five measure-
ments are used for these analyses. This means that data of
the present study yielded 4 times the relation between
psychosocial work characteristics and NFR (Table 1).
Scale scores of the questionnaire were inverted into
binominal variables with scores above the 67th percentile
of the population as cut-off point for high NFR, high job
demands, low job control and low social support, as well as
for the other continuous risk variables, which were treated
as possible confounders. This meant for NFR that a par-
ticipant had to agree on at least 2 items of this scale to be
defined as having a ‘high NFR’. All other cut-off values
can be found in Table 2. For the GEE analyses, a time lag
of 6 months was used, so that the psychosocial work
characteristics and ‘baseline’ NFR were assessed 6 months
prior to the outcome NFR. To prevent reversed causation,
participants with a high NFR at ‘‘baseline’’ for each of the
4 relations between psychosocial work characteristics and
NFR were excluded for that particular relation (Table 1).
Participants excluded for one of the time cohorts could be
part of the other time cohorts, as long as their NFR for that
particular ‘‘baseline’’ was low (NFR was 0 or 1).
Firstly, crude odds ratios (ORs) for the risk of high NFR
were calculated for high job demands, low job control and
low social support, separately. Secondly, crude ORs were
calculated for combinations of job demands and job control,
with the combination of low job demands and high job
control taken as reference. Thirdly, crude ORs were cal-
culated for combinations of job demands, job control and
social support, with the combination of low job demands,
high job control and high social support as reference.
Fourthly, tests for effect modification by gender and age for
all analyses were carried out, as well as statistical tests for
interaction effects of aforementioned combinations. A
binominal variable of age, with the median score as cut-off
point, appeared to be an effect modifier for the influence of
high job demands and aforementioned combinations on
NFR. Analyses for job demands and aforementioned com-
binations were performed again after stratification for age;
resulting in ORs for younger (age B 43 years) and older
workers (age [ 43 years). Finally, all ORs were adjusted
for confounding variables by multiple GEE analyses.
Potential confounding variables were included if those
variables modified the regression coefficients of the vari-
ables and combinations of interest more than 10 %. In all
aforementioned analyses, there was a correction for time of
measurement. Analyses were performed using SPSS 17.0.
Results
The time line of measurements and sample sizes are pre-
sented in Table 1. After each measurement, workers could
enter or withdraw from the study. At the first measurement,
2,039 out of 3,383 workers (response rate = 60 %) filled
out the questionnaire, at the second 1,478 out of 3,019
(response rate = 49 %), at the third 1,259 out of 2,817
(response rate = 45 %), at the fourth 1,189 out of 2,669
(response rate = 45 %) and at the fifth 1,042 out of 2,485
(response rate = 42 %). Only data of two or more
Int Arch Occup Environ Health
123
consecutive measurements of one subject were used, and
this resulted in a total population of 1,531 workers (34 %
males, mean age (SD) = 43 (9) years, 63.1 % working
more than 30 h per week, 72 % working more than 4 h per
day with a computer). After excluding workers with high
NFR at ‘baseline’, analyses were performed on data of at
least 1,215 workers.
The influence of job demands, job control and social
support on NFR, separately, is presented in Table 2. The
influence of job demands is presented for two age groups,
because age appeared to be an effect modifier for the
influence of job demands, which was not the case for job
control and social support. In both age groups, high job
demands resulted in a significantly higher risk for high
NFR 6 months later, where older workers showed the
highest risks. The adjusted OR for the group of 43 years
and younger was 1.7 (95 % CI: 1.2–2.3), and the adjusted
OR for the group of 44 years and older was 2.9 (95 % CI:
2.1–3.9). In both age groups, low social support demon-
strated significantly higher risks for future high NFR, as
well. The adjusted OR for low social support was 1.9
(95 % CI: 1.5–2.3). Low job control also showed higher
risks for future high NFR in the total population, but this
was not statistically significant after adjusting for con-
founding variables.
