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Exploring the Relationship Between Work-Related Rumination, Sleep Quality, and Work-Related Fatigue

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This study examined the association among three conceptualizations of work-related rumination (affective rumination, problem-solving pondering, and detachment) with sleep quality and work-related fatigue. It was hypothesized that affective rumination and poor sleep quality would be associated with increased fatigue and that problem-solving pondering and detachment would be associated with decreased fatigue. The mediating effect of sleep quality on the relationship between work-related rumination and fatigue was also tested. An online questionnaire was completed by a heterogeneous sample of 719 adult workers in diverse occupations. The following variables were entered as predictors in a regression model: affective rumination, problem-solving pondering, detachment, and sleep quality. The dependent variables were chronic work-related fatigue (CF) and acute work-related fatigue (AF). Affective rumination was the strongest predictor of increased CF and AF. Problem-solving pondering was a significant predictor of decreased CF and AF. Poor sleep quality was predictive of increased CF and AF. Detachment was significantly negatively predictive for AF. Sleep quality partially mediated the relationship between affective rumination and fatigue and between problem-solving pondering and fatigue. Work-related affective rumination appears more detrimental to an individual's ability to recover from work than problem-solving pondering. In the context of identifying mechanisms by which demands at work are translated into ill-health, this appears to be a key finding and suggests that it is the type of work-related rumination, not rumination per se, that is important.
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Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
1
Exploring the relationship between work-related rumination, sleep quality
and work-related fatigue.
Dawn Querstret Mark Cropley
School of Psychology, University of Surrey School of Psychology, University of Surrey
d.querstret@surrey.ac.uk mark.cropley@surrey.ac.uk
Objective: This study examined the association between three conceptualisations of
work-related rumination (affective rumination, problem-solving pondering and
detachment) with sleep quality and work-related fatigue. It was hypothesised that
affective rumination and poor sleep quality would be associated with increased fatigue;
and problem-solving pondering, and detachment would be associated with decreased
fatigue. The mediating effect of sleep quality on the relationship between work-related
rumination and fatigue was also tested. Method: An on-line questionnaire was completed
by a heterogeneous sample of 719 adult workers in diverse occupations. Results: The
following variables were entered as predictors in a regression model: affective rumination,
problem-solving pondering, detachment, and sleep quality. The dependent variables were
chronic work-related fatigue (CF) and acute work-related fatigue (AF). Affective
rumination was the strongest predictor of increased CF and AF. Problem-solving pondering
was a significant predictor of decreased CF and AF. Poor sleep quality was predictive of
increased CF and AF. Detachment was significantly negatively predictive for AF. Sleep
quality partially mediated the relationship between affective rumination and fatigue; and
between problem-solving pondering and fatigue. Conclusions: Work-related affective
rumination appears more detrimental to an individual’s ability to recover from work than
problem-solving pondering. In the context of identifying mechanisms by which demands
at work are translated into ill-health, this appears to be a key finding; and suggests that it
is the type of work-related rumination, not rumination per se, that is important.
Keywords: work-related rumination, fatigue, sleep, recovery, work-related stress.
Introduction
Even though there are many contributing factors underlying the relationship between
work-related stress and ill-health, perhaps the most critical mechanism is inadequate
psychological and physical recovery (Fritz, Sonnentag, Spector & McInroe, 2010).
Research has shown that inadequate recovery outside of work is associated with a
number of poor health outcomes including: increased risk of cardiovascular disease
(Suadicani, Hein, & Gyntelberg, 1993), negative mood (Pravettoni, Cropley, Leotta, &
Bagnara, 2007), sleep problems and fatigue (Cropley, Dijk, & Stanley, 2006; Akerstedt,
Fredlund, Gillberg, & Jansson, 2002; Nylen, Melin, & Laflamme, 2007).
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
2
The process of recovery is often conceptualised in the context of two well-known
psychological theories. The Effort-Recovery theory (Meijman & Mulder, 1998) suggests
that people must invest mental and physical resources to deal with work-related
demands. This investment results in a depletion of resources and a need to ‘recover’;
however, recovery will only occur if the depleted systems are no longer taxed (Meijman &
Mulder, 1998; Sluiter, van der Beek & Frings-Dresen, 1999). The Conservation of
Resources Theory (Hobfoll, 1998) proposes that individuals strive to obtain, retain and
protect their resources, which can be external (e.g., objects, financial assets) or internal
(e.g., personal characteristics or energies). When an individual experiences stress their
resources are threatened and in order for recovery to take place new resources must be
gained and those that have been lost must be restored (Sonnentag & Fritz, 2007).
Therefore, the Effort-Recovery and Conservation of Resources theories suggest two
complimentary processes through which recovery is achieved: firstly, by refraining from
demands and activities which tax depleted resources; and secondly, by gaining new
internal resources such as energy which will help to restore threatened resources
(Sonnentag & Fritz, 2007).
Importantly, people appear able to cope with the demands of work as long as a consistent
level of recovery between periods of work activity can be achieved (de Croon, Sluiter &
Frings-Dresen, 2003; Sluiter, de Croon, Meijman, & Frings-Dresen, 2003); with
intermittent stress followed by complete recovery thought to build physiological
‘toughness’ (Winwood, Bakker, & Winefield, 2007). Physiological ‘toughness’ is associated
with low sympathetic nervous system arousal base rates, and responsiveness to stress
such that sympathetic arousal is strong only when required (Winwood et al., 2007).
However, prolonged or repeated stress exposure with sustained arousal appears to result
in damaging health effects (Brosschot, Gerin, & Thayer, 2006); with persistent failure to
unwind after work purported to damage an individual’s health because it wears down the
body’s resilience systems (McEwen, 1998).
If an individual is unable to recover adequately, they may experience fatigue. Given the
increased intensity of work environments, fatigue is a common, almost universal, feature
of modern life (Dawson, Noy, Harma, Akerstedt, & Belenky, 2011). The term fatigue is
used in many different areas and currently there is no single definition; however, the
literature distinguishes between acute and chronic fatigue (Dawson et al., 2011). Acute
fatigue is short-lived and signals that the individual needs recovery (e.g., the fatigue an
individual experiences at the end of their working day); in contrast, chronic fatigue is
persistent and develops as a result of consistent exposure to stress without adequate
recovery (Winwood et al., 2007). Research suggests that between 11% and 30% of
workers in Europe are affected by work-related fatigue (Akerstedt et al., 2002; Houtman,
1997; Loge, Ekeberg, & Kaasa, 1998; Bultmann, Kant, van Amelsvoort, van den Brandt, &
Kasl, 2001); in the USA abnormal fatigue levels have been identified among 14.3% of
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
3
men and 20.4% of women (Chen, 1986); and in Canada similar levels have also been
reported (Winwood et al., 2007).
Fatigue affects psychomotor and cognitive functions as well as mood and motivation
(Williamson, Lombardi, Folkard, Stutts, Courtney & Connor, 2011); and it has been linked
to decreased vigilance (ability to detect and respond to unpredictable events), reaction
times, memory, decision making, information processing, and psychomotor coordination
(Lyznicki, Doege, Davis, & Williams, 1998). The possible consequences of fatigue in the
real-world have been well documented (Williamson et al., 2011; Folkard & Tucker, 2003;
Caldwell & Caldwell, 2005); and there is no doubt that increased levels of fatigue can
have serious consequences in the work environment. For example, fatigue in nurses has
been implicated in medication errors, decreased productivity, cognitive impairment and
increased risk of work-related injuries (Kunert, King & Kolkhorst, 2007). Research
suggests that high work demands and role conflict (Hardy, Shapiro, & Borrill, 1997); high
psychological demands at work, low decision latitude and low social support (Bultmann,
Kant, van den Brandt, & Kasl, 2002; Bultmann, Kant, van Amelsvoort, & Kasl, 2001), are
implicated in causal models of fatigue. However, additional studies are needed to
understand the mechanisms by which work-related demands are translated into
compromised health and well-being. This article focuses on two possible mechanisms
work-related rumination and disturbed sleep with research suggesting these two
mechanisms are predictive of fatigue. For example, Akerstedt, Knutsson, Westerholm,
Theorell, Alfredsson, & Kecklund (2004) examined the multivariate relationship between
mental fatigue, work-related factors (work load, work hours), lifestyle factors and
disturbed sleep using a Swedish sample of 5720; and found that disturbed sleep and
immersion in work (particularly work-related rumination) were most predictive of fatigue.
With increasingly psychologically demanding work environments, one of the factors
thought to be critical in the facilitation of adequate recovery is psychological detachment
from work, which refers to “an individual’s sense of being away from the work situation”
(Etzion, Eden, & Lapidot, 1998, p.579). For psychological detachment to occur individuals
need to take a break from thinking about work-related issues. However, one thing people
may do when they are not at work is that they may ‘ruminate’ (think about work-related
issues and events). Some people think about tasks they’ve left uncompleted, others
ruminate about a problem that needs to be solved, and still others cogitate about
relationship issues with colleagues or negative events at work. People don’t just think
about events or issues that have already occurred, but they also ruminate anticipatively,
about upcoming events/demands and issues they may be expecting at work (Cropley &
Zijlstra, 2011).
