Health and ill health in working women – balancing work and recovery

Health and ill health
in working women
– balancing work and recovery
Ulrica von Thiele Schwarz
©Ulrica von Thiele Schwarz, Stockholm 2008
Cover:
Ikebana arrangement: Boel Lindbergh
Photo: © Åke E:son Lindman
ISBN 978-91-7155-759-9
Printed in Sweden by US-AB, Stockholm, 2008
Distributor: Department of psychology
Abstract
Work conditions within the public health care sector are physically and
psychosocially demanding. This means that balancing work with recovery is
essential for employees in order to avoid ill health and stay healthy. This
thesis is based on four studies. Study I investigated the prevalence of upper
extremity disorders (UED) in female dental personnel. Results showed that
81% reported UED. Consequently, interventions aimed at reducing these
risks were called for. Study II investigated the health-related effects of two
work-place interventions, physical exercise (PE) and reduced working hours
(RWH). Health-improvements were more consistent in the PE group,
suggesting that PE may be an appropriate intervention to reduce health-risks.
However, there were no effects on recovery from work or fatigue, which
may result from other factors, such as overcommitment (OC), that prolong or
sustain stress-related activity. Study III showed that high OC was associated
with poorer next-day recovery and increased fatigue. Also, OC was a more
important predictor of lack of recovery and fatigue than were psychosocial
work characteristics. This highlights the importance of considering
perseverative cognitions in relation to recovery from work and fatigue, and
has implications for interventions targeting work-related ill health. Study IV
related lack of recovery and fatigue to cumulative biological risk, allostatic
load (AL), and to individual biomarkers. Women with a profile characterized
by fatigue, sleep difficulties and lack of short-term recovery had a 2.9
increased risk of AL. This was not shown in analyses of individual
biomarkers. In sum, this thesis shows that recovery from work is an
important factor in relation to women’s work-related health. Fatigue and
recovery should be considered interrelated but distinct concepts and recovery
should be assessed as an early risk factor for stress-related disease with early
risk being investigated using AL rather than individual biomarkers.
Keywords: Allostatic Load, Biological markers, Dentistry, Exercise,
Fatigue, Physical Activity, Public health care, Overcommitment, Reduced
working hours, Stress, Upper Extremity Disorder
Acknowledgements
I am so curious. I guess I never stopped asking those questions you hear
from a five year old: what is that? How does it work? How is this related to
that? WHY?? That’s why I was intrigued by doing research, because to me,
asking question (and sometimes, if you’re lucky, get a hint of an answer) is
what you do.
Of course, I have met and engaged with a lot of people who has helped
me during my PhD studies and to whom I am grateful. I will not pretend to
be able to thank you all, but will limit myself to thank only a few.
First, I would like to thank my supervisors Ulf Lundberg and Petra
Lindfors. Without Ulf’s support, I would not have started my doctorial
studies. His experience was also invaluable in the design of the project, and
in getting it funded, approved and started. He has been reassuring and
always responsive and helpful. He was also responsible for involving Petra
Lindfors in the project, first as a collaborator, then as a co-supervisor, and
for the final years, as head supervisor. Petra has been a tremendous support
and has also contributed to making the whole experience joyful. I have
greatly appreciated the easiness in our collaboration and how our discussions
has improvement my knowledge and widened my perspective.
I have also been lucky enough to met and engage with other researchers,
who have helped me move things along. One such opportunity was
collaborating with Göran Kenttä in two chapters concerning recovery among
athletes. Our discussions concerning the concept of recovery and similarities
and dissimilarities in recovery within different settings were, and are,
enlightening. Collaborating with Susanne Heiwe, with her deep knowledge
on physical activity has also been a very helpful and pleasant experience.
Finally, Dan Hasson, my colleague and friend with whom I never seem to be
finished discussing stress and intervention – your reassurance and constant
expression of belief in my ability as a researcher is not only highly flattering
but also heart-warming.
My thanks also extend to FAS, the Swedish Counsel for Working Life
and Social Research, who funded the project, and to FAS and the
Wallenberg foundation for additional financial support.
In a thesis on work and health, I am happy to say that I am one of those
who have an understanding and supportive employer. Thanks to the
managers for the financial, practical and emotional support I gained in my
effort to do research and thanks for spreading the results outside the
scientific community. Also, thanks to the nurses who without complaining
got up early in the morning, travelled far, followed complicated protocols
and provided a safe environment for the participants. I appreciated sharing
the burdens of logistics with you, as well as the joy of collaboration with the
organisations and meeting with the participants.
On the subject of work and health – my appreciations also go to the
organisations who wanted to improve the situation for employees, with their
health and well-being in mind: the Public Dental Health Service in
Stockholm and Hägersten and Skärholmen District Councils. With more
employers of your kind, the healthiness of work would be in the centre more
often! And of course, thanks to the employees who volunteered to participate
in the research project. Without you, this truly wouldn’t have happened.
Most of all, I am thankful to all of you outside the scientific community,
who have asked me ―so, what are you doing research about‖ and expected a
sensible, understandable answer in maximum three (short) sentences. I am
also thankful for questions like ―but what is it good for?‖ To the extent that I
have managed to be clear on the practical implications of my findings, I owe
it to you.
My final note will be directed towards my family. Thanks to my husband
Niklas for being supportive and encouraging, and to my mum, Majvy, for
giving me extra time to spend on scientific work. And finally, thanks to our
daughter Thea, who makes every thought about research and dissertation
disappear by inviting me to play and cuddle instead.
List of publications
The present thesis is based on the following studies, which are referred to in
the text by their Roman numerals:
Study I
Lindfors, P., von Thiele, U., & Lundberg, U. (2006). Work characteristics
and upper extremity disorders in female dental health workers. Journal of
Occupational Health, 48, 192-197.
Study II
von Thiele Schwarz, U., Lindfors, P., & Lundberg, U. (2008). Healthrelated effects of worksite interventions involving physical exercise and
reduced workhours. Scandinavian Journal of Work, Environment & Health,
34, 179-188.
Study III
von Thiele Schwarz, U. (2008). Overcommitment as related to poor nextday recovery and work-related fatigue among women. Submitted manuscript
Study IV
von Thiele, U., Lindfors, P., & Lundberg, U. (2006). Self-rated recovery
from work stress and allostatic load in women. Journal of Psychosomatic
Research, 61, 237-242.
Studies I, II and IV are reprinted with kind permission from the
publishers.
Abbreviations
ACSM
AL
ANCOVA
ANOVA
CI
DHEAS
ERI
HbA1c
HDL
HPA
LDL
MANCOVA
MANOVA
MSD
OC
OR
PA
PE
PSNS
RWH
SAM
SNS
UED
WHI
WHP
WHR
WRMSD
American College of Sports Medicine
Allostatic Load
ANalysis Of COVAriance
ANalysis Of VAriance
Confidence Interval (usually 95% CI)
DeHydroEpiAndrosterone Sulfate
Effort-Reward Imbalance
Glycated haemoglobin
High-Density Lipoprotein
Hypothalamic-Pituitary-Adrenal axis
Low-Density Lipoprotein
Multiple ANalysis Of COVariance
Multiple ANalysis Of VAriance
MusculoSkeletal Disorder
Overcommitment
Odds Ratio
Physical Activity
Physical Exercise
ParaSympathetic Nervous System
Reduced Working Hours
Sympatho-Adreno-Medullary system
Sympathetic Nervous System
Upper Extremity Disorder
Work-Home Interference
Workplace Health Promotion
Waist-Hip Ratio
Work-Related MusculoSkeletal Disorder
Contents
Introduction ................................................................................................ 11
Theoretical and empirical framework .................................................... 15
Work-related health problems in public health care and dentistry ................ 16
Upper Extremity Disorder ................................................................................. 17
Stress-related disorders.................................................................................... 18
Disease, ill health and health ................................................................................ 18
Stress ........................................................................................................................ 19
The physiology of stress ................................................................................... 20
Allostatic load ..................................................................................................... 21
Recovery ................................................................................................................... 22
Definitions of recovery ...................................................................................... 23
Time frame (timing) of recovery ..................................................................... 24
Fatigue and recovery ......................................................................................... 25
Recovery from work stress ............................................................................... 27
Perseverative cognitions ........................................................................................ 27
Interventions in the workplace ............................................................................. 29
Physical activity interventions ......................................................................... 31
Reduced working hours..................................................................................... 34
Aim of the thesis ..................................................................................................... 36
Method ......................................................................................................... 37
Design of the studies .............................................................................................. 37
Measuring health and ill health ............................................................................. 39
Physiological parameters .................................................................................. 40
Self-ratings.......................................................................................................... 45
Work-related measures .......................................................................................... 48
Physical work characteristics ........................................................................... 48
Psychosocial work characteristics ................................................................... 48
Work-home interference ................................................................................... 49
Summary of Empirical Studies ............................................................... 50
Participants ............................................................................................................... 50
Procedure .................................................................................................................. 51
Study I....................................................................................................................... 51
Study II ..................................................................................................................... 53
Study III.................................................................................................................... 55
Study IV .................................................................................................................... 56
Discussion ................................................................................................... 59
Interpretation of findings ....................................................................................... 59
Promoting health and preventing ill health ................................................... 60
Health and ill health as related to recovery from work ............................... 64
Conceptual issues .................................................................................................... 68
The concept of recovery ................................................................................... 68
Methodological considerations .............................................................................. 75
Intervention Research ....................................................................................... 75
Measurement issues .......................................................................................... 77
Person-oriented versus variable-oriented approach .................................... 80
Operationalization of AL .................................................................................... 81
Statistical considerations .................................................................................. 82
Generalizability ................................................................................................... 83
Ethical considerations ............................................................................................. 83
Practical implications .............................................................................................. 85
Consequences of UED and reasons for action .............................................. 85
Possible interventions — PE and RWH ........................................................... 86
Withdraw from work – what can be done?.................................................... 89
Negative effects of fatigue and lack of recovery .......................................... 89
Conclusions............................................................................................................... 90
Sammanfattning på svenska .................................................................. 91
References .................................................................................................. 94
Introduction
The effects of work on health and ill health have been investigated
extensively. Particularly, adverse effects of poor work conditions have been
thoroughly studied. Health problems, symptoms and diseases associated with
poor work conditions include a variety of symptoms and diseases such as
musculoskeletal pain, cardiovascular diseases, depression and poor health
behaviours such as alcohol consumption, smoking and using drugs (Bongers,
Dewinter, Kompier, & Hildebrandt, 1993; Bongers, Kremer, & ter Laak,
2002; Johnson & Hall, 1988; Niedhammer, Goldberg, Leclerc, David, et al.,
1998; Niedhammer, Goldberg, Leclerc, Bugel, & David, 1998; Reed, Storr,
& Anthony, 2006; Theorell et al., 1998). In recent years, poor psychosocial
work conditions such as high work pace, monotonous work tasks and high
emotional demands are reported more frequently than are poor physical
work conditions such as heavy lifting, strenuous work positions and noxious
exposure (The Work Environment 2007, 2008). This can be partly attributed
to changes in the labour market, where physically hazardous jobs have
become less common, either having been moved to other parts of the world
or changing dramatically due to technical achievements, concurrently with
an increased internationalization and competition and utilization of
information and communication technology that has changed the
psychosocial work environment (Kompier, 2006). Besides a decrease in the
part of the work force that is subjected to a demanding physical work
environment, there have also been improvements for those still exposed to
heavy physical workload, uncomfortable working positions, physical hazards
and challenges to the five senses (odour, noise, poor air quality, etc.). These
improvements include legislation regarding exposure to hazardous factors,
ergonomic developments and technical achievements.
For the psychosocial work environment, the improvements are less
obvious. This is not due to a lack of knowledge about which psychosocial
factors may be harmful for people’s health. We currently know a great deal
about what conditions increase the risk for health impairments. In a recent
review of the literature, it is concluded that there is a consensus regarding
psychosocial factors that may affect health, including organizational culture,
roles, career opportunities, decision latitude, social relationships, work-home
interference, work tasks, work demands or work pace and scheduling of
work (Cox, Griffiths, & Rial-González, 2000). The current understanding
builds on decades of research. An influential model on how psychosocial
11
work characteristics relate to stress and health was presented as early as in
the late 70s: the Demand/Control/Social Support model. The model states
that high psychological demands in combination with low decision latitude
(influence at work), – called job strain, – is the worst situation, particularly if
one’s social support is low, as well (Karasek, 1979; Karasek & Theorell,
1990). The Demand/Control/Social Support model was later complemented
with a second model, the Effort-Reward Imbalance model (ERI). In the ERI
model, balance is also in focus, but this time in terms of balance between
effort spent at work (physical, mentally, socially and motivationally) and the
rewards (monetary, esteem and status) gained (Siegrist, 1996). In the 90s, a
third model relating psychosocial stressors to a cumulative physiological risk
over one’s life- course, the Allostatic Load model, was presented (McEwen,
2000; McEwen & Seeman, 1999). Although differentiation between various
psychosocial stressors is not part of the model, it shows how protective and
adaptive short-term responses to stressors may turn into the harmful
consequences of prolonged activation. From this research follows a renewed
scientific interest in recovery from work, and a third perspective suggesting
that along with balance between demands and control and effort and reward,
a balance between activation and recovery is also needed.
In contrast to the focus on the potential harmful effects of work,
consistent findings show that paid employment has no adverse effects on
health among women (Repetti, Matthews, & Waldron, 1989). On the
contrary, some findings suggest that paid employment is related to improved
health, including less depression, lower mortality and better subjective health
(Klumb & Lampert, 2004). Paid employment has been related to better
social support, increased extrinsic gratification including income, intrinsic
gratification, creativity, and increased control (Barnett & Hyde, 2001; Bird
& Ross, 1993; Hibbard & Pope, 1992; Mirowsky & Ross, 2007; Repetti et
al., 1989; Yoshii & Yamazaki, 1999). These findings remain in longitudinal
studies even after controlling for the fact that there is a reverse relationship
as well: healthy women participate in the labour force to a greater extent
than unhealthy women do (Repetti et al., 1989). On the whole, work is not
bad for people, but rather the opposite: although having multiple roles may
be stressful and decrease autonomy, the negative consequences of multiple
roles seem to be overridden by the positive consequences of occupying
several roles when this provides an opportunity to take part in paid work
(Barnett & Baruch, 1985; Mirowsky & Ross, 2007; Repetti et al., 1989).
This may be due to a buffering effect, whereby stressors from one area are
counteracted, or buffered, by successes and satisfaction from another, but it
may also be related to the quality of the work such as high job reward and
job satisfaction and low levels of harassment (Barnett & Hyde, 2001). These
positive consequences of paid work may be further enhanced when the
workplace is used as an arena for health promotion. There is no other setting
where adults spend so much of their waking hours, making employees easier
12
to reach with health initiatives and making it convenient for them to attend a
health program (W. S. Cohen, 1985).
So, work is generally good for health, but under some conditions may be
related to ill health. One way to understand this is to look at work from a
whole life perspective. In this thesis, the negative effects of work, and work
conditions, on health are understood in terms of stress theory and the
allostatic load model. There is an upper limit to the benefits of multiple
roles, and being exposed to poor work conditions may evoke stress
responses that, in the long term, may lead to ill health (Barnett & Hyde,
2001; Rusli, Edimansyah, & Naing, 2008). However, responding
physiologically to overload and demands in the environment is not
pathological in itself but rather the opposite: it is a beneficial mobilization
that is necessary for adapting to changes in the environment (McEwen,
2000). This holds true as long as the stress response is allowed to be
reversed, as it is during recovery (McEwen, 2008). Therefore, work
conditions (e.g. stressors) and the reactions to stressors (e.g. symptoms) need
to be considered in relation to what happens after the removal of the stressor,
such as after the workday has ended. Effects of both physical and
psychosocial work conditions are assumed to be modified by the time it
takes, and the ability, to recover from work (Frankenhaeuser, Lundberg,
Fredrikson, & Melin, 1989; Sluiter, de Croon, Meijman, & Frings-Dresen,
2003; Sluiter, Frings-Dresen, Meijman, & van der Beek, 2000; Sluiter, van
der Beek, & Frings-Dresen, 1999). Being fatigued after a demanding
workday, or after any other activity that requires effort expenditure, may be
regarded as a natural and healthy response as long as the reaction can be
reversed. This, in turn, is dependent on many factors associated with the
individual’s whole life situation: not only the level of stressors and demands
at work, but also the individual’s reaction to that situation, as well as the
situation outside work – other responsibilities and resources, including time
available for recovery and mental activities that may interfere with the
recovery process. This extends the focus from the job situation alone to
processes and activities that take place outside work as well. This is
particularly relevant for women, whom compared to men often have a
greater total workload and the main responsibility for the household, despite
a labour participation rate similar to men’s (80% compared to 86% in
Sweden) (Gjerdingen, McGovern, Bekker, Lundberg, & Willemsen, 2000;
Statistics Sweden, 2005). Although having multiple roles in itself is
rewarding, juggling work with other responsibilities and needs, particularly
the need to recover from work, may be challenging.
Drawing on the theoretical perspective of stress theory, this thesis focuses
on various aspects of health and ill health among women with emotionally
and physically demanding jobs employed by the public health care sector.
The general aim was to investigate health and ill health among working
women, with specific focus on how efforts associated with work need to be
13
balanced with recovery and the time off work in order to prevent ill health
and promote health. The theoretical and empirical framework is presented in
the next section, starting with a description of public health care in general
and dentistry in particular and followed by an introduction to the workrelated health problems associated with public health and dentistry.
Afterward, stress theory is introduced, including a description of the concept
of recovery, followed by an introduction to interventions in the workplace,
particularly physical activity interventions and reduced working hours. The
section ends with the aim of the thesis and specific research questions.
14
Theoretical and empirical framework
In Sweden, the labour market is gender segregated. Women form the great
majority in the municipal service, including elderly care, child care and
health care. Jobs in this sector are often physically demanding, involving
heavy lifting and working in strenuous positions (Bäckman, 2001; The Work
Environment 2007, 2008). They are also emotionally demanding, involving
care for other people. The psychosocial work environment is poorer in
comparison to other sectors and is characterized by great time pressure and
low possibility to influence one’s work pace and when tasks should be done.
While the proportion of employees reporting poor psychosocial work
conditions has remained largely unchanged in other sectors, there has been
an increase in employees within the public sector reporting high
psychological demands and low autonomy (O. Lundberg & Gonäs, 1998).
Jobs in the municipal sector also often carry low status, offering limited
career opportunities and lower salaries. These are all factors that, according
to the Demand-Control model and the ERI model, increase the risk for ill
health.
In comparison with other human-service workers, dental health workers
often report a poorer work environment (Bejerot, 1998; Finsen, Christensen,
& Bakke, 1998). Dentistry has been described as the most stressful of the
health care professions (R. Freeman, Main, & Burke, 1995). Common
stressors are problems connected to the compliance, pain and anxiety of the
patient; interpersonal relations; the physical strain of the work; economic
pressures; third-party constraints; and the strain of perfectionism and seeking
ideal results (O'Shea, Corah, & Ayer, 1984). In Sweden, questionnaires
concerning the work environment have been administered in the Swedish
Public Dental Health Service (PDHS) since the 40s, revealing dissatisfaction
with high demands and low rewards, piece-work wages, detailed control
systems and lack of self determination (Bejerot, 1998). Research has
indicated that the work environment differs depending on occupation, with
dentists and dental hygienists having the highest demands (Murtomaa,
Haavio-Mannila, & Kandolin, 1990; Rundcrantz, Johnsson, Roxendal, &
Moritz, 1991); see also (Bejerot, 1998). However, since dentists and dental
hygienists, but not dental nurses, have been in focus in most research, less is
known about these variations (Murtomaa et al., 1990; Öberg, Karsznia,
Sandsjö, & Kadefors, 1995; Rundcrantz, Johnsson, & Moritz, 1991;
15
Rundcrantz, Johnsson, Roxendal et al., 1991; Ylipaa, Arnetz, & Preber,
1999).
Dentistry does not only involve a challenging psychosocial work
environment. Most of the workday is spent bent over a patient’s mouth in
order to access the teeth, particularly for dentists and dental hygienists. This
imposes visual demands and requires fixed postures and repetitive
movements for extended periods of time which generates a high muscular
load, particularly on the trapezius muscle (Åkesson, Hansson, Balogh,
Moritz, & Skerfving, 1997; Mileråd, Ericson, Nisell, & Kilbom, 1991;
Öberg et al., 1995). Moreover, the three most common tasks performed by
dentists are similar with no significant differences in muscle activity, posture
or frequency of posture between them. Therefore, the physical load of dental
work seems to be quite stable (Finsen et al., 1998). Working with strenuous
arm postures is particularly risky for women, who have an increased risk for
neck/shoulder pain compared to men (Hooftman, van Poppel, van der Beek,
Bongers, & van Mechelen, 2004).
Work-related health problems in public health care and
dentistry
With challenging work conditions, the prevalence of work-related ill health
in the municipal sector is relatively high. Among the most frequently
reported health problems are musculoskeletal problems including low back
pain and pain in the neck, feeling physically exhausted after work and
fatigue (W. Eriksen, 2003; Leighton & Reilly, 1995; The Work Environment
2007, 2008). There is also a relatively high prevalence of major depression
and stress-related mental disorders (Wieclaw, Agerbo, Mortensen, & Bonde,
2005). These physical and mental problems are reflected in a high sickness
absence (Lund, Labriola, & Villadsen, 2007), which may be an indicator of
both health problems and decreased work ability.
It has been debated whether work-related ill health is particularly
common within dentistry. While some research suggests that dental personal
are as well off and happy as other professional groups (Craven, 2008), other
research has indicated that dentists have an increased risk of coronary artery
disease and hypertension, as well as depression and suicide (Gerschman &
Burrows, 1998). Also, a high prevalence of headaches (60%) and sleeping
difficulties (60%), as well as minor psychiatric illness (32%), has been
reported (Myers & Myers, 2004).
16
Upper Extremity Disorder
Although there are inconsistencies regarding the frequency of work-related
ill health in dentistry, it is commonly agreed that there is a high incidence
(risk of new occurrences within a specific time period) and prevalence (total
number of cases in a population) of musculoskeletal disorder (MSD) among
dental personal (Alexopoulos, Stathi, & Charizani, 2004; Finsen et al., 1998;
Myers & Myers, 2004; Åkesson, Johnsson, Rylander, Moritz, & Skerfving,
1999). MSD is an unspecific diagnosis, including several factors relating to
the function of the muscular system, including muscular strength and
endurance, neuromuscular function (coordination, balance, speed), joint
flexibility and stability, skeletal strength, but also the subjective experience
of pain (self-reported and/or palpation soreness) and functional decline
(Barnekow Bergkvist, 2006). When factors in the work situation are part of
the aetiology, development or exacerbation, MSD is called work-related
musculoskeletal disorder (WRMSD). Different definitions of WRMSD exist,
but they commonly refer to any musculoskeletal condition, either specific or
unspecific, that is caused by work or work practices (Boocock et al., 2005).
The commonness of MSD and the high risk of sickness absence,
productivity loss and early exit from the workplace make it an important
problem from both an individual and organizational perspective, as well as
from the society. In dentists, the one-year prevalence of complaints was 65%
for neck-shoulder complaints and 59% for low back pain in one study
(Finsen et al., 1998). In another study, similar levels were found for point
prevalence levels for at least one musculoskeletal complaint, 62%, with 30%
reporting chronic complaints, 32% seeking medical care and 16% having
spells of absence (Alexopoulos et al., 2004). Comparable numbers from
another study suggest that the in the general population, the point prevalence
of non-specific MSD was 26.4%, with 19.0% reporting reported chronic
complaints (Huisstede et al., 2008).
In this thesis, the focus is on WRMSD that origins from the muscles in
the back and leads to symptoms from the upper extremities (upper back,
neck, shoulders, elbows and wrist-hands), upper extremity disorder (UED).
