AbstractObjectives EVort-recovery theory (Meijman andMulder in Handbook of work and organizational psy-chology, Psychology Press/Erlbaum, Hove, pp 5–33,1998) proposes that eVort expenditure may haveadverse consequences for health in the absence of suY-cient recovery opportunities. Thus, insight in the rela-tionships between eVort and recovery is imperative tounderstand work-related health. This study thereforefocused on the relation between work-related eVortand recovery (1) during workdays, (2) in-betweenworkdays and (3) in the weekend. For these three timeperiods, we compared a group of employees reportingrelatively low levels of work-related eVort (“low-eVortgroup”) and a group of employees reporting relativelyhigh levels of work-related eVort (“high-eVort group”)with respect to (1) activity patterns, (2) the experienceof these activity patterns, and (3) health and well-beingindicators.Methods Data were collected among university staVmembers. Participants (Nhigh-eVort group = 24 and Nlow-
eVort group = 27) completed a general questionnaire andtook part in a 7-day daily diary study covering Wveweekdays and the following weekend. DiVerencesbetween the two eVort-groups were examined bymeans of analysis of variance.
Results Compared to the low-eVort group, the high-eVort group (1) engaged less often in active leisureactivities during the week and worked more overtimein the weekend, (2) considered both work and homeactivities as more eVortful, but not as less pleasurable,and (3) reported higher levels of sleep complaints(weekdays only) and fatigue, more preoccupation withwork (weekdays only) and lower motivation to startthe next workweek during the weekend.Conclusions Work-related eVort is associated withvarious aspects of work time and (potential) recov-ery time in-between workdays and in the weekend.High levels of work-related eVort are associatedwith activity patterns that are less beneWcial in termsof recovery, with higher eVort expenditure duringand after work time, and with diminished health andwell-being.
Keywords EVort · Recovery · Diary study · University staV
Introduction
Much research has shown that high levels of jobdemands are related to increased levels of physical andpsychological health problems across time (e.g., DeLange et al. 2003). Despite this strong focus on therelations between job demands and health, relativelylittle attention has been paid to the psychological andphysiological processes that may explain why health isadversely aVected by high job demands. One notableexception is eVort-recovery (ER) theory (Meijman andMulder 1998; Geurts and Sonnentag 2006). ER theoryargues that working inevitably requires eVort as an
M. L. M. van HooV · S. A. E. Geurts · M. A. J. Kompier · T. W. TarisDepartment of Work and Organizational Psychology, Radboud University , Nijmegen, The Netherlands
M. L. M. van HooV (&)TNO Quality of Life, P.O. Box 718, 2130 AS Hoofddorp, The Netherlandse-mail: [email protected]
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appeal is made to workers’ abilities and their willing-ness to dedicate these abilities to the work task.Expending eVort at work (“work-related eVort”) pro-duces two kinds of outcomes: the tangible result ofwork activities, i.e. a product or service, and the psy-chological and physiological “costs” or load reactions(e.g., fatigue) associated with working. These loadreactions are usually short-lived and reversible: theydisappear after respite from work. However, undercertain circumstances the recovery process may beinsuYcient or inadequate, and then short-term work-related load reactions may turn into adverse and morechronic health problems, such as prolonged fatigue,chronic tension, and sleep deprivation (Åkerstedt2006; Härmä 2006; Sluiter et al. 2001; Van HooV et al.2005).
Recovery opportunities after work may be inade-quate in terms of quantity (time) and/or quality.Recovery time may be insuYcient in case of pro-longed exposure to high demands, for instance, whenworkers continue to pursue job-related activities dur-ing non-work time (e.g., by working overtime) orengage in other demanding (e.g., domestic) activities.Recovery is particularly at stake when during privatetime an appeal is made upon the same psychophysio-logical systems that were activated on the job. Thequality of recovery may be endangered when individ-uals’ psychophysiological systems show prolongedactivation even if not exposed to any special demandsduring the recovery period. This may happen whenworkers have diYculty to relax at home after a stress-ful working day. For example, Brosschot et al. (2005)showed that when workers worry in their private timeabout the past or upcoming working day, the psycho-physiological systems that were activated on the jobremain activated, thus impeding the recovery process(cf. Ursin and Erikson 2004). Due to repeated or pro-longed activation of psychophysiological systems,these systems are in danger of chronic overactivity,producing lasting changes in homeostatic mechanisms(i.e., allostatic load, McEwen 1998). Consequently,these originally adaptive systems may start to mal-function by showing either hyperactivity (the systemsfail to shut-oV) or hypoactivity (the systems are notturned on when needed), constituting a serious healthrisk. For example, chronic stress may cause theimmune system to be not sensitive enough (hypoac-tivity), allowing infectious agents (viruses and bacte-ria) to enter the body and cause infectious diseases.Alternatively, the system may become overreactiveso that the immune system itself causes ill health(such as autoimmune diseases and allergic diseases,Clow 2001).
The present study
EVort and recovery are nowadays salient research top-ics (Zijlstra and Sonnentag 2006). The present studybuilds on and extends this body of knowledge in atleast four regards:
Firstly, although the eVort-recovery process isassumed to unfold on a daily basis, there is only a lim-ited number of studies examining this process fromsuch a day-to-day perspective (e.g., Cropley et al. 2006;Meijman et al. 1992; Rook and Zijlstra 2006; Sonnen-tag 2001; Sonnentag and Zijlstra 2006; Totterdell et al.1995). The majority of research in this area still focuseson either cross-sectional or on global long-term rela-tions between job demands, lack of recovery andhealth (e.g., Kompier 1988; Sluiter et al. 2001). Thus, inorder to obtain more insight in de day-to-day relationsbetween eVort and recovery, the present study exam-ines the relation between work-related eVort andrecovery on a daily basis, both during and after work-ing time.
