Content uploaded by Mikyeung Bae
Author content
All content in this area was uploaded by Mikyeung Bae on Jun 08, 2022
Content may be subject to copyright.
Coping strategies initiated by
COVID-19-related stress,
individuals’motives for social
media use, and perceived
stress reduction
Mikyeung Bae
Oklahoma State University, Stillwater, Oklahoma, USA
Abstract
Purpose –This study examined whether individuals’coping strategies and their motivations for social media
use act as mediators between actual COVID-19-related stress and the perception that social media use can
reduce stress.
Design/methodology/approach –This study empirically develops and tests a research model with data
(N5503) collected through Amazon Mechanical Turk. A path analysis was used to test the research model.
Findings –The path analysis indicated that active coping initiated by individuals under COVID-19-related
stress was more likely to be associated with information and social interaction needs, leading the individuals to
perceive the use of social media as the cause for stress reduction. The expressive support coping strategy
motivated the individuals under stress to seek social interaction, leading individuals to perceive that activities
on social media reduced their stress during the pandemic. Emotional venting and avoidance coping strategies
significantly impacted escape, social interaction, and entertainment seeking by allowing individuals to get
absorbed in social media activities and forget unpleasant thoughts associated with the pandemic.
Originality/value –No previous study has explored the relationship between decisions around the type of
coping strategy used and motivations for media usage, which leads to stress reduction. Understanding how
stress-induced coping strategies influence social media users’specific motivations and reduce users’stress
levels would help communicators understand how users’can encourage individuals to cope with stress by
presenting individuals with more effective social media, resulting in stress reduction and improved well-being.
Keywords COVID-19, Coping strategies, Motivations, Social media use, Stress reduction
Paper type Research paper
1. Introduction
Social distancing, quarantining, and staying at home to prevent the spread of COVID-19 in
the past two years have had significant effects on media consumption, as demonstrated by
the rise of social media usage. A recent Poll (2020) found that 51% of adults in the USA were
increasingly using social media since the outbreak. The primary preventive efforts for the
COVID-19 pandemic continue to be physical restrictions, including distancing, quarantine, or
isolation. More importantly, the unexpected deaths in large numbers led individuals to
deliberate their own mortality. Fear and anxiety about a new disease and its possible personal
outcomes can be overwhelming, causing strong negative emotions. In a Kaiser Family
Foundation (KFF) Tracking Poll (2021) conducted in January, 41% of adults in the USA
reported that their mental health has been adversely affected due to the worry and stress over
the disease.
Studies have found that the damage associated with stress can be mitigated by coping
responses –the cognitive and behavioral efforts that manage specific external and internal
demands appraised as threatening or beyond the control of a person (Lazarus and Folkman,
1984). Although numerous coping methods exist, media consumption is the most central to this
study. Evidence suggests that media are capable of offering relaxing experiences to
individuals, potentially reducing their stress levels (Leung, 2007,2015;Nabi and Krcmar, 2004).
Individuals
coping COVID-
19-related
stress
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1066-2243.htm
Received 1 May 2021
Revised 12 January 2022
30 April 2022
Accepted 1 May 2022
Internet Research
© Emerald Publishing Limited
1066-2243
DOI 10.1108/INTR-05-2021-0269
The intensive use of social media during the pandemic could be considered as a phase or
coping mechanism. The fear of infection and social restrictions likely brought about
significant changes to the way individuals interacted with social media, driving them to seek
further connection and entertainment for relief (Snyder, 2020). Individuals perhaps
considered social media as a key news source for the latest updates on the pandemic and
global health situation (Nielsen, 2020). They perhaps found social media as a safe space to
interact, be entertained, distract themselves, and find inspiration without any risk of
contagion (Nielsen, 2020). People experiencing stress appeared to seek comfort through social
media, receive encouragement, and care about other’s feelings (Leung, 2007).
Surprisingly, the majority of the research on the health effects of social media exposure
has focused on its negative consequences on users’physical well-being. For example, social
media usage has been found to influence both depression and anxiety (Primack et al., 2017),
reduce affective well-being and life satisfaction (Kross et al., 2013), and cause sleep
disturbance (Levenson et al., 2016;Schuur et al., 2019), perceived social isolation (Primack
et al., 2017), and social media addiction (Masur et al., 2014). A recent study (Gao et al., 2020)
conducted during the COVID-19 outbreak in Wuhan, China, addressed the negative effects of
social media use on people’s well-being.
While there is substantial evidence that social media has a negative impact on the mental
health and well-being of its users, this study focuses on how social media can also be an
effective tool to implement coping strategies. Media-focused coping has been evaluated as a
dysfunctional coping strategy (Kuss et al., 2017). In particular, within the negative view,
social media addiction or problematic media use is usually associated with avoidance (e.g.
Brand et al., 2014) or escapism (e.g. Schneider et al., 2018), and equated with a negative coping
style (e.g. Li et al., 2016). However, empirical evidence for such a negative impact of escapism
or avoidance coping is scarce (Halfmann and Reinecke, 2021). Furthermore, as discussed
above, social media has become increasingly important in dealing with stressful situations
and it is fairly common for individuals to mobilize at least some social media resource after
experiencing a negative life event (Leung, 2007;Van Ingen et al., 2016;Van Ingen and Wright,
2016). Social media allows individuals to present themselves and establish or maintain a good
relationship with others, resulting in stress reduction (Leung, 2007,2015). Sippel et al. (2015)
noted the importance of social networks in promoting resilience when facing stress and
trauma. Media psychologists have underscored the relevance of media use in coping with
stressful circumstances, and the potential importance of media use as a psychological
resource in times of crisis (Watson, 2018). Recent studies have found that acute stress and
anxiety resulting from the COVID-19 pandemic were associated with an increased tendency
to use media as a coping tool, and some media coping strategies were associated with
psychological well-being (Eden et al., 2020).
Faced with a global pandemic, coping attempts via social media use may be natural.
Previous research suggests that media exposure is a common coping tool when other coping
resources are limited or unavailable (Kardefelt-Winther, 2014). Dwivedi and Lewis (2021)
found that individuals experiencing decreased social support and occasions for socializing
were more dependent on social media to compensate for the missing social connections.
Disconnection has increased social media use as a coping strategy (Sheldon et al., 2011).
During social distancing, crucial coping resources, such as the availability of social support,
may be largely absent or impaired. As such, social media use can be an effective coping
mechanism in response to the limited offline social connection and support.
How people cope with problems has been studied over decades, but with several negative
life events during the pandemic, the topic has never been more relevant. Although previous
research examined the effectiveness of different coping strategies (e.g. Lazarus and Folkman,
1984) and the role of the Internet in coping (e.g. Leung, 2007;Van Ingen et al., 2016), no study
has examined the role of coping strategies and social media consumption in stress reduction.
