[email protected]

RESEARCH ARTICLE

Social Stressors at Work, Sleep Quality and PsychosomaticHealthComplaints—ALongitudinalAmbulatory FieldStudyDiana Pereira*† & Achim Elfering

Department of Psychology, University of Bern, Bern, Switzerland

Abstract

There is increasing evidence that occupational stress increases psychosomatic health complaints in the long run.However, the underlying mechanisms are still unclear. The present longitudinal actigraphy field study investigatedthe role of sleep quality—objectively assessed sleep-onset latency, sleep efficiency and sleep fragmentation, andsubjectively assessed sleep quality—as a mediator in the relationship between stressful work conditions at time 1and psychosomatic health complaints at time 2. A longitudinal hierarchical regression analysis revealed that socialstressors at work were positively related to objectively assessed sleep fragmentation and to psychosomatic healthcomplaints. Moreover, objectively assessed sleep fragmentation mediated the effect of social stressors at work onpsychosomatic health complaints. Contrary to our expectations, social stressors at work were not related to othersleep quality parameters (i.e. sleep-onset latency, sleep efficiency and subjectively assessed sleep quality) duringfollow-up. Sleep fragmentation is discussed as an important consequence of social stressors at work that increasethe risk of psychosomatic health complaints in the long run. Copyright © 2013 John Wiley & Sons, Ltd.

Received 30 October 2012; Revised 17 April 2013; Accepted 18 April 2013

Keywords

social stress; occupational stress; actigraphy; sleep; psychosomatic health complaints; longitudinal study

*Correspondence

Diana Pereira, Department of Psychology, University of Bern, Muesmattstr. 45, 3000 Bern 9, Switzerland.†Email: [email protected]

Published online 4 July 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smi.2494

IntroductionThe relationship between occupational stressors andpsychosomatic health complaints, such as headaches,gastrointestinal problems and neck pain, has attractedconsiderable attention in occupational stress research(De Jonge, Bosma, Peter & Siegrist, 2000). In line withthis, a number of empirical studies have linked varioustypes of occupational stressors and psychosomatic healthcomplaints (e.g. De Lange, Taris, Kompier, Houtman &Bongers, 2003; Mikkelsen & Einarsen, 2008; Sonnentag& Frese, 2003). According to Brosschot and Van DerDoef (2006), there are at least three good reasons toinvestigate psychosomatic health complaints in occupa-tional research. Firstly, psychosomatic health complaintsare extremely common. According to Eriksen, Ihlebaekand Ursin (1999), 75% of a normal population reportedhaving experienced at least one type of complaint duringthe preceding 30 days. Secondly, psychosomatic healthcomplaints represent one of the most frequent reasonsfor visits to general practitioners (Eriksen & Ursin,2004). Thirdly, most of these complaints concerned vaguesymptoms that remain mainly clinically undiagnosed.

Stress Health 30: 43–52 (2014) © 2013 John Wiley & Sons, Ltd.

Nevertheless, the costs associated with these complaintsare very high when the resultant medical actions, sickleave compensation and loss of productivity are takeninto account (Brosschot & Van Der Doef, 2006). Thus,to prevent sickness and its related costs, it is of particularinterest to understand how occupational stressors mayinfluence psychosomatic health complaints.

Social stressors at work

Although several theoretical models have been developedto explain how occupational stressors may affectemployees’ health, two models have received particularattention so far: the demand control model and theeffort–reward imbalance model (Siegrist & Rödel, 2006).Therefore, studies of the effect of workload and decisionlatitude on psychosomatic health are numerous. Forexample, De Jonge et al. (2000) found that employeesreporting either high demands and low control or amismatch between their efforts and occupationalrewards had elevated risks of psychosomatic healthcomplaints. Even though these models are interesting,they do not taken into account social interactions at