Furthermore, although weekends may oVer impor-tant opportunities for recovery, they are hardlyincluded in previous studies. Exceptions are Fritz andSonnentag’s (2005) diary study, which showed thatwell-being after the weekend was higher when individ-uals had engaged in social activities during the week-end. Also, Totterdell et al. (1995) reported that sleep,mood and social satisfaction were worse on the Wrstrest day following work shifts in comparison with sub-sequent rest days. In a study among shift-workingnurses, Rook and Zijlstra (2006) found weekends to beimportant for recovery as well. To increase the under-standing of the weekend as potential recovery period,the present study also included the weekend.
Thirdly, only limited attention has been given toactual activity patterns during work and non-work timein research on eVort and recovery until now (see forexceptions: Fritz and Sonnentag 2005; Sonnentag 2001;Sonnentag and Bayer 2005). This is remarkable, as sev-eral work psychological theories (e.g., action theory,Frese and Zapf 1994; Taris and Kompier 2005) assumethat job characteristics aVect worker well-beingthrough worker behavior: it is what people do thatmakes them feel tired or enthusiastic. Thus, in order tofully understand eVort-recovery patterns during and in-between workdays, we must know how people spendtheir time on work as well as on home activities. There-fore, the present study provided a detailed assessmentof employees’ activity patterns during and in-betweenworking time.
Finally, what can be a burden for one individualmay constitute a pleasure to the other. Consequently,
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insight in activity patterns in the work and privatedomain is insuYcient to fully understand workers’eVort-recovery patterns, and preferably workers’ expe-rience of the time spent on (non)work activities mustbe examined in this context (see also the recommenda-tions by Sonnentag 2001). Until now, the extent towhich workers experience their daily work and homeactivities as eVortful and/or pleasant has nonethelessremained largely ignored. Therefore, the present studyprovided a detailed assessment of how employeesexperience their activities during and in-between work-ing time in terms of eVort and pleasure.
We distinguished between workers who reported arelatively high level of work-related eVort (i.e., whogenerally experienced their workdays as eVortful)during a standard work week (further referred to asthe “high-eVort group”) and workers who reported arelatively low level of work-related eVort (“low-eVortgroup”). This division of our sample was employedin order to maximize the contrast between the twosubgroups in terms of reported eVort. The two eVort-groups were compared with respect to (1) activity pat-terns (i.e., the time spent on/frequency of engaging inwork activities, domestic activities, active leisure, andpassive leisure), (2) experiences of activities (i.e., thespeciWc eVort and pleasure experienced while engagingin a speciWc work or home activity), and (3) health andwell-being indicators (i.e., fatigue, sleep quality, sleeptime, preoccupation with work, and work motivation).Fatigue is included an indicator of (lack of) recovery.As sleep provides the most “natural” recovery opportu-nity for humans, sleep quality and sleep time are incor-porated as well (Åkerstedt 2006). Preoccupation withwork is assessed, because it may prolong physiologicalactivation and therefore interfere with the recoveryprocess (Brosschot et al. 2005). Finally, to avoid focus-ing exclusively on the “negative” consequences ofworking, work motivation is added in this study toacknowledge that work may be related to positiveaspects of worker behavior as well. These constructswere measured in three time periods: (1) during worktime, (2) in-between successive workdays, and (3) dur-ing the weekend. In order to minimize the amount oftime elapsed between the occurrence and the reports ofa certain activity or experience, we utilized a diarydesign covering Wve uninterrupted weekdays directlyfollowed by two weekend days. In this vein, the risk ofretrospection bias was reduced (Bolger et al. 2003).
This study examines three interrelated researchquestions:
1. How is work-related eVort associated with (a) timespent on work activities, (b) experiences of work
activities, and (c) health and well-being during theworkday?
As the distinction between the two groups is based onemployees’ reports of work-related eVort, we expectthat the high-eVort group will also report to haveexpended higher eVort on (at least some of) the speciWcwork activities compared to the low-eVort group(Hypothesis 1a). Support for this hypothesis is importantfrom the perspective of validation of the eVort-measureused to diVerentiate between the two eVort-groups.
As the high-eVort group should have invested higherlevels of eVort during the work day than the low-eVortgroup, we expect to observe higher levels of fatigue atthe end of the workday (Hypothesis 1b) as well as a(stronger) increase in fatigue during the workday(Hypothesis 1c) in the Wrst group. We do not holda priori expectations concerning the experiences of plea-sure associated with work activities and with respect tothe time spent on and the frequency of engaging ineach work activity.
2. How is work-related eVort associated with (a) timespent on home activities, (b) experiences of homeactivities, and (c) health and well-being in-betweensuccessive workdays?
We distinguish among four categories of home activi-ties, i.e. (1) domestic activities (e.g., householdchores), (2) overtime work, (3) active leisure activi-ties (e.g., exercising), and (4) passive leisure activities(e.g., reading for pleasure, watching TV, listening tomusic; see also Sonnentag 2001). The latter categoryis considered as “passive”, whereas the other threecategories of activities demand eVort to some extent,and are therefore labeled as “active”. Based on ERtheory, it can be argued that our capacity to expendeVort is limited, and that the more eVort is expendedat work, the less remains for home activities. Accord-ingly, the high-eVort group is expected to spend lesstime on and to engage less often in active home activities,and consequently, will spend more time on and engagemore often in passive leisure activities (Hypothesis2a). Because of the supposed limited amount ofenergy left in the high-eVort group, we further expectthat this group will experience engagement in activehome activities as more eVortful relative to the low-eVort group (Hypothesis 2b). As we do not havea priori expectations regarding diVerences betweenthe groups in the pleasure experienced in home activ-ities, possible diVerences are examined in an explor-atory fashion.
Further, we expect that those who have expended higheVort on the job (high-eVort group) will report higher lev-els of fatigue and more sleep complaints in-between
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workdays compared to the low-eVort group (Hypothe-sis 2c). In order to obtain a full picture of the partici-pants’ recovery in-between workdays, sleep time is alsoexamined. Finally, we assume that workers who haveexpended higher eVort during working time, will alsobe more preoccupied with their job after work(Hypothesis 2d). This expectation is in line with Son-nentag and Bayer’s (2005) Wnding that those who expe-rienced high workload during the workday found itmore diYcult to detach from work during eveningsthan others. We do not formulate a priori expectationsregarding possible diVerences in work motivationbetween the two eVort-groups.
