Digital Stress over the Life Span: The Effects of Communication Load and Internet Multitasking on Perceived Stress and Psychological Health Impairments in a German Probability Sample

Abstract

The present study investigated the psychological health effects and motivational origins of digital stress based on a representative survey of 1,557 German Internet users between 14 and 85 years of age. Communication load resulting from private e-mails and social media messages as well as Internet multitasking were positively related to perceived stress and had significant indirect effects on burnout, depression, and anxiety. Perceived social pressure and the fear of missing out on information and social interaction were key drivers of communication load and Internet multitasking. Age significantly moderated the health effects of digital stress as well as the motivational drivers of communication load and Internet multitasking. The results, thus, underline the need to address digital stress from a life span perspective.

Full text

Digital Stress over the Life Span: The Effects of
Communication Load and Internet Multitasking
on Perceived Stress and Psychological Health
Impairments in a German Probability Sample
LEONARD REINECKE
Department of Communication, Johannes Gutenberg University Mainz, Mainz, Germany
STEFAN AUFENANGER
Department of Education, Johannes Gutenberg University Mainz, Mainz, Germany
MANFRED E. BEUTEL and MICHAEL DREIER
Outpatient Clinic for Behavioral Addictions, Department of Psychosomatic Medicine and
Psychotherapy, University Medical Center, Johannes Gutenberg University Mainz,
Mainz, Germany
OLIVER QUIRING and BIRGIT STARK
Department of Communication, Johannes Gutenberg University Mainz, Mainz, Germany
KLAUS WÖLFLING and KAI W. MÜLLER
Outpatient Clinic for Behavioral Addictions, Department of Psychosomatic Medicine and
Psychotherapy, University Medical Center, Johannes Gutenberg University Mainz,
Mainz, Germany
The present study investigated the psychological health effects and
motivational origins of digital stress based on a representative survey
of 1,557 German Internet users between 14 and 85 years of age.
Communication load resulting from private e-mails and social
media messages as well as Internet multitasking were positively
related to perceived stress and had significant indirect effects on
burnout, depression, and anxiety. Perceived social pressure and
the fear of missing out on information and social interaction were
key drivers of communication load and Internet multitasking. Age
This research was supported by a grant from Forschungsschwerpunkt Medienkonvergenz
[Research Center for Media Convergence] at Johannes Gutenberg University Mainz.
Address correspondence to Leonard Reinecke, Department of Communication, Johannes
Gutenberg University Mainz, Jakob-Welder-Weg 12, 55128 Mainz, Germany. E-mail: leonard.
reinecke@uni-mainz.de
Media Psychology, 0:1–26, 2016
Copyright © 2016 Taylor & Francis
ISSN: 1521-3269 print/1532-785X online
DOI: 10.1080/15213269.2015.1121832
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significantly moderated the health effects of digital stress as well as
the motivational drivers of communication load and Internet
multitasking. The results, thus, underline the need to address digital
stress from a life span perspective.
Information and communication technology (ICT) has become an integral part of
everyday life for a growing number of Internet users throughout the world. More
and more Internet users of all age groups seem to be constantlyconnectedtoa
stream of online content and computer-mediated communication (CMC; Vorderer
& Kohring, 2013). A large body of research demonstrates the indisputable benefits
of private online communication and social media use for psychological health
and well-being, such as the acquisition of online social capital (Ellison, Vitak, Gray,
&Lampe,2014), or the satisfaction of intrinsic needs (Reinecke, Vorderer, & Knop,
2014). However, the same communication opportunities that pave the way for
these beneficial effects of online communication carry the inherent risk of impos-
ing a permanent burden on Internet users: Just as pervasive ICT may provide
ubiquitous opportunities to satisfy individual needs, the social expectations to
respond to online communication, the sheer mass of communication content, as
well as the growing trend of combining Internet use with other simultaneous
activities may expose users to information overload and impair their psychological
well-being (Misra & Stokols, 2012).
While the potential dangers of information overload and perceived stress
originating from ICT use at the workplace and in corporate contexts are well
documented (e.g., Ragu-Nathan, Tarafdar, Ragu-Nathan, & Tu, 2008; Reinke &
Chamorro-Premuzic, 2014), the consequences of information overload arising
from personal and private online communication remain largely unknown. Due
to the lack of representative studies that would allow for a test of the effects of
private communication load in the general population and over the life span, it
also remains unclear whether adolescents and young adults, who are particu-
larly enthusiastic users of social media and mobile Internet, are equally suscep-
tible to the potential negative effects of communication overload as older users.
Furthermore, the motivational forces that drive the engagement in frequent
online interactions and Internet multitasking remain largely unexplored. It,
thus, remains unclear, why so many ICT users willingly expose themselves to
potentially burdensome and straining communication patterns.
The aim of the present study is to address these open questions. In the
following sections, we shall first review existing theory and research on the
effects of ICT use and media multitasking on stress and psychological
symptoms. We shall then introduce perceived social pressure and the fear of
missing out as potential motivational drivers promoting communication load
and Internet multitasking. Subsequently, we discuss age as a potential mod-
erator of the effects proposed in our theoretical model. This model is then
tested based on a representative probability sample of German Internet users.
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THE EFFECTS OF ICT STRAIN ON PERCEIVED STRESS AND
PSYCHOLOGICAL HEALTH
The processes and variables that drive the experience of stress have received
considerable attention in psychological research (for an overview, see Lazarus,
1993). According to the transactional theory of stress (Lazarus & Folkman, 1984,
1987), stress reactions are the result of the interaction of person variables and
environmental variables. Stress can be defined as “an unfavorable person-
environment relationship”(Lazarus, 1993, p. 8) and is perceived when the
situational demands are taxing or exceeding the resources of the individual.
Cognitive appraisal is a central mediator between environmental demands and
stress reactions and refers to a process in which individuals “constantly evaluate
the significance of what is happening for their personal wellbeing”(Lazarus,
1993, p. 7). Primary appraisal refers to the evaluation of situational environ-
mental demands and their relevance to the individual’s well-being whereas
secondary appraisal processes evaluate the coping options and resources of the
individual. In combination, primary and secondary appraisal determine the
stress reaction, which is particularly pronounced and negatively valenced
when the environmental demands are perceived as a threat to well-being and
the confidence in successful coping is low (Lazarus & Folkman, 1984,1987). In
the present study, we propose that digital stress, that is stress reactions elicited
by environmental demands originating from ICT use, varies as a function of at
least two factors that challenge the users’coping resources: communication
load (i.e., the number of sent and received private e-mails and social media
messages) and Internet multitasking (i.e., concurrent use of ICT and other
activities). In the following sections, we will review existing research on
communication load and media multitasking and explicate the relationship
between both factors and stress.