The influence of combinations of job demands, job
control and social support is presented for the younger
workers in Table 3 and for the older workers in Table 4.
Firstly, in both age groups, the combination of high job
demands and low job control resulted in significantly
higher risks for future high NFR, where older workers
showed the highest risks. The adjusted OR for the group of
43 years and younger was 1.6 (95 % CI: 1.0–1.7), and the
adjusted OR for the group of 44 years and older was 4.8
(95 % CI: 3.0–7.8).
Secondly, the combination of high job demands, low job
control and low social support demonstrated significantly
higher risks for future high NFR as well, particularly in
older workers. The adjusted OR for the group of 43 years
and younger was 2.2 (95 % CI: 1.0–5.0), and the adjusted
OR for the group of 44 years and older was 7.7 (3.8–15.5).
Noteworthy is that in both age groups there were no
statistically significant interactions observed, neither for
job demands with job control, nor for job demands with job
control and social support (results not shown).
Discussion
The present study investigated, in a population of computer
workers, the influence of adverse psychosocial work
characteristics, in terms of job demands, job control and
social support, on NFR 6 months later. Results demon-
strated adverse effects of high job demands and low social
support on future NFR but did not show an effect of low
job control on future NFR. Furthermore, a combination of
Table 1 Time line of measurements (T1-T5) and sample sizes (N)
T=1 (N=2039) T=2 (N=1478) T=3 (N=1259) T=4 (N=1189) T=5 (N=1042)
0 months 6 months 12 months 18 months 24 months
Job demands
Job control
Social support
Job demands
Job control
Social support
Job demands
Job control
Social support
Job demands
Job control
Social support
Job demands
Job control
Social support
NFR NFR NFR NFR NFR
(N=1225)a
N=823b(N=1019)a
N=698b(N=803)a
N=524b(N=827)a
N=533b
The influence of job demands, job control and social support on the need for recovery (NFR) 6 months latera Indicates the number of participants for whom data was available for two consecutive measurementsb The actual number of participants in the analyses, that is, those for whom data was available for two consecutive measurements and had a low
NFR at ‘‘baseline’’ (NFR \ 2)
Int Arch Occup Environ Health
123
high job demands and low job control as well as a com-
bination of high job demands, low job control and low
social support resulted in an increased risk for high NFR
6 months later. Age modified the adverse effects of high
job demands and aforementioned combinations on NFR;
computer workers of 44 years and older showed higher
risks for high NFR than younger workers. Contrarily,
comprehensive reviews on the JDCS model in relation to
psychosocial well-being did not address any effect modi-
fication by age, in case of adverse psychosocial work
characteristics (Hausser et al. 2010; van der Doef and Maes
1999).
The adverse effects of high job demands and low social
support separately and combined are in line with earlier
studies regarding the influence of psychosocial work
characteristics on mental health outcomes (Choi et al.
2011; de Raeve et al. 2007; Netterstrom et al. 2006; Sluiter
et al. 2003). The most striking finding of this study was that
there was hardly any influence of job control on future
NFR. The lack of influence of job control on NFR in this
study contradicts results of earlier studies on psychosocial
work characteristics and mental health (Dalgard et al.
2009; de Raeve et al. 2007; Sanne et al. 2005). This might
be due to the scale that was used to asses job control; it
contained solely items concerning decision authority and
no items about skill discretion, which were applied in
scales in earlier studies (Dalgard et al. 2009; de Raeve et al.
2007; Sanne et al. 2005). Moreover, it should be noted that
selection bias might have contributed to these study results
as well, as will be explained later on.