3. How is work-related eVort associated with (a) timespent on home activities, (b) experiences of homeactivities, and (c) health and well-being during theweekend days?
The hypotheses formulated for the period in-betweenworkdays (in “Research question 2”) can be extendedto the weekend. Hence, we expect that those who havespent high eVort on the job during week days (the high-eVort group), will—during the weekend—spend lesstime on and engage less often in active and will spendmore time on and will engage more often in passivehome activities (Hypothesis 3a), experience activehome activities as more eVortful (Hypothesis 3b),report more fatigue and more sleep complaints duringthe weekend (Hypothesis 3c), and will be more preoc-cupied with the upcoming workweek, than the low-eVort group (Hypothesis 3d).
Method
Participants and procedure
This study was conducted in two stages among aca-demic staV members of a medium-sized Dutch univer-sity. Of the 696 employees who were tenured andworked at least 3 days a week, only those could partici-pate who (1) did not have a job outside this university(to keep the variation in work activities within accept-able limits), and (2) lived with a partner who worked atleast 2.5 days a week (to increase the likelihood thatthe participants fulWlled at least some home obliga-tions). Of the 146 employees who agreed to participate,133 (19%) completed a general questionnaire (Wrststage of the study). Data from 13 of these 133 wereremoved, as they apparently did not meet one or bothof the selection criteria. To already reduce the inXu-ence of one possible confounder (i.e., working hours)of the associations between work-related eVort and the
variables of interest, this study was restricted toemployees who worked at least 32 contractual hours aweek. As a result, our sample comprised 93 employees(69.6% male; 67.7% ¸1 child living in the household;Mage= 45.0 years, SD = 7.6; 49.5% was assistant profes-sor, 16.1% associate professor, 12.9% full professor,21.5% other jobs, e.g. researcher or lecturer). Due tostrict privacy regulations, we did not know how manyof the employees that were approached for participa-tion in the study actually met our inclusion criteria (i.e.had no job outside the university and lived togetherwith a partner who worked at least 2.5 days a week).Therefore, we do not have insight in how manyemployees were in fact eligible for participation in thestudy, meaning that the overall response rate and therepresentativeness of our sample are unknown.
In the second stage of this study starting about ten daysafter the completion of the general questionnaire, thedaily variables of interest were assessed by means of shortquestionnaires that were completed three times a day,from Monday to Sunday: (1) a morning questionnaire (tobe completed after awaking in the morning, between 7:30and 8:30 a.m.), (2) an afternoon questionnaire (to be com-pleted around 6 p.m.), and (3) an evening questionnaire(to be completed before bedtime, between 10 and 11p.m.). Only diaries that were completed within an accept-able time range around the requested time were includedin the Wnal database. We thus removed morning question-naires that were completed more than 2 h after awaken-ing; afternoon questionnaires that were completed before4:30 p.m., after 8 p.m., or less than 3 h after the morningquestionnaires; and evening questionnaires that wereWlled in less than 2 h after the afternoon questionnaire orafter 3 a.m. This procedure resulted in 76.2% valid morn-ing diaries, 73.4% valid afternoon diaries, and 72.5% validevening diaries.
Variables derived from the general questionnaire (general measures)
Job types included “assistant professor”, “associate pro-fessor”, “full professor”, and “other”, such as researcherand teacher. Age was measured in years; Gender wascoded as “0” for “male” and “1” for “female”. Parentalstatus was coded as “0” for having no children living inthe household and “1” for having at least one childliving in the household. The last three variables arepotential confounders in the relationships of interestand are therefore included as covariates in furtheranalyses.
General fatigue was assessed with the ten-itemfatigue assessment scale (Michielsen et al. 2003). Anexemplary item is “I am bothered by fatigue” [1
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“(almost) never”, 5 (almost) always”], with higherscores reXecting higher levels of fatigue (� = 0.86).
Work engagement was measured with Wve itemsadapted from Rothbard (2001). An example is “WhenI am working, I often lose track of time” (1 “stronglydisagree”, 5 “strongly agree”; � = 0.78).
Job pressure was measured with Wve items from thejob content questionnaire (Karasek 1985), that wererephrased as questions [e.g., “Do you have to workvery fast?” 1 “(almost) never”, 4 “(almost) always”;� = 0.74].
Job control was measured with six items from VanVeldhoven et al. (2002). An exemplary item is: “Canyou take a short break if you feel this is necessary?” [1“(almost) never”, 4 “(almost) always”; � = 0.67].
Social support from colleagues [e.g., “My colleaguesshow their appreciation for the way I do my job”, 1“(almost) never”, 4 “(almost) always”; � = 0.86], andSocial support from supervisor [e.g., “My supervisorshows her/his appreciation for the way I do my job”, 1“(almost) never”, 4 “(almost) always”; � = 0.90] wereboth measured with four items adapted from Geurtset al. (1999).
Positive aVect and negative aVect were measured bymeans of the positive and negative aVect schedule(PANAS; Watson and Clark 1988). Following Roth-bard (2001), we distinguished between positive andnegative aVect regarding work and positive and nega-tive aVect regarding family. Sample items for negativeaVect are “upset” and “distressed”, and examples forpositive aVect are “enthusiastic” and “proud” (1 veryslightly or not at all, 5 extremely), with higher scoresindicating higher negative or positive aVect (negativeaVect: Cronbach’s � = 0.83 for work and 0.84 for home;positive aVect: Cronbach’s � = 0.87 for work and 0.90for home).
Life events Participants could report for ten events(e.g., birth of a child, Wnancial troubles, change of job)whether or not they had experienced this event duringthe past year. The number of events experienced wassummed.