Early research on the effects of ICT use on stress and psychological health
has been dominated by a focus on job-related online communication. A large
number of studies have addressed the impact of ICT-based informational
overload on professionals in various job contexts (for an overview, see Eppler
& Mengis, 2004). Information overload can be defined as “the experience of
feeling burdened by large amounts of information received at a rate too high to be
processed efficiently”(Misra & Stokols, 2012, p. 739). Closely connected to the
phenomenon of ICT-related information overload is the concept of technostress
that can be defined as “stress caused by an inability to cope with the demands of
organizational computer usage”(Tarafdar, Tu, & Ragu-Nathan, 2010,p.304).
Prior research has linked both technostress and information overload to a
number of negative psychological outcomes in the working context, such as
lower job satisfaction, decreased productivity, stress, and burnout (Ragu-Nathan
et al., 2008; Reinke & Chamorro-Premuzic, 2014; Tarafdar, Tu, Ragu-Nathan, &
Ragu-Nathan, 2007; Tarafdar et al., 2010). This research demonstrates that
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information overload arising from ICT use in the work-context places employees
under intense strain, resulting in stress and impaired psychological health and
well-being.
The fact that the majority of existing research on the negative effects of
ICT-related stress and strain is focused on work-related ICT use is not surpris-
ing, given the fact that access to online communication was mainly restricted
to military, governmental, or corporate organizations during the early days of
the Internet (Leiner et al., 2009). The dissemination of Internet access in the
general population, however, has seen an exponential growth throughout the
last two decades (Zickuhr, 2013). The constant connectedness to online
content and communication is further intensified by the fast growing use of
mobile Internet access (Smith & Page, 2015). Accordingly, a growing number
of researchers have suggested that more and more people tend to be “perma-
nently online”(Vorderer & Kohring, 2013, p. 188). In a 24-hour tracking study
of the mobile phone use of 793 university students in four countries, Mihailidis
(2014) found that 31% of the participants logged into social networking apps
more than 13 times in a 24-hour period, clearly demonstrating the centrality
of mobile Internet use for the “tethered generation”(p.58). In a similar
vein, Crawford (2009) refers to the use of social media such as Twitter as
“background listening,”where a constant flow of bits of information and
conversations “continue as a backdrop throughout the day”(p. 528). These
findings suggest that private online communication is taking up a fast growing
share of the time and cognitive capacity of Internet users who are facing a
constant load of incoming messages and communication demands. Thus, the
question whether the pervasive use of private e-mail and social media is
associated with similar stress and strain reactions as work-related online
communication is a pressing challenge to CMC-research: Whereas ICT
overload in the work setting is restricted to a relatively small group of
professionals, communication overload resulting from private online
communication affects large parts of the general population irrespective of
employment status or profession.
Only a few prior studies have explored the effects of information overload
outside the job context. In a survey study with 600 student participants, LaRose,
Connolly, Lee, Li, and Hales (2014) explored the effects of “connection over-
load”(p. 59) arising from the communication demands resulting from social
media and e-mail use. Their results demonstrate that deficient self-regulation of
Internet use and communication demands was significantly related to negative
outcomes of Internet use in everyday life which, in turn, were significant
predictors of perceived stress. In a prospective panel study with 1,127 students
from Sweden, Thomée, Eklöf, Gustafsson, Nilsson, and Hagberg (2007) found
that high levels of ICT use (computer and mobile phone) significantly
predicted increased stress and depression at a 1-year follow up. Two additional
survey studies with over 4,000 young adults in Sweden found significant
detrimental effects of high accessibility demands caused by mobile phone use
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(Thomée, Härenstam, & Hagberg, 2011) and of frequent computer use (Tho-
mée, Härenstam, & Hagberg, 2012) in form of sleep disturbances, stress, and
depression. Finally, a panel study among 484 undergraduate students from the
United States found negative effects of perceived “cyber-based overload”(e.g.,
e-mail volume, pressure to respond, perceived pressure to post content on
social media etc.) on perceived stress and overall health status (Misra & Stokols,
2012, p. 740). In summary, these studies clearly identify information overload
and the communication demands arising from private ICT use as a significant
predictor of perceived stress. In an attempt to replicate these findings of prior
research in a probability sample of the general population, we predicted in the
present study that communication load arising from private ICT use, more
specifically the frequency of sent and received e-mails and social media mes-
sages as well as the frequency of checking behavior, is associated with
increased perceived stress.
H1: Communication load is positively related to perceived stress.
The second potential source of ICT-related stress addressed in the pre-
sent study is Internet multitasking. Prior research has addressed media multi-
tasking both in terms of the simultaneous use of two or more different media
stimuli (e.g., Ophir, Nass, & Wagner, 2009) as well as the combination of
media use and other non-media activities (e.g., Jeong & Fishbein, 2007). In
this study, we, thus, refer to Internet multitasking as any combination of
Internet use with other media or non-media activities. In times of ubiquitous
Internet access, Internet multitasking has become a common phenomenon. In
a diary study with 1,783 Dutch participants aged 13–65 years, Voorveld and
van der Goot (2013) investigated media multitasking with regard to 14 differ-
ent media activities (e.g., watching television, listening to the radio, or using
social media). Participants engaged in media multitasking during 21.9% of the
total time spent on media use. E-mail and website use were the two media
most frequently used in multitasking. In a survey among 547 adolescents in
the United States by Jeong and Fishbein (2007), a substantial share of the
participants reported that they frequently used the Internet during homework
(24%) or interactions with friends (22%). Furthermore, in an experience
sampling study with 189 undergraduate students, Moreno et al. (2012) found
that their participants multitasked at 56.5% of the time they were online.
