Content uploaded by Milad Mirbabaie
Author content
All content in this area was uploaded by Milad Mirbabaie on Feb 04, 2022
Content may be subject to copyright.
17th International Conference on Wirtschaftsinformatik,
February 2022, Nürnberg, Germany
Knowledge Work ‘Unplugged’ - Digital Detox Effects on
ICT Demands, Job Performance and Satisfaction
Milad Mirbabaie1, Lea-Marie Braun2, Julian Marx2
1 Paderborn University, Department of Information Systems, Paderborn, Germany
{milad.mirbabaie}@uni-paderborn.de
2 University of Duisburg-Essen, Department of Computer Science and Applied Cognitive
Science, Duisburg, Germany
{lea-marie.braun, julian.marx}@uni-due.de
Abstract. Information and communication technologies (ICT) have gained
immense importance in the world of work. Knowledge workers, however, do not
only benefit from ICT use. One drawback is the so-called ICT availability
demand which is associated with a constant pressure to be online, including after-
work time. This demand can have severe consequences on the individual such as
impaired wellbeing, harmed job performance and satisfaction. This paper
scrutinizes the extent to which digital detox, a periodic disconnection from
technology, can support knowledge workers to prevent and cope with ICT
availability demands. A two-week online experiment was conducted to measure
the effects of digital detox in the context of knowledge work. The results indicate
a significant decrease in ICT availability demands after conducting digital detox.
Moreover, this paper derives theoretical and practical implications about how
digital detox can be understood and applied in organizational contexts.
Keywords: Digital Detox, ICT Availability Demands, Job Performance, Job
Satisfaction
1 Introduction
As a result of a highly digitized professional world, knowledge workers are confronted
with information and communication technologies (ICT) on a daily basis [1]. ICT use
is a key area of interest in Information Systems (IS) research and practice as its study
often determines the effectiveness of such technologies [2]. A radical transformation of
work has been associated with ICT, leading to faster communication and multiplied
ways of connection especially among knowledge workers [3] whose professions are
based on knowledge creation, diffusion and utilization [4]. The use of ICT warrants
knowledge workers more flexibility [5] and organizations foster ICT-related work
arrangements in form of remote work and “bring your own device” policies to support
their employees’ productivity [6].
Despite greater flexibility, ICT use in professional contexts is also associated with
work intensification, leading to constant availability [7] and more interruptions. Social
norms of availability expectations are highly likely to arise, blurring boundaries
between professional and private life [9]. As a result, the intensive availability
expectations due to ICT has spawned the concept of ICT demands in recent IS
scholarship [10–12]. In general, ICT demands are portrayed by potential ICT-related
stressors in the working context [10], including ICT availability demands to be
accessible via ICT in response to work-related requirements during off-work time and
the expectations to respond in a timely manner [13, 14]. ICT availability demands can
impact knowledge workers’ experience negatively [15]. This includes, for example,
difficulties with concentration, memory, decision-making, and the ability to think
clearly [8, 16]. When continuously experiencing ICT availability demands, research
suggests that ICT availability demands correlate with employees’ psychological and
physiological distress [17]. Moreover, the effects of ICT availability demands impact
workers’ productivity and work withdrawal negatively [18, 19]. In this context, workers
perceiving high demands are more likely to experience pressure in the workplace and
are harmed in their wellbeing which can ultimately lead to burnout [13]. Due to blurring
lines between work and private life, knowledge workers have difficulties detaching
completely from work in their free time, causing a lack of recovery from work which
can impair their ability to refill resources for future work-related activities [20].
Due to negative consequences from ICT availability demands on knowledge
workers, organizations are required to propose a remedy for this problem to reduce ICT
availability demands among their personnel. The emerging practice of digital detox
[21], we argue, represents a possibility to reduce and control ICT availability demands
because it provides strategies to prevent and cope with ICT-related secondary effects
[22]. Digital detox is defined as a periodic disconnection from technologies and
attempts to regulate technology involvement by reducing communication overload and
technology overuse [21]. Knowing that digital detox can be used to mitigate
physiological distress [23] and support individual performance at the workplace [24],
in this study, we extrapolate the concept on the context of ICT availability demands.
Thus, the aim of this paper is to answer the following research question:
RQ: How does digital detox impact the ICT availability demands of knowledge
workers?
We approach this research question with the help of an online experiment conducted
over for two weeks in which knowledge workers were asked to include digital detox
strategies in their working life for one of those weeks. A within-subject design was
chosen to measure the impact of digital detox on ICT availability demands, job
performance and job satisfaction. Both theory and practice can benefit immensely from
the outcome of the study. Knowledge workers face intensive ICT availability demands;
thus, it is crucial to identify and test strategies that support affected knowledge workers
in preventing and coping with the demands. This paper adds to knowledge by
introducing digital detox to the ICT demands literature and providing evidence about a
possible theoretical relationship between the two concepts. Practically, the study
provides important implications for the management of ICT as organizations
increasingly experience travails with the costs associated with ICT availability
demands, impacting their employees’ private and professional lives.
The remainder of this paper is structured as follows. In section 2, we review related
work on ICT availability demands in knowledge work environments. We further
explain digital detox and derive hypotheses. Section 3 outlines the research design in
detail. The results of the online experiment are presented in section 4, enabling the
discussion of the results and implications for theory and practice in section 5. We
conclude with a summary, limitations, and future work in section 6.
