Effects of work stress on work-related rumination, restful sleep, and nocturnal heart rate variability experienced on workdays and weekends.

Journal of Occupational Health Psychology 2014, Vol. 19, No. 2, 217–230

© 2014 American Psychological Association 1076-8998/14/$12.00 DOI: 10.1037/a0036009

Effects of Work Stress on Work-Related Rumination, Restful Sleep, and Nocturnal Heart Rate Variability Experienced on Workdays and Weekends Tim Vahle-Hinz, Eva Bamberg, Jan Dettmers, Niklas Friedrich, and Monika Keller

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Universität Hamburg The present study reports the lagged effects of work stress on work-related rumination, restful sleep, and nocturnal heart rate variability experienced during both workdays and weekends. Fifty employees participated in a diary study. Multilevel and regression analyses revealed a significant relationship between work stress measured at the end of a workday, work-related rumination measured during the evening, and restful sleep measured the following morning. Work stress, measured as the mean of 2 consecutive workdays, was substantially but not significantly related to restful sleep on weekends. Work stress was unrelated to nocturnal heart rate variability. Work-related rumination was related to restful sleep on weekends but not on workdays. Additionally, work-related rumination on weekends was positively related to nocturnal heart rate variability during the night between Saturday and Sunday. No mediation effects of work stress on restful sleep or nocturnal heart rate variability via work-related rumination were confirmed. Keywords: heart rate variability, recovery, restoration, sleep, work stress

participants’ reports of feeling rested after a night of sleep, as assessed the following morning. We focused on the daily effects of work stress because incomplete day-to-day recovery may lead to serious health consequences over time (Geurts & Sonnentag, 2006). Furthermore, using a diary design, we were able to more closely observe the actual experience of the individuals, which was particularly important for our self-reported measure of sleep. Retrospective reports of restful sleep may be biased in that one poor night of sleep may remain prominent in memory and therefore influence sleep ratings over longer time periods (Gorin & Stone, 2001). Furthermore, because somatic restorative processes, such as the regeneration of energy resources or wound healing, take place during sleep (Uchino, Smtih, Holt-Lundstad, Campo, & Reblin, 2007), we included a measure of parasympathetic nervous activity (heart rate variability (HRV)) during the night. A predominant parasympathetic modulation of the heartbeat occurs during rest and recovery (Task Force, 1996) and is associated with regulatory processes of the human body (such as digestion). In addition to the direct effects of work stress on sleep and parasympathetic nervous activity during the night, we also investigated the mediating effect of work-related rumination. Reliving stressful experiences at work during off-work hours has been proposed to lead to a prolonged strain reaction, which might be responsible for the effect of work stress on sleep (Brosschot, Pieper, & Thayer, 2005). The present study has three main objectives: first, to investigate the lagged effects of work stress on restful sleep and nocturnal HRV experienced during workdays, as a physiological measure of health risks; second, to investigate the mediating effect of workrelated rumination on these effects; and third, to explore whether the effects of work stress observed on workdays carry over to the following weekend. In the next sections, we describe each objective in detail. Figure 1 graphically summarizes the proposed relationships.

Work stress is a risk factor for severe mental and physical health problems (Nixon, Mazzola, Bauer, Krueger, & Spector, 2011; Sonnentag & Frese, 2003), and more importantly, the impairment of recovery from work stress may result in ill health (Fritz, Sonnentag, Spector, & Mcinroe, 2010; Kivimäki et al., 2006; Meijman & Mulder, 1998; Schwartz et al., 2003; Zijlstra & Sonnentag, 2006). Sleep is a crucial period of recovery, and although it consumes a large portion of our time, sleep is the most critical natural period for psychological and somatic restorative processes (Brosschot, Van Dijk, & Thayer, 2007). Previous cross-sectional and longitudinal studies have shown that sleep impairment is a predictor of several disorders, such as cardiovascular disease, diabetes, depression, obesity, and even death (Åkerstedt, 2006). Impaired sleep is observed as a secondary symptom of many somatic and psychological disorders and precedes the development of such disorders (Broeren, Muris, Bouwmeester, Van der Heijden, & Abee, 2011). Owing to the central role of sleep in the development and maintenance of many disorders, examining the relationship between work stress and sleep remains an important research task. In the current study, we used a diary design and focused on the effects of work stress, as measured at the end of a workday, on

This article was published Online First March 17, 2014. Tim Vahle-Hinz, Eva Bamberg, Jan Dettmers, Niklas Friedrich, and Monika Keller, Department of Work and Organizational Psychology, Universität Hamburg, Hamburg, Germany. Monika Keller is now working at Unfallkasse Nord. This research was supported in part by grants from the Federal Ministry of Research and Education (BMBF; Grant-ID: 01FH09083). Correspondence concerning this article should be addressed to Tim Vahle-Hinz, Arbeits- und Organisationspsychologie, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany. E-mail: tim.vahle-hinz@ uni-hamburg.de 217

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Figure 1. The hypothesized model. a represents the proposed effects on workdays, and b represents the proposed effects on weekends.

Restful Sleep Several cross-sectional (Åkerstedt, Fredlund, Gillberg, & Jansson, 2002; Geiger-Brown, Trinkoff, & Rogers, 2011) and a few longitudinal studies (Burgard & Ailshire, 2009; de Lange et al., 2009) have shown that a relationship exists between work stress and sleep impairment. Moreover, impaired sleep is a predictor for several diseases (Åkerstedt, 2006). Accordingly, the relationship between work stress and sleep impairment might be a pathway by which work stress leads to ill health in the long run. However, although work stress has been proposed as a primary cause of sleep disturbances, longitudinal evidence for the relationship between work stress and sleep impairment remains limited (Åkerstedt, Nordin, Alfredsson, Westerholm, & Kecklund, 2012), particularly regarding the daily effects of work stress on self-reported measures of sleep. We propose that overnight effects of work stress resulting in nonrestful sleep are an important indicator of disrupted day-today recovery processes and are therefore crucial for one’s health (Meijman & Mulder, 1998). In the current study, we thus propose the following hypothesis: Hypothesis 1a: Work stress on a specific workday is negatively related to restful sleep as measured the morning following a night of sleep.