The work-related character and aetiology of these problems has been
acknowledged frequently (Buckle & Devereux, 2002). UED is particularly
relevant for dentistry, given the specific demands in the physical work
environment, including strenuous working positions and monotonous, finetuned movements. However, it is not only physical work environment that
has been related to MSD. Mental stress and cognitive demands such as time
pressure, repetitive tasks, lack of control, high demands and poor social
support have been associated with increased muscle tension and a high
prevalence of MSD, particularly in the upper extremities (Bongers et al.,
1993; Bongers et al., 2002; U. Lundberg, 2002b; van den Heuvel, van der
Beek, Blatter, Hoogendoorn, & Bongers, 2005). Interactions between high
17
physical and psychosocial demands seem particularly harmful (Devereux,
Vlachonikolis, & Buckle, 2002).
The trapezius muscle, which is at the origin of many UEDs, seems to be
particularly sensitive to emotional stimuli, which has been linked to their
evolutionary role in emotional communication (e.g. shrugging of shoulders).
Psychosocial stimuli may contribute to increased muscular tension. They
may also affect breathing, causing hyperventilation which reduces blood
CO2-levels and leads to increased PH-levels, which in turn contribute to
elevated muscular tension and enhanced sensitivity to sympathetic activity
(Schleifer, Ley, & Spalding, 2002; Schleifer et al., 2008). Long-lasting
mental and/or physical activity may also increase weariness in the first
recruited muscle units, since this keeps these “Cinderella” units active
continuously, causing fatigue (Hägg, 1991; Sjøgaard, Lundberg, & Kadefors,
2000). The experience of UED may also increase due to change in pain
sensitivity, which is due partly to physical changes in the muscles (vicious
circles in the muscle spiders) (H. Johansson & Sojka, 1991; Leeuw et al.,
2007) and partly to increased pain awareness, pain catastrophizing and
behavioural changes, including escape and avoidance-behaviours (H.
Johansson & Sojka, 1991).
Stress-related disorders
Along with musculoskeletal disorders, other stress-related disorders are
common in the municipal setting. High job strain (the combination of high
demands and low influence) shows strong associations with sleep
difficulties, tension prior to work, physical discomfort after a workday and
physical and mental symptoms (Statistics Sweden, 2004). These associations
have strengthened during the past decade (Statistics Sweden, 2004). Among
employees in the human service sector, low possibilities for development,
high meaning of work, low predictability, high quality of leadership, low
role clarity, and high role conflicts have been found to predict burnout three
years later (Borritz et al., 2005). 60% of women experiencing high strain at
work reported a lack of sleep (Statistics Sweden, 2004). Moreover, among
women, experiencing high demands is related to an increased risk for stressrelated sickness absence, even when their influence is high (which is
normally regarded as a better situation). This has been suggested to be
particularly relevant in women working in human-service professions where
emotional demands are high (Statistics Sweden, 2004).
Disease, ill health and health
When workplace health is studied empirically, it is often in terms of ill
health, symptoms and disease, or a lack thereof. However, theoretically, it is
18
often pointed out that health is something more than mere absence of
disease. This is in line with the 1946 definition of health from the World
Health Organization (WHO), which states that health is not simply the
absence of disease but rather a state of complete physical, mental and social
well-being (World Health Organization [WHO], 1946). Put in another way,
health has also been conceptualized as the ability to have and reach goals,
meet personal needs and cope with everyday life (Raphael et al., 1999; Ryff
& Keyes, 1995). Moreover, physical health has been described as referring
to an individual’s ability to perform physical activities free of role
limitations due to physical problems, bodily pain or general health status
(Ware, Kosinski & Keller, 1996), whereas mental health and psychological
well-being refers to an individual’s capacity to realize his or her own ability,
cope with the normal stressors of life, work productively and fruitfully, and
contribute to his or her community (Jahoda, 1958). Viru and Smirnova
(1995) suggest that health may be defined as the resistance to pathogenic
factors. They propose that, as a mechanism, resistance depends on the
effectiveness of specific homeostatic regulations, asserting that being healthy
equals being effective in adapting to change. In sum, although there is a
general agreement that health should be considered as something more than
simply the absence of disease or symptoms, practically, challenges
associated with measuring health contribute to operationlizations of health
that differ from the theoretical perspective, often focusing on a lack of
symptoms or disease as an indicator of health improvements. This thesis
follows the WHO definition of health, but due to the vast amount of previous
research that equates health with a decrease in symptoms, it will sometimes
appear in that context as well.
Stress
In this thesis, work conditions are understood within the framework of stress
research and stress physiology. In prevous research, the term stress has been
used for several different aspects, including the stress stimuli, the stress
experience, the stress-response and the experience of the stress response
(Ursin & Eriksen, 2004). In the following text, the focus will be on the
physiological stress response. However, it should be noted that this response
takes place within individuals whose perceptions of the stress stimuli differs,
as do their expectations on the possible outcomes of the stress response
(H.R. Eriksen, Murison, Pensgaard, & Ursin, 2005). From this follows that
although the stress response is generally considered to be universal, the level
of the stress response may differ between individuals. These differences
depend on the individual’s stimulus- and outcome expectancies. Hence, the
stress response is dependent on both psychological and physiological factors.
19
The physiology of stress
Responding physiologically to variations in internal and external stimuli is
an important ability (McEwen, 2000; Meaney, 2000). Evolutionarily, it has
been necessary for survival in an ever-changing world. This kind of response
is known as the stress response and includes changes in five interrelated
bodily systems, namely the neural, cardiovascular, automatic, metabolic and
immune systems (McEwen, 2008). The regulation of these systems ensures
that the individual is well adapted to the environment by changing the
internal milieu of various bodily organs and systems in accordance with
changes in the demands placed on the body (Chrousos & Gold, 1992;
McEwen, 2004). For example, the pressure the heart and blood vessels have
to apply in order to provide oxygen to different parts of the body differs
depending on body posture, oxygen consumption, etc. Hence, in order to
function properly, our blood pressure must be allowed to vary: it is lower
when we are at sleep or lying down, higher when we are sitting up and even
higher when we are running. The same goes for variation in emotional and
psychosocial stimuli. This process has been labelled allostasis, which means
―stability through change‖ (McEwen & Seeman, 1999; McEwen & Stellar,
1993). In contrast to organs and systems that only tolerates small changes in
a set value, e.g. body temperature or oxygen saturation, the systems involved
in allostasis tolerate variation. In fact, it is through these variations that the
homeostasis of other organs and systems can be ensured.
SAM-system and the HPA-axis
When a person is confronted with a stressor, changes in two neuroendocrine
systems are of central importance for adaptation. These systems are the
sympathetic adrenal-medullary (SAM) system and the hypothalamicpituitary-adrenocortical (HPA) system (see for example U. Lundberg, 1999).
The systems are activated in response to a variety of factors, including
physical threats, e.g. an attacking lion, modern stressors like a computer
shutdown or emotional and psychosocial stressors such as a heated
argument, uncontrollability and social evaluation (Dickerson & Kemeny,
2004). In response to a stressor, the SAM, which includes both the
sympathetic part of the autonomic nervous system (ANS) and the adrenal
medullary system, is quickly activated (U. Lundberg, 2000). Catecholamines
(adrenaline and noradrenaline) are released and contribute to increased heart
rate, blood pressure, muscle tension, mental activity and total energy
consumption (Chrousos & Gold, 1992; U. Lundberg, 2000). This alarm
reaction calls upon the individual to act so that the stressor is dealt with and
so that the extra activation of the system is no longer required. When this is
achieved, the effects associated with activation of the sympathetic nervous
system abate quickly, due to decreased activity in the sympathetic nervous
system and the short half-life of catecholamines (Berne & Levy, 1993).
20
Concurrently, another part of ANS, working in an antagonistic fashion with
the SNS, is activated: the parasympathetic nervous system (PSNS). This
results in decreased heart rate, blood pressure and blood flow in the skeletal
muscles (Lasley & McEwen, 2002). Meanwhile, the blood flow in the
visceral muscles and in the abdomen is increased, as is the saliva secretion.
In short, if the activation of SNS is necessary for survival in the presence of
a stressor, the activation of PSNS ensures survival in the long run by
allowing the focus of the body to be redirected from adapting to the outside
world to taking care of the inside: facilitate metabolism, relieve tension,
allow blood vessels to rest, etc. (Lasley & McEwen, 2002).
When the stress response is activated for more than a few minutes, the
activation of the SAM system is accompanied by activity in the HPA-axis,
which governs the release of cortisol (Berne & Levy, 1993). Two of the most
important properties of cortisol are its immunosuppressant and energy
mobilizing abilities (Tsigos & Chrousos, 2002). Cortisol helps replenish
energy by increasing the levels/concentration of blood lipids and blood sugar
in the bloodstream. This ensures that the bodily systems have sufficient
access to energy, which is particularly important in the face of prolonged
stressors, when energy consumption is high over a period of time. In
comparison to the catecholamines, the physiological effects of cortisol have
a slower onset, a longer time until they reach maximum effect and a much
longer duration of maximum effect (Haynes, Gannon, Orimoto, O'Brien, &
Brandt, 1991). Since it is also more responsive to the psychological and
emotional qualities of the stressor (Dienstbier, 1989; Haynes et al., 1991),
effects of the HPA axis are particularly relevant for many of the stressors of
today. And again, although the short-term effects of the activation of the
HPA axis are essential for survival, there are costs in the long run (U.
Lundberg, 2005).
Allostatic load
In sum, human beings are remarkably well equipped to respond through
changes within our bodily systems that allow us to adapt our internal milieu
in accordance with the external environment. However, this adaptive ability
comes at a cost: the processes that allow this place demands on our internal
milieu (McEwen, 2008). If these demands appear and disappear, there do not
seem to be any long-term negative effects (apart from those associated with
aging). Between demands and the accompanying activation of the stressrelated systems, other processes that restore and replenish the internal
resources are activated. However, when the activation in the SAM system
and the HPA axis is prolonged, these processes are hindered (Seeman,
Singer, Rowe, Horwitz, & McEwen, 1997): the activation starts to wear on
the organs involved. When wear is not adequately repaired, the result is a
depletion of internal resources and increased damage to the processes and
21
organs involved (Seeman, Singer et al., 1997). This process is called
Allostatic Load (AL) and shows how even an adaptive response may prove
harmful if it is activated in excess or beyond the limits of the systems it
depends on (McEwen & Stellar, 1993). Four situations when this may occur
have been described (McEwen & Seeman, 1999): 1) Too much stress, e.g.
too-frequent activation of the stress systems in response to exposure to
repeated, novel stressors that do not allow the system to reach baseline for
long enough periods; 2) lack of adaptation of the stress response to the
repeated occurrence of the same stressor; 3) inability to shut off the stress
response after the end of the stress exposure, for instance being unable to
unwind in the evening after work; and 4) dysregulation of the involved
systems, so that the function of one part negatively affects the other parts. In
psychological terms, it has been suggested that situations characterized by
uncontrollability and unpredictability are particularly likely to lead to
sustained activation (Sapolsky, 2004). Drawing from learning theory, this
has been described in terms of response outcome expectancy (H.R Eriksen,
Olff, Murison, & Ursin, 1999). Both expecting the outcome to be negative
no matter what is done, or completely lacking the ability to predict and
influence the outcome, have been related to sustained, or tonic, activition
(Ursin & Eriksen, 2004).
The consequences of these processes that are related to sustained
activation typically involve the dysregulation of multiple bodily systems,
and are characterized by biological responses deviating from the optimal
range, or by increased difficulties in returning to baseline levels, or resting
levels (McEwen & Seeman, 1999). The AL model also acknowledges that
over one’s life course, the stress of dealing with everyday life and the stress
places on the body by poor diet, smoking, lack of exercise, etc., may start to
wear down the bodily systems involved (Glei, Goldman, Chuang, &
Weinstein, 2007; McEwen, 2008; McEwen & Seeman, 1999). This increases
the natural deterioration of the bodily systems associated with aging. This
cumulative dysregulation may result in an allostatic load, which in turn,
increases the risk for future ill health and disease (Seeman, McEwen, Rowe,
& Singer, 2001). Hence, the AL model describes a mechanism by which the
protective effects of the acute (short-term) stress response turn into the
maladaptive, harmful effects of chronic or long-term stress. This means that
the AL model may explain how daily stress relates to health and disease
(Lasley & McEwen, 2002).
Recovery
In the AL model, the virtue of recovery is evident: processes activated
during a stress response need to be counteracted during a time when no
demands are being placed on the body. Recovery has been discussed in
22
relation to stress-induced arousal since the 1930s, when G.L Freeman (1939)
suggested that psychological recovery from experimental load was related to
the ability to withstand conflict and was thereby important in psychiatry. The
notion that quick recovery from stress-induced arousal was an important
coping characteristic was supported by other researchers in the 60s and 70s
(G. Johansson & Frankenhaeuser, 1973; Mason, 1968) and again in the 90s
(Haynes et al., 1991; Linden, Earle, Gerin, & Christenfeld, 1997). Since
then, scientific interest has slowly grown within multiple sub-disciplines:
work and organizational psychology, sports psychology and experimental
psychology.
Within work psychology, lack of recovery, or poor unwinding, has been
suggested as a key factor in the increasing levels of stress-related ill health in
the working population of industrialized countries (Frankenhaeuser et al.,
1989; Sluiter et al., 1999; Sluiter et al., 2000; Sluiter et al., 2003). Not
surprisingly given the AL model, lack of recovery from work has been
related to high levels of psychosomatic complaints in both cross-sectional
(Frankenhaeuser et al., 1989; Sluiter et al., 1999; Sluiter et al., 2000; Sluiter
et al., 2003) and longitudinal research (Sluiter et al., 2003). A high need for
recovery has also been linked to health factors such as long-term disease and
poor general health status (Jansen, Kant, & van den Brandt, 2002) and
increased sickness absence (de Croon, Sluiter, & Frings-Dresen, 2003;
Sluiter et al., 2003).
Definitions of recovery
Despite a recently growing interest in the concept of recovery, no commonly
agreed on definition exists. In its simplest form, recovery has been defined
as ―a poststress rest period that provides information about the degree to
which the elevation (i.e. reactivity) in the physiological and psychological
parameters being measured persists after the stressor has ended‖ (Linden et
al., 1997). As such, recovery is defined in relation to the stress response,
stress stimuli (stressors), various unspecific physiological and psychological
parameters and within a given time frame (post-stress rest period). However,
although this puts recovery in a context, multiple definitions of each of the
concepts that recovery is related to exist. Within work psychology, A. Craig
and Cooper (1992) defined recovery as ―the timing and efficiency by which
an individual is able to return to an adequate or pre-stressor level of
functioning after the termination of a stressor‖. Hence, they defined recovery
in relation to the termination of the stress stimuli (the stressor) rather than in
relation to the stress response, and without explicitly stating what ―prestressor level of functioning‖ refers to. Again, both the time at which the
process takes place (timing after a stressor) and the result of the process
(efficiency in returning to a pre-stressor level of functioning) are
incorporated in the definition.
23
Extending the work of A. Craig and Cooper (1992), Meijman & Mulder,
(1998) described recovery in the effort-recovery model. The model describes
how effort during work leads to load reactions that need to be reversed, so
that the psychological, biological, and behavioural states can return to their
pre-demand levels. Thereby, fatigue and other effects of stressful situations
may be reduced. Hence, the effort-recovery model differs from the previous
models by relating the recovery process to the experience of stress (effort
during work) and the experience of the stress response (load reactions),
rather than to the stress stimuli and the stress response. It also explicitly
states that not only physiological but also psychological processes need to be
considered. The effort-recovery model predicts that if this normal process of
effort and recovery is interrupted, load may accumulate, resulting in ill
health and reduced well-being.
In the definitions described above, recovery involves both a process of
recovering or restoring health and strength after a stressor, and/or the result
of that process, either absolute or relative to baseline or to the stressor (stress
stimuli), the stress response or the stress experience. In this thesis, the
operationalization of recovery focuses on relative recovery in relation to a
stressor (a workday) and the latency to recover (whether one feels recovered
after a specific time period) (see methodology). This is motivated by the
limited information available on the characteristics of the process of
recovery. The operationalization of recovery in this thesis also leaves to the
participants to judge what it, in fact, means to be recovered. Hence, the
operationalization includes recovery in relation to the experience of the
stress response, since this is what the individual is aware of. This allows for
a more holistic approach to recovery than merely viewing it as a
physiological return to baseline.
Time frame (timing) of recovery
Following the definitions of recovery, the time course of the recovery
process and the variables studied as outcome of recovery need to be
considered. From this follows that empirically, an assumption about the time
frame within which recovery needs to take place always needs to be made, in
order to schedule measurements. However, the magnitude of this parameter
– that is the time required for recovery to take place – is, with some
important exceptions, seldom discussed explicitly (Sluiter et al., 2000).
Besides being important in order to time the measurement correctly, the time
frame of recovery may be important in order to understand differences in
recovery between individuals, and possibly between different situations. If
recovery from a stressful workday is twelve hours for one individual but 24
hours for another, the practical implications are huge. Differences may also
arise within a given time frame. It is possible that two individuals are equally
recovered eight hours after a stressor, but still differs in how and when this
24
recovery happened, that is, the slope of the recovery curve. For example, one
might have done most recovery within the first few hours, while the other
may have remained unrecovered until seven hours after the stressor, and then
recovered completely in the last hour. These questions remain to be
investigated.
The time frame of recovery is also important in relation to long-term ill
health. It has frequently been acknowledged that when it comes to harmful
effects, it is the long-term activation of the stress response that is important
(e.g. ―long-term stress‖). Acute, short-lasting stress may even have a
protective effect (McEwen, 2008). Distinguishing acute stress from longterm stress is therefore of great value. However, there is no clear evidence
indicating when acute stress turns into the harmful effects associated with
long-term stress. Put another way: we do not know when recovery needs to
take place after a stressor, before harm has been done. It may also be
relevant to distinguish between different kinds of ―harmful effects‖: while
months of frequent or sustained stress activation may cause health problems,
demanding work weeks that is followed by rest and recovery may not lead to
bodily harm, but may still have adverse social effects or negative effects on
quality of life. This issue, too, needs to be investigated.
Within work psychology, recovery from work has frequently been studied
as an acute and short-term reaction to work, focusing on recuperation after
one day of work (Jansen et al., 2002; Sluiter et al., 2003). Although there
also are several studies investigating the effects of vacation on recovery
(Etzion, 2003; Westman & Eden, 1997), few have simultaneously
considered recovery after different time intervals. This is the approach taken
in Studies II and IV in this thesis. The time intervals used are similar to those
proposed by Sluiter and colleagues (2000), who defined four categories:
reactivity (the time during a stressor/workday), mesorecovery (10-60
minutes after a stressor, e.g. a coffee break or a lunch break), metarecovery
(recovery between workdays) and macrorecovery (recovery after a weekend
off work).
Fatigue and recovery
Fatigue is a concept that is closely related to recovery from work. It may be
described as part of a continuum stretching from tiredness to exhaustion,
with fatigue being placed in the middle of these two (Kenttä & Svensson,
2008). As such, the continuum stretches from a neutral or even pleasant
sensation to an unpleasant, troubling experience. Tiredness, or acute fatigue,
has been described as task-specific and reversible, in that it can be managed
and reversed by switching activity or by resting, while long-term fatigue is
more resistant to change and less sensitive to the ordinary recovery strategies
(Beurskens et al., 2000). In occupational psychology, the focus has been on
fatigue as an unpleasant, unwanted experience related to high work-related
25
effort, high work-family interference and health complaints (van Hooff,
Geurts, Kompier, & Taris, 2007). Also, the extreme version of fatigue, e.g.
exhaustion, is one of the core dimensions of burnout (Borritz et al., 2006).
In relation to fatigue, recovery may be considered as the other end of the
fatigue continuum, stretching from recovered to feeling refreshed and alert.
However, in relation to recovery, fatigue could also be described either as a
reaction to a stressor (in the context of work stress, short-term fatigue is
often translated into fatigue during and after a workday) or, if the time frame
is longer, a consequence of lack of recovery. This is equal to the distinction
between the acute and long-term fatigue described previously (Beurskens et
al., 2000). From this follows that the relationship between recovery and
fatigue may vary according to the time frame of the study. With shorter time
frames (minutes or hours) fatigue will most likely be a reaction to stress, and
precede recovery. With wider time frames (weeks, months or even years),
which is more common within work and organizational psychology, the
relationship between fatigue and recovery is likely to be reciprocal since lack
of recovery, in the long run, is likely to increase fatigue (Sluiter et al., 2003).
Irrespective of how the relationship between fatigue and recovery is
defined, it seems reasonable to separate fatigue from recovery in the
measurement of recovery. Empirical support for separating fatigue and
recovery can be found in a previous study (Jansen et al., 2002). To
investigate the validity of self-ratings of recovery, items measuring recovery,
fatigue, and psychological distress were subjected to principal component
analyses (using the Need for Recovery Scale, the Checklist Individual
Strength (CIS), and the General Health Questionnaire (GHQ-12)) (Jansen et
al., 2002). The results suggest that self-rated recovery, fatigue, and
psychological distress are distinct, although related, concepts (Jansen et al.,
2002). A parallel to this can be found in research that suggests that recovery
and stress reactivity is different rather than opposing constructs, since factors
that affect recovery not necessarily affect stress reactivity. For example,
research comparing individuals who differ in physical fitness has shown that
difference in speed of recovery after a stressor serves as a more relevant
distinction than does difference in reactivity to the stressor (Haynes et al.,
1991). Hence, recovery is not merely another way of tapping stress
reactivity, and it may be reasonable to separate recovery from fatigue in
measurements of recovery. However, despite this and despite that fatigue
seldom is part of the theoretical definitions of recovery, previously, fatigue
have often been included in measurements (self-ratings) of recovery
(Aronsson, Svensson, & Gustafsson, 2003; Jansen et al., 2002; Sluiter et al.,
2003; van Veldhoven & Broersen, 2003).
26
Recovery from work stress
As precursors of the need for recovery from work, the emphasis has been on
characteristics of the work situation. Both quantitative aspects of work such
as number of hours worked (Jansen, Kant, van Amelsvoort, Nijhuis, & van
den Brandt, 2003; Jansen, van Amelsvoort, Kristensen, van den Brandt, &
Kant, 2003) and qualitative aspects such as mental and physical demands
and lack of decision latitude have been suggested as affecting the need for
recovery (Sluiter et al., 2003). However, non-work activities may also
influence recovery from work. For example, work-related activities during
off-job time have been shown to delay recovery (Sonnentag & Zijlstra,
2006). A number of studies have shown that for women, an interaction
between conditions at work and conditions at home may also contribute to
stress (U. Lundberg & Frankenhaeuser, 1999; Nordenmark, 2004). Since
recovery from work requires the absence of new stressors, factors associated
with the time off may be as important as the characteristics of the work
situation for the process of recovery from work. For example, among
women, being in an unhappy marriage has been related to poor recovery
(Saxbe, Repetti, & Nishina, 2008). Hence, domestic, individual and social
factors such as marital status, total workload and work-home conflict may
influence the time, ability and opportunity available for the individual to
return to the pre-stressor level, thereby modifying the need for recovery.
Non-work hours may involve many different activities and processes,
some of which may hinder recovery and some of which may promote
recovery. Recovery is often described as requiring rest or at least a lack of
stimulation, but frequently, active non-work activities such as exercise as
well as creative and social activities have been found to promote recovery
(Rook & Zijlstra, 2006; Sonnentag, 2001; Winwood, Bakker, & Winefield,
2007). Consequently, active non-work activities may be more effective in
promoting recovery than passive activities, like watching TV. From this
follows that it is not only the preceding stress level and the time allocated for
recovery that are of importance in determining the recovery process, but also
what activities take place.
Perseverative cognitions
It is not only the type of non-work activity, which is a behavioural factor,
which affects recovery. Mental activity, without apparent exertions, may
also contribute to the total load and impede recovery. According to the
perseverative cognition hypothesis, prolonged activation of the stress
systems is often caused by perseverative cognitions (Brosschot, Gerin, &
Thayer, 2006; Brosschot, Pieper, & Thayer, 2005). These are defined as
active cognitive representations of stressors that are prolonged and
27
manifested in phenomena such as worry, rumination and anticipatory stress.
Despite some difference between these concepts, such as worry typically
being associated with anxiety about future events, and rumination being
associated with depression over past events (Papageorgiou & Wells, 1999),
they share some important features. These include the experience of having
repetitive, intrusive, negative cognitions (Papageorgiou & Siegle, 2003;
Segerstrom, Tsao, Alden, & Craske, 2000).