2 Background
2.1 ICT Availability Demands and Knowledge Work
ICT are defined as technologies or devices that have the capacities to acquire, store,
process, or transmit information [3]. In the workplace, ICT have been characterized as
a double-edged sword [25]. On the one hand, ICT support knowledge workers in their
efficiency and facilitates the working process [1, 15]. On the other hand, ICT demands
are associated with additional problems for knowledge workers and an increased level
of stress [26]. In this regard, ICT create expectations of higher productivity [26] and
accessibility [18]. Such negative aspects of ICT demands can lead to negative personal
and organizational outcomes such as decreased job performance and job satisfaction,
increased levels of stress, as well as harmed wellbeing [27].
Workplace ICT demands are defined as “[…] any ICT factor or process at work
involving some type of storing, transmitting, or processing technology (e.g., computer
programs) or device (e.g., computer) that have the potential to be perceived as stressful
by workers” [27]. Whether ICT demands are perceived as stressful is dependent on
various factors such as cognitive or mental capacities among the workers. In detail, ICT
demands mirror the access to a large amount of information, ICT hassles, poor
communication, response expectation or constant availability. This paper puts
availability demands, a sub-concept of ICT demands, into focus as it has severe
consequences on the individual, but considered in isolation, shows great potential to be
controlled by focused strategies. ICT availability demands refer to demands for workers
to be constantly available and accessible, even outside of work hours [14].
ICT availability demands can put forth an “always-on”-expectation, leading to
working conditions that place an additional work demand on knowledge workers [28].
Perceived availability expectations have been associated with increased knowledge
workers’ ICT behaviors, as recent research demonstrated [29]. Thus, knowledge
workers feel forced to check work-related emails continuously. Constant availability
and accessibility at work can further lead to high levels of engagement with work in the
free time [27]. As a result, ICT availability demands take up a great proportion of a
knowledge worker’s internal resources, which, in turn, diminishes work outcomes [20].
In particular, being away from work but still being unable to mentally switch off from
work-related contents impedes recovery and can ultimately harm individual wellbeing
[30], and increasing the likelihood of burnout [31]. Moreover, the pressure of constant
availability can lead to an overwhelming urge to respond immediately to work-related
ICT messages, even outside of regular working hours [32] which can affect employees’
health and work-life balance negatively [6]. Further, repeated exposure to ICT
availability demands at work can lead to an insufficient self-rated health among
employees [33]. Research suggests to consider ICT availability demands carefully as
the resulted pressure due to ICT availability demands can increase the chance work-
family conflict [13].
Due to the negative consequences of ICT availability demands, support for
knowledge workers is needed to be provided by organizations to help them cope with
ICT availability demands or to find prevention measures against them. A related but in
this context not yet empirically tested concept is digital detox.
2.2 Digital Detox in the Context of Work
Digital detox is defined as “[…] efforts to take a break from online or digital media for
a longer or shorter period, as well as other efforts to restrict the use of smartphones
and digital tools” [21]. The reasons for individuals practicing digital detox are to not
be reachable for a while or to have more time for other activities [23]. By that,
individuals use technologies and software more efficiently to reduce digital distraction
[23, 24]. Recent research has investigated the effectiveness of digital detox with a two-
week experiment where participants had to practice digital detox for one week [34].
The results showed that physiological stress was reduced due to digital detox.
Therefore, digital detox qualifies as a possible coping mechanism for individuals who
experience stress due to ICT [23].
Regarding ICT availability demands in the work context, research has already
suggested strategies which aim to tackle availability demands to minimize negative
consequences on employees. For example, it has been declared that one way to handle
response expectations and ongoing interruptions due to ICT which can lower job
performance is to reserve times where emails and instant messaging can be checked
[19]. To cope with constant availability, research stresses the importance to change
organizational policies and culture, encouraging employees to take time off after
closing hours [19]. In this regard, the management could introduce guidelines that
explicitly discourage work communication beyond working hours [35].
The outlined strategies aim to abandon technologies periodically to focus more on
the ongoing activity and take time off from work. Thus, they are in line with the idea
of digital detox [21]. Digital detox has been found to be effective in decreasing
physiological stress caused by technology overconsumption [23]. It is different to
existing ICT demand regulation techniques because it 1) encompasses not only coping
but also prevention strategies, (2) offers strategies that are not bound to personality
traits such as a high ability of self-regulation, and 3) provides a notion that does not
need to distinguish between work and off-time but offers, in addition to selective
strategies, a spectrum of holistic individual and organizational measures. However, it
has not been empirically tested to which extent digital detox is promising in coping
with and preventing ICT availability demands. Based on the presented insights in ICT
availability demands and digital detox literature, we propose that digital detox can
lower the adverse perception of ICT availability demands in the context of knowledge
work. Hence, we derive the following hypothesis:
H1: Digital detox lowers ICT availability demands of knowledge workers compared
to when no digital detox is conducted.
As outlined before, the respective ICT availability demands can influence workers’
job performance negatively. Interruptions due to ICT, for example, disrupt the process
and continuity of working tasks and brings the work to a periodic pause [16]. By that,
the involvement with the task can be impaired and especially when working on complex
and demanding tasks, which are often included in the context of knowledge work,
performance can be decreased immensely [16, 36]. As digital detox helps to focus more
on the current activity, it might help improve job performance by controlling ICT
availability demands. Therefore, it can be assumed that digital detox increases job
performance, partially due to decreased ICT availability demands. Thus, the second
hypothesis is:
H2: The positive relationship between digital detox and job performance is mediated
by ICT availability demands.
