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Advance Publication
INDUSTRIAL HEALTH
Received : May 19, 2015
Accepted : January 12, 2016
J-STAGE Advance Published Date : January 30, 2016
1
Psychological Detachment from Work during Nonwork Time:
Linear or Curvilinear Relations with Mental Health and Work Engagement?
Akihito SHIMAZU, PhD
1, 2
Ko MATSUDAIRA, MD, PhD
3, 4
Jan DE JONGE, PhD
2, 5
Naoya TOSAKA, BA
1
Kazuhiro WATANABE, MA
1, 6
Masaya TAKAHASHI, PhD
7
1
Department of Mental Health, The University of Tokyo, Graduate School of Medicine,
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
2
Asia Pacific Centre for Work Health and Safety, University of South Australia,
Adelaide, Australia
3
Department of Medical Research and Management for Musculoskeletal Pain, 22nd
Century Medical and Research Center, Faculty of Medicine, The University of
Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
4
Clinical Research Center for Occupational Musculoskeletal Disorders, Kanto Rosai
Hospital, 1-1 Kizukisumiyoshicho, Nakahara-ku, Kawasaki 211-8510, Japan
5
Human Performance Management Group, Department of Industrial Engineering and
Innovation Sciences, Eindhoven University of Technology, Eindhoven, The
Netherlands
6
Japan Society for the Promotion of Science, Tokyo, Japan
7
National Institute of Occupational Safety and Health, 6-21-1, Nagao, Tama-ku,
Kawasaki 214-8585, Japan
Address for correspondence: Akihito SHIMAZU, PhD
Department of Mental Health, The University of Tokyo, Graduate School of Medicine,
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
TEL/FAX: +81-3-5841-3612
e-mail: ashimazu@m.u-tokyo.ac.jp
Article type: Original Article
Running title: PSYCHOLOGICAL DETACHMENT, HEALTH, AND WORK
ENGAGEMENT
Number of tables: 1
Number of figure: 4
2
Abstract
This study examined whether a higher level of psychological detachment during non-
work time is associated with better employee mental health (Hypothesis 1), and
examined whether psychological detachment has a curvilinear relation (inverted U-
shaped pattern) with work engagement (Hypothesis 2). A large cross-sectional Internet
survey was conducted among registered monitors of an Internet survey company in
Japan. The questionnaire included scales for psychological detachment, employee
mental health, and work engagement as well as for job characteristics and demographic
variables as potential confounders. The hypothesized model was tested with moderated
structural equation modeling techniques among 2,234 respondents working in the
tertiary industries with regular employment. Results showed that psychological
detachment had curvilinear relations with mental health as well as with work
engagement. Mental health improved when psychological detachment increased from a
low to higher levels but did not benefit any further from extremely high levels of
psychological detachment. Work engagement showed the highest level at an
intermediate level of detachment (inverted U-shaped pattern). Although high
psychological detachment may enhance employee mental health, moderate levels of
psychological detachment are most beneficial for his or her work engagement.
(184/200 words)
Key words: Psychological detachment; Mental health; Structural equation modeling;
Work engagement; Curvilinearity
3
Introduction
In recent years, scholars have argued that not only on-job experiences (how
employees spend their working time) but also off-job experiences (how they spend their
private or leisure time) are crucial for understanding employee well-being
1)
. More
specifically, better knowledge of off-job recovery from the demands experienced during
working time is imperative
2)
. Recovery can be defined as a process during which
individual functional systems that have been called upon during a stressful experience
return to their initial, pre-stressor level
3)
. Recovery can be regarded a process opposite
to the strain process, during which the detrimental effects of stressful situations are
alleviated or eliminated. Recovery is also regarded as an explanatory mechanism in the
relation between acute stress reactions and chronic health impairment
4)
. Certain
experiences outside of work can help in alleviating reactions to work demands
5-7)
. These
so-called recovery experiences consist of psychological detachment, relaxation, mastery,
and control
8)
. Psychological detachment; i.e., the ability of individuals to mentally
“switch off” from work by not doing work-related tasks and not thinking about work
during non-work time, is considered the most crucial recovery experience for protecting
one’s well-being regarding job-related recovery
2, 9)
.