Perseverative cognitions may lead to prolonged activation of the
cardiovascular, endocrinological, immunological and neurovisceral systems
(Brosschot et al., 2006; Brosschot et al., 2005). For example, worry has been
shown to increase automatic activation (increased heart rate and decreased
heart rate variability) (Brosschot, van Dijk, & Thayer, 2007). Among
women, but not men, worry has also been related to increased morning
levels of cortisol (Gustafsson, Lindfors, Aronsson, & Lundberg, 2008). This
prolonged activation may be a mechanism by which perseverative cognitions
prevents recovery from work (Pravettoni, Cropley, Leotta, & Bagnara,
2007).
A related hypothesis has been proposed by Sonnentag and Bayer (2005),
who concluded that the ability to detach from work is important in order to
recover from work stress. Lack of detachment has been related to high
negative activation and fatigue the next morning (Sonnentag, Binnewies, &
Mojza, 2008). In line with this, rumination, particularly among individuals
experiencing high-strain work, has been related to poor unwinding after
work (Cropley & Purvis, 2003). Other studies, focusing on mental activity
and recovery in terms of sleep, have shown that being unable to stop
thinking about work is related to poor sleep (Cropley, Dijk, & Stanley, 2006)
and that this may be a stronger predictor of disturbed sleep than high job
demands are (Åkerstedt et al., 2002). Anticipatory stress, that is worrying
about the next day, has also been related to disturbed sleep, in terms of
distorted physiological sleep patterns and subjectively poor sleep (Kecklund
& Åkerstedt, 2004).
Overcommitment (OC) is described as a motivational pattern
characterized by excessive work-related commitment and a high need for
approval (Siegrist et al., 2004). The core construct in OC is inability to
withdraw from work obligations. As such, OC may be interpreted as
perseverative cognitions, but within a specific context (i.e., work).
Consequently, OC has also been associated with a number of physiological
factors that may be related to an increased physiological activation, such as
higher basal sympathetic activation (Vrijkotte, van Doornen, & de Geus,
2004), lower noradrenaline stress reactivity (Wirtz, Siegrist, Rimmele, &
Ehlert, 2008) and factors that may increase risk for cardiovascular disease
such as an impaired fibrinolytic system (Vrijkotte, et al. van Doornen, & de
Geus, 1999). OC has also been related to vital exhaustion (Preckel, von
Kanel, Kudielka, & Fischer, 2005). However, the direct relationship between
28
OC and recovery has not been investigated. In addition, most research on
OC has been restricted to men (Steptoe, Siegrist, Kirschbaum, & Marmot,
2004), and when both men and women have been studied, the relationships
between OC and recovery-related measures have differed between the two
groups. Generally, associations between OC and factors such as poor sleep
quality and signs of sustained physiological activation has been found
among men but not among women (Eller, Netterstrøm, & Hansen, 2006;
Kudielka, von Känel, Gander, & Fischer, 2004; Steptoe et al., 2004). This is
somewhat surprising, given that women often report more worry and
rumination than do men (Butler & Nolen-Hoeksema, 1994; NolenHoeksema, Larson, & Grayson, 1999; Robichaud, Dugas, & Conway, 2003).
The relationships between OC and recovery and fatigue among women are
investigated in Study III.
Interventions in the workplace
Considering how much of the waking time humans spend at work, factors
associated with the workplace may have powerful effects on individual
function and health. Interventions in the workplace can be placed into three
categories: promotion, prevention and rehabilitation. These categories are
roughly equivalent to primary, secondary and tertiary prevention,
respectively. Rehabilitation and tertiary prevention are activities that are
initiated in response to a disease or problem that is already present, in order
to rehabilitate or prevent its worsening (Quick, 1999a). This makes these
interventions after-the-fact. Secondary prevention refers to interventions that
aim at preventing disease from evolving from early symptoms, while
primary prevention means preventing illness or disease before any symptoms
are present, that is, focusing on health risk factors and/or occupational
demands (Quick, 1999a). Both these perspectives are covered in the
prevention category in the first list. Sometimes, but not always, primary
prevention is said to include health promotion, that is activities that are not
focused on decreasing problems or disease but on increasing health (Quick,
1999b; Tetrick & Quick, 2003). WHO defines health promotion as ―the
process of enabling people to increase control over, and to improve, their
health‖ (WHO, 1986). In this thesis, the focus is on primary prevention and
health promotion, and, to some extent, on secondary prevention.
Distinguishing between these is often difficult in workplace interventions, as
all employees, both those at risk and those not at risk, are targeted (Tetrick &
Quick, 2003). The focus in this thesis on an occupational field with high
prevalence of UED and stress-related illnesses suggests that the interventions
investigated in Study II should be considered secondary. However, since the
employees are still at work and may be considered part of a healthy
population, and since not all of them report symptoms, the interventions may
29
be considered primary prevention or health promotion. Rehabilitation or
tertiary prevention is not discussed in this thesis.
When the context of health promotion is the workplace, workplace health
promotion (WHP) has been defined as the combined efforts of employers,
employees and society to improve the health and well-being of people at
work (European Network for Workplace Health Promotion, 2005). This
includes improvements in the work organization and working environment,
promoting employees’ participation in health activities and encouraging
personal development. WHP has been described as mutually beneficial to
employers and employees: while employees may improve their health, job
satisfaction (Parks & Steelman, 2008) and motivation at work, employers
benefit from this through a reduction of sickness absence and sickness
absence-related costs (Aldana, Merrill, Price, Hardy, & Hager, 2005;
Golaszewski, 2001; Parks & Steelman, 2008), a higher quality of products
and services, more innovation and a rise in productivity (Goetzel &
Ozminkowski, 2008; Mills, Kessler, Cooper, & Sullivan, 2007). Focusing on
WHP may also be a prestige factor that improves goodwill and makes the
organization more attractive as an employer (European Network for
Workplace Health Promotion, 2005).
WHP can take one or both of at least two perspectives on employee
health. From one perspective, health can be regarded as influenced mainly
by individual factors. From the other, health is considered multifactorial,
influenced by both individual factors and by the workplace (and society). In
the first perspective, WHP mainly includes health initiatives targeting the
individual, e.g. smoking, physical activity or diets. Using the workplace as
an arena for reaching adults with these kinds of health initiatives have been
suggested to have a number of advantages (Ilgen, 1990) including reaching a
greater number of individuals compared to individual-based settings (DrachZahavy, 2008). They also have the advantage of utilizing social support for
recommended changes (Bamberger & Sonnenstuhl, 1996) and have a greater
opportunity of providing cues and reinforcement that help maintain
behaviour change, e.g. make relapse less likely (Hays, Hays, DeVille, &
Mulhall, 2000). In the second multifactorial perspective, the focus is more
often on factors in the workplace, such as job design, stress management,
ergonomics, etc. This places this perspective close to the notion of healthy
organizations, in which organizational factors associated with increased
employee health are identified and strengthened (Semmer, 2003; Wilson,
DeJoy, Vandenberg, Richardson, & McGrath, 2004).
The worksite as an arena for health promotion has also been criticized,
since WHP often targets a selected group of already healthy, highly educated
white-collar workers, predominantly men, within large organizations in
Western countries (Dishman, Oldenburg, O'Neal, & Shephard, 1998; Janer,
Sala, & Kogevinas, 2002; Shephard, 1996). From a public health
perspective, other groups may gain more from health promotion initiatives.
30
Physical activity interventions
One of the most common focuses of WHP is physical activity (PA). Getting
people to engage in physical activity has long been considered a public
health interest, given that low levels of PA have been related to several
common disorders, including heart disease (2.0 increased risk for individuals
with low levels of PA), hypertension (1.5), type II diabetes (1.5),
osteoporosis and related factors (2.0), colon cancer (2.0) (Colditz, 1999),
depression (1.3) (Stephenson, Bauman, Armstrong, Smith, & Bellew, 2000)
and breast cancer (1.4-1.7) (Friedenreich, 2001). Despite these risks, many
individuals in Western society are physically inactive. In 2007, 34% of men
and 38% of women in Sweden failed to meet the general guidelines for
physical activity, which correspond to 30 minutes a day of moderate
intensive activity (Statens folkhälsoinstitut [Swedish National Institute of
Public Health], 2008).
Definitions of Physical activity and physical exercise
Often, PA of low to moderate intensity is defined as any bodily movement
produced by skeletal muscles that results in energy expenditure, while
planned, structured and repetitive bodily movement with the goal of
enhancing or sustaining physical capacity is denoted as physical exercise
(PE) (Caspersen, Powell, & Christenson, 1985; Pate et al., 1995). PA and PE
may also be distinguished by differences in intensity levels. Moderateintensity PA is generally equivalent to a brisk walk and noticeably
accelerated heart rate, while PE involves exercise of greater intensity, over
60 or 70% of maximal oxygen uptake, and causing rapid breathing and a
substantial increase in heart rate, for example jogging (Physical Activity and
Public Health, 2007). In this thesis, when the term PA is used alone, it refers
to physical activities of all intensities. When a distinction is made between
PA and PE, PA refers to physical activity of low to moderate intensity while
PE refers to planned physical activity of moderate to high intensity.
According to the American College of Sports Medicine (ACSM), both PA
and PE are appropriate in meeting the guidelines for PA (Physical Activity
and Public Health, 2007). However, while both moderate and vigorous
activities involves aerobic activity, that is, engage large muscular groups in
dynamic muscular activity that affects the circulatory and metabolic systems,
only activities of higher intensity (>70%) have effects on cardiovascular
capacity, while activities of lower intensity (<70%) have effects on periphery
circulation and muscular endurance (American College of Sports Medicine
Position Stand, 1998; Kraemer et al., 2002).
Recommended levels of PA
ACSM suggest that a minimum of 30 minutes of moderate daily PA five
days a week, or vigorous-intensity aerobic physical activity for a minimum
31
of 20 min on three days a week, is sufficient to avoid problems related to a
sedentary life style, and to gain health effects (Pate et al., 1995). These
recommendations are based on total physical activity being a function of
frequency, intensity and duration of each bout of activity. From this follows
that shorter bouts of vigorous activity give health effects equal to those from
longer bouts of moderate-intensity activity. This can be illustrated using
metabolic equivalent (MET), which estimates energy expenditure during PA:
jogging (8 METs) for 12 minutes equals walking (3.3 METs) for 29 minutes
(8 x 12 and 3.3 x 29 both equals 96 METs/min) (Physical Activity and
Public Health, 2007).
Concurrent with recommendations for physical activity, the need to
decrease time spent on sedentary behaviour has also been discussed.
Sedentary behaviour is commonly defined as being static and is associated
with sitting, watching TV, working in front of a computer and travelling by
car, equalling 1-1.5 METs (Clark et al., 2008; Owen, Leslie, Salmon, &
Fotheringham, 2000). Recent research suggest that the combination of high
levels of sedentary behaviour such as watching TV and low levels of
physical activity may be particularly harmful (Sugiyama, Healy, Dunstan,
Salmon, & Owen, 2008). Importantly, those meeting the guidelines for
physical activity but spending much time in sedentary behaviours and those
not meeting the guidelines but spending less time in sedentary behaviours
have been shown to have a similar risk of being overweight or obese
(Sugiyama et al., 2008). Therefore, reducing sedentary behaviours may be as
important as increasing physical activity.
PA in the stress-recovery relationship
From a public health perspective, initiatives to increase PA in the
population is motivated given the solid epidemiological evidence for lack of
PA being important in the development of many of the most common
diseases. However, PA is also relevant from a stress-recovery perspective.
While acute effects of PE involves activating many of the same
physiological systems as in the stress responses, repeated PE leads to a
physiological and behavioural adaptation, so that the same load requires less
response and becomes associated with more positive affect (Anshel, 1996;
Salmon, 2001; van Doornen & de Geus, 1989). This means that a physical fit
individual shows an attenuated reactivity to stressors compared to an unfit
individual. This adaptation has also been shown to generalize to
psychosocial stressors (Forcier et al., 2006; Salmon, 2001). Also, PE has
also been related to speedier recovery after a stressor (Chafin, Christenfeld,
& Gerin, 2008; Traustadottir, Bosch, Cantu, & Matt, 2004). Hence, PE may
decrease the physiological burdon on stress both by attenuating the reactivity
and by decreasing the time it takes to recover. Moreover, it has been
suggested that PA is related to increased general adaptability and more
32
effective homeostatic regulation, thereby increasing the individual’s
resistance to pathogenic factors (Viru & Smirnova, 1995).
On the psychological level, being fit has been related to increased
psychological resources, including boosting self esteem and increasing social
support, which in turn leads to less distress (Ensel & Lin, 2004). PE has also
acute effects on mood, both enhancing positive mood and alleviation
negative mood in the three-four hours following a training session (Yeung,
1996). This may be particularly important in relation to effects of WHP PA,
since this means that some of the acute effect on mood may take place while
still at the workplace.
Effects of WHP PA
There is a general agreement that PA is health-promotive (Marcus et al.,
2006). In the following section, the focus is on effects of PA and/or PE
interventions conducted at the worksite. First, PA interventions have been
shown to be effective in increasing levels of physical activity (Titze, Martin,
Seiler, Stronegger, & Marti, 2001), despite problems with self-selection of
already physically active individuals. It has also been related to increased
physical fitness, improved perceived health status and prevention of early
decline of work ability (Pohjonen & Ranta, 2001). Moreover, PA
interventions have been related to a reduced risk of developing MSD
(Proper, Koning, et al., 2003) and decreased headache and neck pain
(Sjögren et al., 2005). PA has also been related to increased levels of
subjective physical well-being (H.R Eriksen et al., 2002; Sjogren et al.,
2006). Also, effects on total energy expenditure, cardiorespiratory fitness,
percentage of body fat and blood cholesterol have been reported (Proper,
Hildebrandt, van der Beek, Twisk, & van Mechelen, 2003). Hence, WHP PA
has been related to both physiological and psychological effects. However,
reviews and meta-analyses present inconclusive findings regarding effects of
worksite physical activity interventions (Marcus et al., 2006). For instance,
effect sizes for worksite physical activity interventions have been small
(mean r = 0.11) (Dishman et al., 1998; Wilson, Holman, & Hammock,
1996). These results have been explained with reference to the poor quality
of the research in the field (Dishman et al., 1998; Wilson et al., 1996) but it
may also be argued that small effect sizes are to be expected in studies when
the outcome is physical and/or mental health, since there are many possible
determinants of these outcomes. From this follows that the variance
explained by each factor (such as physical exercise) is small (Zapf,
Dormann, & Frese, 1996).
One frequent problem in worksite physical activity interventions involves
low participation rates and self-selection of participants (Alexy, 1991).
Frequently, participation rates in worksite fitness programs range from 15%
to 30% for white-collar workers (Conrad, 1987). With some important
33
exceptions (H.R Eriksen et al., 2002; Pohjonen & Ranta, 2001), participation
levels may be even lower among blue-collar workers (Marshall, 2004).
Moreover, participators are often younger, more educated, more physically
fit and healthier than non-participators prior to the intervention (Alexy,
1991; Conrad, 1987; Marshall, 2004).
Strategies for WHP PA
There are a number of different strategies for implementing PA in the
workplace. Two main categories of WHP are individual-change centred or
environment- or ecological-centred interventions, hence differing in how
much they utilize the workplace as such as an instrument to initiate or
maintain change. Individual-change interventions are by far the most
common, while few environment intervention studies have been conducted
(Yancey et al., 2004). In individual-change interventions, strategies include
health checkups, educational programs or workplace exercise programs, or a
combination thereof (Marshall, 2004). The most common strategy in
ecological or environmental interventions (the words are used
interchangeably) is providing motivational prompts to be more active
(including posting signs and creating walking trails) (Yancey et al., 2004),
although strategies utilizing existing social structures for support (Campbell
et al., 2002; W. S. Cohen, 1985) and incentive-based programs (W. S.
Cohen, 1985; Marshall, 2004) have also been investigated. Apart from this,
attempts to integrate PA into the workday have been made, including
providing time for PA during the workday. These initiatives have proved
promising, in both attracting employees and reaching higher participation
levels than otherwise, and in terms of results on employee health (H. R.
Eriksen et al., 2002; Pohjonen & Ranta, 2001; Yancey et al., 2004). Since
women are particularly likely to motivate lack of physical activity with time
constraints (Tavares & Plotnikoff, 2008), this strategy may be particularly
promising in this group.
Reduced working hours
In the Nordic countries, the demands of working life within municipal
services have contributed to that several WHP initiatives involving reduced
working hours (RWH) have been carried out (Åkerstedt, Olsson, Ingre,
Holmgren, & Kecklund, 2001; Anttila, Nätti, & Väisänen, 2005; Brynja, &
Bildt, 2005; Malmberg, Hansson, & Byrgren, 2003; Wergeland et al., 2003).
In contrast to various types of part-time work, work-time arrangements
involving RWH mean that employees work fewer hours but still retain their
full-time salaries. Often, additional employees are recruited by the
organization to provide full time services (Brynja & Bildt, 2005; Malmberg
et al., 2003). RWH often differs from part-time work in that it involves a
systematic change in work hours, and that it includes all employees at a
34
workplace. The motives for RWH and part-time work also differ: while
RWH is motivated from a health perspective, part-time work may be
motivated by either economic or scheduling motives of the employer or by
employee considerations such as own illness, caring for children or other
personal responsibilities, studies, etc. (Statistics Sweden, 2005).
The mechanism for how RWHs can promote health is still unclear. One
obvious reason RWH is assumed to promote health is that by spending fewer
hours at work, one’s exposure to different risk factors in the work
environment decreases. From a whole-life perspective, RWH may also have
other effects. By reducing time spent on paid work, the total workload (paid
and unpaid work) may decrease, thereby reducing stress. RWH may also
help combine different life domains (e.g. work and family life), thereby
reducing work-family interference and role ambiguity. Moreover, RWH may
allow more time for non-work activities that promotes health, for example
increase time for recovery and time spent on leisure activities such as
physical activity (Åkerstedt et al., 2001; Anttila et al., 2005; Brynja & Bildt,
2005; Malmberg et al., 2003). In sum, this assumes that the RWH is replaced
by activities that are more health-promotive than work is.
As described in the background, there is support for work having positive
effects on health. So, working fewer hours may not only decrease exposure
to potential health hazards but may also reduce the potentially positive
effects of work. This means that the health benefits of not being exposed to
risk factors may be counteracted by reduced time for social interaction and
other positive factors at work. Moreover, it remains to be investigated if an
eight-hour workday, or a 40-hour work week, is associated with increased
health risks compared to a shorter workday or work week (Spurgeon,
Harrington, & Cooper, 1997). In fact, research has shown that not even
extended work hours (12-hour shifts or 48-hour work weeks) are necessarily
harmful or affect performance negatively (Smith, Folkard, Tucker, &
Macdonald, 1998; Tucker & Rutherford, 2005).
One of the most common types of RWH involves a reduction in working
hours from eight to six hours a day or from 40 hours to 30 hours a week.
This kind of RWH has been related to positive social effects and decreased
work-family conflict, particularly in employees with children (Åkerstedt et
al., 2001; Anttila et al., 2005). Apart from positive social effects of the sixhour workday, the potential health-related benefits of RWH remain unclear,
although there is some support for RWH in relation to a reduction of pain in
the neck/shoulder area in employees within the public sector (Bildt, 2007;
Wergeland et al., 2003). Also, decreased stress levels have been reported in
one study (Bildt, 2007). Apart from this, evaluations of different types of
RWH have produced only minor effects on other health-related outcomes,
such as fatigue, disturbed sleep and physiological factors (Åkerstedt et al.,
2001; Bildt, 2007; Brynja & Bildt, 2005).
35
With few exceptions (Åkerstedt et al., 2001; Anttila et al., 2005),
evaluations of health-related effects of RWH often suffer from
methodological shortcomings (Brynja & Bildt, 2005; Malmberg et al., 2003).
For instance, systematic longitudinal research with measurements before,
during and after the implementation of RWH have been scarce, referents
have seldom been included, and, often, existing studies lack adequate
measures reflecting different aspects of health. Also, it remains unclear
whether the effects of RWH are direct or mediated via psychosocial factors,
which follows from the lack of theoretical understanding of various healthrelated effects of RWH.
Aim of the thesis
The main aim of this thesis was to investigate different aspects of health and
ill health in relation to recovery from work among women in the public
health care sector with physically and emotionally demanding jobs. There is
a specific focus on how efforts associated with work need to be balanced
with recovery during the time off work in order to prevent ill health and
promote health. This thesis includes a descriptive study of UED in dentistry,
a study on intervention and an investigation of how recovery from work is
related to psychosocial factors and physiological processes. More
specifically, the following specific research questions were asked:
- How are musculoskeletal disorders in the upper extremities (neck,
shoulders, arms, elbows, wrists, hands or fingers) (UED) related to other
health problems and physical and psychosocial work characteristics in a
workplace meeting modern ergonomic standards (Study I)?
- Are there any health-related effects of two worksite interventions,
physical exercise (PE) and reduced working hours (RWH) (Study II)?
- How are job demands, job control and social support at work and
overcommitment related to fatigue and next-day recovery (Study III)?
- How is self-rated recovery from work stress related to biological
dysregulation in terms of allostatic load (Study IV)?
36
Method
Design of the studies
This thesis is based on four studies ranging from 1) a descriptive study
relating poor work conditions to UED and 2) an intervention study of the
health-related effects of reduced working hours and physical exercise during
work, to two studies focusing on recovery from work: 3) how
overcommitment to work interfere with the recovery process and 4) the
relationship between fatigue and lack of recovery and a cumulative
biological load. Different statistical methods were used for these studies, as
well as partly different data sets. Data for Studies II-IV were gathered using
the same protocol, while a completely different data set was used in Study I.
In the next section, the design of each study is presented and afterward
follows a description of the central concepts in this thesis and how they were
measured. A description of the data sets can be found in the beginning of the
Summary of empirical studies section.
Study I is a descriptive study of the work conditions in dentistry in
relation to UED. The study was set among female employees of a large
public dental health care organization consisting of 48 workplaces. Data
were drawn from a pre-existing sample gathered as part of a general work
environment assessment. The women were categorized into two groups,
those with and those without UED. All items measuring psychosocial work
characteristics were subjected to a principal component analysis (PCA)
before further analysis. The main analyses were performed using
MANOVAs and a hierarchical multiple regression analysis.
From the 48 workplaces that were part of the organization participating in
Study I, six were selected by the employer to participate in an intervention
project studying the effects of reduced working hours (RWH) and physical
exercise (PE) on health. The results from this intervention are presented in
Study II. The inclusion criteria for the workplaces were a) having at least 25
employees b) being economically sound and c) having local management
and a majority of employees consenting to participate. Moreover, three of
the selected workplaces had high short-term sickness absence (that is,
counting all sickness absence with a duration of 21 days or less) and three
had low short-term sickness absence. Workplaces with high and low
sickness absence were then matched into pairs based on number of
employees and the three pairs were randomized into one of the three
37
conditions (RWH, PE or a reference group). This means that randomization
was done on the organizational level rather than the individual level. Having
a cluster of individuals randomly allocated to intervention groups rather than
each individual is the principle behind cluster randomization, which is a
common method within research areas where individual randomization is
often practically impossible and intervention is naturally applied to the
cluster level (e.g. a workplaces, a doctors office, a classroom, etc.) (Jo,
Asparouhov, Muthen, Ialongo, & Brown, 2008). In Study II, one matched
pair of workplaces was randomized to each condition. To minimize risk of
pre-intervention differences between clusters influencing the result, as well
as non-intervention-related changes that may affect one cluster but not the
other, a number of measures were taken: only workplaces belonging to the
same organization within the same work field took part, all workplaces had
at least 25 employees, and the workplaces were matched into pairs based on
sickness absence. Thus, correlations within and between clusters were
designed to be as similar as possible.