Work Stress and Health Risks as Assessed by Heart Rate Variability The model of allostatic load (McEwen, 1998) states that the body adapts to environmental changes via allostatic reactions (e.g., a higher heart rate or lower HRV). These reactions are not without costs. Allostatic load describes the wear and tear on the body as a result of maladaptive physiological reactions to stress. Of considerable importance is the detrimental effect of prolonged physiological activity (McEwen, 1998), which refers to the inability of the body to suppress physiological reactions to stress after a stressor has lessened. Studies that are focused on prolonged phys-

iological activity during off-work time—and that therefore examine physiological recovery and restoration—appear to have promising potential to elucidate the negative health consequences of stress in human daily life (Pieper & Brosschot, 2005; Schwartz et al., 2003). One important allostatic system is the autonomic nervous system (ANS). The ANS modulates bodily functions such as heartbeat and digestion. The modulation of bodily functions through the ANS allows the body to respond to external stimuli. Measurements of HRV are used to assess the activity of the two branches of the ANS: the sympathetic nervous system and the parasympathetic nervous system (Task Force, 1996). Heartbeats are modulated by the intrinsic activity of the sinus node. However, through an innervation of sympathetic and parasympathetic nerves, the ANS can alter the heartbeat and adapt its pace to environmental challenges. The resulting variability can be measured as time variations between successive heartbeats (Berntson et al., 1997). Using pharmacological receptor blockades, vagotomy, or electric nerve stimulation in animals, the physiological meaning of HRV indices, or at least the indices representing parasympathetic nervous activity, has been established (Akselrod et al., 1981; Malliani, Pagani, Lombardi, & Cerutti, 1991). The heartbeat is more synchronous with less variability during physical and physiological arousal because the sympathetic modulation of the heart is dominant (Task Force, 1996; Tarvainen & Niskanen, 2008), whereas higher variability occurs during rest and recovery, which is consistent with a predominantly parasympathetic modulation of the heartbeat (Task Force, 1996). Several studies have found a relationship between lower HRV and a wide range of diseases. Lower HRV is related to cardiovascular disease (Singer et al., 1988; Thayer & Lane, 2007; Tsuji et al., 1996), multiorgan dysfunction (Pontet et al., 2003), and diabetes (Liao et al., 1995). Additionally, Marsland et al. (2007) found a relationship between HRV and the immune system. Furthermore, a lowered HRV is associated with a higher mortality risk


EFFECTS OF WORK STRESS ON WORKDAYS AND WEEKENDS

after myocardial infarction (Kleiger, Miller, Bigger, & Moss, 1987; Task Force, 1996; Thayer & Lane, 2007). Two systematic reviews concluded that a relationship exists between work stress and lower HRV (Chandola, Heraclides, & Kumari, 2010; Togo & Takahashi, 2009). Previous studies have found a relationship between high effort–reward imbalance and reduced HRV (Hintsanen et al., 2007; Loerbroks et al., 2010). Additionally, several studies have indicated that high-strain groups have a lower HRV than low-strain groups (Collins & Karasek, 2010; Kang et al., 2004; van Amelsvoort, Schouten, Maan, Swenne, & Kok, 2000) and that a relationship exists between work stressors and lower parasympathetic nervous activity (Clays et al., 2011). However, other studies have found no such relationship (e.g., Riese, Van Doornen, Houtman, & De Geus, 2004). Furthermore, some studies have reported that a negative relationship exists between specific work arrangements, such as shift (Vrijkotte, van Doornen, & de Geus, 2000) or on-call work (Malmberg, Persson, Flisberg, & Ørbaek, 2011), and HRV. Based on the literature, we propose the following hypothesis: Hypothesis 2a: Work stress on a specific workday is negatively related to nocturnal HRV.

Work Stress and Work-Related Rumination Perseverative cognitions, such as work-related rumination, are defined as “the repeated or chronic activation of the cognitive representation of stress-related content” (Brosschot et al., 2005, 1045) and have been associated with impaired somatic (Verkuil, Brosschot, Gebhardt, & Thayer, 2010; Verkuil, Brosschot, Meerman, & Thayer, 2012; Verkuil & Brosschot, 2012) and mental health (Esbjørn, Reinholdt-Dunne, Caspersen, Christensen, & Chorpita, 2013; Wiersma et al., 2011). The central argument regarding perseverative cognitions indicates that unwinding after a stressful workday is impaired if the stressful experience is relived during time off work. In an experimental study, Glynn, Christenfeld, and Gerin (2007) found that participants showed elevated cardiovascular responses when they recalled a laboratory stress experience. Previous studies have investigated the relationship between work stress and work-related rumination. Berset, Elfering, Lüthy, Lüthi, and Semmer (2011) showed that time pressure and effort–reward imbalance led to heightened work-related ruminative thoughts. Additionally, in a diary study, Cropley and Purvis (2003) found that high-strain teachers reported more ruminative thoughts in the evening. In a longitudinal study, Grebner, Semmer, and Elfering (2005) found a synchronous relationship between work stressors and the inability to switch off after work. Taken together, the literature provides evidence of a relationship between work stress and ruminative thoughts regarding work. However, only the study of Cropley and Purvis (2003) examined the day-level effects of work stress on ruminative thoughts. We propose the following hypothesis: Hypothesis 3a: Work stress on a specific workday is positively related to work-related rumination later that evening.

Work-Related Rumination and Restful Sleep Ruminating can be used to distinguish between good and bad sleepers, and there is evidence for a relationship between rumina-

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tion and bad sleep for patients suffering from insomnia (Carney, Edinger, Meyer, Lindman, & Istre, 2006; Carney, Harris, Moss, & Edinger, 2010). Wicklow and Espie (2000) used content analyses of bedtime thoughts and found a relationship among rehearsing past events, planning and problem solving, and later sleep onset, as measured via actigraphs. Zoccola, Dickerson, and Lam (2009) also observed a relationship between trait rumination and objectively measured longer sleep onset latencies. Thomsen, Yungmehlsen, Christensen, and Zachariae (2003) showed a partial correlation between rumination and sleep quality, controlling for negative emotions. In an experimental study, Guastella and Moulds (2007) also found a relationship between rumination and bad sleep. Moreover, Cropley, Dijk, and Stanley (2006) confirmed that workrelated rumination is negatively related to sleep quality in a diary study, and Berset et al. (2011) found such a negative relationship in a cross-sectional study. Based on the cited literature, we propose the following hypothesis: Hypothesis 4a: Work-related rumination on a specific workday is negatively related to restful sleep as measured the morning after a night of sleep.