Measures derived from the daily questionnaires (daily measures)
To limit the participants’ burden, the questionnairescontained a combination of validated scales as well assingle-item report-marks.
Work-related eVort
In the afternoon questionnaire, participants wererequested to indicate with a report mark the extent to
which they considered the preceding workday as eVort-ful (1 “not at all”, 10 “extremely”).
Activities
Time spent daily on work activities
Participants received a list of 13 major work activitiesand indicated the time (0 “none”, 1 “<1 h”, 2 “1–2 h”,..., and 7 “>6 h”) they had spent on each activityduring regular work time, i.e., until 6 p.m. (afternoonquestionnaire), and during nonwork time, i.e., after 6p.m. (evening questionnaire). We recoded this timerange to obtain an estimate of the actual time in hoursby assuming that the actual time spent on an activitywould lie halfway the two extremes (e.g., the category“<1 h” was recoded as “0.5”). Time spent on researchactivities by day comprised the time spent on “conduct-ing research”, “data-analysis”, “reading specialist liter-ature”, and “writing papers” (until 6 p.m.). Time spenton teaching activities by day included the time spent on“preparing a lecture”, “giving a lecture”, “reading(Ph.D.) students’ assignments”, and “appointmentswith (Ph.D) students” (until 6 p.m.). Time spent onadministrative activities by day consisted of time spenton “preparing a meeting”, “attending a meeting” and“e-mail/phone”. The category “informal contact withcolleagues” was entered in the analyses separately. A13th activity, “other”, was not incorporated in furtheranalyses, as on average only 0.42 h were devoted dailyto these activities. All work activities are potentiallyrelevant to all participants as in the Netherlands lectur-ers also have some research time, and researchers willusually also teach.
Overtime work was computed by summing the timespent on all 13 work activities after 6 p.m. (this univer-sity did not oVer evening classes) during weekdays, andby summing the total time spent on work activitiesbefore and after 6 p.m. on Saturday and on Sunday.
Time spent daily on home activities
Participants indicated in both the afternoon (until 6p.m.) and evening questionnaires (from 6 p.m.) theamount of time they spent that day on ten categoriesof home activities (largely based on those used inSonnentag’s (2001) diary study). Answer possibilitiesand recoding procedure were identical to those usedfor work activities. To ease interpretation of the cate-gories, participants received examples of activities ineach category. Time spent on domestic activities wascalculated by summing the total time (i.e., before andafter 6 p.m.) devoted each day to “household activi-
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ties”, “doing odd jobs in or around the house”, “doingthe groceries”, “care giving activities” and “business-like activities”. Time spent on active leisure activitiescomprised the total time spent daily on “physicalactivities”, “creative activities” and “social activi-ties”. The total time spent on passive leisure activitieswas computed by summing the time devoted to theseactivities (e.g., reading for pleasure, watching TV, lis-tening to music) before and after 6 p.m. The tenthcategory, “other”, was omitted from further analysisas the mean time spent on these activities rangedfrom only 0.15 h on Saturday to 0.21 h during week-days.
Experiences
Participants indicated for each engaged work andhome activity, the extent to which they considered itas eVortful and as pleasant (1 “not at all”, 10“extremely”). An estimate of the average daily eVortand pleasure for each category of activities wasobtained by computing a weighted mean score. Thus,the summed product of hours spent on each activitywithin a category and the eVort (pleasure) experi-enced while executing the activity was divided by thetotal hours spent on the activities in the respectivecategory. By employing such a weighted score, thetime spent on an activity is controlled for, assuringthat the eVort (pleasure) score really reXects eVort(pleasure).
Health and well-being
Fatigue at work (weekdays’ afternoon questionnaire)was measured with eight items adapted from Van Vel-dhoven et al. (2002), for example “I felt tired mentally”(1 “not at all”, 10 “extremely”). Participants rated eachitem twice: (1) with respect to the Wrst hour of theworkday (Cronbach’s � = 0.87) and (2) with respect tothe last hour of the workday (Cronbach’s � = 0.86).
Fatigue was measured in the morning, afternoonand evening questionnaires. Participants rated theircurrent state of fatigue (“How fatigued do you cur-rently feel?”) with a report mark varying from “1”(“not at all”) to “10” (“extremely”).
Sleep complaints (each morning questionnaire)were assessed using a Wve-item sleep quality scale (VanVeldhoven et al. 2002), slightly adapted to make it suit-able for day-to-day measurement. An exemplary itemis: “Last night I woke up several times” (1 “yes”, 0“no”, � = 0.73 across all seven consecutive days). Notethat each day’s values for this scale refer to the previ-ous night.
Sleep time (each morning questionnaire) was com-puted by calculating the self-reported number of hoursin-between the time they went to sleep last night(“what time did you go to sleep last night?”) and thetime they woke up this morning (“what time did youwake up this morning?”). Again, each day’s values forthis scale refer to the previous night.
Preoccupation with work (each morning question-naire) was assessed with one self-developed item: “Iam already mentally involved with the things I have todo at work today [next week]” (1 “not at all”, 5“extremely”).
Work motivation (each morning questionnaire)regarding the upcoming workday (during weekdays) orthe next workweek (during weekend-days) wasassessed with one self-developed item: “I feel likestarting the next workday [workweek]” (1 “not at all”,5 “extremely”).
A table with correlations between the study vari-ables can be obtained from the Wrst author on request.
Figure 1 gives an overview of the measurementstructure.
Creation of the two eVort-groups
The global report mark for work-related eVort asassessed in the afternoon questionnaire was used tocreate the two eVort-groups. A workday was labeledas eVortful if a report mark of six or higher was given.The number of eVortful workdays was summed foreach participant to obtain an estimate of how eVortfulhe/she considered the workweek. To increase reliabil-ity only participants who gave a report mark during atleast three out of the Wve possible workdays wereselected, resulting in a Wnal sample of 72 of the 93original participants. The low-eVort group (n = 27;MeVort = 3.39) consisted of participants who consid-ered none (out of three) or only one workday (out offour or Wve) as eVortful (>6). The high-eVort group(n = 24; MeVort = 6.77) included participants wholabeled two or three (out of three), three or four (out offour) or four or Wve (out of Wve) workdays as eVortful.