A large proportion of the working population ruminate at one time or another. For
example, of 3000 workers interviewed for the Employment Survey of Britain (1992), 72%
reported worrying about their job at some time after work, 22% described themselves as
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
4
regular worriers, and 11% stated they worried about their job after work much of the
time (Gallie, White, Cheng, & Tomlinson, 1998). Furthermore, research suggests that
rumination is on the rise (Felstead, Gallie, & Green, 2002). Rumination is not a new
concept. Research in this area has been dominated by clinical/health psychology, with
rumination implicated in the aetiology of a number of psychological disorders, e.g.,
depression and anxiety (Lyubomirsky, Caldwell, & Nolen-Hoeksema, 1998; Mellings &
Alden, 2000); and associated with increased physical symptom reporting (Hazlett &
Haynes, 1992), intrusive off-task thoughts (Sarason, Pierce, & Sarason, 1996), negative
self-evaluations, diminished feelings of control and feelings of helplessness (Lyubomirsky,
Kasri, & Zehm, 2003). Furthermore, laboratory studies have shown prolonged
physiological arousal and delayed recovery in individuals who ruminate (Roger &
Jamieson, 1988).
There is a preoccupation in the literature with conceptualising rumination as a negative
process; and the majority of research focuses on repetitive thinking about negative
experiences (Pravettoni et al., 2007). On this basis, one may automatically think that
rumination is detrimental to recovery; however, rumination does not necessarily need to
be a negative experience, and a number of authors have suggested that rumination may
be too broad a term. Segerstrom, Stanton, Alden, & Shortridge (2003) argued that
thoughts should not only be distinguished as negative versus positive, but they should
also be separated based on their purpose, or focus (i.e. problem-solving versus searching
for meaning). Pravettoni et al. (2007) have differentiated between ‘repetitive’ and
‘creative’ rumination; and more recently Cropley & Zijlstra (2011) have differentiated
between affective rumination and problem-solving pondering.
For Cropley & Zijlstra the key difference between the affective and problem-solving states
is to do with emotional arousal. In the affective state, psychophysiological arousal
remains high and this is not conducive to the recovery process; in contrast, the problem-
solving state is proposed to exist without psychological and physiological arousal,
therefore it is less damaging for recovery. According to Cropley & Zijlstra, affective
rumination is negatively valenced, whereas problem-solving rumination could potentially
be positively valenced, especially if the process of problem-solving pondering results in a
solution; a position supported by research suggesting that thinking about successfully
completed tasks increases positive affect, self-efficacy and well-being (Seo, Narrett &
Bartunek, 2004; Stajkovic & Luthans, 1998). Therefore, it is possible that rumination with
a problem-solving focus could actually be beneficial to recovery. To the author’s
knowledge, there is no current research considering the differential effects of different
ruminative states on work-related fatigue; however, it seems reasonable to posit that
affective rumination may disrupt recovery processes; whereas rumination with a problem-
solving focus, and psychological detachment (representing an absence of ruminative
thinking), may be beneficial to recovery.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
5
Hypothesis 1: Participants reporting higher levels of affective rumination will report
higher levels of fatigue.
Hypothesis 2: Participants reporting higher levels of problem-solving pondering will
report lower levels of fatigue.
Hypothesis 3: Participants reporting higher levels of psychological detachment will
report lower levels of fatigue.
Another factor important in the context of recovery is sleep. The value of good quality
sleep for effective recovery is well established (Stewart, Abbey, Meana, & Boydell, 1998;
Singh, Clements, & Fiatarone, 1997; O’Connor & Yongstedt, 1995). The brain requires
sleep in order for energy stores to be replenished (Porkka-Heiskanen, Kalinchuk, Alanko,
Urrila, & Stenberg, 2003); and research has shown an association between poor sleep and
a multitude of different health impairments, such as self-reported coronary heart disease
(Schwartz, Anderson, Cole, Cornoni-Huntley, Hays, & Blazer, 1999), gastrointestinal
problems, high blood pressure, and neurological disorders (Taylor, Mallory, Lichstein,
Durrence, Riedel, & Bush, 2007). Performance is also negatively impacted by sleep loss
which can result in increased fatigue, mood changes, and impairment of the immune
system (Harrison & Horne, 1999; Rogers, Szuba, Staab, Evans, & Dinges, 2001). One of
the consequences of sleep disturbance is sleepiness during activity periods which can
result in an increase in work-related accidents (Lauber & Kayten, 1988); with potential
work-related injuries and loss of productivity (Kantermann, Juda, Vetter, & Roenneberg,
2010).
The mechanisms by which demands at work interfere with sleep are poorly understood;
however, the sleep literature agrees that one of the factors thought to interfere with sleep
is rumination, with self-reported sleep disturbance showing a strong relationship with
work-related worries (Akerstedt et al., 2002). People who work in demanding
environments often complain of sleep disturbance and attribute this to work-related
rumination (Berset, Elfering, Luthy, & Semmer, 2010). Furthermore, many researchers
have found significant negative associations between self-reported rumination and sleep
quality (Cropley et al., 2006; Thomsen, Mehlsen, Christensen, & Zachariae, 2003;
Thomsen, Mehlsen, Hokland, Viidik, Olesen, Avlund, Munk, & Zachariae, 2004); and
anticipative rumination has been found to be associated with both subjective and
objective sleep measures (Kecklund & Akerstedt, 2004). Experimental studies also
provide support for an association between rumination and sleep; e.g., longer sleep onset
latency has been observed in high trait ruminators (Zoccola, Dickerson, & Lam, 2009).
Therefore, it is plausible to consider work-related rumination as an extension of demands
at work, and as such, as a proxy for work-related stress. This position has been supported
by research showing that part of the effect of high work demands can be accounted for by
inability to mentally switch off after work (Akerstedt et al., 2004); and by research which
showed that rumination about work mediated the relationship between work demands and
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
6
sleep (Berset et al., 2010). If work-related rumination operates to maintain
psychophysiological response to work-related stressors once the individual has left work,
it is possible this continued activation interferes with recovery processes by negatively
impacting sleep. Conceptually, it is unlikely that rumination directly influences fatigue.
Instead, we argue that the impact rumination has on fatigue is realised via its effect on a
variable that has a direct relationship with fatigue, namely sleep. It is possible for sleep
quality to directly influence levels of fatigue; i.e. if you do not experience restorative
sleep, you may experience higher levels of fatigue. Our contention is that rumination
influences fatigue by interfering with sleep. No previous study has tested the mediating
effect of sleep quality on the relationship between work-related rumination and fatigue. As
sleep is one of our most important restorative processes, and there is evidence suggesting
that rumination interferes with sleep, it seems plausible that rumination could negatively
affect sleep quality, resulting in fatigue.
Hypothesis 4: Participants reporting lower sleep quality will report higher levels of
fatigue.
Hypothesis 5(a): Sleep quality will mediate the relationship between affective
rumination and chronic fatigue.
Hypothesis 5(b): Sleep quality will mediate the relationship between affective
rumination and acute fatigue.
Hypothesis 5(c): Sleep quality will mediate the relationship between problem-solving
pondering and chronic fatigue.
Hypothesis 5(d): Sleep quality will mediate the relationship between problem-solving
pondering and acute fatigue.
Method
Design
Participant completed an online cross-sectional survey.
Pilot study
A pilot study was run with 10 participants before the study commenced to ensure that
questions were appropriate and easily understood, and that the survey did not take longer
than 20 minutes to complete.
Sample and participants
The sample was comprised of 719 working adults (M=50.8%; F=49.2%) with an age
range of 19-69 years (M=42.91, SD=9.41). The majority of participants (88.7% [638])
worked full-time for a mean of 46.61 hours/week (SD=7.53) in jobs they had held for a
mean of 6.99 years (SD=7.36); and 313 participants (43.5%) managed others in their
role. Five hundred and sixty-nine participants (79.2%) were married or had a partner, 56
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
7
participants (7.8%) were separated/divorced or widowed, and 94 participants (13.1%)
were single. Three hundred and thirty participants (45.9%) reported having dependent
children. Four hundred and twenty-three participants (58.8%) worked a traditional 9am-
5pm (Mon-Fri) pattern, 188 participants (26.2%) worked rotating shifts (early, late, and
night), and 102 participants (14.2%) worked a non-standard shift pattern (e.g., long days
with no set shift pattern; mix of weekends and day shifts), with the remaining six
participants (0.8%) working either weekend or night shifts. Participants from emergency
services represented 34.8% (250) of the sample, followed by legal (19.1% [137]),
education (10.3% [74]), nursing (9.5% [68]), administration (7.1% [51]), management
(6.5% [47]), other (4.2% [31]), medicine (3.9% [28]), human resources (2.9% [21]),
and healthcare (1.7% [12]). The majority of participants were University educated
(57.5% [414]), or had completed their high school education or equivalent (41.8%
[301]), with only 4 participants (0.6%) stating they had no formal qualifications.
