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The Recovery Experience Questionnaire: Development and Validation of a Measure for Assessing Recuperation and Unwinding From Work


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Drawing on the mood regulation and job-stress recovery literature, four self-report measures for assessing how individuals unwind and recuperate from work during leisure time were developed (Study 1). Confirmatory factor analyses with a calibration and a cross-validation sample (total N=930) showed that four recovery experiences can be differentiated: psychological detachment from work, relaxation, mastery, and control (Study 2). Examination of the nomological net in a subsample of Study 2 (N=271) revealed moderate relations of the recovery experiences with measures of job stressors and psychological well-being; relations with coping and personality variables were generally low (Study 3). Potential applications for the future use of these short 4-item measures in longitudinal and diary research are discussed.
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The Recovery Experience Questionnaire: Development and
Validation of a Measure for Assessing Recuperation and Unwinding
From Work
Sabine Sonnentag
University of Konstanz
Charlotte Fritz
Bowling Green State University
Drawing on the mood regulation and job-stress recovery literature, four self-report measures for
assessing how individuals unwind and recuperate from work during leisure time were developed
(Study 1). Confirmatory factor analyses with a calibration and a cross-validation sample (total
N 930) showed that four recovery experiences can be differentiated: psychological detachment
from work, relaxation, mastery, and control (Study 2). Examination of the nomological net in a
subsample of Study 2 (N 271) revealed moderate relations of the recovery experiences with
measures of job stressors and psychological well-being; relations with coping and personality
variables were generally low (Study 3). Potential applications for the future use of these short
4-item measures in longitudinal and diary research are discussed.
Keywords: job stress, recovery, unwinding, scale development
Individuals who face stressful work situations ex-
perience poor psychological well-being and tend to
suffer from health problems (De Lange, Taris,
Kompier, Houtman, & Bongers, 2003; Sonnentag &
Frese, 2003). For example, individuals exposed to
job stressors have an increased likelihood for devel-
oping burnout and other symptoms of poor well-
being (Demerouti, Bakker, & Bulters, 2004; Garst,
Frese, & Molenaar, 2000). In addition, stressful work
situations might negatively affect job performance
(Jex, 1998).
Processes related to recovering and unwinding
from job stressors can be relevant for individuals’
health, well-being, and job performance (deCroon,
Sluiter, & Blonk, 2004; Eden, 2001). However, past
research on recovery and recuperation from job stress
mainly focused on general effects of off-job episodes
such as vacations (Fritz & Sonnentag, 2006;
Westman & Eden, 1997) or examined specific off-job
activities such as social, physical, or low-effort ac-
tivities (Sonnentag, 2001; Strauss-Blasche,
Reithofer, Schobersberger, Ekmekcioglu, & Marktl,
2005). Because the underlying psychological experi-
ences associated with recovery gained little research
attention so far (for an exception see Fritz & Son-
nentag, 2005), it remains unexplored why specific
off-job activities are associated with recovery.
Probably, it is not a specific activity per se that
helps to recover from job stress but its underlying
attributes such as relaxation or psychological dis-
tance from job-related issues. Persons may differ
with respect to the specific activities they experience
as recovering while the underlying psychological ex-
periences crucial for recovery may be relatively uni-
form across persons. For example, one person might
recover from job stress by going for a walk while the
other recovers by reading a book. Although the ac-
tivities are different, the underlying processes (e.g.,
relaxation) are rather similar. Going beyond the spe-
cific activities and examining the underlying experi-
ences is crucial for getting more insight into the
psychological processes leading to recovery. To this
end, it is necessary to have reliable and valid mea-
sures available that capture the core functional as-
pects of such recovery experiences. In this paper, we
present a new instrument that assesses specific recov-
ery experiences, namely psychological detachment
from work, relaxation, mastery, and control. In addi-
tion, we examine the relation between these recovery
experiences and potential predictors (work situation
Sabine Sonnentag, Department of Psychology, University
of Konstanz; Charlotte Fritz, Department of Psychology,
Bowling Green State University.
We are grateful to Kerstin Breustedt, Gabriele Bruns,
Maike Debus, Julia Go¨bber, Astrid Kassner, Undine Kruel,
Eva J. Mojza, Kim Pru¨, Holger Roth, Jeannine Sennewald,
and Gudrun Smith for their involvement in data collection
and to Carmen Binnewies, Jana Ku¨hnel, Jennifer McInroe,
Eva J. Mojza, as well as to Lois Tetrick and three anony-
mous reviewers for helpful comments on earlier versions of
this article.
Correspondence concerning this article should be ad-
dressed to Sabine Sonnentag, Department of Psychology,
University of Konstanz, Postbox D 42, D- 78457 Konstanz,
Germany. E-mail:
Journal of Occupational Health Psychology
2007, Vol. 12, No. 3, 204 –221
Copyright 2007 by the American Psychological Association
1076-8998/07/$12.00 DOI: 10.1037/1076-8998.12.3.204
variables, coping, and personality) as well as poten-
tial consequences (psychological well-being).
Conceptualizations of Recovery
Recovery refers to a process during which individ-
ual functional systems that have been called upon
during a stressful experience return to their prestres-
sor levels (Meijman & Mulder, 1998). The recovery
process can be seen as a process opposite to the strain
process. It results in restoration of impaired mood
and action prerequisites and is often also reflected in
a decrease in physiological strain indicators.
To develop an understanding of successful recov-
ery experiences we draw on theories on recovery
processes (Effort-Recovery Model; Conservation of
Resources Theory) as well as on the mood regulation
literature. The Effort-Recovery Model (Meijman &
Mulder, 1998) holds that effort expenditure at work
leads to load reactions such as fatigue or physiolog-
ical activation. Under normal conditions, once the
individual is no longer exposed to the work or similar
demands, load reactions are reversed and recovery
occurs. According to this model, it is an important
precondition for recovery that the functional systems
taxed during work will not be called upon any longer.
The Conservation of Resources Theory (Hobfoll,
1998) assumes that people strive to obtain, retain, and
protect their resources. Resources can be external
entities such as objects or financial assets as well as
internal attributes such as personal characteristics or
energies. Stress threatens these resources and as a
consequence may harm health and well-being. To
recover from stress, individuals have to gain new
resources and restore threatened or lost resources.
Stress recovery on a day-to-day basis particularly
refers to internal resources such as energy or positive
mood. Thus, the Effort-Recovery Model and the
Conservation of Resources Theory suggest two com-
plementary processes by which recovery occurs.
First, it is important to refrain from work demands
and to avoid activities that call upon the same func-
tional systems or internal resources as those required
at work. Second, gaining new internal resources such
as energy, self-efficacy or positive mood will addi-
tionally help to restore threatened resources.
Research on mood regulation offers a more spe-
cific insight into the processes that are relevant for
recovery. Because stressful work conditions often
lead to impaired mood (Fuller et al., 2003), mood
repair is one of the core functions of recovery. Re-
search on mood regulation identified a range of dif-
ferent strategies individuals pursue to improve their
mood including both cognitive and behavioral ap-
proaches (Parkinson, Totterdell, Briner, & Reynolds,
1996; Thayer, Newman, & McClain, 1994).
Parkinson and Totterdell (1999) suggested a clas-
sification of mood regulation strategies comprising
diversionary strategies and engagement strategies.
Diversionary strategies aim at avoiding a negative or
stressful situation and at seeking distraction from it.
Engagement strategies are characterized by confront-
ing or accepting the negative or stressful situation.
Diversionary strategies seem to be most relevant and
promising for stress recovery because engagement
strategies keep the individual cognitively occupied
with the stressful situation and its potential effects
which make recovery less likely.
Recovery Experiences
Among others, diversionary strategies comprise
psychological detachment from work (i.e., mentally
switching off), relaxation-oriented strategies, and
mastery-oriented strategies (Parkinson & Totterdell,
1999). These divisionary strategies, particularly de-
tachment from work and relaxation-oriented strate-
gies, should be useful for recovery because they
imply that no further demands are made on functional
systems called upon during work. Mastery-oriented
strategies should support the recovery process by
building up new internal resources (e.g., self-
efficacy). In addition, because control is a crucial
external resource that provides the opportunity to
gain internal resources (Hobfoll, 1998), we propose
that the experience of control is one important recov-
ery experience.
Psychological Detachment
Although being physically away from the work-
place might be important for recovery, it may not be
sufficient (Hartig, Johansson, & Kylin, 2007). We
propose that becoming psychologically detached
from work is a crucial aspect of any recovery process.
Etzion, Eden, and Lapidot (1998) introduced the term
detachment to describe an “individual’s sense of be-
ing away from the work situation” (p. 579). Detach-
ment implies not to be occupied by work-related
duties such as receiving job-related phone calls at
home or actively engaging in job-related activities. In
our view, psychological detachment also means to
disengage oneself mentally from work. It implies to
stop thinking about one’s work and job-related prob-
lems or opportunities. Psychological detachment
from work goes beyond the pure physical absence
from the workplace during off-job time and abstain-
ing from job-related tasks. It implies leaving the
workplace behind oneself in psychological terms
(Sonnentag & Bayer, 2005).
According to the Effort-Recovery Model, recov-
ery occurs when no further demands are made on
the functional systems called upon during work
(Meijman & Mulder, 1998). When individuals psy-
chologically detach from work during off-job time,
the chances increase that demands on the func-
tional systems taxed during work are reduced.
However, when individuals do not detach and are
still thinking about job-related issues, the identical
functional systems are continuously challenged
and no full recovery can occur.
Empirical evidence suggests that psychological de-
tachment is related to recovery from job stress. For
example, Etzion et al. (1998) showed that detachment
exerts a moderating effect on the relation between
stressors and burnout. Using daily survey data, Son-
nentag and Bayer (2005) reported that individuals
experiencing psychological detachment from work
during leisure time reported better mood at the end of
the evening.
Relaxation is a process often associated with lei-
sure activities. It is characterized by a state of low
activation and increased positive affect (Stone,
Kennedy-Moore, & Neale, 1995). Relaxation may
result from deliberately chosen activities aiming at
the relaxation of body and mind such as progressive
muscle relaxation (Jacobson, 1938) or meditation
(Grossman, Niemann, Schmidt, & Walach, 2004).
Some degree of relaxation may also be achieved
when performing other activities such as taking a
light walk in a beautiful natural environment (Hartig,
Evans, Jamner, Davis, & Ga¨rling, 2003) or listening
to music (Pelletier, 2004). Many individuals expect
relaxation from activities that put few social demands
on them, that require little physical or intellectual
effort, and that present no challenge to them (Tinsley
& Eldredge, 1995). The potential for relaxation ex-
periences to reduce activation and to increase posi-
tive affect are important for recovery in two respects.