Statistical analyses
Data were analyzed by means of (M)ANCOVA, whichallows the examination of relationships between a cat-egorical independent variable (the eVort-subgroups)and continuous dependent variables (Maxwell andDelaney 2005). Gender, age, number of children in thehousehold and number of contractual work hours (32or more) were included as covariates in the analyses,because these may aVect the relationships between
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work-related eVort and the other variables of interestin this study. One key assumption of MANCOVA isthat the criterion variables are multivariately nor-mally distributed (Maxwell and Delaney 2005). Toexamine whether this assumption could be main-tained, the distributions of the criterion variableswere inspected for univariate normality, both for thetotal sample and for the low and high eVort sub-groups. The skewness of the criterion variables wasfor 61 out of 64 variables in the study lower than 1.00.As this number is already expected on basis ofchance, this Wnding suggests that the assumption of amultivariate normal distribution of the criterion vari-ables could be maintained for practical purposes.
Results
Preparatory analyses
Table 1 shows the descriptive statistics for the generalmeasures for the total sample as well as for the twoeVort groups. The total sample can be characterized asmiddle-aged, rather engaged, and not very tired. Themean level of fatigue in the sample does not signiW-cantly diVer from that in a heterogeneous sample of1,123 employees (M = 1.97, SD = 0.57, T(1214) = 1.29,ns; Geurts et al. 2005). Participants report relativelyhigh levels of work pressure and job control. Levels ofjob control are higher than those in a heterogeneous
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sample of 1,740 employees (M = 2.54, SD = 0.63,T(1831) = ¡10.29, P < 0.001; Geurts et al. 2005).
To investigate possible diVerences in the compositionof the two eVort-groups, these groups were comparedwith respect to the general measures. No signiWcantdiVerences were observed regarding age (T = 1.27,df = 49, ns), gender (�2 = 0.07, df = 2, ns), parentalstatus (�2 = 0.14, df = 1, ns), job type (�2 = 1.43, df = 3,ns), general fatigue (T = ¡1.00, df = 49, ns) and workengagement (T = ¡0.72, df = 49, ns). Also, theMANOVA executed with respect to job characteristics(job pressure, job control, social support from col-leagues and supervisor) was not signiWcant, F(4,45) = 0.98, ns. Furthermore, the groups report compa-rable levels of positive and negative aVect (work:T(49) = ¡0.71, ns; family: T(49) = ¡0.13, ns) and posi-tive aVect (work: T(49) = ¡0.39, ns; family: T(49) =1.01, ns). Finally, the two eVort-groups did not diVersigniWcantly regarding the number of life events experi-enced (T(49) = ¡0.29, ns). Thus, in sum, there were nosigniWcant diVerences between the two eVort-groupswith respect to the general measures.
DiVerences between Saturday and Sunday
Preliminary analyses showed that the variables understudy did not diVer signiWcantly between Saturday andSunday (F-values ranged from F(1, 27) = 0.00, ns foreVort reported for active leisure, to F(1, 8) = 1.95, nsfor eVort reported for overtime work). Therefore, fur-ther analyses are based on mean scores across the twoweekend days.
Research question 1
Table 2 presents the means, standard deviations and F-statistics for the daily variables for the total sample andfor each of the two eVort-groups. As to work activities,two analyses were conducted. First, for each partici-pant the percentage of days on which time was spenton each work activity was computed. MANCOVArevealed that these percentages did not diVer signiW-cantly between the two eVort-groups. Secondly, foreach participant we computed the mean time theyspent daily on each work activity across the Wve week-days. Again, MANCOVA did not reveal any signiW-cant diVerence between the two eVort-groups. Thus,the two eVort-groups did not diVer signiWcantly in theirwork activity patterns during the workday.
To study possible diVerences in experiences, twoMANCOVA’s were conducted, both based on meanscores across the Wve workdays. The Wrst analysisrevealed that the two eVort-groups diVered signiW-
cantly in the average amount of eVort reported withrespect to the four work activities. Univariate testsshowed that the high-eVort group experienced eachactivity as more eVortful (Hypothesis 1a supported).The second analysis revealed that the two eVort groupsdid not diVer signiWcantly with respect to the pleasurethey derived from their work activities.
Possible diVerences between the two eVort-groupsin fatigue at work were examined in a 2 (Time: Wrsthour vs. last hour) £ 2 (Group: low vs. high eVort)repeated-measures ANCOVA. The development offatigue during the workday diVered signiWcantly betweenthe two eVort-groups (signiWcant time £ group interac-tion). Post-hoc analyses showed that there were nosigniWcant diVerences between the two groups in theirlevel of fatigue during the Wrst hour of the workday(T = ¡1.20, df = 49, ns). However, the high-eVortgroup reported a signiWcantly higher mean level offatigue during the last hour of the workday (T = ¡2.66,df = 49, P < 0.05), indicating that the high-eVort groupreported more fatigue at the end of the workday(Hypothesis 1b supported), and showed a strongerincrease in fatigue (Hypothesis 1c supported) duringthe workday.
In sum, the participants in the two eVort-groups donot engage in diVerent types of work activities, nor dothey experience their work activities diVerently in termsof pleasantness. However, the high-eVort group reportsto spend signiWcantly more eVort on each of the workactivities, experiences signiWcantly higher work-relatedlevels of fatigue at the end of the work day, as well as astronger increase in fatigue during the workday.
