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Keywords:

  • emotional exhaustion;
  • recovery;
  • teachers;
  • vacation;
  • work engagement

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

This study adds to research on the beneficial effects of vacation to employees' well-being and on the fade-out of these effects. One hundred and thirty-one teachers completed questionnaires one time before and three times after vacationing. Results indicated that teachers' work engagement significantly increased and teachers' burnout significantly decreased after vacation. However, these beneficial effects faded out within one month. Applying hierarchical regression analyses, we investigated the fade-out of vacation effects in detail. In line with the Job Demands-Resources model, job demands after vacation sped up the fade-out of beneficial effects. Additionally, leisure time relaxation experiences after vacation delayed the fade-out of beneficial effects. We conclude that reducing job demands and ensuring leisure time relaxation can prolong relief from vacation. Copyright © 2010 John Wiley & Sons, Ltd.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

Vacation, defined as a time off the job lasting several days to several weeks, has become a topic of interest in organizational behavior and related fields (Lounsbury & Hoopes, 1986). Offering the opportunity to recover from job demands and to replenish resources stressed during work, vacationing can prevent and reduce chronic strain reactions to job stress (Eden, 2001; Geurts & Sonnentag, 2006; Westman & Etzion, 2001). Although several studies have shown positive effects of vacationing on well-being and performance-related outcomes (for example, Etzion, 2003; Fritz & Sonnentag, 2006; Westman & Eden, 1997), these studies have also indicated that these effects are transitory. That is, well-being indicators returned to their pre-vacation levels a few weeks after vacationing, implying that beneficial effects of vacation faded out shortly after vacationing. However, until now, little has been known about factors that have an impact on this fade-out process. Therefore, the purpose of the current study is twofold. First, we examine whether beneficial effects of vacation on employees' well-being, and the fade-out of these vacation effects, exist. Second, we investigate factors that speed up the fade-out of vacation effects as well as factors that delay the fade-out of vacation effects. Identifying factors that contribute to the fade-out could improve our understanding of recovery processes and the accumulation of strain after recovery periods. Furthermore, to derive practical implications about how to prolong vacation relief, it is important to gain knowledge about why beneficial effects fade out.

In our study, we focus on emotional exhaustion and work engagement as main indicators of the fade-out process. We followed suggestions made by Schaufeli, Taris, and van Rhenen (2008) to examine more comprehensive models of employee well-being by simultaneously including emotional exhaustion and work engagement. Work engagement is considered to be the positive antithesis of burnout (Maslach, Schaufeli, & Leiter, 2001). In accordance with Bakker (2009) and Schaufeli and Bakker (2004), we define work engagement in its own right rather than rephrasing burnout as an erosion of work engagement. Thus, we propose that work engagement is not simply the opposite of emotional exhaustion, although negative correlations are expected between both constructs (Schaufeli & Salanova, 2008). In our study, we do not look at trait emotional exhaustion and trait work engagement. Rather, we study both constructs as more transient states that can fluctuate over time. Experiencing high work engagement during a working week does not necessarily imply that one does not occasionally feel exhausted at the end of a working day in this week. Thus, we take both emotional exhaustion and work engagement into account.

There is increasing empirical evidence for the relevance of emotional exhaustion and work engagement for individuals and organizations alike. A meta-analysis of Taris (2006) showed negative correlations between emotional exhaustion and in-role behavior, organizational citizenship behavior, and customer satisfaction. In a sample of teachers, Hakanen, Bakker, and Schaufeli (2006) found that burnout was related to poor health and poor work ability and negatively related to organizational commitment. Accordingly, research has shown that work engagement is relevant for employee performance (Halbesleben & Wheeler, 2008; Salanova, Agut, & Peiró, 2005), high organizational commitment (Demerouti, Bakker, de Jonge, Janssen, & Schaufeli, 2001a; Richardsen, Burke, & Martinussen, 2006), low sickness absence (Schaufeli, Bakker, & van Rhenen, 2009), and positive affect at work (Rothbard, 2001). To the best of our knowledge, our study is the first study on vacation effects that also considers work engagement as an indicator of recovery besides examining emotional exhaustion.

We apply a longitudinal design and study teachers who had vacation that lasted two weeks. Teaching is a high-stress occupation and, in comparison to other professions, teachers show high levels of burnout (Borg & Riding, 1991; Hakanen et al., 2006; Karasek & Theorell, 1990; Travers & Cooper, 1996). Therefore, we expect vacation can have a strong impact on teachers' well-being.

In the following, we first outline why vacationing has an impact on emotional exhaustion and work engagement. We then explain why the beneficial effects of vacation fade out after vacation and propose factors that speed up and delay fade-out.

Vacation effects

At work, employees face job-related stressors and have to spend energy to fulfill their tasks (Meijman & Mulder, 1998). During vacation, job demands are removed from the individual. Therefore, employees' resources called on during work can be rebuilt (Hobfoll, 1989, 2001) and psychological and physiological systems can return to their baseline levels (Craig & Cooper, 1992; Meijman & Mulder, 1998). This restoration process during which negative consequences of job demands are reversed is called recovery. Research has shown that time off that offers opportunities to recover from work results in a decrease in burnout (Etzion, 2003; Fritz & Sonnentag, 2006; Westman & Eden, 1997; Westman & Etzion, 2001). We focus on emotional exhaustion as one core dimension of burnout (Lee & Ashforth, 1996; Shirom, 1989). Demerouti, Bakker, Nachreiner, and Schaufeli (2001b) defined exhaustion as a result of prolonged physical, affective, and cognitive strain at work. We propose that negative consequences of job demands, such as emotional exhaustion, can be alleviated during vacation because the employee is no longer confronted with the physical, affective, and cognitive strains of her or his job. Thus, this process of recovery should become apparent in lower levels of emotional exhaustion after vacationing. Therefore, we propose that one's level of emotional exhaustion will decrease from before to after vacation.

