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This study had two aims. First, we examined whether lunch break settings, activities, and recovery experiences were associated with lunchtime recovery cross-sectionally. Second, we investigated whether lunchtime recovery was related to energy levels (i.e., exhaustion and vigor) across a 12-month period. We collected longitudinal questionnaire data among 841 Finnish workers (59% female, mean age 47 years) from 11 different organizations in various fields at two time points (spring 2013 and 2014). We used hierarchical regression analysis to test our hypotheses. We found that recovery experiences, that is, psychological detachment from work and control during the lunch break, were related to successful lunchtime recovery. After controlling for background factors, main job characteristics (workload and autonomy), and the outcomes at baseline, successful lunchtime recovery was related to a decrease in exhaustion and to an increase in vigor one year later. To conclude, lunch breaks offer an important setting for internal recovery during working days and seem to relate to energy levels at work over time.
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Sianoja, M., et al. (2016). Recovery during Lunch Breaks: Testing Long-Term Relations
with Energy Levels at Work.
Scandinavian Journal of Work and Organizational Psychology
1(1): 7, 1–12, DOI:
* University of Tampere, FI
Radboud University Nijmegen, NL
Corresponding author: Marjaana Sianoja (marjaana.sianoja@uta.)
Recovery during Lunch Breaks: Testing Long-Term
Relations with Energy Levels at Work
Marjaana Sianoja*
, Ulla Kinnunen*
, Jessica de Bloom*
, Kalevi Korpela* and Sabine Geurts
This study had two aims. First, we examined whether lunch break settings, activities, and recovery
experiences were associated with lunchtime recovery cross-sectionally. Second, we investigated whether
lunchtime recovery was related to energy levels (i.e., exhaustion and vigor) across a 12-month period.
We collected longitudinal questionnaire data among 841 Finnish workers (59% female, mean age
47 years) from 11 dierent organizations in various elds at two time points (spring 2013 and 2014).
We used hierarchical regression analysis to test our hypotheses.
We found that recovery experiences, that is, psychological detachment from work and control during
the lunch break, were related to successful lunchtime recovery. After controlling for background factors,
main job characteristics (workload and autonomy), and the outcomes at baseline, successful lunchtime
recovery was related to a decrease in exhaustion and to an increase in vigor one year later.
To conclude, lunch breaks oer an important setting for internal recovery during working days and seem
to relate to energy levels at work over time.
Keywords: lunch breaks; recovery; detachment; control; exhaustion; vigor
Recovery from work stress, that is, psycho-physiological
unwinding after effort expenditure at work that restores
employees’ energy and mental resources, is a mechanism
explaining how employees can protect their well-being
and health in demanding working conditions (Craig &
Cooper, 1992; Geurts & Sonnentag, 2006; Meijman &
Mulder, 1998). Recovery plays an intervening role in the
relationship between stressful job characteristics and the
development of chronic load reactions, such as prolonged
fatigue, sleep disorders, and cardiovascular diseases
(Geurts & Sonnentag, 2006). Therefore, a more profound
understanding of recovery processes is essential in pro-
moting sustainable working life.
Recovery occurs during breaks from work when job
demands are no longer present (Meijman & Mulder,
1998). Different forms of breaks range from sabbaticals
and vacations to short micro-breaks within the working
day. Recovery within working days, referred to as internal
recovery, has received far less attention in the recovery
research literature than off-job recovery, referred to as
external recovery (Sonnentag & Fritz, 2015). Although
recovery during breaks within the working day may not
be as self-evident as recovery during leisure time, internal
recovery has potential in preventing stress from
accumulating early on, helping to maintain perfor-
mance throughout the day and preventing high need for
recovery at the end of the working day (Coffeng, van Sluijs,
Hendriksen, van Mechelen, & Boot, 2015; Geurts, Beckers, &
Tucker, 2014).
As workers typically spend a third to a half of their day
at the workplace it is important to recognize the recovery
potential of within working day breaks, and especially of
the lunch break, which is typically the longest and most
common of breaks in the course of the working day.
Furthermore, organizations have a greater opportunity
to influence employees’ internal recovery than external
recovery and, therefore, lunch breaks as a recovery set-
ting may be of special interest to employers. For example,
organizations may encourage regular lunch breaks and
provide restorative environments (e.g., quiet rooms for
relaxation). The question of how to recover successfully
during lunch breaks has recently gained some research
attention (Brown, Barton, Pretty, & Gladwell, 2014;
Krajewski, Wieland, & Sauerland, 2010; Trougakos, Hideg,
Cheng, & Beal, 2014). Nevertheless, research on internal
recovery is still scarce (Sonnentag & Fritz, 2015).
In this study we examine which lunchtime settings,
activities, and recovery experiences are related to lunch-
time recovery (i.e., how often employees recuperate
successfully from work during lunch breaks) in a cross-
sectional sample (Study 1). Furthermore, we test whether
lunchtime recovery is related to energy levels at work, that
is, exhaustion and vigor, over a 12-month period (Study 2).
Our study contributes to the literature on work stress
Sianoja et al: Lunchtime Recovery and Long-Term OutcomesArt. 7, page 2 of 12
recovery by extending the understanding of how to pro-
mote internal recovery and exploring its relation with
maintaining energy at work. Figure 1 presents the model
of the study with hypothesized relationships.
Recovery during lunch break: Theoretical and
empirical perspectives
In the effort-recovery (E-R) model (Meijman & Mulder,
1998) recovery has been defined as a process of the
psycho-biological system returning to its pre-stressor
level. Recovery occurs when the demands causing strain
are no longer present (Meijman & Mulder, 1998). When
recovery is insufficient, an individual has to invest addi-
tional effort at work, which may cause strain and lead to
accumulating strain reactions in the long term. Recovery
therefore plays a significant role in counteracting
strain caused by job demands and helps in maintaining
well-being and energy at work.
Besides seeing recovery as a passive process (i.e., caused
by mere absence of demands), active perspectives on
recovery have also been introduced. According to conser-
vation of resources (COR) theory (Hobfoll, 2002; Hobfoll,
1989), people are motivated to gain new resources and
protect their existing resources. Resources are defined
broadly as “objects, personal characteristics, conditions,
or energies that are valued by the individual” (Hobfoll,
1989, p. 516). When resources are lost, threatened with
loss, or new resources are not gained after effort invest-
ment, strain occurs. During breaks from work, people
have the opportunity to engage in pleasant activities
and to regain resources (e.g., energy and positive mood).
Thus, to recover during a break, a break must ensure
absence of job demands and provide an opportunity for
employees to regain valued resources (Hobfoll, 2002;
Meijman & Mulder, 1998). This also implies that breaks
should be regular and long enough to allow enough time
for recovery.
Additionally, break location (the place where the break
is spent), break activities, and experiences during the
break may influence its recovery potential as they are
closely related to the absence of job demands and oppor-
tunities for resource gain. These aspects have been argued
(Sonnentag & Natter, 2004) and shown (Sonnentag &
Fritz, 2015; Sonnentag & Zijlstra, 2006; van Hooff & Baas,
2013) to be of importance in terms of recovery during lei-
sure time. Some of these (e.g., activities) have also been
identified in earlier research as important aspects of inter-
nal recovery (see Sianoja, Kinnunen, De Bloom, & Korpela,
When looking at recovery research on where breaks
are spent, a recent 5-day diary study found no difference
between spending breaks inside or outside the office in
terms of resource recovery (Hunter & Wu, 2016). However,
in this study carried out among 95 university staff mem-
bers, the outside condition also included different spaces
inside the office building (e.g., a break room), which may
not offer as beneficial conditions for detachment from
work as spaces outside the office building (e.g., a café or
restaurant). Other studies have been specifically interested
in natural environments. According to an intervention
study by Brown et al. (2014), spending one’s lunchtime
walking in a natural environment was beneficial in terms
of improved mental health when compared to walking in
built environments. Accordingly, this study suggests that
Figure 1: Model of the study.
Sianoja et al: Lunchtime Recovery and Long-Term Outcomes Art. 7, page 3 of 12
break location may be significant in terms of recovery.