Work-Related Rumination and Heart Rate Variability Two experimental studies have found a relationship between rumination and lower HRV (Key, Campbell, Bacon, & Gerin, 2008; VanOyen Witvliet, DeYoung, Hofelich, & DeYoung, 2011). Key et al. (2008) showed that participants with low scores on a trait rumination scale but who ruminated (state rumination) about the stressful task had lower HRV compared with other participants. VanOyen Witvliet et al. (2011) reported a lower HRV compared with baseline measures under the experimental condition of ruminating about a personal offense. Three ambulatory assessment studies linked worry episodes to lower HRV (Brosschot et al., 2007; Pieper, Brosschot, van der Leeden, & Thayer, 2007, 2010). One study explicitly reported a prolonged effect of two hours following worry episodes (Pieper et al., 2010). Furthermore, Brosschot et al. (2007) found a negative relationship between worry episodes and both daytime and nighttime HRV. The authors stated that “the role of worry as a cause of prolonged cardiac activation may be even more convincing if it can be shown that its cardiac effects are prolonged during night” (Brosschot et al., 2007, p. 40). Worry and rumination are considered to be two distinct constructs (Broeren et al., 2011; Carney et al., 2010; Mitchell, Mogg, & Bradley, 2012) in which worry is more future oriented and rumination focuses on previous events (Broeren et al., 2011; Carney et al., 2010). However, the operationalization of worry episodes in the studies of Pieper et al. (Pieper et al., 2007, 2010) includes both worry and ruminative thinking. Therefore, these effects of lower HRV can also be attributed to rumination. The study of Brosschot et al. (2007) clearly operationalized worry instead of rumination; therefore, the authors did not find a relationship between rumination and nocturnal HRV. Furthermore, to the best of our knowledge, no study has investigated the prolonged cardiac effect of work-related rumination with respect to nocturnal HRV. Because worry and rumination are discussed as constructs of perseverative cognition (Brosschot et al., 2005) and there is evidence for a prolonged physiological effect of perseverative cognitions (Pieper & Brosschot, 2005), we propose the following hypothesis:

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Hypothesis 5a: Work-related rumination on a specific workday is negatively related to nocturnal HRV.


Rumination as a Mediator Even after individuals leave the workplace, work stress has been shown to be related to psychological and physiological responses (Frankenhaeuser, 1981). An important question therefore is, how does work stress affect well-being during time off work? Repetitive thoughts regarding a stressful event, such as ruminative thinking about stressful work experiences, are proposed as an extension to stress theory because they provide a mechanism that links stressful work experiences to impaired recovery processes after work (Brosschot et al., 2005). Berset et al. (2011) demonstrated in their cross-sectional study that the relationship between work stress and sleep quality was mediated via work-related rumination. By contrast, Cropley et al. (2006) tested this mediation effect by using a diary design and reported a small reduction of the work stress beta weight; therefore, no mediation was found. However, in a multistudy paper, Zawadzki, Graham, and Gerin (2012) noted the importance of rumination as a mediator. Although the empirical results in the literature regarding the mediating effect of work-related rumination on the relation between work stress and sleep quality have been mixed, because there is strong reason theoretically to assume that such a mediation effect exists, we propose the following hypotheses.

The effort-recovery model indicates that work demands must no longer be present for recovery processes to occur (Meijman & Mulder, 1998). Therefore, the weekend fulfills the requirement for recovery based on this model. The effects of work stress should therefore be weaker on weekends than during workdays. However, ruminating about past stressful work events may disrupt recovery processes on weekends. Therefore, whether work stress during the week translates into disrupted recovery processes on weekends and whether this relationship is mediated via work-related rumination are interesting exploratory research questions. Accordingly, we investigated whether the proposed relationships between work stress, work-related rumination, restful sleep, and nocturnal HRV carry over from workdays to weekends. We therefore expanded our hypotheses of the effects of work stress experienced during workdays to include the following weekend. Specifically, we were interested in whether work stress during a specific work week predicts restful sleep, nocturnal HRV, and work-related rumination on weekends (hypotheses 1b to 3b). We were also interested in whether the proposed relationships between work-related rumination and our dependent variables apply on weekends (hypotheses 4b and 5b) and whether the relationship between work stress during a specific work week and our dependent variables is mediated via work-related rumination on weekends (hypotheses 6b and 7b). Please see Figure 1, which graphically illustrates our hypotheses regarding the effects of work stress on workdays and weekends.

Method Hypothesis 6a: The relationship between work stress measured at the end of a specific workday and restful sleep is mediated by work-related rumination measured on the evening of a specific workday. Hypothesis 7a: The relationship between work stress measured at the end of a specific workday and nocturnal HRV is mediated by work-related rumination measured on the evening of a specific workday. In the present study, we tested for such a mediation effect on a daily basis and measured all variables separately over time. Furthermore, there are no prior studies testing this mediation hypothesis with regard to HRV outcomes.

Effects on Weekends In addition to the effects of work stress during workdays, we also explored whether work stress during the week predicts restful sleep and nocturnal HRV on weekends and the potential mediating effect of work-related rumination on these relationships. We therefore explored whether the effects of work stress experienced on workdays carry over to the following weekend. Research emphasizes differences in well-being between workdays and weekends (Helliwell & Wang, 2013) and supports the importance of weekend activities and experiences for well-being (Fritz et al., 2010; Ryan, Bernstein, & Brown, 2010) and job performance (Fritz & Sonnentag, 2005). We suggest that weekend recovery is important for well-being in daily life and that disruptions in weekend recovery might be related to negative health outcomes over time.

Procedure and Sample The data were drawn from a subsample of a larger research project investigating on-call work. Organizations were contacted to participate in the research project concerning the health consequences of on-call work. After the agreement of the employers and the work council, the employees were invited to participate in the study. To participate in the physiological assessment for the substudy, the employees had to fulfill the following criteria: no heavy smoking, no continuous drug intake, no chronic disease (e.g., rheumatism, diabetes, arteriosclerosis), no pregnant or nursing status, and no insomnia diagnosis. The larger study consisted of a diary study that compared days with on-call work and days with no on-call work. The participants had defined periods of being on call and periods with regular work shifts, where no on-call work was required. Only measurements obtained from days with no on-call work were included in the present study. Additionally, we took great care to ensure that participants worked on a Monday to Friday schedule and had the weekend off, which was a precondition for participation in the physiological substudy. Initially, 55 employees agreed to participate. However, five employees were excluded from the final sample for the following reasons: allergic reactions to the electrodes (1), data were only available for the on-call period (1), a defective electronic diary (1), and working night shifts (2). The remaining 50 employees were from five different organizations in the fields of public utilities, public transportation, logistics, and home care. Forty-eight employees were male, and only two were female. The mean age was M ⫽ 42 years (SD ⫽ 8 years). Most participants held a secondary educational degree (42%) and had completed industrial training



(76%). Eighty percent of the participants worked approximately 40 hours per week, and nearly all participants had worked for their current employer for more than five years (96%). The participants were visited at their workplace one day before the beginning of the study, and a general questionnaire with questions about sociodemographics and control variables was distributed. The device for measuring HRV (Actiheart, Cambridge Neurotechnology, Cambridge, U.K.) was then fitted, and the handling of a handheld computer (used as an electronic diary) was illustrated. The participants were visited again after two days of measurement to store the HRV data and fit a new device for the weekend assessment. In the case of technical problems, the participants were provided with a mobile number to contact a member of the research staff. The participants received 25€ per assessment day for their participation. The study was approved by the ethics committee of the German Psychological society.