Hypothesis 1a: Emotional exhaustion will decrease from before to immediately after vacation.

Besides enabling relief of negative consequences of work, vacation and other respites enhance positive states at work, such as effort expenditure (Fritz & Sonnentag, 2006). We propose that employees' work engagement benefits from vacation, as well. Work engagement is defined as a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption (González-Romá, Schaufeli, Bakker, & Lloret, 2006; Schaufeli, Bakker, & Salanova, 2006). Vigor refers to high levels of energy and mental resilience while working, the willingness to invest effort in one's work, and persistence even in the face of difficulties. Dedication refers to being strongly involved in one's work and experiencing a sense of significance, enthusiasm, inspiration, pride, and challenge. The third component of work engagement, absorption, is characterized by being fully concentrated and engrossed in one's work, thereby experiencing time as passing quickly. According to Kahn (1990), physical, emotional, and psychological resources are a necessary prerequisite for work engagement. Thus, we propose that rebuilding resources during vacation may lead to higher levels of resources (Hobfoll, 1989, 2001) and thus may become apparent in higher levels of work engagement after vacation. In a daily survey study, Sonnentag (2003) showed that feeling recovered in the morning was positively related to work engagement during the subsequent work day. These findings suggest that daily recovery helps individuals to experience work engagement. Also, recovery during a longer time period such as vacation should support individuals' experience of higher levels of work engagement after the recovery period. Therefore, we propose that one's level of work engagement will increase from before to after vacation.

Hypothesis 1b: Work engagement will increase from before to immediately after vacation.

Fade-out of beneficial effects of vacation

When returning to work after vacation, the individual is again confronted with job demands and his or her daily recovery time is reduced. Strain reactions can accumulate and resources restored during vacation are called on at work (Gorgievski & Hobfoll, 2008; Hobfoll, 1989; Meijman & Mulder, 1998). The accumulation of strain reactions and the consumption of resources should be reflected in an increase of emotional exhaustion and a decrease of work engagement in the time period after vacation. In other words, beneficial effects of vacation are proposed to fade out after vacation. Previous research suggests that the return of emotional exhaustion takes place within four weeks after vacation: For example, Westman and Eden (1997) found that burnout returned to its pre-vacation level three weeks after vacation, and Westman and Ezion (2001) found that burnout returned to its pre-vacation level four weeks after vacation.

As this study is the first study investigating the fade-out of work engagement, we propose that the time frame of the fade-out of work engagement may be similar to the time frame of the fade-out of emotional exhaustion.

Hypothesis 2: Emotional exhaustion and work engagement will return to their pre-vacation levels within four weeks after vacation.

Predictors of vacation fade-out

From a previous study (Fritz & Sonnentag, 2006), we know that specific experiences during vacation, such as reflecting negatively on one's job, are related to burnout and health complaints immediately following, and two weeks after, vacation. Strauss-Blasche, Ekmekcioglu, and Marktl (2000) found an improvement in well-being after vacationing for individuals who experienced recuperation during their vacation. What we do not know is which factors after vacation eliminate the potentially positive effects of vacation and which factors prevent positive effects of vacation from fading out. To close this gap, in line with the Job Demands-Resources (JD-R) model (Demerouti et al., 2001b) and the Conservation of Resources (COR) theory (Hobfoll, 1989, 2001), we propose factors that may impact upon the fade-out process of beneficial vacation effects. The JD-R model (Demerouti et al., 2001b) describes how employee well-being may be influenced by two sets of working conditions—namely, job demands and job resources. Job demands refer to physical, psychological, social, or organizational aspects of the job (e.g., time pressure, emotional workload) that require sustained physical and/or psychological effort and are therefore associated with certain physiological and/or psychological costs to the employee (Bakker & Demerouti, 2007). Job resources refer to physical, psychological, social, or organizational aspects of the job (e.g., social support, job control) that reduce job demands and the associated psychological and physiological costs, are functional in achieving work goals, and stimulate personal growth, learning, and development (Demerouti et al., 2001b). The JD-R model proposes that demands and resources evoke two psychological processes. The first is an energetic process of wearing out and overtaxing, in which job demands may exhaust employees' psychological and physiological resources. Secondly, the JD-R model proposes a motivational process in which job resources lead to engagement at work and positive outcomes (Schaufeli & Bakker, 2004). According to the JD-R model, the energetic process of wearing out and overtaxing may lead to the depletion of energy and to a decrease of physiological and psychological resources that is reflected in an increase in emotional exhaustion. Therefore, we propose that job demands will speed up the return of emotional exhaustion of vacation.

In the current study, we took job demands into account that have been identified as salient demands for teachers, such as pupil misconduct (Burke, Greenglass, & Schwarzer, 1996; Evers, Tomic, & Brouwers, 2004; Hakanen et al., 2006) and work overload (Borg & Riding, 1991; Borg, Riding, & Falzon, 1991; Boyle, Borg, Falzon, & Baglioni, 1995). For example, Burke et al. (1996) found that the strongest predictor for the increase of burnout over the course of one year was disruptive behavior of students. Borg and Riding (1991) and Borg et al. (1991) found that time pressure explained substantial variance in teachers' perceived job stress. In line with the energetic process of the JD-R model, which describes that job demands may exhaust employees' psychological and physiological resources, we propose that the confrontation with pupil misconduct and time pressure after vacation will lead to the depletion of resources restored during vacation. That is, for employees experiencing high levels of job demands after vacation, the depletion of psychological and physiological resources should become apparent in a stronger increase of emotional exhaustion after vacation than for employees experiencing lower levels of job demands after vacation. In other words, pupil misconduct and time pressure after vacation will foster the increase of emotional exhaustion.

Hypothesis 3: Pupil misconduct and time pressure after vacation will be positively related to the increase of emotional exhaustion after vacation.