To conclude, spending the lunch break outside the office
building should, in theory, aid recovery, as it ensures
better mental detachment from work offering a “change
of scenery” where job demands are not present (e.g.,
Korpela, De Bloom, & Kinnunen, 2015).
Concerning break activities, earlier studies on internal
recovery have associated relaxing, physical, and social
activities with positive recovery outcomes (Coffeng
et al., 2015; Krajewski et al., 2010; Trougakos et al., 2014).
Of these, we focused on social activities. Wendsche
et al. (2014) showed that collective rest breaks (i.e., breaks
including social activities) were associated with less
turnover than breaks spent alone. In addition, a study by
Trougakos et al. (2014) focusing on different lunch break
activities revealed that social activities that were based on
individuals’ own choice, were conducive to recovery.
In sum, in addition to absence of job demands, as sug-
gested by the E-R model, earlier research shows that
recovery may be also enhanced by engaging in activities
that enable resource replenishment, as suggested by the
COR theory.
Hypothesis 1: a) Having lunch breaks regularly, b) hav-
ing longer lunch breaks, c) spending lunch breaks outside
the office building and d) spending lunch breaks with oth-
ers are positively associated with recovery during lunch
Furthermore, it has been argued that a recovering
break should promote recovery experiences (Coffeng
et al., 2015; Trougakos et al., 2014). According to
Sonnentag and Fritz (2007), there are four such mecha-
nisms: psychological detachment, relaxation, mastery,
and control. Of these, we examined detachment, that is,
not thinking about work, and control, that is, getting to
choose how to spend one’s free time (e.g., lunch breaks).
These two experiences were chosen as they have gained
most support in earlier studies. In studies focusing on
recovery during leisure time, detachment has been
identified as a core recovery experience (Sonnentag &
Fritz, 2015). Psychological detachment from work, in
addition to physical detachment, is crucial, as continuing
to think about job demands during breaks may result
in strain (Sonnentag & Fritz, 2007). In fact, in a cross-
sectional study detachment during work breaks was
connected to less need for recovery at the end of the
day (Coffeng et al., 2015). Furthermore, autonomy (i.e.,
control) during lunch breaks has previously been linked
to beneficial outcomes (Trougakos et al., 2014). More
specifically, autonomy during lunch breaks was recog-
nized as a moderator between lunch break activities and
recovery outcomes: autonomy strengthened the positive
effects of the activities. In addition, preferred work break
activities have been associated with increased resources
after the break (Hunter & Wu, 2016). Therefore break
characteristics that enhance psychological detachment
from work and allow control, may provide beneficial
setting for recovery.
Hypothesis 2: Recovery experiences (detachment and
control) during lunch breaks are positively associated with
recovery during lunch breaks.
Long-term associations between lunchtime recovery
and energy levels at work
As long-term outcomes of recovery we focused on energy,
specifically on exhaustion and vigor at work. According to
the E-R model (Meijman & Mulder, 1998), when recovery
is insufficient, high and continuous demands lead to nega-
tive load effects and depletion of energy, which in the long
term can lead to emotional exhaustion. Emotional exhaus-
tion is one of the core burnout dimensions and refers to
“feelings of being overextended and depleted of one’s
emotional and physical resources” (Maslach, Schaufeli, &
Leiter, 2001, p. 399). Research has shown that emotional
exhaustion predicts mental and physical illness, such as
depression and cardiovascular diseases (Ahola, 2007),
as well as increased sickness absence (Toppinen-Tanner,
Ojajärvi, Väänänen, Kalimo, & Jäppinen, 2005).
Hunter and Wu (2016) found that resource recovery
during workday breaks across one working week was asso-
ciated with lower levels of exhaustion at the end of the
week. As far as we know, the long-term effects between
poor recovery during lunch breaks and exhaustion have
not yet been examined. However, over time employees go
through numerous cycles of daily lunchtime recovery pro-
cesses, which may ultimately result in either gain or loss
of energy depending on whether recovery is successful
or incomplete. Therefore, insufficient recovery may, over
time, result in cumulative resource loss in terms of higher
Hypothesis 3: Insufficient recovery during lunch
breaks is related to high level of emotional exhaustion
over time.
In contrast, successful recovery ensures that energy
levels are sufficient for people to experience vigor at
work (Meijman & Mulder, 1998). Vigor is one of the core
dimensions of work engagement and is characterized
by high activation, energy, and mental resilience while
working (Schaufeli, Salanova, González-Romá, & Bakker,
2002). Work engagement, and particularly vigor, has been
shown to be important in terms of motivation and perfor-
mance at work (Bakker, Demerouti, & Sanz-Vergel, 2014).
It has also been shown that exhaustion and vigor are
not endpoints of the same energy construct (Demerouti,
Mostert, & Bakker, 2010; Mäkikangas, Feldt, Kinnunen, &
Tolvanen, 2012). Thus we cannot conclude that absence
of exhaustion automatically implies high levels of vigor. It
is therefore important to measure both when examining
the energy levels of individuals.
To the best of our knowledge, studies on internal
recovery and its relation to vigor are so far lacking.
However, on a daily level taking micro-breaks at work has
been associated with vitality, a concept related to vigor
(Zacher, Brailsford, & Parker, 2014). Furthermore, earlier
research has established a positive link between external
recovery and work engagement (Kühnel, Sonnentag, &
Westman, 2009; Sonnentag, 2003). If recovery is repeatedly
insufficient during lunch breaks, it may lead to loss of
energy and over time reduce vigor. In addition, recovery is
associated with resource gain (e.g., energy), and resources
tend to accumulate and generate other resources in
the long term (Hobfoll, 2002). Accordingly, successful
Sianoja et al: Lunchtime Recovery and Long-Term OutcomesArt. 7, page 4 of 12
recovery during lunch breaks may result in energy gain,
resulting in higher levels of vigor over time.
Hypothesis 4: Successful recovery during lunch breaks is
related to high level of vigor over time.
Participants and Procedure
The data were collected as a part of larger project on
recovery from work (see Kinnunen et al., 2016). The par-
ticipants of this study were Finnish employees working in
11 different organizations in various fields, mostly work-
ing in cognitively or emotionally demanding jobs. The
most common fields were education, information tech-
nology, and media. The questionnaire data were collected
in two phases. First, in spring 2013 (Time 1), an electronic
questionnaire was sent either directly to the employees’
work e-mail addresses (in seven organizations) or the
link to the questionnaire was delivered to the employees
by our contact persons (in four organizations). Of the
employees contacted (N = 3,593), 1,347 returned the
completed questionnaire after two reminders, yielding a
response rate of 37.5%. Second, in spring 2014 (Time 2)
the electronic questionnaire was sent to those employees’
e-mail addresses who responded in 2013 and who were
still employed in the same organizations (N = 1,192). Of
these, a total of 841 employees returned the completed
questionnaire, yielding a response rate of 70.6%. In
both study phases the employees were informed about
the goals of the study, assured that responses would be
treated confidentially and reminded that participation
was voluntary.
In Study 1, we used the cross-sectional sample col-
lected at T2, because not all variables (i.e., spending lunch
breaks outside, spending breaks with others, lunchtime
detachment, and lunchtime control) were measured at
T1. A cross-sectional design was considered appropriate
because we were interested in the immediate relations of
break settings, activities, and experiences with lunchtime
recovery. Study 2 was based on the longitudinal sample
covering both measurements with a 12-month time lag
between the measurements. It is difficult to theoretically
determine the most appropriate time lag as we lack the-
ories of change, and therefore even descriptive research
on the time courses of important relationships has been
recommended (Kelloway & Francis, 2013). We consider
one year to be an appropriate time lag, as it is so far the
most typical time period used in earlier recovery stud-
ies showing long-term effects (Kinnunen & Feldt, 2013;
Siltaloppi, Kinnunen, Feldt, & Tolvanen, 2011; Sonnentag,
Binnewies, & Mojza, 2010). Additionally, the reality of
data collection in organizations imposed certain limita-
tions. We were not able to schedule measurements more
frequently because we had to consider the organizations’
wishes and time constraints.