Research question 2
Means, standard deviations and F-statistics are pre-sented in Table 3. As to home activity patterns, twoanalyses were performed. First, for every participant,we computed the percentage of workdays they spenttime on each type of home activity (domestic, activeleisure, overtime work, and passive leisure). For eachof these activities, an ANCOVA was conducted.Results showed that the groups only diVered signiW-cantly with respect to active leisure activities: whereasthe high-eVort group spent on less than half of thework days (43%) time on this type of activities, thelow-eVort group spent on more than half of the workdays (62%) time on this type of activities. Secondly, weconducted four ANCOVA’s based on each partici-pant’s mean time spent daily on each of the four activi-ties during the Wve weekdays, but these revealed nodiVerences between the two eVort-groups. Theseresults provide partial support for Hypothesis 2a by
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showing that participants in the high-eVort groupengage on average less often in active leisure activities.
In order to investigate possible diVerences in theirexperiences of home activities, two MANCOVA’swere computed, both based on mean scores across theWve weekdays. The Wrst analysis showed an overall sig-niWcant diVerence between the two eVort-groups in theextent to which they considered home activities aseVortful. Univariate tests demonstrated that the high-eVort group considered active leisure activities andovertime work as more eVortful (Hypothesis 2b sup-ported). The second analysis revealed that the twoeVort-groups did not diVer signiWcantly as to their plea-sure regarding their home activities.
Regarding health and well-being, three analyseswere conducted, each based on mean scores acrossthe Wve workdays. For fatigue, a 3 (time: morning vs.
afternoon vs. evening) £ 2 (group: low vs. high eVort)repeated-measures ANCOVA indicated that fatiguedid not vary signiWcantly as a function of time. How-ever, the two eVort-groups did diVer signiWcantly intheir average level of fatigue (main eVect of Group).Post-hoc analyses demonstrated that the high-eVortgroup reported higher levels of fatigue (M = 5.76)compared to the low-eVort group (M = 3.89,T = ¡4.78, df = 49, P < .001; Hypothesis 2c supportedfor fatigue). The development of fatigue during theday did not vary signiWcantly as a function of eVort-group (time £ group interaction, ns). Furthermore,ANCOVA revealed that the high-eVort groupreported signiWcantly more sleep complaints(Hypothesis 2c supported for sleep complaints). Thethird analysis (ANCOVA) showed that the twoeVort-groups did not diVer signiWcantly with regard to
Table 2 Activity patterns, experiences and recovery indicators during the workday
F-statistics, P-values, and means and standard deviations for the total sample and for the two eVort-groups
608 Int Arch Occup Environ Health (2007) 80:599–613
sleep time. Concerning preoccupation with work,ANCOVA revealed that the high-eVort group wassigniWcantly more preoccupied (Hypothesis 2d sup-ported). A similar analysis conducted for work moti-vation did not reveal any signiWcant diVerencesbetween the two eVort-groups.
In sum, the high-eVort group engaged less often inactive leisure activities in-between successive work-days, but did not diVer signiWcantly from the low eVort-group regarding the experience of pleasure associatedwith these activities. Further, the high-eVort groupexperienced the home activities as more eVortful. Inaddition, we systematically observed higher levels offatigue; more sleep complaints, and a higher preoccu-pation with work in the high-eVort group in-betweenworkdays.
Research question 3
Table 4 presents the relevant means, standard devia-tions and F-statistics for the total sample and for thetwo eVort-groups. To map possible diVerences in activ-ity patterns between the two eVort-groups, two analy-ses were conducted. First, we computed for eachparticipant the percentage of weekend days on whichtime was spent on each home activity: The fourANCOVA’s (one for each percentage) conducted forthese percentage revealed no diVerences between botheVort-groups. Secondly, with respect to the time spenton the four types of home activities, also for each activ-ity an ANCOVA was conducted. Results revealed oneimportant diVerence in activity patterns: the high-eVortgroup spent signiWcantly more time on overtime work
Table 3 Activity patterns, experiences, recovery indicators, work involvement and work motivation in-between workdays
F-statistics, P-values, and means and standard deviations for the total sample and for the two eVort-groups
Int Arch Occup Environ Health (2007) 80:599–613 609
during the weekend compared to the low-eVort group(Hypothesis 3a partially supported).
Conducting multivariate analyses for “pleasure” and“eVort” would result in very restricted sample sizes(n = 13 in both groups). Therefore, only univariatetests were computed, revealing that the high-eVortgroup considered all four activities signiWcantly moreeVortful (Hypothesis 3b supported). Again, the twoeVort-groups did not diVer signiWcantly with respect topleasure associated with their activities.
Three analyses were conducted to examine possiblediVerences between the two eVort-groups regardinghealth and well-being indicators. A 3 (time: morning vs.afternoon vs. evening) £ 2 (group: low vs. high-eVort)repeated-measures ANCOVA revealed a main eVect ofTime. Post-hoc analyses indicated that fatigue increasedsigniWcantly during the day, that is, was lowest in themorning (M = 3.32), somewhat higher in the afternoon(M = 4.08) and highest in the evening (M = 5.41).
Furthermore, overall, the two eVort-groups reporteddiVerent levels of fatigue (signiWcant main eVect ofgroup). Post-hoc analyses showed that the high-eVortgroup reported signiWcantly higher levels of fatigue(M = 5.03) than the low-eVort group (M = 3.61; Hypothe-sis 3c supported for fatigue). Finally, fatigue did not varysigniWcantly between the eVort-groups as a function oftime of the day (non-signiWcant time £ group interaction).Two ANCOVAs indicated that sleep complaints andsleep time did not vary signiWcantly between the eVort-groups (Hypothesis 3c rejected for sleep complaints).
Two additional ANCOVAs indicated that the twoeVort-groups did not signiWcantly diVer with respectto preoccupation with work during the weekend(Hypothesis 3d rejected), but that the high-eVort groupfelt less like starting the next working week (workmotivation).
In sum, the two eVort-groups did not show signiW-cantly diVerent activity patterns during the weekend
Table 4 Activity patterns, experiences, recovery indicators, work involvement and work motivation during the weekend
F-statistics, P-values, and means and standard deviations for the total sample and for the two eVort-groups
610 Int Arch Occup Environ Health (2007) 80:599–613
regarding domestic work, active and passive leisure.However, the high-eVort group spent signiWcantlymore hours on overtime work during the weekend thanthe low-eVort group. Furthermore, the high-eVortgroup experienced all home activities as signiWcantlymore eVortful, although not as less pleasant, than thelow eVort-group. We also observed signiWcantly higherlevels of fatigue during the weekend and less motiva-tion to start the upcoming workweek in the high-eVortgroup.