Procedure
Ethical approval was granted by the Faculty of Arts & Human Sciences Ethical Committee
at the University of Surrey. To recruit participants, as a first step, organisations affiliated
with the University of Surrey through a ‘Recovery from work’ research group were
approached by email and invited to take part in the study. These public and private sector
organisations span multiple industries including: pharmaceuticals, media, energy,
banking, education, emergency services and healthcare.
It was explained that a study was being conducted with the aim of understanding how
adults recover when not at work, and the different factors that may interfere with this
process of recovery. An electronic link to an online survey was sent to organisations who
agreed to take part, and they then forwarded this link to their employees. An article was
written for a professional journal to encourage participation from nursing and other
medical staff, and a link to the online survey was included with the article (Querstret &
Cropley, 2011); and also with an accompanying web article (Querstret, 2011).
Furthermore, details of the study and a live link to the survey were posted on social
networking sites to encourage participation of any individuals who were over 18 years of
age and working. Individuals who chose to participate were encouraged to circulate the
link to family and friends who were over 18 years of age and working. In this way, it was
hoped to increase participation by a “snowballing” effect (Winwood et al., 2007).
Measures
Work-Related Rumination
The Work-Related Rumination Questionnaire (WRRQ) is a new self-report measure
designed to measure a proposed three-factor model of perseverative thinking about work
(Cropley, Michalianou, Pravettoni, & Millward, 2012). It is comprised of three subscales,
each with 5-items: affective rumination, problem-solving pondering and detachment.
Included in the affective rumination subscale are items such as, “Are you troubled by
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
8
work-related issues when not at work?”; an item representative of the problem-solving
pondering subscale is, “After work I tend to think about how I can improve my
performance”; and the detachment subscale includes items such as, “I am able to stop
thinking about work-related issues in my free time”. Items are responded to against a 5-
point likert scale ranging from 1=“Very seldom/never” to 5=“Very often/always”, and
each subscale yields a total score which ranges from 0 to 25. The detachment subscale
has been shown to be strongly and negatively correlated with both the affective
rumination and problem-solving pondering subscales (Cropley et al., 2012). Confirmatory
factor analysis supported each of the three conceptualized factors; and together they
accounted for 68.4% of the variance. Cronbach’s alphas for the present study = .90
(affective rumination), .81 (problem-solving pondering), and .88 (detachment).
Fatigue
The Occupational Fatigue Exhaustion Recovery scale (OFER) is a 15-item measure that
has been validated in several studies as a measure of work-related fatigue (Winwood et
al., 2007; Winwood, Lushington, & Winefield, 2006; Winwood, Winefield, Dawson,
Lushington, 2005). It is comprised of three subscales of five items each which represent
chronic fatigue (CF), acute fatigue (AF), and inter-shift recovery (ISR) respectively.
Typical items for CF include, “I often dread waking up to another day of my work”; and
items included on the AF subscale include, “After a typical work period, I have little
energy left”. Each item is responded to on a seven point likert scale ranging from
0=“Completely disagree” to 6=Completely agree”. Each subscale yields a total score that
ranges from 0-100. Cronbach’s alphas for the present study = .91 (CF), .93 (AF). Due to
the focus of this article, the ISR subscale was not analysed.
Pittsburgh Sleep Quality Index
The Pittsburgh Sleep Quality Index (PSQI) is a validated questionnaire comprised of 19
items assessing sleep quality and disturbances over a one-month interval (Buysse,
Reynolds III, Monk, Berman, & Kupfer, 1988). These 19 items result in seven component
scores (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency,
sleep disturbances, use of sleep medication, and daytime dysfunction) which are summed
together to yield a global PSQI score, ranging from 0 to 21. A score >5 indicates poor
sleep quality (Buysse et al., 1988). Cronbach’s alpha for this scale has been reported to
be 0.83 (Buysse et al., 1988; Carpenter & Andrykowski, 1988).
Control variables
Single items were included in the survey for gender (1=female; 2=male), age, dependent
children (1=yes, 2=no), work status (1=full-time, 2=part-time, 3=temporary worker,
4=self-employed), work pattern (1=9am-5pm [Mon-Fri], 2=rotating shifts, 3=night work,
4=weekend work) and hours worked per week. The reason for controlling for demographic
data (i.e. gender, age, dependent children) was that women or people with children may
differ in their ability to properly recover when not at work, due to duties at home or the
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
9
requirements of child care. Additionally, older people may have more difficulties
recovering adequately than younger people who may engage in active recovery
processes. Hours worked per week and work status may have an influence over fatigue
levels as those working longer hours may have fewer opportunities for recovery. Work
pattern may influence fatigue as those working shifts may find it more difficult to recover
than those working a traditional pattern.
Because negative affect (NA) may bias responses in survey studies (Brief, Burke, George,
Robinson, & Webster, 1988), and could therefore influence how people judge their level of
fatigue, we included it as a control variable. Negative affect was assessed using 10 items
of the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988).
Items were single words representing different emotions associated with NA; for example,
“Distressed”, “Guilty”, and “Irritable”. Respondents rate the extent to which they have
experienced a particular emotion (during the past month) against a 5-point likert scale
ranging from 1=“Very slightly or not at all” to 5=“Extremely”. A total score for NA is
yielded, with higher scores representing greater affect. Cronbach’s alpha in the present
study = .89. The PANAS is a widely used scale which has been validated in occupational
health settings (Kortte, Gilbert, Gorman, & Wegener, 2010).
Whilst this study was focussed on the relationship between work-related rumination, sleep
and fatigue; we felt it was important to control for other measurable variables which
theoretically, and on the basis of existing research, could also be related to fatigue. For
example, research based on the Demand-Control model (Karasek & Theorell, 1990) has
shown that high job demands and low levels of control at work are associated with
increased strain and psychophysiological complaints (de Lange, Taris, Kompier, Houtman
& Bongers, 2003; Van der Doef & Maes, 1999). In the context of the Effort Recovery
Theory, increased job demands interfere with recovery processes by reducing the time
available to the individual; and limited control at work can damage recovery because
individuals may be required to continue expending effort at times when they require a
break psychologically and physiologically. As such, both low control at work and high
levels of demand at work can compromise opportunities for recovery (Sluiter et al.,
2003), potentially resulting in fatigue. We included measures to assess job demands, job
control and recovery opportunities to control for their impact on fatigue, thereby affording
us a clearer picture of the unique contribution of the variables of interest, namely
affective rumination, problem-solving pondering and sleep quality.
Job demands and job control
Job control and job demands were measured by including relevant items from the Job
Content Questionnaire (JCQ; Karasek, Brisson, Kawakami, Houtman, Bongers, & Amick,
1988). Ten items were used to measure perceived job demands, including items, “Do you
have to work very fast?”; and ten items were used to measure perceived job control,
including items such as, “Do you have a choice in deciding HOW you do your work?”. Each
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
10
item was responded to on a 4-point likert scale ranging from 1=“Never/Almost never” to
4=“Often”. For each of these scales, items are summed to yield a total score which ranges
from 10 to 40, with high scores indicating high job demands, or high job control,
respectively. Cronbach’s alphas for the present study = .78 (job demands) and .86 (job
control). This is a widely used measure that has been validated in occupational health
settings (Kuper & Marmot, 2003).
Opportunities for recovery
Opportunities for recovery were measured using the Opportunities for Recovery Scale
which was developed to measure opportunities for recovery both within and outside of the
work context (van Veldhoven & Sluiter, 2009). Items included on the scale include, “Can
you interrupt your work if you find it necessary to do so?”. The scale is comprised of 9
items which are responded to on a 4-point likert scale ranging from 0=“Never” to
3=“Always”. The scale yields a total score ranging from 0-18. Cronbach’s alpha for the
present study = .85. Cronbach’s alpha for this scale has been reported in three previous
study samples at .70, .75, and .77 (van Veldhoven & Sluiter, 2009).
Results
Four participants identified themselves as suffering from chronic fatigue syndrome so the
analyses were run once with them and then again without them. As their inclusion made
no difference to the results, they were included in the analyses. One of the items in the
affective rumination scale references fatigue (“Do you become fatigued by thinking about
work-related issues during your free time?”), so the results were run once with this item
included in the affective rumination measure and once without it included. As the unique
variance for affective rumination appeared to be inflated both for chronic fatigue and for
acute fatigue with the item included, it was removed from the affective rumination
measure and the remaining 4-items were used in the analysis (Cronbach’s alpha = .87).