Of the sample used in both studies (N = 841), 58.6%
were women. The participants’ average age was 47.1 years
(range 21–67, SD = 10.0). Most of the participants (76.4%)
were living with a partner (either married or cohabit-
ing), and 45.6% had children (average of two) living at
home. Of the sample, 38.2% held a university degree
(master’s level or higher), 26.6% had a polytechnic degree,
and the rest (35.2%) had a vocational school qualification
or less. Of the participants, 8.3% were blue-collar workers
(e.g., cleaners), 30.0% lower white-collar workers
(e.g., office workers), 57.8% senior white-collar workers
(e.g., teachers) and 3.8% senior-level managers (e.g., chief
executive officers). The majority had a permanent job
(89.0%), worked full-time (96.8%) and had a regular day
shift (89.7%). Average weekly working hours were 39.1
(SD = 5.9). Of the participants, 53.6% worked in the public
sector as teachers or administrative staff in vocational or
upper secondary schools, or in a polytechnic (university of
applied sciences). The rest (46.4%) worked in the private
sector in various jobs.
In analyzing sample attrition we compared the respond-
ents (n = 841) of the longitudinal sample with the non-
respondents. The results indicated that the respondents
did not differ from the non-respondents in terms of gen-
der, age, having a partner, number of children or level of
education. They also did not differ in terms of the study
variables measured at both time points (regularity of
taking lunch breaks, lunch break length, lunchtime recov-
ery, exhaustion, or vigor). However, the respondents were
more often employed as senior white-collar workers (58%
vs. 50%) than the non-respondents (p < .05) and more
often on a permanent job contract (89% vs. 79%) than the
non-respondents (p < .001). Also, the respondents worked
more hours per week (39.1 vs. 37.9 hours, p < .01) and
more often on regular day shifts (90% vs. 83%, p < .01)
than the non-respondents. As we used the data collected
at T2 in our cross-sectional study, this sample attrition
concerns both Study 1 and Study 2.
Recovery during lunch breaks
To measure the degree of recovery during lunch breaks
at T1 and T2, we used one item “I recuperate from work
during my lunch break” from the Recovery after Breaks
Scale (Demerouti, Bakker, Sonnentag, & Fullagar, 2012)
aiming to capture specifically how well and regularly
employees recover during their lunch breaks. The item
was rated on a scale from 1 (very seldom or never) to 5
(very often or always). Earlier studies have provided sup-
port for the validity of single item measures (e.g., Drolet &
Morrison, 2001; Elo, Leppänen, & Jahkola, 2003). Con-
cerning recovery, it has been shown that recovery
from work measured with one item correlated highly
with longer recovery scales, such as need for recovery
(Kinnunen, Feldt, Siltaloppi, & Sonnentag, 2011).
Break settings, activities and experiences
Of break settings and activities, we measured regularity of
lunch breaks [dichotomized to 0 = occasionally (1–3 times
a week), 1 = regularly (4–5 times a week)] and length of
the lunch break (in minutes). Those participants (n = 36 at
T1 and n = 32 at T2) who reported not taking lunch breaks,
were not asked to answer any further lunch break related
questions (recovery during lunch break, break activities,
or experiences) and as lunch break recovery was the main
focus in our study, they were excluded from the analyses.
Sianoja et al: Lunchtime Recovery and Long-Term Outcomes Art. 7, page 5 of 12
In addition at T2, we asked whether the employees
habitually spent their lunch breaks outside the office
building [“I spend my lunch break outside my company
building (e.g., in a restaurant or in a café)”] or with others
[“I spend my lunch break with others (e.g., with colleagues,
acquaintances, friends or family members)”]. The answers
were dichotomized [0 = no (hardly ever or once a week),
1 = yes (2–5 times a week)].
Of recovery experiences, we measured detachment and
control during lunchtime at T2. Both detachment and
control were measured with one item (respectively: “I dis-
tance myself mentally from my work during lunch breaks”
and “I decide myself how to spend my lunch breaks”)
from the Finnish version of the Recovery Experience
Questionnaire (Kinnunen et al., 2011; Sonnentag & Fritz,
2007). The items were adapted to concern lunch breaks
and measured on a scale from 1 (very seldom or never) to
5 (very often or always).
Potential long-term outcomes
Emotional exhaustion was measured at T1 and T2 with
the five-item scale (e.g., “I feel emotionally drained from
my work”) from the Maslach Burnout Inventory (Kalimo,
Hakanen, & Toppinen-Tanner, 2006; Maslach, Jackson, &
Leiter, 1996) with response options on a seven-point
response scale from 0 (never) to 6 (every day). The Cron-
bach’s alphas were .93 at T1 and .93 at T2.
Vigor was measured at T1 and T2 with the three-item
shortened scale (e.g., “At my work, I feel bursting with
energy”) from the Utrecht Work Engagement Scale
(Schaufeli, Bakker, & Salanova, 2006) using a seven-point
response scale ranging from 0 (never) to 6 (every day). The
Cronbach’s alphas were .89 at T1 and .90 at T2.
Control variables
Of the background factors, we controlled for age (in years),
gender (1 = woman, 2 = man) and working hours per week,
as these may play a role in recovery (e.g., Mohren, Jansen, &
Kant, 2010; Siltaloppi et al., 2011). Working hours were
measured with a single question: “How many hours do
you actually work per week? (Include paid and unpaid
overtime, but not your commuting time)”.
We also controlled for main job characteristics, namely
workload and autonomy, measured at T1 and T2 as they
may act as confounding variables in our study. First,
appropriate job design may above all promote internal
recovery (Geurts et al., 2014) as it enables the employees
to adjust their work according to their current need for
recovery. Furthermore, job demands and resources play a
pivotal role in maintaining energy as job demands may
start a health deteriorating process leading to exhaustion,
and job resources, in turn, to a health promoting pro-
cess leading to an increase in vigor (Bakker et al., 2014).
Workload was measured with three items (e.g., “How
often does your job require you to work under time pres-
sure?”, Cronbach’s alphas .88 at T1 and .87 at T2) from the
Quantitative Workload Inventory (Spector & Jex, 1998).
Autonomy was measured with five items (e.g., “I can influ-
ence decisions that are important for my work”, Cronbach’s
alphas .77 at T1 and .78 at T2) from the QPS Nordic-ADW
(Dallner et al., 2000). All job characteristics were meas-
ured with a five-point scale from 1 (very seldom or never)
to 5 (very often or always).
In both studies (Studies 1 and 2), we used hierarchical
regression analyses to test our hypotheses. In the cross-
sectional Study 1 lunchtime recovery served as a depend-
ent variable. At the first step, we added the control vari-
ables (age, gender, weekly working hours, workload, and
autonomy). At the second step we added variables describ-
ing lunch break settings and activities (regularity of the
lunch breaks, length of the lunch break, break outside,
and with others). Finally, at the third step we added recov-
ery experiences (detachment and control) during lunch
In the longitudinal Study 2, we followed similar steps
with both outcomes (exhaustion and vigor). At the first
step, we controlled for the outcome at Time 1. At the sec-
ond step, we added control variables (age, gender, weekly
working hours, workload, and autonomy). Lunchtime
recovery at Time 1 was added at the final step, as we were
interested in its explanatory power after controlling for
the outcome at Time 1, background factors and work
Descriptive results
Means, standard deviations, and zero-order correlations of
the study variables are presented in Table 1 (Study 1) and
Table 2 (Study 2). We first looked at the frequencies of
lunch break characteristics examined in Study 1, in which
all variables were measured at T2. To have a regular lunch
break was common in our sample, as 86% of the partici-
pants reported taking a lunch break 4–5 times a week. Of
those participants who took lunch breaks at least once a
week, 37% reported habitually spending the break out-
side the office building and 71% with other people. In
Study 1, of the lunch break settings and activities, regular
lunch breaks (r = .21), longer lunch breaks (r = .16), breaks
outside the office building (r = .17), and breaks with oth-
ers (r = .08) showed positive associations with lunchtime
recovery. However, both recovery experiences – detach-
ment and control – during lunch breaks showed the
strongest correlations: high level of detachment (r = .59)
and control (r = .30) during lunch breaks were associated
with successful lunchtime recovery. In addition, of the
control variables, workload was negatively (r = .12) and
autonomy positively (r = .33) associated with recovery dur-
ing lunch breaks.