In the context of respites from work, detachment has been described as an
“individual’s sense of being away from the work situation”
10)
. Psychological
detachment has been further characterized as not being involved in work-related
activities, such as phone calls, e-mails, or other work-related tasks, during off-work
time
8)
. Psychological detachment from work extends beyond the pure physical absence
from the workplace during off-job time and abstaining from job-related tasks. It implies
leaving the workplace behind oneself in psychological terms
11)
.
4
The relation between psychological detachment and well-being can be explained by
COR theory
12)
and the Effort-Recovery Model
3)
. Conservation Of Resources (COR)
theory asserts that an individual aspires to preserve, protect, and build resources.
Resources are characterized as objects, conditions, personal characteristics, or energies
that have specific importance for the individual. According to COR theory, stress occurs
when individuals are threatened with resource loss, actually lose resources, or fail to
gain resources following resource investment. The inability to replenish energy
resources may lead to long-term fatigue, which hampers normal functioning in many
aspects in daily life, including work. Thus, to recover from stress, individuals have to
gain new resources and restore threatened or lost resources. Psychological detachment
can contribute to gaining new resources and restore threatened or lost resources.
The Effort-Recovery Model
3)
holds that effort expenditure at work leads to load
reactions such as fatigue or physiological activation. Load reactions can accumulate and
lead to impaired health and well-being, unless individuals can recover from work. By no
longer being exposed to job-related demands, load reactions can return to pre-stressor
levels, and recovery can occur before the next working period starts. This implies that
recovery strategies such as psychological detachment during off-work time can be an
opportunity to return to and stabilize at a baseline level. Thus, both the Effort-Recovery
Model and COR theory suggest two complementary processes by which recovery
occurs. First, it is important to refrain from work demands and to avoid activities that
call upon the same functional systems or internal resources as those required at work.
Second, gaining new internal resources such as energy, self-efficacy or positive mood
will additionally help to restore threatened resources
8)
.
Previous studies that examined the relation between psychological detachment
5
and well-being have revealed that psychological detachment is positively associated
with mental health and negatively associated with job stress and burnout
6, 8, 11, 13, 14)
.
Therefore, we expect that a higher level of psychological detachment during non-work
time will be associated with better mental health (Hypothesis 1).
Regarding positive aspects of employee well-being, the present study focuses on
work engagement, which refers to a positive, fulfilling, work-related state of mind that
is characterized by vigor, dedication, and absorption
15)
. Previous studies have shown
that psychological detachment is positively associated with work engagement
16-18)
,
because detachment may contribute to the prevention of continued resource drain and
restoration of resources
18)
. If employees do not unwind from one’s work, depleted
resources can lead to low work engagement. Thus, we can assume that low levels of
psychological detachment are associated with low work engagement.
However, the relation between psychological detachment and work engagement
appears to be more complex. For instance, Shimazu et al.
19)
showed a negative relation
between these variables, suggesting that switching off mentally during off-job time did
not improve work engagement, but rather decreased it. When individuals are highly
detached from their jobs during off-job time, they may feel difficulty in “switching on”
again in the next morning
14)
, and they may need more time to mobilize their energy for
their job, which results in impaired work engagement.
These findings suggest that (very) low and (very) high levels of psychological
detachment will be detrimental to work engagement. As a result, moderate levels of
psychological detachment will be associated with the highest levels of work
engagement. All these findings imply non-linear rather than linear relations between
detachment and work engagement, which is in line with Warr’s (1994) assumptions on
6
work
20)
, mental health and well-being. Accordingly, we expect that psychological
detachment will have a curvilinear relation (inverted U-shaped pattern) with work
engagement (Hypothesis 2).
Method
Study population
An Internet research company with 1.5 million registered research volunteers
aged 20–69 years, was used to conduct a large Internet-based cross-sectional survey on
occupation, health and well-being in 2011. We randomly selected 106,250 volunteers
from 201,170 monitors, living in three greater metropolitan areas of Japan (23 wards of
Tokyo, the City of Osaka, and the City of Nagoya). On March 25, 2011, the selected
volunteers were invited to take part in the study via an e-mail containing a link to the
survey. Participants received online shopping points as an incentive for participation. In
order to prevent double registration, e-mail addresses were checked and a link to the
questionnaire was disabled once the survey was completed. On March 31, 2011, the
survey was closed when more than five thousand participants responded (a total of
5,860 surveys were collected). Therefore, a specific response rate could not be
calculated for this survey.