Design We used an electronic diary (Dell ⫻51, mQuest 5.0) to assess work stress, work-related rumination, and restful sleep on two consecutive workdays and on weekends. An alarm clock was set to remind the participants to complete the electronic diary on three occasions each day. Work stress was measured when the participants left work. Work-related rumination was measured in the evening before the participants went to bed. Restful sleep was measured on awakening. Each measurement time was recorded by the electronic diary to ensure that all data were collected at the specified time. No work stress measurements were collected on the weekends because the participants had the weekend off. Workrelated rumination was measured on Saturday evening, and restful sleep was measured on Sunday morning. HRV was assessed on two nights during the week and on Saturday night. Figure 2 illustrates the study design.

Measures To assess work stress at the end of a workday, we constructed an index by multiplying the subscale measuring work-related overload, obtained from the instrument for the salutogenesis job analysis (SALSA; Rimann & Udris, 1997), and the hours worked that day. For the subscale “work-related overload,” three items

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were rated on a five-point scale (1 ⫽ not applicable to 5 ⫽ applicable). One sample item was You have enough time to get your work performed (reverse coded). The average Cronbach’s alpha for both measurement days was .78 (Day one ⫽ .77; Day two ⫽ .78). Work-related rumination was measured with one item from the irritation scale (Mohr, Rigotti, & Müller, 2005): Today I had to think about work-related problems at home. The item was rated on a five-point scale (1 ⫽ I totally disagree to 5 ⫽ I totally agree). Restful sleep was assessed using one item from a scale developed by Jenkins, Stanton, Niemcryk, and Rose (1988). The participants rated their tiredness from the previous night on a 5-point scale (Item: After last night I felt tired and exhausted; 5 ⫽ I totally disagree to 1 ⫽ I totally agree). The item was reverse coded; therefore, high values indicated restful sleep.

Nocturnal HRV Ambulatory recordings. We measured inter-beat-intervals of successive heartbeats (IBI) using the Actiheart monitor (Cambridge Neurotechnology, Cambridge, U.K.) to assess nocturnal HRV. Actiheart simultaneously measures the heart rate and movement counts. Because this device is light and flat and allows for simultaneously measurements of mobility, it is particularly suitable for diary studies in the work context. Validity and measurement reliability for this device have been reported (Brage, Brage, Franks, Ekelund, & Wareham, 2005). ECG was sampled with a frequency of 128 Hz, but the IBIs were logged using an interpolation with a 1000 Hz resolution. Processing the recordings. To ensure the HRV measurements were obtained when the participants were asleep, we combined data obtained from the electronic diary with objectively defined times of falling asleep and waking. Specifically, when the participants woke up, they stated the time that they fell asleep during the previous evening and the time that they awoke. We used heart rate and activity data to objectively determine the periods of sleep. Trinder et al. (2001) showed that heart rate rapidly increases by approximately 10 –15 beats per minute upon awakening. Similarly, heart rate decreases at night (Thayer & Lane, 2007). Using this information, we checked whether the self-reported times of falling asleep and awakening were physiologically plausible to define a sleep period each day. Fifteen minutes of every full hour of the sleep period was used to calculate the HRV measurements.

Figure 2. Study design.


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Beginning at the time that the participants fell asleep, fifteen 60-s segments, which were suitable for analysis, were derived. The segments were visually checked for artifacts and according to a published algorithm that uses percentile-based distributions of the individual IBI series (Berntson, Quigley, Jang, & Boysen, 1990). This check was performed using ARTiiFACT (Kaufmann, Sütterlin, Schulz, & Vögele, 2011). Detected artifacts were corrected using a cubic spline interpolation (Kaufmann et al., 2011). However, segments with more than 10% artifacts according to the median number of beats per 1-min interval in the corresponding sleep period were eliminated from further analyses. HRV measurements. The HRV parameters were analyzed using Kubios HRV Version 2.0 (Tarvainen & Niskanen, 2008). However, before analyzing the HRV parameters, the IBI data segment was again visually checked for artifacts, and the remaining artifacts were manually corrected. If this correction did not result in a visually valid data segment, the segment was excluded from further analysis. At least 90% of the night data had to be analyzable to include the night into subsequent statistical analyses. Subsequently, the trend components were removed using the smoothness priors method (Tarvainen, Ranta-aho, & Karjalainen, 2002). From the detrended data, the time domain measure root mean square of successive differences (RMSSD), which represented parasympathetic nervous activity, was calculated. We used the RMSSD to index parasympathetic nervous activity because this parameter is less affected by breathing (Penttilä et al., 2001). The RMSSD derived from the 60-s segments were aggregated according to the previously defined sleep period. The measurements and analyses were performed in accordance with the recommendation of the Task Force of The European Society of Cardiology and The North American Society of Pacing and Electrophysiology (1996). Because the RMSSD were positively skewed and nonnormally distributed, we used natural log transformation, which resulted in a normal distribution (Shapiro-Wilk-Test: W ⫽ .99, ns). Control variables. Age and sex (1 ⫽ female, 2 ⫽ male) were included as control variables in all our analyses. The timeseparated measurement of our variables controls for common method bias. Additionally, we added participants’ negative mood at times of measurement of our independent variables into our analyses. Therefore, we were able to partial out participants’ affect during ratings, which also reduces common method bias. Negative mood was measured with a two-item scale developed by Wilhelm and Schoebi (2007). The scale ranges from 5 ⫽ tired/without energy to 1 ⫽ awake/full of energy. We chose this specific measurement because it is closely related in content to our dependent variable “restful sleep.” Correlations between the two items during the week ranged from .63 to .83. The correlation on Sunday morning was .78. Concerning HRV, we accounted for several confounding factors. We tested for their effect on HRV in separate analyses and only included significant predictors. On a general level, we assessed the effect of contraceptive use, subjective health condition (one item, 5 ⫽ very well to 1 ⫽ poor), subjective fitness (one item, 5 ⫽ very fit, doing competitive sports in free time to 1 ⫽ doing no exercise at all), household income, season, body mass index, smoking status (1 ⫽ yes, 2 ⫽ no), depressive mood (15 items from the ADS questionnaire; Hautzinger & Bailer, 1993), and positive and negative affect (PANAS; Watson & Clark, 1988). On a day

level, we assessed the effect of caffeine or tobacco intake, medication use, time falling asleep (operationalized as the hours since midnight of the previous day), hours slept that night, amount of available data for analysis, and high physical effort during the day. Only the smoking and age variables had a significant effect on HRV and were included as control variables in the further analyses.