In Study 2 there were significant longitudinal correla-
tions between lunchtime recovery and both potential
long-term outcomes (Table 2). Lunchtime recovery at T1
was negatively related to exhaustion at T2 (r = .35) and
positively related to vigor at T2 (r = .36). Of the control var-
iables gender (female), long weekly working hours, high
workload and low autonomy were related to exhaustion at
T2, and gender (female) and high level of autonomy were
related to vigor at T2. In addition, lunchtime recovery
(r = .48) and both outcomes (r = .69 for exhaustion and
Sianoja et al: Lunchtime Recovery and Long-Term OutcomesArt. 7, page 6 of 12
M / % SD 1 2 3 4 5 6 7 8 9 10 11
1. Lunchtime recovery 3.42 0.97
2. Age 48.13 10.02 .04
3. Gender158.6% – .03 .04
4. Weekly working hours 38.65 5.90 .03 .06 .07*
5. Workload 3.82 0.79 .12*** .07 .15*** .27***
6. Autonomy 3.20 0.80 .33*** .06 .16*** .05 .24*** –
7. Regularity of lunch breaks286.2% .21*** .13*** .04 .04 .05 .10**
8. Length of lunch break 29.02 8.55 .16*** .05 .11** .02 .05 .06 .08*
9. Lunch break outside336.9% – .17*** .04 .11 ** .12** .08* .14*** .15*** .15***
10. Lunch break with others471.4% .08* .09** .13*** .03 .02 .05 .21*** .07* .12**
11. Detachment at lunch break 3.33 1.06 .59*** .01 .01 .09* .16*** .18*** .21*** .18*** .19*** .03
12. Control at lunch break 4.27 0.96 .30*** .03 .11** .03 −.05 .38*** .05 .19*** .22*** .05 .24***
Table 1: Means, standard deviations, and zero-order correlations of the study variables in Study 1.
Note. 1Gender: 1 = female, 2 = male; 2Regularity of lunch breaks: 0 = occasionally (1–3 times a week), 1 = regularly (4–5 times a week); 3Break outside: 0 = no (hardly ever or once
a week), 1 = yes (2–5 times a week); 4Break with others: 0 = no (hardly ever or once a week), 1 = yes (2–5 times a week).
The second column shows percentages for categorical variables: 1 % of female participants; 2 % of participants taking lunch breaks regularly; 3 % of participants typically spending
lunch breaks outside; 4 % of participants typically spending lunch breaks with others.
* p < .05; ** p < .01; *** p < .001; 807 < N < 841.
Sianoja et al: Lunchtime Recovery and Long-Term Outcomes Art. 7, page 7 of 12
M / % SD 1 2 3 4 5 6 7 8 9
1. Lunchtime recovery T1 3.39 1.00
2. Age T1 47.13 10.02 .08*
3. Gender158.6% – .01 .04
4. Weekly working hours T1 39.09 5.94 .09* .01 .06
5. Workload T1 3.89 0.82 .16*** .03 .16*** .28***
6. Autonomy T1 3.18 0.82 .30*** .08* .16*** .05 .30***
7. Exhaustion T1 1.92 1.45 .41*** .04 .11** .12** .36*** .35***
8. Vigor T1 4.53 1. 21 .43*** .01 .06 .05 .01 .26*** −.45***
9. Exhaustion T2 1.92 1.41 .35*** .02 .15*** .08* .31*** .30*** .69*** .35***
10. Vigor T2 4.37 1.32 .36*** .00 .09** .07 .04 .19*** .37*** .68*** −.45***
Table 2: Means, standard deviations, and zero−order correlations of the study variables in Study 2.
Note. 1Gender: 1 = female, 2 = male.
The second column shows percentages for categorical variables: 1 % of female participants.
* p < .05; ** p < .01; *** p < .001; 785 < N < 841.
r = .68 for vigor) were relatively stable between T1 and T2.
No mean level changes occurred in lunchtime recovery or
exhaustion between T1 and T2. However, vigor was signifi-
cantly lower at T2 than at T1 (p < .001).
Testing the hypotheses
Study 1
The results of the hierarchical regression analysis con-
cerning the associations between lunch break settings,
activities, recovery experiences, and lunchtime recovery
are shown in Table 3. At step 1, control variables (back-
ground variables and job characteristics) explained 12%
of the variance in lunchtime recovery and autonomy at
work significantly contributed to lunchtime recovery.
Regular lunch breaks, longer lunch breaks and habitu-
ally spending lunch breaks outside the office building
contributed to successful lunchtime recovery, increas-
ing the explanation rate of the model to 17%. Spend-
ing lunch breaks with others did not contribute to
lunchtime recovery. After adding recovery experience
variables to the model at step 3, only regularity of the
lunch breaks (of the lunchtime characteristics entered at
step 2) continued to be associated with lunchtime recov-
ery. Both detachment and control were positively related
to recovery, and they raised the explanation rate of the
model to 41%. Detachment (β = .51, p < .001) predicted
lunchtime recovery more strongly than control (β = .09,
p < .01).
In sum, Hypothesis 1 was partially supported, as most
of the positive effects of lunchtime settings and activities
disappeared when lunchtime recovery experiences were
entered into the model. More specifically, Hypothesis 1a
was fully supported, as taking lunch breaks regularly con-
tributed to successful lunchtime recovery. Hypotheses
1b and 1c were partially supported, as longer lunch
breaks and spending breaks outside were only significant
before recovery experiences were entered into the model.
Hypothesis 1d did not receive support, as spending
lunch breaks with others did not contribute to recovery.
Furthermore, Hypothesis 2 was fully supported, as both
high levels of detachment and control during lunch break
contributed to successful lunch break recovery.
Study 2
The results of hierarchical regression analyses exploring
the longitudinal relationships of lunchtime recovery with
exhaustion and vigor are shown in Table 4. Concerning
exhaustion, at step 1, exhaustion at T1 strongly predicted
exhaustion at T2 explaining 47% of the variance. At the
second step, adding the control variables, the explanation
rate of the model increased by 1 %, as gender (female)
was significantly related to exhaustion. At the final
step, lunchtime recovery at T1 contributed significantly
(β = .07) to exhaustion at T2. The increase in the explana-
tion rate was significant, although it increased only 0.3%.
The explanation rate of the final model was 48%. Thus,
in line with Hypothesis 3, successful recovery at lunch
breaks seems to explain – to a minor degree – a decrease
in exhaustion across one year.
In the model predicting vigor, at step 1, vigor at T1
strongly predicted vigor at T2 explaining 47% of the
variance. At the second step, adding the control variables
neither background factors nor job characteristics were
significant predictors of vigor. At the final step, lunchtime
recovery at T1 contributed significantly (β = .10) to vigor
at T2 and added 1% to the explanation rate. The explana-
tion rate of the final model was 48%. Thus, in line with
Hypothesis 4 successful recovery at lunch breaks seems to
explain – to a minor degree – an increase in vigor across
one year.
This study had two main aims. First, we investigated
whether certain lunch break settings, activities, and expe-
riences were related to recovery during lunch breaks.
Second, we examined whether lunchtime recovery was
associated with energy levels at work one year later. We
based our study on the E-R model and the COR theory.
Sianoja et al: Lunchtime Recovery and Long-Term OutcomesArt. 7, page 8 of 12
Lunchtime recovery
Step 1 Step 2 Step 3
Predictors β β β
Age .06 .09* .06*
Gender1.03 .04 .03
Weekly working hours .04 .05 .00
Workload .04 .04 .01
Autonomy .33*** .30*** .22***
Regularity of lunch breaks2.15*** .07*
Length of lunch break .11** .03
Lunch break outside3.11** .01
Lunch break with others4−.00 .02
Detachment at lunch break .51***
Control at lunch break .09**
ΔR2.12*** .06*** .24***
R2.12*** .17*** .41***
Table 3: Results of hierarchical regression analysis for lunchtime recovery (Study 1), N = 774.