Our respondents were very close to the people living in 23 wards of Tokyo, the
City of Osaka, and the City of Nagoya in terms of mean age (45.2 years in our
respondents, 43.9 in Tokyo, 44.8 years in Osaka, and 43.8 years in Nagoya), gender
(50.8 % in our respondents, 50.7 % in Tokyo, 51.5 % in Osaka, and 50.7 % in Nagoya),
and employment status (46.5 % regular employment in our respondents, 46.1 % in
Tokyo, 46.2 % in Osaka, and 50.1 % in Nagoya). However, our respondents had higher
educational level (40.9 % undergraduate or higher) than those living in Tokyo (33.2 %),
7
in Osaka (20.8 %), and in Nagoya (26.0 %)
21, 22)
.
In our respondents, the proportion of respondents working within primary
industries (e.g., agriculture, forestry, and fisheries) and secondary industries (e.g.,
mining, manufacturing, and constructions) was extremely low (0.1% and 7.6%
respectively). Therefore, we analyzed responses only from those individuals working in
tertiary industries (e.g., transport and postal activity, wholesale and retail trade,
accommodations, eating and drinking services, finance and insurance, advertising,
education and learning support, and medical, health care and welfare). Individuals with
a reported age of either < 20 years or ≥ 65 years, those with non-regular employment, or
shift workers were excluded
23, 24, 25)
. A total of 2,234 participants were retained and
included in the analysis. The mean age of the participants was 41.7 years (SD = 11.3).
Of the participants, 63.9% were male, 54.4% were married, 55.9% had a university
degree or higher, and 12.2% worked more than 60 hours per week.
Measures
Psychological detachment
Psychological detachment was assessed using the corresponding subscale of the
Japanese version of the Recovery Experience Questionnaire
8, 19)
, consisting of four
items (i.e., “I forget about work,” “I don’t think about work at all,” “I distance myself
from my work,” and “I get a break from the demands of work”). All items were scored
on a five-point Likert scale, ranging from 1 (do not agree at all) to 5 (fully agree).
Responses for the 4 items were summed to get a scale score. Cronbach’s alpha
coefficient was .86.
8
Mental health
Mental health was assessed using the corresponding subscale of the SF-36 version
1.2
26-28)
, consisting of five items (i.e., “Have you been a very nervous person?”, “Have
you felt so down in the dumps that nothing could cheer you up?”, “Have you felt calm
and peaceful? (reversed) ”, “Have you felt downhearted and blue?”, and “Have you
been a happy person? (reversed)”). All items were scored on a six-point Likert scale,
ranging from 1 (all of the time) to 6 (none of the time). We used the SF-36 mental
health summary score as a measure of mental health (Range: 0-100)
29)
. Cronbach’s
alpha coefficient was .84.
Work engagement
Work engagement was assessed using the short form of the Utrecht Work
Engagement Scale (UWES)
15)
, which has been validated in Japan
30)
. The UWES
includes three subscales that reflect the underlying dimensions of engagement: Vigor (3
items; e.g., “At my job, I feel strong and vigorous”), Dedication (3 items; e.g., “I am
enthusiastic about my job”), and Absorption (3 items; e.g., “I am immersed in my
work”). All items are scored on a seven-point Likert scale ranging from 0 (never) to 6
(always). Responses for the 3 items each were summed to get a scale score. Cronbach’s
alpha coefficients were .87 for vigor, .84 for dedication, and .86 for absorption.
Potential confounders
We controlled for two types of potential confounders; i.e., (1) job
characteristics and (2) demographic characteristics. Their relation with detachment and
our outcome measures is well-established in the literature
4, 9, 11)
.
9
Job characteristics were assessed using three scales of the Brief Job Stress
Questionnaire (BJSQ
31)
): job demands, job control and workplace support. The first two
scales consisted of 3 items each, for instance “My job requires working hard” and “I
have influence over the pace of my work”. Workplace support consisted of 6 items: 3
items for supervisor support and 3 items for coworker support. To receive a more
parsimonious model and to avoid multi-collinearity, we combined the two subscales in
overall workplace support due to a high bivariate correlation (r = 0.59; p < .001). All
items were scored on a four-point Likert scale, ranging from 1 (disagree) to 4 (agree).
Cronbach’s alpha coefficients were .81 for job demands, .85 for job control, and .86 for
workplace support.