Research has shown that that increased demands at work can lead to decreased job
satisfaction [16]. ICT availability demands support the pressure to be accessible and
increase the workload by providing a great amount of information. All this leads to
workers experiencing strain, which can lead to dissatisfaction [16, 37]. Following the
line of argumentation of hypothesis two, it can be assumed that when ICT availability
demands decrease due to digital detox, job satisfaction might indirectly grow due to
controlling and/or abandoning ICT. This assumption leads us to our third hypothesis:
H3: The positive relationship between digital detox and job satisfaction is mediated
by ICT availability demands.
3 Research Design
3.1 Sample and Procedure
To answer the research question and investigate the derived hypotheses, an
experimental setting has been developed which we expound in detail in this section.
The experiment was designed to be conducted remotely and to last for 14 sequential
days. A within-subject design was developed to compare ICT availability demands, job
performance and job satisfaction from the same participants between different
conditions. To participate, it was required to have a permanent job in the context of
knowledge work and to be confronted with ICT regularly. The procedure of the
experiment is presented in Figure 1.
Figure 1. Procedure of the Experiment
Survey:
•ICT Availability Demands
•Job Performance
•Job Satisfaction
Information:
•Start of Study
•Proceeding FridayMonday No Digital Detox
Friday
Survey:
•ICT Availability Demands
•Job Performance
•Job Satisfaction
Monday
Instructions:
•Digital Detox
•Application Digital Detox
WEEK 1
WEEK 2
In the first week, the participants were asked to work as usual. They received the
first survey via email at the end of the first week (Friday) which they could fill out in
their personal time. In the early morning of the Monday of the second week, instructions
of how to conduct a digital detox were sent to the participants via email. By that, it was
assured that participants received the mail before starting their workday. They were
asked to include digital detox each day they are working within this week. On the Friday
of the second week, the last survey with the same measures was sent to the participants
and marked the end of the experiment.
The participants were recruited via social media as well as via a forum from the
(blinded for the review). The language of the survey was German. The survey started
on the 7th of December and ended two weeks later on the 18th. In total, 47 participants
took part in the experiment of which four had to be excluded as they abandoned the
experiment. Out of the remaining 43 participants, 81.4% were female and 18.6% male.
The mean age was 23.86 (SD = 4.05) with a range from 18 to 34. Most of the
participants (69,8%) graduated from school with an Abitur. 10 (23,3%) participants had
a bachelor’s degree and 4.7% a master’s degree. One (2.3%) participant graduated from
school with a technical college entrance qualification. Moving to the working situation
of the participants, 48.8% were student assistants, 34.9% were part-time employees and
14.0% full-time employees. Lastly, 2.3% were full-time employees in a leading
position. Most of the participants (44.2%) have worked in their organization for at least
two years. 18.6% of the participants have worked in their organization for one year,
18.6% for three months, 14.0% for three years and 2.3% in each case for 5 years and 6
months. When asking how familiar the participants already are with the concept of
digital detox, 14.0% have not heard about a digital detox before. 46.5% stated that they
have heard about the concept before but do not exactly know what it is about. 34.9%
indicated to be familiar with the concept but not to have conducted a digital detox
themselves and 4.7% were very familiar with the concept.
3.2 Material
As the aim was to introduce digital detox to knowledge workers and measure its impact
on ICT availability demands, job satisfaction and job performance, instructions had to
be developed presenting how to conduct a digital detox. Four strategies were introduced
to the participants that have different degrees of intervention. In this study, we focused
on varying the dimension of time (breaks, appointments, off-work hours, constantly) as
opposed to components (devices, applications) as two distinct dimensions of digital
detox as described by [38].
• Digital detox during breaks (Strategy A): Refrain from work-related
contents completely during your lunch break. Use the time to clear your head
and do not get disturbed by emails, messages, or phone calls.
• Digital detox after working hours (Strategy B): Refrain from any work-
related contents after working hours. This includes private conversations with
colleagues. Do not check your email, other messages, or phone calls. Enjoy
your evening off and don't let your work interrupt you.
• Digital detox as an appointment (Strategy C): Set a fixed time in your
calendar that makes it clear to your colleagues that you do not want to be
disturbed. You can use this time to complete your tasks without being
interrupted. Only when this appointment has expired, you can check your
messages and emails again.
• Digital detox by turning off push-notifications (Strategy D): Turn off all
your push-notifications for a certain period so that you are not disturbed for
that time. Use this time to work effectively on your tasks. Only when your set
time is over, you can check your messages and emails again.
Further, instructions of how to use the digital detox strategies were written. It was
stressed that the participants of the study were allowed to choose the strategy they
preferred. They were also allowed to use all strategies and switch them from day to day.
Next to these instructions, a protocol was sent to the participants where they could note
which strategy they chose for which day and to report their experiences (such as
success, disruptions, failures) with digital detox. In fact, it was stressed that failing to
conduct a digital detox would not exclude from participating in the study. This should
ensure that participants report their experiences honestly.
3.3 Measures
Suitable questionnaires were selected from previous research to measure ICT
availability demands, job performance, and job satisfaction, respectively.
ICT Availability Demands was measured with two subscales from the ICT
demands questionnaire, response expectation and availability [16]. One example item
would be: “I am expected to respond to email messages immediately”. The six
statements of ICT availability demands were measured using a 5-point frequency scale
ranging from (0) never to (4) almost always. Relying on Cronbach’s alpha, the internal
reliability was good for the two times of measurement, ICT availability demands (1) ɑ
= .83, ICT availability demands (2), ɑ = .77.
Job Performance was measured with the job performance scale [39]. The scale
consisted of 18 items like “I managed to plan my work so that I finished it on time”.