Analysis Workday analysis. Because our data possessed a hierarchical structure in which the days were nested in persons, we conducted a multilevel analysis using the nlme package in R (R Core Team, 2012). Following Bliese’s (2012) recommendations, we began by testing an unconditional means model to calculate the ICC values and test whether the intercept variance was significantly different from zero. The ICC1 for rumination was .11 (ICC2 ⫽ .64), .43 (ICC2 ⫽ .60) for restful sleep, and .82 (ICC2 ⫽ .89) for nocturnal HRV. Taken together, the results indicate the need for a multilevel approach. In the second step, we tested our hypotheses in separate multilevel models. Because of the temporal structure of our data, we controlled for autocorrelation and heteroscedasticity (Bliese, 2012). In the current study, we were interested in the day-level effects and not in the unique within-person effects. Consequently, we centered the independent variables at the sample means (Ohly, Sonnentag, Niessen, & Zapf, 2010, p. 89; also see Fritz & Sonnentag, 2009 for a similar approach). Although person-mean centering is frequently recommended (Enders & Tofighi, 2007; Ohly et al., 2010), this approach would remove all the between personvariance and change the meaning of the predictors. In sum, in the present study, we examined whether a high- or low-stress workday compared with the participants’ average experience was related to our outcomes (grand-mean centering) rather than whether high or low daily work stress compared with the average workday of a specific person was related to our outcomes (person-mean centering). We used list-wise deletion to handle missing data in all our analyses. Weekend analysis. We conducted a multiple regression analysis using R to test our weekend hypotheses. We ran separate analyses and used the work stress means from two consecutive workdays as a predictor of work-related rumination on Saturday evening, restful sleep on Sunday morning, and nocturnal HRV during the night between Saturday and Sunday. We visually inspected our data for a normal distribution of the residuals. Heteroscedasticity was inspected with the White test (White, 1980). The Durbin-Watson statistics ranged from 1.5 to 2.1, which indicated that the statistics for the autocorrelation of the residuals were within recommended boundaries (Bühner, 2011). The assessment during the week was temporarily followed by a weekend data collection for some participants. For the current analysis, we excluded eight participants, which resulted in a sample of 42 male employees. Missing data were eliminated through list-wise deletion. Mediation analysis. We tested for the indirect effects proposed in our mediation hypotheses with the Monte Carlo Method adapted for multilevel data (Bauer, Preacher, & Gil, 2006; Selig & Preacher, 2008). This procedure is found to perform similarly to other bootstrap methods. Furthermore, it can be used within multilevel frameworks and with small sample sizes (Preacher & Selig,



2012). To be comparable with our multilevel effects, we also tested for the indirect effects in our weekend analysis by using the same procedure. Reverse causation analysis. Studies on the relationship between work stress, rumination, and sleep have noted the possibility of reverse causation. Namely, with regard to work stress, Åkerstedt (2006) found that individuals might not want to handle upcoming demands and were therefore more likely to perceive them as stressful. Similarly, Burgard and Ailshire (2009) stated that workers might view their working conditions as less favorable after a bad night of sleep. With respect to rumination, disruption of daytime functions attributable to inadequate restful sleep might initiate rumination (Carney et al., 2010; Mitchell et al., 2012). Empirical evidence partially supports these assumptions. For example, Minkel et al. (2012) showed in an experimental study that nonrested participants reacted with more stress to a low-stress task compared with rested controls. No differences were observed in a high-stress task. Regarding daytime functioning, previous studies have found a negative relationship with insomnia (Ustinov et al., 2010) and sleep quality (Ahrberg, Dresler, Niedermaier, Steiger, & Genzel, 2012). However, other studies have not found such a relationship for insomnia (Riedel & Lichstein, 2000). Because reverse causation is theoretically plausible in our study, we addressed such a possibility in our workday analysis.

Results Correlations The means (M), standard deviations (SD), and zero-order correlations for all the study variables in our workday analysis are shown in Table 1. Work stress was positively correlated with work-related rumination (r ⫽ .51, p ⱕ .01) and negatively correlated with restful sleep (r ⫽ ⫺.30, p ⱕ .01). Additionally, there was a weak but nonsignificant negative relationship between work stress and RMSSD (r ⫽ ⫺.14, ns). Work-related rumination was negatively related to restful sleep, but this relationship was only marginally significant (r ⫽ .18, p ⱕ .10). There was no relationship between work-related rumination and RMSSD (r ⫽ ⫺.05, ns). RMSSD was significantly negatively correlated with age (r ⫽ ⫺.37, p ⱕ .01) and positively correlated with smoking (r ⫽ .36, p ⱕ .01), thus indicating that being younger and a nonsmoker was related to higher parasympathetic nervous activity at night.

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Table 2 shows the means (M), standard deviations (SD), and zero-order correlations for all the study variables in our weekend analysis. Work stress during the week was positively but not significantly related to work-related rumination on Saturday evening (r ⫽ .16, ns) and negatively but not significantly related to restful sleep on Sunday morning (r ⫽ ⫺.24, ns) and RMSSD during the night between Saturday and Sunday (r ⫽ ⫺.15, ns). Work-related rumination, measured on Saturday evening, was negatively related to restful sleep on Sunday morning (r ⫽ ⫺.45, p ⱕ .01) and positively but not significantly related to RMSSD during Saturday night (r ⫽ .25, ns). Parasympathetic nervous activity during Saturday night was higher for nonsmokers (r ⫽ .50, p ⱕ .01) and younger participants (r ⫽ ⫺.30, p ⱕ .10). Additionally, RMSSD during Saturday night was negatively but not significantly related to negative mood on Saturday evening (r ⫽ ⫺.26, ns) and positively but not significantly related to negative mood during the week (measured as the mean of two consecutive workdays; r ⫽ .22, ns). The tables in the following sections report significant results, whereas nonsignificant results are reported solely within the text. However, these results are available from the corresponding author upon request.

Workday Analysis Effects of work stress on restful sleep, nocturnal HRV, and work-related rumination. Concerning hypothesis 1a, our workday analysis showed that work stress measured at the end of a workday was a significant negative predictor of restful sleep measured the following morning (see Table 3). Work stress measured at the end of a workday was not associated with nocturnal HRV (hypothesis 2a; Est. ⫽ .00, t(29) ⫽ 0.32, ns, differences in ⫺2ⴱLog ⫽ 8.99, ⌬df ⫽ 5, p ⫽ ns, n ⫽ 74 days) but proved to be a significant positive predictor of work-related rumination measured that evening (see Table 3). Therefore, regarding the effects of work stress during workdays, hypotheses 1a and 3a were supported, and hypothesis 2a was rejected by these results. Effects of work-related rumination on restful sleep and nocturnal HRV. We examined whether work-related rumination measured in the evening of a workday predicts restful sleep the next morning (hypothesis 4a) and nocturnal HRV (hypothesis 5a). Work-related rumination measured on the evening of a workday was not related to restful sleep measured the following morn-

Table 1 Means, Standard Deviations, and Zero-Order Correlations of the Day Variables Variable 1. 2. 3. 4. 5. 6. 7. 8. 9.