Table 2 Odds ratios (ORs) of GEE analyses for Need for Recovery (NFR)
N and observations (O) Risk
level
Observations
(% of O)
NFR 6 months later (high NFR C 2)
OR crude
(95 % CI)
OR adjusted
(95 % CI)
Job demands (JD): 0–8 N = 1250, O = 2592 Age B 43 years Low: 0–4 969 (37 %) 1 1
High: 5–8 322 (12 %) 1.7 (1.2–2.3)* 1.7 (1.2–2.3)a*
Age [ 43 years Low: 0–4 945 (36 %) 1 1
High: 5–8 356 (14 %) 2.9 (2.1–3.9)* 2.9 (2.1–3.9)a*
Job Control (JC): 0–9 N = 1217, O = 2396 High: 0–2 1716 (72 %) 1 1
Low: 3–9 680 (28 %) 1.3 (1.0–1.6)** 1.1 (0.9–1.5)b
Social support (SS): 0–7 N = 1250, O = 2592 High: 0–2 1943 (75 %) 1 1
Low: 3–7 649 (25 %) 1.9 (1.5–2.3)* 1.9 (1.5–2.3)a*
* Significant at p \ .01, ** significant at p \ .05a No confounders were foundb Adjusted for social support, work tasks and neck and upper limb symptoms
Table 3 Odds ratios (ORs) of GEE analyses for Need for Recovery (NFR) of younger workers (age B 43 years)
N and observations (O) Job type Observations (% of O) NFR 6 months later (high NFR C 2)
OR crude (95 % CI) OR adjusted (95 % CI)
Job demands (JD) &
Job control (JC)
N = 614, O = 1199
Low JD\high JC 675 (56 %) 1 1
Low JD\low JC 224 (19 %) 1.0 (0.6–1.5) 0.9 (0.6–1.3)a
High JD\high JC 208 (17 %) 1.7 (1.1–2.4)* 1.6 (1.0–2.4)a**
High JD\low JC 92 (8 %) 1.9 (1.2–3.1)* 1.6 (1.1–2.4)a**
Job demands (JD) &
Job control (JC) &
Social Support (SS) N = 614, O = 1199
Low JD\high JC\high SS 521 (43 %) 1 1
Low JD\high JC\low SS 154 (13 %) 1.7 (1.1–2.6)** 1.6 (1.0–2.5)a**
Low JD\low JC\high SS 166 (14 %) 0.8 (0.5–1.4) 0.7 (0.4–1.3)a
Low JD\low JC\low SS 58 (5 %) 2.1 (1.1–4.0)** 1.8 (1.0–3.4)a
High JD\high JC\high SS 158 (13 %) 1.6 (1.1–2.6)** 1.6 (1.0–2.5)a**
High JD\high JC\low SS 50 (4 %) 2.8 (1.5–5.3)* 2.8 (1.5–5.3)a*
High JD\low JC\high SS 64 (5 %) 2. 0 (1.1–3.7)** 1.7 (0.9–3.1)a
High JD\low JC\low SS 28 (2 %) 2.7 (1.3–5.7)* 2.2 (1.0–5.0)a**
* Significant at p \ .01, ** significant at p \ .05a Adjusted for neck and upper limb symptoms
Int Arch Occup Environ Health
123
Because there was no impact of low job control on
future NFR in this study, the influence of job control in
case of high job demands was further investigated.
According to the strain hypothesis of the JDCS model, jobs
with high demands and low control are the most harmful
for workers’ health (Johnson and Hall 1988). Furthermore,
the buffer hypothesis of this model states that high job
control can moderate the negative impact of high job
demands (Hausser et al. 2010; Johnson and Hall 1988).
Additional analyses of a group with high job demands in
combination with high and low job control demonstrated a
significantly increased risk for high NFR 6 months later in
case of low job control. However, there was no interaction
between high job demands and job control. Therefore,
results corroborated the strain hypothesis of the JDCS
model but did not confirm the buffer hypothesis. Hausser
et al. (2010) defined buffering explicitly as attenuation due
to an interaction effect.
Effect modification by age for the influence of adverse
psychosocial work characteristics on psychological well-
being is seldom reported. Nevertheless, a decline in the
work ability of the ageing worker could explain the higher
risks found in older workers in this study. Ilmarinen et al.