All statements were measured using a 5-point frequency scale ranging from (0) never
to (4) almost always. The internal reliability for the two times of measurement was
good, job performance (1) ɑ = .71, job performance (2) ɑ = .94.
Job Satisfaction was measured with a short version containing eight items [40].
“My work is not much fun, but you should not expect too much” would be one example
item. Participants could agree or disagree with the statement using a 5-point Likert scale
of agreement (1 = completely disagree, 5 = completely agree). For both measuring
times, the Cronbach’s values showed good internal reliability, job satisfaction (1) ɑ =
.71, job satisfaction (2), ɑ = .93.
4 Results
The statistical analysis was carried out by using SPSS 27.0 for MacOS. Additionally,
the computational tool and SPSS plugin PROCESS v3.5 was used for the mediator
models [41]. As a first step of the analysis, the needed variables were calculated after
checking the respective Cronbach’s alpha values of the scales for the two times of
measurements. ICT availability demands (1) and (2), job performance (1) and (2) as
well as job satisfaction (1) and (2) were calculated by building the mean of the
respective number of items. The descriptive statistics for the variables are summarized
Table 1. Normal distribution was checked and could be assumed for each variable for
two times of measurement, ICT availability demands (1) p = .200, (2) p = .124; job
performance (1) p = .42, (2) p = .29; job satisfaction (1) p = .39, (2) p = .43 (reporting
Shapiro-Wilk-Test).
Table 1. Descriptive Statistics for ICT Availability Demands, Job Performance and Satisfaction
Variables for two times of
measurement
M
SD
Min
Max
ICT Availability Demands (1)
2.29
0.89
.67
4.00
ICT Availability Demands (2)
1.84
0.81
0.00
3.83
Job Performance (1)
2.06
0.47
1.17
3.33
Job Performance (2)
2.44
0.82
0.83
4.00
Job Satisfaction (1)
3.45
0.77
1.75
5.00
Job Satisfaction (2)
3.40
0.76
1.63
4.88
During the second survey, the participants were asked which digital detox strategy
they chose in total. Figure 2 shows how often the different strategies were chosen,
revealing that digital detox after working hours was selected the most, followed by
digital detox during breaks and digital detox by turning off push-notifications. The
strategy digital detox as an appointment was chosen the least.
Figure 2. Usage of Digital Detox Strategies
An ANOVA with repeated-measures was conducted with ICT availability demands
as a within-factor to test the first hypothesis. Mauchly’s sphericity could be assumed.
22
33
7
21
0
5
10
15
20
25
30
35
During Breaks After Working Hours As an Appointment Turning off Notifications
Usage of Digital Detox Strategies
It was found that a digital detox had a significant influence on ICT availability demands.
When no digital detox was conducted, the ICT availability demands were higher (M =
2.29, SD = 0.89) and decreased significantly within the week a digital detox was
conducted (M = 1.84, SD = .81), F(1, 42) = 11.93, p = .001, ηp2 = .221. Thus, hypothesis
1 can be seen as confirmed. We further tested whether prior experience with digital
detox influenced the result of decreased ICT availability demand by running an
ANOVA with experience as the dependent variable and ICT availability demands (2)
as the dependent variable. No difference in ICT availability demands could be depicted,
F = 0.48, p = .49.
To test hypothesis 2 and 3, two mediation analyses were carried out with digital
detox as the predictor, job performance (H2) and job satisfaction (H3) as the criterium,
respectively, and ICT availability demands as the mediator. For that, the data has been
restructured to be able to predict the extent to which digital detox influences job
performance and satisfaction and whether the direct paths would be mediated by ICT
availability demands. For both calculations, multicollinearity could not be assumed
with correlations between all variables involved lower than .7. Starting with hypothesis
2, the overall model was significant, F (1, 82) = 6.12, p = .014, predicting 6.94% of the
variance. An effect of digital detox on job performance was found, B = .44, p = .008.
After entering the mediator ICT availability demands into the model, digital detox
predicted the mediator significantly, B = -2.74, p = .015, which, however, did not
predict job performance, B = -.03, p = .824. The relationship between digital detox and
job performance was still significant after entering the mediator, B = .43, p = .005. As
there was no effect between ICT availability demands and job performance, we rejected
the hypothesis. Moving to job satisfaction, the overall model was significant, F (1, 82)
= 6.12, p = .015. No total effect of digital detox on job satisfaction was observed, B = -
04, p = .794. As reported before, digital detox predicted ICT availability demands,
which could not predict job satisfaction, B = .01, p = .860. We rejected hypothesis 3.
5 Discussion
5.1 Reducing ICT Availability Demands
Motivated by the negative consequences of ICT availability demands on knowledge
workers [27, 28], such as impaired job performance and satisfaction, this research aims
to examine digital detox as a prevention measure. Knowing that digital detox can reduce
stress [34], a gap in research was revealed of how digital detox can impact ICT
availability demands among knowledge workers. A research design was developed, and
a two-week experiment conducted to test the derived hypotheses which closed the
research gap by answering the research question. This research contributes by providing
a theoretical understanding of how digital detox influences ICT availability demands,
job performance and satisfaction.
Even though knowledge workers benefit from ICT use as they support working
processes [1, 3], knowledge workers also have to deal with ICT availability demands
which can lead to increased levels of stress [26]. We suggested that a digital detox has
the potential to prevent the perception of ICT availability demands to be evaluated
negatively and by that, supporting job performance and satisfaction and tested this
assumption quantitively. Relying on the results, we found that digital detox conducted
for one week has indeed the potential to decrease ICT availability demands.