However, we do not expect pupil misconduct and time pressure to be related to the fade-out of work engagement after vacation. According to the JD-R model (Bakker & Demerouti, 2007; Schaufeli & Bakker, 2004), job resources should be primarily related to work engagement whereas job demands should be unrelated to work engagement. Empirically, Schaufeli and Bakker (2004) demonstrated that burnout and work engagement exhibit different patterns of possible causes. Burnout was primarily predicted by job demands and a lack of job resources whereas work engagement was exclusively predicted by job resources and not predicted by job demands. Similarly, Hakanen et al. (2006) showed the same pattern of relationships in a sample of teachers. Whereas job demands were related to burnout, job demands were not directly related to work engagement.

As proposed above, being back at work after vacation implies there is a confrontation with job demands and a quantitative reduction of recovery time. However, although recovery time is reduced drastically when employees start working after vacation, there are still opportunities to recover from work during time off the job. During evenings and weekends, employees are no longer confronted with job demands and recovery can take place. An experience that turned out to be crucial for recovery is the experience of relaxation during off-job time (Sonnentag & Fritz, 2007) because this experience implies that no further demands are made on functional systems called upon during work. During relaxation experiences, activation is reduced and regeneration of psychological and physiological systems can take place (Meijman & Mulder, 1998). Relaxation may be obtained by taking a walk (Hartig, Evans, Jamner, Davis, & Gärling, 2003), taking a bath (Totterdell & Parkinson, 1999), listening to music (Pelletier, 2004), or by performing relaxation techniques such as meditation (Grossman, Niemann, Schmidt, & Walach, 2004; Hewitt & Miller, 1981) or progressive muscle relaxation (Jacobsen, 1938).

We propose that the experience of relaxation during evenings and weekends promotes the restoration of resources during off-job time. Thus, looking at the time period of four weeks after vacation, the process of daily restoration of resources and the process of consumption of resources restored during vacation take place simultaneously. We propose that daily restoration of resources due to relaxation experiences during off-job time can work against the consumption of resources restored during vacation. In other words, the fade-out of beneficial effects of vacation should therefore be slower for employees experiencing relaxation during off-job time after vacation. More specifically, we expect that leisure time relaxation experiences after vacation will delay (a) the increase of emotional exhaustion and (b) the decrease of work engagement after vacation.

Hypothesis 4a: Leisure time relaxation experiences after vacation will be negatively related to the increase of emotional exhaustion after vacation.

Hypothesis 4b: Leisure time relaxation experiences after vacation will be negatively related to the decrease of work engagement after vacation.

Method

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

Sample

Teachers from German schools participated in our study. To recruit study participants, we approached school principals, informed them of the study, and told them that data collection would take place around a two week long vacation. After they agreed to participate, we sent information about the study and application forms to the teachers. Those teachers who applied by sending back the application form received survey packages before Easter vacation or Whitsun holidays. Survey packages included an information letter, four questionnaires, and a stamped return envelope preaddressed to the researchers at the university. The information letter introduced the study as research on “recovery during vacation” and emphasized voluntariness and confidentiality of responses. Further, the respondents were clearly instructed as to when to fill out the questionnaires. We used questionnaires in different colors (red, blue, orange, and yellow) to help participants to complete the correct questionnaire at each measurement occasion. We asked for current date and current day of week in all questionnaires to control whether participants filled out the questionnaires at the instructed points in time or not. Additionally, we sent e-mails to the participants to remind them to fill out the questionnaires. To enhance participation, we promised feedback about the study and later sent feedback to school principals and participating teachers.

We sent out 304 survey packages. A total of 160 employees returned survey packages (response rate of 52.6 per cent). We excluded respondents who did not fill out the questionnaires at the instructed points in time and respondents who had employment contracts with less than 40 per cent of fulltime. Due to missing data, the final sample consisted of 136 employees for Time 3 (overall response rate of 44.7 per cent) and 131 employees for Time 4 (overall response rate of 43.1 per cent). The majority of the respondents were women (69.1 per cent). According to data from the German Federal Statistical Office (Statistisches Bundesamt, Fachserie 11, Reihe 1, 2007/08), in the school year 2007/2008, 69.1 per cent of German teachers were female. Thus, our sample is representative regarding the proportion of females. Average age was 46.6 years (SD = 11.2), ranging from 26 to 65 years. About 70 per cent of the participants had at least one child.

Measures

We gathered data with four questionnaires. Participants had to complete the first questionnaire at the end of the last working day before vacation (Time 1), the second questionnaire at the end of the first working day after vacation (Time 2), the third questionnaire at the end of the last working day of the second working week after vacation (Time 3), and the fourth questionnaire at the end of the last working day of the fourth working week after vacation (Time 4). Work engagement and emotional exhaustion were assessed at all four measurement points. To capture the immediate effects of vacation, we decided to measure work engagement and emotional exhaustion immediately after vacation (Time 2), that is, at the end of the first working day after vacation. Time pressure, pupil misconduct, relaxation experiences, and negative affect were measured at Time 3 and Time 4, respectively. Demographic control variables were measured before the vacation (Time 1). All items were in German.

Work engagement

We assessed work engagement with six items of the Utrecht Work Engagement Scale devised by Schaufeli et al. (2006), slightly adapted to measure work engagement day-specifically (at Time 2) and week-specifically (at Time 1, 3, and 4). The three underlying dimensions, vigor, dedication, and absorption, were captured with two items each. Items had to be answered on a seven-point Likert scale ranging from 0 (strongly disagree) to 6 (strongly agree). Sample items were “This week [Today], I felt bursting with energy at work” and “When I was working this week [today], I forgot everything else around me”. Cronbach's α was 0.88, 0.90, 0.89, and 0.86 for Time 1, Time 2, Time 3, and Time 4, respectively.