Demographic characteristics such as age, gender, marriage, education, and
working hours per week were also included as potential confounders in the
questionnaire.
Data analyses
To test the hypotheses, we conducted moderated structural equation modeling
(MSEM) analyses, using the AMOS software package
32)
. We preferred MSEM to
hierarchical regression analyses, because MSEM allows multivariate testing of
outcomes, allows assessing and correcting for measurement error, and provides
measures of fit of the models under study. We followed the procedure proposed by
Mathieu et al.
33)
as described by Cortina et al.
34)
. Linear psychological detachment and
mental health had only one indicator that was the standardized (centered) scale score of
the respective factor
33)
. The indicator of the latent curvilinear psychological detachment
was the squared term of the standardized (centered) scale score of psychological
10
detachment. Work engagement had three indicators (i.e., vigor, dedication, and
absorption). Correlation between linear psychological detachment and curvilinear one
was constrained to be zero, whereas mental health and work engagement were allowed
to correlate. The paths from the latent exogenous factors to their indicators were fixed
using the square roots of the scale reliabilities, and the error variances of each indicator
were set equal to the product of their variances and 1 minus their reliabilities. See
Figure 1 for our hypothesized model. For more details regarding the calculation of the
reliability score of the curvilinear term, we refer to Cortina et al.
34)
.
-------------------------
Figure 1 about here
-------------------------
The fit of the models was assessed with the chi-square statistic, the goodness-of-
fit index (GFI), the comparative fit index (CFI), the non-normed fit index (NNFI), and
the root-mean-square error of approximation (RMSEA). It is suggested that GFI, CFI,
and NNFI values that exceed .90 and RMSEA values as high as .08 are indicative of
acceptable fit
35)
.
Ethics statement
This study was approved by the medical/ethics review board of the Japan Labour
Health and Welfare Organization and The University of Tokyo medical department.
Results
Simple statistics
Zero-order correlation coefficients are shown in Table 1. Psychological detachment
was positively correlated with mental health (r = .22, p < .001), and negatively
11
correlated with vigor (r = -.04, p < .05), dedication (r = -.06, p < .01), and absorption (r
= -.14, p < .001).
----------------------------
Table 1 about here
----------------------------
Results of MSES analyses
Results of the MSEM-analyses showed that the hypothesized model (Model 1)
fits to the data (χ
2
(8) = 236.72, p < .001, GFI = .97, NNFI = .93, CFI = .96) although
RMSEA value exceeded .08 (RMSEA = .11). In line with Hypothesis 1, linear
psychological detachment was positively related to mental health (β = .24, p < .001). As
to Hypothesis 2, both linear and curvilinear psychological detachment were negatively
related to work engagement (β = -.10, p < .001 and β = -.06, p < .01, respectively).
To ensure that no curvilinear relation existed between psychological detachment
and mental health in addition to linear one, we examined the alternative model that adds
the path from curvilinear psychological detachment to mental health. The model fit of
the alternative model (Model 2: χ
2
(7) = 216.11, p < .001, GFI = .97, NNFI = .92, CFI
= .97, RMSEA = .12) was similar to one of the hypothesized model. However, the chi-
square difference test, comparing the hypothesized model (Model 1) with the alternative
model (Model 2), shows a significant improvement in model fit (∆χ
2
(1) = 20.61, p
< .001). This means that the alternative model (Model 2), including the path from
curvilinear psychological detachment to mental health, offers a better account of the
data than the hypothesized model (Model 1). Therefore, we decided to adopt the
alternative model (Model 2) in further examination.
As can be seen in Figure 2, linear psychological detachment was significantly and
12
positively related to mental health (β = .22, p < .001) whereas curvilinear psychological
detachment was also significantly but negatively related to it (β = -.10, p < .001). In
addition, both linear and curvilinear psychological detachment were significantly and
negatively related to work engagement (β = -.11, p < .001 and β = -.09, p < .01,
respectively). Please note that the results regarding the curvilinear relationship between
psychological detachment and work engagement were similar in all three sub
dimensions of the construct (i.e., vigor, dedication, and absorption).
----------------------------
Figure 2 about here
----------------------------
Regarding the curvilinear relation between psychological detachment and mental
health, Figure 3 shows that initially there is a positive relation: more detachment is
associated with better mental health. However, at high levels of psychological
detachment, the positive relation between psychological detachment and mental health
became less prominent, and even seems to disappear. Mental health did not increase
further and remained at a high level.