First, as Brosschot, Pieper, and Thayer (2005) sug-
gested, prolonged activation resulting particularly
from stressful work is an important mediating mech-
anism by which job stressors translate into illness.
Therefore, processes that reduce this prolonged acti-
vation are crucial in order to restore an organism’s
prestressor state. Second, Frederickson (2000) argued
that positive emotions can undo the effects of nega-
tive emotions. Positive affect resulting from relax-
ation experiences will be helpful in reducing negative
affect resulting from job stress. Empirical evidence
suggests that relaxation experiences help in reducing
stress-related complaints, in the short as well as in the
long run (Stone et al., 1995; Van der Klink, Blonk,
Schene, & Van Dijk, 2001).
Mastery Experiences
Mastery experiences refer to off-job activities that
distract from the job by providing challenging expe-
riences and learning opportunities in other domains.
These activities offer opportunities for experiencing
competence and proficiency. Typical examples in-
clude taking a language class, climbing a mountain,
or learning a new hobby (Fritz & Sonnentag, 2006).
Also volunteer work in which one can demonstrate
one’s competencies can include aspects of mastery
experiences (Ruderman, Ohlott, Panzer, & King,
Mastery experiences challenge the individual with-
out overtaxing his or her capabilities. Attaining mas-
tery experiences is not necessarily effortless but re-
quires a certain degree of self-regulation. For
example, for experiencing mastery by taking a lan-
guage class, it is necessary to exercise some control
over oneself in order to drive to the course and to
overcome the impulse to spend a lazy evening at
home (cf. Vohs & Baumeister, 2004). Although mas-
tery experiences might put additional demands on the
individual, these experiences are expected to result in
recovery because they will help to build up new
internal resources such as skills, competencies, and
self-efficacy (Bandura, 1997; Hobfoll, 1998). In ad-
dition, mastery experiences during off-job time will
help in improving positive mood (Parkinson &
Totterdell, 1999).
First empirical evidence suggests that mastery ex-
periences during off-job time are related to recovery.
For example, mastery experienced during a vacation
was negatively related to exhaustion after the vaca-
tion (Fritz & Sonnentag, 2006). Similarly, the pursuit
of sport—an activity that is often associated with
mastery experiences—is related to an improvement
in affect (Rook & Zijlstra, 2006; Sonnentag & Natter,
Control During Leisure Time
Individuals have a general desire to control events
in their life (Kelley, 1971). Control can be described
as a person’s ability to choose an action from two or
more options. Here, we will focus on the degree to
which a person can decide which activity to pursue
during leisure time, as well as when and how to
pursue this activity.
Personal control seems to be associated with pos-
itive reactions (Burger, 1989). It can lead to a posi-
tive reevaluation of potentially stressful situations
and is associated with lower distress and higher psy-
chological well-being (Lazarus, 1966). Using an ex-
perience-sampling approach, Larson (1989) found
that the experience of control during the day was
positively related to happiness. Thus, individual well-
being is increased when one feels in control of im-
portant life domains (Bandura, 1997).
In contrast, the perception that one’s ability to
react to and influence the social world is reduced can
be associated with higher levels of psychological
distress (Rosenfield, 1989). This experience of low
control can further result in negative self-evaluations
and decreased self-worth which again can be associ-
ated with anxiety or depression (Rosenfield, 1989).
The experience of control during leisure time may
satisfy one’s desire for control by increasing self-
efficacy and feelings of competence, which in turn
promote well-being. In this sense, control may act as
an external resource that enhances recovery from
work during off-job time. In addition, control during
leisure time gives the individual the opportunity to
choose those specific leisure activities that he or she
prefers and that may be especially supportive for the
recovery process. Increased levels of recovery may
then become evident in a person’s increased well-
being and potential for action regulation.
Accordingly, Griffin, Fuhrer, Stansfeld, and
Marmot (2002) found that women experiencing low
control at home showed higher levels of depression
five years later than women high in control at home
while men experiencing low control at home showed
higher levels of depression as well as anxiety than
men with high control at home.
Potential Predictors and Consequences of
Recovery Experiences
Job Stressors and Job Control as Potential
Predictors of Recovery Experiences
We propose that job stressors and job control are
associated with recovery experiences. Job stressors
are conditions in the work situation that make action
regulation more difficult (Frese & Zapf, 1994). Typ-
ical job stressors include workload (time pressure,
overtime), role ambiguity, and situational constraints.
Job control refers to an individual’s discretion to
determine the timing and methods of his or her ac-
tions (Jackson, Wall, Martin, & Davids, 1993) and is
seen as a resource in the action regulation process
(Frese & Zapf, 1994).
We expect negative relations of job stressors with all
four recovery experiences. First, individuals facing job
stressors such as time pressure or overtime might find it
difficult to detach from work during off-job time. When
experiencing job stressors, that is when being con-
fronted with problems and time constraints at work,
individuals will be more likely to keep thinking about
their job in order to develop solutions for these diffi-
culties. In addition, they will anticipate problems and
constraints for the next working day. Empirical evi-
dence suggests that stressful job situations are nega-
tively related to psychological detachment from work
during off-job time (Cropley & Purvis, 2003; Grebner,
Semmer, & Elfering, 2005).
Second, job stressors will be negatively related to
relaxation experiences off the job. Research has
shown that exposure to stressors is associated with
prolonged activation (Brosschot et al., 2005). For
example, employees exposed to high job stress
showed elevated heart rate and systolic blood pres-
sure after work (Vrijkotte, Van Doornen, & De Geus,
2000). This higher level of activation caused by job
stressors will make it more difficult to arrive at a state
of relaxation during off-job time.
Third, job stressors increase fatigue (Zohar,
Tzischinski, & Epstein, 2003) which makes it more
difficult to engage in self-regulatory processes
(Muraven, Tice, & Baumeister, 1998). Because ac-
tivities that result in mastery experiences require a
certain degree of effort and self-regulation, job stres-
sors and associated fatigue will make it less likely to
experience mastery off the job because it is more
difficult to initiate and uphold the respective activi-
ties. Accordingly, research showed that job stressors
are negatively related to the engagement in active
leisure activities such as sport (van Hooff, Geurts,
Kompier, & Taris, 2007).
Job stressors may also decrease the experience of
control outside work. For example, high work de-
mands in terms of long work hours or work brought
home leaves less time available for leisure activities.
This reduces the amount of time the individual can
have control over during off-work time. In addition,
as mentioned above, job stressors such as time pres-
sure or situational constraints may increase fatigue
(Zohar et al., 2003). This may reduce the amount of
internal resources available for self-regulation and
decision making. As a result, the individual may
perceive to have lower control during leisure time
although the “objective” level of control may be
With respect to job control we expect a less uni-
form pattern of relations. We hypothesize negative
relations between job control and psychological de-
tachment and relaxation, and positive relations with
mastery and control. Job control means having deci-
sion latitude about how to do one’s work. This im-
plies that often several options about how to proceed
are available. Therefore, one will be more inclined to
continue thinking about one’s job after work and
psychological detachment from work will be more
difficult. Similarly, because high job control will
stimulate continuous thinking about work during off-
job time, relaxation will be more difficult (Brosschot
et al., 2005).
Job control enables individuals to take an active
approach toward their environment that is reflected in
the pursuit of learning activities (Taris & Kompier,
2005) and other proactive behaviors (Frese, Kring,
Soose, & Zempel, 1996). Because of spillover pro-
cesses across different life domains (Edwards &
Rothbard, 2000) such an active approach should gen-
eralize beyond the job domain and result in the en-
actment of more mastery experiences also during
off-job time. Moreover, job control enables individ-
uals to adapt their working strategies and effort ex-
penditure to their current state (Taris et al., 2006). As
a consequence, they will be less fatigued after work
and will find it less difficult to engage in effortful
activities that provide the opportunities for mastery
Perceiving and experiencing job control will make
it more likely that an individual will also try to exert
control during off-job time (Meissner, 1971). This
means that perceptions of control may “spill over”
into the nonwork domain and that experiencing job
control will be associated with high levels of expe-
rienced control during off-job time.
Coping Styles as Potential Predictors of
Recovery Experiences
We assume that coping styles are related to recov-
ery experiences. Lazarus and Folkman (1984) defined
coping as “constantly changing cognitive and behav-
ioral efforts to manage specific external and/or inter-
nal demands that are appraised as taxing or exceeding
the resources of the person” (p. 141). As coping
refers to an individual’s attempts to deal with stress,
recovery activities can be seen as a way of time-
delayed coping with job stress. However, the con-
cepts are not identical. Whereas coping refers to the
stressor and to the way individuals deal with it,
recovery refers to the way they restore their internal
One categorization of coping styles refers to the
differentiation between problem-focused and emo-
tion-focused coping (Lazarus & Folkman, 1984).
Problem-focused coping includes problem-solving
behaviors and aims at directly addressing and chang-
ing the stressor or other aspects of the situation.
Examples of problem-focused coping include active
coping, planning, suppression of competing activi-
ties, restraint coping, and seeking of instrumental
social support (Carver, Scheier, & Weintraub, 1989).
Emotion-focused coping refers to attempts to manage
cognitions or emotions directly, without changing the
environment. Examples include seeking of emotional
social support, positive reinterpretation, acceptance,
or denial. Carver et al. (1989) suggested a third
category including less successful coping attempts
such as focus on emotions and disengagement.
We propose that some, but not all, coping styles
are associated with recovery experiences. Specifi-
cally, we do not expect a significant relation between
problem-focused coping and psychological detach-
ment from work or relaxation. One might argue that
seeking solutions for work-related problems or stres-
sors keeps individuals cognitively busy with the
problem so that psychological detachment and relax-
ation would be impeded. However, as problem-
solving attempts—probably already during working
time—are successful individuals will find it easier to
detach themselves from work during off-job time and
to relax. We expect that problem-focused coping will
show positive, albeit weak, relations with mastery
and control. Individuals who actively address stres-
sors might also approach their off-job time more
actively. Therefore, they will engage more in activi-
ties that provide mastery experiences and will expe-
rience more control. With respect to emotion-focused
coping we propose a positive relation with all four
recovery experiences. As individuals try to manage
their cognitions and emotions related to job stress,
they will try to seek experiences that give them some
relief and improve their positive mood. However,
particularly with respect to mastery and control we
do not expect strong associations. When it comes to
the coping styles that Carver et al. (1989) assumed to
be less useful such as disengagement or focus on
emotions, the similarity between disengagement and
psychological detachment from work is obvious.
Therefore, we hypothesize a positive relation be-
tween disengagement and psychological detachment.
With respect to the other three recovery experiences
or focus on emotions, we do not propose any signif-
icant relations.