The design of Study II was longitudinal, including a reference group and
repeated measures over time. More specifically, data including both selfratings and physiological measures were gathered before the start of the
intervention (T1), after six month (T2) and after 12 months (T3). Data were
analysed using individuals as unit of analysis. To examine the effects of the
interventions on outcome measures, interaction and overall time effects were
tested using repeated measures analyses of variance (ANOVAs), considering
all three time points for self-ratings and two time points (T1 and T3) for the
physiological measures. Significant main effects of time and interaction
effects were followed by separate repeated measures ANOVAs for the three
groups, with time of measurement as a within-subjects factor. From this
follows that for each interaction effect or main effect, each group was
studied individually.
Study III was also of a longitudinal design, using the same data set as
Study II but utilizing data only from T2 and T3 (obtained six months apart)
and only self-ratings. The predictive value of job demands, job control and
social support, and overcommitment to work, on poor next-day recovery and
fatigue six months later, respectively, was analysed using hierarchical
multivariate regression analyses. In contrast to the automated stepwise
regression procedure, this approach is guided by theory or logic, meaning
that the researcher controls the analysis (Babyak, 2004; Tabachnick &
Fidell, 2007). In the first block, occupation and having children at home
were entered as predictors. Job demands, job control and social support was
entered in the second block, followed by OC in the third block. In the fourth
block, next-day recovery was entered as a predictor of fatigue six months
later, and fatigue was entered as a predictor of next-day recovery.
In Study IV, the design was cross-sectional. The data set was partly the
same as in Studies II, but also included employees from another part of the
38
public health care sector (elderly care). Data from both self-ratings and a
health checkup from T1 were utilized. The data were analysed using a
person-oriented approach (cluster analysis) before being subjected to
variable-oriented analyses (logistic regression analyses, MANOVA and
MANCOVA). In contrast to variable-oriented approaches, in which
continuous variables in terms of means and variance are related to other
variables, a person-oriented approach allows assessment of differences in the
participating individuals’ configuration of responses to items of a factor
(Bergman, El-Khouri, & Magnusson, 2003). This means that instead of
looking at a group of individuals based on their total sum on an index or
their mean on a scale, their pattern of response on the scale is in focus
(Bergman et al., 2003). Individuals with similar response patterns are
grouped together, leading to the emergence of subgroups. These subgroups
are interpreted as mirroring underlying common categories, or types, with
typical characteristics.
Measuring health and ill health
In this thesis, health and ill health among women working in public health
care are in focus. However, the scientific study of health is complicated by
the variety of definitions and operationalizations of health that exist (Marks,
2000). Frequently, it is argued that health should be considered a separate
concept and not simply the opposite to disease/ill health (Sarafino, 2002).
Following this line of thought, health may include aspects such as the
subjective experience of health, well-being, positive functioning or coping
abilities. Practically, however, health has often been defined in line with the
biomedical model, by the absence of disease or lack of symptoms (Mellner,
2004).
In Study II, health is an essential concept since the study concerns the
effect of RWH and PE on many aspects of functioning. The importance of
assessing health as something more than a lack of symptoms and disease was
particularly important since previous interventions studies of reduced
working hours have suggested that the effect may be found in outcomes
related to subjective aspects of well-being and functioning rather than in the
prevention of ill health (Åkerstedt et al., 2001; Anttila et al., 2005). It was
also important since the intervention was set among a working population.
This may be considered a healthy population per se, thereby reducing the
variance in symptoms and ill health and providing a ceiling effect of
improvements in these areas. To account for the variation in the many
aspects of these concepts, in Study II, health and ill health were measured in
several ways (see below). In Studies II and IV, both self-ratings and
biological markers were used. Using data from both self-ratings and
biological markers allows for triangulation of the data (Breitmayer, Ayres, &
39
Knafl, 1993). This means using different methods to study the same
phenomena, thereby cross-validating the results against each other for
confirmation. This increases the reliability of the studies. When different
kinds of data point in the same direction, the risk of misinterpretation of the
data is reduced. Also, the use of different kinds of data may provide a fuller
picture of the phenomena under study (Breitmayer et al., 1993).
Physiological parameters
In Studies II and IV, physiological measures of health and ill health were
part of the assessment, along with self-ratings. Physiological measures are
often regarded as more objective than self-rated ones (Åkerstedt & Theorell,
2002). They are also important in providing information on possible
pathways between work conditions and health, ill health and symptoms.
Many physiological markers may also act as early warning signs of illness or
disease that are yet not perceivable or diagnosable (Gruenewald, Seeman,
Ryff, Karlamangla, & Singer, 2006). A disadvantage is that many biological
markers show seasonal and circadian, particularly diurnal, variability, which
needs to be considered in the planning of the studies (Garde, Hansen,
Skovgaard, & Christensen, 2000; Imai et al., 1996; Ockene et al., 2004; van
Anders, Hampson, & Watson, 2006). Besides being sensitive to when the
measurements are taken, they are also sensitive to how they are taken. To
account for this in this thesis, health checkups followed a standardized
protocol. This involved sampling of blood followed by measurements of
waist-hip ratio (WHR) and measurements of blood pressure and heart rate
(supine position), repeated three times with five minutes of rest in between.
An average of the two last recordings was used in analyses. Blood samples
were collected between 7:30 and 10 a.m. and participants were instructed to
refrain from eating for 12 hours prior to the checkup. In addition, they were
asked to rise at least two hours before the checkup and, in the meantime,
refrain from consuming coffee and nicotine and to avoid intense mental or
physical activity. Moreover, in Study II which was a longitudinal study, only
data collected during the same season were used in the analyses. This was
done because seasonal variation is particularly pronounced in countries such
as Sweden, which is located far from the equator and subjected to large
variations in temperature and sunlight (Al-Tamer, Al-Hayali, & AlRamadhan, 2008).
In this thesis, both markers that are related to known risk factors (such as
high blood pressure, high levels of blood lipids and blood sugar, etc.) and
markers related to the stress and recovery processes (e.g. prolactin and
DHEAS) are included. These are described below.
40
Cardiovascular measures
Blood pressure and heart rate were assessed as markers of the function in the
cardiovascular system. Blood pressure reaches its highest levels when the
heart is contracting: this is the systolic blood pressure (SBT). When the heart
relaxes, the blood pressure reaches its lowest level, which is known as the
diastolic blood pressure (DBT). The magnitude of the blood pressure
depends on how forceful the heart contracts and on the resistance in the
vessels of the body. Blood pressure varies depending on activity. For
example, standing up requires higher pressure than sitting down, and running
requires higher pressure than walking. Prolonged exposure to high blood
pressure, which may result from heritage factors, overweight, stress or poor
health habits, may lead to increased blood pressure at rest, called chronic
hypertension. In this thesis, blood pressure was measured at rest, when blood
pressure is at its lowest.
Blood lipids
As part of everyday life, energy is mobilized by transporting blood lipids
such as cholesterol and triglycerides to the muscles. Cholesterol is also
needed in order to build cells, insulate around nerve cells and to produce sex
hormones like testosterone and oestrogen, and is transported in the blood by
proteins. Two of the most widely known transport proteins are low-density
lipoprotein (LDL), which carries the cholesterol to the blood vessels, and
high-density lipoprotein (HDL), which carries the cholesterol from the
vessels to the liver where it is broken down. From this follows that LDL has
been related to increased atherosclerosis, while HDL protects against it
(Slyper, 1994). Therefore, total cholesterol, LDL, HDL, triglycerides and a
ratio between LDL and HDL are of interest in evaluating changes in blood
lipids. Traditionally, genes, age, diet, smoking and physical activity levels
have been described as the most important factors affecting blood lipid
levels (Lussier-Cacan, Xhignesse, Kessling, Davignon, & Sing, 1999;
Unden, Krakau, Hogbom, & Romanus-Egerborg, 1995) but psychological
stress has also been shown to increase these levels (Brindley, McCann,
Niaura, Stoney, & Suarez, 1993; Dimsdale & Herd, 1982; Niaura, Stoney, &
Herbert, 1992). Some studies also indicate relationships between blood lipids
and sustained emotional arousal (Melamed, 1994) and between blood lipids
and work conditions such as effort-reward imbalance (Peter et al., 1998).
Although the mechanisms for the relationship between blood lipids and
stress are not yet fully known, it has been suggested that they are related to
the activation of the SAM system, including the elevation of catecholamines,
cortisol and blood pressure in response to a stressor (Stoney, Bausserman,
Niaura, Marcus, & Flynn, 1999). Therefore, blood lipids may be used both
41
as an indicator of cardiovascular disease risk and a mirror of energy
mobilization and stress reactivity.
Metabolic measures
Glucose (blood sugar) and glycated haemoglobin (HbA1c) are important
parts of the metabolic system. As with blood lipids, glucose and HbA1c have
been shown to increase in response to psychological stress (Netterstrøm,
Danborg, & Olesen, 1988; Schuck, 1998). They have also been found to be
elevated in burnout patients (Grossi, Perski, Evengard, Blomkvist, & OrthGomer, 2003). This is related to the function of both cortisol and adrenaline:
while cortisol stimulates the production and storage of glucose in the liver,
adrenaline stimulates the breakdown and release of glucose from the liver.
While glucose levels are relatively instable (but within a very limited range)
and are affected by a number of immediate factors, particularly food intake,
HbA1c mirrors the average glucose levels during the previous few weeks
(Netterstrøm, 2000). Since HbA1c is not affected by food intake,
menstruation cycle variations, physical activity levels or body position
(although it has been related to high age, high weight, coffee and alcohol
intake and smoking) (Björntorp, 1996; Netterstrøm & Sjol, 1991) it is
relatively easy to assess.
Another indicator of metabolic functioning is the waist-hip ratio (WHR).
A high WHR (above 0.8 for women and above 1.0 for men) has been related
to increased risk for cardiovascular disease, diabetes and overweight (de
Koning, Merchant, Pogue, & Anand, 2007).
Endocrine measures
The neuroendocrine systems have both anabolic and catabolic effects.
Catabolic refers to the destructive metabolic process involving energy
mobilization and the conversion of substances into metabolites. Anabolic
effects refer to the opposite functioning: the synthesis of proteins and other
substances that help rebuild and replenish our bodily systems. In the wellfunctioning organism, these two complementary parts are in balance.
However, the balance may be disturbed if the organism is put under
prolonged pressure, e.g. long-term stress, so that the concentration of
catabolic hormones such as prolactin and cortisol increases and that of
growth hormones and sex hormones decreases.
DHEAS (dehydroepiandrosterone sulfate) is a form of the steroid
hormone DHEA (dehydroepiandrosterone), which is a precursor of both
male and female sex hormones (including testosterone and oestrogen)
(Buvat, 2003; Leowattana, 2004). In this thesis, DHEAS was chosen over
DHEA since DHEAS has a longer half-life (8-11 hours compared to 30-60
minutes), which means that it is less sensitive to acute effects (Leowattana,
2004). Both DHEA and DHEAS are believed to have general anabolic
effects (Buvat, 2003). In this thesis, DHEAS is assessed as a stress-sensitive
42
marker of the functioning in the anabolic system, as it is a functional
antagonist of cortisol. Some studies have indicated that high levels of
DHEAS have been related to fewer mobility limitations and better cognitive
function, particularly among women (Glei, Goldman, Weinstein, & Liu,
2004), although this result has failed to be replicated in other studies
(Goldman & Glei, 2007). Low levels of DHEAS have been associated with
perceived stress (Goldman, Glei, Seplaki, Liu, & Weinstein, 2005) and
DHEAS in combination with high levels of catabolic markers, e.g. HbA1c, is
associated with increased risk of cardiovascular disease (Alexandersen,
Haarbo, & Christiansen, 1996). DHEAS has also been related to changes in
the work environment. In one study, levels of DHEAS increased in
concordance with a worsening of the psychosocial work environment
(Netterstrøm & Hansen, 2000).
Prolactin is a peptide that modulates the activity and the receptor
sensibility in the dopamine and the serotonin system and is well known for
its role in lactation in women (M. E. Freeman et al., 2000). However, it has
also been related to psychosocial processes and stress (Armario, Marti,
Molina, de Pablo, & Valdes, 1996; Biondi & Picardi, 1999; M. E. Freeman
et al., 2000). On the behavioural level, prolactin concentrations have been
associated with depression, lack of interest, decreased libido and irritability
(Theorell, 2000). In association with job characteristics, high levels of
prolactin have been related to high emotional strain (Ohlson, Soderfeldt,
Soderfeldt, Jones, & Theorell, 2001). It has been suggested that high levels
of prolactin are particularly related to stress responses characterized by
hopelessness or powerlessness (Drago et al., 1989).
Allostatic Load
In Study IV, a composite measure was computed including parameters from
multiple regulatory systems (Seeman, Singer et al., 1997). This was done to
assess cumulative biological dysregulation, such as allostatic load (AL). This
may reduce uncertainties associated with the analysis of each biological
marker separately. To date, the operationalization of AL differs between
studies, depending on the type and number of biomarkers available
(Gruenewald et al, 2006; McEwen & Seeman, 1999; Seeman, Singer et al.,
1997; Seeman et al., 2001; Seeman et al., 2004). In Study IV, the following
parameters were included (for a description of each measure, see above):
heart rate and systolic and diastolic blood pressure (measures of
cardiovascular activity); HDL, LDL, LDL/HDL ratio and total cholesterol
(blood lipids associated with increased risk of atherosclerosis and
cardiovascular disease) and triglycerides (measures of fat deposits; high
values are associated with diabetes and overweight); serum DHEAS (a
functional HPA axis antagonist); glucose and HbA1C (metabolic measures);
prolactin (sensitive to sleep and stress) (Armario et al., 1996; M. E. Freeman,
Kanyicska, Lerant, & Nagy, 2000) and WHR (reflects adipose tissue
43
deposition and metabolism). Using empirical cut-points (Crimmins,
Johnston, Hayward, & Seeman, 2003; Karlamangla, Singer, McEwen, Rowe,
& Seeman, 2002; Seeman, McEwen, Singer, Albert, & Rowe, 1997;
Seeman, Singer et al., 1997; Seeman et al., 2004) and observed values (that
is including those on medication potentially affecting one or more of the
parameters), the participants were categorized into quartiles for each of the
13 parameters. The number of parameters for which the individual had a
value in the highest risk quartile was added, and the upper quartile of the AL
index was calculated to form a high AL group (for all parameters except for
HDL and DHEAS, the top quartile equals highest risk). Means, standard
deviations and cut-points can be found in Table 1. A quartile distribution of
biological parameters allows for the identification of individuals with higher
activity in their biological systems and an increased risk for future ill health.
This way of summarizing the data has yielded results similar to those yielded
by other ways for various health-related outcomes (Seeman, Singer et al.,
1997), and a recent study recommended this method for the cross-sectional
analysis of AL (Karlamangla, Singer, & Seeman, 2006).
Table 1. Allostatic load calculations: Criterion cut-points, means and standard
deviations for individual biological components for the three cluster profiles of
recovery
Measure
Allostatic load
Controlled for age
Systolic blood
pressure
Diastolic blood
pressure
Heart rate
Waist-hip ratio
Total cholesterol
Triglycerides
High-density
lipoprotein (HDL)
Low-density
lipoprotein (LDL)
LDL/HDL ratio
Glucose
Glycated haemoglobin (HbA1C)
Prolactin
DHEAS
44
75%
Cutpoint
≤ 5.0
Recovered
n =108
M (SD)
3.38 (2.51)
3.20
Nonrecovered
n= 51
M (SD)
2.84 (2.61)
3.11
Fatigued
N = 82
M (SD)
Total
N= 241
M (SD)
3.88 (2.57)
3.99
3.43 (2.57)
≤ 127.0
117.4 (17.5)
113.8 (17.6)
115.4 (19.3)
115.9 (18.1)
≤ 87.5
≤ 69.3
≤ .87
≤ 5.80
≤ 1.20
80.8 (11.8)
64.6 (8.9)
.82 (.07)
5.12 (.96)
.95 (.42)
77.8 (11.6)
61.9 (8.4)
80 (.08)
4.99 (1.04)
.94 (.48)
78.0 (12.6)
66.0 (9.2)
82 (.07)
5.20 (1.00)
1.02 (.48)
79.2 (12.1)
64.5 (9.0)
82 (.07)
5.12 (0.99)
.97 (0.46)
≥ 1.54
1.81 (.36)
1.73 (.31)
1.73 (.40)
1.76 (.36)
≤ 3.50
≤ 2.10
≤ 5.50
2.89 (.82)
1.67 (.60)
5.07 (.41)
2.82 (.93)
1.70 (.71)
4.95 (.46)
3.02 (.80)
1.83 (.65)
5.05 (.44)
2.92 (0.84)
1.73 (0.65)
5.03 (0.44)
≤ 4.60
≤ 11.0
≥ 2.50
4.39 (.29)
7.99 (4.14)
3.95 (1.95)
4.38 (.31)
8.62 (3.16)
4.61 (2.55)
4.45 (.35)
8.71 (4.20)
3.91 (1.79)
4.41 (0.31)
8.37 (3.97)
4.07 (2.05)
Self-ratings
One of the most frequently used measures of health and ill health in relation
to work is self-ratings (Hurrell, Nelson, & Simmons, 1998). These have the
advantage of being relatively easily distributed, non-invasive and able to
assess aspects such as general well-being and quality of life that are not
easily measured by ―objective‖ measures. Often, getting a picture of an
individual’s perception of a situation (e.g. perceived work situation or
perceived health) is at least as important as getting the objective picture, not
least since it is the individual’s subjective experience of a situation that to a
large extent governs his or hers responses to that situation. The subjectivity
of self-ratings also has some disadvantages that may bias the results. For
example, self-ratings are known to be affected by social desirability (giving
the answer one believes is the ―correct‖ one) and negative affectivity (a
general tendency to perceive things negatively) (Hurrell et al., 1998; Watson
& Pennebaker, 1989). These problems are particularly pronounced when
both exposure and outcome are measured using self-ratings, since they may
lead to spurious relationships (Hurrell et al., 1998).
Lack of recovery and fatigue
Assessment of lack of recovery from work and work-related fatigue has
often been done using an index including both items related to recovery and
items related to fatigue. In this thesis, except in Study I, fatigue and lack of
recovery were assessed using the eight-item ―Recovery from work scale‖
(Aronsson et al., 2003; Gustafsson, Lindfors, Aronsson, & Lundberg, 2006).
This scale includes items assessing general levels of fatigue during and
directly after the workday (e.g. ―I feel tired during work‖, ―I feel mentally
exhausted after the workday‖), one item assessing sleep difficulties and four
items concerning recovery from work after different lengths of time off
work, e.g. after a night’s sleep, in the morning before work, after a weekend,
and after a vacation (e.g. ―Generally, I feel refreshed and recovered by the
time my workday begins‖, ―Generally, I feel refreshed and recovered when I
am back at work after a weekend off‖). Respondents were asked to indicate
their overall level of recovery and fatigue in a five-point response format
with never and very often as endpoints. The items for each subscale were
added so that high scores indicated poor recovery/high fatigue. In Study III,
modified versions of the recovery and fatigue subscales were used. From the
fatigue scale, the item measuring sleep difficulties was omitted to avoid an
overlap with the overcommitment scale used in the same study. The revised
recovery scale included two of the four recovery items, namely those
focusing on recovery between workdays. This was done to simplify the
interpretation of the relationships between fatigue and recovery over time, by
focusing on an experience relating to approximately the same time period for
45
both fatigue and recovery. In Study IV, all eight recovery and fatigue items
were used in the cluster analyses.
Study I, which utilized data from a general work environment assessment,
assessed a factor labelled fatigue through three items: disturbed sleep,
tiredness after work and inability to stop thinking about work-related issues
during one’s free time. All items were rated along a six-point response
format with low and high as endpoints. Scores on both items were added to
high scores indicating more fatigue. From this follows that the
operationalization of fatigue differs somewhat between the studies: the
narrowest definition including only mental and physical fatigue during or
after a workday is used in Study III, while the widest definition is used in
Study I.
Overcommitment
In measuring OC, the motivational pattern characterized by excessive workrelated commitment and a high need for approval, the six-item subscale of
the effort-reward instrument has been widely used (Siegrist et al., 2004).
Five of the six items on the scale focus on one core notion of the concept:
the inability to withdraw from work obligations. The sixth item measures
impatience/irritability. In Study III, OC was used to assess perseverative
cognition relating to work. Responses were given in a four-point response
format and items were added to form an overcommitment index.
Physical activity
The level of physical activity was assessed through two items: Overall
physical activity (exemplified in the questionnaire as walking, biking,
household chores, gardening, playing with children) and physical exercise
(exemplified as aerobics, running and swimming). This was based on the
general recommendations for physical activity and exercise (Jansson, 2003).
The respondents were asked to rate how much time on average they spent on
physical activity and physical exercise, respectively, during a normal week.
Ratings were made on a four-point scale ranging from Less than one hour a
week or No activity at all (1) to 5-6 hours a week or More than one hour a
day (4).
Upper extremity disorder
UED was assessed using a symptom report including three items covering
pain in the neck or shoulder area, pain in arms or elbows, and pain in wrists,
hands or fingers, following previous research (Bongers et al., 2002;
Kuorinka et al., 1987). For each item, respondents were asked to indicate
whether they suffered from such health problems. Sum scores were
computed and ranged from 0 to 3, with high scores indicating more
symptoms. In Study I, the UED index was also used to categorize
individuals into different groups, those with and those without UED.
46
General symptoms
In Study I and II, symptom reports were used and from these, indices of
general symptoms were computed. In Study I, the symptom report included
five items (heartburn and stomach pain, headache, chest pains, colds and
skin problems) and in Study II, a modified version of the QPSNordic was
used, including nine common symptoms (heartburn, nausea, stomach ache,
palpitations, coughs, colds, headaches, fatigue and sleep disturbances)
(Dallner et al., 2000). In both reports, respondents were asked to indicate
whether they had experienced a symptom during the past six months. Sum
scores were computed, with high scores indicating more symptoms. Forming
an overall symptom report may provide an indicator of the total ―load‖ of
symptoms. It also helps to keep down the number of statistical tests in the
analyses compared to doing separate analyses for each symptom.
Self-rated health
One straightforward and commonly used way to asses health is to simply ask
people to rate how they perceive their overall health (Manderbacka,
Lahelma, & Martikainen, 1998; Miilunpalo, Vuori, Oja, Pasanen, &
Urponen, 1997). This has been suggested to capture an individual’s overall
perception of health, including biological, psychological and social health
dimensions (Fylkesnes & Forde, 1992; Manderbacka, 1998) such as general
health status, sleep quality, self-esteem, social support, sense of coherence,
clinical health ratings, chronic physical and emotional problems and stress
(Goldman, Glei, & Chang, 2004; Hasson, Arnetz, Theorell, & Anderberg,
2006; Idler & Benyamini, 1997). Often, this is done in a single-item format
(Burström & Fredlund, 2001; Fylkesnes & Forde, 1992; Goldman et al.,
2004; Idler & Benyamini, 1997; Miilunpalo et al., 1997). In this thesis
(Study II), self-rated health was assessed using a single-item question, in
which respondents were asked to rate their current health status compared to
other individuals of the same age. Ratings were made on a five-point scale
ranging from Very good (1) to Very poor (5) (Eriksson, Unden, & Elofsson,
2001).
Work ability
Another aspect of health is the individual’s work ability. Like self-rated
health, this is a general rather than specific measure of health. It includes
aspects such as the ability of the worker to perform at work with respect to
factors associated with work, such as job demands, ergonomics and
supervisor behaviour as well as individual resources including health,
competence and motivation (Ilmarinen et al., 1991; Ilmarinen, Tuomi, &
Seitsamo, 2005; Tuomi & Oja, 1998). Since work ability decreases with age,
it has been extensively studied in relation to aging workers to investigate the
sustainability of working life, but studies have shown that it is also relevant
47
for younger workers (Torgén, 2005). It is also related to sickness absence,
which in Sweden, like in most Western countries, is defined not just as the
presence or absence of disease, but as an individual’s ability to perform his
or hers work duties, that is by relating the symptoms to how it affects one’s
work capacity and work ability (Tengland, 2006). As such, self-rated work
ability is highly correlated with future sickness absence (Kujala et al., 2006).
Work ability is part of the assessment in Study II. It was measured using a
single item adopted from the Work Ability Index (Dallner, 1999; Dallner et
al., 2000; Ilmarinen, 2007; Tuomi & Oja, 1998). Respondents were asked to
rate their current work ability as compared to their work ability at its best on
a ten-point scale ranging from Completely lacking work ability (1) to Work
ability at its best (10).