All statistical analyses were performed using PASW 18 (SPSS, 2009). Before conducting
the main analyses, the data were tested for the presence of outliers, normality, and
linearity (Field, 2009). Due to the size of the sample (N=719) statistical tests of normality
(e.g., skewness, kurtosis, Shapiro wilk) were not appropriate. This is because even small
deviations from normality will produce a highly significant statistic in large samples (Field,
2009). Instead, we reviewed histograms for all variables and confirmed visually their
normal distribution. Furthermore, when running the regression analyses, we reviewed the
distribution of residuals for the dependent variables (acute fatigue; chronic fatigue) and
confirmed normality this way. Means, standard deviations and ranges for all variables can
be viewed in Table 1.
[Insert table 1 about here]
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
11
Correlation analysis
The data were analysed using Pearson’s Product Moment Correlation Coefficient. To
account for multiple comparisons, a bonferroni correction was applied, and significance
was evaluated against an alpha level of p<.001 (Miller, 1984). Analysis of the correlation
matrix revealed that the relationships between affective rumination, detachment, sleep
quality and acute and chronic fatigue, were all significant and in the direction predicted by
hypotheses 1, 3 and 4 (respectively). The significant positive relationship between
problem-solving pondering and the two fatigue outcomes was not in the direction
predicted by hypothesis 2; however, further analysis revealed that problem-solving
pondering meets the criteria of a suppressor variable (Cohen & Cohen, 1975). Its effects
will be explained in the results section and interpreted in the discussion. Identification of
potential confounds was undertaken by reviewing the correlations between the proposed
control variables (gender, age, dependent children, work status, work pattern, hours
worked per week, job demands, job control, recovery opportunities and negative affect)
and the outcome variables (chronic fatigue and acute fatigue). As age, work status, work
pattern, dependent children and hours worked per week were not significantly correlated
with the outcome variables; they were not included as control variables in further
analyses. Gender, negative affect, job demands, job control, and recovery opportunities
were controlled in further analyses as they were significantly correlated with both
outcome variables. All correlations can be viewed in Table 2.
[Insert table 2 about here]
Multiple regression analyses
Hypotheses 1, 2, 3, and 4 were tested using a multiple regression approach in which the
control variables (gender, negative affect, job demands, job control, and recovery
opportunities) were entered in Step 1; and the predictor variables (affective rumination,
problem-solving pondering, detachment, and sleep quality) were entered in step 2. The
results for chronic fatigue are displayed in Table 4; the results for acute fatigue are
displayed in Table 5. To test for multicollinearity, variance inflation factor (VIF) and
tolerance statistics were assessed and all variables were within acceptable limits (i.e.,
VIF<10; tolerance>.1; Field, 2009); therefore multicollinearity did not bias the regression
models.
Table 3 shows that the control variables accounted for 19.33% of the variance in chronic
work-related fatigue (CF); and that, with the exception of job demands, all of the control
variables were significant predictors. The predictor variables entered in step 2 contributed
significantly to the prediction of CF. Affective rumination (9% of the unique variance) and
sleep quality (1% of the unique variance) showed significant positive relationships with
CF; and problem-solving pondering (1% of the unique variance) was a significant negative
predictor of CF. Detachment was not a significant predictor of CF.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
12
[Insert table 3 about here]
Table 4 shows that the control variables - which were all significant predictors - accounted
for 18.5% of the variance of acute work-related fatigue (AF). The predictor variables
entered in step 2 contributed significantly to the prediction of AF. Affective rumination
(3% of the unique variance), and sleep quality (2.2% of the unique variance) showed
significant positive relationships with AF. Detachment and recovery opportunities showed
significant negative relationships with AF.
[Insert table 4 about here]
The negative association of problem-solving pondering with both fatigue variables in the
respective regression results, when considered in the context of its positive association
with both fatigue variables in the correlation table, identify it as a suppressor variable
(Cohen & Cohen, 1975) within the data. In order to establish which of the variables
problem-solving pondering was interacting with, we systematically removed each variable
from the model and reran the regression analysis with each of the resultant reduced
models. The only variable that reduced the negative predictive power of problem-solving
pondering when it was removed from the model was affective rumination. Problem-
solving pondering and affective rumination are positively related in the correlation table
and they are both positively related to the chronic and acute fatigue. However, when they
are entered into a regression equation together, problem-solving pondering takes on a
negative sign. According to Pandey & Elliott (2010), problem-solving pondering meets the
criteria of a negative suppressor variable. It’s inclusion in the regression equation clarifies
the relationship between affective rumination and the two forms of fatigue. It does this by
removing error variance, which is shared by problem-solving pondering and affective
rumination, from the model. Our detailed interpretation of these results will be addressed
in the discussion.
In summary, affective rumination was the strongest predictor of both fatigue outcomes,
accounting for 9% of the unique variance in CF and 3% of the unique variance in AF.
Problem-solving pondering was a significant predictor of decreased CF and AF. Poor sleep
quality was predictive of higher levels of CF and AF. Hypotheses 1 and 4 were fully
supported. We contend that hypothesis 2 has been partially supported because of the
incongruence of the the positive zero-order correlation between problem-solving
pondering and the two fatigue outcomes in the correlation table; against the negative
relationship between problem-solving pondering and the two fatigue outcomes in the
regression equations. Our position is that the correlation table presents an incomplete
picture of the relationship between variables; and that the regression equation reflects
more accurately the relationship between problem-solving pondering and fatigue (Pandey
& Elliott, 2010). However, we cannot conclude that hypothesis 2 has been fully supported
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
13
on this basis. Hypothesis 3 was partially supported as detachment was negatively
predictive of AF but not CF.
[Insert figure 1 about here]
Testing for mediation
To establish mediation, four steps must be satisfied (Baron & Kenny, 1986; Judd & Kenny,
1981). Step 1: The predictor variable (work-related rumination) should be correlated with
the outcome variable (fatigue) as this establishes that there is a direct effect to be
mediated (pathway c, Figure 1). Step 2: Work-related rumination should be correlated
with the mediator (sleep quality; pathway a, figure 1). Step 3: Sleep quality should affect
fatigue (pathway b, figure 1). Step 4: A regression equation is performed with both sleep
quality and work-related rumination as predictors of fatigue. If work-related rumination
no longer affects fatigue after sleep quality has been controlled a model of complete
mediation has been supported. If work-related rumination continues to affect fatigue once
sleep quality is controlled, a model of partial mediation would be supported. However,
these four steps alone do not establish mediation; it is also prudent to provide a statistical
test of the significance of the indirect pathway, or the mediation effect. Baron and Kenny
(1986) recommend testing the significance of the indirect path (a x b, figure 1) by the
Sobel z-test shown in the equation below (or variants).
2 2 2 2
ab
ab
Z
b s a s
The Sobel z-test assesses whether the difference between the total effect and the direct
effect is statistically significant. Because our sample size was large (N=719), we utilised
the Sobel Z test as per Baron & Kenny’s (1986) recommendation (c.f. Zhao, Lynch, &
Chen, 2010).
As there were two measures of work-related rumination in the study (affective rumination
and problem-solving pondering), and there were also two fatigue outcomes (CF and AF),
four separate mediation tests were performed. Mediation tests one and two ascertained
whether sleep quality mediated the relationship between affective rumination and CF, or
affective rumination and AF, respectively. Mediation tests three and four tested whether
sleep quality mediated the relationship between problem-solving pondering and CF, or
problem-solving pondering and AF, respectively.
Mediation tests
For all four mediation hypotheses (5(a); 5(b); 5(c); 5(d)), the first mediation step was
supported because both forms of work-related rumination affective rumination and
problem-solving pondering - were significantly correlated with both CF and AF. For all four
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
14
hypotheses, Step 2 was supported as sleep quality was significantly correlated with
affective rumination, and with problem-solving pondering; i.e., higher levels of affective
rumination and problem-solving pondering were associated with decreased sleep quality.
For all four hypotheses, Step 3 was also supported as sleep quality was significantly
associated with both CF and AF; with poorer sleep quality (higher scores on the PSQI)
associated with higher reported levels of CF and AF.
[Insert table 5 about here]
For hypotheses 5(a) and 5(b), a full mediation model was not supported because affective
rumination remained a significant predictor of CF, and of AF, once sleep quality was
controlled. However, the results support a partial mediation model for both hypotheses
because the addition of sleep quality to the model reduced the beta of affective
rumination for both fatigue outcomes. Furthermore, the Sobel z-test was significant
indicating that sleep quality mediated the relationship between affective rumination and
CF (z=6.1921, p<.001); and also between affective rumination and AF (z=6.5350,
p<.001). Table 5 shows test results for the mediation effect of sleep quality on the
relationship between affective rumination and the two fatigue outcomes.