43

Social Stressors, Sleep and Psychosomatic Complaints D. Pereira and A. Elfering

work. However, with the changed nature of work,service jobs have become the major employment sectorin Western countries. Therefore, social interactionswith co-workers, supervisors and costumers are partof the everyday life for a large proportion of employees(e.g. Dormann & Zapf, 2004). Social interactions atwork may have both positive and negative effects onemployees (Dormann & Zapf, 2004). On the one hand,the opportunity to interact with others may fosterfeelings of social companionship and relatedness; onthe other hand, social interactions, in terms of socialstressors at work, may also have a variety of negativeeffects on individuals, such as irritation and depression(Dormann & Zapf, 2004). The negative effect of socialstressors at work on individuals may best be explainedby the need-to-belong theory (Baumeister & Leary,1995). According to this theory, individuals have anaturally pervasive drive to establish and sustain aminimumnumber of long-lasting, positive and significantinterpersonal relationships. If the need to belong is notsatisfied, this may go beyond negative affect and causesigns of maladjustment, behavioural or psychologicalpathology and health problems (Baumeister & Leary,1995). Drawing on the need-to-belong theory, Semmer,Jacobshagen, Meier and Elfering (2007) assumed in theirstress-as-offence-to-self concept that social stressors atwork are a very direct way of treating the need to belong.Thus, social stressors at work should be related toimpaired well-being and impaired health. Furthermore,compared with other stressors at work, such as timepressure, social stressors at work represent not only avery common but also the most troublesome andupsetting stressor (Dormann & Zapf, 2002; Smith &Sulsky, 1995).

Many stress scientists have tried to explain howoccupational stressors at work elicit harmful effects onhealth. Heretofore, it has been said that stress-relatedphysiology may play a particularly crucial mediatingrole (e.g. Meijman & Mulder, 1998). However, stress-related physiological activation in response to occupa-tional stressors is normally short-lived and fullyreversible within a short period. Thus, stress-relatedphysiology cannot fully explain how health impairmentsemerge. To better understand how occupational stressorsresult in health impairments, additional explanatorymechanisms are needed. Geurts and Sonnentag (2006)argued that incomplete recovery may help explain howacute load reactions may develop into more chronicload reactions that impair health.

Recovery from work stressors, and sleep

Recovery as a process of psychophysiological unwindingafter effort expenditure (Meijman & Mulder, 1998) isconsidered to be an important intervening variable inthe causal chain of stressful work characteristics and thedevelopment of psychosomatic health complaints in thelong run (Geurts & Sonnentag, 2006). Sleep is one of

44

the most important recovery mechanisms available tohumans. There is increasing evidence that occupationalstress may play an important role in the developmentof disturbed sleep quality (e.g. Åkerstedt et al., 2002;Åkerstedt, Nilsson & Kecklund, 2009; Ekstedt et al.,2006; Lallukka, Rahkonen & Lahelma, 2011; Pereira,Meier & Elfering, 2012). According to Åkerstedt (2006)and Åkerstedt et al. (2009), the increased physiologicaland psychological activation in response to occupationalstressors is not commensurate with the deactivationthat is a main characteristic of sleep; thus, the experienceof stressors at work (which unavoidably will lead toincreased activation) should be related to impaired sleepquality. This assumption is in line with the effortrecovery theory (Meijman & Mulder, 1998) and theallostatic load theory (McEwen, 2006), which providefurther explanations of why occupational stressorsimpair sleep quality and health in the long run.According to the effort recovery theory (Meijman &Mulder, 1998), work stressors require effort on the partof individuals, involving physiological and psychologicalreactions, such as accelerated heart rate, elevated bloodpressure and fatigue. Under normal circumstances, thatis, after spending a certain period off work, the psycho-physiological systems will stabilize again at a specificbaseline level, leading to recovery. However, particularlystressful work conditions, such as the experience of socialstressors at work, may lead to persistent psychophysio-logical load reactions, and as a consequence, recoveryand sleep may be endangered. In such a case, the workerwill have to begin work again in a suboptimal conditionand will have to invest compensatory effort to performadequately. This will lead to increased intensity of loadreactions, higher demands on recovery processes andfinally a cumulative process resulting in less transitorysymptoms or even permanent symptoms such asimpaired sleep and psychosomatic complaints (e.g.Sluiter, Frings-Dresen, Van der Beek & Meijman, 2001).Moreover, in line with the findings of McEwen (2006)and McEwen and Wingfield (2003), the failed recoveryof the stress responses is particularly important, becauseit can cause diverse health impairments.

Thus, when the physiological activation involved inthe stress response is considered, it seems logical toexpect a connection with sleep; however, accordingto Åkerstedt et al. (2009), the evidence in terms ofstudies of causal connections is surprisingly modest.Insofar as evidence is available from a number ofcross-sectional studies, it has shown a link betweenoccupational stress, sleep impairments and impairedhealth (Åkerstedt, 2006). Åkerstedt, Kecklund, Alfredssonand Selen (2007) indicated that disturbed sleep is apredictor of long-term sickness absence. Moreover, ina longitudinal study, Leineweber, Kecklund, Janszky,Åkerstedt and Orth-Gomér (2003) found that womenreporting poor sleep quality at baseline had a two anda half times higher risk of a new cardiovascular eventwhen compared with women with good sleep.