Sex Age Smoker Negative mood afternoon Negative mood evening Work stress Rumination Restful sleep RMSSD

M

SD

1

2

3

4

5

6

7

8

9

1.96 41.96 1.76 2.64 3.45 19.70 1.76 3.37 35.70

0.20 7.72 0.43 1.02 1.12 7.82 0.76 1.06 19.22

— .04 ⫺.11 .08 ⫺.10 ⫺.09 ⫺.07 ⫺.03 ⫺.04

— ⫺.02 ⫺.24 ⫺.08 ⫺.04 .16 .18 ⫺.37

— .03 .10 ⫺.03 .03 ⫺.04 .36

— .55 .21 .15 ⫺.27 .00

— .11 .15 ⫺.35 ⫺.08

— .51 ⫺.30 ⫺.14

— ⫺.18 ⫺.05

— ⫺.08

—

Note. n ⫽ 77–100 (days); r ⱖ .30 is significant at p ⬍ .01; sex: 1 ⫽ female, 2 ⫽ male; smoker: 1 ⫽ yes, 2 ⫽ no; RMSSD ⫽ root mean square of successive differences; M and SD are presented as raw data; correlations are based on the natural log transformed variable.

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Table 2 Means, Standard Deviations, and Zero-Order Correlations of the Weekend Variables Variable


1. 2. 3. 4. 5. 6. 7. 8.

Age Smoker Weekly negative mood afternoon Negative mood Sat evening Weekly work stress Rumination Sat Restful sleep Sun RMSSD

M

SD

1

2

3

4

5

6

7

8

42.60 1.74 2.59 3.09 18.72 1.39 3.38 33.07

7.32 0.45 0.88 1.14 6.67 0.63 1.03 17.4

— ⫺.08 ⫺.27 ⫺.16 .04 .02 .33 ⫺.30

— .02 .09 .02 .11 ⫺.11 .50

— .40 .15 .01 ⫺.27 .22

— .31 .23 ⫺.50 ⫺.26

— .16 ⫺.24 ⫺.15

— ⫺.45 .25

— .02

—

Note. n ⫽ 35– 42 (individuals); r ⱖ .33 is significant at p ⬍ .05, and r ⱖ .45 is significant at p ⬍ .01; sex: 1 ⫽ female, 2 ⫽ male; smoker: 1 ⫽ yes, 2 ⫽ no; Sat ⫽ Saturday; Sun ⫽ Sunday; RMSSD ⫽ root mean square of successive differences; M and SD are presented as raw data; correlations are based on the natural log transformed variable.

ing (Est. ⫽ ⫺.23, t(41) ⫽ ⫺1.58, ns, differences in ⫺2ⴱLog ⫽ 14.04, ⌬df ⫽ 4, p ⱕ .01, n ⫽ 91 days) or nocturnal HRV measured on the same night (Est. ⫽ .01, t(31) ⫽ 0.10, ns, differences in ⫺2ⴱLog ⫽ 15.83, ⌬df ⫽ 5, p ⱕ .01, n ⫽ 77 days). Hypotheses 4a and 5a were rejected.

Weekend Analysis Effects of work stress on restful sleep, nocturnal HRV, and work-related rumination. In the regression analysis concerning the effects of work stress on weekends, we did not observe associations among work stress (measured as the mean of two consecutive workdays), restful sleep measured on Sunday morning (␤ ⫽ ⫺.21, ns, R2 adj. ⫽ .12, F(3, 33) ⫽ 2.62, p ⱕ .10, n ⫽ 37 individuals), nocturnal HRV during Saturday night (␤ ⫽ ⫺.14, p ⫽ ns, R2 adj. ⫽ .34, F(4, 26) ⫽ 4.81, p ⱕ .01, n ⫽ 31 individuals), or work-related rumination measured on Saturday evening (␤ ⫽ .15, ns, R2 adj. ⫽ ⫺.06, F(3, 34) ⫽ 0.34, ns, n ⫽ 38 individuals). Concerning our weekend analysis, hypotheses 1b, 2b, and 3b were rejected. Effects of work-related rumination on restful sleep and nocturnal HRV. Our weekend analysis indicated that the workrelated rumination measured on Saturday evening was a negative predictor of restful sleep measured Sunday morning (see Table 4). Hypothesis 4b was supported by this result. Work-related rumination measured on Saturday evening was a significant positive predictor of nocturnal HRV during Saturday night. Additionally, negative mood measured on Saturday evening was a significant negative predictor of nocturnal HRV. Table 4 summarizes these results. As the effect of work-related rumination on nocturnal HRV is opposite of our prediction, hypothesis 5b was rejected.1

Mediation Analysis Although we could not always establish a direct relationship between work stress and our dependent variables in our analyses, we tested for the significance of indirect effects (see Hayes, 2009; Rucker, Preacher, Tormala, & Petty, 2011). However, in both our workday and our weekend analysis, 95% confidence intervals included zero. Therefore, no significant indirect effects from work stress on restful sleep/nocturnal HRV via work-related rumination were confirmed (the results are not shown but can be obtained from the corresponding author). Accordingly, hypotheses 6a/b and 7a/b were rejected.

Reverse Causations Analysis No reverse causations were observed in our analyses. Thus, a bad night of sleep did not predict work stress or work-related rumination later that day (work stress: Est. ⫽ .18, t(36) ⫽ 0.26, ns, differences in ⫺2ⴱLog ⫽ 42.42, ⌬df ⫽ 3, p ⱕ .01, n ⫽ 85 days; work-related rumination: Est. ⫽ .06, t(37) ⫽ 0.75, ns, differences in ⫺2ⴱLog ⫽ 14.57, ⌬df ⫽ 3, p ⱕ .01, n ⫽ 87 days).

Discussion The present study shows the lagged effects of work stress on work-related rumination, restful sleep, and nocturnal HRV experienced during both workdays and weekends. Specifically, we demonstrated that work stress measured at the end of a workday led to more ruminative thinking about work in the evening and less restful sleep measured the following morning. However, these effects of work stress were not observed on weekends. Work stress during the week, measured as the mean of two consecutive workdays, was not significantly associated with work-related rumination or restful sleep on weekends. However, concerning the relationship with restful sleep, we observed a substantial but nonsignificant correlation in the predicted direction (r ⫽ ⫺.24). Therefore, the lack of support for our weekend hypothesis could be due to the small sample size. Taken together, our results further support research indicating that strain reactions to stress at work do not stop when individuals leave the workplace (Zijlstra & Sonnentag, 2006). However, the spillover of work stress into the weekend was not fully supported by our study. Perseverative cognitions are discussed as a pathway from work stress to prolonged strain reactions (Brosschot et al., 2005). However, the present study did not find support for this pathway because we failed to establish mediation in our day and weekend analyses. This result is consistent with previous research. Cropley et al. (2006) also failed to find a mediation effect of work-related rumination in the relation between work stress and sleep in their diary study. However, Berset et al. (2011) were able to show a mediation effect in a cross-sectional study. Such inconclusive 1 Burton, Rahman, Kadota, Lloyd, and Vollmer-Conna (2010) demonstrated that a reduced RMSSD was a predictor of repeated awakenings during the night. We therefore suggest that, in line with our predictions, a poor night of sleep (e.g., as a result of multiple awakenings) leads to reduced RMSSD.