Emotional exhaustion

We measured emotional exhaustion with four items of the Maslach Burnout Inventory—General Survey (Schaufeli, Leiter, Maslach, & Jackson, 1996). Items had to be answered on a seven-point Likert scale ranging from 0 (never) to 6 (all the time). Sample items were “This week [Today], I felt emotionally drained by my work” and “This week [Today], I felt burned out from my work”. Cronbach's α was 0.92, 0.90, 0.91, and 0.95 for Time 1, Time 2, Time 3, and Time 4, respectively.

To show that work engagement and emotional exhaustion represent two empirically distinct constructs, we conducted confirmatory factor analyses (CFAs). Results for Time 2 revealed that a two-factor model with the items of work engagement loading on one factor and the items of emotional exhaustion loading on the other factor (χ2 = 43.9, df = 34, RMSEA = 0.04, CFI = 0.98, NNFI = 0.97) fit the data better than a model with all items loading on one factor (Δχ2 = 353.1, df = 1, p < 0.001). Analyses for Time 3 and Time 4 displayed similar results. CFAs for Time 3 revealed a better fit of the two-factor model (χ2 = 67.2, df = 34, RMSEA = 0.08, CFI = 0.95, NNFI = 0.93) compared to the one-factor model (Δχ2 = 307.9, df = 1, p < 0.001). Likewise, results for Time 4 demonstrated a better fit of the two-factor model (χ2 = 55.7, df = 34, RMSEA = 0.06, CFI = 0.97, NNFI = 0.95) compared to the one-factor model (Δχ2 = 238.5, df = 1, p < 0.001). Intercorrelations of the two latent factors were −0.22, −0.36, and −0.35, for Time 2, Time 3, and Time 4, respectively. We are confident, therefore, that the items of work engagement and emotional exhaustion represent two empirically distinct constructs.

Job demands

We assessed time pressure with four items of the ISTA developed by Semmer, Zapf, and Dunckel (1999). We measured week specific time pressure at Time 3 and Time 4, using a five-point Likert scale ranging from 1 (almost never) to 5 (very often). A sample item was “How often were you pressed for time this week?”. Cronbach's α was 0.80 and 0.88 at Time 3 and Time 4, respectively. Furthermore, we assessed pupil misconduct at Time 3 and Time 4 with six items from a teacher-specific measure developed by Krause (2004). Items had to be answered on a five-point Likert scale ranging from 1 (almost never) to 5 (very often). Sample items were “This week, pupils did not pay attention to the content of lessons and disturbed lessons” and “This week, it has been difficult for pupils to focus on instruction for several minutes”. Cronbach's α was 0.87 for Time 3 and Time 4.

Relaxation experiences

We measured relaxation experiences at Time 3 and Time 4 with four items from the Recovery Experience Questionnaire developed by Sonnentag and Fritz (2007), slightly adapted to measure week-specific relaxation experiences. Items had to be answered on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Sample items were “During my spare time this week I used the time to relax” and “During my spare time this week I did relaxing things”. Cronbach's α was 0.91 and 0.88 for Time 3 and Time 4, respectively.

One might argue that time pressure, pupil misconduct, and lack of relaxation experiences show substantial conceptual overlap. Therefore, we conducted CFAs with the items of time pressure, pupil misconduct, and relaxation experiences for Time 3 and Time 4. Results from CFAs for Time 3 revealed that the three-factor model (χ2 = 135.1, df = 74, RMSEA = 0.07, CFI = 0.93, NNFI = 0.90) fit the data better than the best fitting two-factor model (Δχ2 = 152.2, df = 2, p < 0.001) and the one-factor model (Δχ2 = 498.8, df = 3, p < 0.001). Likewise, results for Time 4 showed that the three-factor model (χ2 = 137.0, df = 74, RMSEA = 0.07, CFI = 0.93, NNFI = 0.90) fit the data better than the best fitting two-factor model (Δχ2 = 217.8, df = 2, p < 0.001) and the one-factor model (Δχ2 = 481.2, df = 3, p < 0.001).

Control variables

At Time 1, we measured a number of additional variables (gender, age, number of children, weekly work hours) that we included as control variables in the regression analyses. At Time 3 and Time 4, we further assessed week-specific negative affect. Particularly, we measured week-specific negative affect with the ten negative affect items from the PANAS (Watson, Clark, & Tellegen, 1988). Sample items were “upset” and “distressed”. Using a five-point Likert scale ranging from 1 (not at all) to 5 (extremely), higher scores indicated higher negative affect. Cronbach's α was 0.82 and 0.87 for Time 3 and Time 4, respectively. In the following analyses, we controlled for concurrently measured negative affect. The rationale for doing so was to eliminate the potential influence of response tendencies stemming from individuals' current affect while answering the questionnaire.

Data Analysis

To test if vacation has beneficial effects (Hypotheses 1a and 1b) and if these effects fade out (Hypothesis 2), we conducted multivariate repeated measures analysis of variance with a within-subjects factor time and two dependent variables; work engagement and emotional exhaustion. As Mauchly's test of sphericity turned out to be significant for both dependent variables, we used the adjustment value epsilon (Greenhouse-Geisser) for the tests of within-subjects effects. We introduced contrasts among the within-subject variable time to compare Time 1 with Time 2, Time 2 with Time 3, and Time 3 with Time 4. The contrasts Time 1 versus Time 2 tested whether the level of work engagement before vacation differed from the level of work engagement immediately after vacation and whether the level of emotional exhaustion before vacation differed from the level of emotional exhaustion immediately after vacation (vacation effects). The contrasts, Time 2 versus Time 3 and Time 3 versus Time 4, tested the increase of emotional exhaustion and the decrease of work engagement at both two and four weeks after vacation (fade-out effects).