[Insert table 6 about here]
For hypotheses 5(c) and 5(d), Step 3 was supported as problem-solving pondering was
significantly associated with CF, and also with AF; i.e., higher levels of problem-solving
pondering were associated with decreased levels of CF and AF. A full mediation model was
not supported because problem-solving pondering remained a significant predictor of CF,
and of AF, once sleep quality was controlled. However, the results support a partial
mediation model for both hypotheses because the addition of sleep quality to the model
reduced the beta of problem-solving pondering for both fatigue outcomes. Furthermore,
the Sobel z-test was significant indicating that sleep quality mediated the relationship
between problem-solving and CF (z=3.6014, p<.001); and also between problem-solving
pondering and AF (z=3.5990, p<.001). Table 6 shows test results for the mediation effect
of sleep quality on the relationship between problem-solving pondering and the two
fatigue outcomes.
In summary, sleep quality partially mediated the relationship between affective
rumination and both fatigue outcomes, and problem-solving pondering and both fatigue
outcomes; therefore, the four mediation hypotheses (5(a), 5(b), 5(c), 5(d)) were partially
supported.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
15
Discussion
This study addressed the relationship between work-related rumination, sleep quality and
fatigue. It was hypothesised that affective rumination and poor sleep quality would be
predictive of increased levels of fatigue (hypotheses 1 & 4), and that problem-solving
pondering and psychological detachment would be predictive of decreased levels of
fatigue (hypotheses 2 & 3). Hypotheses 1 and 4 were fully supported; hypothesis 2 and 3
were partially supported. Additionally, the mediating effect of sleep quality on the
relationship between affective rumination and fatigue, and problem-solving pondering and
fatigue, was explored. Sleep quality partially mediated the relationship between affective
rumination and both forms of fatigue, and also partially mediated the relationship
between problem-solving pondering and both forms of fatigue. Therefore, hypotheses
5(a), 5(b), 5(c) and 5(d) were partially supported.
The major finding of this study was that affective rumination was the most significant
predictor of both acute and chronic fatigue, in both cases accounting for the largest
amount of unique variance. In fact, affective rumination accounted for 9% of the unique
variance in chronic fatigue, and for 3% of the unique variance in acute fatigue, suggesting
it is a significant factor in the context of work-related fatigue. In line with the Effort-
Recovery theory (Meijman & Mulder, 1998), it’s possible that affective work-related
rumination continues to tax those systems engaged during work-time, thereby operating
to extend work-related demands and maintain psychophysiological arousal.
However, the findings are also suggestive that the two types of work-related rumination
may operate differentially on recovery processes; specifically, it appears that problem-
solving pondering may be less detrimental to recovery than affective rumination. This
finding is interesting as this was hypothesised on the basis of theory (Cropley & Zijlstra,
2011), with little pre-existing research to draw on. However, Pravettoni et al. (2007)
investigated the process of recovery from fatigue, and hypothesised that ruminative
processes would be different for different types of workers. They differentiated between
industrial workers and knowledge workers positing that industrial workers engaged in
more ‘repetitive’ rumination - which tended to be focussed on past events, and was
negatively valenced - whereas knowledge workers (who work in more psychologically
demanding environments) engaged in more ‘creative’ rumination which was focussed on
future events, and could potentially be a positive experience. Whilst this study did not
focus on the different ruminative styles of different occupational groups, the findings here
do suggest there may be different ruminative styles or processes. There was a clear
delineation between affective rumination and problem-solving pondering and these two
styles of rumination appeared to operate differentially on recovery processes.
As stated earlier, the changing sign of problem-solving pondering from positive in the
correlation table, to negative in the regression equation, identified it as a suppressor
variable (Cohen & Cohen, 1975). Ironically, suppressor variables may more accurately be
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
16
named ‘enhancers’ because they suppress the ‘noise’ they share with one (or multiple)
predictors and therefore clarify relationships between predictors and outcome variables,
increasing the predictive power of the regression model (Pandey & Elliott, 2010). We
contend that the positive variance shared between affective rumination and problem-
solving pondering reflects the fact that sometimes people who ruminate with a problem-
solving focus will also have an emotional response (which is fundamental to affective
rumination). For example, it may be that a solution does not present itself and frustration
occurs which could then invoke a similar psychophysiological response as we hypothesise
is integral to affective rumination.
However, the fact that affective rumination and problem-solving rumination, when present
in the regression equation together, operate differentially on the fatigue outcome,
highlights that there is also an important conceptual difference between them. Problem-
solving pondering and affective rumination clarify each other’s relationship with fatigue by
reducing the irrelevant shared variance (or noise) in the regression model. If either of
these variables was removed from the model, this would present an incomplete picture of
the relationship of the two types of rumination to fatigue. This highlights the importance
of ensuring suppressor variables are included in multiple regression models because they
improve the explanatory power of the model and remove irrelevant shared ‘noise’
between predictor variables (Pandey & Elliott, 2010). Our considered position is that while
both forms of rumination can interfere with recovery, it is when problem-solving
ruminators also have an emotional response that recovery is most compromised. We
assert therefore that affective rumination is more detrimental to recovery than problem-
solving pondering.
What could be the reason for this differential effect on recovery? One possibility is that
the different types of work-related rumination may differentially activate the sympathetic
and parasympathetic nervous systems. The negatively-valenced, emotion-focused
orientation of affective work-related rumination may mean that it is similar to clinical
rumination. Clinical rumination has been implicated in the aetiology and maintenance of a
number of psychological disorders, e.g., depression & anxiety (Lyubomirsky et al., 1998;
Mellings & Alden, 2000); and research suggests that it has the effect of taking the
prefrontal cortex temporarily “off-line” (Ottaviano, Shapiro, Davydov, Goldstein, & Mills,
2009). The prefrontal cortex normally exerts inhibitory control over excitation of the
sympathetic nervous system; and clinical rumination appears to disinhibit these circuits,
resulting in parasympathetic withdrawal and relative dominance of the sympathetic
system (Brosschot, van Dijk, & Thayer, 2007). Therefore, it could be that affective work-
related rumination bypasses prefrontal systems maintaining sympathetic arousal. This
position appears to be supported by research showing that high trait rumination is
associated with increased levels of salivary cortisol secretion, which is a physiological
marker for stress response (Rydstedt, Cropley, Devereux, & Michalianou, 2009).
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
17
In contrast, problem-solving pondering may be operating via the prefrontal cortex,
thereby dampening the psychophysiological response and engaging the parasympathetic
system. This has intuitive appeal because problem-solving pondering involves finding
solutions to work-related problems; therefore, it follows that areas of the brain involved in
planning and executive function (e.g., prefrontal cortex) would be activated. Another
possibility is that problem-solving pondering operates protectively because the individual
finds a solution to a problem, thereby concluding the ruminative process; whereas
affective rumination offers no such relief. Martin & Tesser (1996), in their self-regulation
model of ruminative thought, suggest there are three mechanisms by which ruminative
thinking can be stopped: distraction, disengagement from the goal, and goal attainment.
In the context of this theory, problem-solving pondering may satisfy a requirement for
goal attainment (if a solution is arrived at), offering a sense of achievement and
satisfaction for the individual. This would align with the findings of previous studies
suggesting that reflecting on completed tasks has been shown to increase positive affect,
self-efficacy and well-being (Seo et al., 2004; Stajkovic & Luthans, 1998).
Compromised sleep quality was also a significant predictor of both acute and chronic
fatigue. This result was expected and in line with previous research suggesting that
impaired sleep is implicated in compromised recovery (Stewart et al., 1998; Singh et al.,
1997; O’Connor & Youngstedt, 1995). However, it is not clear what aspects of sleep
quality are most predictive of fatigue and further analysis is planned to investigate this in
more detail. For example, if the sleep quality measure is broken down into its component
parts for analysis, it will be possible to explore specifically which of the components (e.g.,
delayed sleep onset; interrupted sleep; duration of sleep) is most predictive. The use of a
composite measure for sleep quality may also explain the finding of only a partial
mediation effect of sleep quality on the relationship between work-related rumination and
fatigue. Whilst this partial mediation finding aligns with research suggesting rumination
interferes with sleep (Cropley et al., 2006; Thomsen et al., 2003; Thomsen et al., 2004;
Zoccola et al., 2009; Harvey, Tang, & Browning, 2005); it would be interesting to
examine if one or more of the specific sleep quality components mediates completely the
relationship between work-related rumination and fatigue. For example, recent research
suggests that the way in which rumination interferes with sleep is by delaying sleep onset
(Zoccola et al., 2009). The fact that the direct relationship between work-related
rumination and fatigue remained significant even when controlling for sleep quality
indicates that there are other, as yet unexplored, mediator variables to be considered.
The relationship between sleep quality and fatigue is difficult to interpret. One reason for
this is that while sleep quality can be considered a predictor of fatigue, it may also be
compromised as a result of fatigue, e.g., non-refreshing sleep is a symptom of chronic
fatigue syndrome (Van’t Leven, Zielhuis, van der Meer, Verbeek, & Bleijenberg, 2009).
Because of the cross-sectional nature of the data causality between variables cannot be
established (Field, 2009). Therefore, it is not possible to be sure of the direction of the
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
18
relationship between sleep quality and fatigue. While the interpretation that poor sleep
quality predicts fatigue is one possibility, it is also possible that the direction of causality
is reversed.
