Bidirectional relations between work-related stress, sleep quality and perseverative cognition☆
Introduction
Roughly one out of three individuals in Western countries reports sleep problems [1], [2]. The negative effects of poor sleep quality on health and work performance have been established in many studies [3], [4], [5], [6], [7], [8]. Other research has focused on a wide variety of possible factors causing poor sleep quality [9].
One of the potential causes of longer periods of disturbed sleep is chronic work-related stress [10]. Levi and Levi [11] define work-related stress as emotional, cognitive, behavioural, and physiological reactions to negative attributes of work, a state characterized by high levels of arousal and distress. Although working is inevitably associated with short-term stress-related load effects (e.g., fatigue, negative affect, elevated heart rate), these effects will cause no harm and will not disturb sleep, as long as they return to baseline levels during off-job periods. Sufficient recovery from work-related stress is jeopardized, however, when bodily stress systems (e.g., hypothalamo-pituitary-adrenocortical system, sympathetic-adrenal-medullary system) remain activated during off-job time (“sustained activation”) [12]. This prolonged stress-activation leads to bodily wear and tear (“allostatic load”) that can eventually cause serious disease [13]. In line with this, recent studies show that work-related stress without sufficient recovery seems to be a serious risk factor for sleep [10], [14], [15], [16].
Sleeping is at the same time one of the most crucial opportunities to recover from work stress [15], [17]. Sleep is essential for restoration of bodily processes (e.g., endocrine effects, glucose changes), which seem to counteract the negative impact of daily stress [18]. Longitudinal research designs are needed to find more valid evidence for the assumed relationship between work-related stress and sleep quality, but until now this type of research is scarce. The current study aimed to fill this gap by using a longitudinal full-panel design (with a one-year time lag) measuring both sleep quality and work-related stress at two points in time.
The first aim of this study was to examine whether work-related stress predicts poor sleep quality. Based on previous research [10], [18], we hypothesized that work-related stress is associated with decreased sleep quality one year later (Hypothesis 1: normal causation). Additionally, it seems plausible [15], [17] that poor sleep quality is associated with work-related stress one year later. In line with the stressor creation hypothesis [19], [20], poor sleep quality may evoke new stressors (e.g., interpersonal conflicts due to irritation), which in turn may increase stress. Hence, we tested whether poor sleep quality is associated with increased work-related stress one year later (Hypothesis 2: reversed causation).
Next to work-related stress and sleep quality, we also included measures of work-related perseverative cognition (PC). PC is defined as “repeated or chronic activation of the cognitive representation of one or more psychological stressors” [21, p.114]. It is believed to be a major cause of prolonged physiological activation and of impaired recovery and sleep [10], [22]. Field research has shown that particularly work-related PC is accountable for prolonged physiological activation [23]. Work-related PC is characterized by repetitive thoughts about issues associated with work [24]. Research has consistently shown that work-related PC is related to sleep problems [25], [26], [27]. Hence, the second aim of this study was to longitudinally examine to what extent PC intervenes in the relationship between work-related stress and poor sleep quality. Building on previous research, we expected that work-related stress is associated with increased PC one year later (Hypothesis 3: normal causation), and that PC, in turn, is accountable for poorer sleep quality one year later (Hypothesis 4: normal causation). We also examined possible reversed causation, that is, poor sleep quality is associated with an increase in PC one year later (Hypothesis 5: reversed causation). Lastly, we expected that PC is related to an increase in work-related stress one year later (Hypothesis 6: reversed causation).
Section snippets
Design and participants
This study employed a two-wave full panel design with a time lag of 13 months. Employees who had completed the Netherlands Working Conditions Survey 2010 [NWCS, 28] were invited for a longitudinal follow-up study in 2012 and 2013. The NWCS is a yearly survey conducted among a large, randomly selected sample of Dutch employees. It provides insight into the quality of working life and employee health. All participants who completed the online version of the NWCS in 2010 and agreed to participate
Descriptive statistics
Means, standard deviations and correlations are presented in Table 2. Correlations between constructs of interest were all significant and in the expected direction, e.g. a positive correlation between work-related stress and PC. Stability of the study variables over time was high with correlations ranging between 0.55 and 0.68 and standardized beta coefficients ranging between 0.46 and 0.65 (see also Fig. 2).
Moreover, the prevalence of work-related stress, sleep quality, and PC was inspected.
Discussion
The first aim of this study was to examine the temporal relationship between work-related stress and sleep quality. We hypothesized that work-related stress and sleep quality influence each other (H1 & H2), but only a reversed temporal relationship was found. Poor sleep quality was related to an increase in work-related stress the following year, whereas higher work-related stress was not associated with a decrease in sleep quality one year later.
The second aim of this study was to determine
Acknowledgments
We thank William M. van der Veld of the Radboud University in Nijmegen, the Netherlands, for his statistical advice during the revision of this article.
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Place where work was conducted: Radboud University, Behavioural Science Institute, Nijmegen, The Netherlands