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Table 3 Multilevel Estimates for Work Stress Predicting Restful Sleep and Work-Related Rumination Restful sleep Null model Estimate (SE)


Variable Intercept Age Gender Smoker Negative mood afternoon Work stress ⫺2 ⫻ Log (lh) Differences of ⫺2 ⫻ Log df Level 1 intercept variance (SE) Level 2 intercept variance (SE)

Estimate (SE)

t ⴱⴱ

3.38 (0.13)

Work-related rumination Model 1

26.07

269.71 3 0.64 (0.80) 0.49 (0.70)

Null model Estimate (SE)

t ⴱⴱ

3.40 (0.12) 0.02 (0.02) ⫺0.18 (0.59)

28.13 1.15 ⫺0.31

⫺0.18 (0.11) ⫺0.03 (0.01) 255.57 14.14ⴱⴱ 7 0.61 (0.78) 0.35 (0.59)

⫺1.66 ⫺2.29ⴱ

1.75 (0.09)

204.56 3 0.30 (0.54) 0.28 (0.53)

Model 1 Estimate (SE)

t ⴱⴱ

18.58

1.76 (0.08) 0.02 (0.01) 0.21 (0.36) 0.63 (0.18) 0.12 (0.07) 0.05 (0.01) 181.69 22.87ⴱⴱ 9 0.23 (0.48) 0.16 (0.40)

t 21.32ⴱⴱ 1.51 0.58 3.42ⴱⴱ 1.79 4.18ⴱⴱ

Note. Restful sleep: n null model ⫽ 49 individuals, 94 days; n model 1 ⫽ 47 individuals, 89 days, df for t values range from 40 to 44; Work-related rumination: n null model ⫽ 49 individuals, 94 days; n model 1 ⫽ 48 persons; 90 days df for t values range from 40 to 45. ⴱ p ⱕ .05. ⴱⴱ p ⱕ .01.

results might be observed for several reasons: first, the mediation effect might be more relevant for chronic stress than for day-level stress. The stressful experience of a specific day might be sufficiently strong and may not require amplification by mental representations. Namely, ruminating in the evening after a stressful workday might not be necessary to translate the negative effects of work stress into impaired sleep. However, individuals under chronic work stress conditions may anticipate work stress to be present in the future. Therefore, ruminating about previous stressful events might also imply that they will occur again. Thus, under chronic stress conditions, the effects of worry (thoughts regarding the apprehension of future events) and rumination (thoughts regarding the experience of past stressful events and their meaning) might be combined. Second, authors of previous work have indicated that an emotional arousal is necessary to evoke negative effects of rumination (Cropley, Michalianou, Pravettoni, & Millward, 2012; Thomsen et al., 2003). Thomsen et al. (2003) referred to the associative networks theory, which implies that if an emotion is evoked, associated information will be activated and will

Table 4 Regression Analyses of Work-Related Rumination Saturday Evening on Restful Sleep Sunday Morning and Nocturnal HRV During Saturday Night Restful sleep Variable Age Smoker Negative mood Sat evening Rumination R2 Adj. R2

␤ 0.29 ⫺0.37 ⫺0.38

Nocturnal HRV

t 2.32

ⴱ

⫺2.93ⴱⴱ ⫺3.00ⴱⴱ 0.45 0.41

␤

t

⫺0.39 0.43 ⫺0.42 0.30

⫺2.97ⴱⴱ 3.31ⴱⴱ ⫺3.17ⴱⴱ 2.25ⴱ 0.52 0.45

Note. Restful sleep: n ⫽ 40 individuals, F(3, 36) ⫽ 9.94, p ⱕ .01; Nocturnal HRV: n ⫽ 35 individuals, F(4, 30) ⫽ 8.00, p ⱕ .01. smoker: 1 ⫽ yes, 2 ⫽ no; Sat ⫽ Saturday. ⴱ p ⱕ .05. ⴱⴱ p ⱕ .01.

amplify the emotion. In this way, work stress that leads to emotional arousal (e.g., social conflicts at work) might also lead to impaired sleep via ruminative thoughts regarding the incident. However, work stress that is mainly exhausting might lead directly to impaired sleep without the amplification of ruminative thoughts. Because we measured work stress as an index calculated by multiplying work overload by the hours worked, we did not explicitly include an emotional component. Future studies focusing on emotional or social aspects of work stress and their relationship with impaired sleep and work-related rumination might elucidate the inconclusive results of previous research. This conjecture is further supported by a longitudinal study that reports that particularly negative emotional work experiences are related to poor sleep (Burgard & Ailshire, 2009). Thinking about work-related problems during free time leads to relived work stress. Thus, mental representations of stress can elicit strain responses, even if the stressor is not present (Glynn et al., 2007). This finding was partly supported by our results. Days with higher work-related rumination in the evening did not lead to reduced feelings of restful sleep the following morning. However, work-related rumination on Saturday evening was a strong negative predictor of restful sleep measured on Sunday morning. Several studies have investigated the relationship between mental stress representations and sleep (Broeren et al., 2011; Carney et al., 2006; Guastella & Moulds, 2007; Thomsen et al., 2003), but only a few studies have found a relationship between work-related rumination and sleep (Berset et al., 2011; Cropley et al., 2006; Querstret & Cropley, 2012). Additionally, to the best of our knowledge, no studies have investigated this relationship with respect to weekends. Because the weekend is traditionally a time for recovery, thinking about work-related problems might reduce the regeneration effect of the weekend. Our results suggest that thinking about work-related problems over the weekend is more strongly related to less restful sleep compared with thinking about work-related problems on workdays. Ruminating about workrelated problems leads to less restful sleep on weekends but not on workdays. This interesting difference in the effect of ruminating