Personality as a Potential Predictor of
Recovery Experiences
We propose that some, but not all, of the Big Five
personality dimensions are related to recovery expe-
riences. We mainly postulate relations between con-
scientiousness and emotional stability on the one
hand and recovery experiences on the other. Except
for one specific relation we do not expect openness to
experience, agreeableness, and extraversion to be re-
lated to the recovery experiences.
Conscientiousness refers to the extent to which an
individual is orderly, self-disciplined, achievement-
oriented, and reliable (Barrick & Mount, 1991; Costa
& McCrae, 1992). As conscientious individuals take
their jobs seriously, they might also think about their
jobs during off-job time. For example, they might
reflect about how to do their work during the upcom-
ing workday. It will be more difficult for them to
psychologically detach from work and relax during
off-work time. At the same time, because they are
achievement-oriented, they might not limit their am-
bitions and self-discipline to their jobs but will also
deliberately pursue activities that offer mastery ex-
periences in other life domains.
Emotional stability is an individual’s tendency to
experience positive emotional states and to show
good emotional adjustment to stressful events (Costa
& McCrae, 1992). It is necessary for regulating one’s
feelings and reactions to stress. Therefore, individu-
als high in emotional stability will not be bothered
much by stressful events encountered at work. They
will find it easier to psychologically detach them-
selves from work and relax during off-job time. As
emotionally stable individuals have a more positive
approach toward their lives, they will also be more
inclined to seek challenging experiences during off-
job time. As they are more tolerable toward stressful
situations, they will be more willing to accept the
demanding nature of activities associated with mas-
tery experiences. Therefore, we hypothesize that
emotional stability will be positively related to mas-
tery experiences. In addition, we propose a positive
relation between emotional stability and control dur-
ing off-job time. As time off the job is often associ-
ated with additional stressors from the family do-
main, individuals high on emotional stability might
feel less emotionally affected by these stressors and
experience more control.
Openness to experience describes individuals in
terms of their creativity, flexibility, and willingness
to take risks (Costa & McCrae, 1992). Because indi-
viduals high on openness to experience are curious
and search for new learning opportunities, we expect
that they will look for opportunities to engage in
mastery experiences. Therefore, we hypothesize a
positive relation between openness to experience and
mastery. We do not expect that openness to experi-
ence will be related to any of the three other recovery
Agreeableness is an individual’s tendency to be
kind, gentle, and to get along well with others in
social settings (Costa & McCrae, 1992). Therefore,
agreeableness should be related to the quality of
interpersonal relations during off-job time. However,
it should be independent of the four recovery expe-
Extraversion refers to the extent to which individ-
uals are sociable, assertive, and energized by social
interactions (Costa & McCrae, 1992). We assume
that both extravert and introvert individuals have the
potential to psychologically detach from work, to
relax, to experience mastery and control—although
the specific activities by which they reach these ex-
periences may largely differ.
Psychological Well-Being as a
Potential Consequence
As recovery experiences help in unwinding from
stress, they will contribute to psychological well-
being. Here we focus on indicators of (impaired)
well-being (e.g., burnout, health complaints, and de-
pressive symptoms), need for recovery, life satisfac-
tion, and sleep.
Unfavorable work situations are associated with
impaired psychological well-being such as health
complaints (Leitner & Resch, 2005), burnout
(Maslach, Schaufeli, & Leiter, 2001), or depressive
symptoms (Dormann & Zapf, 2002). We propose
that recovery experiences are negatively related to
these three indicators of impaired psychological
well-being. Work causes strain reactions in the
individual that will accumulate and in the long
term may develop into health complaints, burnout,
or depressive symptoms if they are not reversed
(Meijman & Mulder, 1998). Recovery experiences
have the potential to “undo” these strain reactions.
Therefore, we hypothesize that the recovery expe-
riences are negatively related to health complaints,
burnout, and depressive symptoms.
Need for recovery is a specific aspect of impaired
well-being and refers to the desire for being tempo-
rarily relieved from demands in order to recuperate
and to replenish internal resources (Sluiter, Van der
Beek, & Frings-Dresen, 1999). Individuals who
chronically experience a high need for recovery feel
that the time regularly available for recovery is not
sufficient for restoring their internal resources. We
hypothesize that recovery experiences are negatively
related to need for recovery.
Life satisfaction is a subjective global judgment of
a person’s quality of life (Diener, Emmons, &
Larson, 1985). Research showed that life satisfaction
is not only influenced by top-down processes with
personality factors affecting life satisfaction, but also
by bottom-up processes with domain-specific satis-
factions impacting on life satisfaction (Heller,
Watson, & Ilies, 2004). Individuals with favorable
recovery experiences will tend to be more satisfied
with their leisure time which in turn will be positively
related to life satisfaction. Empirical research sug-
gests that recovery-related experiences are related to
life satisfaction (Strauss-Blasche, Ekmekcioglu, &
Marktl, 2002). Therefore, we hypothesize that recov-
ery experiences are positively related to life satisfac-
Sleep in itself is important for recovery. During
sleep, many functions of the organism are restored. In
addition, positive recovery experiences should re-
duce the strain level built up during the working day
and should in turn enhance sleep quality. For exam-
ple, when not sufficiently detaching from work and
when keeping thinking about work-related issues,
sleep onset and sleep quality will be impaired. Sim-
ilarly, when relaxation after work is missing, activa-
tion will continue which will make it more difficult to
fall asleep. Mastery and control will give the individ-
ual a feeling of satisfaction and accomplishment that
will have a positive impact on sleep quality.
Table 1 summarizes the hypothesized relations be-
tween recovery experiences and potential predictors
and consequences.
Study 1: Item Generation and Item Review
Our first study aimed at generating and reviewing
items to assess recovery experiences. For all four
dimensions (i.e., psychological detachment, relax-
ation, mastery, control), we generated items that
should tap the respective construct. For generating
these items, we referred to the description of the
constructs as outlined in the introduction of this ar-
ticle, reviewed the literature on recovery and on
mood regulation, and used brainstorming techniques
to cover a broad range of experiences that reflect
these constructs. In total, we generated 47 items, 8
items for psychological detachment, 11 items for
relaxation, 16 items for mastery, and 12 items for
To examine content validity of these items we
provided 16 advanced psychology students with de-
scriptions of the four dimensions and presented the
items to them in a random order. Five students
(31.3%) were in their third year of psychology major,
two students (12.5%) were in their fourth year of
psychology major, five students (31.3%) were in their
fifth year of psychology major, and four participants
(25%) were even more advanced psychology stu-
dents. The students were asked to classify each item
into one of the four dimensions or to an additional
“other” category. To reduce the workload for each
individual rater, eight raters classified a first set of 23
items, eight other raters classified a second set of 24
All items that were classified to the correct a priori
category by at least 75% of the raters were retained.
Based on this decision rule, a total of 35 items re-
mained: 6 items for psychological detachment, 9
items for relaxation, 11 items for mastery, and 9
items for control. Because psychological detachment
had only six items remaining, we kept the two orig-
inal items that did not meet the 75% decision rule.
Both items were correctly classified by 62.5% of the
raters. Thus, we used 37 items for further scale de-
Study 2: Examining Construct Validity
Sample and Procedure
Because recovery opportunities and recovery ex-
periences may largely vary between jobs, we sampled
employees from a variety of different jobs. To recruit
study participants, we first contacted managers of a
broad range of different organizations in various
business sectors. After the managers expressed inter-
est in participation, we approached the employees
either by mail or in person at their workplace, pre-
sented the study and asked for participation.
We contacted a total of 1409 persons by mail and
420 persons directly at their workplace. All these
potential participants were provided with the survey
material and a cover letter describing the study. Per-
sons approached by mail also received a prestamped
envelope addressed to the researchers. Surveys com-
pleted by the persons contacted directly were col-
lected by a member of the research team. From the
persons contacted by mail, 755 questionnaires were
returned (response rate of 53.6%). From the persons
directly contacted, 236 questionnaires were returned
(response rate of 56.2%). A total of 991 question-
naires were returned, for an overall response rate of
Most participants were women (71%). Partici-
pants’ mean age was 38.3 years (SD 12.3), mean
job tenure was 15.1 year (SD 11.2). Among all
participants, 24.0% had a supervisory position. Of the
total sample, 58.0% had children with an average of
1.8 children. Participants came from a broad variety
of private and public organizations with 26.7% work-
ing in the public administration, 18.3% as teachers in
schools, 11.0% in call centers, 9.6% in hospitals,
9.3% in nursing homes, 6.0% in public relation agen-
cies, 4.5% in retail companies, and 4.1% in insurance
organizations. The remaining participants came from
a manufacturing company, banks, hotels, travel agen-
cies, and other service organizations. The percentage
of participants working irregular hours was 18.6%.
Data on psychological detachment from N 148
teachers participating in this study were also used in
another study (Sonnentag & Kruel, 2006).
The survey included a total of 37 items assessing
recovery experiences (psychological detachment: 8
items, relaxation: 9 items, mastery: 11 items; control:
9 items). Participants were asked to respond to the
items with respect to their free evenings (e.g., “Dur-
ing time after work, I kick back and relax”) on a
5-point scale from1 (I do not agree at al) to5(I fully
agree). Moreover, we assessed gender, age, number
of children, job tenure and occupation. In a sub-
sample (N 271), we additionally measured a range
of other variables to examine the nomological net of
the recovery experience measures (see Study 3).
Strategy for Analyzing Data
To examine the construct validity of our recovery
experience measures, we used a cross-validation ap-
proach and randomly split the overall sample (N
991) into two subsamples. Because of missing val-
ues, sample size in each of the two subsamples was
N 465. We used the first subsample for finding the
best-fitting model (calibration sample) and then
cross-validated this model with the second subsample
(cross-validation sample).
Table 1
Hypothesized Relations Between Recovery Experiences, Potential Predictors, and Potential Outcomes
detachment Relaxation Mastery Control
Job situation variables
Job stressors ⫺⫺
Job control ⫺⫺
Problem-focused coping 0 0 ⫹⫹
Emotion-focused coping ⫹⫹
Other coping strategies 000
Agreeableness 0 0 0 0
Openness 0 0 0
Extraversion 0 0 0 0
Conscientiousness ⫺⫺0
Emotional stability ⫹⫹
Psychological well-being
Health complaints ⫺⫺
Burnout ⫺⫺
Depressive symptoms ⫺⫺
Need for recovery ⫺⫺
Life satisfaction ⫹⫹
Sleep problems ⫺⫺
Note. ⫹⫽hypothesized positive relation; ⫺⫽hypothesized negative relation; 0 no relation hypothesized.
By using calibration sample data, we submitted a
covariance matrix based on the 37 items derived from
Study 1 to a set of Confirmatory Factor Analyses.