To test if job demands speed up the fade-out of beneficial effects of vacation and if relaxation experiences delay the fade-out of beneficial effects of vacation (Hypotheses 3, 4a, and 4b), we conducted a set of hierarchical regression analyses. We expected job demands to be positively related to an increase of emotional exhaustion after vacation. Furthermore, we expected relaxation experiences to be negatively related to a decrease of work engagement after vacation and to an increase of emotional exhaustion after vacation. Job demands and relaxation experiences were measured at the end of the second (Time 3) and fourth working week (Time 4) after vacation with items and instructions which referred to the current week. We hypothesized that experiences of the second working week should be reflected in an increase of emotional exhaustion and a decrease of work engagement during the first two weeks after vacation. Thus, to capture the change in emotional exhaustion and work engagement during the first two weeks after vacation, we ran hierarchical regression analyses predicting emotional exhaustion and work engagement at Time 3 (two weeks after vacation). We entered the outcome variable immediately after vacation (Time 2) as control variable to control for the level of emotional exhaustion and work engagement immediately after vacation. Thus, predictors further entered explained the differences in the change of the outcome variable from Time 2 to Time 3. In other words, predictors further entered explained differences in the return of emotional exhaustion and the fade-out of work engagement during the first two working weeks after vacation. Similarly, we ran hierarchical regression analyses predicting emotional exhaustion and work engagement at Time 4 with the outcome variable immediately after vacation (Time 2) as the control variable.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

Descriptive analyses

Table 1 shows means, standard deviations, internal consistencies, and intercorrelations of study variables. Autocorrelations of emotional exhaustion were r = 0.38 (between Time 1 and Time 2), r = 0.55 (between Time 2 and Time 3), and r = 0.54 (between Time 3 and Time 4). Autocorrelations of work engagement were r = 0.32 (between Time 1 and Time 2), r = 0.46 (between Time 2 and Time 3), and r = 0.67 (between Time 3 and Time 4). Time pressure at Time 3 was related to time pressure at Time 4 (r = 0.62), pupil misconduct at Time 3 was related to pupil misconduct at Time 4 (r = 0.78), and relaxation experiences at Time 3 were related to relaxation experiences at Time 4 (r = 0.54). As one might expect, time pressure was positively related to emotional exhaustion (Time 3 and Time 4) and not related to work engagement. Pupil misconduct was positively related to emotional exhaustion (Time 3 and Time 4). Pupil misconduct also showed negative correlations with concurrently measured work engagement. In line with hypotheses, relaxation experiences were negatively related to emotional exhaustion and positively related to work engagement (but only at Time 3).

Table 1. Means, standard deviations, internal consistencies, and intercorrelations
VariableMSDα123456
1. Gender      
2. Age46.6311.170.44***     
3. Number of children1.461.140.23**0.50***    
4. Weekly work hours33.377.770.29***−0.07−0.27**   
5. Negative affect (T3)1.610.480.82−0.06−0.01−0.03−0.02  
6. Negative affect (T4)1.740.600.87−0.080.050.050.030.66*** 
7. Time pressure (T3)3.280.780.800.000.000.040.090.37***0.23**
8. Time pressure (T4)3.390.930.88−0.17*−0.030.120.040.27**0.35***
9. Pupil misconduct (T3)2.800.710.87−0.010.00−0.010.000.29***0.35***
10. Pupil misconduct (T4)2.740.680.87−0.06−0.06−0.010.030.170.33***
11. Relaxation (T3)2.870.920.91−0.020.100.040.08−0.31***−0.12
12. Relaxation (T4)2.670.880.880.120.11−0.130.05−0.25**−0.34***
13. Work engagement (T1)3.091.110.880.060.17*0.13−0.08−0.05−0.03
14. Work engagement (T2)3.481.040.90−0.08−0.15−0.080.020.040.17
15. Work engagement (T3)3.210.970.890.00−0.060.080.01−0.19*−0.06
16. Work engagement (T4)3.110.920.860.040.050.060.03−0.16−0.18*
17. Emotional exhaustion (T1)2.941.420.92−0.16−0.12−0.03−0.020.30***0.32***
18. Emotional exhaustion (T2)1.541.320.90−0.100.070.00−0.17*0.29***0.20*
19. Emotional exhaustion (T3)2.421.330.91−0.03−0.02−0.090.030.58***0.45***
20. Emotional exhaustion (T4)2.881.390.95−0.10−0.09−0.020.090.40***0.51***
Variable7891011121314
1. Gender        
2. Age        
3. Number of children        
4. Weekly work hours        
5. Negative affect (T3)        
6. Negative affect (T4)        
7. Time pressure (T3)        
8. Time pressure (T4)0.62***       
9. Pupil misconduct (T3)0.26**0.28**      
10. Pupil misconduct (T4)0.18*0.32***0.78***     
11. Relaxation (T3)−0.20*−0.01−0.160.00    
12. Relaxation (T4)−0.18*−0.40***−0.16−0.090.54***   
13. Work engagement (T1)0.050.11−0.13−0.140.02−0.01  
14. Work engagement (T2)0.080.16−0.070.000.01−0.060.38*** 
15. Work engagement (T3)0.020.06−0.19*−0.090.24**0.000.54***0.55***
16. Work engagement (T4)0.020.07−0.09−0.21*0.13−0.020.50***0.41***
17. Emotional exhaustion (T1)0.34***0.33***0.36***0.30***−0.07−0.13−0.39***−0.06
18. Emotional exhaustion (T2)0.150.100.19*0.18*−0.010.02−0.03−0.21*
19. Emotional exhaustion (T3)0.58***0.35***0.43***0.29**−0.34***−0.19*−0.14−0.10
20. Emotional exhaustion (T4)0.46***0.60***0.37***0.41***−0.20*−0.36***−0.160.02
Variable1516171819
  • N = 131–136.

  • Note: Gender: 0 = female, 1 = male. T1 = Time 1, before vacation; T2 = Time 2, immediately after vacation; T3 = Time 3, two weeks after vacation; T4 = Time 4, four weeks after vacation.

  • *

    p < 0.05;

  • **

    p < 0.01;

  • ***

    p < 0.001.