The effects of media multitasking have been addressed from a number of
theoretical perspectives in prior research. Some studies (e.g., Z. Wang et al.,
2012) have made reference to central bottleneck theories that propose that
human information processing is limited and can only accommodate one
stimulus at a time (for an overview, see Meyer et al., 1995). Consequently,
when two tasks need to be processes simultaneously, they have to be queued,
resulting in performance impairments during multitasking. Other research
on media multitasking (e.g., David, Xu, Srivastava, & Kim, 2013; Jeong &
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Fishbein, 2007; Pool, Koolstra, & Van der Voort, 2003) is grounded on limited
capacity models of information processing (e.g., Lang, 2000). In contrast to
bottleneck approaches, limited capacity theory does not propose that stimuli
need to be processed serially, but suggests that cognitive overload occurs
when the cognitive resources demanded by the concurrent tasks exceed the
limited cognitive capacities of the individual (Lang, 2000), resulting in reduced
performance (David et al., 2013; Pool et al., 2003; Z. Wang et al., 2012) and
increased perceived task demand (David et al. 2013) during media multi-
tasking. More recently, research on media multitasking (e.g., David, Kim,
Brickman, Ran, & Curtis, 2015) has also adapted theories of information
processing with a particular focus on concurrent multitasking, such as the
threaded cognition model (Salvucci & Taatgen, 2008). The threaded cognition
framework proposes that concurrent tasks can be conceptualized as separate
threads of processing that are coordinated by a serial procedural resource.
While different threads can be processed in parallel, resource conflicts can
arise when two or more threads require attention from the central procedural
resource or if multiple tasks demand the same resources (e.g., perceptual or
motor resources; Salvucci & Taatgen, 2008).
Although the cognitive models applied in media multitasking research
differ with regard to the specific mechanisms they identify as the source of the
limited capacity for multitasking, all models suggest that media multitasking
places the cognitive resources of media users under considerable strain. In
accordance with transactional models of stress, these environmental demands
originating from media multitasking in general and Internet multitasking in
specific, are likely to result in stress reactions. Cognitive demand, however,
may not be the only source of stress elicited by Internet multitasking. Multi-
tasking is often highly habitual (Hwang, Kim, & Jeong, 2014; Zhang & Zhang,
2012) and can turn into a form of deficiently self-regulated media use inter-
fering with other tasks and obligations (David et al., 2015). Recent experience
sampling research demonstrates that media use frequently conflicts with other
goals in everyday life (Hofmann, Vohs, & Baumeister, 2012). Such goals
conflicts and the negative self-conscious emotions triggered by self-control
failure due to media use (Reinecke, Hartmann, & Eden, 2014) could be a
further mechanism linking Internet multitasking to increased stress.
In fact, previous research provides initial evidence of a relationship
between media multitasking and perceived stress. Media multitasking has
been linked to significant increases in perceived stress both in the working
context (Mark, Gudith, & Klocke, 2008) as well as the private domain (Misra &
Stokols, 2012). The link between multitasking and stress is further supported
by an in situ observational study conducted by Mark, Wang, and Niiya (2014).
The computer activities of 48 students as well as their psychophysiological
condition were monitored for 7 days during all waking hours. Multitasking
was significantly related to psychophysiological indicators of stress. Besides
stress reactions, media multitasking has also been linked to other negative
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psychological health outcomes, such as depression and anxiety (Becker,
Alzahabi, & Hopwood, 2013). Based on the theoretical considerations
outlined above and the findings of previous research establishing a significant
connection between media multitasking and stress reactions, we expected to
find a positive relationship between Internet multitasking and perceived stress
in the general population.
H2: Internet multitasking is positively related to perceived stress.
A large body of research demonstrates that perceived stress is a crucial risk
factor for a number of negative psychological health outcomes. In a meta-analysis
by Lee and Ashforth (1996), stress was strongly and consistently associated
with burnout. Furthermore, perceived stress has been linked to depression and
anxiety in the working context (Rusli, Edimansyah, & Naing, 2008)aswellasthe
general population (Bergdahl & Bergdahl, 2002). This suggests that the increased
levels of perceived stress resulting from communication load (Hypothesis 1) and
Internet multitasking (Hypothesis 2) increase the risk of negative psychological
health outcomes.
H3: Perceived stress is positively related to a) burnout and b) depression and
anxiety.
SOCIAL PRESSURE AND FEAR OF MISSING OUT AS DRIVERS OF
COMMUNICATION LOAD AND INTERNET MULTITASKING
In addition to expanding our insights into the potential implications of strain
resulting from ICT use, the present study also attempts to address the under-
lying motivational processes that increase the personal risk of engaging in
potentially harmful ICT-usage practices. Prior research has demonstrated that
CMC is characterized and guided by strong social norms and expectations,
placing communication partners under considerable social pressure. Viola-
tions of social expectations in CMC interaction, such as not responding to
e-mails in a socially acceptable timeframe, result in negative evaluations of the
communication partner (Kalman & Rafaeli, 2011). Similar forms of availability
demands and social pressure are also present in other forms of online com-
munication, such as social media use (Quan-Haase & Young, 2010; E. S.-T.
Wang & Chen, 2012). We, thus, propose that the perceived social pressure to
be constantly available has a significant impact on communication patterns.
Supporting this rationale, Misra and Stokols (2012) found that perceived
pressure to respond to online communication was a significant predictor of
information load. We, thus, suggest that availability expectations of their social
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environment place Internet users under perceived pressure to check for
new e-mails or social media messages frequently and to respond to online
communication immediately (hence, increasing communication load) and
irrespective of situational demands or conflicting activities (resulting in
Internet multitasking).
H4: Perceived social pressure to be constantly available is positively related
to a) communication load and b) Internet multitasking.
In addition to perceived social pressure, recent research has linked online
communication and social media use to the fear of missing out (Przybylski,
Murayama, DeHaan, & Gladwell, 2013). Fear of missing out is defined as “a
pervasive apprehension that others might be having rewarding experiences
from which one is absent”(Przybylski et al., 2013, p. 1841). Social media in
particular provide easy access to social information and an easy way to stay
socially involved (Quan-Haase & Young, 2010). As the fear of missing out is
characterized “by the desire to stay continually connected with what others
are doing”(Przybylski et al., 2013, p. 1841), social media use should be a
particularly attractive option to stay informed about social activities for indivi-
duals with high levels of fear of missing out. In fact, prior research has found
strong empirical connections between the fear of missing out and the intensity
of social media use (Przybylski et al., 2013). These results suggest that the
fear of missing out should be positively related to the frequency of online
communication and checking behavior, resulting in higher levels of commu-
nication load. Prior research also provides evidence linking fear of missing out
to Internet multitasking. In a study with undergraduate students, Pryzybylski
et al. (2013) found that students showing higher levels of fear of missing out
had a higher tendency to use social media during meals or lectures and used
their mobile phones to check or send e-mails while driving their car more
frequently than students low on fear of missing out. We, thus, expected the
fear of missing out to be a significant motivational driver of both communica-
tion load as well as Internet multitasking.
H5: The fear of missing out is positively related to a) communication load
and b) Internet multitasking.