Due to accessibility, workers feel the pressure to be constantly connected and
reachable, even after working hours [42]. As a result, affected individuals feel strained
from technologies and are unable to mentally detach from work after work hours [27].
Relying on our results, digital detox has the potential to prevent and manage the need
of constant connectedness. One way to implement digital detox is to abandon all work-
related technologies and contents after working hours. By that, the pressure of being
online in the own free time can be decreased as digital detox guides workers through it.
By that, workers can mentally detach from work which is crucial in order to relax and
gather new energy for the next day [13]. Moreover, digital detox can help knowledge
workers to deal with interruption due to ICT during the working day [14]. In this regard,
digital detox can help to control communication to support knowledge workers’
wellbeing and prevent stress. A digital detox can be used to turn-off all push-
notifications and by that, communication is controlled, and push-notifications do not
interrupt the working day frequently. Time can be saved to return to the task after an
incoming push-notification and concentration can be upheld. Furthermore, a digital
detox provides room and space to deal with communication when the worker has the
capacity for it. When, for example, a knowledge worker is involved in an important
work task and puts all its concentration on it, an incoming message can disrupt the
working flow and the message might be evaluated negatively [43]. The consequence
might be an answer written down in a hasty and maybe hostile manner [44]. However,
when digital detox prevents the working flow to be interrupted, the worker reads the
new messages when having time and capacities. In turn, more thoughtful and well-
grounded answers might be the result.
Regulating ICT availability demands is not only crucial for knowledge workers’
wellbeing but also to ensure job performance and job satisfaction. When being stressed
by ICT availability demands, it can harm job performance and satisfaction [14, 36, 37].
Thus, we presumed that a digital detox can indirectly influence job performance and
satisfaction positively. However, our results did not indicate any relationship between
ICT availability demands and job performance or job satisfaction. When ICT
availability demands lowered during the time of the experiment, no change in job
performance or satisfaction could be predicted. We found, however, that a digital detox
by itself was able to predict job performance significantly. When a digital detox was
conducted, job performance increased accordingly. This finding mirrors the importance
of introducing digital detox in knowledge work arrangements and stresses the need for
future research on this matter. Job performance is not only dependent on ICT
availability demands but on several other factors such as technostress [45], emotional
exhaustion or work overload [46, 47]. Thus, it can be assumed that digital detox
restrains one of these or other factors determining job performance, explaining the
increase of it. Future research could start here and examine the influence of digital detox
on different factors important for knowledge workers’ everyday experience. Regarding
job satisfaction, no change could be observed when introducing digital detox. It might
be the case that job satisfaction needs a longer period to be changed and enhanced. The
digital detox, however, was only conducted for one week which might be too concise
to change the overall perception of being satisfied with the current work situation.
Going in another direction, job satisfaction does not only rely on ICT availability
demands, but also on interpersonal relationships between co-workers [48, 49]. Thus,
even when lowering ICT availability demands, job satisfaction might not increase
because influencing factors such as interpersonal relationships might be negatively
impacted by digital detox caused by reduced social interactions. Future research could
rely on these assumptions and examine digital detox in a long run as well as its effects
on interpersonal relationships.
5.2 Theoretical and Practical Implications
The findings of this study have important theoretical implications for IS research,
especially concerning ICT demands, digital detox, and knowledge work. This paper
adds important insights to the ICT demands literature by investigating the new arising
concept of digital detox. Research has already shown that ICT availability demands can
have severe consequences on job performance and satisfaction [27, 28], thus, is
crucially needed to be tackled. We can conclude that digital detox is able to reduce ICT
availability demands, reducing the pressure of constant availability among knowledge
workers. Even though we did not find any change of job performance and satisfaction
due to reduced ICT availability demands, we depicted an increase of job performance
due to digital detox by itself. Further, the paper gives insights in the mechanism beyond
ICT availability demands. A digital detox does not change the frequency or
interruptions of the availability demands. It is much more a change of perception
regarding the demands. ICT availability demands exist, whether workers digital detox
or not, but digital detox helps individuals to not evaluate the demands negatively.
Instead, a digital detox can support individuals in dealing with ICT demands so that
distress does not occur.
The paper contributes to practice as well by providing several important implications
for organizations. Both the management and employees need to be aware of the costs
associated with ICT availability demands. Especially the management should take
negative consequences of these demands into account when establishing organizational
policies. Relying on our results, we strongly suggest including digital detox into work
arrangements as it has the potential to minimize ICT availability demands. When
management supports employees in conducting digital detox, distress due to ICT can
be prevented, enhancing job performance and satisfaction, so that, in turn, managers
profit from digital detox as well. We suggest that organizations consider reinforcing
policies that complicate work-related interactions after closing hours. When digital
detox is supported by organizations, the organizational climate changes so that
employees feel comfortable leaving work behind in their free time. Further,
organizations need to be aware of the social norms and expectations concerning
availability. With implementing digital detox, organizations set a tone that takes away
the pressure of constant connection and accessibility which, in turn, will foster
sustainable wellbeing among knowledge workers.
6 Conclusion, Limitations and Future Research
ICT availability demands are associated with a strong pressure on knowledge workers,
inducing constant availability, lack of control, poor communication, and information
overload. All this can lead to an impaired individual wellbeing, loss in job performance
and satisfaction. We suggested digital detox as a prevention and coping measure for
knowledge workers affected by ICT availability demands. The results of a two-week
experiment indicate lowered ICT availability demands due to digital detox. Thus, we
propose digital detox as a useful tool and concept to be subject to future IS research.