Note. 1Gender: 1 = female, 2 = male; 2Regularity of lunch breaks: 0 = occasionally (1–3 times a week), 1 = regularly
(4–5 times a week); 3Break outside: 0 = no (hardly ever or once a week), 1 = yes (2–5 times a week); 4Break with others:
0 = no (hardly ever or once a week), 1 = yes (2–5 times a week).
* p < .05; ** p < .01; *** p < .001.
Model 1 Model 2
Exhaustion Vigor
Step 1 Step 2 Step 3 Step 1 Step 2 Step 3
Predictors at T1 β β β β β β
Dependent variable at T11.68*** .65*** .63*** .69*** .68*** .64***
Age T1 .04 .03 .03 .04
Gender2.07* .07* .05 .05
Weekly working hours T1 .02 .02 .04 .05
Workload T1 .05 .06 .02 .03
Autonomy T1 .03 .02 .03 .01
Lunchtime recovery T1 .07* .10**
ΔR2.47*** .01** .003* .47*** .01 .01**
R2.47*** .48*** .48*** .47*** .48*** .49***
Table 4: Results of hierarchical regression analysis for exhaustion (Model 1) and vigor (Model 2) at T2 (Study 2), N = 745.
Note. 1Dependent variable at T1: For the first model Exhaustion at T1, for the second model Vigor at T1. 2Gender: 1 = female,
2 = male.
* p < .05; ** p < .01; *** p < .001.
Among our sample of Finnish workers, having lunch
breaks was common, as 86% of the participants took them
4–5 times a week. On average, the participants felt occa-
sionally recovered after their lunch breaks and no changes
in this regard were observed across one year. In line with
our expectations, of the break settings or activities, regu-
larity of the lunch breaks, length of the lunch break and
spending lunch breaks outside the office contributed to
successful lunchtime recovery. Thus, our study supports
the importance of taking regular lunch breaks. However,
associations between break length and breaks outside
were no longer significant after taking recovery experi-
ences into account. As expected, we found that higher
levels of detachment and control during lunch breaks
were related to more successful lunchtime recovery. This
finding concurred with earlier research on internal recov-
ery (Coffeng et al., 2015; Trougakos et al., 2014). In light
of our results, it seems that detachment is more mean-
ingful in terms of lunchtime recovery than control. This
is logical, as detachment ensures total absence of job
Sianoja et al: Lunchtime Recovery and Long-Term Outcomes Art. 7, page 9 of 12
demands, whereas employees with high level of control
may still choose to engage, for example, in discussing
work issues. Our result therefore extends the earlier find-
ing that detachment from work is a powerful recovery
experience during non-work time (Sonnentag & Fritz,
2015). However, our one-item measure for control did not
necessarily capture all dimensions of control as a recovery
experience, for example control over when to take lunch
breaks (cf. Sonnentag & Fritz, 2007). The measure used
may therefore have underestimated the importance of
control during breaks. We recommend future studies to
assess recovery experiences at lunchtime with multiple
items to capture their full meaning.
Both taking longer lunch breaks and habitually spend-
ing breaks outside the workplace premises were corre-
lated with higher levels of detachment. Thus our results
suggest that lunch break length and spending lunch
breaks outside the office building may matter for lunch-
time detachment, which in turn relates to lunchtime
recovery. We recommend that future studies, with longi-
tudinal designs enabling appropriate mediation analysis,
test whether lunchtime recovery experiences mediate the
effects of lunchtime settings and activities on recovery.
One earlier study found that spending the break inside
versus outside one’s office (outside = in the same build-
ing or outside the building) did not have an effect on
recovery after breaks during the working day (Hunter &
Wu, 2016). As our results suggest that where lunch
breaks are spent could matter, it is important to note that
our measure (outside = outside the office building) was
different from the one used by Hunter and Wu (2016).
Therefore we suggest that future studies use more com-
prehensive measures in differentiating where breaks are
spent to disentangle these differing results. For example,
spending breaks in the break room of the department
could have different recovery outcomes from spend-
ing breaks outside the office building in a restaurant.
Furthermore, our outside condition was quite general,
and did not take specific recovery enhancing environ-
mental factors (e.g., natural settings) into account. Given
that natural settings are more likely to afford restorative
experiences than are built environments, comparing
them would be a good option for future studies (Brown
et al., 2014).
Furthermore, in our study, spending the lunch breaks
with others was not associated with recovery. This is
surprising, as earlier research suggests that breaks
including social activities are more beneficial for recovery
than breaks spent alone (Wendsche et al., 2014).
However, earlier research has also suggested that social
activities are more beneficial when based on one’s
own choice (Trougakos et al., 2014). Our study took
no account of this issue, which may explain our non-
significant finding. Additionally, we did not distinguish
between spending the break with colleagues and spend-
ing the break with other people, like friends and family.
This may be important, as in theory spending the lunch
break with friends or family may relate to more success-
ful detachment from work than spending the break with
colleagues. Therefore we recommend that future stud-
ies take into account whether social activities are based
on employees’ own choice and with whom employees
spend their breaks.
When looking at lunchtime recovery and its long-term
relationship with energy levels, we found that successful
lunchtime recovery was associated with less exhaustion
one year later, as expected. Although the effects we found
were small, it is worth noting that this relationship was
still valid after controlling for baseline level of exhaustion
and several controls. Thus successful lunchtime recovery
explained a minor decrease in exhaustion in the long
term. Our findings lend tentative support to our expec-
tations derived from the E-R model: insufficient recovery
during lunch breaks is related to loss of energy. When
this loss of energy accumulates over time due to repeated
episodes of insufficient recovery, it may partly explain
increased levels of exhaustion. Furthermore, our result
is in line with the conclusions of earlier studies linking
internal recovery with less exhaustion in the short term
(Hunter & Wu, 2016).
Similarly, the connection between lunchtime recovery
and vigor was supported. Successful recovery was related
to a minor increase in vigor one year later after controlling
for baseline level of vigor and several other controls. These
findings tentatively support our expectations derived
from the E-R and COR theories that successful recovery
prevents energy loss and increases internal resources
(e.g., energy). When lunchtime recovery is repeatedly
successful, it accumulates and generates new resources
across time, relating to a small increase in vigor. As the
levels of exhaustion and vigor at work were reasonably
stable over one year (i.e., the T1 level explained about half
of their variance at T2), our findings estimating the long-
term change in energy levels due to lunchtime recovery
can be considered promising. Taken together, lunchtime
recovery seems to be of importance in terms of energy at
work over time.
Limitations, strengths, and suggestions for future
This study has certain limitations that should be consid-
ered. First, choosing the best time lag for studying lon-
gitudinal relations between internal recovery and energy
is not self-evident and the one-year time lag used in our
study is debatable. Our results explained variation in
energy levels only to a minor degree. The effects would
likely be stronger if more frequent measures over shorter
time lags (e.g., every couple of months) were applied.
Future research may benefit from testing similar long-
term effects with more frequent measurements over dif-
ferent time spans. Nevertheless, our longitudinal analysis
supported long-term relationships between lunchtime
recovery, exhaustion and vigor, supporting the view that
employees’ degree of recovery during their lunch breaks
may have significance, not only on a daily level, but also
in the long-term.
Second, although previous studies have demonstrated
one item measures to be valid substitutes for longer
scales (Drolet & Morrison, 2001; Elo et al., 2003; Fisher,
Matthews, & Gibbons, 2016; Kinnunen et al., 2011) future
research may benefit from using multiple item measures
for lunchtime recovery and recovery experiences. Third,
Sianoja et al: Lunchtime Recovery and Long-Term OutcomesArt. 7, page 10 of 12
a further limitation concerning the measures is that our
study relies solely on self-report measures and may there-
fore suffer from common method bias. This limitation
mainly concerns the cross-sectional part of this study, as
temporal separation can be an effective way to reduce
common method bias (Spector, 2006). Still, future studies
may benefit from using measures that are more objective,
such as physiological measures, in examining internal
recovery. Also, the cross-sectional study permits no causal
interpretations. In the future the question of what factors
promote recovery during lunch breaks may best be tested
with intervention studies.