DIGITAL STRESS OVER THE LIFE SPAN: AGE AS A MODERATOR OF
THE PROPOSED EFFECTS
Our theoretical model predicts both the well-being implications as well as the
underlying motivational drivers of communication overload and Internet
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multitasking. What remains unclear, however, is the question whether the
hypothesized effects equally apply to Internet users of all age ranges. Both the
public as well as the scholarly discourse is frequently characterized by the
assumption that younger users are more apt and knowledgeable ICT users,
simply because they have been exposed to new media early on in their lives
(Hargittai, 2010;Helsper&Eynon,2010). Accordingly, younger generations of
Internet users have been referred to as “digital natives,”supposedly possessing
better expertise and a deeper understanding of online media than “digital immi-
grants”who did not have access to ICT at an early age (Prensky, 2001). A number
of researchers have provided empirical evidence against this simplistic idea of
strong generational differences in ICT expertise, demonstrating that members of
the group of digital natives vary considerably regarding their online use and
Internet skills (Hargittai, 2010) and that age is only one among many other
predictors of ICT expertise (Helsper & Eynon, 2010). At the same time, prior
research clearly demonstrates that the prevalence of ICT use decreases over the
life span and that younger users engage in media multitasking more frequently
than older users (Carrier, Cheever, Rosen, Benitez, & Chang, 2009;Helsper&
Eynon, 2010; Voorveld & van der Goot, 2013). This suggests that, on average,
younger Internet users should be more intensively exposed to strain resulting
from communication load and Internet multitasking. It remains unclear, however,
whether these higher levels of ICT-related strain also result in higher levels of
perceived stress or whether younger and older users differ systematically with
regard to the inherent coping resources to deal with ICT-related stressors.
Communication load as well as Internet multitasking are cognitively demand-
ing and deplete the limited cognitive capacity of ICT users. Stress arises when the
demands of the environment exceed the resources available to the individual
(Lazarus & Folkman, 1984). A higher cognitive capacity should, thus, act as a
buffer against perceived stress, that may result from communication load and
Internet multitasking. A broad body of research demonstrates that central execu-
tive functions such as speed of processing, memory, and reasoning (Verhaeghen
&Salthouse,1997)aswellasdual-taskperformance(Verhaeghen&Cerella,2002)
deteriorate with age. Hence, older ICT users may be less well prepared to cope
with ICT-related cognitive strain than younger users, suggesting a stronger effect
of communication load and Internet multitasking on perceived stress. This notion
is supported by the findings of Carrier et al. (2009), demonstrating that older
participants found media multitasking more difficult than younger participants.
Reduced cognitive resources may be compensated by other coping resources
such as ICT expertise or Internet self-efficacy. Prior research, however, does not
provide a unanimous picture of the effects of age on Internet skills. In a study by
Helsper and Enyon (2010), perceived Internet skills were negatively related to
age. In a study comparing different forms of Internet skills among younger and
older ICT users, however, van Deursen, van Dijk, and Peters (2011)cametothe
conclusion that older users exhibited lower levels of medium-related Internet skills
(i.e.,formalsskillssuchasoperatingtheInternet browser and navigation skills) but
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higher levels of content-related Internet skills (i.e., strategic skills such as selecting
information or evaluating sources) than younger users. Furthermore, prior find-
ings on age differences in perceived technostress also provide mixed results.
While older participants in a study by Ragu-Nathan et al. (2008) experienced
less technostress than younger participants, age was positively related to technos-
tressinastudybyK.Wang,Shu,andTu(2008). Given these ambiguous results,
the aim of the present study was to explore potential age-differences in the effects
ofICT-relatedstrainonperceivedstressoverthelifespan.
RQ1: Are the effects of communication load and Internet multitasking on
perceived stress moderated by age?
Furthermore, we suggest that the underlying motivational mechanisms
driving communication load and multitasking may also be moderated by age.
Research in the field of developmental psychology suggests that the suscept-
ibility to social pressure varies among different age groups. Identification with
the peer group and growing autonomy from parents are particularly important
developmental tasks in middle adolescence, resulting in an increased will-
ingness to conform to the peer group and increased salience of social pressure
(Brown & Larson, 2009). The influence of social pressure on behavior is, thus,
particularly pronounced for adolescents and young adults and decreases in
adult life (Steinberg & Monahan, 2007). Applied to the context of online
communication, this may suggest that—compared to younger users—social
pressure to be constantly available could have a smaller effect on the CMC
practices of older individuals. The age-dependent effects of the fear of missing
out on online communication, however, remain largely unclear. Findings by
Pryzybylski et al. (2013) clearly demonstrate that the fear of missing out is
negatively related to age. However, this does not imply that comparable levels
of fear of missing out result in different behavioral outcomes for younger
versus older individuals. The last goal of the present study was, thus, to
explore potential variations of the effects of social pressure and fear of missing
out on communication load and Internet multitasking over the life span:
RQ2: Are the effects of perceived social pressure to be constantly available
and the fear of missing out on communication load and Internet multi-
tasking moderated by age?
METHOD
Sample and Procedure
Our theoretical model was tested based on a representative probability sample
of the German population aged 14 years and over. Data were collected by the
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German market research institute USUMA. Participants were randomly
sampled based on the sampling points of the ADM-sampling system (von der
Heyde, 2009). The ADM-sampling system is a sampling frame for representative
face-to-face interviews in Germany, provided by the Arbeitskreis Deutscher
Markt-und Sozialforschungsinstitute [German Association of Market and Social
Research Agencies], and represents a quasi-standard for probability sampling in
Germany. The sampling system is based on a stratified net of 258 sampling
points in combination with a random-route selection of private households
(von der Heyde, 2009).
In the present study, 4,644 German households were sampled and contacted
based on the ADM-sampling system, resulting in a sample of N= 2,527 completed
interviews (response rate = 54.8%). Participants who reported they never used the
Internet (n= 830) or who provided incomplete data (n= 140) were excluded from
further analyses, resulting in a final sample of N= 1,557 participants (51.6%
females, ages ranging from 14 to 85 years, M
age
= 42.37 years, SD = 14.84 years).
Participants reported to use the Internet on average at M=5.56daysperweek
(SD = 1.89) and the majority of participants (63%) reported using the Internet for
more than 1 hour on a typical weekday. Furthermore, more than half of the
sample (54.4 %) reported using mobile Internet access via smartphones or tablet
computers at least once per week.