The paper is not free from limitations. The first part of the limitations addresses the
sample of participants whose mean age was rather young (M = 23.86). Also, more
females took part in the study than males. Previous research has shown that digital
detox influences people of different age ranges and gender differently [50, 51]. Thus,
further research should include workers of all age ranges to understand the influence of
digital detox in all facets and assure an equal gender distribution. In the present study,
participants were allowed to take part when working at least two days per week. Also,
the job description was not documented. Further research should include a sample of
only full-time employees as they might be affected the most of ICT availability
demands and, consequently, digital detox. The particular job descriptions should be
surveyed as well to understand digital detox in different disciplines. The second part of
the limitations addresses the research design. Whether the participants conducted a
digital detox or not was measured by self-reports. Even though the instructions stressed
that participants were not excluded from the study when failing in conducting the detox,
participants might still have portrayed their conduct better than it actually was. Still, as
the study was carried out online, the concept of self-reporting was the best choice as
monitoring devices, for example, would have restrict the participants’ privacy
immensely. Further, including a control group where participants do not digitally detox
could address the self-report and other simultaneity biases such as framing in the study
which should be considered for further research. The length of the experiment can be
criticized as it only lasted for two weeks of which one week was allocated for digital
detox. Thus, the results should be seen as first directions and need to be replicated with
a longitudinal study to understand the long-term effects of digital detox. Lastly, the
experiment was conducted in a time where COVID-19 has lasted already for
approximately half a year and individuals had time to adjust to the new situation. Still,
the results might have been different without the world-wide pandemic. The situation
in general might have led to a higher level of stress among employees working remotely
from home [52]. Thus, the cognitive and emotional consequences form the pandemic
COVID-19 must be considered when interpreting the current results.
Based on the findings, the concept of digital detox holds a major potential for future
IS research. We included four different digital detox strategies to tackle ICT availability
demands. Future work can conduct an experiment testing the different strategies against
each other. Results could yield distinctive guidelines aiming for supporting employees
individually based on their working situation and life circumstances.
References
1. Harris, K.J., Harris, R.B., Valle, M., Carlson, J., Carlson, D.S., Zivnuska, S., Wiley, B.:
Technostress and the entitled employee: impacts on work and family. Inf. Technol.
People. (2021). https://doi.org/10.1108/ITP-07-2019-0348.
2. Ali-Hassan, H., Nevo, D., Wade, M.: Linking dimensions of social media use to job
performance: The role of social capital. J. Strateg. Inf. Syst. 24, 65–89 (2015).
https://doi.org/10.1016/j.jsis.2015.03.001.
3. Baptista, J., Stein, M.K., Klein, S., Watson-Manheim, M.B., Lee, J.: Digital work and
organisational transformation: Emergent Digital/Human work configurations in modern
organisations. J. Strateg. Inf. Syst. 29, 1–10 (2020).
https://doi.org/10.1016/j.jsis.2020.101618.
4. Kianto, A., Shujahat, M., Hussain, S., Nawaz, F., Ali, M.: The impact of knowledge
management on knowledge worker productivity. Balt. J. Manag. 14, 178–197 (2019).
https://doi.org/10.1108/BJM-12-2017-0404.
5. Palvalin, M., Lönnqvist, A., Vuolle, M.: Analysing the impacts of ICT on knowledge
work productivity. J. Knowl. Manag. 17, 545–557 (2013). https://doi.org/10.1108/JKM-
03-2013-0113.
6. Santuzzi, A.M., Barber, L.K.: Workplace Telepressure and Worker Well-Being: The
Intervening Role of Psychological Detachment. Occup. Heal. Sci. 2, 337–363 (2018).
https://doi.org/10.1007/s41542-018-0022-8.
7. Barley, S.R., Meyerson, D.E., Grodal, S.: E-mail as a source and symbol of stress.
Organ. Sci. 22, 887–906 (2011). https://doi.org/10.1287/orsc.1100.0573.
8. Chesley, N.: Information and communication technology use, work intensification and
employee strain and distress. Work. Employ. Soc. 28, 589–610 (2014).
https://doi.org/10.1177/0950017013500112.
9. Derks, D., Bakker, A.B.: Smartphone Use, Work-Home Interference, and Burnout: A
Diary Study on the Role of Recovery. Appl. Psychol. 63, 411–440 (2014).
https://doi.org/10.1111/j.1464-0597.2012.00530.x.
10. Stadin, M., Nordin, M., Broström, A., Magnusson Hanson, L.L., Westerlund, H.,
Fransson, E.I.: Information and communication technology demands at work: the
association with job strain, effort-reward imbalance and self-rated health in different
socio-economic strata. Int. Arch. Occup. Environ. Health. 89, 1049–1058 (2016).
https://doi.org/10.1007/s00420-016-1140-8.
11. Seo, H.J., Lee, Y.S., Hur, J.J., Kim, J.K.: The impact of information and communication
technology on skilled labor and organization types. Inf. Syst. Front. 14, 445–455 (2012).
https://doi.org/10.1007/s10796-010-9276-7.
12. Stadin, M., Nordin, M., Broström, A., Hanson, L.L.M., Westerlund, H., Fransson, E.I.:
Technostress operationalised as information and communication technology (ICT)
demands among managers and other occupational groups–results from the Swedish
longitudinal occupational survey of health (SLOSH). Comput. Human Behav. 114,
106486 (2021).