Work-related measures
Physical work characteristics
Physical work characteristics were assessed in Study I. As described earlier,
dentistry presents a very demanding physical work environment due to the
specific work situation. This includes strenuous and/or fixed postures for
extended periods of time, fine-tuned yet forceful movements and exposure to
vibration and noise. In the assessment, physical work characteristics were
divided into physical work environment and physical load. Physical work
environment was measured with five items covering computerized work,
lighting, indoor climate and exposure to two types of noise. Physical load
was measured with four items including monotonous movements with the
hands or arms, painful or strenuous work positions, heavy lifting and
sedentary work. These items cover factors associated with an increased risk
for work-related disorders (Arbetsmiljöverket [Swedish Work Environment
Authority], 2004). All these items were rated along a six-point scale ranging
from All the time to Never. For both measures, additive indices were
calculated with high scores indicating poor conditions.
Psychosocial work characteristics
As described in the introduction, a number of psychosocial work factors are
known to influence individual health and functioning. Since different data
sets were used in Study I than in Studies II-IV, the measures in Study I differ
from those analysed in the other studies. In Study I, psychosocial work
characteristics were examined using ten items rated along a six-point scale
with Yes, absolutely and No, not at all as endpoints. An initial data reduction
was performed resulting in three components: 1) support (5 items), 2)
influence at work (3 items), and 3) work-related worries (2 items). Additive
48
indices were calculated for all three measures. For support and influence at
work, low scores indicate poor conditions. For work-related worries, low
scores indicate less worry.
In Studies II and III, psychosocial work characteristics were covered by
three factors: job control (2 items), job demands (5 items) and social support
(6 items) (Karasek, 1979; Karasek & Theorell, 1990; Schreurs & Taris,
1998). All items were rated along a four-point scale which ranged from No,
almost never (1) to Yes, very often (4) for all factors but social support that
ranged from No, completely disagree (1) to Yes, completely agree (4). The
job demand-control model postulates that two characteristics of a job are
particularly important as a source of job stress: psychological job control and
job control, or decision latitude. While job demands are relate to workload,
job control involves the employee’s ability to control his own activities and
skill usage (Karasek & Theorell, 1990). The job demand-control indexes
have been used extensively during the recent decades and have been related
to several ill health factors, including increased risk for cardiovascular
disease (Belkic, Landsbergis, Schnall, & Baker, 2004) and MSD (Bongers et
al., 2002). Social support has also been suggested as an important factor in
the stress-strain relationship (S. Cohen & Wills, 1985). For example, social
support has been found to reduce the strains experienced, mitigate perceived
stressors and moderate the stress-strain relationship (Viswesvaran, Sanchez,
& Fisher, 1999). As suggested by previous research (Schreurs & Taris,
1998), the three factors were analysed separately.
Work-home interference
Work-home interference (WHI), that is, whether working life interferes with
home life, was included in Study II and assessed using two items (Frone,
Russell, & Cooper, 1992). Both items were rated on a seven-point scale
ranging from Very seldom (1) to Very often (7) and the ratings were added
into a WHI-sum score, with high scores indicating high interference.
49
Summary of Empirical Studies
This thesis includes four studies. The designs of these studies and relevant
measures are presented in the Method section. Since the data sets coincide in
some of the studies, a general description of the data sets is given first,
followed by a brief description of the background, results and conclusions
for each of the four studies.
Participants
In Study I, 1,795 individuals of the 2,025 employees at a large dental health
company, including all personnel (both dental health workers and other
categories of personnel) who were on duty and present at their workplace
during the two weeks of data collection were invited to participate. Hence,
besides those who were temporarily absent, those on long-term absence
(e.g., parental leave and long-term sick leave) were excluded. The response
rate was 96%. For the purpose of the present study, only data from female
dental health workers, n = 945 were included (31% dentists, 12% dental
hygienists and 57% dental nurses). The average age of the respondents was
45.4 years (SD = 10.4) and the majority of the women, 70%, were employed
full-time.
In Study II, 197 employees at six workplaces in the dental health
organization described above were invited to participate in the three-wave
study, and 195 volunteered. Of the 177 women who completed all three
waves of data collection, blood samples were missing for six women. In
addition, physiological data from three diabetics and six pregnant women
were excluded. This means that for analysis of biomarkers, data from 162
women were available. For Study III, data from the second and third wave of
the data collection was utilized. 179 women participated in both waves, after
a dropout of 4.8% (due to change of jobs, parental leave and, in one case, a
declination to participate in the follow-up). Due to missing data on self-rated
next-day recovery or fatigue or any of the independent variables, the final
sample consisted of 160 women.
In Study IV, the data from the first wave of data collection from Study II
was extended to include participants from two different public health care
organizations in Stockholm, Sweden. 367 of the 390 persons invited to
participate volunteered. For the purposes of the present study, only data from
50
female employees (n = 312) were included. The final sample consisted of
241 women, after excluding those who were pregnant (n = 9), individuals
with known diabetes medulla (n = 7), those with missing data (n = 38) and
those with univariate outliers in biomarkers considered erroneous (n = 17).
There were no significant differences in demographic characteristics
between the women included in the final sample and the others.
Procedure
In Study I, questionnaire data were collected at 48 workplaces by their
occupational health company as part of an assessment of working conditions,
occupational hazards and employee health, initiated by the employer.
Participation was voluntary but was encouraged by the employer. To ensure
anonymity and confidentiality, all employees were asked to complete the
questionnaire individually and return it to a representative of the
occupational health company within two weeks. Thus, the employer had no
access to individual answers.
Since Studies II, III and IV are based on the same large data set, the same
procedure was applied in all three studies. Biomarkers and self-ratings in
questionnaires were obtained before any intervention took place (T1), and
six months (T2) and 12 months after the interventions (T3) to allow analyses
of changes between different points in time (Taris & Kompier, 2003). The
time lag between measurements was based on experiences from previous
studies (Anttila et al., 2005; Wergeland et al., 2003). Prior to each of the
three phases, the participants were given detailed oral and written
information about the project, ethical issues and procedures for the
measurements involved (questionnaire and a health checkup). The
questionnaire was completed at home and returned to the licensed nurse who
performed the health checkups (for a description of the protocol for these,
see Physiological parameters in the Method section).
Study I
By the very nature of the work, dentistry constitutes a work setting that is
both psychosocially and physically challenging and the prevalence of
musculoskeletal disorders is high. The aim of Study I was to investigate how
musculoskeletal disorders in the upper extremities (neck, shoulders, arms,
elbows, wrists, hands or fingers) (UED) are related to work characteristics,
fatigue and general health problems in a high-demand work. Moreover, since
dentistry involves different occupations a second aim was to investigate
differences in work characteristics, fatigue and general health problems in
relation to work position.
51
Of the 945 participants, 81% reported UED with no significant
differences between occupations. Women with UED reported significantly
worse physical work environment (p = .0001), higher physical load (p =
.0001) and more work-related worries (p = .040), and less influence at work
(p = .0001) and poorer support (p = .003) than did employees without UED.
They also reported more fatigue (p = .0001) and more general health
problems (p = .0001) than did women without UED. Significant differences
were also found between dentists and nurses in work conditions (p = .0001)
and health problems (p = .0001). Dentists reported significantly higher
physical load than did nurses (p = .0001) and higher scores on fatigue than
did the other two groups of employees (p = .0001), whereas nurses reported
significantly lower scores on influence at work (p = .0001).
A hierarchical regression analysis showed that in predicting numbers of
UED, a higher physical load was the most important predictor, followed by
more general health problems, higher age and a poorer physical work
environment. Neither marital status, position, number of years performing
current tasks, fatigue nor the psychosocial work characteristics made a
unique contribution to the model. The full model explained 18% of the
variance in UED.
The authors conclude that the prevalence of UED in this sample (81%)
was extremely high, particularly since the workplaces met all modern
ergonomic and physical work environment requirements. It was also
concluded that although all employees objectively worked in the same
environment, those reporting UED regarded their physical and psychosocial
working conditions as poorer compared to their colleagues who did not
report UED. The differences between occupational groups were expected:
dentists and dental hygienists, who spend more time in strenuous positions
doing monotonous, fine-tuned movements, reported higher physical load and
dental nurses, who have their workday planned by the dentist, reported less
influence at work. In predicting UED, physical load was, not surprisingly,
the most important predictor. More surprisingly, psychosocial work
environment did not contribute to the prediction at all. Also, 82% of the
variance in UED was not explained by the investigated factors. The authors
suggest that in dentistry the effects of psychosocial work conditions are
overshadowed by the high physical load. In sum, the study shows that
female dental health care workers are at risk of developing musculoskeletal
disorders and are therefore likely to benefit from additional improvements to
the work environment, targeted prevention and intervention aimed at
reducing these risks.
52
Study II
As shown in Study I and in previous studies, even when ergonomic
standards are high, many employees in dentistry report UED and high
physical and psychological demands. To improve health and prevent
decreased work ability and sickness absence, workplace interventions that
improve employee health are therefore important, from both an individual
and an organizational perspective. Reducing exposure by reducing work
hours, or increasing tolerance by increasing physical exercise, are two
possible interventions. The aim of Study II was to examine the health-related
effects of two worksite interventions, physical exercise (PE) and reduced
working hours (RWH). A reference group (R), for which no intervention was
carried out, was also included. In both intervention groups, 2.5 hours of
work/week were allocated to intervention. In the RWH group, full-time
weekly hours were reduced from 40 hours/week to 37.5 hours/week with no
expectations on how to spend the extra free time. In the PE group, the 2.5
hours, divided into two occasions, were allocated to a free choice of physical
exercise as long as it was of medium to high intensity, corresponding to 55%
to 89% of maximum heart rate. Hence, the intervention involved PE rather
than PA. The reasons for this were to decrease the variation in intensity
levels associated with letting the study participants make their on choices, to
be able to study effects related to cardiovascular capacity and to have an
appropriate intensity level considering the duration of the training (2.5
hours/week). To ensure proper implementation, all employees recorded in
writing the type of activity and the duration of each exercise session and
these written reports were checked weekly by a specifically assigned
employee. For employees working part time, the reduction of working hours
was less than 2.5 hours so that, instead of similarity in absolute numbers, the
reduction was similar in relative numbers. A great majority had either a
reduction of 2.5 hours (46%) or 2 hours (39%). All employees retained their
salaries. No additional personnel were employed and all workplaces were
expected to deliver full services throughout the study period. The PE group
included 62 women, the RWH group included 50 women and 65 served as
referents. The mean age for the whole sample was 46.6 years.
The results showed increased levels of physical exercise (pPE < .001; pRWH
< .001; pR < .001) in all groups, but the increase was significantly greater in
the physical exercise group than in the other two groups (p < .001). Physical
activity levels increased as well (pPE < .001; pRWH = .039; pR = .016). The
interaction effect was approaching significance (p = .077), with post hoc
analyses suggesting greatest increase in PA in the PE group. For blood
lipids, neuroendocrine markers and cardiovascular measures, no significant
time x group effects were found. However, there was a time effect showing
increased levels of blood lipids from T1 to T3 for all blood lipids but the
LDL/HDL ratio. Post hoc analyses showed increased levels of all blood
53
lipids in the R group and increased levels of total cholesterol and HDL in the
RWH group while only total cholesterol had increased significantly in the
PE group. Significant effects were also found for metabolic measures. For
glucose, there was a significant time x group effect (p = .04), with post hoc
analyses showing significant decreases in the PE group only (p = .036). A
significant interaction effect also emerged for WHR (p = .02), with post hoc
analyses revealing that WHR increased in the RWH group (p <.001). For
HbA1c, there was an effect of time showing decreased levels of HbA1c (p =
.03), but no interaction effect. Post hoc analyses showed a decrease in the PE
group that was approaching significance (p = .084).
For self-reports, no significant effects emerged for self-rated health, WHI,
lack of recovery or fatigue. For work ability, however, the time x group
effect (p = .01) was significant. Post hoc analyses showed that work ability
decreased in the R group (p = .005), while there were no significant changes
in the PE and the RWH groups. Similar results were found for general
symptoms (p = .063): the number of symptoms increased in the R group (p =
.006). For UED, the interaction effect was approaching significance (p =
.062), suggesting significant decreases in UED in the PE group only (p =
.012).
It was concluded that the greater increase in physical exercise in the PE
group suggests that the intervention was successful in implementing
increased physical activity. Taken together, Study II shows that RWH
increased levels of physical activity and exercise, and was related to positive
effects on HDL but also negative effects on total cholesterol and WHR.
When it was mandatory to spend the reduced working hours on physical
exercise, the increase in physical exercise was even greater and was
associated with positive effects on glucose and UED, but also with an
increase in total cholesterol. Hence, the effects seemed to differ between
interventions. In addition, work ability decreased and general symptoms
increased in the reference group, a pattern similar to findings from previous
studies (Pohjonen & Ranta, 2001). This means that beside some health
improvements in the intervention groups, a decline in health, or increase in
ill health, was found among referents but not in intervention groups. This
may suggest that part of the health benefits of workplace interventions may
be in terms of delaying or preventing negative effects otherwise found.
However, an overall decline in health is most likely to happen over a longer
period of time, implying that in order to find such effects, longer follow-up
periods would be needed. Somewhat surprisingly, no improvements were
found in either group in recovery from work.
It was also concluded that most interaction effects failed to reach
significance. This was discussed as resulting from the small effect sizes
often associated with workplace health interventions and the study of health
effects among a healthy population (Dishman et al., 1998; Wilson et al.,
1996), but also that the conditions may have been too similar, particularly
54
since levels of physical activity increased in all groups and since participants
were quite physically active to begin with. In sum, as a practical implication,
interventions involving a modest reduction in working hours seem to be
more effective when the time is spent on physical exercise, at least in terms
of physical health.
Study III
Psychosocial work conditions have been related to stress-related disorders,
and lack of recovery and fatigue have been suggested as a mediator in this
relationship. However, mere time for recovery, for example as follows from
a reduction in working hours, does not necessarily improve recovery. One
reason for this may be that factors such as worry and rumination may
prolong or sustain the physiological activation associated with a stress
reaction. The purpose of Study III was to investigate the relationships
between psychosocial work characteristics in terms of job demands, job
control and social support at work and perseverative cognitions related to
work in terms of overcommitment, and fatigue and next-day recovery among
women.
The results showed that overcommitment to work were a strong predictor
of poor next-day recovery from work and work-related fatigue among
women. More specifically, fatigue at T3 was predicted by having children at
home, high job demands, high OC and poor next-day recovery six months
earlier (42% of variance explained) while poor next-day recovery at T3 was
predicted by job demands and fatigue in the final model (explaining 31% of
the variance). OC was a significant predictor of poor next-day recovery only
when fatigue was not considered in the model.
It was concluded that perseverative cognitions relating to work, such as
overcommitment, may be an equally, or even more, important predictor of
next-day recovery and fatigue than are psychosocial work conditions. This is
interpreted in terms of adaptive and unadaptive process: even though job
demands may be considered a stressor, and may lead to stress reactions such
as fatigue after a workday, individuals may be able to cope with these
demands and stress reactions and recover, e.g. return to a pre-stress level
when the stressor has ended (e.g. after the workday). This would constitute
an adaptive stress-recovery process. If the individual, on the other hand, is
unable to withdraw from work cognitively and/or emotionally, his or her
ability to recover may be limited.
55
Study IV
In the allostatic load (AL) model, the importance of rest and recovery for
avoiding the harmful consequences associated with long-term stress
activation is evident. However, the concept of recovery from work stress has
not been directly investigated in relation to AL. Therefore, the aim of Study
IV was to investigate the relationships between self-rated recovery from
work stress and biological dysregulation load in terms of AL in employed
women.
All eight item from the recovery from work scale (Aronsson et al., 2003;
Gustafsson, et al., 2006), including both recovery and fatigue items, were
used in a cluster analysis. This produced three clusters denoted recovered,
non-recovered and fatigued, that are presented in Figure 1 in terms of the
deviation from total mean on each item of the recovery measure.
Figure 1. Deviation from total mean on self-rated recovery and fatigue for three
clusters with distinct recovery profiles (N =241).
Along with a recovered group consisting of 108 women with a pattern
suggesting overall better recovery and less fatigue than the other clusters,
two profiles with poorer recovery and more fatigue emerged. A cluster
denoted non-recovered, consisting of 51 women, showed a pattern
56
characterized by poor recovery from work, particularly in terms of long-term
recovery (weekends and vacations). Moreover, these women reported not
being thoroughly rested after sleep. The fatigued cluster, consisting of 82
women, was characterized by high levels of mental and physical fatigue after
work, frequent sleeping problems, and relatively poor recovery between
workdays. However, their long-term recovery was better than that of the
non-recovered cluster. In the recovered cluster, there were more dental
nurses (p = .002), older women (p = .013) and women working part-time (p
= .025) than in the other clusters.
The percentage of women belonging to the highest risk group for a
cumulative biological load (the top quartile of AL) is presented in Figure 2.
Though logistic regression analysis, the odds of being in the top quartile of
the AL measure were predicted.
Figure 2. Percentage of women belonging to the top quartile of AL for three clusters
with distinct recovery profiles.
In the full model, 17.7% of the variance in the dichotomized AL was
explained (Nagelkerke R2). Both age and cluster membership reliably
predicted the odds of high AL. Odds ratios (OR) indicated that along with
higher age, belonging to a fatigued group compared to a recovered group
increased the risk of belonging to the upper quartile of AL (OR 2.86).
Analyses of differences between cluster groups in separate biomarkers using
MANOVA and MANCOVA controlling for age showed that the groups did
not differ significantly in separate biomarkers. The results suggest that selfrated recovery and fatigue is related to a cumulative biological
dysregulation, but not necessarily to differences in individual biological
parameters. The risk of high AL was more pronounced among women
whose profiles were characterized by sleeping problems and mental and
physical fatigue, and to some extent poor recovery between workdays,
57
(fatigued profile) than when these characteristics were absent (the recovered
profile). Moreover, a third profile particularly characterized by poor longterm recovery emerged and hence, two profiles characterized by poor
recovery but differing in risk for AL were found. In sum, Study IV provides
support for a focus on cumulative load when investigating the biological
pathways of self-rated recovery from work stress. It also shows that recovery
is an important factor to consider in relation to biological cumulative
dysregulation, supporting previous findings suggesting that recovery may be
a pathway in the stress/ill health relationship.
58
Discussion
The main aim of this thesis was to investigate different aspects of health and
ill health in working women, with a specific focus on how efforts associated
with work need to be balanced with recovery and the time off work in order
to prevent ill health and promote health. Hence, the theoretical context was
stress theory. This suggests a very wide aim, and within this, this thesis
focuses on such aspects of health and ill health that are likely to be (at least)
partly work-related and associated with balance between effort and recovery
(e.g. stress-related). Moreover, the inclusion of both health and ill health in
the aim of the study reflects an effort to investigate factors associated both
with symptoms and risk-factors of disease (e.g. a negative aspect) and
positive aspects of human functioning. From this follows that the results are
interpreted with both prevention (of ill health) and promotion (of health) in
mind.
Interpretation of findings
As described in the introduction, work has frequently been related both to
positive aspects of health and functioning and to ill health and disease
(Barnett & Hyde, 2001; Bongers et al., 1993; Bongers et al., 2002; Johnson
& Hall, 1988; Klumb & Lampert, 2004; Niedhammer, Goldberg, Leclerc,
David, 1998; Niedhammer, Goldberg, Leclerc, Bugel et al., 1998; Reed et
al., 2006; Repetti et al., 1989; Theorell et al., 1998). While some factors
associated with ill health (e.g. UED) were investigated directly in this thesis,
the positive role of work that is pointed out in the Background section was
not. However, the results from the studies in this thesis may be interpreted
with both prevention of ill health and promotion of health in mind. In this
section, the findings from the studies are discussed in relation to the aim of
the thesis. First, the results are interpreted in terms of prevention of ill health
and promotion of health in general. Then the discussion focuses on
interpreting the findings in relation to recovery from work.
59
Promoting health and preventing ill health
In Study II, the preventive and promotive effects of two WHP initiatives
were investigated directly. The selection of type of WHP was guided by
stress theory and the effort to investigate effects on both ill health and health.
There were several reasons for choosing PE and RWH as interventions: both
were relevant to the theoretical framework of this project and both were
preferred by the employees (as expressed in an earlier workplace
assessment) and the employer. In addition, physical activity and reduced
working hours were discussed as possible interventions in several
organisations and in the media, motivating a scientific evaluation of these
initiatives. The results indicated that PA may have some positive effects in
terms of prevention of ill health, while the effects of RWH remain unclear.
Overall, PA was related to decreased glucose levels and decreased UED,
while RWH was related to increased levels of HDL, total cholesterol and
WHR. Moreover, in follow-up analyses of changes over time in each
intervention group separately, a significant decrease was also found in
systolic blood pressure in the PA group and a significant increase was found
in DHEAS in the RWH group (unpublished results). These results are
discussed in more detail below.
The effects of PA on glucose (and systolic blood pressure), that is
metabolic and cardiovascular measures, are a common finding in relation to
PA and PE (Eaton, 1992; Yang et al., 2008), and these effects are
particularly likely in an intervention that focuses on cardiovascular or
cardiorespiratory fitness. It shows that PE may be effective in prevention of
these risk-factors. However, the effect of PA on UED requires more
elaboration. In previous studies, some have reported positive effects of PA
on MSD (Oldervoll, Ro, Zwart, & Svebak, 2001; Proper, Koning, et al.,
2003; Sjögren et al., 2005) while others have found no such effects (Gerdle,
Brulin, Elert, Eliasson, & Granlund, 1995; Takala, Viikari-Juntura, &
Tynkkynen, 1994). This may be related to differences in kind of PA. Along
with cardiovascular fitness, PA and PE may also involve muscular strength
and endurance, coordination and musculoskeletal flexibility (Barnekow
Bergkvist, 2006). In a review of the effects of work-related physical exercise
on musculoskeletal health, it was concluded there was support for a positive
effect on neck-shoulder pain from specific training of the neck and
shoulders, involving strength or muscular endurance, among women
working with persistent but low physical load and lack of variation
(Barnekow Bergkvist, 2006). The result from Study II is somewhat at odds
with this, given that the training was non-specific (not explicitly targeting
the upper extremities) and did not require maximal muscular strength or
endurance training (the ability to perform repeated contractions over a
specific period of time). However, there are several possible mechanisms
that may explain the effect of PA on UED, drawing from the research on
60
mechanisms in the development of WRMSD. These mechanisms may
explain direct physiological effects of PA and PE on muscle function, but
also indirect effects related to changes in psychological and psychosocial
factors.
First, PA may help wash out lactic acid that has accumulated during
physical work (Baynard, Miller, & Fernhall, 2003). Second, it may provide
rest for the muscles, particularly the ―Cinderella‖ muscle units that are first
engaged in muscle activities (Hägg, 1991; Sjøgaard et al., 2000). Third, PA
may increase muscle strength or muscle endurance (Barnekow Bergkvist,
2006) or coordination and mobility, which is important for an efficient
power transference as well as for decreasing risk for overload (Hodges,
2000). Fourth, it may enhance memory and/or concentration and vigilance
during work, which in turn may decrease the risk of injury or wear due to
tiredness (Potter & Keeling, 2005). Fifth, PA during work hours may
facilitate short-term recovery by providing a break from the ordinary work
tasks (Schleifer et al., 2008). As such, PA may be equivalent to any activity
that constitutes a change in work task or work flow. Sixth, the fact that there
was no increase in perceived demands despite the fact that full productivity
was expected supports the possibility that PA is related to increased
resistance or increased resources, suggesting a moderation effect of PA in
the stress-distress relationship (Ensel & Lin, 2004). Seven, PA during work
hours may decrease hyperventilation and the associated disruption of the
acid-base equilibrium (Schleifer et al., 2002). This may either be a direct
effect of PA due to changes in briefing behaviour, or an indirect effect that
follows from having a break which may relieve acute stress reactions,
including hyperventilation. Eight, PA may decrease the experience of pain
due to an increased release of endorphins (Barnekow Bergkvist, 2006). Nine,
decrease in UED may steam from lowered levels of mental stress which in
turn may decrease muscle tension. This explanation is, however, less likely
in this study, since no decrease in perceived stress was found (analyses not
shown).