Fourth, the response rate was relatively low (37.5% at
T1 and 23.4% at T2 relative to baseline respondents) and
self-selection occurred between T1 and T2 in terms of a
permanent job contract, occupational status (more often
senior white-collar workers), working more often on
regular day shifts, and longer working hours per week.
This self-selection also concerns the cross-sectional part
of our study, where we used the sample collected at T2.
This was due to the fact that our T1 questionnaire did
not include all items related to lunch breaks (spend-
ing lunch breaks outside, spending breaks with others,
detachment, or control). Therefore, the generalizability
of our results may be limited. However, the response
rate is similar to those of other studies conducted in
organizational settings (see Baruch & Holtom, 2008,
for a review), and our large and diverse sample makes
the results more generalizable to wider populations.
Nevertheless, it would be useful to replicate our results
in other samples in future.
Fifth, our study included a limited variety of lunch-
time activities and only examined their frequency. For
example, we asked how often employees engaged in
social activities or spent their breaks outside the office
building, but did not differentiate with whom and where
exactly the breaks were spent. Therefore we recommend
that future studies take these issues into account using
more specific and comprehensive measures. We also
recommend measuring other experiences in addition
to detachment and control during workday breaks. For
example, relaxation may be important in terms of inter-
nal recovery, as it reduces psycho-physiological activa-
tion and elicits positive affect (Sonnentag & Fritz, 2007).
It may be possible to increase the experience of relaxa-
tion during breaks by engaging in relaxation exercises
(Krajewski et al., 2010) or less deliberately by engaging
in other relaxing activities, such as listening to music or
going for a walk.
Despite these limitations, our study has several
strengths. Earlier research on recovery has focused almost
exclusively on external recovery. This study provides new
insights on recovery during within working day breaks.
Specifically, it demonstrated that although lunch breaks
are limited in time, taking regular lunch breaks, which
enhance mental detachment and control over how to
spend the break, relate positively to successful recovery.
Our study also demonstrated that lunchtime recovery has
importance in terms of long-term exhaustion and vigor.
Our results on lunchtime recovery may be of particular
interest to organizations, as compared to external recov-
ery, organizations may influence the settings they provide
for recovery during within working day breaks.
This study demonstrated that lunchtime recovery may
best be promoted by ensuring control and especially
detachment during lunch breaks. In practice, organiza-
tions could promote lunchtime recovery by giving options
to spend lunch breaks in different ways that enable
detachment, such as spending the break in a non-work
environment or offering a space for relaxing activities.
This recommendation is suitable for fields where workers
are at risk of insufficient recovery, for example, employees
in cognitively or emotionally demanding jobs, and where
the work tasks enable flexibility in terms of lunch break
settings and activities. Furthermore, our study suggests
that recovery during lunch breaks and energy levels at
work are related across time. Thus if lunchtime recovery
is repeatedly successful, it may contribute to a decrease
in exhaustion and an increase in vigor. In summary, lunch
breaks offer an important recovery setting to promote
occupational health and well-being alongside recovery
during leisure time.
Funding Statement
This study was supported by the Academy of Finland
(grant 257682).
Competing Interests
The authors declare that they have no competing interests.
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How to cite this article: Sianoja, M., Kinnunen, U., de Bloom, J., Korpela, K. and Geurts, S. (2016). Recovery during Lunch Breaks:
Testing Long-Term Relations with Energy Levels at Work.
Scandinavian Journal of Work and Organizational Psychology
, 1(1): 7,
1–12, DOI:
Submitted: 04 April 2016 Accepted: 08 August 2016 Published: 30 August 2016
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Scandinavian Journal of Work and Organizational Psychology
is a peer-reviewed open
access journal published by Stockholm University Press.
... For instance, there are rest breaks, toilet breaks, coffee or tea breaks, lunch or meal breaks (hereafter referred to as meal breaks), and prayer breaks. In practice, the meal break is the most common and longest break during a workday for many employees (Sianoja et al., 2016). ...
... To date, there has been little research on the effect of work breaks on employee health (Eurofound, 2019; for reviews see Albulescu et al., 2022;Chan et al., 2022;Lyubykh et al., 2022;. However, in line with the assumptions of the effort-recovery model (Meijman and Mulder, 1998), some studies found that work breaks are related to reduced fatigue (e.g., Blasche et al., 2022;Cropley et al., 2020;Cropley et al., 2022;Ho et al., 2014) and improved health (e.g., Cropley et al., 2022;Faucett et al., 2007;Lohmann-Haislah et al., 2019;Park et al., 2021;Sianoja et al., 2016;Wu et al., 2012). For instance, in a study with Austrian hospital physicians, self-determined rest breaks related to reduced fatigue during work (Blasche et al., 2022). ...
... That the effect sizes reported in this study are rather small can be explained by the fact that health is determined by a multitude of factors, of which work-related variables in general, and specific work break characteristics in particular, make up only a small part. However, our results are in line with previous research showing associations between work breaks and employee health (e.g., Lohmann-Haislah et al., 2019;Sianoja et al., 2016;Wu et al., 2012;Xu et al., 2012). Moreover, our results support the theoretical assumptions of the effort-recovery model (Meijman and Mulder, 1998) with regard to at-work recovery, more specifically, work breaks. ...
This study aimed to investigate the prevalence of three characteristics of work break organization, namely skipping work breaks, interruptions of work breaks, and meal break duration, and their relationships with physical and mental health. We used data from the BAuA-Working Time Survey 2017, a representative workforce survey in Germany, and restricted the sample to 5979 full-time employees. Logistic regression analyses were conducted with in total five health complaints as dependent variables: back pain and low back pain, pain in the neck and shoulder region, general tiredness, faintness, or fatigue, physical exhaustion, and emotional exhaustion. Many employees often skipped their work breaks (29%) and experienced break interruptions (16%). Frequent skipping of work breaks was significantly positively, that is detrimentally, related to all five health complaints and frequent interruptions of work breaks also, except for neck and shoulder pain. Meal break duration was significantly negatively, that is beneficially, related to physical exhaustion.
... Earlier research has mainly focused on the individual ways to recover from work, such as recovery enhancing activities (physical exercise and hobbies) and recovery experiences [11,12]. Organizational level studies have focused on ergonomic shift scheduling [13,14] and recovery during breaks [15,16]. Moreover, leisure time recovery between work shifts [17] and during weekends [18], as well as vacations [19], have been investigated. ...
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Work in the health and social sector (HSS) is highly straining and therefore recovery from work needs to be promoted. Less is known on how job resources can be used to alleviate job strain and increase recovery from work. Thus, we analyzed the following: the association between job demands and work recovery; the connections of engaging leadership and psychological safety to recovery from work; and the moderating effects of engaging leadership and psychological safety on the relationship between strain and recovery from work. This cross-sectional study of 18,155 HSS and 4347 eldercare employees in 2020 using linear regression analysis showed that job strain (p < 0.001) and moral distress (p < 0.001) were associated with decreased recovery from work. Engaging leadership (p < 0.001) and psychologically safe work community (p < 0.001) enhanced recovery from work independently. Engaging leadership mitigated the harmful effect of job strain (p < 0.01) and moral distress (p < 0.05), and psychological safety mitigated the effect of job strain (p < 0.001), but not moral distress (p > 0.05). Thus, it is important to reduce job strain so that employees recover from work. Further job resources such as engaging leadership and psychological safety are important in themselves as they support recovery from work and employees' well-being, but also as they alleviate job demands.
... Consistent with this idea, previous research has found that breaks can reduce or prevent stress and help to facilitate recovery from early symptoms of work-related mental and physical fatigue. 37 However, research is needed to test psychological stress as a potential mediator of the beneficial effects of these treatments. The moderation effect of lumbar support on the beneficial effects of the postural shift intervention for low back pain is consistent with previous research showing that lumbar support helps to prevent the development of low back pain. ...