First, we separately fitted single-factor models for
each of the four constructs and then fitted two-factor
models for all possible pairs of constructs (relaxation
vs. mastery, relaxation vs. psychological detachment,
relaxation vs. control etc.). Subsequently, we deleted
items that (a) had very high cross-loading on another
than the intended factor, (b) showed high across-
factor correlated measurement errors, and (c) low
loadings on the intended factor (modification indices
exceeding 25.00 and factor loadings below 0.50).
This procedure resulted in a set of 20 items. We
conducted a Confirmatory Factor Analysis with these
20 items by specifying a four-factor structure. Anal-
ysis showed a reasonable, although not very good fit
631.13; df 164; GFI .88; NNFI .96;
CFI .95; RMSEA .078; SRMR .055). To
arrive at a better model fit and at shorter, more
parsimonious scales, we again removed some items
based on the above specified criteria. The final model
comprised 16 items with an acceptable fit (
317.15; df 98; GFI .92; NNFI .97; CFI .97;
RMSEA .069; SRMR .045). We compared this
four-factor model with alternative one-factor, two-
factor, and three-factor models. Table 2 shows the fit
indices of the best-fitting two-factor models and best-
fitting three-factor models. The four-factor model
showed a significantly better fit than the one-factor
model (⌬␹
2131.66; df 6; p .001), all
two-factor models (⌬␹
1713.31; df 5; p
.001), and all three-factor models (⌬␹
df 3; p .001).
In the next step, we further examined this factor
structure with the cross-validation sample. We first
tested a model with the 20 items used in the calibra-
tion sample. This 20-item model resulted in a reason-
able but slightly worse fit than analysis with the
calibration sample (
705.82; df 164; GFI
.87; NNFI .95; CFI .96; RMSEA .084;
SRMR .060). The four-factor model with 16 items
resulted in an acceptable fit (
403.60; df 98;
GFI .90; NNFI .96; CFI .96; RMSEA .082;
SRMR .049) although the RMSEA slightly devi-
ated from the recommended value of .080. Again,
this four-factor model showed a better fit than the
one-factor model (⌬␹
2597.16; df 6; p
.001), all two-factor models (⌬␹
2033.05; df
5; p .001), and all three-factor models (⌬␹
704.46; df 3; p .011).
Table 3 displays items wordings, factor loadings,
and alphas for both subsamples. Taken together, the
confirmatory factor analyses showed that the four
recovery experience scales represent distinct con-
structs and show good reliability. Table 4 shows that
the correlations among the latent variables were mod-
erate. Only relaxation and control were rather highly
correlated. For further analyses we used the un-
weighted means of all scale items as indicators for
the respective scales.
Table 2
Goodness of Fit Statistics
Calibration sample
One-factor model 2448.80 104 .60 .72 .75 .22 .15
Best fitting two-factor model
2030.46 103 .65 .77 .80 .20 .14
Best fitting three-factor model
863.65 101 .81 .91 .92 .13 .06
Four-factor model 317.15 98 .92 .97 .97 .07 .05
Cross-validation sample
One-factor model 3000.76 104 .55 .67 .71 .25 .16
Best fitting two-factor model
2436.65 103 .60 .74 .78 .22 .18
Best fitting three-factor model
1108.06 101 .77 .89 .91 .15 .07
Four-factor model 403.60 98 .90 .96 .96 .08 .05
Note. GFI goodness-of-fit index; NNFI nonnormed fit index; CFI comparative fit index; RMSEA root mean
square error of approximation; SRMR standardized root mean square residual.
Psychological detachment and relaxation items loading on the first factor and mastery and control items loading on the
second factor.
Relaxation and control items loading on the first factor, psychological detachment items loading on the
second, and mastery items loading on the third factor.
Relaxation and control items loading on the first factor and
psychological detachment and mastery items loading on the second factor.
Study 3: Examining the Nomological Net
Study 3 aimed at analyzing the nomological net of
the four recovery experience measures by examining
their relations with potential predictors and conse-
Two subsamples from Study 2 participated in this
study. Subsample 1 comprised 134 persons (47% men).
Mean age was 40.9 years (SD 10.4); mean job tenure
was 18.4 years (SD 11.2). About a third (32.1%) of
the first subsample held a supervisory position. Of all
participants in this subsample, 53% had children with
an average of 2.0 children. Most participants came from
local public administration organizations (86.8%). The
other participants worked in travel agencies (7.8%) and
retail organizations (5.4%). Subsample 2 comprised 137
persons (60.6% men) with a mean age of 38.6 years
(SD 9.6) and mean job tenure of 15.3 years (SD
9.4). Of these 137 persons, 30% worked in a supervi-
sory position. About a half (52.6%) of the participants
had children with an average of 1.8 children. Partici-
pants worked in the field of local public administration
(79.9%), in a technical service company (7.5%), travel
agencies (7.6%), and retail organizations (6.0%).
Table 3
Factor Loadings and Alphas for Recovery Experience Measures
detachment Relaxation Mastery Control
I forget about work. 0.96 (0.05)
0.90 (0.04)
I don’t think about work at all. 0.88 (0.05)
0.91 (0.05)
I distance myself from my work. 0.85 (0.04)
0.79 (0.04)
I get a break from the demands of work. 0.69 (0.04)
0.56 (0.03)
I kick back and relax. 0.74 (0.04)
0.66 (0.03)
I do relaxing things. 0.52 (0.03)
0.75 (0.04)
I use the time to relax. 0.70 (0.03)
0.79 (0.04)
I take time for leisure. 0.61 (0.03)
0.64 (0.03)
I learn new things. 0.60 (0.04)
0.65 (0.04)
I seek out intellectual challenges. 0.79 (0.04)
0.72 (0.03)
I do things that challenge me. 0.64 (0.04)
0.66 (0.03)
I do something to broaden my horizons. 0.60 (0.03)
0.67 (0.03)
I feel like I can decide for myself what
to do. 0.79 (0.05)
0.58 (0.03)
I decide my own schedule. 0.60 (0.03)
0.86 (0.04)
I determine for myself how I will spend
my time.
0.69 (0.03)
0.68 (0.03)
I take care of things the way that I want
them done.
0.67 (0.04)
0.48 (0.03)
Cronbach’s alpha .84 .85 .79 .85
.85 .85 .85 .85
Note. Factor loadings with standard errors in parentheses. Upper rows give estimates from the calibration sample, lower
rows give estimates from the cross-validation sample.
There were no mean differences in the four recov-
ery experience scales, neither between these two sub-
samples nor between these two subsamples and par-
ticipants who only participated in Study 2. Overall,
also the correlational patterns did not differ between
the various subsamples. However, the correlation be-
tween relaxation and control in the two subsamples
was somewhat higher, r .64, N 271, than in the
larger sample (excluding the two subsamples), r
.51, N 719, z 2.72, p .01.
In both subsamples we assessed job stressors and
job control. We additionally measured coping and
personality variables in subsample 1, and psycholog-
ical well-being in subsample 2. We decided not to
measure all variables in both subsamples in order not
to impose heavy time demands on our participants
when completing the surveys. Table 5 displays
means, standard deviations, correlations, and alphas
for all study variables. Higher scores indicate a
higher degree of the phenomenon under study.
Work situation variables. We assessed job stres-
sors and job control with measures developed by
Semmer (1984; cf. Zapf, 1993). To cover different
job stressors, we assessed time pressure, role ambi-
guity, situational constraints, and hours of overtime.
We measured time pressure with five items (e.g.,
“How often is a fast pace of work required of you?”)
using a 5-point scale from 1 (almost never)to5(very
often). For assessing role ambiguity we used five
items (e.g., “How often do you receive contradictory
instructions from different supervisors?”) with a
5-point scale from 1 (almost never)to5(very often).
We measured situational constraints with five items
describing two contrasting workplaces (e.g., “Person
A must spend a lot of time in order to get information
and/or materials to pursue his or her work activity.”
“Person B always has the necessary information
and/or materials at his or her disposal.”). On a 5-point
scale from 1 (my job is exactly like that of Person B)
to5(my job is exactly like that of Person A), partic-
ipants had to indicate which of the descriptions most
adequately characterized their work situation. We
assessed hours of overtime with one single item. We
measured job control with five items (e.g., “Can you
yourself decide on which way to carry out your
work?”) using a 5-point scale from 1 (very little)to5
(to a very large extent).
Coping. We assessed coping in subsample 1 with
the COPE measures (Carver et al., 1989) in their
German version (Vollrath & Torgersen, 2000). We
measured four coping strategies representing prob-
lem-focused coping (active coping, planning, re-
straint coping, use of instrumental social support),
two coping strategies representing emotion-focused
coping (denial, use of emotional social support), and
three other coping attempts (focus on emotions, be-
havioral disengagement, mental disengagement). All
coping strategies were assessed with four items each
on a 4-point scale from 1 (never)to4(often).
Personality. We assessed the Big Five personal-
ity factors in subsample 1 with the German Version
(Lang, Lu¨dtke, & Asendorpf, 2001) of the Big Five
Inventory (John & Srivastava, 1999) and measured
conscientiousness with nine items, emotional stabil-
ity with seven items, openness to experience with 10
items, extraversion with eight items, and agreeable-
ness with eight items on 5-point scales from1 (not at
all)to5(very much).
Psychological well-being. In subsample 2 we as-
sessed health complaints, burnout, depressive symp-
toms, need for recovery, life satisfaction, and sleep
problems as indicators of (poor) psychological well-
being. We measured health complaints with 12 items
from the General Health Questionnaire (Goldberg,
1972; e.g., “Did you experience a lack of self-
confidence during the last two weeks?”) on a 4-point
scale from 1 (not at all)to4(much more than usual).
We measured burnout with the Oldenburg Burnout
Inventory (Demerouti, Bakker, Nachreiner, &
Schaufeli, 2001) and assessed emotional exhaustion
(e.g., “After my work I usually feel worn out and
weary”) and disengagement (e.g., “I usually talk
about my work in a derogatory way”) with eight
items each on a 4-point scale from1 (fully disagree)
to4(fully agree). We assessed depressive symptoms
with eight items developed by Mohr (1986; e.g., “I
am often in a sad mood”). We used a 7-point re-
Table 4
Correlations Between the Latent Variables
detachment Relaxation Mastery Control
detachment .42 .19 .41
Relaxation .46 .30 .71
Mastery .21 .34 .28
Control .37 .65 .25
Note. Correlations above the diagonal are from the cali-
bration sample. Correlations below the diagonal are from
the cross-validation sample. All correlations are significant
at p .01.
sponse scale from 1 (almost always)to7(never) that
was reversed for correlational analysis. Need for re-
covery was measured with 11 items (van Veldhoven
& Broersen, 2003; e.g., “At the end of a working day
I am really feeling worn-out”) using a 4-point scale
from 1 (never)to4(always). For measuring life
satisfaction we used five items from the Satisfaction
With Life Scale (Diener et al., 1985; e.g., “In most
ways my life is close to my ideals”) to be answered
on a 7-point scale from 1 (fully disagree)to7(fully
agree). We measured sleep problems with nine items
from the Pittsburgh Sleep Quality Index (Buysse,
Reynolds, Monk, Berman, & Kupfer, 1989) using a
4-point scale from 1 (not at all)to4(three times or
more per week).