Unfortunately, the data presented in Study II are not sufficient for
drawing any firm conclusions regarding which of these explanations, if any,
that are the most important in explaining the effect of PA on UED: clarifying
these mechanisms is a task for future research. However, it is likely that the
mechanisms relating to having a break is more important than those focusing
on maximal strength, given that the type of work performed by the
participants in this study does not require maximal strength but involves
persistent, lower load levels. It may also be suggested that different
mechanisms may be relevant for different individuals, depending on their
choice of PE and on their muscular functioning and PA levels before the
intervention. For example, for an individual who was not physically active
before the intervention, benefits relating to increased PE in itself, such as
increased muscular strength and/or cardiovascular fitness, may be most
61
relevant. For an individual who was previously active, on the other hand,
doing PE during work hours (instead of, or in combination with, the previous
exercise regime) may assert effects in terms of providing rest for muscles
that are strained during work and by providing a break in the ordinary work
tasks, thereby decreasing stress and promoting short-term recovery.
Moreover, the mechanisms suggested above are not mutually exclusive and
are likely to interact, and they may be related both to direct physiological
effects of PE and indirect effects, as a mediator of psychological processes
affected by PE. Nevertheless, the results from Study II suggest that PA may
be related to prevention of ill health in terms of decreased UED and risk
factors for metabolic and cardiovascular disease. However, no effects in
terms of the promotion of health were found in the PE group. For example,
no changes were found in self-rated health, WHI or positive health
(unpublished results). Hence, previous findings suggesting positive effects of
PE on psychological factors such as subjective well-being (H.R. Eriksen et
al., 2002; Sjögren et al., 2006) were not replicated in Study II. This may be
related to differences in the assessment of well-being. It may also be related
to differences in pre-intervention PA levels. The women in Study II were
already relatively physical active before the intervention, and while the
physiological effects may steam from changes in intensity level (e.g.
increasing PE), psychological effects may be more pronounced in
individuals who were not previously physically active (e.g. changing from a
sedentary to a physical active life style).
The effects of RWH on health and ill health were more subtle than the
effect of PA. It may be suggested that RWH, if anything, may rather be
related to the promotion of health than the prevention of ill health. Although
the increase in HDL may be interpreted in relation to the cardiovascular and
metabolic systems, the concurrent increase in total cholesterol left the
LDL/HDL ratio unchanged. This makes the interpretation of the increase in
HDL as a reduction of risk factors for cardiovascular disease uncertain,
particularly since there also was an increase in WHR in the RWH group.
However, in the follow-up analyses of changes over time in the intervention
groups separately (analyses not shown), an increase in DHEAS was found in
the RWH. Both HDL and DHEAS have been suggested to be related to
increased anabolic activity (McEwen, 2000; McEwen & Seeman, 1999). As
such, the increased HDL and DHEAS could be markers of unspecific effects
on the processes that help build up organs and tissues, which work in
antagonism with the catabolic stress responses. This would make RWH more
relevant as health promotion than prevention ill health. However, the
interpretation is weakened both by the lack of solid evidence of positive
health effects of HDL and DHEAS and by the fact that while DHEAS
increased in the RWH group in separate ANOVA for the RWH group, the
interaction failed to reach significance in the repeated measures ANOVA
with comparisons between groups. Similarly, a time effect but no interaction
62
effect was found for HDL, which also increased in the reference group. An
increase in total cholesterol also contributes to the difficulties in drawing any
firm conclusions, as does the lack of effect on any of the self-ratings of
health and well-being. In sum, any anabolic effects of RWH remain
speculative.
Besides potentially differentiated effects of PA and RWH on the
prevention of ill health and the promotion of health, both may be related to a
different kind of positive effect. In the reference group, but not in the PA or
RWH group, self-rated work ability decreased and the number of general
symptoms increased during the time period. Similar results have been found
in a previous study, where a decrease in work ability was found among
referents but not among an intervention group (Pohjonen & Ranta, 2001).
From this follows that some of the effects of these WHP may rather be in
terms of a delay or reduction of future health problems. However, the change
in general symptoms was only a trend and should be interpreted with
caution. On the other hand, an overall decline in health is more likely to be
evident over a longer period of time, implying that in order to find more
robust effects, longer follow-up periods would be needed.
While Study II investigated the direct preventive and promotive effects of
WHP on health and ill health, the contributions of Studies I and III were
mainly to provide data on the relationships between work conditions and
health, ill health and recovery, from which promotive and preventive actions
can be suggested. The results from Study I clearly show that UED is a great
problem in dentistry, affecting over 80% of employed women. Even though
the point prevalence of UED is frequently higher among dental personnel
than the general working population (Alexopoulos et al., 2004; Finsen et al.,
1998; Myers & Myers, 2004; Åkesson et al., 1999), the prevalence found in
Study I is particularly high. This may follow from the study group, which
included only women, who often report more UED than men do
(Rundcrantz, 1991; Rundcrantz, Johnsson, & Moritz, 1991) and the long
tenure of the employees (mean tenure 15 years, unpublished results). Also, a
majority (70%) were working fulltime, that is 40 hours/week. This is more
than in other public health care professions in Sweden, in which fulltime
weekly work hours are usually 37 to 38 hours due to union agreements. The
relationship between UED and high physical workload was clear, despite the
fact that the workplace met all modern ergonomic requirements. This
suggests that having a good ergonomic environment may not be enough to
prevent UED, but rather that it may be necessary to implement other
initiatives. These are discussed further in the practical implications section of
this thesis. Another contribution from Study I is the inclusion of dental
nurses in the study. Most studies on dentistry focus on dentists and/or dental
hygienists despite the fact that a majority of dental personnel are dental
nurses (57% in Study I) (see for example (Craven, 2008; Finsen et al., 1998;
Rundcrantz, Johnsson, & Moritz, 1991). The results from Study I suggest
63
that in order to prevent ill health and promote health, differentiated
initiatives may be called for. Although the prevalence of UED was similar
among dental nurses and dentists/dental hygienists, they rated their work
environment and other symptoms differently. While dentists reported the
highest levels of physical load and fatigue, dental nurses reported the lowest
levels of influence at work.
The results from Study III suggest that in order to find effective
prevention of stress-related ill health, it is not only psychosocial work
conditions, including job demands, that need to be considered. Specifically,
being overcommitted to work as evident in an inability to stop thinking
about work after leaving for the day may have an even greater impact on
processes that are vital to sustained health than do conditions during work.
This does not contradict the vast amount of research showing that high job
demands, low job control and other job factors act as stressors and are
related to stress-related ill health (e.g. Belkic et al., 2004; Bongers et al.,
1993; Niedhammer, Goldberg, Leclerc, Bugel et al., 1998). However, it does
suggest that in the framework of stress theory, time off work is important to
consider. Even when the job situation leads to stress reactions, these may be
counteracted during time off work. Overcommitment to work may therefore
be particularly troubling in relation to recovery, and may act both as a
stressor in itself and by worsening the effect of job stressors by preventing
recovery after these stressors. As such, OC may both start an activation
period and/or prolong an activation period associated with previous
stressors.
Overcommitment may also be related to work conditions more directly.
Although most research on worry, rumination and overcommitment has
mainly focused on personality traits (Nolen-Hoeksema & Davis, 1999;
Siegrist, 1996), there is some evidence that factors in the environment may
increase worry as well. For example, uncertainty and unpredictability, which
have been suggested as core elements in psychosocial stress factors
(Sapolsky, 2004), have also been suggested as predictors of worry (Dugas,
Freeston, & Ladouceur, 1997). It may be argued that work factors that
increase uncertainty may also increase OC. Such factors may include unclear
work goals, poorly specified work tasks and lack of feedback on when work
is completed. The importance of these factors has been showed in recent
research investigating factors associated with work-related health (Hellgren,
Sverke, & Näswall, 2008). From this follows that interventions targeting
both individual and organizational factors may be motivated in the
prevention of OC and the promotion of recovery from work.
Health and ill health as related to recovery from work
In recent decades, the theoretical framework for stress research has expanded
to focus on sustained activation and lack of recovery for understanding
64
health consequences of demands in the workplace. Study IV shows that lack
of recovery, particularly in individuals with a pattern characterized by
fatigue and sleep difficulties, is related to an increased risk of allostatic load,
that is, a cumulative biological wear and tear. However, this association did
not show up in analyses of separate biomarkers. Since analyses of separate
biomarkers have been the most common way to investigate associations with
health and ill health, the relationship between lack of recovery and fatigue
and biological wear may have been missed. From this follows that taking a
multisystem approach may be more relevant than investigating separate
biomarkers in order to investigate the health consequences of lack of
recovery and fatigue. This is particularly true when prevention is of interest:
with longer follow-up periods, the AL may have turned into diseases and
turned prevention into rehabilitation.
In relation to the aim of this thesis, the result from Study IV suggest that
in order to promote health and prevent ill health, factors related to recovery
need to be considered. Some of these factors were investigated in Study III.
As described above, the main contribution of Study III was the relative
importance of overcommitment in contrast to psychosocial work conditions
such as high demands and job control. Previous studies relating psychosocial
work conditions to lack of recovery have not simultaneously considered
overcommitment. From Study III follows that in the promotion of health and
the prevention of ill health in the context of recovery, the ability to mentally
let go of work should be considered along with, for example, job demands.
Study III also untangled some of the confusion concerning the
relationship between fatigue and recovery. The relationship between
overcommitment and poor next-day recovery was mediated by fatigue and
vice versa. A conceptual model drawn from the result is presented in Figure
3 and shows how having children at home, high job demands, OC and
fatigue and next-day recovery may be interrelated. More specifically, it
shows that while all these factors predicts fatigue six months later, poor
next-day recovery is predicted directly only by job demands and fatigue. The
relationship between OC and poor next-day recovery six months later
(dotted line) is partly indirect, through the effect of OC on fatigue. Also, the
model shows that the relationship between OC and job demands and fatigue
six months later is partly mediated by poor-next day recovery, as suggested
by the decrease in Beta values for these factors in the regression models in
Study III. The results suggest a dual role for fatigue: both as an outcome of
stressors and lack of recovery, and as a precursor of lack of recovery (for
example, as a stress reaction). This is similar to the distinction between acute
and long-term fatigue (Beurskens et al., 2000). Hence, depending on the time
frame of the study, fatigue may be either a precursor of recovery (a stress
reaction) or a consequence of lack of recovery (a health consequence).
Separating the stress response from the recovery process and the
consequences of poor recovery is important not least from a preventive
65
perspective, since fatigue associated with the stress response and fatigue
associated with lack of recovery may call for different kinds of interventions.
As suggested in the model, fatigue and poor next-day recovery may have
mediating effects in their interrelations with job demand and OC. However,
they may also be considered moderators, in that an individual who is already
fatigued or have difficulties recovering between workdays may respond
differently to job demands and OC, thereby changing the relationship
between these factors and poor next-day recovery.
Figure 3. A conceptual model presenting how having children at home, high job
demands and OC are related to fatigue and poor next-day recovery, and their
interrelations.
The importance of OC in relation to fatigue and poor next-day recovery
from work may be one explanation for the lack of effect of RWH and PA on
recovery from work (Study II). Reduced working hours would
hypothetically increase the time for recovery. But, this would assume that
the hours not spent on work are instead spent on activities that promote
recovery. Previous research has shown that active non-work activities like
social and physical activities promote recovery while passive activities such
as watching TV may not. In fact, increasing time for sedentary behaviour
(including watching TV) may not only be insufficient in promoting recovery
but harmful in itself, according to recent research on sedentary behaviour
(Hu, Li, Colditz, Willett, & Manson, 2003; Sugiyama et al., 2008). While
type of non-work activity was not assessed in Study II, it may be suggested
that the result of RWH may differ depending on what type of non-work
activity the individual engages in. For example, if the RWH means replacing
66
paid work with non-paid household work or other duties, positive effects of
recovery are not to be expected. From this follows that with RWH
initiatives, it is up to the individual to decide how to spend the extra free
time, thereby having a great influence on the outcome of the intervention. In
all RWH initiatives to date, the employers have had no influence on how the
RWH is spent. Hence, the outcome of the intervention may depend on
factors that the employer does not have any influence over. This may make
RWH less appropriate as a WHP initiative.
While the lack of effect of RWH on recovery from work may be
dependent on what the RWH was replaced by, no simple explanation can be
offered for the lack of effect on recovery in the PA group. Previous research
has shown that physical activity promotes processes that are related to
recovery (Barnekow Bergkvist, 2006), although no studies have directly
investigated the effect of a PA WHP initiative on recovery. It is possible that
doing PA during work hours is stressful, particularly when expectations on
performance are maintained despite a decreased number of work hours
(Gerdle et al., 1995). However, no effects of perceived stress were found,
and perceived job demands did not increase (unpublished results). Another
explanation may be a ceiling effect for PA on recovery. The participants
were by no means sedentary before the intervention. With a mean level of
low-intensity physical activity corresponding to approximately 3-4 hours of
weekly physical activity before the intervention, the increase in PA may not
have a profound effect on recovery. More research is needed to learn about
dose-response effects of PA on recovery.
Study I showed that in dentistry, the prevalence of UED was extremely
high and that individuals with UED perceived their work environment as
significantly worse than their colleagues without UED did. They also
reported more work-related worries and more fatigue, including tiredness
after work, disturbed sleep and an inability to stop thinking about work.
Since this was a cross-sectional study, the direction of these relationships is
unknown, although results from previous prospective studies have shown
that a poor work environment increases the risk of UED (Bongers et al.,
2002; van den Heuvel et al., 2005). However, although there was a
relationship between having UED and a poor work environment and some
aspects of recovery, namely fatigue, and with work-related worries, neither
psychosocial work conditions, work-related worries or fatigue turned out to
be predictors of UED. In Study I, this was attributed to the physical work
situation in dentistry being so demanding that it overshadowed the acute
effects of the other factors on UED. Also, the full model only explained 18%
of the variance of UED. This suggests that factors other than those
investigated, for example heritage factors, health behaviours, correct
utilizing of ergonomical equipment, body awareness, etc. need to be
investigated to provide a fuller answer.
67
In Study I, there was a difference in fatigue between occupational groups,
with dentists reporting more fatigue than nurses. This may stem from
differences in the work situation. Dentist reported greater influence at work
than nurses did, which likely is a consequence of the fact that during work,
the dentist decides and plans the subsequent steps in the treatment and in
doing so, determines the tasks and work pace of the assisting dental nurse.
Although influence at work is generally considered a positive work
characteristic, it may also have some negative consequences. Being
responsible may increase mental stress, including an inability to stop
thinking about work (which was one item on the fatigue scale in Study I). In
combination with the higher physical load experienced by the dentists, the
higher level of fatigue among them is not surprising. However, the dental
hygienists also had high levels of influence at work but in contrast to the
dentists, showed lower levels of fatigue after work. Again, this may result
from differences in the work situation: while dentists decide and plan work
for a team, the dental hygienists usually decide and plan only their on work.
The additional responsibility of planning work for a colleague may act as a
stressor, or increase role overload, which has been reported as a stress factor
among supervisors (R. Clark & Smith, 1987).
Conceptual issues
The concept of recovery
As described in the introduction, the concept of recovery contains some
problematic aspects and lacks a common definition. Not at least, the same
word is used for both the process and the result, and for both the
physiological response and the subjective experience. Moreover, recovery is
related to different parts of the stress process in different definitions: to the
stress stimuli or stressors, the stress experience, the stress response and the
result, or experience, of the stress response (e.g. stress level, health
consequences), or to the whole process. This lack of precision in the use of
the term recovery is problematic and its clarity would probably improve if
different words were used for the different parts of the process.
Unfortunately, this lack of precision may be evident also in this thesis.
Although the term recovery, as stated in the introduction, in this case refers
to the experience of the stress response in relation to a stressor (a workday)
and the latency to recover (whether one feels recovered after a specific time
period), other parts of the process have not been consistently denoted. For
example, ―the recovery process‖ is discussed in Study IV, referring to the
whole process. Also, inconsistencies may appear when referring to previous
studies, since their definition of recovery may differ. In this thesis, no effort
will be made to present new denotations for the different parts of the
68
recovery process. However, it is stressed that in studies of recovery (that is,
whatever part of the process it may refer to), it should be clearly stated what
part it refers to. Special care should also be taken to ensure that the
theoretical definition is in accordance with the empirical definition (the
operationalization).
A model of recovery
Drawing on the discussion of some of problematical aspects of the concept,
previous research and the results from this thesis, a hypothetical model of the
recovery from work process is presented in Figure 4. In this model, recovery
(that is, the sustained level of arousal (or fatigue) including both the stress
response and the subjective experience a period of time after the removal of
the stressor) is suggest to be determined by at least four parts: 1) the type,
intensity and experience of the stressor (or stimuli); 2) the stress response
and the experience of this response, e.g., fatigue, that is reactivity; 3) the
time allowed for the recovery process (e.g., time between shifts or time off
work); and 4) qualitative aspects that facilitate or impede the process. Hence,
the first two are related to the activation (stress) phase, and two to the
counteracting recuperation phase. The recovery process may be defined as
having ended either a) when the stress reactions are reversed b) after a
specific time period or c) when vigour is achieved. These parts are discussed
more thoroughly below.
Figure 4. A conceptual model of the recovery process starting with the stress
reaction, followed by recovery and supercompensation.
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In the first part of the model it is stated that a number of factors may act
as stressors that may lead to a need for recovery. Work-related factors acting
as stressors that have been shown to increase the need for recovery include
high job demands and low job control (Sluiter et al., 2003; Sonnentag &
Kruel, 2006), high job involvement (Sonnentag & Kruel, 2006) and high
number of hours worked (Jansen, Kant et al., 2003). However, very few
stressors (e.g. only physiological stressors such as extreme heat or cold or
pain) have the capacity to always inflict a stress response. Instead, it is
widely accepted that it is the individual’s appraisal of the stressors as either
threatening or challenging that determines his or her reaction to the situation.
This will determine the individual’s experience of the situation as stressful or
not. The individual’s response to the stressor constitutes the second part of
the model. This may be determined by predispositions such as the reactivity
of the stress systems, the individual’s appraisal of the stressor and the
expectancy he or she has on how he or she will be able to respond to the
stressor.
The second part of the model includes both the type of reactivity
(different kind of stress responses such as increased heart rate, muscular
tension and experience of fatigue and discomfort) and the intensity of the
response (how much the individual reacts). It also includes the individual’s
experience of the response. From these two parts of the model, it is implied
that the need for recovery varies with the intensity of the stressor and the
stress reaction, e.g. that more recovery is needed to return to a pre-stressor
level after an intense stressor and/or stress reaction than after a less intense
one. This seems to be the underlying assumption in most studies of recovery,
in which most analyses assume linear relationships. The second part also
includes the notion that the stress response may be delayed, remain high or
even increase after the stressor is removed. This is a consequence of stress
hormones that do not immediately disappear from the blood after the
removal of the stressor. For example, the half life of cortisol is about one
hour (Barton, Horan, Clague, & Rose, 1999). The stress response may also
be sustained for other reasons, including cognitive and emotional processes.
These are discussed in the fourth part of the model.
The third part of the model concerns the time during which recovery from
work takes place. This dimension is generally included in definitions of
recovery. However, the actual amount of time (e.g. minutes, days, weeks,
etc.) needed for recovery is, with some important exceptions (Sluiter et al.,
2000), seldom discussed. Also, often, no factors other than the passage of
time are considered. Instead, it seems that an underlying assumption is often
that recovery is a function of time alone, as in the Effort-Recovery model
(Meijman & Mulder, 1998). From this follows that with adequate time
between work shifts or other effort expenditures, recovery is assumed to
occur automatically. This makes recovery a passive process and may be a
more relevant view if recovery is discussed solely from a physiological
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perspective. However, if recovery is discussed from a biopsychosocial
perspective, there is evidence suggesting that recovery is an active process
that is affected by different activities, behaviours and individual
predispositions. This constitutes the fourth part of the model. Among factors
believed to intervene with the recovery process (either facilitate or impede it)
is doing work-related activities during off-job time (impedes recovery)
(Sonnentag & Zijlstra, 2006; Zijlstra & Sonnentag, 2006), worrying or
ruminating (impedes recovery) (Pravettoni et al., 2007; Sonnentag et al.,
2008), doing active non-work activities such as exercise and creative and
social activities (facilitates recovery) (Rook & Zijlstra, 2006; Sonnentag,
2001; Winwood et al., 2007) and being physically fit (facilitates recovery)
(Traustadottir et al., 2004).
It is also possible that different kinds of activities affect recovery
differently depending on what kind of activity caused the need for recovery.
In sport psychology, this is known as the matching principle of recovery
(Kenttä & Hassmen, 1998). This means that different kinds of loads give rise
to different kinds of recovery needs (as well as differences in magnitude).
For example, high physical energy output may require dietary supplements
to facilitate recovery, while mental and emotional load may require physical
activity or social support, rather than carbohydrates. From this follows that
some recovery activities may be appropriate under some circumstances
while others are not. Although this has not yet been investigated within work
psychology, related findings have been presented. A study that showed that
evening recovery experience predicted affect next morning also suggested
that different aspects of the recovery experience, that is detachment, mastery
and relaxation, may be related to different affects (Sonnentag et al., 2008).
While mastery, which was defined as challenging off-job experiences that
offer opportunities for learning and success, was related to positive
activation (e.g. feeling alert, strong and interested), relaxation was related to
serenity (e.g. feeling calm, laid-back and placid). Low psychological
detachment from work was related to negative activation (e.g. distressed,
upset and jittery) and fatigue. Although these results do not directly
investigate the matching principle (that is matching load with recovery), they
do suggest that specific recovery activities are related to different outcomes.
Another important factor affecting the recovery process, which is relevant
for recovery from a biopsychosocial perspective and the fourth part of the
model, is sleep quality and sleep disturbances (Rook & Zijlstra, 2006). Since
this thesis focuses on recovery from work in general and not sleep in
particular, the importance of sleep will be discussed briefly with no ambition
to cover the whole research area. The importance of poor sleep in the stressstrain relationship has been highlighted recently (Åkerstedt et al., 2002;
Åkerstedt, 2006). Although the full function of sleep is not known, anabolic
processes are plentiful during sleep, while catabolic processes are at their
lowest. As such, sleep is likely to be necessary for recovery. However,
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recovery is also likely to be necessary for sleep: high levels of stress impede
the sleep process and compromise the quality of sleep. Particular, worry over
the stressors of the next day is troublesome, as is rumination over past events
(Åkerstedt, 2006; Åkerstedt, Kecklund, & Axelsson, 2007; Cropley et al.,
2006; Ellis, Hampson, & Cropley, 2007). This is parallel to the findings in
Study III, whereby overcommitment was related to lack of recovery and
fatigue. The consequences of poor sleep, in combination with mental and
physical fatigue during and after the workday and not feeling fully rested
were also highlighted in Study IV, in which the group with this profile had a
higher risk of AL. Unfortunately, the results do not yield any information on
the temporal order of the items included in the profile, or their relative
importance. However, drawing on previous results concerning the health
consequences of poor sleep (Åkerstedt & Nilsson, 2003), the sleep
difficulties may very well be important in the relationship between the
fatigued profile and AL.
Generally, recovery is defined in relative rather than absolute terms, that
is, in relation to a baseline or pre-stressor level, a stressor, and/or a stress
response. This does not yield information on any absolute levels of recovery,
that is, whether the result of the process needs to reach a certain level for it
to be sufficient, regardless of the starting level. For example, is return to
baseline always necessary, if baseline is very low, or is return to baseline
always sufficient, even if baseline levels are very high? (As mentioned in the
introduction, baseline lacks in precision but in this case should be interpreted
as resting levels of, for example, blood pressure). This may very well be the
case. Keeping this in mind, the relative model fits most cases, and is the
approach taken in this model.
When does the recovery process end?