(1997) reported in a comprehensive follow-up study that
the work ability, measured by the work ability index,
declined significantly among workers, aged 45 years and
older, who continued working for a period of 11 years. In
addition, older workers seem to be more susceptible for
developing higher levels of NFR; different studies showed
that older workers (age [ 45 years) have a higher NFR
(Kiss et al. 2008; Mohren et al. 2010).
Noteworthy is that the results from the present study
seemed to be quite robust, since changing the cut-off value
for a high NFR to three or higher led to the same results,
that is, similar or slightly lower Odds Ratios for job
demands, job control and social support.
Strengths & limitations of the study
Strength of this study is that the time-varying nature of
both psychosocial work characteristics and psychological
well-being was taken into account. All study variables were
assessed consecutively 5 times over a period of 2 years,
which fortified results. Edwards (2008) argued that longi-
tudinal research should incorporate more time lags between
exposure and outcome to strengthen the ability to draw
causal inferences. For analyses, a time lag of 6 months was
used between exposure and onset of symptoms. Additional
analyses (results not shown) demonstrated that a time lag
of 6 months resulted in the strongest relations between the
psychosocial work characteristics and NFR as compared to
time lags of 12 or 18 months. Likewise, De Raeve et al.
(2007) argued that time lags between work characteristics
and mental health should not be longer than 1 year,
because of the time-varying nature of work characteristics.
With respect to the internal validity of the study results,
different types of potential bias are worth noting. Firstly,
selection bias may have played a role, although it is diffi-
cult to determine the impact of this type of bias, because
workers could enter, withdraw or re-enter at each time
point. However, to get some insight into selection bias, the
obtained study variables, from the questionnaire of the
participants who participated at T = 1 and T = 2, were
compared to those who participated at T = 1, but not at
T = 2. Indeed, there were some differences between those
two groups. The group of participants who did not fill out
Table 4 Odds ratios (ORs) of GEE analyses for need for recovery (NFR) of older workers (age [ 43 years)
N and observations (O) Job type Observations (% of O) NFR 6 months later (high NFR C 2)
OR crude (95 % CI) OR adjusted (95 % CI)
Job demands (JD) &
Job control (JC)
N = 602, O = 1196
Low JD\high JC 600 (50 %) 1 1
Low JD\low JC 272 (23 %) 1.4 (0.9–2.1) 1.3 (0.9–2.0)a
High JD\high JC 233 (19 %) 2.6 (1.8–4.0)* 2.6 (1.8–3.9)a*
High JD\low JC 91 (8 %) 5.3 (3.4–8.4)* 4.8 (3.0–7.8)a*
Job demands (JD) &
Job control (JC) &
Social Support (SS) N = 601, O = 1195
Low JD\high JC\high SS 458 (38 %) 1 1
Low JD\high JC\low SS 142 (12 %) 1.6 (1.0–2.7) 1.6 (1.0–2.8)a
Low JD\low JC\high SS 198 (17 %) 1.4 (0.9–2.3) 1.4 (0.8–2.2)a
Low JD\low JC\low SS 74 (6 %) 2.1 (1.1–3.9)** 2.0 (1.0–3.8)a**
High JD\high JC\high SS 180 (15 %) 2.3 (1.4–3.7)* 2.3 (1.4–3.7)a*
High JD\high JC\low SS 52 (4 %) 6.2 (3.3–11.4)* 5.8 (3.1–10.8)a*
High JD\low JC\high SS 55 (5 %) 4.8 (2.6–8.9)* 4.5 (2.3–8.5)a*
High JD\low JC\low SS 36 (3 %) 8.8 (4.5–17.4)* 7.7 (3.8–15.5)a*
* Significant at p \ .01, ** significant at p \ .05a Adjusted for neck and upper limb symptoms
Int Arch Occup Environ Health
123
the questionnaire at T = 2 (but might have entered the
study again at e.g. T = 4) had a significantly higher
prevalence of low job control, low social support and high
monotonous work. There were no age or gender differ-
ences. Taking into account the difference between both
groups for job control, selection bias could have changed
the influence of job control on NFR, since participants with
low job control at T = 1 withdrew themselves more often.