Practical implications
There are practical implications for organisations to consider. Often, organisations believe
that their responsibility for employee health and well-being is limited to the time that
employees are at work, and careful strategies are developed to manage working hours
and associated workload. However, with increasing technological advances many
employees are ‘taking their work home with them’ (e.g., PDA’s and access to emails at
home). This may make the boundary between work and non-work time much more
difficult for individuals to establish, resulting in compromised space for recovery activities
and processes to take place. While there are undoubtedly some roles in any organisation
which are critical and require individuals to work at times outside of their allotted hours;
many organisations use the promise of constant connectivity as an incentive, with PDA’s
and company mobile technology offered as a perk of promotion. Perhaps if fewer
individuals were constantly connected to their work outside of their working hours, more
opportunity for recovery would be created (Cropley & Millward, 2009).
Directions for future research
There are a number of avenues worthy of exploration through future research. Firstly, it
would be interesting to explore further the link between work-related affective rumination
and clinical rumination. Can they be considered the same construct in terms of
neurocognitive processing? Furthermore, clinical rumination is often characterised as a
trait tendency; as such, it would be of interest to explore the stability of work-related
rumination over time. Also of interest is the link between ruminative style and personality
constructs, and the stability of ruminative style. Research suggests that individuals vary
their personality across different social contexts (Querstret & Robinson, in press); and it
would be of interest to assess whether individuals vary their ruminative style across
different stress contexts. As this research appears to suggest that it is not rumination per
se, but type of rumination, that is implicated in compromised well-being; it would be
interesting to develop and test interventions designed to help those who ruminate
affectively to adopt a more problem-solving focus. Furthermore, exploration of the
different brain regions involved in different work-related ruminative states would be very
useful. Finally, it would be of interest to carry out longitudinal research to see if acute
fatigue sufferers develop chronic fatigue without intervention.
Limitations
The most significant limitation of this study is its cross-sectional nature which means that
establishing causation related to the relationship between variables is not possible.
Another limitation is the self-report nature of the data, which could have inflated the
associations between variables through common method variance (Podsakoff, MacKenzie,
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
19
Lee, & Podsakoff, 2003). However, this should have been minimised because the
measures included on the questionnaire spanned a variety of different constructs; and
scales were varied to minimise the chance that individuals would simply respond “by rote”
(Podsakoff et al., 2003). A further potential limitation of the study was that it was
essentially limited to those subjects with Internet connectivity which could potentially bias
the sample in favour of higher sociodemographic groups. However, The Office of National
Statistics (ONS, 2011) reported that the penetration of Internet connectivity is
approximately in the order of 77% within the UK, and connectivity is not confined to the
more economically affluent or specific ethnic groups.
The occupational characteristics of the sample suggests a bias toward occupations that
are inherently more psychologically stressful; however, as we were interested in
rumination, and rumination is reported to be more prevalent in workers with
psychologically demanding roles (Pravettoni et al., 2007), this was not considered a
detriment. Finally, it could be that the sample showed a distribution skew as a result of
“volunteer bias” whereby individuals suffering greater levels of fatigue might be less
willing to participate; however, it could also be argued that workers who were more
fatigued may be more willing to participate due to being personally invested in the subject
matter (Winwood et al., 2007). Furthermore, the study was presented as an exploration
into the factors that interfered with an individual’s ability to adequately recover outside of
their working days, and there was no direct reference to fatigue in the study information.
The study limitations are offset by some considerable strengths. Firstly, the large sample
size (N=719) had an almost equal gender split, and was comprised of participants
representing a broad cross-section of industry sectors. Furthermore, the novel findings of
this study extend our understanding of the mechanisms by which work-related stress may
be translated into ill-health via inadequate recovery; and highlight some interesting future
directions for research in this area.
Conclusions
The major finding in this study was that affective rumination appears more detrimental to
recovery processes than problem-solving pondering. Specifically, it appears to be the
emotional component which seems to be problematic. In the context of identifying
mechanisms by which demands of work are translated into ill-health, this appears to be a
key finding. The finding that problem-solving pondering may be less detrimental to
recovery suggests that it is the type of rumination, not rumination per se, which is
important. Therefore, strategies to help affective ruminators engage in a more problem-
solving focussed rumination style could be very effective.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related
fatigue. Journal of Occupational Health Psychology, 17, 341-353.
20
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fatigue. Journal of Occupational Health Psychology, 17, 341-353.
27
TABLE 1
Means, standard deviations and ranges for study measures
Measure
Mean
SD
1.
Affective rumination
11.42
3.56
2.
Problem-solving pondering
14.82
3.62
3.
Detachment
15.88
4.52
4.
Chronic fatigue
40.44
27.01
5.
Acute fatigue
53.50
26.39
6.
Sleep quality
7.05
4.09
Study measures: 1. Affective rumination, 2. Problem-solving pondering, 3. Detachment (Work-
Related Rumination Scale); 4. Chronic fatigue, 5. Acute fatigue (Occupational Fatigue Exhaustion
Recovery scale); 6. Sleep quality (Pittsburgh Sleep Quality Index).
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-related fatigue. Journal of Occupational Health Psychology, 17, 341-
353.
28
TABLE 2
Zero order correlations for all study variables
Variables
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1.
Age
-
2.
Work status
-.036
-
3.
Hours worked per week
.058
-.179*
-
4.
Dependent children
-.196*
-.071
-.042
-
5.
Gender
.108
-.107
.323*
-.109b
-
6.
Negative affect
-.176*
.028
-.019
.004
-.247*
-
7.
Job demands
-.029
.062
.200*
-.046
-.164*
.161*
-
8.
Job control
.043
.186*
-.027
-.036
-.143*
-.123a
.271*
-
9.
Recovery opportunities
.011
.152*
-.239*
.027
-.242*
-.115*
-.015
.704*
-
10.
Affective rumination
-.097*
.008
.121*
.057
-.167*
.508*
.265*
-.158*
-.292*
-
11.
Problem-solving pondering
-.056
.089
.149*
-.030
-.124*
.313*
.480*
.124*
-.076
.586*
-
12.
Detachment
.029
-.034
-.161*
.021
.154*
-.389*
-.381*
.055
.219*
-.712*
-.664*
-
13.
Chronic fatigue
-.047
-.044
.051
.081
-.147*
.487*
.088
-.340*
-.368*
.628*
.246*
-.441*
-
14.
Acute fatigue
-.024
-.052
.056
-.010
-.139*
.416*
.160*
-.317*
-.378*
.533*
.254*
-.443*
.712*
-
15.
Sleep quality
.005
-.003
-.030
.020
-.050
.402*
-.027
-.265*
-.270*
.376*
.140*
-.303*
.433*
.431*
-
Bonferroni statistic applied; *p<.001; ap=.001, bp=.004
Control variables: gender, negative affect, job demands, job control, recovery opportunities; Study variables: affective rumination, problem-solving pondering,
detachment, chronic fatigue, acute fatigue, sleep quality.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-
related fatigue. Journal of Occupational Health Psychology, 17, 341-353.
29
TABLE 3
Results from multiple regression analysis predicting chronic fatigue
Step 1
Step 2
Beta
t
Beta
t
1. Gender
-.122
-3.743***
-.070
-2.421*
2. Negative affect
.404
12.676***
.189
5.954***
3. Job demands
.038
1.121
.008
0.258
4. Job control
-.141
-3.033**
-.141
-3.449**
5. Recovery opportunities
-.251
-5.467***
-.096
-2.316*
6. Affective rumination
.486
11.478***
7. Problem-solving pondering
-.153
-3.942***
8. Detachment
-.054
-1.288
9. Sleep quality
.102
3.532***
Adjusted R2
.354
.509
F
79.742***
83.553***
R2
.359
.515
F
79.742***
57.000***
*p<.05, **p<.01, ***p<.001. Constant: step 1=46.977, step 2=30.584
Control variables: 1. Gender, 2. Negative affect, 3. Job demands, 4. Job control 5. Recovery opportunities;
Study measures: 6. Affective rumination, 7. Problem-solving pondering, 8. Detachment; 9. Sleep quality.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-
related fatigue. Journal of Occupational Health Psychology, 17, 341-353.
30
TABLE 4
Results from multiple regression analysis predicting acute fatigue
Step 1
Step 2
Beta
t
Beta
t
1. Gender
-.127
-3.757***
-.086
-2.751**
2. Negative affect
.317
9.613***
.138
4.007***
3. Job demands
.121
3.459**
.090
2.560**
4. Job control
-.134
-2.782**
-.134
-3.005**
5. recovery opportunities
-.276
-5.834***
.144
-3.182**
6. Affective rumination
.276
5.989***
7. Problem-solving pondering
-.122
-2.900**
8. Detachment
-.144
-3.150**
9. Sleep quality
.163
5.194***
Adjusted R2
.311
.416
F
65.779***
57.722
R2
.174
.251
F
65.779***
35.926***
*p<.05, **p<.01, ***p<.001. Constant: step 1=50.214, step 2=55.161
Control variables: 1. Gender, 2. Negative affect, 3. Job demands, 4. Job control, 5. Recovery opportunities; Study
variables: 6. Affective rumination, 7. Problem-solving pondering, 8. Detachment, 9. Sleep quality.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-
related fatigue. Journal of Occupational Health Psychology, 17, 341-353.