----------------------------
Figure 3 about here
----------------------------
With regard to the curvilinear relation between psychological detachment and
work engagement, Figure 4 shows that moderate levels of psychological detachment
were associated with the highest levels of work engagement, whereas very low and very
high detachment were associated with lower levels of work engagement (i.e., inverted
U-shaped pattern).
13
----------------------------
Figure 4
----------------------------
In a final step, we conducted additional analysis to control for potential
confounders (i.e., age, gender, marriage, education, working hours, job demands, job
control, and workplace support). Specifically, each control variable was included in the
alternative model (Model 2) as a manifest variable simultaneously and was allowed to
relate to all variables in the model. After controlling for confounding variables, the path
coefficients were virtually the same as those of the alternative model (Model 2), but the
model fit decreased (χ
2
(35) = 1538.06, p < .001, GFI = .91, NNFI = .53, CFI = .82,
RMSEA = .14). These results indicate that the added relations of the control variables to
the model variables were weak. Importantly, many control variables did not
significantly affect the structural paths in the model (i.e., 18 out of 48 paths were not
statistically significant). Therefore, the control variables were removed from the final
model in Figure 2.
Discussion
The aim of this large cross-sectional Internet survey study was to examine
whether higher levels of psychological detachment during non-work time would be
associated with improved employee mental health (Hypothesis 1). We also examined
whether psychological detachment would have a curvilinear relation (i.e., inverted U-
shaped pattern) with work engagement (Hypothesis 2). Examination of the curvilinear
relation was novel, because prior research on the function of psychological detachment
on work engagement is inconsistent in this respect
16-19)
.
As far as the relation between psychological detachment and mental health is
14
concerned, MSEM revealed that not only linear psychological detachment (β = .22, p
< .001) but also curvilinear detachment (β = -.10, p < .001) was significantly related to
mental health. This result was contrary to our expectation. Examining Figure 3, the
positive relation between psychological detachment and mental health flattened after
higher levels of psychological detachment. This pattern of findings suggests that mental
health initially improves when people psychologically detach. However, employee
mental health does not benefit any further from extremely high levels of psychological
detachment. It is important to note that mental health does not suffer at such very high
levels of psychological detachment. Although most previous studies showed that higher
levels of psychological detachment during non-work time were associated with better
employee mental health
6, 8, 11, 13)
, our result suggests that the favorable effect of
psychological detachment may have an upper limit on mental health, at least among our
participants. Future research needs to examine under which conditions and for whom
psychological detachment has such a curvilinear relation with mental health.
As to the relation between psychological detachment and work engagement, we
also found a curvilinear relation. Moderate levels of psychological detachment were
associated with highest levels of work engagement, whereas very low and very high
psychological detachment was associated with lower levels of work engagement (i.e.,
inverted U-shaped pattern). Very low levels of psychological detachment may drain
one’s resources and inhibit resource restoration, whereas very high levels of
psychological detachment may require a longer time to get back into “working mode” in
the next morning
9)
. These may negatively impact work engagement, particularly at high
levels of detachment. Finally, it is worth noting that the curvilinear relation between
psychological detachment and work engagement resembles (albeit at a weaker level) a
15
previously found relation between psychological detachment and job performance in
earlier research
14)
. Given that both of these are more strictly work-related variables, the
current finding may have implications for future research on the topic.
Limitations and suggestions for future research
Next to several strengths such as a large sample size and sufficient study power,
there are also several limitations of this study. First, we used self-report survey data.
Self-report measures may be biased due to, for example, negative affect. Common
method variance might have affected the results, suggesting that the true associations
between variables might be weaker than those observed in this study. Although several
studies have shown that these influences are not as high as could be expected
36-38)
, our
findings should be replicated using more objective measures (e.g., peer-ratings of
mental health and work engagement) in the future.
Second, we used a cross-sectional study design, which precludes making causal
inferences. For instance, our data showed that psychological detachment was related to
better mental health. This might indicate that more psychological detachment leads to
better mental health. It might also be that individuals enjoying better mental health are
more likely to detach themselves from their work. Based on the cross-sectional analyses
of the current study, it can only be concluded that psychological detachment is related to
mental health and well-being. More longitudinal research is needed to uncover the
causal sequence in the relation between psychological detachment and its consequences.