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Introduction: Neck and low back pain are significant health problem in sedentary office workers. Active break and postural shift interventions has been proved to reduce the incidence of new onset of both neck and low back pain. Objectives: To identify variables that moderate the effects of active breaks and postural shift interventions on the development of neck and low back pain in office workers. Methods: Using data from a 3-arm (active break, postural shift, and control group) cluster randomized controlled trial (N = 193), we evaluated the moderating effects of age, job position, education level, sex, perceived psychological work demands, number of working hours, and using a chair with lumbar support on the benefits of 2 interventions designed to prevent the development of neck and low back pain in office workers. Moderation analyses were conducted using the Hayes PROCESS macro, with post hoc Johnson-Neyman techniques and logistic regressions. Results: Significant interactions between intervention groups and 3 moderators assessed at baseline emerged. For the prevention of neck pain, the effect of the active break intervention was moderated by the number of working hours and the effect of the postural shift intervention was moderated by the level of perceived psychological work demands and the number of working hours. For the prevention of low back pain, the effect of postural shift intervention was moderated by having or not having a chair with lumbar support. Conclusions: The study findings can be used to help determine who might benefit the most from 2 treatments that can reduce the risk of developing neck and low back pain in sedentary workers and may also help us to understand the mechanisms underlying the benefits of these interventions.
... Likewise, coworker support (e.g. Avanzi et al., 2015) and taking breaks (Sianoja et al., 2016) as potential elements of the team health climateare associated with less exhaustion. Taken together, we propose that, H3. ...
Purpose Health-oriented leadership is an emerging concept that is promising for better understanding how leaders can support employee well-being. However, there is uncertainty about the process through which health-oriented leadership relates to employee well-being. Advancing health-oriented leadership research, this study aims to examine employee self-care and the perceived team health climate as mediating mechanisms. Design/methodology/approach The authors conducted a time-lagged study with three measurement points (NT1 = 335, NT2 = 134, NT2 = 113) to test these mechanisms. Findings The results show that health-oriented leadership at Time 1 positively relates to employee self-care and perceived team health climate at Time 2, which, in turn, are negatively associated with employee exhaustion at Time 3. Originality/value The indirect associations suggest that health-oriented leadership relates to employee well-being via the perceived team health climate and the individuals' self-care. By revealing an important mediating mechanism, this study contributes to the health-oriented leadership literature and can help organizations and leaders improve health promotion in organizations.
... A significant number of studies have examined how to enhance recovery during free evenings, weekends, and vacations (Sonnentag et al., 2017). Lately, more studies focusing on the recovery potential of workday breaks, such as lunch breaks, have also emerged (Bosch et al., 2018;Sianoja et al., 2016;Trougakos et al., 2014;von Dreden & Binnewies, 2017). However, virtually all previous studies have focused on one temporal recovery setting at a time (e.g., lunch breaks or evenings), and how recovery at different temporal settings is interconnected is not well understood (Sonnentag et al., 2017). ...
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Recovery from work stress during workday breaks, free evenings, weekends, and vacations is known to benefit employee health and well-being. However, how recovery at different temporal settings is interconnected is not well understood. We hypothesized that on days when employees engage in recovery-enhancing lunchtime activities, they will experience higher resources when leaving home from work (i.e., low fatigue and high positive affect) and consequently spend more time on recovery-enhancing activities in the evening, thus creating a positive recovery cycle. In this study, 97 employees were randomized into lunchtime park walk and relaxation groups. As evening activities, we measured time spent on physical exercise, physical activity in natural surroundings, and social activities. Afternoon resources and time spent on evening activities were assessed twice a week before, during, and after the intervention, for five weeks. Our results based on multilevel analyses showed that on days when employees completed the lunchtime park walk, they spent more time on evening physical exercise and physical activity in natural surroundings compared to days when the lunch break was spent as usual. However, neither lunchtime relaxation exercises nor afternoon resources were associated with any of the evening activities. Our findings suggest that other factors than afternoon resources are more important in determining how much time employees spend on various evening activities. Fifteen-minute lunchtime park walks inspired employees to engage in similar health-benefitting activities during their free time.
... On the other hand, if the employee break room is in a hospitable condition which can be seen as a positive servicescape, hospitality employees may be able to focus on an energy restoration without being interrupted by the surroundings. With support by the study of Sianoja, Kinnunen, de Bloom, Korpela, and Geurts (2016) identifying the long-term benefits of short breaks (e.g., lunch break), the accumulation of energy recovery in the employee break room on a daily basis is expected to positively affect employees' well-being. On the contrary, the repetition of incomplete recovery in a poor-conditioned employee break room might lead to aggravate their psychological well-being in a long term (Bowler, Buyung-Ali, Knight, & Pullin, 2010). ...
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Hospitality employees are suffering from various energy-related symptoms without opportunities to recharge themselves during the workday. In this regard, the employee break room, a sanctuary where employees can take refuge, can be suggested as an effective means to prevent negative consequences and to increase their psychological well-being. By combining Bitner’s servicescape model with job-demand resource model, this study demonstrated the potential effect of the physical environment of the employee break room. Survey data was collected from 311 hospitality employees. The results identified that employees’ perception of the physical environment of the break room promotes their work engagement, directly and indirectly increasing their psychological well-being.
Background: Rest breaks have been shown to reduce acute fatigue, yet not all nurses who take rest breaks report lower fatigue. Psychological detachment-letting go of work-related thoughts-during rest breaks and workload may be key factors in explaining this phenomenon. Objective: To examine the mediating role of psychological detachment during rest breaks and determine how workload moderated that pathway to lower acute fatigue among hospital nurses. Methods: In this cross-sectional study, data were collected from 1861 12-hour shift nurses who answered an online survey between July and September 2021. The survey included measures of occupational fatigue, psychological detachment from work, workload, and questions on breaks, work, health, and demographics. Structural equation modeling was used in Mplus 8.9 software to estimate the direct and indirect effects of rest breaks on acute fatigue at 3 levels of workload. Results: Nurses, on average, reported high acute fatigue, rarely experienced psychological detachment during rest breaks, and reported heavy workloads. Around 60% were able to sit down for a break on their last shift but with patient-care responsibilities. The relationship between taking a rest break and acute fatigue was fully mediated by psychological detachment from work. However, this relationship only held in the context of manageable workloads. Conclusion: Our findings showed that within-shift recovery is possible when nurses can psychologically detach from work during rest breaks. However, this within-shift recovery mechanism was disrupted for nurses with heavy workloads.
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This study aims to identify whether daily activities during the lunch break, performed before eating, are associated with improvements in several indicators related to recovery from work stress. No existing studies examine the daily effects of sitting mindfulness meditation and aerobic physical exercise practiced during lunch break as daily internal work recovery activities. This three-armed randomized controlled trial was carried out over 22 working days with service sector workers (n = 94, age mean, 46.8) The RCT was registered in, Identifier: NCT03728062. The mindfulness group received a mindfulness-based intervention (sitting meditation), while the physical exercise group practiced an aerobic exercise program with the same time intervals as the mindfulness group (15–30 minutes); the third group was the control group. We measured daily effects on fatigue, psychological detachment, sleep quality, stress symptoms, and attention problems. Measurements of daily variables were collected through an ad hoc App. Growth curve analysis reveals that mindfulness and physical exercise can effectively reduce fatigue, stress boschphysicalBosch physical exercise significantly improved sleep quality.
The increase in remote work during COVID-19 has drawn attention to the function of commutes as work-home transitions. While prior work-home research has referenced commutes as an example of role transitions, little is known about how the characteristics of a commute or the behaviors and processes undertaken in a commute affect their nature. We integrate research on commute characteristics, role transitions, and psychological recovery to develop a transitional perspective of commuting. We provide a conceptualization of liminal space that differentiates its physical and temporal dimensions and its psychological dimension as characteristics of the space through which one transitions during the commute and the experience of rolelessness one may perceive while doing so. We argue that perceived liminality during the commute frees cognitive resources for psychological role transition and recovery. Based on our conceptual model, we discuss implications for role transitions, commuting, and telecommuting research. Plain Language Summary Commutes provide a regular opportunity for individuals to shift from the work domain to the home domain. While making this transition, commuters occupy a “liminal space” in which they are neither fully engaged with work or home thoughts and behaviors. We explain and explore the physical, temporal, and psychological dimensions of this space, how the characteristics of commutes shape these dimensions, and how these dimensions create an opportunity for individuals to both recover from work and more effectively shift into the home role domain after the commute.