Table 5 shows the relations between all study
variables. Time pressure was negatively related to all
recovery experience variables with the exception of
mastery. Role ambiguity and situational constraints
were negatively related to psychological detachment
and control. Hours of overtime were negatively re-
lated to psychological detachment and relaxation but
not to mastery or control. Job control was positively
related to control during off-job time. Taken together,
analysis largely confirmed our hypotheses for job
stressors and partially for job control.
Correlations between coping and recovery experi-
ences were low and mostly nonsignificant. There were
some significant correlations, namely between active
coping and the experience of mastery and control. Re-
straint coping was positively related to psychological
detachment and mastery. Seeking instrumental social
support showed a positive relation with relaxation and
control. Seeking emotional social support was nega-
tively related to psychological detachment and posi-
tively related to relaxation and control. Mental disen-
gagement was positively related to relaxation. These
generally low correlations between coping and recovery
experiences provided partial support for our hypotheses
and overall demonstrated that there is only limited over-
lap between the way an individual responds to a stres-
sors (i.e., coping) and how he or she experiences recov-
ery off the job.
Most correlations between the personality variables
and the recovery experience constructs were low and
nonsignificant indicating that personality seems not to
be a core predictor of how individuals experience their
off-job time. Openness to experience and extraversion
were positively related to mastery. Emotional stability
was positively correlated with psychological detach-
ment, mastery, and control. Overall, most of our hy-
potheses on the relation between personality and recov-
ery experiences were supported.
We found moderate relations between recovery
experiences and well-being measures. Psychological
detachment and control showed negative relations
with health complaints, emotional exhaustion, de-
pressive symptoms, need for recovery, and sleep
problems. Relaxation showed negative relations with
health problems, emotional exhaustion, need for re-
covery, and sleep problems. Mastery was negatively
related to emotional exhaustion, depressive symp-
toms, and need for recovery. All recovery experience
measures showed positive relations with life satisfac-
tion. Except for the burnout dimension disengage-
ment, the overall pattern of correlations supported
our hypotheses.
Overall Discussion
In this article we presented measures for assessing
recovery experiences. Confirmatory factor analyses
showed that four distinct recovery experiences can be
differentiated (psychological detachment, relaxation,
mastery, control). The scales have good internal con-
sistencies and are short so that they can be used in
future research without putting high time demands on
study participants.
Correlational analyses showed that job stressors
were related to three of the four recovery experi-
ences. The rather high negative correlation between
time pressure and psychological detachment is in line
with earlier research (Sonnentag & Bayer, 2005)
suggesting that time pressure and the associated high
workload make it particularly difficult to switch off
from work during leisure time. Relaxation was re-
lated to aspects of quantitative workload, but not to
other job stressors. It might be that particularly pro-
longed activation because of time pressure and over-
time hinders relaxation during off-job time, whereas
other job stressors do not necessarily result in pro-
longed activation but impede other aspects of recov-
ery by depleting self-regulatory resources (Sonnentag
& Jelden, 2005). Unexpectedly, job stressors were
not related to mastery experiences. It might be that
individuals do not react uniformly to job stressors.
Some individuals might feel that job stressors hinder
them to enjoy mastery, whereas others might delib-
erately try to counteract the negative effects of job
stressors by engaging in activities that provide the
opportunity for positive experiences and mastery.
Job control was not related to psychological de-
tachment, relaxation, or mastery. One might specu-
late that the association between job control and
recovery experiences is a more complex one. For
example, in jobs with high control there might exist
some recovery opportunities even during working
time (Taris et al., 2006), in turn making detachment
and relaxation at home more likely. However, as job
control often implies the possibility and the necessity
to make decisions, at the same time recovery off the
job might be impaired.
Correlations between coping measures and recov-
ery experiences were generally low and mostly non-
significant. One reason for the low correlations might
be that our coping measures were rather broad and
did not focus on coping with job-related matters
whereas the recovery experiences, particularly psy-
chological detachment, more closely referred to job-
related recovery. However, problem-focused coping
was related to the recovery experience control which
might reflect a person’s general tendency to actively
approach everyday situations and problems. Interest-
ingly, both social support measures were related to
relaxation. It might be that social support is particu-
larly helpful in calming down after work. It will be an
interesting question for future research to examine in
more detail if social support at work or social support
at home is more closely related to relaxation.
Table 5
Means, Standard Deviations, Zero-Order Correlations, and Alphas of Study 3 Variables
MSD 123456789
Recovery experiences
1. Psychological detachment
3.00 0.97 .89
2. Relaxation
3.29 0.80 .33 .87
3. Mastery
3.04 0.71 .16 .24 .82
4. Control
3.70 0.77 .33 .64 .30 .87
Job situation variables
5. Time pressure
3.03 0.96 .49 .31 .04 .32 .89
6. Role ambiguity
2.40 0.66 .19 .03 .02 .21 .33 .69
7. Situational constraints
2.59 0.69 .15 .11 .08 .21 .34 .57 .70
8. Hours of overtime
4.51 6.06 .23 .18 .05 .11 .42 .00 .01
9. Job control
3.68 0.66 .11 .02 .08 .16 .07 .29 .20 .29 .77
10. Active coping
2.84 0.54 .03 .12 .26 .18 .08 .10 .12 .15 .19
11. Planning
2.90 0.56 .10 .02 .14 .13 .10 .04 .09 .21 .27
12. Restraint coping
2.69 0.91 .17 .16 .02 .17 .11 .01 .15 .03 .05
13. Instrumental social
2.48 0.67 .07 .33 .09 .18 .05 .06 .09 .02 .07
14. Emotional social support
2.56 0.74 .19 .33 .07 .18 .03 .01 .05 .03 .06
15. Denial
1.24 0.36 .00 .13 .05 .07 .04 .12 .04 .19 .18
16. Focus on emotions
2.27 0.85 .07 .16 .03 .13 .00 .18 .12 .19 .17
17. Behavioral
1.49 0.45 .02 .05 .14 .10 .02 .15 .11 .19 .23
18. Mental disengagement
2.24 0.56 .06 .22 .02 .06 .03 .28 .20 .27 .25
19. Agreeableness
3.64 0.52 .13 .02 .06 .07 .14 .16 .11 .05 .11
20. Openness
3.46 0.60 .03 .04 .35 .06 .08 .00 .10 .20 .18
21. Extraversion
3.45 0.64 .06 .07 .22 .15 .04 .09 .11 .22 .19
22. Conscientiousness
3.73 0.60 .09 .12 .12 .07 .04 .06 .03 .02 .14
Psychological well-being
23. Emotional stability
3.30 0.61 .30 .12 .21 .24 .18 .24 .24 .14 .22
24. Health complaints
2.01 0.54 .47 .24 .15 .25 .32 .40 .41 .08 .32
25. Emotional exhaustion
2.41 0.57 .56 .34 .25 .41 .44 .33 .45 .06 .22
26. Disengagement
2.05 0.54 .16 .09 .11 .13 .02 .40 .42 .09 .47
27. Depressive symptoms
2.81 1.04 .40 .16 .18 .18 .16 .44 .42 .05 .35
28. Need for recovery
2.19 0.58 .52 .27 .24 .38 .34 .34 .44 .08 .18
29. Life satisfaction
4.58 1.28 .37 .22 .24 .21 .22 .40 .37 .06 .21
30. Sleep problems
1.79 0.54 .25 .18 .02 .21 .12 .26 .29 .04 .21
Note. Alphas are displayed on the diagonal.
N 267–271; all correlations r .12 are significant with p .05.
N 134; all correlations r .17 are significant with p
N 137; all correlations r .17 are significant with p .05.
Range: 1 to 5.
Range 1 to 4.
Range 1 to 7.
As predicted, correlations between personality and
recovery experience measures were generally low.
The significant correlations between emotional sta-
bility and the recovery experiences might indicate
that poor recovery from work may partly result from
low emotional stability or negative affectivity. How-
ever, the correlations were only moderate in size
suggesting that poor recovery experiences do not
only reflect low emotional stability.
Recovery experiences were related to most of the
indicators of psychological well-being. These find-
ings might indicate that poor recovery harms psycho-
logical well-being. It might also be that individuals
suffering from impaired well-being are less likely to
enjoy positive recovery experiences.
Among all four recovery experiences, psycho-
logical detachment showed the strongest relations
with impaired well-being. This finding might
indicate that psychological detachment is the most
relevant recovery experience. Overall, our analyses
demonstrated that recovery experiences, particu-
larly psychological detachment and control were
associated with job stressors and well-being.
Although any causal inferences from these
cross-sectional findings are premature, our study
suggests that it is promising to examine the rela-
tions between an unfavorable work situation,
poor recovery and impaired well-being in more
detail. For example, one might speculate that job
stressors lead to poor recovery experiences that in
Table 5
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
.65 .79
.10 .28 .63
.33 .36 .02 .79
.15 .20 .01 .77 .85
.17 .27 .02 .02 .03 .71
.09 .12 .00 .22 .25 .10 .73
.37 .24 .01 .00 .01 .28 .35 .72
.30 .13 .15 .06 .21 .34 .25 .33 .66
.14 .07 .13 .16 .12 .06 .08 .07 .09 .69
.27 .31 .07 .23 .23 .07 .03 .11 .02 .23 .78
.45 .26 .08 .32 .29 .00 .05 .32 .09 .31 .37 .85
.43 .24 .07 .08 .07 .11 .13 .34 .11 .24 .35 .28 .75
.29 .14 .04 .02 .13 .11 .21 .42 .25 .40 .13 .40 .18 .79
-------------- .91
-------------- .51.84
-------------- .48.45.81
-------------- .
-------------- .
--------------.54 .49 .55 .65 .44 .88
-------------- . .79
turn negatively affect well-being (cf. Geurts &
Sonnentag, 2006).