However, it should be noted that there is a growing body of literature that demonstrates
longitudinal effects of psychological detachment on health and well-being, particularly
at day-level
39-42)
. They support our causal inferences from both theoretical and empirical
16
viewpoints.
Third, our data were collected from people living in three greater metropolitan
areas of Japan (23 wards of Tokyo, the City of Osaka, and the City of Nagoya), which
requires caution regarding the generalizability of our findings. Our sample may not
represent other working populations quite well. Therefore, further studies are necessary
to examine whether our results are applicable to workers in local areas.
Fourth, our data were collected via the Internet, which again requires caution
regarding the generalizability of our findings. It has been claimed that the
socioeconomic and educational status of the average Internet user is usually greater than
that of the general population
43)
. Indeed, our participants reported higher educational
status than those completing nationwide paper-and-pencil surveys in Japan
44)
and those
living in Tokyo, in Osaka, and in Nagoya
21, 22)
. Thus, similar to typical Internet studies,
self-selection might be a limitation of the present study.
Finally, psychological detachment did not have much explanation for outcomes in
our participants. Specifically, linear and curvilinear psychological detachment explained
successively 6 % and 2 % of the variances of mental health and work engagement in
Model 2. One possible explanation is that we did not examine the combined effects of
psychological detachment and other types of recovery experiences. Until now, only
bivariate associations of recovery experiences with outcome variables have mainly been
investigated. However, in reality, it is less likely that people use either type of recovery
experience exclusively. Rather, they may use various types of recovery experiences
simultaneously given the positive correlations among them (e.g., r = .16 - 63 by
Sonnentag
8)
, and r = .26 - .70 by Shimazu et al.
19)
). Hence, it is important to examine
the combined as well as independent associations of each type of recovery experience
17
with well-being in employees. According to COR theory
12)
, employees using various
type of recovery experiences simultaneously are assumed to experience better well-
being because multiple recovery experiences may provide more opportunity for
recovery from resource loss and for resource gain. Another possible explanation is that
we did not consider conditions under which employees use psychological detachment.
This suggests the possibility that psychological detachment may not be favorable for
everybody and in all situations
45)
. For instance, employees who experience their jobs as
highly meaningful and enjoyable might find detachment difficult to achieve, but lack of
detachment might be less of a problem for such people. Thus, job features might
moderate the relation between psychological detachment and well-being. Future
research needs to examine the conditions under which psychological detachment can
have more favorable effects.
Implications for practice
Our findings have some implications for practice. A first implication is that
psychological detachment during non-work time is associated with employee mental
health and work engagement in different ways.
With regard to employee mental health, higher levels of detachment would
facilitate better mental health (although the favorable effect of detachment had
limitations). It is important that both organizations and supervisors should support
employee detachment by advising that employees be as unavailable as possible (e.g., via
e-mail, texting or phone) during their nonwork time. It might be beneficial for workers
to detach from work if they do not use their smartphones or tablets for work-related
issues during free time
46-48)
. However, it might also be possible that checking one’s
work e-mails helps to detach from work in particular circumstances. For example, if
18
s/he is unsure whether s/he has forgotten to inform a colleague about an important
work-related issue, to check the sent box of his/her e-mail account might help him/her
thereafter to detach from work. Further research needs to examine whether the use of
communication devices such as smartphones or tablets during non-work time can be
beneficial or not for one’s detachment from work. Organizations and supervisors can
also support employee detachment by not initiating work-related communication with
their employees during non-work time, thereby allowing detachment to occur
14)
.
Supervisors can act as role models in this respect by not being available during non-
work time. This is particularly important in a country like Japan, because those who are
in charge of changing long working culture in Japan are often work addicts
themselves
49)
. Furthermore, improving working conditions to achieve adequate levels of
job demands can be a promising avenue to facilitate psychological detachment because
high job demands (e.g., reduce time pressure) can inhibit psychological detachment
during off-work time
2)
.
It is also important for employees who are at risk for workaholism (i.e., working
excessively with an obsessive manner
50)
) to modify this tendency, since it inhibits
psychological detachment
2)
. Training programs that focus on time management and
problem solving skills might be helpful, because workaholic employees take on more
work than they can handle and accept new tasks before completing previous ones
51)
.
Rational emotive therapy
52)
might be also helpful, since workaholic people suffer from
the belief that they should be perfect
53)
.