INTR
The most cited categories of coping strategies are active coping (including actions of
gathering information and planning to deal with the stress source), expressive support
coping (including seeking help and comfort), emotional venting coping (including expressing
one’s unpleasant feelings), and avoidance coping (including distracting oneself from the
sources of the problem) (Duhachek, 2005;Folkman and Lazarus, 1985;Stanton et al., 2000).
The uses and gratifications theory posits that individuals seek uses and gratifications to
satisfy their psychological needs (e.g. informational, social, emotional, and escape needs)
through selective exposure to media (Katz et al., 1973;Palmgreen et al., 1985). With diversion
being identified as a key psychological need, the desire to reduce or manage stress would
trigger this particular need, motivating media selection (Nabi et al., 2017). Ruggiero (2000)
emphasized the importance of the uses and gratifications perspective to study social media.
As the underlying assumption is that individuals are actively involved in media usage, the
theory has become increasingly relevant in social media studies on active social interaction
and engagement (Sundar and Limperos, 2013). Similarly, the mood management theory
predicts that individuals, when motivated by hedonic desires to regulate their moods, select
media content to meet these goals, one of which may be to manage the outcome of stressful
experiences (Zillmann, 1988,2000). During the pandemic, when social distancing has become
a norm, it is natural to think that social interaction may be the best way to relieve one’s stress
level and improve their mental well-being. Several scholars have examined the role of social
interaction in providing emotional support (Damian and Ingen, 2014;Frison and Eggermont,
2015;Leung, 2007;Van Ingen et al., 2016). However, most of them provide only fragmented
information about online coping and, importantly, do not pay attention to how the stressed
individuals’coping strategies are associated with their motivations to use social media, which
may alleviate distress, and thereby predict their social well-being.
Given that the functional approach suggests that persuasive procedures are more effective
when they match the functional basis of targeted attitudes (Lavine and Snyder, 1996,2000), this
study proposes that the more stressed individuals employ expressive support coping, the more
their motivations for using social media are associated with meeting social and emotional
needs, leading to greater perceived stress reduction. Active problem-solving as a coping
mechanism is expected to be associated with information needs, leading to higher perceived
stress reduction. When stressed individuals initiate emotional venting or avoidance coping, it
motivates them to engage with social media by expressing unpleasant feelings, seeking
entertainment, or getting involved in social interaction activities. They do this to forget about
the stressful environment that causes the feeling of alienation.
As the pandemic has had a significant impact on social media usage, understanding how
stress-induced coping strategy influences social media users’specific motivations and
reduces their stress levels will help communicators in understanding how they can encourage
individuals to cope with specific types of stress, by presenting them with more effective ways
to employ social media for stress reduction and well-being.
2. Theoretical frameworks
2.1 Stress and coping strategies
Stress refers to a process of behavioral, emotional, mental, and physical reactions caused by
prolonged, increased, or new pressure that is significantly greater than the resources
possessed by individuals (Carver, 2011). No event or situation is considered to be inherently
stressful; rather, the individuals’subjective judgment of the situation as threatening or
harmful is defined as a stressor (Folkman and Lazarus, 1985). However, the damage
associated with stress can be mitigated by coping strategies (Lazarus and Folkman, 1984).
Commonly studied categories of coping strategies in the transactional theory of stress and
coping (Lazarus and Folkman, 1984) include problem-focused active coping (including actions
Individuals
coping COVID-
19-related
stress
emphasizing the cause of the threat, such as how to improve a situation produced by the threat,
gathering information, or planning actions on handling the source), expressive support-seeking
(including seeking help, comfort, and social approval), avoidance (including attempting to
create physical or mental distance between oneself and a stressor, or close off oneself mentally
from the source of the stressor), and emotional venting (including attempting to express one’s
emotions) (Duhachek, 2005;Park and Folkman, 1997;Stanton et al.,2000).
Additional coping strategies are often referred to as emotion-focused strategies and they
may represent variants of distancing or emotional venting (Carver and Connor-Smith, 2010).
Along with problem-focused coping strategy, the transactional theory of stress and coping
(Lazarus and Folkman, 1984;Park and Folkman, 1997) proposes an emotion-focused coping
strategy, which entails actions such as avoiding a situation or engaging in activities to divert
one’s attention away from a problem to regulate distress (Folkman, 2011). However, Stanton
et al. (2000) highlight that the range of emotion-focused coping strategies employed is quite
broad, including strategies such as avoidance of unpleasant thoughts about the stressful
situation and venting to feel better. Accordingly, the aggregate of these distinct aspects of
emotion-focused coping might make the term “emotion-focused”ambiguous (Baker and
Berenbaum, 2007).
Duhachek (2005) also proposes expressive emotional venting and social support-seeking
coping, along with problem-focused active coping and avoidance coping. Coping based on
expressive social support seeking entails attempting to collect social resources to act toward
ameliorating a stressor and getting advice from someone about what to do (Duhachek, 2005).
When individuals are experiencing negative events, they attempt to conserve and seek key
social resources, such as interpersonal relationships (Barrick et al., 2002;Chiaburu et al., 2007).
Relationship maintenance, which refers to individuals’motivation to keep in touch and
maintain social bonds with others (Ong et al., 2006), is consistent with investment in social
resources. Previous studies have summarized the basic dimensions of coping strategy into
active coping, expressive support coping, emotional venting coping, and avoidance coping.
2.2 Motivations of social media use
The uses and gratifications theory assumes that the appropriate media and their messages
seek to gratify a variety of social and psychological needs (Katz et al.,1973).
Socio-psychological origins of needs give rise to motives for behavior, which are guided by
social circumstances into seeking various gratifications through media consumption
(Palmgreen et al., 1985). As the uses and gratifications theory assumes that people are
active and selective in their media use, it is considered as a relevant approach to investigate
social media use, as social media extracts active participation from the users. Over time,
studies have adopted varying lists of motivations for media use (Ruggiero, 2000). Although
some differences have been observed across specific social media applications, the
fundamental needs or motivations underlying social media use are similar. These include
information, entertainment, social interaction, and escapism—the broad categories of needs
under the uses and gratifications approach (Bae, 2018).
Information motivation covers several information-related media gratifications. Sub-
motivations include examining what relevant events and conditions are occurring in
someone’s direct daily environment and in society (Muntinga et al., 2011), and seeking advice
and opinions (Kim et al., 2011;Lee and Ma, 2012;Leung, 2015;Wang and Fesenmaier, 2003). In
fact, social networking sites (SNS) become ideal places to satisfy information needs owing to
the trust individuals have in their online contacts and the richness of information available
(Agichtein et al., 2008).