1. Gender     
2. Age     
3. Number of children     
4. Weekly work hours     
5. Negative affect (T3)     
6. Negative affect (T4)     
7. Time pressure (T3)     
8. Time pressure (T4)     
9. Pupil misconduct (T3)     
10. Pupil misconduct (T4)     
11. Relaxation (T3)     
12. Relaxation (T4)     
13. Work engagement (T1)     
14. Work engagement (T2)     
15. Work engagement (T3)     
16. Work engagement (T4)0.54***    
17. Emotional exhaustion (T1)−0.22**−0.20*   
18. Emotional exhaustion (T2)−0.18*−0.20*0.32***  
19. Emotional exhaustion (T3)−0.33***−0.30***0.57***0.46*** 
20. Emotional exhaustion (T4)−0.21*−0.31***0.60***0.33***0.67***

Beneficial effects of vacation and fade-out of beneficial effects of vacation

The multivariate repeated measures analysis of variance with two dependent variables, emotional exhaustion and work engagement, revealed a significant effect of the within-subjects factor time with a Wilks' λ (U statistic) of 0.52, F (6, 126) = 19.29, p < 0.001, η2 = 0.47. The results for univariate repeated measures analyses of variance are shown in Table 2. They indicate that the level of emotional exhaustion and work engagement significantly changed across the four measurement occasions.

Table 2. Analyses of variance for emotional exhaustion and work engagement with the within-subjects factor time
VariableTime 1 MTime 2 MTime 3 MTime 4 MdfaNFη 2
  • Note: a = We used the adjustment value epsilon (Greenhouse-Geisser) for the tests of within-subjects effects. Without using adjustment value epsilon df = 3, 393. T1 = Time 1, before vacation; T2 = Time 2, immediately after vacation; T3 = Time 3, two weeks after vacation; T4 = Time 4, four weeks after vacation.

  • ***

    p < 0.001.

Emotional exhaustion2.951.552.432.882.62, 343.8213257.16***0.30
Work engagement3.063.453.203.112.79, 365.571327.34***0.05

We introduced contrasts among the within-subject variable time to compare Time 1 with Time 2, Time 2 with Time 3, and Time 3 with Time 4. Results are shown in Figure 1. Emotional exhaustion significantly decreased from before vacation (Time 1) to immediately after vacation (Time 2), F (1, 131) = 98.75, p < 0.001, increased from immediately after vacation (Time 2) to two weeks after vacation (Time 3), F (1, 131) = 52.45, p < 0.001, and further increased from two weeks after vacation (Time 3) to four weeks after vacation (Time 4), F (1, 131) = 21.79, p < 0.001. Work engagement significantly increased from before vacation (Time 1) to immediately after vacation (Time 2), F (1, 131) = 13.73, p < 0.001, and decreased from immediately after vacation (Time 2) to two weeks after vacation (Time 3), F (1, 131) = 9.23, p < 0.01. Work engagement did not change from two weeks after vacation (Time 3) to four weeks after vacation (Time 4), F (1, 131) = 1.08. Overall, the results revealed a beneficial effect of vacation on emotional exhaustion and work engagement, supporting Hypotheses 1a and 1b. In addition, the results indicated a fade-out effect for emotional exhaustion and work engagement as proposed in Hypothesis 2.

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Figure 1. Means of emotional exhaustion and work engagement across time

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Predictors of the fade-out of beneficial effects of vacation

Table 3 displays findings from the hierarchical regression analyses. In these analyses, we predicted emotional exhaustion and work engagement two and four weeks after vacationing from job demands and relaxation experienced after vacationing. In Step 1, we entered the control variables gender, age, number of children, weekly work hours, and negative affect. In Step 2, we entered the outcome variable measured at Time 2 to control for the level of the outcome variable immediately after vacationing. In Step 3, we included experiences after vacationing (time pressure, pupil misconduct, and relaxation experiences) into the analyses.

Table 3. Hierarchical regression analyses of emotional exhaustion and work engagement on experiences after vacation
VariableEmotional exhaustionWork engagement
Time 3Time 4Time 3Time 4
βΔR2βΔR2βΔR2βΔR2
  • N = 136 for T3; N = 131 for T4.

  • Note: Time 2 = immediately after vacation; Time 3 = two weeks after vacation; Time 4 = four weeks after vacation. a = Negative affect measured concurrently, that is at Time 3 predicting outcome variables at Time 3 and at Time 4 predicting outcome variables at Time 4. b = Experiences of the second week after vacation (Time 3) predicting outcome variables at Time 3 and experiences of the fourth week after vacation (Time 4) predicting outcome variables at Time 4. Gender: 0 = female, 1 = male.

  • p < 0.1;

  • *

    p < 0.05;

  • **

    p < 0.01;

  • ***

    p < 0.001.

Step 1: Control variables 0.35*** 0.29*** 0.06 0.04
 Gender0.01 0.07 0.05 −0.02 
 Age0.01 −0.07 −0.10 0.11 
 Number of children−0.08 −0.06 0.14 0.05 
 Weekly work hours0.05 0.07 −0.01 0.05 
 Negative affecta0.25*** 0.24** −0.15* −0.28** 
Step 2: Outcome variable (Time 2) 0.10*** 0.07*** 0.31*** 0.22***
 Emotional exhaustion (Time 2)0.30*** 0.24***     
 Work engagement (Time 2)    0.54*** 0.45*** 
Step 3: Experiences after vacation b 0.19*** 0.21*** 0.05* 0.03
 Time pressure0.35*** 0.41*** 0.10 0.10 
Pupil misconduct0.18** 0.13* −0.10 −0.14 
 Relaxation experiences−0.16** −0.11 0.19** −0.08 
Total R2 0.64*** 0.57*** 0.42*** 0.29***

Analyses for emotional exhaustion showed that job demands and relaxation experiences were related to the fade-out of emotional exhaustion. Step 3 revealed that time pressure and pupil misconduct were positively related to emotional exhaustion at Time 3 and that relaxation experiences were negatively related to emotional exhaustion at Time 3, explaining 19.4 per cent of additional variance in emotional exhaustion. Predicting emotional exhaustion at Time 4, time pressure and pupil misconduct were positively related to emotional exhaustion at Time 4, explaining 20.8 per cent of additional variance in emotional exhaustion at Time 4. Relaxation experiences were negatively related to emotional exhaustion at Time 4 but failed to reach the significance level of p = 0.05. In sum, results for emotional exhaustion supported Hypothesis 3 and partly supported Hypothesis 4a.