As described in the model, the termination of the process may be determined
by different factors. Three possible ways are suggested in this model, two
theoretically motivated (a and c in the model) and one motivated by practical
reasons. Of these, the first (a), in which recovery is said to be achieved when
arousal levels have returned to baseline or a pre-stressor level of functioning,
is cited most frequently in theoretical models. However, in empirical studies
and for practical reasons, the second option (b) is the most common: A
specific time period during which the recovery should have taken place is set
(e.g. after a night’s sleep), and the level of remaining arousal at that time is
assessed. This was the approach taken in this study, with participants being
asked to rate their level of recovery at different time points after the workday
had ended (assumed to equal the termination of work stressors). However,
choosing a meaningful time frame for the study of recovery is compromised
by the lack of information on the timing of recovery. As described in the
introduction, in the research of recovery from work, the time frame is often
same-day recovery, e.g. immediately after work or before sleep (Jansen et
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al., 2002; Sluiter et al., 2003). Longer time frames, such as the next morning
or after a weekend, are more seldom considered. An exception to this is
recovery after vacation, which has been investigated more thoroughly
(Etzion, 2003; Westman & Eden, 1997). The concentration on short time
frames may be unfortunate. If the assessment of the recovery process takes
place too soon after the termination of the stressor, the assessment will
contain information on the stress response rather than the efficiency of the
recovery process. Lack of same-day recovery may therefore be tapping stress
reactivity rather than recovery (e.g. a strong stress reaction that takes time to
subside). The value of this information from a health perspective may be
questioned: being fatigued or aroused in the proximity of the removal of the
stressor may be part of a natural and well-functioning stress-recovery
response. This may also contribute to the confusion concerning the
relationship between recovery and fatigue, since, as discussed in the
introduction and Study III and as is evident in the model, fatigue may very
well be both precursor to recovery and a consequence of lack of recovery.
Moreover, focusing on short time frames may miss associations relating to
not feeling fully rested after a night’s sleep, that is not being recovered
between workdays. This has previously been related to elevated cortisol
levels (Gustafsson et al., 2008) and has strong face validity: while it may be
reasonable to be fatigued after a workday, feeling refreshed again when it is
time for the next workday is of practical importance. Including more than
same-day recovery in the assessment of recovery from work was also
supported in an inspection of the frequency distribution for the fatigue and
recovery items from Study IV. This shows that although approximately half
of the participating women reported that they often or very often felt
fatigued (mentally and physically) during and after the workday, the
percentage of women reporting that they never or seldom were recovered
after a nights sleep and before the next workday was approximately 30%.
This dropped to 11% after a weekend and 3% after a vacation (unpublished
results). Although this gives an indication of the timeline for recovery from
work, data with more time points are needed to yield more information on
this process, including intense data from both self-ratings and physiological
measures. In addition, it is suggested that in future research, time frames of
recovery should be explicitly discussed and motivated given the aim of the
study, including both the theoretical and empirical definitions. Efforts should
also be made to distinguish between the reactivity phase and the recovery
phase. This means being certain of whether the assessment is done on the
up-slope or down-slope of the curve (see Figure 4).
Along with the ending of the recovery process being determined by a
return to baseline, or a specific time period, a third option for determining
the end of the recovery process is suggested: when vigour is achieved. This
is a direct parallel to what is expected as an end product of recovery in
sports. In the study of recovery within that discipline, recovery is an
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indispensable part of the training process. The sought-after result is not
merely a return to baseline but improved function, for example muscle
strength, a process labelled supercompensation (Fry, Morton, & Keast,
1992). Does a parallel to supercompensation in sports exist within recovery
from work? That is, does stress that is followed by sufficient recovery lead
not only to a return to baseline but to vigour, an improved functioning or
toughness? This may be dependent on what the individual is recovering
from. For example, if the individual is severely fatigued, or exhausted,
recovery may be interpreted as ―not being fatigued any longer‖, that is as a
return to a baseline. If the individual is merely tired or experiencing less
severe fatigue, recovering may include feeling alert or invigorated. This
could be a psychological parallel to super-compensation.
While the overall model of improved functioning after a stressor if
followed by sufficient recovery can be translated from sport psychology into
work psychology, the mechanism likely cannot. The mechanism for
supercompensation within sport is physiological, involving overtraining
(exceeding the load previously handled) and recovery, which leads to
adaptation by muscles, joints and cells (Kenttä, 2001). Similar physiological
mechanisms relevant for recovery from work and work stress may involve
physiological habituation, e.g. a reappearing stressor that does not evoke as
large a stress response as a novel stressors does, or adaptation, e.g. up- or
down-regulation of transmitter systems and/or receptors (H.R. Eriksen et al.,
1999). Moreover, psychological mechanisms may be important. Such
psychological mechanisms relevant to supercompensation may be found
within the literature of coping. For example, positive effects of successful
coping, defined as the reduction of uncertainty that follow from having a
positive outcome expectancy, are indicated (although not further discussed)
in the cognitive activation theory of stress (Ursin & Eriksen, 2004).
Moreover, although coping is frequently related to the regulation of distress
and the management of problems causing distress, it may also be related to
positive outcomes (Folkman & Moskowitz, 2000). Such outcomes may
include positive emotional experiences, including mastery, gain, happiness,
pride or relief (Folkman & Lazarus, 1985). In discussing the mechanism for
how coping may help individuals minimize or avoid the adverse effect of
health, Folkman and Moskowitz (2000) have suggested that one such
mechanism may be the experience of positive affect. The function of
positive affect has been described as involving decreased vigilance and a
change in information processing (Aspinwall, 1998), including a broadening
of an individual’s attentional focus and behavioural repertoire, which in turn
has been suggested to build social, intellectual and physical resources
(Fredrickson, 1998). Physiologically, positive emotions have been described
as undoing the after-effects of negative emotions (Fredrickson & Levenson,
1998; Fredrickson, Mancuso, Branigan, & Tugade, 2000), thereby buffering
against negative effects of stress. Future research needs to clarify the role of
74
recovery in relation to an analogue to supercompensation, coping, positive
affects and other aspects that may be related to improved functioning.
Methodological considerations
This section focuses on the some of the general methodological
considerations that are relevant in this thesis. Issues already discussed in the
Method section will not be repeated here. For those methodological
considerations discussed in each study, which can be found in the reprints at
the end of this thesis, only issues that need further elaboration will recur
here. Finally, considerations with direct relevance to the interpretation of the
findings are discussed in the Interpretation of findings section, earlier in the
discussion.
Intervention Research
Much is known about the basic relationships between work conditions and
health and ill health. That is, we are now able to say with some certainty that
factors such as high job demands, low job control, effort-reward imbalance,
lack of social support, etc., increase stress and are potentially harmful to
health. However, there are still relatively few intervention studies compared
to observational studies, despite good reasons for conducting them: 1)
intervention studies are usually more conclusive regarding causality and 2)
allow the investigation of implementation of workplace change, 3) positive
results are often more convincing, particularly to people outside the
scientific community and 4) are more easily disseminated from research to
practise and 5) by necessity involve collaboration between researchers and
workplaces, facilitating learning and communication on both sides
(Kristensen, 2005). One reason for the relative lack of intervention research
may very well be the inherent challenges in this kind of research, ranging
from difficulties in finding organizations willing to participate, high costs,
low participation rates when individuals are not approached dependent on
their own needs but the needs of the organization and high dropout rates due
to change of jobs, etc., to low power and lack of understanding for
conducting workplace interventions within the research community, etc.
Also, conducting workplace interventions of high methodological quality,
particularly randomized controlled trials (RCT), is often difficult. For
example, only rarely is it possible to use a blinding procedure and a placebo
condition and often, individual randomisation is not acceptable from an
organizational perspective (Shephard, 1996). Therefore, the use of
methodologies other than RCTs has been suggested as acceptable in
workplace intervention studies (Kristensen, 2005). These designs include
quasi-experimental designs, such as in Study II. However, not using RCT
75
still means that effort has to be put into overcoming some of the problems
stemming from not using experimental methodology. In Study II, the use of
a control group, the randomization on the organizational level and the
prospective design with evaluation against baseline measures are three things
that improve the study’s methodological quality (Kristensen, 2005).
One of the major problems with non-experimental designs is the lack of
control over confounding variables. Using a randomization procedure on the
organizational level minimizes the risk of confounding factors related to the
workplace, such as differences in leadership or motivation for change that
would make one work group more prone to participate than another. It is
also administratively convenient and may enhance subject compliance, help
avoid intervention contamination and be more easily translated into practice
(Raudenbush, 1997). However, this kind of randomization does not protect
against confounders associated with individual differences. When control
over confounders cannot be achieved by individual randomization, statistical
control is an option. However, controlling for too many confounders is not
only statistically challenging and may cause problems with interpretation,
but also decreases external validity. In Study II, differences between groups
at T1, before the intervention, were carefully investigated, and very few
significant differences (in fact, only one, higher perceived demands in the
RWH group) were found. Therefore, no confounding variables were
controlled for. Still, without an experimental design, there is no guarantee
that factors other than the intervention did not affect the outcome. Despite
these issues, intervention research provides a great opportunity to clarify
relationships between variables. But most of all, its high external validity
makes it more powerful in providing evidence of the effectiveness of
interventions and WHP to organizations. Along with providing an example
of possible interventions that may be used as guidelines for organizations,
this may contribute to bridging the gap between science and practise. Not
least, this is a powerful argument for doing intervention research.
Randomizing on the organizational level is similar to using cluster
randomization in that pre-existing natural groups, or clusters, are randomized
instead of individuals. However, cluster randomization usually involves
more clusters, making the randomization procedure more similar to an
individual randomization (Raudenbush, 1997). In Study II, only three pairs
of clusters, that is pairs of matched workplaces (see Method section for a
description of the matching and randomization procedure), were allocated to
the three conditions, which means that it was a very restricted
randomization. As described above, the main reasons for using any kind of
randomization were to protect against confounders associated with
organizational factors such as differences in leadership and motivation,
increase compliance, avoid intervention contamination and maintain the
natural groups. Matching, on the other hand, was used to protect against
confounders associated with pre-existing individual differences in health as
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measured by sickness absence levels. Another goal of the matching
procedure was to minimize differences between clusters. This is important in
order to minimize or avoid cluster effects, which may distort results if
baseline differences between clusters are large, since data from individuals
within a cluster tend to be correlated (Raudenbush, 1997). Baseline
comparison between groups showed that this goal was achieved.
All study participants for whom values on biomarkers deviated outside
the expected range and needed medical consideration were immediately
informed of this. This means that some participants received information on
their biological indicators during the project. Getting this information may
have influenced individual behaviours, for example seeing a doctor, starting
or changing medication or making changes in health behaviours that in turn
may have influenced the outcome measures in Study II. However, there were
no differences in the number of participants receiving feedback in each
intervention group. This, in combination with the relatively large groups,
may have limited the risk of having feedback influencing the result. In
addition, giving feedback to participants on medical issues is highly
motivated from an ethical perspective and was in accordance with the ethical
guidelines.
In Study III, longitudinal data from an intervention project were used,
despite the fact that the intervention was not in focus. However, data from
the second and third wave of data collections were utilized and hence, no
systematic change took place between the measurements. Also, none of the
interventions had any effect on the factors of interest in the Study III (as
shown in Study II). Furthermore, there were no effects of intervention
groups when controlling for this in Study III (analyses not shown). Despite
this, the interventions did affect other factors, as shown in Study II. The
results from Study III should therefore be replicated on longitudinal data that
are not part of an intervention project.
Measurement issues
As discussed in the introduction, the main drawback of self-ratings are
subjectivity and the risk of shared response bias (if both independent and
dependent variables are self-ratings), while biological markers may suffer
from seasonality and diurnal variation and sensitivity to confounding factors
associated with the time of assessment, as well as interpretation difficulties
(Åkerstedt & Theorell, 2002; Hurrell et al., 1998; Watson & Pennebaker,
1989). Control over well-known confounding factors such as smoking,
eating, wake-up time and high stress levels was sought after by providing
detailed instructions to the participants on how to behave before the health
checkups. Data on compliance were gathered at the health checkup to allow
statistical control. Information on medical conditions and medications was
gathered in the questionnaire, and data from individuals with metabolic
77
disorders and those who were pregnant or breastfeeding were removed from
further analyses. Overall, compliance with the health checkup instructions
was high with small and/or few deviations. Moreover, biological markers in
women may be particularly difficult to interpret due to variations in hormone
concentration over the menstrual cycle. However, the biological markers
included in this study do not vary with the menstrual cycle (Ahmad, Pollard,
& Unwin, 2002; Epstein, McNeilly, Murray, & Hockaday, 1975).
Measuring health is particularly challenging (for a systematic discussion,
see the Method section). A number of steps were taken to provide a valid
picture of health. These included using multiple markers of health as well as
using data from different systems (e.g. different biological systems and selfratings). Although effort was made to assess a broad map of indicators of
health and ill health, the markers included still represent a selection of
possible aspects of health and ill health. This means that, for example,
oxygen uptake, adrenaline and noradrenaline, personality traits, selfefficiency, coping and resilience were not assessed. Oxygen uptake, as
measured using a sub-maximal cycle test, would have been helpful in
evaluating the effects of PA on cardiovascular fitness. However, this would
have complicated the measurement protocol and as such, increased costs and
may have led to increased dropout. The same argument was made against the
assessment of catecholamines, which is most reliably done from urine
samples (U. Lundberg, 2002a). Extra blood samples for the assessment of
immunomarkers were drawn and saliva samples for the assessment of
cortisol were collected but were not yet analysed for inclusion in this thesis,
due to time- and financial restraints.
The questionnaire used in this thesis was constructed with the
intervention project in mind. Since the theoretical foundation for effects of
RWH is limited, and since a wide range of factors may be affected by
changes in PA, the self-rating questionnaire was constructed to assess a wide
range of possible outcome factors. The questionnaire was extended to also
include factors that may act as confounders, making statistical control
possible if necessary. Therefore, the questionnaire used in this thesis was
extensive. Despite this, possible confounding factors such as personality
traits, self-efficiency and coping were not assessed. The main reason for this
was to avoid an even lengthier questionnaire by focusing on assessing
factors more directly related to ill health, health, work and balance between
work and non-work.
In Study I, data from a general work environment assessment were used.
This means that the items were pre-existing, and were not influenced by the
researchers. Before statistical analysis, the data were inspected to ensure
their suitability for data analysis. For example, new scales were constructed
using factor analysis. Although it is a disadvantage not to use frequently
used scales, the pre-analytic procedures increased the reliability of the
measures while avoiding analysing single-items, which would increase the
78
risk of Type I error. However, for one factor in particular, the statistical
analyses yielded a result that may be somewhat confusing given the other
operationalizations in this thesis. This was the factor labelled fatigue, which
in Study I included three items: disturbed sleep, tiredness after work and an
inability to stop thinking about work-related issues during one’s free time. In
Study III, which focused more specifically on these concept, inability to stop
thinking about work is the core construct of OC (Siegrist et al., 2004). This
shows one of the disadvantages of exploratory factor analysis: the results are
dependent on which items are included in the analysis. This means that items
may load on different factors in different analyses, depending on which
items are included. In the interpretation of the results from Study I, it is
important to keep in mind that the items of the fatigue factor differ from the
fatigue factor in the other studies, and that caution is needed in interpreting
the relationship between this factor and UED, since the factor includes items
relating to both fatigue and OC.
The operationalization of fatigue also differed somewhat between Studies
II and III. Sleep difficulties related to excessive thinking of work is included
both in the fatigue measure used in Study II and in the OC scale. To avoid
overlaps in Study III, where the interrelationships between fatigue and OC
was analysed, the sleep item was omitted from the fatigue scale in this study.
In Study III, the overlap with the OC scale meant increasing the risk for the
triviality trap, that is having an independent and a dependent variable that are
so similar that they come close to measuring the same thing (Hurrell et al.,
1998). In Study II, no such risks were evident and in that case, keeping a
previously used scale in its original form was considered more important.
No objective measure of physical activity was assessed in this thesis. This
is unfortunate, since self-ratings of physical activity frequently deviate from
objective levels, with low correlations with absolute time spent on physical
activity and energy expenditure (C. L. Craig et al., 2003; Wareham et al.,
2002). However, other ways of measuring PA that are more valid than selfratings, such as accelerometers (pedometers), involve considerably more
complicated protocols, making such measures expensive, rather invasive and
time-consuming. Also, questionnaires on physical activity usually have good
reliability and can be used to assess prevalence estimates and to categorize
participants into activity categories (C. L. Craig et al., 2003; Wareham et al.,
2002). This makes self-ratings of PA and PE suitable for this thesis, since its
aim makes relative levels of physical activity and physical exercise (between
groups and, particularly, between time points) more relevant than absolute
levels. However, using a scale with a wider range than the four-point scale
used in this thesis may have allowed for more detailed analysis. On the other
hand, the differentiation between PA and PE is a strength, and decreases the
drawbacks of using a four-point scale.
PA level was a factor that was deliberately manipulated as part of the
intervention in one of the groups in Study II. This means that PA was
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controlled for in the design, and from this follows that, with respect to the
PA group in Study II, the self-ratings served as a control of the compliance
with the intervention (that is, did those who were supposed to exercise really
exercise? This is equivalent to ―Did the patient really take the pill?‖ in
medical studies). This is an important aspect of any intervention study, since
it has direct relevance to the validity of the study: if a participant in the
intervention groups participates in the study but not in the intended activity,
it is not the effect of the intended activity that is investigated. Along with
measuring self-ratings of physical activity, follow-through was also
encouraged more directly through the design of the intervention: each PA
session was scheduled during work hours and each participant was to record
their PA sessions each week in a shared forum. This was then checked
weekly by a specially assigned employee, and any deviations were
discussed.
Using three time points, six months apart, is in line with previous studies
(Anttila et al., 2005; Wergeland et al., 2003). Furthermore, in both Study II
and Study III, it was sufficient to show relations between the studied
variables. However, using more time points may have further highlighted the
effect of the interventions. For example, longer follow-up times may have
clarified the effects on work ability and general symptoms. Also, more
intense data points may have elucidated the process of recovery and
mechanisms involved in RWH. Moreover, to further clarify the different part
of the recovery process, more intense data points would be helpful.
However, including more data points may also increase reactivity to the
measures and the risk of increased dropout, leading to a biased sample and
measures (Kompier & Kristensen, 2001).
Person-oriented versus variable-oriented approach
In most studies, as well as in Studies I-III in this thesis, a variable-oriented
approach is taken. As described in the Method section, in variable-oriented
research variables instead of individuals are studied. This means that in the
analyses, the individuals are considered replaceable, randomly selected data
carriers. This allows for a wide range of statistical analyses to be used and
relationships between variables to be investigated. However, it is based on
the assumption that all individuals in a population are homogenous
(Tabachnick & Fidell, 2007). Individual differences are considered errorvariance. This may be considered provocative and counter-intuitive,
particularly within the behavioural science. In a person-oriented approach,
which was taken in Study IV, the assumption is that a population consists of
subgroups, and that the ―error variance‖ consists of meaningful, individual
differences (Bergman et al., 2003). In its smallest entity, the subgroup
consists of one individual. However, since this is impractical in studies,
individuals who exhibit similarities are combined into larger subgroups. In
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contrast to the variable-oriented approach, behaviours instead of variables
are sampled. Unfortunately, person-oriented methods are sparsely used in
biological and work psychology and therefore, many researchers are
unfamiliar with the methods. The use of person-oriented methods is
motivated when subgroups exhibiting different patterns are expected,
because these may be masked when a variable-oriented approach is used.
Such patterns appeared in Study IV, in which not all women with poor
recovery and fatigue were likely to have an increased risk for AL. Letting
the aim of the study influence the approach taken, and/or combining
variable-oriented and person-oriented approaches is an important task for
future research.
Operationalization of AL
In Study IV; the separate biological markers were added to form a
cumulative score of AL. This measure has several advantages as a stressrelated outcome compared to individually analysed biomarkers, including
having a clear theoretical foundation and making it possible to minimize
statistical test by using a sum variable. The biological parameters included in
the operationalization of AL differ somewhat between studies, but the
reasons for choosing them are similar: the parameters should reflect multiple
regulatory systems, and have known or hypothesized links to various health
endpoints (Gruenewald et al., 2006; McEwen & Seeman, 1999; Seeman,
Singer et al., 1997; Seeman et al., 2001; Seeman et al., 2004). These reasons
guided the selection of parameters in this thesis as well. Furthermore, and
similar to previous studies (Gruenewald et al., 2006; McEwen & Seeman,
1999; Seeman, Singer et al., 1997; Seeman et al., 2001; Seeman et al., 2004),
the choice was restricted to the parameters available in the present dataset.
Although this means that catecholamine, cortisol and immunomarkers were
not included, the AL measure included markers of cardiovascular activity;
blood lipids associated with increased risk of atherosclerosis and
cardiovascular disease; measures of fat deposits associated with increased
risk of diabetes and overweight; integrated measure of glucose metabolism, a
measure of adipose tissue deposition and metabolism, a functional HPA axis
antagonist and a hormone sensitive to sleep and stress.
Unfortunately, as with most other studies using different
operationalizations of AL, similarity between the AL measure used in Study
IV and those used in other studies cannot be established. Recent research
comparing different operationalizations of AL has shown that differences in
the biological markers included have only a modest effect on various healthrelated outcomes, although it indicates that keeping the continuous
properties of the included biological markers in the summary index may
yield stronger predictions regarding some health outcomes (Seplaki,
Goldman, Glei, & Weinstein, 2005). However, the additive method used in
81
this thesis is the most common, and has the advantage of being more easily
interpreted and allowing for comparison with other studies using the same
method.
Studies using AL also differ in the calculation of cut-points and data from
individuals using medication. Cut-points can be derived either clinically or
empirically, or a mix. In this thesis, empirically based cut-points were used.
This is in line with previous studies on AL (Crimmins et al., 2003;
Karlamangla et al., 2002; Lindfors, Lundberg, & Lundberg, 2006; Seeman et
al., 1997; Seeman, Singer et al., 1997; Seeman et al., 2004). Using empirical
cut-points may be motivated by the fact that since AL is a pre-clinic
measure, cut-points should also be pre-clinical. This is particularly relevant
given the population studied. Using clinical cut-points in a group of healthy,
working women would mean that only a very restricted number of cases
would be available for analysis. Scoring of individuals taking medication
that might influence levels of one or more of the biological parameters is a
common dilemma in research on AL (for instance, see Seeman, Singer, Ryff,
Dienberg Love, & Levy-Storms, 2002). In our study, the number of
individuals taking such medication was low (16%). In addition, the analyses
were rerun excluding women reporting that they currently took medication
that alters blood pressure, cholesterol or glucose levels to examine the effect
of medication on our results. These results were not different from those
reported in the Study IV (unpublished results) and consequently, we
conclude that the impact of medication on AL is of minor importance in the
present sample which includes healthy, employed women.
Statistical considerations
In this thesis, different statistical methods were used. As discussed above,
with only one exception, these were variable-oriented approaches. The
general approach guiding the choice of statistical method in this thesis,
besides being appropriate in answering the research questions and having
data that met the relevant assumptions, was 1) to use analyses of variance
whenever groups differences were of interest and number of covariates was
limited 2) to use logistic regression when relative risk was of importance
(Tabachnick & Fidell, 2007) and 3) to use the most uncomplicated methods
whenever possible. With the exception of Study II, a number of different
analytic strategies were used in each study.
Using multiple indicators of health and ill health has many advantages as
discussed previously, but may also have some unfavourable consequences.
One of the more important risks is that of Type I error (false positive), which
increases with the number of statistical tests performed. This problem is
specifically relevant in Study II. Simply decreasing the number of
significance tests empirically (for example, by factor analysis) was not
feasible, since this would decrease the validity of the study. Nor was the
82
theoretical framework sufficient for guiding the removal of outcome factors.
A bonferroni correction was not done, since the power of this kind of
intervention study is limited to begin with. A further decrease in power
would inflate the risk of Type II error substantially. Instead, the results are
interpreted as patterns rather than focusing on each individual outcome. To
further minimize the risk of Type I error, the effect in each group was tested
only after a significant time- or interaction effect was present. By doing this,
more detailed information on what contributed to the interaction and/or main
effect was gained while all factors for each condition still did not have to be
analysed.
Generalizability
This thesis was set among municipally employed women working with
dental care or elderly care. This sector employs very few men and therefore,
the results from this thesis can be argued to be valid for the sector as such.