Entertainment motivation covers several gratifications related to being diverted from
problems or routine; emotional release (Hong and Chiu, 2016), relaxation (Whiting and
INTR
Williams, 2013), and enjoyment (Kim et al., 2011;Shiau and Luo, 2013;Yoon and Rolland,
2015). Social interaction covers various media gratifications related to other people, for
example, gaining a sense of belonging (Seidman, 2013), connecting with friends, family, and
society (Bae, 2018;Chiu and Huang, 2015;Jung and Sundar, 2016;Lee and Ma, 2012), and
seeking emotional or other support (Bae, 2018;Muntinga et al., 2011). There has been an
increase in studies examining the role of social media in providing emotional and social
support for individuals under stress (Damian and Van Ingen, 2014;Frison and Eggermont,
2015;Leung, 2007,2015).
Escapism covers several avoidance-related media gratifications, which fulfill media users’
needs to distract themselves from their stressful daily routines (Knobloch-Westerwick et al.,
2009). Several studies suggest that engaging insocial media is closely related to escaping from
reality, looking for distraction, or coping strategies (Halfmann and Reinecke, 2021;Gao et al.,
2017;Kircaburun and Griffiths, 2019;Knobloch-Westerwick et al., 2009;Krueger, 2002;Masur
et al.,2014). Kircaburun and Griffiths (2019) found that individuals use Instagram as a tool to
distract themselves from reality, while Young et al. (2017) revealed that escapism leads
individuals to use SNS, resulting in active online political activities. In line with the uses and
gratifications perspective, influential work in the drive and motivation theory (i.e. self-
determination theory; Ryan and Deci, 2000) posits three major types of motivations: a drive
toward competence or agency, autonomy, and relatedness or social affiliation. These basic
psychological needs gratification has been linked to the use of both social media (Johnson et al.,
2021;Masur et al., 2014;Reinecke and Trepte, 2014;Sheldon et al., 2011), and movies or TV
series (Granow et al., 2018), and video clips with narratives (Slater et al., 2014). Accordingly, it
seems plausible to assume that individuals with limited access to avenues that make them feel
competent, autonomous, and socially connected attempt to compensate for intrinsic needs by
the gratifications derived from media use (Eden et al., 2020;Sheldon et al., 2011).
Mood management theory posits that individuals who are motivated by hedonic desires to
regulate their moods, select media content to meet these goals, one of which may be to manage
reacting to stressful experiences (Zillmann, 1988,2000). Indeed, empirical evidence shows
that people turn to different media platforms in response to daily hassles and stress
(Anderson et al., 1996;Thayer et al., 1994). For example, studies found that media
consumption benefits well-being through positive affect and stress reduction (George et al.,
2013;Leung, 2007,2015;Rui and Stefanone, 2013). Nabi et al. (2016) further found that
individuals’TV viewing reduced their stress-related hormone, cortisol, and calmed them
down and relaxed them after stressful events. Moreover, individuals’stress levels motivate
them to keep in touch and maintain social bonds with others, which helps them to relieve or
avoid unpleasant feelings (George et al., 2013;Leung, 2007,2015;Rui and Stefanone, 2013).
Halfmann and Reinecke (2021) found that escapism through social media use can be a
functional short-term strategy, in that it may temporarily help the individual reduce stress
and prepare for subsequent problem-focused coping attempts. These studies that are
grounded in the mood management theory suggest that media can temporarily alleviate the
negative effects of stress by displacing the anxious thoughts and substituting the negative
effects with positive effects (Leung, 2015).
2.3 Functional matching effect
To recap, the literature on the transactional theory of stress and coping has virtually ignored
the use of media as a viable way to mitigate stress. Although scholars have identified media
consumption as a potential resource for stress management, the related research has not fully
acknowledged it (Nabi et al., 2017). Media psychology research has underlined the importance
of studying media use for coping purposes both as a motive for media use and as a behavior in
the stress management process (Wolfers and Schneider, 2021); however, there is no deeper
Individuals
coping COVID-
19-related
stress
reflection on the exact function of social media needs in the transactional theory of stress (see
Table 1 for an overview of previous research perspectives and findings). Thus, primarily,
how people manage their stress and how this fits in with the repertoire of motivations that
help predict social media use, which in turn alleviates stress, remains unanswered.
During the COVID-19 pandemic, when confronted with the limited control on external
problem-solving measures, coping strategy or motivation for media use alone may not
determine the effectiveness of coping processes. The functional approach suggests that the
persuasive procedures are more effective when they match the functional basis of the
targeted attitudes (Lavine and Snyder, 1996,2000). The correspondence between an
individual’s goal and the means of goal pursuit results in a positive subjective experience that
is transferred to the evaluation of the target object (Labroo and Lee, 2006). Applying the
functional approach to the matching effect between individuals’coping and media use
motivation, this study highlights the psychological mechanism underlying how decisions
regarding the type of coping strategies used are related to the motivation for media use,
leading to stress reduction.
As previous studies have suggested, when individuals employ an active coping strategy,
they think about how to improve a stressful situation, and seek guidance, advice, and
information that can provide them with a solution (Folkman, 2011), which characterizes
information-seeking and social-interaction motivations. Van Ingen et al. (2016) found that
active coping and planning to find remedies were the most reported online coping strategies
among the study participants.
When employing expressive social support coping, individuals regulate their emotions by
expressing care and affection, engaging in problem-solving talk (Wendorf and Yang, 2015),
and seeking advice from someone about ways to reduce the negative effects of stress (Mathur
et al., 2008), which corresponds with social interaction motivations. Individuals under stress
compensate for their social anxiety by engaging in online communication (Baker and Oswald,
2010). In some cases, online networks provide opportunities to communicate with others more
comfortably, which provides these individuals with greater opportunities, increased sources
of social support, and a greater diversity in terms of life experiences and knowledge than
what is typically available offline (Van Ingen and Wright, 2016;Wright and Miller, 2010).
Thus, the following hypotheses are proposed.
H1. Individuals under stress who employ an active coping strategy will be associated
with (a) information and (b) social interaction motivations for using social media.
H2. Individuals under stress who employ an expressive support coping strategy will be
associated with social interaction motivations for using social media.