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Recovery experiences (i.e., psychological detachment, relaxation, mastery, and control; Sonnentag and Fritz (Journal of Occupational Health Psychology, 12, 204–221, 2007)) are thought to enhance both work and health outcomes, though the mechanisms are not well understood. We propose and test an integrated theoretical model in which work engagement and exhaustion fully mediate the effects of recovery experiences on job performance and health complaints, respectively. Meta-analytic associations (k = 316; independent samples; N = 99,329 participants) show that relaxation and mastery experiences positively predict job outcomes (work engagement, job performance, citizenship behavior, creativity, job satisfaction) and personal outcomes (positive affect, life satisfaction, well-being), whereas psychological detachment reduces negative personal outcomes (negative affect, exhaustion, work-family conflict), but does not seem to benefit job outcomes (work engagement, job performance, citizenship behavior, creativity). Control experiences exhibit negligible incremental effects. Path analysis largely supports the theoretical model specifying separate pathways by which recovery experiences predict job and health outcomes. Methodologically, diary and post-respite studies tend to exhibit smaller effects than do cross-sectional studies. Finally, within-person correlations of recovery experiences with outcomes tend to be in the same direction, but smaller than corresponding between-person correlations. Implications for recovery experiences theory and research are discussed.
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The validity of organizational research relies on strong research methods, which include effective measurement of psychological constructs. The general consensus is that multiple item measures have better psychometric properties than single-item measures. However, due to practical constraints (e.g., survey length, respondent burden) there are situations in which certain single items may be useful for capturing information about constructs that might otherwise go unmeasured. We evaluated 37 items, including 18 newly developed items as well as 19 single items selected from existing multiple-item scales based on psychometric characteristics, to assess 18 constructs frequently measured in organizational and occupational health psychology research. We examined evidence of reliability; convergent, discriminant, and content validity assessments; and test-retest reliabilities at 1- and 3-month time lags for single-item measures using a multistage and multisource validation strategy across 3 studies, including data from N = 17 occupational health subject matter experts and N = 1,634 survey respondents across 2 samples. Items selected from existing scales generally demonstrated better internal consistency reliability and convergent validity, whereas these particular new items generally had higher levels of content validity. We offer recommendations regarding when use of single items may be more or less appropriate, as well as 11 items that seem acceptable, 14 items with mixed results that might be used with caution due to mixed results, and 12 items we do not recommend using as single-item measures. Although multiple-item measures are preferable from a psychometric standpoint, in some circumstances single-item measures can provide useful information. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
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Work recovery research has focused mainly on how after-work break activities help employees replenish their resources and reduce fatigue. Given that employees spend a considerable amount of time at work, understanding how they can replenish their resources during the workday is critical. Drawing on ego depletion (Muraven & Baumeister, 2000) and self-determination theory (Deci & Ryan, 1985), we employed multi-source experience sampling methods to test the effects of a critical boundary condition, employee lunch break autonomy, on the relation between lunch break activities and end-of-workday fatigue. Although specific energy-relevant activities had a main effect on end-of-workday fatigue, each of these was moderated by the degree of autonomous choice associated with the break. Specifically, for activities that supported the psychological needs of relatedness and competence (i.e., social and work activities, respectively), as lunch break autonomy increased, effects switched from increasing fatigue to reducing fatigue. To the extent that lunch break activities involved relaxation, however, lunch break autonomy was only important when levels of relaxation were low. We conclude that lunch break autonomy plays a complex and pivotal role in conferring the potential energetic benefits of lunch break activities. Contributions to theory and practice are discussed.
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Organizational researchers and practitioners are increasingly interested in self-regulatory strategies employees can use at work to sustain or improve their occupational well-being. A recent cross-sectional study on energy management strategies suggested that many work-related strategies (e.g., setting a new goal) are positively related to occupational well-being, whereas many micro-breaks (e.g., listening to music) are negatively related to occupational well-being. We used a diary study design to take a closer look at the effects of these energy management strategies on fatigue and vitality. Based on conservation of resources theory, we hypothesized that both types of energy management strategies negatively predict fatigue and positively predict vitality. Employees (N = 124) responded to a baseline survey and to hourly surveys across one work day (6.7 times on average). Consistent with previous research, between-person differences in the use of work-related strategies were positively associated with between-person differences in vitality. However, results of multilevel analyses of the hourly diary data showed that only micro-breaks negatively predicted fatigue and positively predicted vitality. These findings suggest that taking micro-breaks during the work day may have short-term effects on occupational well-being, whereas using work-related strategies may have long-term effects.
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This is an illustrative review on studies revealing the restorative, i.e. stress-reducing, effects of natural settings. We focus on the effects of viewing or being physically active in the natural setting and the effects of indoor plants and window views on restoration and recovery. These themes represent interesting and potentially fruitful areas for future studies that combine work and environmental psychological aspects. There is conceptual similarity between recovery experiences and processes of perceived restorativeness. Increasing evidence shows that outdoor natural environments are more efficient in producing restoration than outdoor built environments. Anecdotal evidence shows that window views to natural elements buffer the negative impact of job stress on intention to quit; the more natural elements, the less the negative impact of job stress on turnover intentions. A laboratory study recording brainwaves and blood volume pulse has indicated that people are less nervous or anxious when looking at the window view to nature compared with the window view to the city or no window view. Also the amount of outdoor nature contact during breaks at work seems to be associated with less perceived stress and better self-rated health. Research has showed that plants in the office room seem to enhance the solution of creative tasks but deteriorate simple, proofreading or sorting tasks which require continuous concentration to the task. Some practical recommendations can be made on the basis of current evidence but more rigorous experimental and intervention studies are needed. Article can be downloaded via:
This one-year follow-up study (N = 841) investigated the relationship between boundary crossing behavior from work to non-work and work-related rumination (i.e., affective rumination, problem-solving pondering and lack of psychological detachment from work during off-job time). This relationship is important to examine as work-related rumination is a risk factor for poor recovery and ill-health over time. The aims were twofold: first, to examine these relationships in terms of temporal ordering, and, second, to show how individual differences regarding stability and change of boundaries from work to non-work are reflected in work-related rumination across time. The structural equation modeling (SEM) analyses lent support to the hypothesized normal causation model compared with the reversed causation and reciprocal models. However, only the cross-lagged relationship between high boundary crossing behavior at T1 and lack of psychological detachment at T2 was significant. Through latent profile analysis (LPA), six subgroups of boundary crossing behavior across time were identified. Over 70% of the employees belonged to the stable (low, moderate, high) and about one third to the changing (mostly increasing) boundary crossing subgroups. Employees in the two stable (high and moderate) boundary crossing subgroups reported less psychological detachment and more problem-solving pondering during off-job time than did those in the low boundary crossing subgroup. Employees in the change groups reported simultaneous expected changes especially in their problem-solving pondering. No effects on affective rumination were found. Thus frequent boundary crossing behavior from work to non-work plays a different role regarding the various forms of work-related rumination during non-work.
It has been shown that recovery (i.e., unwinding from one’s job demands) is important for reducing the negative effects of job stress. Consequently, poor recovery from job stress deserves research attention as a risk factor in the job stress–strain relationship. Recovery can occur both during free time (i.e., evenings, weekends, vacations) and within working days (i.e., lunch breaks and shorter breaks at work). In this chapter, we focus on within-working day recovery, which has thus far received much less attention than off-job recovery. Our aim is to examine the role of at-work breaks in employee recovery. We reviewed findings from earlier empirical studies to address the following three questions: First, do breaks at work have effects on employeeʼ well-being and health? Second, are there specific activities during work breaks that impact the recovery process and outcomes? Third, are there other factors than activities that either hinder or facilitate recovery during breaks at work? The review revealed, first, that breaks at work benefit health and well-being, especially when employees are free to take a break at a point of heightened fatigue. Second, in terms of recovery, engaging in relaxing break activities is beneficial regardless of the length of the break. Third, autonomy related to break schedules and activities, as well as positive affect seem to facilitate recovery at work, whereas obligatory activities and the accompanying negative affect hinder recovery. In practice, both employees and organizations should pay attention to utilizing breaks from work for unwinding in order to sustain long-term well-being and health.