Measures
Social Pressure. Perceived social pressure to be constantly available was
assessed with four items adapted from the perceived norm scale by Fishbein
and Ajzen (2010). Participants responded to the items (e.g., “My friends expect
me to be constantly available”) on a 5-point scale ranging from 1 (does not
apply at all)to5(fully applies). The items formed a unidimensional scale and
showed a high reliability (Cronbach’sα= .92, composite reliability (CR) = .92).
Fear of Missing Out. Three items were used to measure the fear of
missing out on important events and information when not using the Internet.
Participants responded to the items (e.g., “If I would use the Internet less
frequently, I would fear missing out on important things”) on a scale from 1
(does not apply at all)to5(fully applies). The items showed a unidimensional
factor structure and a satisfactory reliability (Cronbach’sα= .91, CR = .91).
Communication Load. Six items were developed to measure commu-
nication load based on prior operationalizations of communication demands
(e.g., LaRose et al., 2014). The average daily number of sent and received
private e-mails and messages from social media, respectively, was assessed on
8-point scales ranging from 0to >100. Additionally, the frequency of the
perceived urge to check private e-mail and social media messages,
respectively, was measured on a 5-point scale ranging from 0 (never)to4
(constantly). Explorative principal components analysis with oblique
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(Promax) rotation yielded two correlated factors with eigenvalues >1. The
three items measuring communication load resulting from private e-mail
loaded on the first factor (eigenvalue = 3.21, all factor loadings > .68, Cron-
bach’sα= .76, CR = .76), while the three items measuring communication load
through social media messages loaded on the second factor (eigenvalue =
1.35, all factor loadings >.88, Cronbach’sα= .90, CR = .90). The two factors
explained 76.34% of the variance. To account for the correlated two-factor
structure of the measure, communication load was modeled as a second-order
factor accounting for the two first order latent constructs in the subsequent
analyses.
Internet Multitasking. Five items were used to assess Internet multitasking.
Participants indicated on a 5-point scale from 0 (never)to4(very frequently)how
often they use the Internet while they simultaneously a) use other media, b) are in
a conversation with another person, c) are having a meal with another person, d)
interact with their romantic partner, e) go out with their friends. These scenarios
were chosen based on the findings of prior research demonstrating that media
multitasking is particularly prevalent in combination with other media, during
social activities, and during meals (Jeong & Fishbein, 2007;Shih,2013). In the
present study, the five items showed a unidimensional factor structure and a
satisfactory internal consistency (Cronbach’sα=.84,CR=.86).
Perceived Stress. The ten items of the Perceived Stress Scale (S. Cohen,
Kamarack, & Mermelstein, 1983) were used to assess subjective stress levels.
Participants responded to the items on a 5-point scale from 0 (never)to4(very
often). The items showed a satisfactory internal consistency (Cronbach’sα= .85,
CR = .86). The results of an exploratory principal components analysis
with oblique (Promax) rotation, however, suggested that instead of the expected
unidimensional structure, the items loaded on two correlated factors with eigen-
values >1. The six items of the scale indicating higher levels of stress (e.g., “In the
last month, how often have you felt nervous and ‘stressed’?”) loaded on the first
factor (eigenvalue = 4.42, all factor loadings > .73, Cronbach’sα= .85, CR = .86),
while the four reverse-coded items of the scale (e.g., “In the last month, how
often have you been able to control irritations in your life?”)scoredonthe
second factor (eigenvalue = 1.97, all factor loadings > .78, Cronbach’sα= .86,
CR = .86). To account for the correlated two-factor structure of the measure,
perceived stress was modeled as a second-order factor accounting for the two
first order latent constructs in the subsequent analyses.
Burnout. The six items of the personal burnout subscale of the Copen-
hagen Burnout Inventory (Kristensen, Borritz, Villadsen, & Christensen, 2005)
were used to assess burnout in the present study. Participants responded to
the items (e.g., “How often are you emotionally exhausted?”) on a 5-point
scale ranging from 1 (never/almost never)to5(
always). The items showed a
unidimensional structure and a high reliability (Cronbach’sα= .92, CR = 92).
Depression and Anxiety. The 4-item Patient Health Questionnaire-4
(PHQ-4; Löwe et al., 2010) was used to measure depression and generalized
12 L. Reinecke et al.
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anxiety. The scale consists of an item stem (“Over the last 2 weeks, how often
have you been bothered by the following problems?”), followed by two items
measuring depression (e.g. “feeling down, depressed, or hopeless”) and
anxiety (e.g., “not being able to stop or control worrying”), respectively.
Participants responded to the items on a 4-point scale from 0 (not at all)to
3(nearly every day). The items showed a unidimensional structure in the
present study (eigenvalue = 1.82, all factor loadings > .79, 71% explained
variance) and a high reliability (Cronbach’sα= .86, CR = .86). They were, thus,
modeled as a combined depression and anxiety factor.
Data Analytic Procedure
A three-group structural equation model was computed using the AMOS 23
software packet and the maximum likelihood method. To reveal potential
moderation effects of age, the sample was split in three subsamples. The
subsamples were formed on the basis of theoretical as well as methodological
considerations. Following the definition by Prenszky (2001; see also Helsper &
Eynon, 2010), participants born in 1980 or later were categorized as members of
the generation of digital immigrants. This first subsample of younger
Internet users accordingly consisted of participants of the age range of 14 to
34 years (n= 512) and included 32.9% of the participants of the full sample. To
ensure equal sample sizes and to allow for a comparison of middle-aged and
older participants, the remaining group of digital immigrants was separated into
two subsamples of participants in the age range of 35 to 49 years (n= 510) and
50 to 85 years (n= 535), respectively, by a split at the 66th age percentile. The
statistical model (see Figure 1) tested all paths predicted in Hypotheses 1–5.
Furthermore, due to their substantial zero-order correlations, social pressure
and fear of missing out as well as the residuals of communication load and
Internet multitasking were allowed to covary in the model. Model fit was tested
based on the χ
2
and the CMIN/df statistics and a combination of three additional
fit indices recommended by Hu and Bentler (1999): the comparative fit
index (CFI), the root mean square error of approximation (RMSEA), and the
standardized root mean square of residuals (SRMR).