Analyses for work engagement showed that time pressure and pupil misconduct were not related to the fade-out of work engagement at Time 3 and at Time 4. As predicted, relaxation experiences were related to the fade-out of work engagement. Relaxation experiences entered in Step 3 explained 4.8 per cent of additional variance in work engagement at Time 3, but failed to explain a significant amount of additional variance in work engagement at Time 4. To sum up, results for work engagement partly supported Hypothesis 4b. Interestingly, concerning Hypotheses 4a and 4b, relaxation experiences were a significant predictor of emotional exhaustion and work engagement two weeks after vacationing (Time 3), but failed to predict emotional exhaustion and work engagement four weeks after vacationing (Time 4).

Additional analyses

We run additional analyses to test if results differ for males and females. Gender predicted neither the fade-out of emotional exhaustion nor the fade-out of work engagement (please see Table 3). Furthermore, we tested if gender moderates the relationships between our predictor variables time pressure, pupil misconduct, and relaxation experiences and the outcome variables work engagement and emotional exhaustion. None of the interaction terms predicting the fade-out of work engagement and the return of emotional exhaustion at Time 3 and Time 4 was significant. Thus, results do not differ between males and females.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

We pursued two goals with this study. First, we wanted to show beneficial effects of vacation on employees' well-being and to examine the fade-out of these effects. Second, we investigated factors after vacation that eliminate the potentially positive effects of vacation and factors that prevent the positive effects of vacation from fading out. We focused on individuals' emotional exhaustion and work engagement as indicators of the fade-out process.

As predicted, our results revealed a beneficial effect of vacationing on emotional exhaustion and work engagement with a decrease of emotional exhaustion and an increase of work engagement immediately after vacation. Therefore, results are in line with the assumption that depleted resources can be restored by removing job-related demands during vacation time (Hobfoll, 1989, 2001; Meijman & Mulder, 1998). However, these benefits are transitory. Beneficial effects faded out within one month after vacationing. Our results indicated that job demands after vacation contribute to the fade-out, eliminating positive effects of vacationing. High levels of high pupil misconduct and time pressure after vacation were positively related to an increase of emotional exhaustion after vacation. These findings are consistent with the assumption of COR theory (Hobfoll, 1989, 2001) that resources of the individual are threatened when the individual is confronted with demands during stressful work. Our study also showed that experiencing leisure time relaxation during the weeks after vacation may preserve the positive effects of vacationing from fading out. Leisure time relaxation experiences worked against the fade-out of emotional exhaustion and work engagement after vacation. This finding could be seen as an indication that two processes take place simultaneously, the process of consumption of resources that have been restored during vacation and the process of daily restoration of resources. To a certain amount, daily recovery seems to compensate for the consumption of resources restored during vacation. However, relaxation experiences only worked against the fade-out within the first two weeks after vacation, but failed to prevail over the fade-out process after four weeks. This result suggests that in the long run, short recovery periods may not be sufficient to maintain the higher level of resources individuals have gained during vacation.

Whereas this study focused on leisure time relaxation experiences predicting fade-out of work engagement, future studies might also take into account job resources after vacation. The JD-R model (Demerouti et al., 2001b) proposes a motivational process in which job resources foster work engagement. Job resources such as social support after vacation may add to psychological resources restored during vacation and might further enhance individuals' engagement at work. In a study with teachers, Bakker, Hakanen, Demerouti, and Xanthopoulou (2007) showed that job resources (e.g., appreciation) particularly influenced work engagement when teachers were confronted with high levels of pupil misconduct. Future research might investigate whether job resources add to psychological resources restored during vacation. However, one could also propose that teachers might be less dependent on job resources immediately after vacation because they have stored energy resources they can rely on.

Our findings add to research on individual recovery, specifically on how individuals' well-being at work benefits from time off the job. To the best of our knowledge, this is the first study which explicitly investigated predictors of the fade-out of vacation effects. We included occupation-specific job demands that turned out to be crucial for teachers' well-being (e.g., Borg & Riding, 1991, Burke et al., 1996; Hakanen et al., 2006). In line with the positive psychology approach (Bakker & Schaufeli, 2008; Luthans, 2002), we not only studied demands and impaired well-being, but also relaxation—a positive leisure experience, and work engagement—a positive state at work. Thus, we have contributed to research on positive factors that foster work engagement such as recovery during vacation and leisure time relaxation during work-weeks.

One should note that the beneficial effects of vacation for work engagement obtained in this study might be underestimated due to measurement issues. The criterion measures, emotional exhaustion and work engagement at Time 1, Time 3, and Time 4, referred to the previous week. At Time 2, measures had to be framed day-specifically because participants indicated their work engagement and emotional exhaustion at the first day after vacation. Parkinson, Briner, Reynolds, and Totterdell (1995) compared measures of negative mood and positive mood measured daily versus weekly. They concluded that for positive mood, the average of measures of daily positive mood was significantly lower than a measure of weekly positive mood. Thus, the level of work engagement (a positive state) measured daily immediately after vacation (Time 2) could be reduced by the fact that it was measured with a daily timeframe as opposed to Time 1, Time 3, and Time 4, when it was measured with a weekly timeframe. Therefore, the positive effect of vacation that was obtained for work engagement might be underestimated due to the daily timeframe. For negative mood, Parkinson et al. showed that the average of measures of daily negative mood was equal to a measure of weekly negative mood. Thus, the level of emotional exhaustion (a negative state) should not be affected by the daily versus the weekly time frame.