However, stressed individuals who initiate emotional venting coping may engage in several
activities to alleviate their negative feelings, such as updating their status primarily for the
sake of disclosing emotional information to others (Hampton et al., 2011), or engaging in
relationship maintenance activities on social media to express their negative feelings
(Wendorf and Yang, 2015), or interacting substantially with friends, acquaintances, or new
people on SNS to relieve stress by expressing their negative feelings or by receiving
encouragement from them (Damian and Van Ingen, 2014;Frison and Eggermont, 2015;Hong
and Chiu, 2016;Lee and Ma, 2012;Leung, 2007). Emotional venting coping may also be
associated with escapism because stressed individuals may try to regulate their unsolicited
emotional states by withdrawing from stressful situations (Hoffmann et al., 2017).
When avoidance coping is initiated by stressed individuals, they may engage in social
media to forget the stressful environment and distract themselves from the potentially
negative details about the source of stress (Ehrich and Irwin, 2005;Masur et al., 2014); this
situation corresponds with escapism motivation. The compensatory Internet use theory
INTR
Literature Theory Coping mechanism Finding
Stanton et al.
(2000)
TTSC Functional emotional
expressive coping
Mediating effect of emotional expressive
coping in relationship between stressful
life event and psychological well-being
Wright and Bell
(2003)
CMC Social support seeking Mediating role of social support through
computer-mediated support groups in
relationship between stress and
psychological well-being
Leung (2007) U&G, MMT N/A Mediating roles of entertainment and
relationship maintenance motivations in
the effect of stress on Internet use.
Mediating effect of perceived social
support in the relationship between stress
and stress reduction
Sheldon et al.
(2011)
SDT Pleasant distraction
from problems
Mediating effect of Facebook use in
relationship between perceived social
disconnection and Facebook addiction
Kircaburun and
Griffiths (2019)
Social presence N/A Mediating role of escapism in the effect of
Instagram use on problematic Instagram
use
Vitak and Ellison
(2013)
CMC Social support seeking Mediating role of social support seeking in
the effect of social media use on stress
reduction
Brand et al. (2014) CT Maladaptive Avoidance
coping
Effect of maladaptive avoidance coping
and need satisfaction expectancy on
Internet addiction
Masur et al.
(2014)
U&G, SDT Escapism Mediating roles of motivations to use SNSs
for escapism/acquiring information/
meeting new people in the effect of low
levels of autonomy/competence/
relatedness on SNS addiction
Frison and
Eggermont
(2015)
TTSC Social support seeking Mediating effect of social support seeking
through Facebook in the effect of daily
stress on depressed mood
Leung (2015) U&G, MMT Media as a stress coping
tool
Mediating effects of entertainment, social
interaction, and information seeking
motivations in relationship between tablet
use in solitude and stress reduction
perception
Li et al. (2016) SDT; TTSC Positive/approach vs.
negative/avoidance
coping
Positive/approach coping attenuated the
link between Internet addiction and
psychological need satisfaction. No
relationship No evidence for the
moderating role of negative/avoidant
coping
Van Ingen et al.
(2016)
TTSC Functional emotion-
focused coping
No association between online problem-
focused coping and well-being, Negative
relationship between online
socioemotional coping and well-being
Van Ingen and
Wright (2016)
CT Online as a coping tool Positive relationship between loneliness
and mobilizing online coping resources
Gao et al. (2017) Belongingness N/A Mediating role of escapism and pleasure in
the effect of social presence on SNS
addiction
(continued )
Table 1.
Summary of theories
and research findings
of the reviewed articles
Individuals
coping COVID-
19-related
stress
(Kardefelt-Winther, 2014) suggests that when individuals have psychological problems in the
real world, they use virtual networks to escape their negative feelings. Social media may fulfill
individuals’needs to distract themselves from stressful situations in a dreamlike,
Literature Theory Coping mechanism Finding
Kuss et al. (2017) TTSC Dysfunctional escapist
coping
Mediating effect of dysfunctional media-
focused escapist coping between
Psychopathology and Internet addiction
Nabi et al. (2017) U&G, MMT Media as a stresscoping
tool
Positive relationship between social
support coping and media use among
student sample
Negative relationship between social
support and emotional expressive coping
strategies and media use among cancer
survivors
Stevens and
Carpentier (2017)
MMT Avoidance coping Moderating role of dispositional avoidance
coping tendency in predicting hedonic
media choice to reduce negative affect
Young et al.
(2017)
U&G Escapism No relationships between stress, escapism,
passive Facebook use, and passive
Facebook addiction
Jurgens and
Helsloot (2018)
TTSC Problem-solving Positive roles of information gathering,
information dissemination, collaborative
problem-solving through social media
during disasters
Meier et al. (2018) U&G
TTSC
Dysfunctional escapism Mediating role of escapist Facebook use in
the effect of low life satisfaction and strains
Schneider et al.
(2018)
TTSC Maladaptive avoidance
coping
Mediating effect of avoidance coping (e.g.
denial and behavioral disengagement) in
relationship between the total gaming
hours on Internet gaming disorder
symptoms
Watson (2018) Cyber
psychology
Emotion-oriented
coping
Mediating role of emotion-oriented coping
in the effect of community stress on
bloggers’subjective well-being
Eden et al. (2020) TTSC, MMT,
SDT
Functional emotion-
focused coping
Mediating effect of escapist coping in the
effect of stress on negative affect,
Mediating effect of hedonic media use in
the effect of stress on flourishing,
mediating effect of avoidant coping in the
negative effect of stress on mental health
Dwivedi and
Lewis (2021)
CT Social media as a coping
tool
Mediating role of social exclusion concern
in the effect of societal and financial
concerns on social media use
Halfmann and
Reinecke (2021)
TTSC Functional escapism Mediating role of functional escapist
coping in the effect of binge-watching on
stress reduction
Johnson et al.
(2021)
SDT N/A Mediating role of perceived need
satisfaction (e.g. autonomy and
competence) via social media in the effect
of self-control on self-control capacity
Note(s): Abbreviation of theories: TTSC 5transactional theory of stress and coping; CMC 5computer-
mediated theory
U&G 5uses and gratification theory; MMT 5mood management theory; SDT 5self-determination theory
and CT 5compensatory theory
Table 1.
INTR
make-believe world of media (Bae, 2018;Knobloch-Westerwick et al., 2009;Kwon et al., 2013;
Papacharissi and Mendelson, 2011). Stressed individuals may not actively seek information
to solve the stressful situation. However, they may engage in overall social media use for
entertainment, including watching shared videos or photographs, and for social interaction to
establish online social relationships to escape from the problem stressors (Kwon et al., 2013;
Masur et al., 2014;Young et al., 2017). Thus, the following hypotheses are proposed.
H3. Individuals under stress who employ an emotional venting coping strategy will be
positively associated with (a) social interaction, (b) entertainment, and (c) escapism
motivations for using social media.