Our studies have some limitations. First, the four
recovery experience measures might not comprise all
potentially relevant recovery experiences. One might
argue that the general affective valence of a recovery
activity represents an important aspect of any recov-
ery experience. That is, the potential of a recovery
experience to enhance positive emotions might be
particularly important (Fredrickson, 2000). Instead of
conceptualizing positive affective valence as a sepa-
rate recovery experience, we think that finding plea-
sure in off-job activities is a higher-order concept that
cannot be easily differentiated from other recovery
experiences. Empirical studies on mood regulation
suggest that pleasure is associated with experiences
such as relaxation or distraction (Thayer et al., 1994;
Totterdell & Parkinson, 1999).
Similarly, the degree to which a recovery activity
provides opportunities for social contact and connect-
edness might be important. Scholars in the field of
social psychology have argued that social inclusion is
one core striving of human beings (Baumeister &
Leary, 1995). Also with respect to recovery pro-
cesses, the relevance of social activities has been
demonstrated (Fritz & Sonnentag, 2005). Therefore,
future research may put more emphasis on the social
embeddedness of recovery. However, when doing so,
we suggest keeping in mind that social contact and
connectedness might not only be a source of social
support and recovery, but potentially also of social
undermining and interpersonal conflict.
The correlations between the latent variables re-
laxation and control were rather high. Therefore, one
might question if relaxation and control represent two
distinct constructs. However, confirmatory factor
analyses showed that the 4-factor model fitted the
data better than a 3-factor model. In addition, al-
though the correlational patterns of the relaxation and
the control scale with other variables showed simi-
larities, they were far from being identical suggesting
that it makes sense to differentiate between relaxation
and control.
Finally, it has to be noted that the sample sizes in
Study 3 were relatively small. Therefore, particularly
the nonsignificant correlations should be interpreted
with great caution. A replication with a larger sample
is clearly desirable.
Suggestions for Future Research and
Potential Applications
The correlations found between low psychological
detachment and impaired well-being might suggest
that psychological detachment from work during off-
job time is crucial for protecting one’s well-being.
However, this conclusion is premature—not only be-
cause our data do not warrant any causal interpreta-
tion. Not detaching from work does not necessarily
imply that thinking about work is negative per se.
Positively reflecting about one’s work (e.g., thinking
about a recent success or about an inspiring goal)
might even improve well-being (Fritz & Sonnentag,
2005). It can be promising for future research to
assess in greater detail the type and quality of work-
related thoughts during off-job time.
Our relaxation items refer to experiences that can
be initiated both by deliberate relaxation exercises
(e.g., progressive muscle relaxation) and by other
activities such as taking a walk or listening to calm
music. It could be interesting for future research to
differentiate between purposeful relaxation practices
and other experiences that have a strong relaxational
component and to explore their role in the recovery
In Study 3, we focused on zero-order correlations
between recovery experiences and a range of other
variables. Future research may examine more com-
plex patterns of relations. For example, recovery ex-
periences might be conceptualized as a moderator in
the relation between job stressors and impaired well-
being with poor recovery experiences increasing the
association between job stressors and poor well-
being. Moreover, personality might be examined as a
moderator in the relations between job stressors and
recovery experiences. For example, one could argue
the job stressors are particularly related to poor psy-
chological detachment in persons low on emotional
One important application would be to use the
recovery measures in longitudinal research. Future
studies should examine if recovery experiences can
predict changes in well-being and job performance
over time. Moreover, as our scales are short, they can
also be easily adapted for use in diary studies. Such
studies could examine recovery processes at the day
level and could therefore shed more light onto short-
er-term processes related to the maintenance of pos-
itive mood and performance capability. For example,
the recovery experience scales can be applied when
extending research on episodic models of perfor-
mance (Beal, Weiss, Barros, & MacDermid, 2005). It
would be particularly interesting to examine if recov-
ery experiences can explain day-level variations in
performance. Another option could be to integrate the
recovery experience measures in studies on physio-
logical processes related to activation and unwinding
(Semmer, Grebner, & Elfering, 2004; Sonnentag &
Fritz, 2006).
To conclude, the recovery experience question-
naire offers an economic and reliable approach to
assess individuals’ unwinding and recuperation pro-
cesses. It can be a useful tool in the endeavor to better
understand the mechanisms underlying the effects of
job stressors on the individual. In addition, and
maybe more importantly, it can serve as an instru-
ment that identifies experiences helpful in protecting
individuals’ well-being and performance capability.
Bandura, A. (1997). Self-efficacy: The exercise of control.
New York: Freeman.
Barrick, M. R., & Mount, M. K. (1991). The big five
personality dimensions and job performance: A meta-
analysis. Personnel Psychology, 44, 1–26.
Baumeister, R. F., & Leary, M. R. (1995). The need to
belong: Desire for interpersonal attachments as a funda-
mental human motivation. Psychological Bulletin, 117,
Beal, D. J., Weiss, H. M., Barros, E., & MacDermid, S. M.
(2005). An episodic process model of affective influ-
ences on performance. Journal of Applied Psychology,
90, 1054–1068s.
Brosschot, J. F., Pieper, S., & Thayer, J. F. (2005). Expand-
ing stress theory: Prolonged activitation and persevera-
tive cognition. Psychoneuroendocrinology, 30, 1043–
Burger, J. M. (1989). Negative reactions to increases in
perceived personal control. Journal of Personality and
Social Psychology, 56, 246 –256.
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R.,
& Kupfer, D. J. (1989). Pittsburgh sleep quality index
(PSQI). Psychiatry Research, 28, 193–213.
Carver, C. S., Scheier, M. F., & Weintraub, J. K. (1989).
Assessing coping strategies: A theoretically based ap-
proach. Journal of Personality and Social Psychology,
56, 267–283.
Costa, P. T., Jr., & McCrae, R. R. (1992). Revised neo
personality inventory (NEO-PI-R) and neo five-factor
inventory (NEO-FFI) professional manual. Odessa, FL:
Psychological Assessment Resources.
Cropley, M., & Purvis, L. J. M. (2003). Job strain and
rumination about work issues during leisure time: A
diary study. European Journal of Work and Organiza-
tional Psychology, 12, 195–207.
deCroon, E. M., Sluiter, J. K., & Blonk, R. W. B. (2004).
Stressful work, psychological job strain, and turnover: A
2-year prospective cohort study of truck drivers. Journal
of Applied Psychology, 89, 442– 454.
De Lange, A. H., Taris, T. W., Kompier, M. A. J., Houtman,
I. L. D., & Bongers, P. M. (2003). “The very best of the
millenium”: Longitudinal research and the demand-
control-(support) model. Journal of Occupational Health
Psychology, 8, 282–305.
Demerouti, E., Bakker, A. B., & Bulters, A. J. (2004). The
loss spiral of work pressure, work-home interference and
exhaustion: Reciprocal relations in a three-way study.
Journal of Vocational Behavior, 64, 131–149.
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli,
W. B. (2001). Job demands-resources model of burnout.
Journal of Applied Psychology, 86, 499 –512.
Diener, E., Emmons, R. A., & Larson, R. J. (1985). The
satisfaction with life scale. Journal of Personality As-
sessment, 49, 71–75.
Dormann, C., & Zapf, D. (2002). Social stressors at work,
irritation, and depressive symptoms: Accounting for un-
measured third variables in a multi-wave study. Journal
of Occupational and Organizational Psychology, 75, 33–
Eden, D. (2001). Vacations and other respites: Studying
stress on and off the job. In C. L. Cooper & I. T.
Robertson (Eds.), International review of industrial and
organizational psychology (pp. 121–146). Chichester:
Edwards, J. R., & Rothbard, N. P. (2000). Mechanisms
linking work and family: Clarifying the relationship be-
tween work and family constructs. Academy of Manage-
ment Review, 25, 178 –199.
Etzion, D., Eden, D., & Lapidot, Y. (1998). Relief from job
stressors and burnout: Reserve service as a respite. Jour-
nal of Applied Psychology, 83, 577–585.
Fredrickson, B. L. (2000). The undoing effect of positive
emotions. Motivation and Emotion, 24, 237–258.
Frese, M., Kring, W., Soose, A., & Zempel, J. (1996).
Personal initiative at work: Differences between East and
West Germany. Academy of Management Journal, 39,
37– 63.
Frese, M., & Zapf, D. (1994). Action as the core of work
psychology: A German approach. In H. C. Triandis,
M. D. Dunnette, & L. M. Hough (Eds.), Handbook of
industrial and organizational psychology (2nd ed., Vol.
4, pp. 271–340). Palo Alto, CA: Consulting Psycholo-
gists Press.
Fritz, C., & Sonnentag, S. (2005). Recovery, health, and job
performance: Effects of weekend experiences. Journal of
Occupational Health Psychology, 10, 187–199.
Fritz, C., & Sonnentag, S. (2006). Recovery, well-being,
and performance-related outcomes: The role of workload
and vacation experiences. Journal of Applied Psychol-
ogy, 91, 936 –945.
Fuller, J. A., Stanton, J. M., Fisher, G. G., Spitzmu¨ller, C.,
Russell, S. S., & Smith, P. C. (2003). A lengthy look at
the daily grind: Time series analyses of events, mood,
stress, and satisfaction. Journal of Applied Psychology,
88, 1019–1033.
Garst, H., Frese, M., & Molenaar, P. C. M. (2000). The
temporal factor of change in stressor-strain relationships:
A growth curve model on a longitudinal study in East
Germany. Journal of Applied Psychology, 85, 417– 438.
Geurts, S. A. E., & Sonnentag, S. (2006). Recovery as an
explanatory mechanism in the relation between acute
stress reactions and chronic health impairment. Scandi-
navion Journal of Work, Environment and Health, 32,
482– 492.
Goldberg, D. (1972). The detection of psychiatric illness by
questionnaire. London: Oxford University Press.
Grebner, S., Semmer, N. K., & Elfering, A. (2005). Work-
ing conditions and three types of well-being: A longitu-
dinal study with self-report and rating data. Journal of
Occupational Health Psychology, 10, 31– 43.
Griffin, J. M., Fuhrer, R., Stansfeld, S. A., & Marmot, M.
(2002). The importance of low control at work and home
on depression and anxiety: Do these effects vary by
gender and social class? Social Science & Medicine, 54,
Grossman, P., Niemann, L., Schmidt, S., & Walach, H.
(2004). Mindfulness-based stress reduction and health
benefits: A meta-analysis. Journal of Psychosomatic Re-
search, 57, 35– 43.
Hartig, T., Evans, G. W., Jamner, L. D., Davis, D. S., &
Ga¨rling, T. (2003). Tracking restoration in natural and
urban field settings. Journal of Environmental Psychol-
ogy, 23, 109 –123.
Hartig, T., Johansson, G., & Kylin, C. (2007). The telework
tradeoff: Stress mitigation vs. constrained restoration.
Applied Psychology: An International Review, 56, 231–
Heller, D., Watson, D., & Ilies, R. (2004). The role of
person versus situation in life satisfaction: A critical
examination. Psychological Bulletin, 130, 574 600.