Discussion
The present study was devised to enhance our insightin the associations between work-related eVort andrecovery from that eVort. To this purpose, we com-pared two groups of employees reporting diVerent lev-els of work-related eVort (high vs. low) with respect totheir activities, experiences, and health and well-beingin three time-periods: (1) during work time, (2) in-between work days and (3) during the weekend.
Activity patterns
Our results revealed that the two eVort-groups did notdiVer signiWcantly in terms of their activity patterns atwork. However, two signiWcant diVerences wereobserved in the home domain. The Wrst manifesteditself in-between work days: the high-eVort group per-formed active leisure activities on fewer days than thelow-eVort group, which is unfortunate, as active leisureactivities seem to promote recovery (Sonnentag 2001).
A second diVerence appeared during the weekend.Contrary to our expectations (Hypothesis 3c), employ-ees in the high-eVort group spent more time on work-ing overtime in the weekend. This implies that theseemployees devote part of potential recovery time dur-ing the weekend to activities that may interfere withthe recovery process (cf. Sonnentag 2001).
The amount of time devoted to domestic activitiesduring the weekdays and weekend days did not varysigniWcantly between the two eVort-groups. This may bedue to the fact that many domestic activities are obliga-tory in nature (e.g., it is diYcult to circumvent doing thehousehold chores). Finally, no signiWcant diVerencesbetween the groups emerged concerning low-eVortactivities, both during weekdays and weekend days.
Experiences
Regarding experiences, we distinguished between eVortand pleasure. The high-eVort group reported signiWcantly
more eVort for all work activities. In the home domain,the high-eVort group judged overtime and active lei-sure activities as more eVortful during weekdays andjudged all activities as more eVortful during the week-end. No signiWcant diVerences between the groupswere observed with respect to pleasure, neither duringwork time nor in-between workdays, nor in the week-end. Hence, work-related eVort is independent of thepleasure derived from work and home activities.
Health and well-being
We observed a stronger increase in work-relatedfatigue during the workday for the high-eVort groupthan for the low-eVort group. Thus, whereas the twogroups did not diVer signiWcantly in work-relatedfatigue at the start of the working day, the high-eVortgroup was more fatigued at the end of the working day.This diVerence persisted in-between workdays. ThisWnding might explain why the high-eVort groupengaged less often in active leisure in-between work-days than the low-eVort group. Also during the week-end, the high-eVort group remained signiWcantly morefatigued than the low-eVort group. Possibly, this maybe due to the fact that the former group spent moretime on overtime.
A somewhat diVerent pattern of results wasobserved with respect to sleep complaints: The high-eVort group reported more sleep complaints during theweek, but not in the weekend. The additional Wndingthat the two groups did not diVer signiWcantly withrespect to sleep time suggests that work-related eVortrelates to sleep quality, but not sleep quantity.
During the week, the high-eVort group was appar-ently more preoccupied with work than the low-eVortgroup. However, it cannot be excluded that this ispartly due to our item wording. Although we askedparticipants to indicate the extent to which they werealready preoccupied with the upcoming workday, itwould seem possible that this measure (also) reXectsthe extent to which participants were still ruminatingabout their past working day. In the weekend, the twogroups did not diVer signiWcantly in their preoccupa-tion with the upcoming workweek. This is surprising, asthe high-eVort group spent more time on work-relatedactivities during these days. The high-eVort groupnonetheless reported less work motivation than thelow-eVort group.
Limitations and suggestions for future research
Six issues with respect to the present study must be dis-cussed. First, as we employed a single item report mark
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to create the two eVort-subgroups, the reliability andvalidity of this measure can be questioned. However,we believe that there are good arguments in favor ofemploying this report mark: (1) we did not rely on asingle observation of this measure, as each participantcompleted the item on at least three occasions; (2)employees in the high-eVort group considered each ofthe four categories of work activities as more eVortfulthan the low-eVort group, thus suggesting that thereport mark correctly reXects the eVort experiencedduring the workday; and (3) there is a correlation of0.85 (P < 0.001) between our single-item eVort-mea-sure and a weighted mean score of the eVort experi-enced during the separate work activities. The latterwas computed by Wrst weighting the number of hoursspent on each activity by the eVort expended to thisactivity; the sum of these weighted scores was dividedby the total number of work hours. Thus, our single-item report mark seems to measure a very similarquantity as a much more reWned measure of eVort.
A second point of concern is the procedure used tocreate the two eVort-subgroups. These groups werecreated based on the number of days participants con-sidered their work as eVortful. To probe the possibilitythat our Wndings are biased by this somewhat arbitraryprocedure we repeated our analyses using a slightlydiVerent eVort indicator. For each participant whocompleted the report mark of global work-relatedeVort on at least three occasions, the mean score onthis report mark across the week was computed. Basedon these scores, two new subgroups were created: Oneincluding participants with scores in the highest tertile,and a second with participants having scores in the low-est tertile. Analyses were repeated for these twogroups, yielding results that were highly similar tothose found for the original subgroups (results can beobtained from the Wrst author on request). Thus, ourWndings appear robust across diVerent measures ofeVort expenditure.