13. Kao, K.Y., Chi, N.W., Thomas, C.L., Lee, H.T., Wang, Y.F.: Linking ICT Availability
Demands to Burnout and Work-Family Conflict: The Roles of Workplace Telepressure
and Dispositional Self-Regulation. J. Psychol. Interdiscip. Appl. 154, 325–345 (2020).
https://doi.org/10.1080/00223980.2020.1745137.
14. Day, A., Paquet, S., Scott, N., Hambley, L.: Perceived information and communication
technology (ICT) demands on employee outcomes: The Moderating effect of
organizational ICT support. J. Occup. Health Psychol. 17, 473–491 (2012).
https://doi.org/10.1037/a0029837.
15. Morgan, K., Morgan, M., Hall, J.: Psychological developments in high technology
teaching and learning environments. Br. J. Educ. Technol. 31, 71–79 (2000).
https://doi.org/10.1145/1050330.1050438.
16. Day, A., Paquet, S., Scott, N., Hambley, L.: Perceived information and communication
technology (ICT) demands on employee outcomes: The moderating effect of
organizational ICT support. J. Occup. Health Psychol. 17, 473–491 (2012).
https://doi.org/10.1037/a0029837.
17. Dettmers, J., Vahle-Hinz, T., Bamberg, E., Friedrich, N., Keller, M.: Extended work
availability and its relation with start-of-day mood and cortisol. J. Occup. Health
Psychol. 21, 105–118 (2016). https://doi.org/10.1037/a0039602.
18. Tarafdar, M., Tu, Q., Ragu-Nathan, B.S., Ragu-Nathan, T.S.: The impact of technostress
on role stress and productivity. J. Manag. Inf. Syst. 24, 301–328 (2007).
https://doi.org/10.2753/MIS0742-1222240109.
19. Stich, J.F., Farley, S., Cooper, C., Tarafdar, M.: Information and communication
technology demands: outcomes and interventions. J. Organ. Eff. 2, 327–345 (2015).
https://doi.org/10.1108/JOEPP-09-2015-0031.
20. Bakker, A.B., Demerouti, E.: The Job Demands-Resources model: State of the art. J.
Manag. Psychol. 22, 309–328 (2007). https://doi.org/10.1108/02683940710733115.
21. Syvertsen, T., Enli, G.: Digital detox: Media resistance and the promise of authenticity.
Converg. Int. J. Res. into New Media Technol. 1–15 (2019).
https://doi.org/10.1177/1354856519847325.
22. Wilcockson, T.D.W., Osborne, A.M., Ellis, D.A.: Digital detox: The effect of
smartphone abstinence on mood, anxiety, and craving. Addict. Behav. 99, 2–5 (2019).
https://doi.org/10.1016/j.addbeh.2019.06.002.
23. Anrijs, S., Bombeke, K., Durnez, W., Van Damme, K., Vanhaelewyn, B., Conradie, P.,
Smets, E., Cornelis, J., De Raedt, W., Ponnet, K., De Marez, L.: MobileDNA: Relating
physiological stress measurements to smartphone usage to assess the effect of a digital
detox. Commun. Comput. Inf. Sci. 356–363 (2018). https://doi.org/10.1007/978-3-319-
92279-9_48.
24. Basu, R.: Impact of Digital Detox on Individual Performance of the Employees. Int. J.
Res. Anal. Rev. 6, 378–381 (2019).
25. Lowry, D., Moskos, M.: Hanging on the Mobile Phone: Experiencing Work and Spatial
Flexibility. Natl. Inst. Labour Stud. 0–19 (2006).
26. Wang, K., Shu, Q., Tu, Q.: Technostress under different organizational environments:
An empirical investigation. Comput. Human Behav. 24, 3002–3013 (2008).
https://doi.org/10.1016/j.chb.2008.05.007.
27. Day, A., Scott, N., Kelloway, E.K.: Information and communication technology:
Implications for job stress and employee well-being. In: New developments in
theoretical and conceptual approaches to job stress. Emerald Group Publishing Limited
(2010).
28. Park, Y.A., Fritz, C., Jex, S.M.: Relationships Between Work-Home Segmentation and
Psychological Detachment From Work: The Role of Communication Technology Use
at Home. J. Occup. Health Psychol. 16, 457–467 (2011).
https://doi.org/10.1037/a0023594.
29. Grawitch, M.J., Werth, P.M., Palmer, S.N., Erb, K.R., Lavigne, K.N.: Self-imposed
pressure or organizational norms? Further examination of the construct of workplace
telepressure. Stress Heal. 34, 306–319 (2018). https://doi.org/10.1002/smi.2792.
30. Sonnentag, S., Fritz, C.: Recovery from job stress: The stressor-detachment model as an
integrative framework. J. Organ. Behav. 36, 72–103 (2015). https://doi.org/10.1002/job.
31. Barber, L.K., Santuzzi, A.M.: Please respond ASAP: Workplace telepressure and
employee recovery. J. Occup. Health Psychol. 20, 172–189 (2015).
https://doi.org/10.1037/a0038278.
32. Park, Y., Liu, Y., Headrick, L.: Improving lives of teachers: Staying connected to work,
work-family boundary control, and strain. 78th Annu. Meet. Acad. Manag. AOM 2018.
(2018). https://doi.org/10.5465/AMBPP.2018.7.
33. Stadin, M., Nordin, M., Broström, A., Magnusson Hanson, L.L., Westerlund, H.,
Fransson, E.I.: Repeated exposure to high ICT demands at work, and development of
suboptimal self-rated health: findings from a 4-year follow-up of the SLOSH study. Int.