Hobfoll, S. E. (1998). Stress, culture, and community: The
psychology and physiology of stress. New York: Plenum
Jackson, P. R., Wall, T. D., Martin, R., & Davids, K. (1993).
New measures of job control, cognitive demand, and
production responsibility. Journal of Applied Psychol-
ogy, 78, 753–762.
Jacobson, E. (1938). Progressive relaxation. Chicago: Uni-
versity of Chicago Press.
Jex, S. M. (1998). Stress and job performance: Theory,
research, and implications for managerial practice.
Thousand Oaks, CA: Sage.
John, O. P., & Srivastava, S. (1999). The big five trait
taxonomy: History, measurement, and theoretical per-
spectives. In L. A. Pervin & O. P. John (Eds.), Handbook
of personality: Theory and research (2nd ed., pp. 102–
138). New York: Guilford Press.
Kelley, H. H. (1971). Attribution in social interaction. Mor-
ristown, NJ: General Learning Press.
Lang, F. R., Lu¨dtke, O., & Asendorpf, J. B. (2001). Testgu¨te
und psychometrische A
quivalenz der deutschen Version
des Big Five Inventory (BFI) bei jungen, mittelalten und
alten Erwachsenen [Validity and psychometric equiva-
lence of the German version of the Big Five Inventory
(BFI) in young, middle-aged, and old adults]. Diagnos-
tica, 47, 111–121.
Larson, R. (1989). Is feeling “in control” related to happi-
ness in daily life? Psychological Reports, 64, 775–784.
Lazarus, R. S. (1966). Psychological stress and the coping
process. New York: McGraw-Hill.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and
coping. New York: Springer.
Leitner, K., & Resch, M. G. (2005). Do the effects of job
stressors on health persist over time? A longitudinal
study with observational stressor measures. Journal of
Occupational Health Psychology, 10, 18 –30.
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job
burnout. Annual Review of Psychology, 52, 397–422.
Meijman, T. F., & Mulder, G. (1998). Psychological aspects
of workload. In P. J. D. Drenth & H. Thierry (Eds.),
Handbook of work and organizational psychology (Vol.
2: Work psychology, pp. 5–33). Hove, England: Psychol-
ogy Press.
Meissner, M. (1971). The long arm of the job: A study of
work and leisure. Industrial Relations, 10, 239–260.
Mohr, G. (1986). Die Erfassung psychischer Befindensbe-
eintra¨chtigungen bei Arbeitern [Assessment of impaired
psychological well-being in industrial workers]. Frank-
furt/M.: Lang.
Muraven, M., Tice, D. M., & Baumeister, R. F. (1998).
Self-control as limited resource: Regulatory depletion
patterns. Journal of Personality and Social Psychology,
74, 774–789.
Parkinson, B., & Totterdell, P. (1999). Classifying affect-
regulation strategies. Cognition and Emotion, 13, 277–
Parkinson, B., Totterdell, P., Briner, R. B., & Reynolds, S.
(1996). Changing moods: The psychology of mood and
mood regulation. London: Longman.
Pelletier, C. L. (2004). The effect of music on decreasing
arousal due to stress: A meta-analysis. Journal of Music
Therapy, 41, 192–214.
Rook, J. W., & Zijlstra, F. R. H. (2006). The contribution of
various types of activities to recovery. European Journal
of Work and Organizational Psychology, 15, 218–240.
Rosenfield, S. (1989). The effects of women’s employment:
Personal control and sex differences in mental health.
Journal of Health and Social Behavior, 30, 77–91.
Ruderman, M. N., Ohlott, P. J., Panzer, K., & King, S. N.
(2002). Benefit of multiple roles for managerial women.
Academy of Management Journal, 45, 369 –386.
Semmer, N. (1984). Streßbezogene Ta¨tigkeitsanalyse
[Stress-oriented task-analysis]. Weinheim: Beltz.
Semmer, N. K., Grebner, S., & Elfering, A. (2004). Beyond
self-report: Using observational, physiological, and situ-
ation-based measures in research on occupational stress.
In P. L. Perrewe´ & D. C. Ganster (Eds.), Research in
occupational stress and well-being: Emotional and phys-
iological processes and positive intervention strategies
(Vol. 3, pp. 205–263). Amsterdam, NL: Elsevier.
Sluiter, J. K., Van der Beek, A. J., & Frings-Dresen,
M. H. W. (1999). The influence of work characteristics
on the need for recovery and experienced health: A study
on coach drivers. Ergonomics, 42, 573–583.
Sonnentag, S. (2001). Work, recovery activities, and indi-
vidual well-being: A diary study. Journal of Occupa-
tional Health Psychology, 6, 196 –210.
Sonnentag, S., & Bayer, U.-V. (2005). Switching off men-
tally: Predictors and consequences of psychological de-
tachment from work during off-job time. Journal of
Occupational Health Psychology, 10, 393– 414.
Sonnentag, S., & Frese, M. (2003). Stress in organizations.
In W. C. Borman, D. R. Ilgen, & R. J. Klimoski (Eds.),
Comprehensive handbook of psychology (Vol. 12: Indus-
trial and organizational psychology, pp. 453– 491).
Hoboken, NJ: Wiley.
Sonnentag, S., & Fritz, C. (2006). Endocrinological pro-
cesses associated with job stress: Catecholamine and
cortisol responses to acute and chronic stressors. In P. L.
Perrewe´ & D. C. Ganster (Eds.), Research in organiza-
tional stress and well-being: Employee health, coping
and methodologies (pp. 1–59). Amsterdam, NL: Elsevier.
Sonnentag, S., & Jelden, S. (2005). The recovery paradox:
Why we don’t exercise after stressful days. Poster pre-
sented at the conference of the Society for Industrial and
Organizational Psychology, Los Angeles.
Sonnentag, S., & Kruel, U. (2006). Psychological detach-
ment from work during off-job time: The role of job
stressors, job involvement, and recovery-related self-
efficacy. European Journal of Work and Organizational
Psychology, 15, 197–217.
Sonnentag, S., & Natter, E. (2004). Flight attendants’ daily
recovery from work: Is there no place like home? Inter-
national Journal of Stress Management, 11, 366–391.
Stone, A. A., Kennedy-Moore, E., & Neale, J. M. (1995).
Association between daily coping and end-of-day mood.
Health Psychology, 14, 341–349.
Strauss-Blasche, G., Ekmekcioglu, C., & Marktl, W.
(2002). Moderating effects of vacation on reactions to
work and domestic stress. Leisure Sciences, 24, 237–249.
Strauss-Blasche, G., Reithofer, B., Schobersberger, W., Ek-
mekcioglu, C., & Marktl, W. (2005). Effect of vacation
on health: Moderating factors of vacation outcome. Jour-
nal of Travel Medicine, 12, 94 –101.
Taris, T. W., Beckers, D., Verhoeven, L. C., Geurts,
S. A. E., Kompier, M. A. J., & van der Linden, D. (2006).
Recovery opportunities, work-home interference, and
well-being among managers. European Journal of Work
and Organizational Psychology, 15, 139 –157.
Taris, T. W., & Kompier, M. A. J. (2005). Job characteris-
tics and learning behavior. In P. L. Perrewe´ & D. C.
Ganster (Eds.), Research in occupational stress and well-
being: Exploring interpersonal dynamics (Vol. 4, pp.
127–166). Amsterdam, NL: JAI Press.
Thayer, R. E., Newman, J. R., & McClain, T. M. (1994).
Self-regulation of mood: Strategies for changing a bad
mood, raising energy, and reducing tension. Journal of
Personality and Social Psychology, 67, 910 –925.
Tinsley, H. E. A., & Eldredge, B. D. (1995). Psychological
benefits of leisure participation: A taxonomy of leisure
activities based on their need-gratifying properties. Jour-
nal of Counseling Psychology, 42, 123–132.
Totterdell, P., & Parkinson, B. (1999). Use and effective-
ness of self-regulation strategies for improving mood in
a group of trainee teachers. Journal of Occupational
Health Psychology, 4, 219 –232.
van der Klink, J. J. L., Blonk, R. W. B., Schene, A. H., &
van Dijk, F. J. H. (2001). The benefits of interventions
for work-related stress. American Journal of Public
Health, 91, 270 –276.
van Hooff, M. L. M., Geurts, S. A. E., Kompier, M. A. J.,
& Taris, T. W. (2007). Workdays, in-between workdays
and the weekend: A diary study on effort and recovery.
International Archives of Occupational and Environmen-
tal Health, 80, 599 613.
van Veldhoven, M., & Broersen, S. (2003). Measurement
quality and validity of the “need for recovery scale.”
Occupational and Environmental Medicine, 60, i3–i9.
Vohs, K. D., & Baumeister, R. F. (2004). Unterstanding
self-regulation. In R. F. Baumeister & K. D. Vohs (Eds.),
Handbook of self-regulation: Research, theory, and ap-
plication (pp. 1–9). New York: Guilford Press.
Vollrath, M., & Torgersen, S. (2000). Personality types and cop-
ing. Personality and Individual Differences, 29, 367–378.
Vrijkotte, T. G. M., Van Doornen, L. J. P., & De Geus,
E. J. C. (2000). Effects of work stress on ambulatory
blood pressure, heart rate, and heart rate variability. Hy-
pertension, 35, 880 886.
Westman, M., & Eden, D. (1997). Effects of a respite from
work on burnout: Vacation relief and fade-out. Journal of
Applied Psychology, 82, 516 –527.
Zapf, D. (1993). Stress-oriented analysis of computerized
office work. European Work and Organizational Psy-
chologist, 3, 85–100.
Zohar, D., Tzischinski, O., & Epstein, R. (2003). Effects of
energy availability on immediate and delayed emotional
reactions to work events. Journal of Applied Psychology,
88, 1082–1093.
Received May 22, 2006
Revision received November 17, 2006
Accepted November 20, 2006
... As a result, the home environment can become permeated by work outside working hours, hindering psychological detachment from work (Charalampous et al., 2022;Kinnunen et al., 2016;Sonnentag et al., 2010). Psychological detachment is a process that restores employees' energetic and mental resources consumed by demands imposed by work (Zijlstra et al., 2014) and is an essential prerequisite of effective recovery (Sonnentag and Fritz, 2007). It is. ...
... It is. While relaxation, mastery and control over leisure can also aid recovery (Sonnentag and Fritz, 2007), prior studies have identified psychological detachment as the most significant recovery experience (de Jonge et al., 2012;Sonnentag and Fritz, 2015). The essential role of psychological detachment in recovery and the threat to it posed by working from home (Charalampous et al., 2022) motivated the current study. ...