However, the results may also be generalized to working women in other
sectors, particularly those with similar job characteristics. Self-employed or
home-staying women or men, on the other hand, may differ in aspects
relevant to the results. Employment status may interact with financial, health
and social factors. Employed men and women differ in their work-home
configuration, with women generally taking more responsibility for home
and children and doing more unpaid work (Gjerdingen et al, 2000; Krantz,
Berntsson, & Lundberg, 2005; U. Lundberg & Frankenhaeuser, 1999). Men
and women also differ endocrinologically, which may obscure relationships
between self-ratings and biological markers. Therefore, results from this
thesis, particularly from Studies III and IV, needs to be replicated among
men.
As described in the introduction, some work factors are particularly
pronounced within this field, including a combination of high emotional and
physical demands, and the prevalence of work-related illness is high
(Bäckman, 2001; O. Lundberg & Gonäs, 1998; The Work Environment
2007, 2008). Therefore, care must be taken in generalization to other sectors.
However, although it represents a particular work sector, different
educational levels are represented within dentistry (but not within elderly
care). This suggests that generalization may be made across educational
levels.
Ethical considerations
Doing research in the workplace means reaching potential participants
through their employer, on whom the employees are more or less dependent.
The employer’s decision to allow a research project to take place may
83
influence employee decision to participate, if they believe their employeeemployer relationship would be affected by it. From this follows that
particular care must be taken to ensure that participation or non-participation
does not affect the employee’s situation in the workplace, in either a positive
or negative way. An obvious first step is to guarantee employee anonymity,
so that the employer has no knowledge about who has volunteered to
participate in the research project and who has not. In the research presented
in this thesis, care was taken to separate the participation in the WHP, which
was a responsibility of the employer, from the participation in the data
collection done to evaluate the interventions, for which the researchers were
responsible. Hence, the employer decided that participating in the WHP was
mandatory, while participation in the evaluation of the WHP was voluntary.
This was communicated both orally and in writing. Secondly, the union was
involved in the decision to allow the research project to take place. This
means that the employee representatives supported the project, and that
employees had a saying in the decision. Despite this, and despite efforts to
keep the employers blind as to who participated in the research part of the
project, the possibility cannot be eliminated that the awareness among
employees that participating was encouraged by the employer still may have
influenced their decision to participate.
Allowing a research project to take place at a workplace means
investments from both an individual and an organizational perspective. For
the individuals, time has to be allocated for receiving information, health
checkups and questionnaires. They also have to withstand the discomfort
associated with undergoing a physical exam (e.g. measuring blood pressure
and taking blood samples). For the employer, the investment involves
allowing health checkups and information meetings during work hours,
hence decreasing productivity. To compensate for this in some way, an effort
was made to reciprocate to both individuals and employers. This was done
after the end of the project, by giving feedback on the results of the studies.
Each individual received their results from the three health checkups, in
writing, and each workplace was given a presentation of the results for that
group as well as the overall results of the studies. Detailed, written reports on
the group results were also produced and presented to the organizations
involved.
Another ethical question concerns the WHP itself. Who bears the
responsibility for individual health, the employee or the employer? Despite
the obligations outlined in the Work Environment Act (Arbetsmiljöverket
[Swedish Work Environment Authority], 2008), it is difficult to ignore the
responsibility of each individual for his or her on health. One argument for
the individual’s responsibility is that health is affected by, and affects, much
more than work. Since the employer does not have an influence over these
circumstances, it can be argued that they should not bear any responsibility
for them either. In fact, only the individual has the potential to influence all
84
factors that are related to health. Another argument for health as an
individual responsibility is that, although employers or others may influence
individual behaviour, only the individual can change it.
A related question is what kind of demands an employer can put on
employee health and employee health behaviours. This question may not
have a given answer. First, it depends on the answer to the first question. If
health is regarded as solely an individual responsibility, the employer may
either set criteria for what they expect of their employees without providing
any means, or take a ―hands-off‖ approach and leave health-related issues
exclusively to the individual. Both approaches may be argued to be ethically
questionable. In Sweden, the employer is responsible for the work
environment. This means that the organization is obligated not only to
minimize risks but also to facilitate employee health and well-being from a
broader perspective (Arbetsmiljöverket [Swedish Work Environment
Authority], 2008). As such, it can be argued that in order to fulfil the legal
requirements, WHP is appropriate. Moreover, the work environment-health
relationship is dependent not only on the work environment per se, but also
on the employee-work environment fit. No matter what measures are taken
to improve the ergonomic situation, for example, it still depends on how well
equipped the individual is to meet the demands of the workplace. That is,
having employees who are fit or strong enough to meet the demands of their
workplace may be a necessity for employers to meet their legal obligations.
From this perspective, putting demands on employee fitness may be
reasonable, particularly if work time is allocated for these activities. This is
also the case within some occupations, such as among fire-fighters and
policemen, where physical exercise has traditionally been an integrated part
of work.
Practical implications
Consequences of UED and reasons for action
Since working adults spend so many of their waking hours at their
workplaces, the conditions there are important for employee health and wellbeing. For most people, the benefits of paid work override the costs: not only
financially but by providing goal-directed activity and a daily structure,
along with social contacts. Paid employment has been related to better social
support, increased creativity and control and increased intrinsic and extrinsic
gratification, including income (Barnett & Hyde, 2001; Bird & Ross, 1993;
Hibbard & Pope, 1992; Mirowsky & Ross, 2007; Repetti et al., 1989; Yoshii
& Yamazaki, 1999). However, it is undisputed that poor work conditions
have the potential of causing ill health and sickness. In dentistry, this
includes UED, which is a very common problem. The negative
85
consequences this has for the individual are obvious, in terms of pain and the
long-term increased risk for sickness absence, decreased productivity and
early exit from the work force (Hagberg, Vilhemsson, Tornqvist, &
Toomingas, 2007; Huisstede et al., 2008; Wiitavaara, Barnekow Bergkvist,
& Brulin, 2007). From this follows that for the individual, there is an
increased risk not only of losing his or hers health, but also of losing the
benefits of having a paid work. For the individual, increasing one’s
knowledge about what factors are related to UED may increase the
possibility for the individual to notice, and make changes to, a potentially
harmful situation. For example, being aware of the risks associated with
being exposed to high physical load may increase the individual’s
motivation for utilizing the ergonomical equipment that the employer
supplies.
However, work-related ill health is a problem not only for those
individuals who suffer, but also for their employer. Many of the
consequences that affect the individual also affect the employer. Factors like
reduced work ability, sickness absence, high turnover and early retirement
all have financial implications for the organization. First, there are direct
costs related to sickness absence and high turnover (sickness salaries during
early sickness absence, the cost of rehabilitation, recruitment costs, etc.).
Second, the indirect costs are high. One of the highest is productivity costs,
that is the productivity losses due to the values lost when the employee is not
present doing his or her job, and replacement costs, that is the cost of
replacing the absent employee. Productivity costs may also include losses
associated with poor performance among employees who have impaired
health and/or functioning, but still are part of the work force. Also, indirect
costs may include legal sanctions, fines, etc. Organizations may therefore be
motivated not only by moral and/or legal obligations to intervene, but by
economic reasons as well.
Possible interventions — PE and RWH
The fact that many adults spend so much time at work does not only poses a
potential problem in terms of exposure to harmful environments. It also
makes the workplace a suitable arena for health interventions and health
promotion. Even small improvements in working conditions or employee
health habits may be effective in improving employee health. In Study II, it
is shown that PE during work hours may be related to improved physical
health, whereas RWH cannot be recommended as a general intervention to
improve health. As explained above, one reason for this may be that the
effect of RWH may be dependent on how the reduced working hours are
spent. What individuals do during their free time is a factor that few
organizations have influence over. PE, particularly when scheduled during
working hours, on the other hand, may be less dependent on individual
86
factors and may therefore be better suited as an ―all-for-one‖ intervention
(that is, general rather than adapted to individual needs). Another option for
employers is WHP that is adapted to individual needs, giving the individual
a choice between different interventions or targeting different interventions
to employees at different stages of change. This has yielded support in
previous research (Marshall, 2004).
PE during working hours seems particularly appropriate when the goal is
to improve physical health and/or when physical fitness is important for
fulfilling job requirements. The challenge for organizations wishing to gain
the positive effects related to PE interventions lies in reaching all employees.
Previous research has shown that almost inevitably, physical activity
interventions are more successful in attracting employees who are already
physical active, whereas sedentary employees and those with health
problems seldom participate (Alexy, 1991). Reaching blue-collar workers
has been particularly challenging (Gebhardt & Crump, 1990). This is
particularly troublesome since it is among those who are less likely to
participate that the need is greatest and the most pronounced effects can be
expected. If physically inactive employees do not participate, it may even be
questionable whether physical exercise is an effective intervention,
particularly if the exercise is scheduled during work hours and hence
involves a cost in terms of fewer productive hours. However, Study II shows
that it is possible to achieve a high participation rate. This is in line with
previous research showing considerably higher participation rates when the
PA takes place during work hours (H R. Eriksen et al., 2002; Pohjonen &
Ranta, 2001; Yancey et al., 2004).
Since attracting participators to initiate and maintain a PA program is one
of the great challenges in health promotion, much of the literature on PA
focuses on motivation: what makes people start and sustain an exercise
regime? (see for example Armitage & Conner, 2000). The PA initiative in
this thesis was mandatory. This means that the initiation of PE was
externally regulated and motivated and negatively reinforced. According to
the self-termination theory (Ryan & Deci, 2000), this kind of motivation is
less likely to maintain the behaviour, and more likely to produced negative
affect than intrinsic motivation, that is when the behaviour in itself is
rewarding (Deci & Ryan, 2008). Also, mandatory PA may interfere with
autonomy, to act volitionally, which frequently has been described as an
important part of intrinsic motivation (Deci & Ryan, 2008; Ryan & Deci,
2000). Hence, a mandatory PA initiative may counteract factors associated
with maintenance of behaviour and positive affect. However, although
intrinsic motivation is important in order to increase long-tem engagement,
externally regulated behaviours may be appropriate in initiating activities.
By making the PE mandatory, individuals will have the opportunity of
directly experiencing the effects of PE, as well as directly testing his or hers
abilities to perform the activity. According to the theory of planned
87
behaviour, this will increase the likelihood for a positive attitude towards the
behaviour and a sustained engagement in the activity, given that that
experience is more positive than negative and that the individual succeeds in
doing the behaviour (Ajzen, 1991). Also, regardless of what motivates the
PE, doing it regularly may transform the behaviour into a habit, which
requires less cognitive and motivational effort to perform (Aarts, Paulussen,
& Schaalma, 1997). Nevertheless, it may be appropriate for organisations to
help individuals in the transformation from being primarily externally
motivated to being internally motivated and experience greater autonomy,
for example by encourage the individual to set achievable goals with the PE,
by providing opportunity to get individual feedback on the effects (e.g.
health checkups) and by discussing the positive affects related to the training
experience.
Although the PA in Study II was mandatory, it was of great importance to
motivate and inspire employees to approve of the intervention, so that they
chose to stay at the workplace, complied with the intervention and
participated in the scientific evaluation. The experience from this project
suggests that including employees at an early stage in the decision process,
facilitating interaction and discussion among employees regarding all
aspects of the intervention, having highly visible support from upper
management and providing the opportunity to assess improvements and
giving feedback may contribute to a high participation rate. This is in line
with previous research showing that being clear about the goals of the
initiative, having long-term management support and evaluating and giving
feedback on the results to employees are important for employee
commitment (Gebhardt & Crump, 1990). To summarize, PE may be
recommended to organizations wishing to increase employee health,
particularly if care is taken to reach those who are not already active.
Although not investigated in this thesis, PE interventions may also be
motivated by other goals: decreased turnover and early exit from the
workplace (that is, support a sustainable work life), positive financial
returns, increased goodwill and ease of recruitment by being considered an
attractive and sought-after employer, etc. (for example, see Golaszewski,
2001).
From a public health perspective, the results from this thesis support the
notion of the workplace as a promising arena for health promotion targeting
adults. However, from this perspective it should also be noted that choosing
the workplace as an arena for health promotion and health interventions
means targeting a population that in many aspects is already blessed:
healthier and richer, with a greater social network and longer life
expectancy, etc. (Alexy, 1991; Conrad, 1987; Marshall, 2004). As such,
workplace interventions may be less appropriate from a public health
perspective. However, WHP and other public health initiatives are not
mutually exclusive – that is, one does not disqualify the other. In fact, if
88
some public health initiatives are taken care of by employers instead of
public health organizations or governments, more of their means may be
available to less fortunate groups.
Withdraw from work – what can be done?
Study III shows that OC is important in understanding recovery between
workdays and work-related fatigue. From this follows that it is not only
factors associated with the workplace that need to be considered in
interventions aimed at decreasing stress-related ill health. For organizations,
this means providing employees with the tools to handle or prevent
perseverative cognitions and may include interventions focusing on the
individual as well as those focusing on the work situation and organization.
As an intervention targeting the individual, cognitive behavioural therapy
has been promising in treating rumination and worry within a clinical
context (Borkovec, Newman, & Castonguay, 2003; Kehle, 2008), and may
prove valuable within the context of work stress as well. However, this
needs to be investigated in future research. For interventions targeting the
work situation, it may be speculated whether minimizing unclarities and
insecurities associated with work are appropriate. Research has shown that in
the working life of today, it is becoming increasingly common to be
uncertain of when one’s work is done and against what standards the work is
being evaluated (Hellgren et al., 2008). These factors may increase
rumination. From this follows that clarifying goals, providing feedback (e.g.
being able to observe the result of one’s job or receiving oral feedback from
supervisors), etc. may aid the employees in detaching from work and
decreasing rumination. These kinds of initiatives are taken within the
framework of organizational behaviour management and have been
successful in other aspects, such as increasing employee motivation and
commitment and in improving productivity (Daniels, 2000). However, the
effects on rumination and the ability to withdraw from work need further
investigation.
Negative effects of fatigue and lack of recovery
Although there is an agreement on stress as being related to various negative
effects on health, less is known about the relationships between lack of
recovery and fatigue and ill health. Study IV provides evidence that
individuals with a recovery profile characterized by mental and physical
fatigue during and after the workday, disturbed sleep and not being fully
rested after a nights sleep have an increased risk of AL, a cumulative
biological load. This shows that lack of recovery and fatigue may have
health-damaging effects even among women who are still working and
considered part of a healthy population. This implies that lack of recovery
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and fatigue may be an early warning sign of a potentially health harming
process. As such, recovery and fatigue should be part of workplace
assessment of work environment and employee health. It seems likely that
monitoring factors that act as early warning signs would make it possible for
organizations to act preventively rather than rehabilitatively, or after-thefact. Such initiatives may be more powerful since the ill health process is at
an earlier stage and as such may be more easily reversed, thereby preventing
the loss of workforce to sickness absence, early retirement or turnover.
Conclusions
The public health care in general, and dentistry in particular, involves
demanding work conditions, both psychosocial and ergonomically. The risk
of work-related ill health is high, particularly when efforts at work are not
balanced with sufficient recovery from work as proposed by stress theory.
This thesis shows that UED is particularly common. Finding interventions
that may improve employee health is therefore important. However, simply
decreasing the number of hours spent at work, thereby decreasing exposure
to the work environment and allowing more time for leisure activities, did
not lead to positive health effects. It is concluded that it is an
oversimplification to believe that whatever you do outside work will prove
more beneficial to your health than what you experience during work. The
effect on physical health among women who took part in physical exercise
during working hours, on the other hand, was promising, and this may be an
appropriate intervention to improve physical health, including decreasing
UED. Neither decreased work hours nor physical exercise had any effect on
recovery or fatigue. It is suggested that factors outside work that prolong or
sustain the stress-related activity in the body may contribute to this. It was
shown that being overcommitted to work was associated with poorer nextday recovery and increased fatigue and that this factor was a more important
predictor of lack of recovery and fatigue than were psychosocial work
characteristics. Therefore, it is suggested that factors that affect the ability to
let go of work need to be considered in relation to work-related ill health,
whether in terms of direct interventions aimed at the individual or
organizational efforts that would reduce uncertainties associated with work.
The importance of intervening when individuals experience lack of recovery
and fatigue was demonstrated in the increased risk for a cumulative
biological load, in terms of allostatic load, among fatigued and nonrecovered women. This also highlights the importance of assessing recovery
from work as an early risk factor for stress-related disease.
90
Sammanfattning på svenska
Även om förvärvsarbete generellt är hälsofrämjande så kan krävande
psykosociala och ergonomiska arbetsförhållande öka riskerna för
arbetsrelaterad ohälsa. Syftet med den här avhandlingen var att studera olika
aspekter av arbetsrelaterad hälsa och ohälsa bland kvinnliga anställda inom
offentlig sektor i allmänhet och tandvård i synnerhet. Detta gjordes utifrån
en stressteoretisk referensram med särskilt fokus på återhämtning från
arbetet. Den här avhandlingen inkluderar 1) en deskriptiv studie av
smärtproblematik i de så kallade övre extremiteterna (s.k. UED, från
engelskans Upper Extremity Disorder) inom tandvården, 2) en undersökning
av effekten av två arbetsplatsförlagda interventioner samt 3) två studier som
fokuserar på hur återhämtning från arbetet är relaterat till psykosociala
arbetsplatsförhållanden, oförmåga att släppa tankarna på arbetet och till
kumulativ biologisk belastning, s.k. allostatisk belastning (AL). Den första
studien visade att en anmärkningsvärd stor andel av kvinnlig
tandvårdspersonal led av UED: 81 % av 945 deltagare rapporterade sådan
problematik. Dessa personer upplevde både den psykosociala och den
fysiska arbetsmiljön som sämre än anställda utan UED. Signifikanta
skillnader återfanns också mellan tandläkare och tandsköterskor, där
tandläkare rapporterade högre fysisk belastning och mer utmattning medan
tandsköterskor rapporterade lägre grad av inflytande över arbetet. En
hierarkisk regressionsanalys visade att en hög fysisk belastning var den
viktigaste prediktorn för UED, följt av antalet allmänna hälsoproblem, högre
ålder och sämre fysisk arbetsmiljö. Slutsatsen var att förekomsten av UED
var mycket hög, i synnerhet med tanke på att arbetsplatserna hade hög
ergonomisk standard. Det noterades också att psykosociala
arbetsförhållanden, något förvånande, inte predicerade UED och detta antogs
bero på att den höga fysiska belastningen överskuggade eventuella effekter
av den psykosociala miljön. Sammanfattningsvis konstaterades att kvinnlig
tandvårdspersonal riskerar att utveckla muskelbesvär och att det därför att
angeläget att hitta interventioner som förbättrar hälsan för anställda inom
detta arbetsfält.
Syftet med den andra studien var att undersöka de hälsorelaterade
effekterna av två arbetsplatsförlagda interventioner: fysisk träning respektive
förkortad arbetstid. I båda interventionsgrupperna förkortades
veckoarbetstiden med 2,5 timmar, från 40 till 37,5 timmar. I
arbetstidsförkortningsgruppen fick tiden användas till vad som helst, medan
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tiden i träningsgruppen var avsedd för medel- till högintensiv fysisk träning
fördelat på två tillfällen per vecka. Arbetstidsförkortningsgruppen omfattade
50 kvinnor, träningsgruppen inkluderade 62 kvinnor, och referensgruppen,
där ingen förändring skedde, bestod av 65 kvinnor. Resultaten visade på
signifikanta skillnader mellan grupperna över tid i glukos (p = .04),
midje/höft-kvot (p = .036) och självskattad arbetsförmåga (p = .01). Post hoc
analyser visade att glukosnivåerna minskade signifikant i träningsgruppen (p
= .036), att midje/höft-kvoten ökade i arbetstidsförkortningsgruppen (p
<.001) och att arbetsförmågan minskade i referensgruppen (p = .005).
Skillnaderna mellan grupperna över tid närmade sig också signifikans för
generella symptom (p = .063) och UED (p = .062), då antalet symptom
ökade i referensgruppen och UED minskade i träningsgruppen. Andra
resultat pekade på ökade nivåer av det anabola hormonet DHEAS, HDL och
totalkolesterol i arbetstidsförkortningsgruppen, ökade nivåer av
totalkolesterol i träningsgruppen och generellt ökade nivåer av blodfetter i
referensgruppen. Således tycks effekterna av interventionerna skilja sig åt.
Tydligast var de positiva effekterna i träningsgruppen, där några av de
traditionella riskfaktorerna för ohälsa påverkades i positiv riktning.
Slutsatsen är att träning på arbetstid ger lovande resultat, och att det kan vara
en lämplig intervention för att förbättra den fysiska hälsan samt för att
minska förekomsten av UED.
Något förvånande gav inte interventionerna i Studie II några effekter på
trötthet eller återhämtning från arbete. Detta kan bero på faktorer utanför
arbetet som förlänger eller upprätthåller den stressrelaterade aktiviteten i
kroppen. I Studie III studerades hur psykosociala förhållanden på arbetet,
antalet hemmavarande barn och oförmåga att släppa tankarna på arbetet
påverkade återhämtning mellan arbetsdagar och arbetsrelaterad trötthet sex
månader senare. Resultaten visade att en oförmåga att släppa tankarna på
arbetet hade samband med sämre återhämtning och ökad arbetsrelaterad
trötthet. Oförmågan att släppa tankarna på arbetet var minst lika viktig som
kraven i arbetet. En praktisk implikation av resultaten är således att faktorer
som gör att det är svårt att släppa tankarna på arbetet behöver påverkas för
att kunna minska stressrelaterade problem. Detta kan i sin tur innebära såväl
individinriktade som organisatoriska åtgärder.
Resultaten av Studie III indikerade också att trötthet både kan ses som en
stressreaktion, och följaktligen föregå återhämtning, och som en konsekvens
av bristande återhämtning. Implikationerna av detta för framtida forskning
diskuteras, och en konceptuell modell för återhämtning presenteras. I
modellen visas hur återhämtning är relaterat till såväl stressorer,
stressreaktivitet, återhämtningens förläggning i tiden och faktorer som
påverkar återhämtningsprocessen.
I Studie IV undersöktes risken för framtida ohälsa bland kvinnor som
upplever en brist på återhämtning och arbetsrelaterad trötthet. Genom en
kombination av personorienterade och variabelorienterade metoder framkom
92
tre olika återhämtningsprofiler, där profilen som karaktäriserades av trötthet,
sömnsvårigheter och bristande korttidsåterhämtning hade en 2.86 gånger
högre risk för hög allostatisk belastning, d.v.s. en kumulativ biologisk
belastning. Resultaten visade också att även om självskattad återhämtning
var kopplad till allostatisk belastning så fanns det inga skillnader i de
biologiska markörerna när de analyserades var för sig. Vidare framkom att
de två profilerna som uppvisade bristande återhämtning skiljde sig åt i risk
för allostatisk belastning, vilket har betydelse när återhämtning och trötthet
ska studeras vetenskapligt. För att summera ger resultaten från Studie IV
stöd för att fokusera på kumulativ biologisk belastning för att förstå
mekanismerna mellan bristande återhämtning och framtida ohälsa. Studien
visar också på vikten av att följa upp bristande återhämtning och trötthet som
en tidig riskfaktor för stressrelaterad ohälsa.
Sammanfattningsvis visar den här avhandlingen att det är viktigt att ta
hänsyn till återhämtning från arbetet för att förstå kopplingen mellan stress
på arbetet och ohälsa. Begreppet återhämtning behöver utvecklas ytterligare,
och det är angeläget att särskilja bristande återhämtning från arbetsrelaterad
trötthet och att vara noggrann med den tidsmässiga aspekten av
återhämtning. De praktiska implikationerna av avhandlingen är att det finns
stöd för att organisationer kan genomföra åtgärder som förbättrar hälsan och
minskar risken för ohälsa hos medarbetarna genom fysisk träning på
arbetstid. För att tidigt kunna ingripa vid framtida ohälsa rekommenderas att
bristande återhämtning och arbetsrelaterad trötthet inkluderas i
arbetsmiljökartläggningar och att man i högre grad fokuserar på kumulativ
biologisk belastning, alltså gör en sammanvägning av flera enskilda
biologiska indikatorer.
93
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