31
TABLE 5
The mediating effect of sleep quality on the relationship between affective
rumination and CF, and affective rumination and AF
Step 1
Step 2
Step 3/4
Beta
t
Beta
t
Beta
t
Chronic fatigue (CF)
Affective rumination
.628
21.634*
.376
10.879*
.543
17.967*
Sleep quality
.228
7.563*a
Acute fatigue (AF)
Affective rumination
.533
16.873*
.376
10.879*
.432
13.250*
Sleep quality
.268
8.209*a
*p<.001; apartial mediation effect
Step 1: outcome=chronic fatigue/acute fatigue, predictor=affective rumination; Step 2: outcome=affective
rumination, predictor=sleep quality; Step 3: outcome=chronic fatigue/acute fatigue, predictor=sleep quality,
affective rumination.
Querstret & Cropley. Journal of Occupational Health Psychology (authors copy).
Citation: Querstret, D., & Cropley, M. (2012). Exploring the relationship between work-related rumination, sleep quality, and work-
related fatigue. Journal of Occupational Health Psychology, 17, 341-353.
32
TABLE 6
The mediating effect of sleep quality on the relationship between problem-solving
pondering and chronic fatigue, and problem-solving pondering and acute fatigue
Step 1
Step 2
Step 3/4
Beta
t
Beta
t
Beta
t
Chronic fatigue
Problem-solving pondering
.246
6.804*
.140
3.782*
.190
5.694*
Sleep Quality
.406
12.199*
Acute fatigue
Problem-solving pondering
.254
7.040*
.140
3.782*
.198
5.952*
Sleep Quality
.403
12.115*
*p<.001
Step 1: outcome=chronic fatigue/acute fatigue, predictor=problem-solving pondering; Step 2: outcome=sleep
quality, predictor=problem-solving pondering; Step 3: outcome=chronic fatigue/acute fatigue, predictor=sleep
quality, problem-solving pondering.
... It has been well-documented that workplace stressors give rise to rumination (e.g., [1][2][3][4]). Previous research mainly examined the link between work-related rumination and various psychological and physiological well-being outcomes (e.g., [5][6][7]) and it has been demonstrated that work-related rumination is a detrimental process to employees' well-being. To be able to meet the work demands without rumination and the following negative outcomes, employees may need some nutrients, such as supportive work environments during work and psychological detachment from work during nonwork time. ...
... Grounded in self-determination theory [8,9], the present study focuses on the antecedents of work-related rumination with a weekly diary design. Since the type of rumination rather than rumination per se is critical due to their differential relationships with well-being [5], three concepts of work-related rumination were employed in the current study to examine the weekly changes in each type based on perceived autonomy support, an essential nutrient for employees in the workplace, and fear of failure, a form of performance anxiety. Both autonomy support and fear of failure play a significant role in boosting or dampening well-being, which necessitates exploring their role on the weekly changes in work-related rumination to be able to provide effective means of decreasing workrelated rumination. ...
... The previous research showed that although these three concepts are correlated [17,18], they seem to tap different aspects of work-related rumination [19]. Moreover, Querstret and Cropley (2012) [5] suggested that the type of rumination rather than rumination per se can be crucial due to their differential associations with recovery. Therefore, three concepts of workrelated rumination are used in the current study to examine the weekly changes in each type during three weeks and the specific mechanism underlying the relationship between perceived autonomy support and work-related rumination. ...
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Grounded in self-determination theory, the present study examined the weekly fluctuations in different forms of work-related rumination depending on perceived autonomy support and fear of failure at the workplace. Work-related rumination has three dimensions, affective rumination (negative emotions or affect), problem-solving pondering (thinking over the actions to handle the problems), and psychological detachment (mentally distancing oneself from work during nonwork time). In total, 111 employees (M age = 34.88, SD = 10.43) from various occupations were followed over the course of three weeks via weekly measurements , resulting in 333 matched observations. Multilevel random coefficient modeling showed that on the weeks when employees reported higher levels of perceived autonomy support from the leader, they engaged in affective rumination and problem-solving pondering less. However, weekly fluctuations in psychological detachment from work was not associated with perceived autonomy support. Moreover, on the weeks when employees experienced high fear of failure, they reported less psychological detachment from work during nonwork time. Lastly, within-and and between-person fear of failure moderated the negative link between perceived autonomy support and affective rumination. Findings showed that perceived autonomy support is a protective factor for employees high in both state and trait fear of failure in decreasing affective rumination. Directions for future research and implication for practice were discussed.
... For instance, as the epitome of perseveration, rumination has been regarded as a "thief of flow" (Peifer and Zipp, 2019), as it impairs the ability to recover and to attain a sense of fluency at work, both of which are necessary for entering flow (Peifer et al., 2020). However, some studies have noted that finding solutions to problems during nonworking time generates positive emotions and a sense of accomplishment, which can accelerate psychological recovery and therefore promote flow at work (Querstret and Cropley, 2012). Despite noticeable differences among these accounts account, they have gradually converged on a consensus that implicitly identifies rumination as a transmitter of the influence of stress on flow. ...
... Work-related rumination refers to the tendency to think about work events repetitively during nonworking hours (Cropley and Zijlstra, 2011) and was once believed to inhibit psychological recovery because it perpetuates the mental representation of stressors and leads to slower responses to demands (Brosschot et al., 2006). Nevertheless, other scholars have found that if employees find solutions to problems outside working hours or evaluate their work positively, they can experience positive emotions and report higher levels of wellbeing (Querstret and Cropley, 2012), organizational citizenship behavior (Binnewies et al., 2009) and creativity (Vahle-Hinz et al., 2017). Based on interviews, Cropley and Zijlstra (2011) classified work-related rumination into affective rumination (intrusive, common and recurring negative thoughts about work) and problem-solving pondering (evaluating previous tasks to seek continuous improvement) according to the content of such rumination. ...
... In fact, according to Zhang et al.'s (2019) metaanalysis, hindrance stressors are positively associated with a problem-solving prevention focus. Second, as expected, problem-solving pondering positively affects flow, and affective rumination inhibits flow, further confirming the division between the positive and negative attributes of rumination (Querstret and Cropley, 2012). In addition, work-related rumination mediates the effects of stressors on flow, but the mediating effects offset each other. ...
Article
Purpose This study aims to illustrate the mechanisms underlying the effect of stress on flow states in the context of a multilevel organization, in which case employees' perseverative cognition and reactions to challenge–hindrance stressors are affected by leader mindfulness. Design/methodology/approach Study 1 employed a three-wave time-lag survey, and study 2 conducted a diary study across 10 workdays to replicate the results of study 1. Multilevel structural equation modeling and Monte Carlo simulation were performed using Mplus 8.0 software to test all hypotheses. Findings Problem-solving pondering transmits the nonlinear effect of challenge stressors on flow, and affective rumination mediates the negative effect of hindrance stressors on flow. Leader mindfulness amplifies the tendency of followers to ruminate on the positive aspects of challenge stressors, consequently increasing their positive reactions and flow. Although leader mindfulness fails to influence followers to ruminate less on hindrance stressors, it negates the harmful effect of affective rumination on the flow experience. Originality/value This study is one of the first to examine the associations between stressor types and flow in the workplace. The authors also develop a new theory that highlights the ability of leader mindfulness to shape subordinates' stress, cognitions and reactions through social modeling and the authors identify the boundaries of its beneficial effects.
... A literatura internacional tem mostrado que a ruminação relacionada ao trabalho pode influenciar a saúde dos trabalhadores [2][3][4][5] , tendo sido associada ao mal-estar psicológico, à fadiga, aos problemas de sono e às alterações na secreção de cortisol [5][6][7][8] . Por outro lado, é pertinente destacar que pensamentos positivos relacionados ao trabalho, no período de folga, podem resultar em efeitos benéficos para os trabalhadores 9 . ...
... No entanto, os pensamentos recorrentes relativos às questões do trabalho, quando ocorrem de forma indesejada e fora do controle do indivíduo, podem comprometer o processo de recuperação pelo qual o trabalhador deve passar quando está de folga, como afirmam Sonnentag e Fritz 10 . Desta forma, a longo prazo, a ruminação pode levar a problemas de saúde 6 . ...