Secondly, self-report bias may have influenced the
results, because study variables were obtained from survey
data using self-report measures. However, a study by
Griffin et al. (2007) showed that there was no difference
between self-reported or observed job control in relation to
depression and anxiety symptoms. Moreover, a study by
Sluiter et al. (2001) showed that self-reported NFR, using
the ‘Need for recovery scale’ developed by (van Veldhoven
and Broersen 2003), was associated with objectively
assessed physiological measures of participants, such as
cortisol and adrenaline levels. Thus, NFR, as perceived by a
worker, can be a valid indicator of psychophysiological
recovery after work. Thirdly, feedback bias might have
played a role as well; this implies that earlier outcomes may
affect subsequent exposures. As explained by Eisen (1999),
the GEE method cannot control for this bias. In favour of
the present study was that feedback bias was minimized as
much as possible by excluding participants with high NFR
at ‘baseline’, and exposure and outcome variables were
assessed at different time points.
Practical implications
Results demonstrated that high job demands can be
harmful for worker’s psychological well-being, particularly
in older workers, and results also showed that high job
control did not attenuate the negative impact of high job
demands. However, evidence-based interventions to reduce
job demands at the workplace are scarce. Interventions that
are frequently used are courses aimed at improving time
management skills and handling stress in the workplace
(https://www.rsiquickscan.com/research/interventions.pdf).
Promising moderators, which might buffer the negative
impact of high job demands, are psychological detach-
ment and other recovery experiences, as introduced by
Sonnentag and Fritz (2007). Psychological detachment
means to disengage oneself mentally from work during off-
job time (Sonnentag and Fritz 2007). It has been argued
that the lack of recovery could have even more impact on
workers’ well-being than job strain itself (Lundberg 2005;
Sonnentag and Zijlstra 2006). A quasi-experimental study
by Hahn et al. (2011) already indicated that a training
program on recovery experiences resulted in a decrease of
perceived stress and state negative effect of participants.
However, prevention efforts should not be limited to
self-management. It is the organisation that creates the
stress, and, therefore, the prevention and management of
workplace stress should primarily consist of organisational
level interventions. In this regard, Michie (2002) gave
several useful examples of possible interventions strate-
gies, where the emphasis is on the organisation, rather than
the individual, such as giving employees the opportunity to
participate in the design of his/her own work situation,
adapt working conditions to people’s differing physical and
mental attitudes and limit or avoid closely controlled or
restricted work.
The present results apply to a source population of
computer workers of a Dutch Occupational Health Service,
with a relatively large variety of job titles. The majority of
these workers were primarily engaged in administrative
work, and all workers, including the health care profes-
sionals, had a substantial amount of computer work per day
(all of them worked at least 2 h per day with a computer
and 72 % even more than 4 h per day). Even though, we
realize that there are clear organisational differences
between the different occupations in this population, we
argue that this is typical for a group computer workers.
Therefore, we consider this population to be representative
of computer workers in general. However, it is recom-
mended in future research to further investigate the effects
of job demands, job control and social support in other
populations of computer workers, and then focus specifi-
cally on differences between younger and older workers.
Conclusion
This study demonstrated, in a population of computer
workers, that high job demands predicted high NFR
6 months later, and this relation was more pronounced in
older workers. Low social support predicted future high
NFR as well, but this was not the case for low job control.
Furthermore, a combination of high job demands and low
job control as well as a combination of high job demands,
low job control and low social support resulted in an
increased risk for future high NFR, where older workers
showed higher risks.
Conflict of interest The authors declare that they have no conflict
of interest.
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