... 2.2 Psychological detachment from work in the context of remote working from home The concept of psychological detachment was initially introduced by Etzion and associates (Etzion et al., 1998) and described as "an individual's sense of being away from the work situation." Psychological detachment, also termed switching off, refers to both a physical and mental distancing from work and involves not doing work or entertaining work-related thoughts Sonnentag and Bayer, 2005;Sonnentag and Fritz, 2007;Sonnentag and Niessen, 2020). ...
Purpose This paper examines an employee's recovery process in the remote-working context. It explores which elements of remote work are energy-consuming for employees and what action they can take to instigate the essential recovery strategy of psychological detachment. Design/methodology/approach The study adopts a qualitative research approach based on 89 semi-structured interviews with employees working from home with six large corporations from multiple industries. The data were interpreted using thematic analysis. Findings The study identifies a main theme – the energy-consuming elements of remote work – and three sub-themes: extended working hours, intensive working and reduced social support. Each theme incorporates elements controlled by individuals (internal) and those beyond their control (external). Second, the authors identified strategies that helped individuals to detach from work, and devised four sub-themes, the authors labeled cognitive controlling, physical disconnection from work, time-bound routines and non-work activities. Originality/value This is the first study to focus on recovery as a process in the context of remote working, and it contributes to the knowledge of psychological detachment and strategies for recovery and to the literature on contemporary remote working.
Full-text available
Well-being conditions at work are determined by the balance between the demands from the organizational context and the perception of people to possess resources concerning the ability to cope with such requests. The pandemic caused by COVID-19 has changed working conditions, and employees have had to adapt to smart working (SW) by bringing new resources into play to meet new demands. Many organizations are questioning how to implement SW after the pandemic. According to the JD-R model, the present study considered workload during smart working and Techno-stress (the perceived stress concerning the use of technologies) as new requests (i.e., demands) coming from the organization and Psychological Detachment (the ability to create psychological distancing from work) as a personal resource. We investigated the moderator role of Psychological Detachment in the relationship between workload in SW and Well-being, mediated by Techno-stress (in its three dimensions: Techno-Overload, Techno-Invasion, and Techno-Complexity). The sample is made up of 622 Italian public administration employees who completed a questionnaire containing the following scales: Quantitative Workload Inventory, Well-being Index, Psychological Detachment, Techno-stress Creator Scale. Mediation and moderate-mediation models have been tested with PROCESS Macro. Findings showed that Techno-Invasion and Techno-Complexity fully mediate the relationship between workload in SW and well-being. Psychological detachment moderates the effect of the workload on Well-being, which in turn is mediated by Techno-Invasion. Furthermore, findings suggest the importance of identifying protective factors that can mitigate the workload effects on the employees' well-being in SW.
A lack of recovery like psychologically detaching from work can be detrimental to health. High cognitive demands may jeopardise detachment from work. Longitudinal studies concerning the long-term effects of cognitive demands on health and work ability via psychological detachment are understudied. Research has shown that social support may buffer the relationship between job demands and psychological detachment. However, the role of supervisor support was not examined specifically. We hypothesise psychological detachment to mediate the relationship between cognitive demands, general health, and work ability. Supportive or inconsiderate behaviours of a supervisor can further moderate the relationship between cognitive demands and psychological detachment. Statistical analyses were carried out with three-wave panel data from the German Federal Institute for Occupational Safety and Health with lags of two years (2015–2019) from 3,867 employees who took part in the survey. The results conveyed that mediation by psychological detachment was significant, while supervisor (non)support moderated the relationship between cognitive demands and psychological detachment only cross-sectionally. This study emphasises the role of supervisor in the stressor-detachment model and the positive effect of recovery experience on health. Therefore, in practice, the role of supervisor behaviour for employees’ psychological detachment should be addressed in management training courses.
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Indonesia's construction industry has experienced remarkable growth over the past decade, as evidenced by statistical data from 2010 to 2019. The number of companies focused on construction has surged in tandem with Indonesia's economic growth. However, this rapid growth has led to a significant discrepancy between the increasing number of staff and available companies. Such an imbalance places immense pressure on construction staff, straining their workloads and overall job satisfaction. To address this issue, a comprehensive research study was conducted employing a combination of field research and literature reviews. The research involved direct visits to the study site to gather primary data from respondents. Primary data collection methods included observations and the use of questionnaires, which probed various variables relevant to the study. Furthermore, extensive literature reviews were conducted, drawing insights from journals, articles, textbooks, and relevant government regulations. The primary objective of this research was to investigate the relationship between workload, work distress, sleep problems, and job satisfaction among employees within the construction industry. The study aimed to identify potential avenues for enhancing employee job performance by mitigating familial and sleep-related challenges. The research focused on employees working within multinational and international contractor branches, as the exact population figures were unavailable, necessitating a nonprobability sampling approach. The research employed quantitative analysis, specifically structural equation modeling (SEM), to examine the intricate connections between work-related factors and their impact on employees' well-being and job satisfaction. The findings of the study revealed both direct and indirect influences of work and family dynamics on job-related issues within the private sector. Notably, companies in the construction industry experienced heightened work pressure, attributed to their higher workload, yet also exhibited greater support from regulatory and business sectors. This research underscores the significance of distinguishing between different sectors when exploring the interplay between work and family dynamics. By shedding light on the unique challenges faced by the construction industry, this study contributes to the existing body of work-family literature, emphasizing the need for tailored approaches when analyzing work-family relationships in distinct sectors.
Purpose This study aims to investigate the impact of overnight off-work relaxation on the performance of frontline service employees (FLEs). Specifically, the authors focused on FLEs' customer-directed extra-role service behavior (C-ERSB) and coworker-directed extra-role service behavior (CW-ERSB) as indicators of outstanding service performance. Drawing on the conservation of resources (Hobfoll, 1989) and ego depletion theories (Baumeister, 2002), the authors hypothesized that the positive effect of overnight relaxation on ERSBs will be mediated by the state of recovery. Additionally, the authors examined the boundary conditions of these relationships by testing the moderating effects of work–family conflict (WFC) and family–work conflict (FWC). Design/methodology/approach The study employed an episodic sampling method. One hundred thirty-five FLEs completed two daily surveys (before- and after-work) over five consecutive workdays, yielding 636 time-lagged day-level observations. Multilevel path modeling was performed to analyze the mediation and second-stage moderated mediation effects. Findings Results showed that overnight off-work relaxation was positively related to FLEs' next-day C-ERSB and CW-ERSB via next-morning recovery state. The positive relationship between overnight off-work relaxation and the next-morning recovery state was weaker for FLEs who experienced overnight WFC. FWC during work hours weakened the positive relationship between the next-morning recovery state and CW-ERSB, but not the relationship between the next-morning recovery state and C-ERSB. Originality/value The study used an episodic sampling method to reveal the significance of off-work relaxation, recovery and family–work interface on FLEs' ERSBs, a critical yet underexplored phenomenon in service literature. This study sheds light on the pathways to achieve exceptional service performance by revealing the importance of overnight off-work relaxation and the conditions that promote ERSBs.
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Se presenta las características básicas del análisis de los recursos humanos centrado en el concepto de energía personal, así como determinadas estrategias que permitan a los trabajadores recuperar su nivel físico, mental y emocional, luego del desgaste diario al ejecutar sus funciones. Además, se indaga sobre el “Trabajo Emocional”. El documento está orientado principalmente a psicólogos y otros profesionales que proporcionen servicios a organizaciones laborales concediendo prioridad a los recursos humanos. The basic characteristics of the analysis of human resources centered on the concept of personal energy are presented, as well as certain strategies that allow workers to recover their physical, mental and emotional level, after the daily wear and tear when performing their functions. In addition, it inquires about the “Emotional Work”. The document is mainly aimed at psychologists and other professionals who provide services to labor organizations giving priority to human resources.
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This study extends previous research on respite from work and addresses the question of how individuals use their leisure time to recover from work. It is hypothesized that time spent on work-related and household activities has a negative effect on well-being, whereas low-effort, social, and physical activities are assumed to have a positive effect. One hundred Dutch teachers completed a diary on leisure time activities and situational well-being for 5 days, and work situation variables were assessed with a questionnaire. Multilevel analyses in which preleisure well-being and work situation variables were entered as control variables supported 4 of the 5 hypotheses. Moreover, a lagged effect of high time pressure on poor situational well-being was found. The study showed that leisure time activities and a low-stress work situation contribute independently to an individual's well-being. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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We examined the relationships between multiple life roles, psychological well-being, and managerial skills in two studies of managerial women. Qualitative results suggested that the roles women play in their personal lives provide psychological benefits, emotional advice and support, practice at multitasking, relevant background, opportunities to enrich interpersonal skills, and leadership practice that enhance effectiveness in the management role. Quantitative results indicated that multiple role commitment positively related to life satisfaction, self-esteem, and self-acceptance. Commitment to multiple roles was also related to interpersonal and task-related managerial skills.
In this chapter, we review empirical research evidence on the relationship between stressors and catecholamines (i.e., adrenaline and noradrenaline) and cortisol. With respect to acute stressors, both laboratory and field research have shown that the exposure to stressors leads to an increase in catecholamine and cortisol levels. With respect to more chronic stressors, research evidence is less consistent. Chronic mental workload was found to be related to elevated adrenaline levels. With respect to cortisol responses the interaction between workload and other variables seems to play a role. Empirical studies suggest that chronic stressors affect the responsivity to acute stressors. Research showed that after the exposure to stressors catecholamine and cortisol recovery is delayed.
This chapter examines employee learning behavior as a function of work characteristics. Karasek's Demand-Control (DC) model proposes that high job demands and high job control are conducive to employee learning behavior. A review of 18 studies revealed that whereas most of these supported these predictions, methodological and conceptual shortcomings necessitate further study. Perhaps the most important weakness of the DC-based research on learning is that the conceptual foundations of the DC model regarding employee learning behavior are quite rudimentary, while the role of interpersonal differences in the learning process is largely neglected. The second part of this chapter explores the relationship between work characteristics and learning behavior from the perspective of German Action Theory (AT). AT explicitly discusses how work characteristics affect learning behavior and assigns a role to interpersonal differences. We conclude by presenting a model that integrates action-theoretical insights on learning with DC-based empirical results.
This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is suited for use with different age groups, and other potential uses of the scale are discussed.
Work-family research emphasizes the importance of mechanisms that link work and family. However, these mechanisms typically are described in metaphoric terms poorly suited to rigorous research. In this article we translate work-family linking mechanisms into causal relationships between work and family constructs. For each relationship we explain its sign and causal structure and how it is influenced by personal intent. We show how these respecified linking mechanisms constitute theoretical building blocks for developing comprehensive models of the work-family interface.