RESULTS
Means, standard deviations, and zero-order correlations among all studied
variables are presented in Table 1. With χ
2
(1953) = 5401.48, p<.001, CMIN/
df = 2.77, CFI = .910, RMSEA = .034, 90% CI = [.033, .035], and SRMR = .06, the
model showed an acceptable fit to the data. The convergent and discriminant
validity of all constructs was tested based on the average variance extracted
(AVE), the maximum shared squared variance (MSV), and the average shared
Digital Stress Over the Life Span 13
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squared variance (ASV). All constructs showed satisfactory convergent
discriminant validity (all AVEs ≥.50). Furthermore, all variables showed
satisfactory discriminant validity (AVE > MSV and AVE > ASV), with the
exception of perceived stress (AVE = .55, MSV = .67, and ASV = .26) and
depression and anxiety (AVE = .61, MSV = .67, and ASV = .22). The subopti-
mal ratio between the AVE and MSV values of both constructs is caused by
their strong mutual correlation (see Table 1). We decided to retain both
variables in their current form, however, as both constructs were a) measured
with prevalidated and commonly used measures and b) are strongly related
both theoretically and in prior empirical research (Bergdahl & Bergdahl, 2002;
Rusli et al., 2008).
As predicted in Hypothesis 1, communication load was positively related
to perceived stress in the age range of 50 to 85 years (β= .28, p< .001), but not
in the subsamples of participants aged 14 to 34 years (β= -.04, p= .609) and
.39
Group 1: Ages 14-34 years, n= 512
Group 2: Ages 35-49 years, n= 510
Group 3: Ages 50-85 years, n= 535
Fear of
Missing out
Communication
Load
Internet
Multitasking
Burnout
Depression/
Anxiety
Perceived
Stress
Social
Pressure .28
.24
.30
.31
.64
ns
.33
.79
.81
.32
Fear of
Missing out
Communication
Load
Internet
Multitasking
Burnout
Depression/
Anxiety
Perceived
Stress
Social
Pressure .12
.35
.11
.54
.54
ns
.32
.77
.90
Fear of
Missing out
Communication
Load
Internet
Multitasking
Burnout
Depression/
Anxiety
Perceived
Stress
Social
Pressure ns
.38
ns
.67
.49
.28
.ns
.82
.89
.45
FIGURE 1 Observed three-group structural equation model, χ
2
(1953) = 5401.48, p<.001,
CMIN/df = 2.77, CFI = .910, RMSEA = .034, 90% CI = [.033, .035], and SRMR = .06. Scores in
the figure represent standardized path coefficients significant at p< .05.
14 L. Reinecke et al.
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35 to 49 years (β= .08, p=.248). With regard to Research Question 1, this
pattern of results suggests a moderation effect of age on the effect of
communication load on perceived stress. The categorization of a continuous
moderator variable (i.e., age), as performed to establish the age groups for the
three-group model in the present study, results in a loss of information and
lowers the statistical power for the detection of moderation (J. Cohen, Cohen,
West, & Aiken, 2003). To compensate for this and to treat age as a continuous
moderator variable, the significance of all moderation effects addressed in
Research Questions 1 and 2 was additionally tested with hierarchical regres-
sion analyses. The independent variable and the moderator were standardized
and entered in the first step, followed by the interaction term in the second
step. The results demonstrate a significant interaction effect of communication
load and age (β= .07, p< .05) and a significant increase in the explained
variance in stress (ΔR
2
=.004, p< .05). Accordingly, age significantly moder-
ated the effect of communication load on stress, with older users suffering
more strongly from ICT-related strain.
As predicted in Hypothesis 2, Internet multitasking was significantly related
to perceived stress in the age range of 14 to 34 years (β=.33,p<.001)and35to49
years (β= .32, p< .001), but not in the subsample of participants ages 50 years
and above (β= .12, p= .079). However, the interaction effect between age
and Internet multitasking did not reach significance (β=.02,p= .443; ΔR
2
<.001,
p= .443).
Hypotheses 3a and 3b predicted a significant positive relationship
between perceived stress and a) burnout as well as b) depression/anxiety.
Both hypotheses were supported by the data and perceived stress was
strongly positively related to both dependent variables in all three subsamples
(see Figure 1). To further explore the implications of ICT-related strain on
psychological health outcomes, the indirect effects of communication load
and Internet multitasking via perceived stress on burnout and depression/
TABLE 1 Means, Standard Deviations and Zero-Order Correlations
MSD 1 2345678 910
1. Age 42.37 14.84 –
2. Messages sent 1.24 1.01 –.26** –
3. Messages received 1.50 1.11 –.30** .77** –
4. Urge to check
messages
1.14 .98 –.28** .66** .58** –
5. Internet multitasking .73 .76 –.38** .39** .47** .43** –
6. Perceived stress 1.24 .64 –.11** .14** .18** .13** .29** –
7. Burnout 2.12 .77 .05 .04 .12** .04 .13** .58** –
8. Depression/anxiety .40 .53 –.01 .12** .17** .12** .24** .63** .62** –
9. Perceived social
pressure
2.76 1.18 –.30** .30** .34** .38** .38** .15** .05 .054* –
10. Fear of missing out 2.14 1.16 –.31** .42** .43** .52** .44** .20** .03 .16** .56** –
*p< .05; **p< .01.
Digital Stress Over the Life Span 15
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anxiety were bootstrapped with 5,000 bootstrap samples with replacement.
The results are summarized in Table 2. Communication load had a significant
indirect effect on burnout and depression/anxiety in the subsample of parti-
cipants in the age range between 50 and 85 years, but not in the two younger
subsamples. Furthermore, Internet multitasking had a significant influence on
both psychological health outcomes in the age range of 14 to 34 years and 35
to 49 years but not in the subsample of participants in the age range of 50 to
85 years (see Table 2).
As predicted in Hypothesis 4a, perceived social pressure was significantly
related to communication load for individuals in the age range of 14 to 34 years
(β= .28, p< .001) and 35 to 49 years (β= .12, p< .05), but not in the subsample of
participants in the age range of 50 to 85 years (β=–.05, p= .465). A similar
pattern of results emerged with regard to Internet multitasking. As predicted in
Hypothesis 4b, perceived social pressure was significantly related to Internet
multitasking for individuals in the age range of 14 to 34 years (β= .30, p< .001)
and 35 to 49 years (β= .11, p< .05), but not in the sub-sample of participants in
the age range of 50 to 85 years (β= .04, p= .482). Hierarchical regression
analysis revealed a significant moderation effect of age on the relationship
between social pressure and communication load (β=–.07, p< .01; ΔR
2
=
.01, p< .01) as well as between social pressure and media multitasking (β=–.12,
p< .001; ΔR
2
= .02, p< .001). Accordingly, younger individuals were more
susceptible to the effects of social pressure than older users.