D. Pereira and A. Elfering Social Stressors, Sleep and Psychosomatic Complaints

However, the question of whether impaired sleep isan important intervening variable in the causal chainof occupational stressors and the development ofpsychosomatic health complaints in the long run canempirically only be answered by longitudinal studies(Meijman & Mulder, 1998). To extend research, weaimed to analyse the longitudinal effect of socialstressors at work on sleep and psychosomatic healthcomplaints and to test whether sleep quality mediatesthe effect of social stressors at work on the developmentof psychosomatic health impairments.

The present studyIn this study, we examined the longitudinal effects ofsocial stressors at work on sleep quality and onpsychosomatic health impairments and tested whethersleep quality mediated the positive effects of socialstressors at work on psychosomatic health impairments.

Sleep quality is a complex phenomenon that isdifficult to define and measure objectively (Buysse,Reynolds, Monk, Berman & Kupfer, 1989). Accordingto Åkerstedt et al. (2009), the impression from conferencediscussions is that it only exists as a subjective phenom-enon. However, despite the dominance of the subjectivecomplaints (i.e. complaints of long sleep latency or highamounts of wakefulness after sleep onset), there havebeen a number of attempts to define sleep qualityobjectively (Åkerstedt et al., 2009). To consider differentaspects, we used three different parameters to assess sleepquality objectively: sleep-onset latency, sleep efficiencyand sleep fragmentation. To further triangulate themeasure of sleep quality, we also measured subjectivesleep quality.

Our longitudinal actigraphy field study extendedexisting research by examining the neglected effect ofsocial stressors at work on various sleep qualityparameters and psychosomatic health impairments,and by examining whether sleep quality mediates therelationship of social stressors at work on psychosomatichealth complaints. In sum, we tested two hypotheses.Firstly, social stressors at work are positively related topsychosomatic health complaints (1a); to objectivelyassessed sleep quality, which comprises sleep-onsetlatency (1b), sleep efficiency (1c) and sleep fragmentation(1d); and to subjectively assessed sleep quality (1e). Theeffect of social stressors at work on psychosomatic healthcomplaints is mediated by objectively assessed sleepquality, which comprises sleep-onset latency (2a), sleep

Path a

Path c’ (Pa

Social stressors atwork

Sleep qu

Figure 1. Hypothesized mediation model


efficiency (2b) and sleep fragmentation (2c) and bysubjectively assessed sleep quality (2d) as shown inFigure 1.

Material and methodsTo test our hypotheses, we used a longitudinal actigraphyfield design. Therefore, we assessed social stressors atwork and psychosomatic health complaints at time 1(T1, baseline) and at time 2 (T2, 6weeks later).According to De Lange, Taris, Kompier, Houtman andBongers (2004), there is a lack of information aboutthe optimal length of time lags in occupational healthresearch. Dormann,Werner & Zapf (2006) andDormannand Haun (2009) reported results from a meta-analysison longitudinal studies within occupational stressresearch. Dormann et al. and Dormann and Haunestimated the optimal time lag by making assumptionson the stability of stressors and strains and concludedthat current time lags (their mean time lag within 79studies was 1.5 years) could and should be shortenedto 1–3months. Our time lag of 6 weeks is in the middleof this recommended range.

Objective and subjective sleep fragmentations weremeasured during two working weeks, from Mondayuntil Friday. Note that weekends were not included inthe analysis.

Participants and design

Participants were recruited via personal advertisement bytwo research assistants (snowball sampling). Potentialparticipants were contacted by telephone, by mail orpersonally and were provided some initial informationabout the study. After participants gave their consent toparticipate, survey packages were handed to them, whichincluded instructions about how and when to fill in thequestionnaires and about the use of the actigraphyassessment. In face-to-face meetings, the researchassistants instructed participants to fill in the first generalquestionnaire and then to return this questionnaire.Then, participants were instructed to wear the actigraphyassessment device continuously and to complete dailysleep diaries for two working weeks. One month afterconcluding the actigraphy and diary assessment, partic-ipants had to fill in the second general questionnaire. Atthe end of the study, the research assistants collected thediaries, the actigraph and the second general question-naire, and the participants were debriefed. As compensa-tion for participants’ time and to encourage participation,

Path b

th c)

Psychosomatichealth complaints

ality

45


we offered individual feedback about their work situationand well-being at the end of the study. Note that onlyparticipants who were working full time were includedin the study.

Materials

General questionnaires at T1 and T2

Before actigraphy assessment started, participantsfilled in a general questionnaire including questionsabout demographic background, e.g. gender and age,social stressors at work and psychosomatic healthcomplaints. After 6weeks, participants filled in the samequestionnaire again.