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Introdução: A ruminação relacionada ao trabalho se refere aos pensamentos relativos aos diversos aspectos do trabalho que ocorrem nos períodos de folga. Objetivo: Descrever o processo de adaptação transcultural da escala de ruminação relacionada ao trabalho para o contexto brasileiro (B-WRRS) e analisar suas propriedades psicométricas. Método: Foi realizada a tradução, retrotradução e avaliação psicométrica inicial de uma escala composta por 15 itens e três dimensões, onde a B-WRRS foi testada em 173 trabalhadores de cargos administrativos de uma instituição pública. Para a avaliação da validade dimensional, iniciou-se com a análise fatorial confirmatória, tendo como base o modelo original proposto pelos autores da escala. Foi realizada também a análise fatorial exploratória, utilizando o Mplus. Resultados: A adaptação da escala cumpriu as etapas de avaliação da equivalência conceitual, de itens, semântica e operacional, apresentando grande aceitabilidade e compreensão por parte dos respondentes. A avaliação da estrutura fatorial da B-WRRS corroborou a tridimensionalidade da escala. Conclusão: Por ser simples e rápido, o preenchimento da B-WRRS se destaca como promissor para o uso no ambiente de trabalho. O processo de adaptação transcultural do instrumento não apresentou divergências conceituais nem semânticas. Entretanto, as diferenças observadas na composição das dimensões indicam a necessidade de novas avaliações psicométricas para estabelecer a equivalência funcional da B-WRRS.
... 30 Work-related rumination is also associated with increased cortisol secretion and has been associated with poor sleep quality. [31][32][33] However, there is limited research on the association between work-related rumination and headaches and eyestrain, and thus, more research is needed on the association between work-related rumination and headaches and eyestrain, as well as the use of communication devices outside of work hours. ...
... Problem-solving pondering was then measured using all three of the items from the short version of the Work-Related Questionnaire (Querstret & Cropley, 2012) that was adapted by Junker et al. (2020). The sample item is "I found myself re-evaluating something I have done at work. ...
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This study explores how employees’ flow experience at work emerges, is sustained, and continuously grows over time. Based on the job demand-resource model, we propose the intraday upward spiral of flow: Challenging demands and job resources activate employees’ flow experience, further encouraging them to seek more challenges and resources. Furthermore, drawing on the perseverative cognition theory and spill-crossover model, we propose the inter-day upward spiral of flow: The antecedents (or consequences) of flow can overflow from work to the family domain and result in employees’ positive rumination, thus promoting the next-day flow experience. Our diary study generated 1,208 data points from 142 employees over 10 working days. We found that in the morning, challenging demands and job resources positively affected the participants’ flow, further encouraging them to pursue more challenging demands and job resources in the afternoon and thus enter this state again. Moreover, the afternoon’s challenging demands and job resources promoted the respondents’ problem-solving pondering at night, which further increased their next-morning challenging demands, job resources, and, thus, their flow. Through this study, we expand the emerging literature on positive organizational behavior and provide information for practitioners on how to build and sustain employees’ peak states.
... Hence, regarding the health-impairment process as propositioned by JD-R theory, research suggests that affective work rumination is especially detrimental to employees' ability to recover from stressors at work [53,54]. Furthermore, reports indicate that psychological detachment from work and work rumination mediates the relationship between job demands and exhaustion by reducing or prolonging and accentuating the effect of job demands. ...
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High levels of job demands are considered as the main predictor for teachers’ exhaustion, but longitudinal studies of the causal effects are few. Recently it has been suggested that research should further explore possible reciprocal relationships between stressors and strain and investigate if work rumination contributes to explain these relationships. In a sample of teachers (n = 1067) using a three-wave design, we hypothesized positive causal effects of job demands (work pace and role conflict) on affective work rumination, and of affective work rumination on exhaustion. We also hypothesized a positive reversed causal effect of exhaustion on affective work rumination, and of affective work rumination on job demands. Furthermore, affective work rumination was expected to mediate the positive causal and reversed causal effects between job demands and exhaustion. The results partly confirmed the expected causal and reversed causal effects. However, affective work rumination was only found to mediate the reversed causal effect of exhaustion and role conflict. Furthermore, a reciprocal relationship was only found between role conflict and exhaustion. The empirical, theoretical, and practical implications of the study are discussed.
... Researchers in the field of work stress have found that the effects of work stress on individuals can continue after work through the role of persistent cognition. This persistent cognition is work rumination, which refers to the state in which some people ruminate over work-related issues and events outside of work [20]. Negative work stress, such as effort-reward imbalance, workplace incivility, and job insecurity, can cause negative work rumination [21], namely, repetitive thinking about negative experiences and experiencing negative emotions in the process [12]. ...
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Work withdrawal behavior is a type of negative reaction when employees face obstacles at work. Its negative impact on individuals and organizations has caught the attention of academic circles and managers. In this study, data from 596 full-time employees were collected using two timepoint measurements one month apart. The internal mechanism of the link between obstructive stress and job withdrawal behavior was analyzed, and the combined effects of work control and cognitive flexibility on the negative effects of obstructive stress were analyzed in terms of the work demand-control-personal model. The results showed that negative work rumination played a complete mediating role between obstructive stress and work withdrawal behavior, and cognitive flexibility, obstructive stress, and work control had a significant three-way interaction. The results suggest that more attention should be paid to the role of employee cognition to avoid employees' withdrawal behavior in the face of work obstacles. In addition, when providing work resources to employees, the organization should also consider ensuring that work resources can be fully utilized to play a positive role in buffering work obstacles.
... Ruminative thinking is, therefore, a crucial mechanism in explaining the adverse impact of work-related stressors on health outcomes [45]. The negative association between work-related rumination, especially affective rumination, and health problems, such as low mood, is extensively researched [46,47]. On a within-person level, nighttime ruminative thinking was linked to increased negative affect the following morning [48]. ...
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The link between workplace bullying and impaired employee psychological health is well established. Insights into the role of cognitive processes in reaction to stressful events, as well as personality traits in this relationship, remain scarce. In this study, we investigated moderated mediation models that link workplace bullying with employee well-being and mood. The study employs both cross-sectional and longitudinal methodologies within the same group of employees with workplace bullying experience (n = 59). Results from a cross-sectional survey show that affective rumination fully mediates the link between workplace bullying and employee well-being. Contrarily, findings from a daily diary study indicate that day-to-day variations in bullying experiences do not affect the subsequent morning mood. Thus, workplace bullying primarily acts through affective ruminative thinking rather than having a direct effect, especially on individuals low in neuroticism. These insights contribute to a more comprehensive understanding of the relevance of repetitive cognitive processes and personality traits as mechanisms that link workplace bullying with psychological well-being. Implications include the need for a better understanding of the accumulation processes of persistent ruminative thought and the relevance of stressor pile-up to explain spillover effects into the next day in order to understand long-term health impairment.
... Affective rumination is a type of negative cognitive appraisal related to distressing events and characterized by recurrent work-related thoughts outside of work (Querstret and Cropley, 2012;Wesselmann et al., 2013a). Research has shown that affective rumination reduces sleep quality (Syrek et al., 2017), increases aggressive behaviors (Porath and Erez, 2009) and triggers individuals' tendency to interpret ambiguous situations as threatening (Zadro et al., 2006). ...
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Purpose The perseverative cognition framework suggests that observing ostracism has negative implications for observers due to affective rumination and that a proactive personality might make observers more vulnerable to this effect. Design/methodology/approach Data from 49 team leaders and 218 team members were obtained through a three-wave survey in China. Path analysis was used to examine the theoretical model. Findings The results indicate that observing ostracism increased turnover intention and reduced task performance and that these relationships were mediated by affective rumination. Furthermore, these effects were stronger for observers with high proactive personality. Research limitations/implications Workplace ostracism harms employees; however, its effects on observers remain underexplored. This paper extends research on the effects of ostracism by revealing that ostracism is not only harmful to the well-being of its victims but also adversely affects the work-related attitudes and behaviors of observers, especially those with proactive personality. Practical implications Organizations should be aware of the harmful effects of workplace ostracism on observers, and take actions to inhibit workplace ostracism as well as reduce the negatives impacts. Originality/value The results reveal the cognitive mechanism of affective rumination, in which observing workplace ostracism affects observers' behaviors and attitudes, highlighting the importance of observing effect of workplace ostracism.
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Primarily using a variable-centered approach, job search research explores the connections between antecedents, processes, and outcomes. A person-centered approach, however, categorizes individuals based on personal and contextual elements. This study used CSM as a theoretical framework to identify job seeker profiles by exploring configurations of job search self-efficacy, conscientiousness, financial need, social pressure, and job search quality and intensity. We examined how these profiles correspond with sociodemographic variables and job search outcomes such as rumination, interviews, and job offers. In a sample of 300 job seekers, four profiles emerged: casual job search contemplator, financially burdened job seeker, financially secure job seeker, and multifaceted job search strategist. The contemplator profile correlated with the fewest interviews, while the financially burdened job seeker had the most. These findings suggest career counselors need to recognize distinctive job seeker patterns requiring tailored counseling approaches, underscoring the potential of the person-centered approach for further job search research.
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