H5 predicted a positive relationship between the fear of missing out and a)
communication load as well as b) Internet multitasking. Hypotheses 5a and 5b
were supported by the data in all three age groups (see Figure 1). Hierarchical
regression analysis revealed a significant moderation effect of age on the relation-
ship between fear of missing out and communication load (β=.05,p< .05; ΔR
2
=
.002, p< .05), suggesting that fear of missing out and communication load were
more strongly related at higher age. The path between fear of missing out and
Internet multitasking, however, was not significantly moderated by age (β=–.03,
p= .162; ΔR
2
=.001,p= .162).
TABLE 2 Indirect Effects of Communication Load and Internet Multitasking via Perceived
Stress on Psychological Health Outcomes
Ages 14–34 years Ages 35–49 years Ages 50–85 years
Burnout
Depression/
anxiety Burnout
Depression/
anxiety Burnout
Depression/
anxiety
Communication
load
–.03 –.03 .06 .07 .23** .24**
Internet
multitasking
.26** .26** .25** .29** .10 .10
*p<.05;**p< .01. Notes. All scores represent standardized beta coefficients. The significance of the indirect
effects (c’) was tested using bootstrapping (maximum likelihood) with 5,000 bootstrap samples with
replacement.
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DISCUSSION
The goal of the present study was to extend prior research on ICT-related
stress and strain by testing the health implications and motivational drivers of
private communication load and Internet multitasking in a representative
sample of the general population and over the life span. The results of our
study strongly emphasize the relevance of addressing stress and strain evol-
ving from the spreading “always on”communication practices. Our findings
with regard to Hypotheses 1 and 2 clearly demonstrate that communication
load resulting from sending, receiving, and checking private e-mails and social
media messages, as well as Internet multitasking are significantly related to
increased perceived stress. The indirect effects of communication load and
Internet multitasking on burnout and depression/anxiety (see Hypotheses 3a
and 3b in the results section) further demonstrate that the potential health
impairments resulting from private ICT-strain extend to decreased levels of
psychological well-being. To the best of our knowledge, our study is the first
to demonstrate such negative effects of ICT strain in the general population
and over the entire life span. The present study thus crucially extends
prior research by demonstrating a) that the strain resulting from private CMC
has similar effects on psychological health and well-being as ICT-induced
information overload in the workplace and b) that these effects occur in the
general population and do not only affect a small “net avant-garde”restricted
to members of the generation of digital natives.
In addition to the effects of communication load and Internet multitasking on
psychological health and well-being, the present study also sheds light on the
motivational drivers of communication patterns that promote ICT-related stress.
As predicted in Hypotheses 4 and 5, both social pressure as well as the fear of
missing out make Internet users more susceptible to CMC behavior that, ulti-
mately, increases their risk of stress and psychological health impairments. Prior
research suggests, however, that social motivations and the need for information
are not the sole predictors of Internet use and media multitasking. Other factors
such as affective gratifications, media enjoyment, convenience, and efficiency, as
well as habitual media use have been identified as additional drivers of social
media use and Internet multitasking (Hwang et al., 2014; Quan-Haase & Young,
2010; Zhang & Zhang, 2012). Explicating the role of these variables as potential
drivers of digital stress remains an important task for future research.
While the present study clearly underlines the universal relevance of ICT-
related stress over the life span, our findings also demonstrate marked dis-
crepancies between different age groups both with regard to the effects of
communication load and Internet multitasking on psychological health
(see Research Question 1) as well as the motivational drivers of ICT use
(Research Question 2): While younger Internet users were less susceptible
to the negative effects of communication load, higher numbers of sent and
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received mails and social media messages and more frequent checking beha-
vior was significantly related to stress and, in turn, to burnout, depression, and
anxiety in the age group of users above 50 years. The opposite pattern of
results was evident for Internet multitasking, which was more strongly related
to stress and resulting psychological health impairments in young and middle-
aged users than in older users. Furthermore, older and younger users in the
present study engage in stress-inducing ICT usage patterns for different moti-
vational reasons. Social pressure had a stronger effect on the communication
patterns of younger individuals while older users were less likely to give in to
social availability demands. The opposite pattern of results was observed for
the fear of missing out. Whereas fear of missing out was a significant motiva-
tional driver of communication load in all age groups, its influence was
particularly pronounced in the group of older Internet users. The present
study, thus, expands prior research from Przybylski et al. (2013) by identifying
age as a moderator of the effects of the fear of missing out on CMC.
Although our findings largely support our hypotheses and provide new
insights into the potential origins and effects of ICT-related stress, a number of
limitations have to be taken into consideration when interpreting our results. A
first limitation refers to the cross-sectional nature of our data. Our findings are
exclusively correlational and do not provide unequivocal evidence concern-
ing causality or the direction of effects found in our data. This appears to be a
particularly relevant issue with regard to the relationship between ICT use and
stress. Whereas communication load and Internet multitasking are treated as
sources of perceived stress in the present study, the direction of effects could
also be reversed. In fact, research on Internet addiction suggests that proble-
matic forms of Internet use can represent a dysfunctional strategy of coping
with stress and frustration (e.g., Li, Zhang, Li, Zhen, & Wang, 2010). The same
mechanisms could also apply to the nonpathological forms of ICT use
assessed in the present study. We, thus, computed an alternative statistical
model (i.e., social pressure and fear of missing out as predictors of perceived
stress which, in turn, predicts communication load and Internet multitasking).
This model, however, showed a lower model fit (χ
2
(1959)= 5816.39, p<.001,
CMIN/df = 2.97, CFI = .898, RMSEA = .036, 90% CI = [.035, .037], and
SRMR=.10) than our original model. We, thus, believe that it is justified to
retain the model in its current form. Ultimately, however, the cross-sectional
data collected in the present study do not provide a sufficient basis to
determine the direction of effects between the observed variables. Future
research should, thus, further explore the effects of communication load and
Internet multitasking on stress and psychological well-being in experimental
settings or with longitudinal designs. Longitudinal studies would also help to
address the question whether the age-differences found in the present study
originate from age effects (e.g., age-related declines in cognitive capacity) or
from cohort effects (e.g., the different socialization of digital natives and digital
immigrants).