Social stressors with co-workers

Social stressors at work were measured by a scale ofFrese and Zapf (1987). The scale comprises itemsreferring to social climate at work and conflicts withco-workers. The instruction given to the participantswas as follows: ‘How has the social working climatebeen in general?’ The scale included items such as‘With some colleagues there is often conflict’, ‘Aroundhere, one gets reprimanded even for little things’,‘Some colleagues always assign the pleasant tasks’,‘When an error occurs, some colleagues always blameme’ and ‘One has to pay for the mistakes of others’.The items were scored on a five-point scale rangingfrom strongly disagree (1) to strongly agree (5). Internalconsistency at T1 was 0.80.

Psychosomatic health complaints

Ratings on psychosomatic health complaints weremade on a nine-item scale based on Mohr’s (1986)work. The instruction given to participants was asfollows: ‘How would you rate your health complaintsin the preceding 30 days?’ The items used were ‘gastro-intestinal problems’, ‘restlessness/nervousness’, ‘difficultiesin concentrating’, ‘lower back pain’, ‘neck pain’, ‘dizziness’,‘exhaustion’, ‘headaches’ and ‘heartburn’. The items werescored on a five-point scale ranging from rarely/none (1)to frequently/constantly (5). Internal consistency was 0.75at T1 and 0.80 at T2. The test–retest reliability was 0.71.

Sleep actigraphy

Heretofore, most studies analysing the effect ofoccupational stressors on sleep have assessed self-reported sleep quality. Self-reports are important,however, as studies relying solely on self-report forboth independent (e.g. stressors) and dependent (e.g.sleep) variables are able to underlie the problem ofcommon-method variance, which may lead to inflatedor even spurious correlations and predictions (Semmer,Grebner & Elfering, 2004). To avoid the problem ofcommon-method variance, we used both self-reportedsleep quality and more objective indicators of sleepquality. There aremanyways to assess objective indicatorsof sleep; heretofore, sleep evaluation in humans has

46

been usually performed with polysomnography (PSG).The PSG technique has been considered the goldstandard for detecting sleep impairments (De Souzaet al., 2003); however, during the last decade, actigraphy(activity-based monitoring) has also become anessential tool in sleep research and sleep medicine(Sadeh & Acebo, 2002). The term actigraphy refers tomethods of monitoring and collecting data generated bymovements using miniature computerized wristwatch-like devices. Through algorithms, the sleep quality canbe derived. A major strength of actigraphy comparedwith PSG is the ability to monitor sleep–awake patternscontinuously with minimal inconvenience over anextended period at home (Sadeh & Acebo, 2002).Actigraphy is a good way to provide a low-cost, non-invasive, objective and longitudinal method for thediagnosis of sleep disorders in an ambulatory setting(Kushida et al., 2001). A comparison of actigraphy withthe gold standard of PSG has yielded agreement ratesranging from 78% to 95% (Kushida et al., 2001).Furthermore, according to a study conducted byMorgenthaler et al. (2007), actigraphy is a valid way todetermine sleep patterns in normal, healthy populationsand in patients suspected of certain sleep disorders, andit should therefore be used more frequently in occupa-tional health research.

The actigraph used in the present study wasBodyMedia’s SensewearW armband (BodyMedia Inc.,Pittsburgh, PA). The Sensewear armband is a multi-accelerometer device similar to a regular actigraph.Every minute, twin-axis oscillometric sensors assess bodymovements, surface body temperature, galvanic skin re-sponse and heat flux. The collected data were analysedwith a BodyMedia software, which estimates phases ofbeing asleep and awake using computer algorithm-defined thresholds of activity, and thus, sleep qualitycan be derived (Littner et al., 2003). The algorithm cre-ated is based on the principle that there are reducedmovements during sleep phases and increased move-ment during phases of wakefulness (Sunseri et al.,2011). In a study by Germain, Buysse and Kupfer(2006), the algorithm correctly identified 93% of all sleepepochs and 83% of all wakefulness epochs, and thus, thealgorithm can be accepted as reliable.

Participants wore the armband on the non-dominantarm for two consecutive working weeks. The actigraphcould be removed when they took a shower. Otherwise,the actigraphs were worn continuously for 24-h periodswithout removal during two working weeks. Napsduring the day were not included in the analysis, sowe only included the data for recorded nights.