H4. Individuals under stress who employ an avoidance coping strategy will be positively
associated with (a) escapism, (b) social interaction, and (c) entertainment motivations
for using social media.
Studies reported that information seeking (Lee and Ma, 2012;Leung, 2015), entertainment
seeking (Shiau and Luo, 2013;Yoon and Rolland, 2015), socializing seeking (Jung and Sundar,
2016), social/emotional support seeking (Damian and Van Ingen, 2014;Leung, 2015), and
escapism (Halfmann and Reinecke, 2021;Young et al., 2017) are primary motivations for social
media use. Stressed individuals may have their own expectations that these needs will be
satisfied by particular types of contents, and spend more time on social media (Katz et al., 1973).
Transactional theory of stress and coping posits that if individuals perceive situational
demands as stressful, they evaluate their coping options along with the expected effectiveness
of using a particular coping strategy (Lazarus and Folkman, 1984). This strategy ensures that
the desire to reduce or manage stress induced by the pandemic would trigger a particular need
that would, in turn, motivate media consumption (Nabi et al.,2017). Therefore, social media use
may be considered a potential resource for stress management. Further, under the functional
approach (Lavine and Snyder, 1996,2000), the correspondence between stressed individuals’
coping strategies and media use motivations may play an important role in the actual time
spent on social media. Individuals may be motivated to cope with their stress by undertaking
certain coping behaviors on social media. Thus, it is reasonable to infer that stressed
individuals’social media use would depend on their adopted coping strategies and motivations
for the media use, and the following hypothesis is proposed.
H5. (a) Information seeking motivation, (b) social interaction motivation, (c)
entertainment motivation, and (d) escapism motivation will positively influence
stressed individuals’social media use.
2.4 Social media use and stress reduction
Social media has been blamed for the rise in mental health problems. Several studies report
associations between the increased time spent on social media and heightened levels of
mental health problems (Banjanin et al., 2015;Barry et al., 2017;Scott and Woods, 2018). Time
spent on social media might displace other more important activities protecting mental
health, such as sleep (Scott and Woods, 2018) or physically meeting with friends (Twenge,
2017). However, previous studies have not found evidence that time spent using social media
might influence an individual’s mental health over time (Berryman et al., 2018;Coyne et al.,
2020). Kardefelt-Winther (2014) found that the relationships between social anxiety and
excessive online gaming lost significance when stress was controlled for. The author further
proposed a theory of compensatory Internet use where negative life situations can give rise to
a motivation to go online to alleviate negative affect. According to this perspective, if life is
characterized by a lack of social stimulation, the individual is motivated to go online to
socialize. This theory has been supported by the media-focused coping research, where
Individuals
coping COVID-
19-related
stress
individuals facing decreased social support or social connection are more likely to depend on
media to compensate for the missing social support (Hofer and Eden, 2020) and to remain in
contact with others (Eden et al., 2020).
Conversely, social media use has been found to be linked to positive well-being in users
(Grieve and Watkinson, 2016;Reinecke and Trepte, 2014). Stressed individuals might turn to
social media as a form of escapism to numb emotional pain (Coyne et al., 2020), as a form of
social support-seeking, which led users to reduce their distress levels (Berryman et al., 2018).
Individuals who engaged in problem-solving interactions with other users on Facebook as a
form of coping mechanism had higher success in reducing stress levels (Stevens et al., 2011).
Supportive interactions on SNSs, which serve as a significant psychological coping resource,
have a buffering effect, reducing feelings of stress (Cohen and Lancaster, 2014;Sippel et al.,
2015;Wright, 2000). Others suffering from COVID-19-related stress may be able to show
empathic understanding, and give appropriate information and advice (Morelli et al., 2014;
Thoits, 2011;Van Ingen et al., 2016;Wu and Bernardi, 2021), giving relief to the stressed
individuals. Such individuals turn to social media to entertain themselves as an emotional
venting coping strategy (Hampton et al., 2011;Wendorf and Yang, 2015), resulting in a feeling
of relief (Joinson, 2008). Leung (2015) also found that both fun-seeking and information-
seeking activities on SNSs were significantly related to stress reduction perception. Thus, the
following hypothesis is proposed.
H6. Social media use will have a positive impact on stress reduction perception.
Given that media consumption can be considered as the coping efforts made by stressed
individuals to manage stress, the following hypothesis is also proposed:
H7. Stress will indirectly influence stress reduction perception through coping strategies,
motivations for social media use, and the use of social media.
The proposed hypotheses are summarized in the model in Figure 1.
Coping strategy Motivation
Stress
Avoidance
Emotional
Venting
Expressive
Support
Active
Entertainment
Information
SM Use
Stress
Reduction
Escapism
Social
Interaction
H1a
H1b
H2
H3a
H3b
H3c
H4a
H6
H4b
H4c
H5a
H5b
H5c
H5d
Note(s): Dashed lines refer to indirect effect of stress on stress reduction perception
through coping strategies and motivations (H7), SM = Social media
Figure 1.
Conceptual model of
relationships between
coping strategies
initiated by COVID 19-
related stress,
motivations for social
media use, social media
use, and perceived
stress reduction
INTR
3. Method
3.1 Participants
Participants (N5503) were recruited through Amazon Mechanical Turk(MTurk) in November
2020 and received a $1 incentive each for participation. The study’s primary purpose was to
explore how the psychological mechanism underlying the decision regarding the type of coping
strategies used is related to social media usage leading to stress reduction. It was necessary to
investigate the mediating effects of coping strategies and motivations on perceptions of stress
reduction. The required sample size to detect the mediated effect is 400 or more for 0.8 power
(Fritz and Mackinnon, 2007); thus, the sample size was found reasonable for this study.
Previous research has documented that the psychometric quality of the data is as strong
as could be expected for more traditional means of data collection (Cheung et al., 2017;
Goodman et al., 2013;Hauser and Schwarz, 2016). MTurk participants are more attentive to
the details and procedures of the study than college students (Goodman et al., 2013;Hauser
and Schwarz, 2016;Ramsey et al., 2016). Attentiveness is important to ensure data quality
(Aust et al., 2013) and for statistical conclusion validity (Shadish et al., 2015), defined as the
extent to which statistical inferences made about the correlation (or covariation) between two
variables are warranted (Fleischer et al., 2015). MTurk data have been found to produce
similar effect size estimates in standard tasks (Chandler et al., 2014) and high test-retest
reliability (Chandler and Paolacci, 2017). Of these 503 participants, seven were eliminated
because of incomplete data. The final sample (N5496) comprised 302 males (60.9%) and 191
females (38.5%) with three participants (0.6%) not indicating their gender. The average age
was 38.76 (SD 511.34), with ages ranging from 21 to 72. Table 2 presents the participants’
demographic profiles and social media use.