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about work-related problems between weekends and workdays should be investigated further in future studies. Regarding nocturnal HRV, we did not find support for any of our hypotheses. Work stress was not associated with nocturnal HRV, and work-related rumination had an effect opposite of our prediction. As stated above, our work stress measure did not include a social or emotional component of work stress. Future studies should include different measures of work stress to assess its relationship with HRV. Additionally, Togo and Takahashi (2009) stated in their review concerning HRV and occupational health that studies using a homogenous sample tend to report inconclusive results. The null results concerning work stress in our study may have been observed because the majority of our sample worked for the same company. However, we also observed no relationship between workrelated rumination and nocturnal HRV in our workday analysis. Research concerning the relationship between worry episodes and HRV indicates that the duration of worry episodes is more important than the frequency of worry episodes (Brosschot & Van den Doef, 2006; Brosschot et al., 2007). Regarding our results, we only measured work-related rumination once in the evening and did not account for frequency or duration. However, as physiological activity during the night is proposed to be important for the restorative processes of sleep (Brosschot et al., 2007), it is important to further investigate this relationship in future studies. The weekend analysis showed a positive relation between workrelated rumination measured on Saturday evening and nocturnal HRV measured on Saturday night (␤ ⫽ .30, p ⱕ .05, R2 adj. ⫽ .45, F(4, 30) ⫽ 8.00, p ⱕ .01, n ⫽ 35 individuals). This positive relationship is puzzling. We can only speculate about its meaning. In sports science, two physiological reactions to overtraining are discussed. Type I is characterized by high sympathetic nervous activity, and type II, by high parasympathetic nervous activity at rest (Sluiter, Frings-Dreesen, Meijman, & van der Beek, 2000). Overtraining is characterized by repeated insufficient recovery between workouts and increased training volume (Hooper, Traeger MacKinnon, Howard, Gordon, & Bachmann, 1995). Type II reactions to overtraining are speculated to indicate a recovery overshoot. Thus, the positive relationship between work-related rumination and nocturnal HRV during Saturday night might reflect such an overshoot. A stressful work week might be similar to athletes’ overtraining (e.g., high effort but fewer recovery opportunities) and therefore result in increased bodily recovery reactions on weekends. Thinking about the past stressful work week might therefore be related to higher parasympathetic nervous activity during the night. Furthermore, correlations in Table 2 show that negative mood measured on Saturday evening is negatively related to nocturnal HRV during the night between Saturday and Sunday (r ⫽ ⫺.26, ns) but negative mood during the past work week is positively related to nocturnal HRV Saturday night (r ⫽ .22, ns). This result might further underline the conjecture regarding a type II reaction. Future studies should research this topic further. To measure a recovery overshoot, a difference between rested baseline measures of HRV activity and HRV activity during the weekend after a stressful work week might shed more light on this issue. Knowledge about the relationship between work stress and nocturnal HRV might be highly valuable for research investigating the pathways between work stress and ill health by combining two proposed pathways between work stress and ill health (the sleep

and physiological pathways). Furthermore, because high parasympathetic nervous activity represents recovery processes, high activity during the night might be important for restorative processes to occur. Therefore, HRV during the night might be an important indicator of restoration, which extends beyond recovery. Another explanation for our inconclusive results concerning nocturnal HRV might be our analytical strategy: we restricted our HRV analysis to 60-s intervals and were therefore not able to assess the parameters indicating sympathetic nervous activity (Berntson et al., 1997). Because our methodological approach was justified to obtain reliable HRV measurements from IBI data, future studies should combine measurements of sympathetic and parasympathetic nervous activity to explain the inconclusive results.

Limitations The present study has several limitations, which could be addressed in future studies. First, the sample size is rather small, particularly for our weekend analysis. Therefore, a replication of our study with an assessment covering more than two workdays and preferably including at least two weekends is advisable. Second, our sample was drawn from a larger sample of a study concerning the relationship between on-call work and well-being. The research found that on-call work was consistent with sleep difficulties, which might have confounded our results (Nicol & Botterill, 2004). Therefore, the generalizability of our sample to other employees is questionable. However, we only included healthy participants and explicitly excluded participants who reported chronic sleep difficulties. Third, work-related rumination was assessed with only one item. We therefore measured whether participants thought about work-related problems on a workday evening. Cropley et al. (2012) recently reported a measure of work-related rumination that consisted of three different dimensions: problem-solving pondering, affective rumination, and detachment. The authors found different relationships between these dimensions and unhealthy food choices. Therefore, including different aspects of rumination and explicitly requesting affective reactions related to rumination might shed more light on the relationship between work stress and rumination. Additionally, the effects of rumination might also be positive (Baars, 2010). Resolving a work-related problem by thinking about it might be beneficial for one’s daily health. Ambulatory assessment studies have reported different results concerning the frequency and duration of worry episodes, thus indicating that thinking about a problem or worrying might not have negative effects if it is associated with goal attainment (Brosschot et al., 2007). Future studies should include different measures of rumination, such as the frequency and duration of ruminative thoughts. Fourth, we did not include all IBI data in our analysis of nocturnal HRV. Therefore, sleepspecific changes in HRV might have confounded our results. However, we treated artifacts by using an algorithm and visual inspection to detect and correct them. This method is recommended by the Task Force of The European Society of Cardiology and The North American Society of Pacing and Electrophysiology (1996). Therefore, the data included in our analysis were highly reliable. However, ECG measures could be used instead of IBI to further improve the data quality. Fifth, chronic work stressors were not included in the present study. Because research shows that chronic stressors lead to reduced detachment from work on a daily


basis (Sonnentag & Bayer, 2005), their effects should be included in future studies.


Practical Implications Our results indicate that thinking about work-related problems is associated with reduced feelings of restful sleep on weekends. Therefore, helping individuals to reduce negative work-related thoughts might be beneficial for sleep and thus health and wellbeing. Mindfulness-based stress reduction programs have been reported to reduce ruminative thinking in clinical (Campbell, Labelle, Bacon, Faris, & Carlson, 2012) and healthy populations (Chiesa & Serretti, 2009). Mindfulness means “bringing one’s complete attention to the experiences occurring in the present moment, in a nonjudgmental or accepting way” (Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006, p. 27). A recent study reported beneficial effects of a self-training mindfulness intervention at work (Hülsheger, Alberts, Feinholdt, & Lang, 2013). Therefore, interventions that enhance mindfulness can be implemented in workplaces to reduce work-related ruminative thoughts and therefore enhance employees’ well-being. In addition to this person-centered approach, another practical implication stems from the reported relationship between work stress at the end of a workday and work-related rumination later that evening. For example, Martin and Tesser (1996) proposed distraction, disengagement from goals, and goal attainment as three mechanisms to stop ruminative thinking. If goal attainment on a stressful workday is not possible because there is simply too much to do, autonomy and time control might help employees to adjust work demands to individual needs and to recover on weekends. Therefore, a job design that reduces time pressure or provides resources that enable employees to reach or postpone workrelated goals (e.g., autonomy or social support) might be beneficial to reduce ruminative thinking after a stressful workday (Sonnentag & Zijlstra, 2006). Furthermore, research has shown that positive interactions after work with family members and friends are helpful in detaching oneself from work (Sonnentag & Kruel, 2006). Particularly after a stressful work week, it might be important to engage in positive social contacts.

Conclusion The strength of the present study is the analysis of the effects of work stress experienced during both workdays and weekends because these effects influence the recovery processes of daily life. Our tests of lagged effects ruled out the possibility of reverse causation among the study variables, and we used a physiological measure of health risk (HRV) to reduce the possibility of bias from common method variance. Our study took into account that sleep is the longest and possibly most important restorative period in daily life. Therefore, the presented negative links between work stress and restful sleep in our workday analysis, as well as those between work-related rumination and restful sleep in our weekend analysis, might be important for research on the development of work-related diseases.

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Received July 3, 2013 Revision received November 26, 2013 Accepted January 18, 2014 䡲

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