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A second methodological limitation concerns the use of self-report
measures. All variables were assessed based on the subjective self-reports of
our participants which may be biased or subject to systematic error. Psycho-
logical health impairments such as burnout, depression, and anxiety are
socially stigmatized. Responses to the respective self-report measure may,
thus, have been affected by social desirability considerations. Future research
on the psychological health impact of ICT-strain would, thus, strongly benefit
from the use of psychophysiological measures of stress and more elaborate
clinical assessments of psychological symptoms. Such alternative measures of
psychological health could also help to address issues of validity. As reported
in the results section, the stress and the anxiety and depression measure used
in the present study showed suboptimal discriminant validity due to their high
mutual correlations. This may at least in part be explained by the brevity of the
PHQ-4. A more differentiated assessment of different dimensions of psycho-
logical health could help to address validity issues in future research. Further-
more, the accuracy of self-report measures of media use is subject to ongoing
debate. The estimation of behavior frequencies poses a significant cognitive
challenge to survey participants that may result in distorted estimates of media
use (Greenberg et al., 2005). Self-report data of CMC (e.g., sent and received
text messages) typically show only moderate correlations with server log data
(e.g., Boase & Ling, 2013). Such effects may affect the accuracy of the com-
munication load measure used in the present study. Future studies addressing
the sources of digital stress would thus benefit from more objective measures
of CMC-behavior, such as tracking, experience sampling, or diaries.
A third limitation of the present study refers to the treatment of age as a
moderator variable. Participants were separated into three age groups refer-
ring to the generation of digital natives (14–34 years) as well as middle-aged
(35–49 years) and older (50–85) members of the generation of digital immi-
grants. We are aware that the differentiation of digital natives and digital
immigrants has been criticized for its relative theoretical simplicity (Hargittai,
2010; Helsper & Eynon, 2010). We do believe, however, that this generational
approach provides an informative structure for the explorative research ques-
tions concerning age as moderator (Research Questions 1 and 2) addressed in
the present study. Given the fact that no prior research has systematically
explored age differences in digital stress and taking into account the broad
range of effects tested in our theoretical model, we believe that a more fine-
grained differentiation of age groups that could theoretically account for age
differences both in the motivational drivers of ICT use as well as the resulting
effects on stress and psychological health is beyond the scope of the present
study and an open challenge for future research. Furthermore, we believe that
the additional moderator analyses based on age as a continuous variable
reported above can compensate for potential shortcomings of our categorical
age groups and thus complement the results of our three-group structural
equation model in a meaningful way.
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Besides these methodological limitations, the present study leaves a
number of further questions for future research. While we have discussed
potential reasons for the age differences in perceived stress resulting from ICT-
use in our theoretical argumentation, none of these underlying processes and
variables has been assessed in the present study. It, thus, remains unclear why
older individuals were more vulnerable to the detrimental effects of commu-
nication load than younger Internet users. The decline of cognitive capacity at
a higher age (Verhaeghen & Cerella, 2002; Verhaeghen & Salthouse, 1997)
could be a plausible explanation for this age difference. A current review
article by Salthouse (2012) comes to the conclusion that the existing empirical
evidence clearly suggest a monotonic age-related decline in central cognitive
variables such as reasoning and information processing abilities with correla-
tions between age and cognitive performance ranging from –.30 to –.50.
Within the context of transactional stress theory this suggests that due to
decreased cognitive capacity, older users possess fewer resources to cope
with the cognitive strain elicited by communication demands and should
show a higher likelihood for stress reactions. This explanation should equally
apply to the effects of Internet multitasking on perceived stress which, how-
ever, did not show the same pattern of interaction with age. The comparison
of our three subsamples even suggests that older individuals are better at
coping with Internet multitasking than younger users. This effect could be a
result of accommodation: Prior research on aging and cognitive ability
suggests that older individuals engage in various strategies to compensate
for age-related decreases in cognitive capacity, such as the avoidance of
deficit-revealing situations (Salthouse, 2012). With regard to Internet multi-
tasking this could imply that older users more actively avoid situations in
which multitasking exceeds their cognitive capacity, for example, by choosing
relatively undemanding concurrent activities. Such accommodation strategies
may be less easily available with regard to communication load as users have
limited control over incoming messages and the necessity to respond.
Age-related differences in cognitive capacity may not be the sole origin of
age differences in stress reactions to ICT-related strain. Older and younger users
may also differ systematically in the perceived gratifications of CMC use, resulting
in different stress appraisals. In a current study by Ellison et al. (2014), age was
negatively related to social capital obtained on Facebook. This could suggest that
the social gratifications received through CMC use are particularly rewarding for
younger users, whereas for older users online communication plays a less sub-
stantial role for maintaining social relationships. This could have a crucial influ-
ence on the stress appraisal process as the social gratifications obtained through
CMC might at least partly compensate for the strain resulting from communication
load. This stress-buffering effect, however, may be less pronounced for older
users who seem to benefit less from the social gratifications of CMC. Finally, age
differences in self-control could be a further underlying mechanism providing a
theoretical explanation for the pattern of results found in the present study. As
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discussed above, media multitasking can evolve into a strongly habitual and
deficiently self-regulated behavior that may interfere with other tasks and respon-
sibilities in daily life (David et al., 2015). Internet multitasking could, thus, be a
form of procrastination and represent instances of Internet use at the expense of
other, less hedonically pleasant primary activities. Younger users might be more
susceptible to deficiently self-regulated media multitasking because they engage
in media multitasking more frequently (Carrier et al., 2009) and are, thus, more
likely to develop a multitasking habit. Furthermore, according to a meta-analysis
by Steel (2007), age is strongly negatively correlated with the tendency to
procrastinate. In combination, these findings suggest that younger user may
have a higher risk of experiencing conflict between habitual Internet multitasking
and other goals and obligations. These goal conflicts are likely to result in
negative self-related emotions (Reinecke, Hartmann, et al., 2014) and should,
thus, increase the likelihood of stress reactions due to Internet multitasking.
On a more general level, the present study raises a number of further
questions concerning the effects of CMC on psychological well-being. While
the present study has focused on the risks and potential detrimental effects
arising from CMC for psychological health, there can be no doubt that
personal online communication and social media use provides a plethora of
gratifications and positive experiences that strongly and positively
contribute to well-being (e.g., Ellison et al., 2014; Reinecke, Vorderer, et al.,
2014). The results of the present study in no way place the beneficial potential
of CMC in question. Rather, they suggest that future research needs to
integrate findings on the positive versus negative effects of CMC more system-
atically and coherently. The fact that the existing research has found mixed
effects of online communication on psychological well-being underlines the
need to learn more about the moderator and mediator processes that lead to
beneficial versus detrimental effects of CMC and make some ICT-users more
susceptible to the psychological risks of online communication than others.
We believe that addressing the questions outlined above and gaining a better
understanding of the processes that make CMC a rewarding and enriching
experience versus a stressful and health impairing burden is of highest societal
relevance and represents a pressing challenge and a worthwhile task for
future CMC research and media psychology.
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