In our study, we used three objectively assessed sleepquality indicators, such as sleep-onset latency, sleepefficiency and sleep fragmentation. Following Pereiraet al. (2012), we coded sleep-onset latency as the timeparticipants needed to fall asleep after going to bed.Sleep efficiency was defined as the percentage of timespent asleep between sleep onset and last awakening



in the morning. Additionally, sleep fragmentation wascoded as the number of awakenings that lasted 5minor longer and that were preceded and followed by atleast 15min of uninterrupted sleep (also Sadeh, Keinan& Daon, 2004). We used the average of sleep-onsetlatency, sleep efficiency and sleep fragmentation duringthe two working weeks (i.e. from Monday to Friday).We controlled our data for inaccurate measures(participants taking off the actigraphs or malfunctionof the actigraphs) by evaluating visual graphs producedby the software and by evaluating the exported Exceltabs. Visual graphs were used to identify only rathercoarse consecutive loss of data that could easily bedetected by the eye. This first test helped to establishwhether any participants were not wearing the deviceand whether the device was not collecting data in acorrect manner (i.e. if the device has lost skin contact).In these cases, the whole night’s measurements werecoded as missing. Scattered single missing measurementsthat exceed 20% of the total measurements resulted inthe measurement being coded as completely missing.Thus, the mean scores across measurements were onlycalculated for participants with sporadic missingmeasurements below 20%.

Subjective sleep diaries

Every morning, self-reported sleep quality wasmeasured by a single item from the measure devisedby Buysse et al. (1989): ‘How would you evaluate thisnight’s sleep?’ The response format ranged from verybad (1) to very good (4). Self-reported sleep qualitywas coded as the average assessed during the twoworking weeks (i.e. from Monday to Friday).

Control variables

To obtain a better understanding of the role of socialstressors at work, we controlled our analyses for timepressure. Ratings on time pressure were made on afour-item scale based on that of Semmer, Zapf andDunckel (1995). The scale used statements such as‘How often are you pressed for time’, ‘How often mustyou miss or delay a break because of you having toomuch work to do’, ‘How often must you finish worklater because of having too much to do’ and ‘How oftenis a fast pace of work required of you?’ The items werescored on a five-point scale ranging from rarely/never(1) to very often (5). The internal consistency was

3.24**

.15 (.29

Social stressors atwork

Sleep Fragm

Figure 2. Bootstrap test of the indirect effect of social stressors at work o

**p< 0.01, *p< 0.05, one tailed


0.76. Because psychosomatic health complaints maydiffer depending on age and gender, we entered ageand gender as control variables in the analyses. Becausethe number of awakenings was likely to increasedepending on the time spent asleep (Pereira et al.,2012), we included sleep duration in the analysis toassess the number of awakenings in relation to totalsleeping time. To allow for potential causal interferences,we used a longitudinal actigraphy field design andcontrolled for psychosomatic complaints assessed at T1.

Ethics commission

The study was performed in accordance with therecommendations of the Declaration of Helsinki (WorldMedical Association, 2008) and was approved by thelocal ethics commission.

Procedure/analysis

To test our first hypotheses, we computed hierarchicallinear regression analyses with SPSS 19.0 (IBM Corpora-tion, Armonk, NY), regressing psychosomatic health com-plaints on chronic social stressors at work and on sleepquality. Psychosomatic health complaints at T1, age, gen-der and time pressure were entered in the first step, andthe predictor was entered in the second step. The media-tion hypothesis was tested with SPSS 19.0 using a boot-strap test of the indirect effects (Preacher & Hayes,2008). Preacher andHayes (2008) proposed bootstrappingbecause it is more robust in small samples than other ap-proaches to testing mediation. Bootstrapping, a non-parametric resampling procedure, is an additional methodadvocated for testing mediation that does not impose theassumption of normality on the sampling distribution.Bootstrapping is a computationally intensive method thatinvolves repeatedly sampling from the data set and esti-mating the indirect effect in each resampled data set. By re-peating this process thousands of times, an empiricalapproximation of the sampling distribution of the indirect(mediation) path is built up and is used to construct con-fidence intervals for the indirect effect.

ResultsAltogether, 81 potential participants were contacted.To be included in the study, participants had to meettwo criteria: they had to be full-time workers and beemployed in organizations constructed of teams ofsupervisors and colleagues. Seventy-five people agreed

.04*

*)

Psychosomatichealth complaints

entation

n psychosomatic health impairments via objectively assessed sleep.