Arch. Occup. Environ. Health. 92, 717–728 (2019). https://doi.org/10.1007/s00420-
019-01407-6.
34. Anrijs, S., Bombeke, K., Durnez, W., Van Damme, K., Vanhaelewyn, B., Conradie, P.,
Smets, E., Cornelis, J., De Raedt, W., Ponnet, K., De Marez, L.: MobileDNA: Relating
physiological stress measurements to smartphone usage to assess the effect of a digital
detox. In: Proceedings of the International Conference on Human-Computer Interaction
(HCI). pp. 356–363 (2018). https://doi.org/10.1007/978-3-319-92279-9_48.
35. Wright, K.B., Abendschein, B., Wombacher, K., O’Connor, M., Hoffman, M.,
Dempsey, M., Krull, C., Dewes, A., Shelton, A.: Work-Related Communication
Technology Use Outside of Regular Work Hours and Work Life Conflict: The Influence
of Communication Technologies on Perceived Work Life Conflict, Burnout, Job
Satisfaction, and Turnover Intentions. Manag. Commun. Q. 28, 507–530 (2014).
https://doi.org/10.1177/0893318914533332.
36. Wang, B., Liu, Y., Qian, J., Parker, S.K.: Achieving Effective Remote Working During
the COVID-19 Pandemic: A Work Design Perspective. Appl. Psychol. 70, 16–59
(2021). https://doi.org/10.1111/apps.12290.
37. Cho, S., Kim, S., Chin, S.W., Ahmad, U.: Daily effects of continuous ICT demands on
work–family conflict: Negative spillover and role conflict. Stress Heal. 36, 533–545
(2020). https://doi.org/10.1002/smi.2955.
38. Radtke, T., Apel, T., Schenkel, K., Keller, J., von Lindern, E.: Digital detox: An
effective solution in the smartphone era? A systematic literature review. Mob. Media
Commun. (2021). https://doi.org/10.1177/20501579211028647.
39. Ramos-Villagrasa, P.J., Barrada, J.R., Fernandez-del-Rio, E., Koopmans, L.: Assessing
Job Performance Using Brief Self-report Scales : The Case of the Individual Work
Performance Questionnaire. J. Work Organ. Psychol. 35, 195–205 (2019).
40. Fischer, L., Lück, H.E.: Allgemeine Arbeitszufriedenheit. Zusammenstellung
sozialwissenschaftlicher Items und Skalen. 1–11 (2014).
41. Hayes, A.F., Preacher, K.J.: Conditional process modeling: Using structural equation
modeling to examine contingent causal processes. In: Structural equation modeling: A
second course, 2nd ed. pp. 219–266. IAP Information Age Publishing, Charlotte, NC,
US (2013).
42. Ragu-Nathan, T.S., Tarafdar, M., Ragu-Nathan, B.S., Tu, Q.: The consequences of
technostress for end users in organizations: Conceptual development and validation. Inf.
Syst. Res. 19, 417–433 (2008). https://doi.org/10.1287/isre.1070.0165.
43. Adamczyk, P.D., Bailey, B.P.: If not now, when?: The effects of interruption at different
moments within task execution. Conf. Hum. Factors Comput. Syst. - Proc. 6, 271–278
(2004).
44. Grandhi, S.A., Jones, Q.: Knock, knock! Who’s there? Putting the user in control of
managing interruptions. Int. J. Hum. Comput. Stud. 79, 35–50 (2015).
https://doi.org/10.1016/j.ijhcs.2015.02.008.
45. Tarafdar, M., Pullins, E.B., Ragu-Nathan, T.S.: Technostress: Negative effect on
performance and possible mitigations. Inf. Syst. J. 25, 103–132 (2015).
https://doi.org/10.1111/isj.12042.
46. Diestel, S., Cosmar, M., Schmidt, K.H.: Burnout and impaired cognitive functioning:
The role of executive control in the performance of cognitive tasks. Work Stress. 27,
164–180 (2013). https://doi.org/10.1080/02678373.2013.790243.
47. Halbesleben, J.R.B., Bowler, W.M.: Emotional exhaustion and job performance: The
mediating role of motivation. J. Appl. Psychol. 92, 93–106 (2007).
https://doi.org/10.1037/0021-9010.92.1.93.
48. Aziri, B.: JOB SATISFACTION: A LITERATURE REVIEW. Manag. Res. Pract. 31,
1037–1042 (2011). https://doi.org/10.1254/jjp.31.1037.
49. Harris, J.I., Winskowski, A.M., Engdahl, B.E.: Types of workplace social support in the
prediction of job satisfaction. Career Dev. Q. 56, 150–156 (2007).
https://doi.org/10.1002/j.2161-0045.2007.tb00027.x.
50. Thomas, V., Azmitia, M., Whittaker, S.: Unplugged: Exploring the costs and benefits
of constant connection. Comput. Human Behav. 63, 540–548 (2016).
https://doi.org/10.1016/j.chb.2016.05.078.
51. Schmuck, D.: Does digital detox work? exploring the role of digital detox applications
for problematic smartphone use and well-being of young adults using multigroup
analysis. Cyberpsychology, Behav. Soc. Netw. 23, 526–532 (2020).
https://doi.org/10.1089/cyber.2019.0578.
52. Mattern, J., Lansmann, S., Hüllmann, J.: It’s Not that Bad! Perceived Stress of
Knowledge Workers During Enforced Working from Home Due to COVID-19. In:
Wirtschaftsinformatik 2021 Proceedings. pp. 263–279 (2021).
https://doi.org/10.1007/978-3-030-86790-4_19.