To ensure that participants were experienced in social media and aware of their motivations
for using social media, the inclusion criterion was that they must be regular users of social
media (e.g. Facebook, Instagram, Twitter, or Snapchat), and logged into any platform at least
five times a week. Effectivescreening can provide readers with the assurance thatthe sample is
representative of the population of interest and possesses sufficient experience related to the
study topic, enhancing data quality (Crump et al.,2013). The demographic characteristics did
not have a statistically significant impact on any dependent variable (p> 0.05). The largest
group of participants’(40.1%) daily time spent on social media was 1–2 h. Facebook was the
most popular social media platform (36.2%), followed by Instagram (20.2%). There were no
pronounced differences in social media use by demographic characteristics (p> 0.05).
3.2 Procedures
Participants were directed from the MTurk website to a survey instrument on Qualtrics. The
study included two unpaid screening questions at the beginning of the instrument and used
Qualtrics branch logic to terminate participation for those not answering in a specified manner.
First, participants had to have an active account on any social media platform. Second, they had
to log into it at least five times a week to increase the likelihood of having sufficient experience.
Participants who passed the screening questions were qualified to take the survey. Then, the
participants were asked to indicate the extent to which they experienced the COVID-19-related
stress. Subsequently, they responded to questions regarding the coping strategies they employed
during the pandemic, time spent on SNS, motivations for SNS use, and stress reduction
perception, followed by demographic questions. The online survey lasted approximately 15 min.
3.3 Measures
3.3.1 Stress. To assess the participants’COVID-19-related stress levels, a four-item stress
scale was used (Durante and Laran, 2016). Example items were: “I find it difficult to relax,”
and “I find myself getting agitated”(M54.96, SD 51.21).
Individuals
coping COVID-
19-related
stress
Total sample size: 496 Frequency Percentage
Gender
Male 302 60.9
Female 191 38.5
Prefer not to respond 3 0.6
Age
21–34 220 44.4
35–54 216 43.6
55 and over 60 12
Ethnicity
White/Caucasian 388 78.2
African American 57 11.5
Hispanic or Mexican 13 2.6
Asian 29 5.8
American Indian 6 1.2
Other (Biracial) 3 0.6
Education
High school or GED 47 9.5
2 year college 37 7.5
4 year college 291 58.7
Master’s degree 112 22.6
Professional degree (JD, MD) 3 0.6
Doctoral degree 3 0.6
Prefer not to respond 3 0.6
Income
$19,999 or less 44 8.9
$20,000 to $59,999 229 46.2%
$60,000 to $99,999 155 31.2%
$100,000 to $139,000 39 7.9%
$140,000 to $179,999 19 3.8%
$180,000 or more 7 1.4
Prefer not to respond 3 0.6
Social media use time
30–60 min 81 16.3
1–2 h 199 40.1
2–3 h 133 26.8
3–4 h 53 10.7
4–5 h 19 3.8
More than 5 h 11 2.2
Social media Platform
Facebook 180 36.2
Instagram 100 20.2
Twitter 71 14.3
YouTube 57 11.5
WhatsApp 43 8.7
Reddit 18 3.6
Tumblr 6 1.2
TikTok 6 1.2
Snapchat 5 1.0
Pinterest 3 0.6
WeChat 1 0.2
Other (Parler) 6 1.2
Devices use for social media (duplicate response)
Laptop 313 63.1
Smartphone 256 51.6
Desktop 168 33.9
Tablet 61 12.3
Smart TV 24 4.8
Table 2.
Participants’
demographic
characteristics and
social media use
INTR
3.3.2 Coping strategies. To measure coping strategies, Duhachek’s (2005)
multidimensional coping scale was adopted. The original measurement scale has three
sub-coping strategies: active coping, expressive support coping, and avoidance coping.
A confirmatory factor analysis grouped expressive support items into two dimensions with
an eigenvalue greater than 1, explaining 61.40% (labeled expressive support) and 61.06%
(labeled emotional venting) respectively. Thus, this study used four sub-coping strategies:
active coping, expressive support coping, emotional venting coping, and avoidance coping.
Active coping was measured with a six-item scale. Example items were “I concentrate on
ways to solve the problem”and “I think about the best way to handle things”(M55.44,
SD 50.85). Expressive support coping was measured with a seven-item scale. Example items
were “I seek out others for comfort,”“I share my feelings with others I trust and respect,”and
“I try to get advice from someone about what to do”(M54.98, SD 51.14). Emotional venting
was measured with a five-item scale. Example items were “I express my emotions somehow”
and “I take time to express emotions”(M55.18, SD 51.02). To measure avoidance coping, a
four-item scale was used. Example items were “I try to take my mind off of it by doing other
things”and “I distract myself to avoid thinking about it”(M55.15, SD 51.04).
3.3.3 Motivation to use social media. Information-seeking motivation was assessed by a
four-item scale (Bae, 2018). Example items were “I use social media to learn about COVID-19
unknown to me”and “I use social media to get new ideas about COVID-19”(M55.16,
SD 51.15). Social interaction motivation was measured by a five-item scale adopted from
previous studies (Bae, 2018;Leung, 2007). Example items were “I use social media because it
is effective in exchanging ideas with other people”and “I use social media to talk out my
problems and get advice”(M53.20, SD 51.38). Entertainment motivation was measured by
a four-item scale (Smock et al., 2011). Example items were “I use SNSs because it is enjoyable”
and “I use social media because it relaxes me”(M53.02, SD 51.45). Escapism motivation
was measured by a four-item scale developed by (Gao et al., 2017), such as “I use social media
to escapee from problems and pressure”and “I use social media to escape from things that are
unpleasant and worrisome”(M53.12, SD 51.32).
3.3.4 Social media use. Social media use was assessed by asking participants “How much
time do you spend on social networking sites, like Facebook, Twitter, Instagram, on a typical
day?”They were asked to exclude the time spent on social media for work. Response
categories range from 1 (less than 30 min) to 9 (more than 7 h).
3.3.5 Stress reduction perception. To assess the extent to which participants agreed that
using social media helps them cope with stress, a two-item scale was adopted from Leung
(2015), comprising “Being able to use social media helps me turn off the emotional stress I
experience during the COVID-19 pandemic”and “Use of social media helps me reduce my
overall stress levels”(M55.06, SD 51.24). All items were measured on a seven-point Likert
scale ranging from strongly disagree (1) to strongly agree (7).