47


to participate in the study (response rate = 92.59%).Fifteen participants were not included in the analysesbecause of missing data (e.g. they had not filled inquestionnaires or did not wear Sensewear armband).Our final sample consisted of 60 full-time employeesworking in a variety of Swiss industries (health care,finance and management); of this final sample, 35(58.3%) participants were female and 25 (41.7%) weremale. Participants were between 17 and 56 years of age(M= 34; SD= 12.3). Of our participants, 12% reportedhaving completed primary education, 48% reportedhaving completed secondary education and 40%reported having at least a bachelor’s degree, whereas73% of the participants had a permanent employmentstatus and 27% were temporarily employed.

Correlations

Means and standard deviations are presented in Table I.As can be seen in Table I, social stressors at work werepositively correlated with objective sleep fragmentation(r= 0.36, p< 0.01), with psychosomatic complaintsat T1 (r= 0.35, p< 0.01) and with psychosomaticcomplaints at T2 (r= 0.37, p< 0.01). Objective sleepfragmentation was negatively correlated with sleepduration (r=�0.24 p< 0.10), with psychosomaticcomplaints controlled for T1 (r=0.23, p< 0.10) and withsleep efficiency (r=�0.49, p< 0.01). Psychosomatichealth complaints at T2 were positively correlated withpsychosomatic complaints at T1 (r= 0.71, p< 0.01),indicating a high stability of psychosomatic healthcomplaints across the 6weeks.

Hierarchical linear regression

The final step-standardized coefficients of the hierarchicalregression analyses are presented in Table II. In line with

Table I. Descriptive statistics among the study variables

M SD 1 2 3

General measures (level 2)

1 Age 33.86 12.28 –

2 Sexa — — 0.25† —

3 Time pressure 3.09 0.74 0.07 0.16 —

4 Social stressors at work 1.53 0.40 �0.02 0.14 0.

5 Sleep fragmentation 9.72 3.23 �0.17 0.22 �0.

6 Sleep-onset latency 12.44 6.60 �0.15 0.09 0.

7 Sleep efficiency 67.40 20.74 �0.07 �0.08 0.

8 Sleep duration 382.24 51.57 �0.22† �0.30* 0.

9 Subjective sleep quality 3.13 0.38 �0.17 �0.27* 0.

10 Psychosomatic complaints at T1 2.05 0.61 �0.09 �0.09 0.

11 Psychosomatic complaints at T2 1.92 0.64 �0.20 �0.20 0.

12 Psychosomatic complaints at T2

controlled for T1

— — �0.16 �0.21 0.

Note.a0 = female, 1 =male (N= 60).

**p< 0.01, *p< 0.05, †p< 0.10, two tailed.

48

our first hypothesis, social stressors at work were related topsychosomatic health complaints (b=0.20, t(57) = 1.80,p< 0.05, ΔR2 = 0.03). Moreover, social stressors at workwere related to objectively assessed sleep fragmentation(b=0.36, t(57) = 2.73, p< 0.05, ΔR2 = 0.11). However,contrary to our expectations, social stressors at work werenot related to other sleep quality indicators. In summary,our first hypothesis was partially supported.

Mediation test

For our second hypothesis, we examined whether theeffect of social stressors at work on psychosomatic healthcomplaints is mediated by sleep quality. With age,gender, psychosomatic health complaints at T1, sleepduration and time pressure as covariates in the mediatoranalyses, the bootstrap test of the indirect effect of socialstressors at work via objectively assessed sleep fragmenta-tion showed an indirect effect (unstandardized regressioncoefficient B=0.15), which differed significantly fromzero (90% confidence interval = 0.0036–0.3662). Whensocial stressors at work increased by one scale point, theindirect effect of psychosomatic health impairmentsincreased by 4%, owing to an increase in sleep fragmen-tation. The significant mediation is also shown inFigure 2. Therefore, the inclusion of this mediatorreduced the effect of social stressors at work on psycho-somatic health impairments from 0.29 (path c inFigure 2, p= 0.05) to 0.15 (path c0 in Figure 2, ns). Thus,objectively assessed sleep fragmentation fully mediatedthe effect of social stressors at work on psychosomatichealth impairments.

Reverse causation

Even though we assumed that the relationship betweenwork and health is one directional, such that work

4 5 6 7 8 9 10 11 12

18 —

01 0.36** —

09 0.09 0.24 —

09 �0.05 �0.49** �0.37* —

20 �0.01 �0.24† 0.25† 0.26 —

20 �0.08 0.10 �0.09 �0.04 0.10 —

27* 0.35** �0.16 �0.15 0.15 0.19 �0.22 —

20 0.37** 0.04 �0.05 �0.04 0.09 �0.21 0.71** —

21 0.38** 0.23† �0.15 �0.15 0.09 0.22 — — —


Table

II.Hierarchicalreg

ressionestim

ates

formod

elsregressedon

social

stressorsat

work(hypothe

ses1a

–e)