Thirdly, our study relied exclusively on self-reportmeasures, and this might have resulted in an overesti-mation of the associations among the variables due tocommon method variance. However, this should haveinXated all relations studied and not just part of these:the fact that some relationships were found while oth-ers were not, argues against the inXuence of commonmethod variance in our study. Besides, alternativemeasures such as observational or physiological mea-sures are not free of error variance either, and shouldtherefore not be considered superior to self-reportmeasures (Semmer et al. 2004; see also Kompier 2005).Furthermore, by demonstrating (1) that using self-reports does not guarantee Wnding signiWcant results,
(2) that potential biasing variables (social desirability,negative aVectivity and acquiescence) do not generallyinXate correlations among study variables and (3) thatmonomethod correlations are not by deWnition higherthan multimethod correlations, Spector (2006) con-cludes that “the popular position suggesting commonmethod variance automatically aVects variables mea-sured with the same method is a distortion and over-simpliWcation of the true state of aVairs” (p 221). Thus,all in all we do not believe that common method biasseverely biased our Wndings, although the use of physi-ological and performance measures in addition to self-reports could provide interesting insights in futureresearch.
A fourth issue is the impact of potential third vari-ables. One might argue that diVerences between thetwo eVort-groups regarding (experiences of) activitiesand health and well-being indicators might be due topersonality characteristics or other person or work-related constructs, rather than to work-related eVort.However, in our study we attempted to exclude theinXuence of these variables to our best ability: The twoeVort-groups turned out not to diVer regarding thenumber of life events experienced, general work char-acteristics (work pressure, job control, social support),fatigue, work engagement, age and positive and nega-tive aVect. Of course this does not exclude the possibil-ity that other third variables (e.g., other aspects ofpersonality) may have acted as third variables in thisstudy.
Fifth, this study did not oVer insight in the intriguingquestion into the origin of the diVerences in work-related eVort between the two subgroups studied. Itmay be that these diVerences are at least partly due todiVerences in participants’ objective work performance(e.g., number of publications or student evaluations),but such measure was not incorporated in this study.Thus, it is unclear how the diVerences between the twoeVort-groups in their work-related eVort are related toreal output diVerences, and future studies on this topicshould also include objective measures of task perfor-mance.
Finally, the present research employed a very spe-ciWc sample, consisting of academic staV members whoworked at least 32 h a week and who lived togetherwith a partner who worked at least 2.5 days a week,and who, as is common for tenured academics in theNetherlands, have relatively high job security and arenot dependent on fund raising. Although we believethat our main Wndings on the relations among eVort,recovery, health and well-being are not unique to thissample, it is desirable to replicate this study foremployees in other professions, in other family
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situations and/or with other working hours. Thus,future studies should employ samples from other con-texts to broaden our understanding of eVort and recov-ery patterns.
Assets of this study
In spite of these limitations, we believe that the presentstudy extends and enhances previous research on eVortand recovery in at least four respects. First, this study isamong the very few that examine eVort and recoveryfrom a day-to-day perspective, allowing us to demon-strate that work-related eVort is related to variousaspects of daily work and (potential) recovery time. Inthis vein, this study shows how eVort expenditure atwork is actually imbedded in everyday life, and how itrelates to recovery during time-oV-the job.
Secondly, this study emphasized the importance ofthe weekend as a (potential) opportunity for recovery.Whereas some diVerences between the two eVort-groups persisted throughout the weekend (e.g., higherlevels of fatigue and eVort-investment for the high-eVort group), other diVerences manifested themselvesonly during the working week (i.e., less active leisure,more sleep complaints and more preoccupation withwork for the high-eVort group) or only during theweekend (i.e., more overtime work and less work moti-vation for the high-eVort group). Thus, not all workersemploy the recovery opportunities oVered by theweekend in a similar fashion: some seem to employ theweekend as a means to catch up with their overduetasks. These results suggest that it would be worthwhileto study the reasons why workers diVer in the way theyuse their weekend.
Thirdly, by paying attention to employees’ activitypatterns at work and outside work, we were able toshow that eVort expenditure at work relates to activitypatterns in the home domain. Namely, high levels ofeVort expenditure at work were associated with lessengagement in active leisure and more overtime work.This Wnding thus suggests that for some workers, higheVort expenditure at work is not compensated by a cor-responding degree of participation in recovery activi-ties. Given that an imbalance between eVort andrecovery is associated with adverse health outcomes,this particular group of workers may, in the long run,be a risk group for the development of ill health.
Fourthly, we demonstrated that experiences associ-ated with engagement in work and home activities areimportant: higher eVort investment at work is relatedto experiences of higher eVort expenditure outsidework, but not to experiences of less pleasure regardingwork or home activities.
Practical implications
Based on our study’s results, three practical suggestionscan be formulated. Firstly, adequate control opportuni-ties in the job setting will allow workers to adjust theirwork behavior to their current need for recovery and,thus, to prevent the development of negative load reac-tions during working. Secondly, employees should beencouraged to engage in leisure activities that poten-tially contribute to the recovery process, such as activeleisure. Finally, the time spent on overtime work shouldbe kept within acceptable limits, as overtime workimpedes the recovery process. Employers should not todemand excessive overtime work from their employees,in order to guarantee suYcient (potential) recoverytime (see also Beckers et al. in press).
Theoretical implications
Our study revealed that workers who invest high eVortat work diVer in their oV-the-job activity patterns fromthose who invest low eVort at work: members of theWrst group are to a lesser degree engaged in active lei-sure during evenings in-between work days, and theyspend more time on overtime work during the week-end. This diVerent activity pattern may have conse-quences for the recovery process, as previous researchsuggests that active leisure promotes recovery, whereasovertime work impedes this process (Sonnentag 2001).That recovery is endangered in the high-eVort group isalso evidenced by the higher levels of fatigue duringnon-work time (evenings and weekends) and the lowersleep quality during the week. Apart from a diVerentactivity pattern, those expending high eVort at workalso expend high eVort on home activities, which alsomay endanger the recovery process. Therefore, despitethe fact that those investing high eVort at work do notexperience their activities as less pleasant than thoseexpending low eVort, they may be considered at riskfor developing health problems in the long run.
Acknowledgments This study was supported by ASPASIAGrant # 015.000.027 from the Netherlands Organization for Sci-entiWc Research (NWO) to Sabine Geurts. We thank Sabine Son-nentag and Jessica Rehe for their valuable input in this study.
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