With regard to work engagement, the relation with psychological detachment is
more complex and suggest a different practical implication: Moderate levels of
psychological detachment would be associated with the highest levels of work
19
engagement. Although operationalizing the optimal level of psychological detachment
seems to be not very easy, it should be noted that thinking about work may not be
necessarily negative per se
9, 54)
. Positively reflecting about one’s work (e.g., thinking
about a recent success or about an inspiring goal) might even improve work engagement,
but this thinking should not be too much – there seems to be an upper limit for work
reflection. Future research needs to clarify the preferable type and amount of work-
related thoughts during off-job time to improve work engagement.
Conclusion
Although higher levels of psychological detachment may enhance employee
mental health, it seems that moderate levels of psychological detachment are most
beneficial for his or her work engagement. In future, more research is needed to address
how, and under which conditions, to attain optimal levels of psychological detachment
to achieve both better employee mental health and greater work engagement.
20
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25
Table 1. Descriptive statistics for the key study variables (N=2,234)
Variable
Range
Mean
SD
1
2
3
4
5
6
7
1
Age
20-64
41.74
11.31
2
Gender
a
0-1
.64
.48
-.10
***
3
Marriage
b
0-1
.54
.50
-.41
***
.31
***
4
Education
c
0-1
.56
.50
-.08
***
-.19
***
-.03
5
Working hours (per week)
d
0-1
.12
.33
-.06
**
-.15
***
-.04
*
.03
6
Job demands
3-12
8.20
2.22
-.14
***
-.07
**
.02
.09
***
.26
***
7
Job control
3-12
8.10
2.02
.18
***
-.02
-.10
***
.00
-.06
**
-.16
***
8
Workplace support
6-24
15.20
3.89
-.03
.03
-.05
*
-.01
-.01
-.02
.30
***
9
Psychological detachment
4-20
13.77
3.53
.01
.06
**
.07
**
-.05
*
-.11
***
-.25
***
.07
***
10
Mental health
0-100
59.93
19.37
.14
***
-.04
*
-.12
***
.03
-.09
***
-.22
***
.25
***
11
Vigor
0-18
6.93
3.67
.20
***
.03
-.11
***
.01
.01
.01
.31
***
12
Dedication
0-18
8.25
3.77
.17
***
.05
*
-.09
***
.01
.05
*
.13
***
.29
***
13
Absorption
0-18
6.97
3.87
.14
***
.00
-.08
***
.03
.06
**
.14
***
.27
***
26
Table 1. (continued)
Variable
8
9
10
11
12
1
Age
2
Gender
a
3
Marriage
b
4
Education
c
5
Working hours (per week)
d
6
Job demands
7
Job control
8
Workplace support
9
Psychological detachment
.05
*
10
Mental health
.35
***
.22
***
11
Vigor
.30
***
-.04
*
.31
***
12
Dedication
.30
***
-.06
**
.25
***
.82
***
13
Absorption
.24
***
-.14
***
.18
***
.79
***
.83
***
Note: * p < .05 ** p < .01 *** p < .001. SD: Standard Deviation.
a
Gender was coded as 1 (men) and 0 (women).
b
Marriage was coded as 1 (yes) and 0
(no).
c
Education was coded as 1 (university or higher) and 0 (college or lower).
d
Working hours per week was coded as 1 (60 =<) and 0 (< 60).
27
DetachmentDetachment
e
Detachment
X
Detachment
Cross-product
term
Mental
Health
Mental health
Work
Engagement
Vigor Dedication
Absorption
e
e
e e
e
e
e
Figure 1. Hypothesized model (Model 1).
Note: e = error.
28
DetachmentDetachment
e
Detachment
X
Detachment
Cross-product
term
Mental
Health
(R
2
= .06)
Mental health
Work
Engagement
(R
2
= .02)
Vigor Dedication
Absorption
.93 ***
1.00 ***
.22 ***
-.10 ***
-.11 ***
-.09 **
.30 ***
1.00 ***
.89 ***
.89 ***
.93 ***
e
e
e
e
e e
e
Figure 2. Standardized solution (Maximum Likelihood estimates) of the final (alternative) model (Model 2: N=2,234).
Note: e = error. *** p < .001, ** p < .01, * p < .05.
29
Figure 3. Curve-fitting between psychological detachment and mental health.
30
Figure 4. Curve-fitting between psychological detachment and work engagement.