Variables

Psychosom

aticcomplaints

Sleep-on

setlatency

Sleepefficiency

Sleepfragmentation

Subjective

sleepqu

ality

bΔR2

R2

bΔR2

R2

bΔR2

R2

bΔR2

R2

bΔR2

R2

Step

1:control

variables

0.49**

0.49**

0.06

0.06

0.22

0.22

0.17*

0.17*

0.15*

0.15

Sexa

�0.19†

0.16

0.03

0.23

†�0

.25†

Age

�0.07

�0.20

0.06

�0.30*

�0.12

Tim

epressure

�0.04

0.09

0.12

�0.07

0.29*

Psychosom

aticcomplaintsat

T1

0.56**

Objective

sleepdu

ration

�0.24†

Step

2:predictor

0.03

†0.52

†0.00

0.07

0.00

0.22

0.11**

0.29**

0.15

0.01

Socialstressorsat

work

0.20*

0.05

�0.02

0.36**

�0.09

Note.Betaweightsreferto

thefullmod

el.

a 0=female,1=male.

**p<0.01,*p

<0.05,†p<0.10.



stressors influence health at a later point in time, otherstudies have also mentioned a reverse causal relationshipin which health influences work characteristics at a laterpoint in time (De Lange et al., 2004). To obtain a betterunderstanding of the relationship between workcharacteristics and health, we also analysed the reversecausal relationship between work and health. The finalstep-standardized coefficients of the hierarchicalregression analyses indicated that psychosomatic healthimpairments at T1 were not significantly related tosocial stressors at T2 (b= 0.11, t(56) = 1.13, p> 0.10,ΔR2 = 0.01). Furthermore, no sleep quality parameterwas related to social stressors at T2. Thus, our resultsdid not provide evidence for a reverse causal relationshipbetween work characteristics and health, indicatingthat the effects of work characteristics on health werecausally predominant.

DiscussionThe goal of this study was to contribute to the literatureon recovery by examining the effects of social stressorsat work on several sleep quality parameters and onpsychosomatic health complaints by testing whether sleepquality is a mediator within a longitudinal actigraphy fieldstudy. Hierarchical regression analyses revealed that, evenafter controlling for time pressure, social stressors atwork were positively related to objectively assessed sleepfragmentation and to psychosomatic health complaints.Furthermore, the effect of social stressors at work onthe change in psychosomatic health complaints wasmediated by objectively assessed sleep fragmentation.Contrary to our expectations, however, social stressorsat work were not related to sleep-onset latency, sleepefficiency and subjectively assessed sleep quality duringfollow-up.

Our results provide further empirical evidence for theneed-to-belong theory (Baumeister & Leary, 1995).Accordingly, social stressors at work may represent athreat to the need to belong and cause health problemseven when time pressure is controlled for. Furthermore,our results are in line with those of Zapf and Frese (1991)and Dormann and Zapf (2002) who showed that socialstressors at work have a variety of negative effects onindividuals’ well-being and health.

Our results further show that social stressors at workplay an important role in the development of work-related loss of sleep quality (i.e. sleep fragmentation).Surprisingly, social stressors at work were found to bepredominantly related to sleep fragmentation, whereasa relationship between social stressors at work andsleep-onset latency, sleep efficiency and self-reportedsleep quality could not be found. Even though thisresult is surprising, it provides further empiricalevidence for a diary study in support of a diary studyconducted by Pereira et al. (2012) by showing thatsocial stressors at work are positively linked withobjectively assessed sleep fragmentation—but not withother sleep quality indicators. The current study goes

49


an important step beyond that of Pereira et al. (2012) bytesting the long-term association of sleep fragmentationon changes in individual health complaints. Accordingto Åkerstedt et al. (2009), the importance of sleepfragmentation has been established by several studiesas being related to the next day’s performance. Eventhough the exact mechanism has not been established,it appears that sleep fragmentation prevents restorativeeffects (Åkerstedt et al., 2009). An alternative explanationcomes from Wesensten, Balkin and Belenky (1999) whoreported in a review that sleep fragmentation systematicallyaffects recuperation because of the low-quality stage 1sleep, independently of total sleep time. Thus, we maysuppose that sleep fragmentation is a milder form ofsleep impairment, being initially largely unperceivedby individuals. Future studies should provide furtherempirical evidence of our result pattern and shouldcontribute to a better understanding of the underlyingmechanisms of the different sleep parameters.