4. Data analysis
4.1 Measurement model
A two-step approach suggested by Anderson and Gerbing (1988) was adopted. First, the
measurement model was assessed with confirmatory factor analysis (CFA) using AMOS. The
adequacy of the measurement model was evaluated based on the model fit criteria. To ensure a
sufficiently good model fit, the normed chi-square (
χ
2/df), goodness-of-fit-index (GFI),
comparative fit index (CFI), normed fit index (NFI), Tucker–Lewis index (TLI), and root
mean square error of approximation (RMSEA) were used. For the CFA model,
χ
2/df was low
(1232.59/848 51.45), suggesting a 3.0 value (Kline, 2010). GFI, CFI, NFI, and TLI were 0.902,
0.971, 0.913, and 0.966, respectively, exceedingthe standard 0.90 model fit (Kline, 2010).RMSEA
was 0. 030, or less than the standard of 0.05, showing a good fit (Browne and Cudeck, 1992).
Individuals
coping COVID-
19-related
stress
All factor loadings were significant (p< 0.001) and the standardized factor loadings for all
items exceeded the minimum level of 0.50 suggested by Bagozzi and Yi (1988) (see Table 3).
Construct reliability (CR) and average variance extracted (AVE) of each construct exceeded
the minimum criteria of 0.70 and 0.50, respectively (Fornell and Larcker, 1981).
Construct and measurement items Loading tAVE CR
Stress 0.53 0.82
I find it difficult to relax due to coronavirus 0.78
I find myself getting agitated by coronavirus 0.71 14.95
I find it hard to wind down due to coronavirus 0.79 16.43
I am in a state of nervous tension due to coronavirus 0.61 12.92
Coping strategies
Active coping 0.50 0.86
Concentrate on ways of solving the problem 0.73
Try to make a plan of action 0.69 12.96
Generate potential solutions 0.68 12.80
Think about the best ways of handling things 0.71 13.37
Concentrate my efforts on doing something about it 0.74 13.71
Do what has to be done 0.70 13.01
Expressive support 0.55 0.90
Seek out others for support 0.77
Tell others how I feel 0.73 16.94
Rely on others to make me feel better 0.71 16.37
Share my feelings with others I trust and respect 0.69 15.91
Ask friends with similar experiences what they did 0.80 18.86
Try to get advice from someone about what to do 0.75 17.39
Have a friend assist me in fixing the problem 0.74 17.03
Emotional venting 0.51 0.84
Take time to express my emotions 0.80
Express my emotions somehow 0.74 17.51
Delve into my feelings to understand them 0.72 16.89
Take time to figure out what I am feeling 0.71 16.59
Would acknowledge my emotions 0.60 13.65
Avoidance 0.51 0.81
Try to take my mind off it by doing other things 0.74
Distract myself to avoid thinking about it 0.70 13.30
Avoid thinking about it 0.71 13.32
Find satisfaction in other things 0.70 13.29
Motivations
Information 0.59 0.85
To know unknown facts about COVID-19 0.74
To know useful things about COVID-19 0.75 15.90
To get new ideas about COVID-19 0.78 16.51
To research on COVID-19 0.81 16.98
Social interaction 0.74 0.93
To let others know I care about their feelings 0.81
To help others 0.87 22.99
To show my concern about other people 0.87 23.11
To talk about my problems and get advice 0.86 22.89
Because it is effective in exchanging ideas with other people 0.88 23.63
(continued )
Table 3.
Measurement scales
item loading, CR,
and AVE
INTR
4.2 Testing the hypotheses
The hypothetical model assumes that stressed individuals would employ a coping strategy,
which would further facilitate their motivations to use social media, and would predict the
actual social media use, resulting in a stress reduction perception. The model fit values were:
χ
2ð52:07Þ/df (8) 56.51, GFI 50.982, CFI 50.983, NFI 50.980, TLI 50.904, RMSEA 50.072.
According to the standard for the
χ
2value, the GFI, CFI and RMSEA index, the fit results are
acceptable (Kline, 2010).
The evaluation of the standardized coefficients shows that stress significantly predicts
each coping strategy (β
active coping
50.25, t55.69, p< 0.001; β
expressive support coping
50.33,
t57.77, p< 0.001; β
emotional venting coping
50.34, t58.08, p< 0.001; β
avoidance coping
50.41,
t59.87, p< 0.001, see Figure 2). As predicted, active coping is significantly associated with
information-seeking needs (β50.32, t57.50, p< 0.001) and social interaction (β50.14,
Construct and measurement items Loading tAVE CR
Entertainment 0.64 0.88
Because it is enjoyable 0.79
Because it relaxes me 0.82 19.61
To have a pleasant rest 0.81 19.45
To have a good time 0.80 19.17
Escapism 0.63 0.87
SNS help me escape from the world of reality 0.76
SNS help me escape from problems and pressure 0.81 18.60
SNS help me escape from things that are unpleasant and worrisome 0.78 17.78
SNS help me feel as if I am in a different world of reality 0.81 18.60
Perceived stress reduction 0.64 0.78
Being able to use social media helps me turn off the emotional stress I
experience during the pandemic of COVID-19
0.85
Use of social media helps me reduce my overall stress level 0.74 15.70 Table 3.
Coping strategy Motivation
Stress
Avoidance
R2= 0.16
Emotional
Venting
R2= 0.12
Expressive
Support
R2= 0.11
Active
R2= 0.06
Entertainment
R2= 0.17
Information
R2= 0.10
SM Use
R2= 0.42
Stress
Reduction
R2= 0.16
Escapism
R2= 0.25
Social
Interaction
R2= 0.37
0.25***
0.33
***
0.34
***
0.41
***
0.32
***
0.14**
0.14
**
0.49***
0.54
***
0.13**
0.26***.
0.25***
0.45***
0.27***
0.24
***
0.39***
0.1
0.24***
0.09*
Note(s): SM = social media, GFI = goodness-of-fit-index, CFI = comparative fit index,
NFI = normed fit index, TLI = Tucker-Lewis index, RMSEA = root mean square error
of approximation
p* < 0.05, p** < 0.01, p*** < 0.001
Figure 2.
Relationships between
coping strategies,
motivations, social
media use, and
perceived stress
reduction
Individuals
coping COVID-
19-related
stress
t53.52, p< 0.01), thus, supporting H1a and H1b. As stressed people employ expressive
support coping, they are more likely to seek social interaction (β50.54, t514.60, p< 0.001),
supporting H2. Emotional venting significantly elicits social interaction motivation (β50.13,
t53.40, p< 0.01), relaxing entertainment seeking (β50.26, t56.30, p< 0.001), and escapism
(β50.25, t56.15, p< 0.001). Avoidance coping significantly predicts social interaction
motivation (β50.09, t52.50, p< 0.05), entertainment motivation (β50.24, t55.69,
p< 0.001), and escapism (β50.45, t511.12, p< 0.001). Thus, H3a-c, and H4a-c are supported.