Limitations and implications for further research

The current study has some limitations. The first limitation is the exclusive use of self-report data. We acknowledge that we cannot rule out the possibility that common method variance might have led to the inflation of relationships between the variables (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). However, we used a longitudinal design with four measurement occasions. According to Podsakoff et al., variables measured at different points in time are less likely to suffer from common method bias. In future studies, one might also ask colleagues about one's level of work engagement, or spouses about one's level of emotional exhaustion. Also, objective measures for relaxation experiences could be obtained. For instance, one might assess how much time individuals spent on relaxing activities such as performing meditation (Grossman et al., 2004).

Second, future studies might benefit from implementing a control group of participants without vacations (for an example, see Etzion, 2003). Demonstrating that control group's well-being does not change during the same period would strengthen the findings.

The third limitation bears on the generalizability of our findings. Because our sample is a self-selected sample, one should be careful generalizing the findings. One might assume that only teachers who are generally less exhausted were willing to spent effort and to participate in this study. In addition, one might ask if beneficial effects of vacation and the fade-out of these effects (a) are different for other occupational groups, (b) are dependent on the length of vacation, and (c) are different for other indicators besides psychological well-being. Regarding generalizability across occupational groups, future studies might want to focus on cross-occupational issues. For example, one might assume a faster fade-out for employees in occupations facing high work load. Additionally, specific demands may be related to the fade-out in different occupations. Concerning length of vacation, a recent meta-analysis revealed no relationship between length of the vacation and the strength of the effect of vacationing on well-being and performance-related indicators (de Bloom, Kompier, Geurts, de Weerth, Taris, & Sonnentag, 2009). This result suggests that the exclusive investigation of a vacation that lasted two weeks is not a major threat to the generalizability of our findings.

Regarding the generalizability across indicators of the fade-out, this study focused on psychological well-being. Other vacation studies also examined absenteeism (Westman & Etzion, 2001), self-rated task performance, and effort expenditure (Fritz & Sonnentag, 2006). In all studies, fade-out took place within four weeks after vacation. Several studies have shown a positive relationship between chronic stress and impaired physiological well-being such as a disrupted cortisol circadian rhythm (e.g., Dahlgren, Kecklund, & Åkerstedt, 2005; Lindeberg, Eek, & Lindbladh, 2008) and a positive relationship between insufficient recovery from job stress and biologic dysregulation in terms of allostatic load (e.g., von Thiele, Lindfors, & Lundberg, 2006). Having a longer time off the job during vacation might protect individuals from developing allostatic load in the long run (McEwen, 1998). A study of Strauss-Blasche, Ekmekcioglu, and Marktl (2003) also investigated effects of vacation on physiological indicators. Results of this study indicated that a three weeks lasting respite from chronic demands may reduce atherogenic lipid levels (cholesterol) in chronically stressed individuals. To capture these potential benefits of vacation, future studies might also take physiological indicators into account.

Future research might also investigate organizational level variables, which could play a role in the fade-out of work engagement and the return of emotional exhaustion after vacation. For example, schools might differ in how they arrange the first week after vacation. These school level factors might explain variance in the fade-out of beneficial vacation effects in addition to individual level factors we considered in this study.

Practical implications and conclusion

Several practical implications emerged from this study. Organizations should take care to see that individuals have sufficient recovery time at their disposal, for example, by implementing regulations that restrict skipping vacation or exchanging days of one's vacation for financial rewards because vacation can serve as a powerful instrument to lessen emotional exhaustion and to foster work engagement. To prolong relief from vacation, it is important to reduce job demands and to ensure relaxation during off-job time after vacationing. For example, school administration could reduce the number of students in classes—although we admit that this recommendation is not very realistic because of the current economic situation.

Until now, we lack adequate knowledge to derive practical implications about optimal vacation length and timing of vacation. To improve well-being of employees in order to advance organizational effectiveness, Etzion (2003) suggested encouraging employees to take several short breaks (one week each) throughout the year rather than one long vacation. On the one hand, the reasonableness of this suggestion is supported by results of the recent meta-analysis mentioned before (de Bloom et al., 2009), which showed that length of vacation was not significantly related to the strength of positive effects of vacation. On the other hand, none of these studies included physiological indicators of biologic dysregulation in terms of allostatic load. Having in mind that physiological processes adapt more slowly than mood, we do not know if this suggestion is functional for individuals' physiological and psychological health at a later time.

Looking at the fade-out of beneficial effects of vacation, one might ask “When positive effects fade out so fast, why does vacation matter at all?”. We suppose that potential benefits of recurrent vacationing that develop over the years may not be captured by assessing short-term well-being or performance-related outcomes. In a sample of men at high risk for coronary heart disease, Gump and Matthews (2000) found more frequent annual vacation to be associated with a significant reduction in the risk of death during a 9-year follow up period. Although positive effects of vacationing might be transitory regarding the variables studied herein, we conclude that vacations do matter. There may be unstudied benefits of recurrent vacationing that develop in the long run and that definitely deserve research attention.

Biographical Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

Dr. Jana Kühnel works at the University of Konstanz, Germany, from where she also received her Ph.D. in 2009. Her research covers topics within positive organizational psychology (e.g., engagement at work, positive affect, benefits of recovery from work related strain).

Biographical Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References

Sabine Sonnentag is a full professor of Work and Organizational Psychology at the University of Konstanz, Germany. In her research, Dr. Sonnentag is mainly interested in how individuals can achieve sustained high performance at work and remain healthy at the same time. She studies recovery from job stress, proactive work behavior, learning, and self-regulation in the job context.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Biographical Information
  8. Biographical Information
  9. References
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