According to our second hypothesis, the effect of socialstressors at work on psychosomatic health complaints wasmediated by objectively assessed sleep fragmentation. Thisresult is in line with that of Geurts and Sonnentag (2006),showing that poor sleep quality is an important interveningvariable in the causal chain of stressful work characteristicsand the development of psychosomatic health complaintsin the long term. Furthermore, according to the effortrecovery theory (Meijman & Mulder, 1998) and theallostatic load theory (McEwen, 2006), work stressorsmay lead to a cumulative process of persistent physiologicaland psychological load reactions, resulting in less transitoryor even permanent symptoms such as impaired sleepand psychosomatic complaints.

This is, to the best of our knowledge, the firstlongitudinal study that has simultaneously investigatedthe relationship between social stressors at work,objectively assessed sleep quality and psychosomatichealth complaints.

Study advantages and limitations

Our study has some advantages worthy of beingreported. One major advantage of our approach is theuse of a longitudinal design, combining data fromdifferent sources. In conducting longitudinal studiesand by controlling for T1, the inference of causality isstronger than in cross-sectional studies. A secondadvantage is the use of a combination of data fromdifferent sources, namely, questionnaire self-report dataand physiological data. By combining data from differentsources, we avoided the problem of common-methodvariance in the assessment (Semmer et al., 2004).

However, there are a number of limitations of ourstudy that should be noted. Firstly, methodologicalconsiderations regarding the use of actigraphy datashould be taken into account. The use of actigraphyhas become an essential tool in sleep research and sleepmedicine (Sadeh & Acebo, 2002). However, some sleepresearchers have warned of the possible major limitations

50

of the data obtained. They particularly call into questionthe reliability and validity of the actigraphy data gathered(Sadeh & Acebo, 2002). Even though the validity of theBodyMedia Sensewear armband has been shown in thelaboratory (Lotjonen et al., 2003), further validation ofSensewear actigraphy in naturalistic settings is needed.In a recent study, however, Kawada et al. (2011) comparedSensewear-detected rotational body movements at nightwith video recordings and showed 72% agreementwithout systematic deviation with equal percentagesof undetected movements (15%) and false-positivedetection of movements (14%). Moreover, a recentstudy byWouwe, Valk and Veenstra (2011) also showedSensewear armbands to be sensitive, accurate andspecific. Nevertheless, further validation of the actigraphydata is needed. It is also worth noting that the focus of thepresent study was on occupational stressors. Within thecontext of sleep research, the more precise measurementof sleep quality should also include PSG to measureshort-duration sleep disruption in future studies.

Secondly, our participants had higher educationthan the average in Swiss society, and according toprevious research, people with higher education andoccupational status report better health (Mackenbach,Kunst, Cavelaars, Groenhof & Geurts, 1997; Winkleby,Jatulis, Frank & Fortman, 1992) and better workconditions (e.g. fulfilling, subjectively rewarding jobsand higher levels of social support; Ross & Wu, 1995).Of particular importance for the present study is thatpeople of high occupational status report a lowprevalence of social stressors at work. The results ofthe descriptive statistic confirmed this assumption;our participants reported low levels of social stressorsat work, low sleep quality impairments and low levelsof psychosomatic complaints. This shows that manyparticipants presumably did not experience socialstressors at work, but despite this restriction in variation,the association with sleep fragmentation was found.Overall, this may have led to an underestimation in thecurrent study of the true relation between social stressorsat work and sleep fragmentation. Thus, the restriction inthe range of participants may be a core reason why wedid not find other links between social stressors at workand sleep parameters.

Thirdly, we reported results acquired from a relativelysmall sample size. According to Field (2005), the size ofthe sample used is very important in obtaining reliableresults. Furthermore, the results achieved with smallsamples suffer from power problems and population bias.The small sample size may have lead to an underestima-tion of the results, therefore contributing to the non-significant relationship between social stressors at workand sleep-onset latency, sleep efficiency and self-reportedsleep quality.

Practical implications and conclusion

Our results suggest that social stressors at work areantecedents of impaired sleep quality (increased



fragmentation) and increased psychosomatic healthcomplaints. According to Åkerstedt et al. (2009), pooror shortened sleep is related to fatal accidents at work,and reduced performance. Furthermore, according toBrosschot and Van Der Doef (2006), psychosomatichealth complaints are associated with high costs,taking into account the involved medical actions,sick leave compensation and loss of productivity.


Thus, to prevent the long-term negative effects onpsychosomatic health, social stressors at work shouldbe prevented, or at least minimized. In addition,social support from supervisors and colleaguesshould be increased. According to Dormann andZapf (1999), social support can provide a bufferfor the negative effects of work-related social stressorson health.

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