Information-seeking motivation significantly predicts social media use (β50.14, t53.62,
p< 0.01). Furthermore, as H5 predicted, social media use is significantly influenced by social
interaction motivation (β50.49, t512.78, p< 0.001), entertainment motivation (β50.27,
t56.45, p< 0.001), and escapism (β50.24, t55.16, p< 0.001), and it significantly predicts
stress reduction perception (β50.39, t59.31, p< 0.001). Thus, H6 is supported as well.
To assess whether mediation (H7) was present in the proposed model, the significance of
the indirect effects was tested using the bias-corrected bootstrap based on 2000 samples at
the 95% confidence interval (CI). The bias-corrected approach is considered the best way to
test indirect paths in mediation analysis (Mackinnon et al., 2004), and it requires a smaller
sample than many of the other tests (Fritz and Mackinnon, 2007). The Plugins package in
AMOS was run to test indirect effects, including serial mediation (Gaskin et al., 2020).
As Table 4 presents, all indirect pathways were significant for each sample (i.e. none of the
estimated 95% CIs contained the value of zero), indicating that coping strategies and motivations
had significant indirect effects on perceived stress reduction via social media use, supporting H7.
Thus, activities on social media can play multiple roles in the reduction of COVID-19-related
stress.
5. Discussion
5.1 Active coping and information and social interaction seeking motivations for using
social media
As hypothesis 1 predicted, the active coping initiated by individuals under COVID-19-related
stress was significantly related with information- and social interaction-seeking motivations,
Path β95% CI
stress →active →information →SM use 0.120 0.002, 0.024
*
stress →active →information →SM use →PSR 0.015 0.011, 0.060
**
stress →active →social interaction →SM use 0.006 0.002, 0.014
**
stress →active →social interaction →SM use →PSR 0.003 0.001, 0.006
*
stress →expressive support →social interaction →SM use 0.056 0.022, 0.068
***
stress →expressive support →social interaction →SM use →PSR 0.043 0.016, 0.056
***
stress →emotional venting →entertainment →SM use 0.015 0.005, 0.035
*
stress →emotional venting →entertainment →SM use →PSR 0.007 0.002, 0.016
*
stress →emotional venting →social interaction →SM use 0.012 0.005, 0.026
**
stress →emotional venting →social interaction →SM use →PSR 0.006 0.002, 0.012
**
stress →emotional venting →escapism →SM use 0.022 0.009, 0.040
***
stress →emotional venting →escapism →SM use →PSR 0.010 0.004, 0.020
***
stress →avoidance →escapism →SM use 0.039 0.019, 0.062
**
stress →avoidance →escapism →SM use →PSR 0.017 0.008, 0.030
***
stress →avoidance →social interaction →SM use 0.011 0.004, 0.024
**
stress →avoidance →social interaction →SM use →PSR 0.005 0.002, 0.012
**
stress →avoidance →entertainment →SM use 0.022 0.012, 0.041
***
stress →avoidance →entertainment →SM use →PSR 0.010 0.005, 0.019
***
Note(s): SM 5social media, PSR 5perceived stress reduction and CI 5confidence interval
p
***
< 0.001, p
**
< 0.01, p
*
< 0.05
Table 4.
Standardized path-
specific indirect effects
of stress on perceived
stress reduction
through coping
strategies, motivations,
and social media use
INTR
which led them to perceive the use of social media as reducing their stress. When stressed
individuals employ an active coping strategy, they are more likely to engage in social
interaction and information seeking that can provide them with a solution (Folkman, 2011;
Leung, 2015). This finding is in light with media-focused coping (e.g. Knobloch-Westerwick
et al., 2009;Vitak and Ellison, 2013) suggesting that stressed individuals elect to spend more
time with information relevant to successfully navigating areas where they were
experiencing stress. In addition, they may actively reach out to the entire network and
consequently maximize the chances of receiving useful information and advice (Vitak and
Ellison, 2013). The constructive effort to gain access to a variety of different experiences of the
COVID-19 pandemic may foster a sense of control over one’s stressful situation (Wright and
Bell, 2003). This finding indicates that social media can represent an important source of
health-related information on COVID-19 and on protective behavior, allowing stressed
individuals to enhance collaborative problem-solving and to make sense of the situation,
coping with it through social interaction (Jurgens and Helsloot, 2018).
5.2 Expressive support coping and social interaction motivations for using social media
As H2 predicted, the expressive support coping strategy motivated individuals under stress
to seek meeting their social needs, such as looking for pandemic-related advice, and led them
to perceive that activities on social media can reduce their stress during this period. As Van
Ingen and Wright (2016) addressed, SNS provide stressed individuals with opportunities to
communicate with others easily and comfortably. During the pandemic, crucial coping
resources, such as the availability of social support, would be largely impaired, and stressed
individuals may be dependent relatively more on social media to deal with the psychological
consequences of negative life events. They can easily consult others with similar issues online
(Hofer and Eden, 2020). This is valuable because such people are often capable of showing
empathic understanding, giving appropriate advice (Wright and Bell, 2003), and thus, satisfy
the stressed individuals’intrinsic needs for relatedness, competence, and autonomy (Ryan
and Deci, 2000). This finding corresponds with online community literature that suggests
that the shared experiences of a group enable meaningful exchanges, such as venting about
shared stresses that other close friends might not understand (Wu and Bernardi, 2021).
Members of an online support group are likely to understand where these stresses are coming
from and recognize the importance of expressing the negative feelings (Van Ingen et al., 2016).
This is also consistent with previous findings that social interaction and social support are
potent factors that can reduce exposure to stress, and promote health, contributing to a higher
quality of life (Leung, 2007,2015;Wright, 2000).
5.3 Emotional venting coping and social interaction, entertainment, and escapism
motivations for using social media
The study results supported H3, where the emotional venting strategy was significantly
associated with entertainment, social interaction, and escapism seeking motivations that allowed
people to regulate their negative and distressing feelings. These findings are consistent with
previous studies, which found that stressed individuals turn to social media to relieve their
depressive feelings by connecting with others online (Coyne et al.,2020), and expressing one’strue
(fearful) self on social media (Grieve and Watkinson, 2016). This is also in line with the mood
management theory, which states that social media can alleviate negative feelings caused by
stress by displacing anxious thoughts and substituting negative effects with positive effects, as a
result of emotional venting activities online (George et al.,2013;Rui and Stefanone, 2013). Stressed
individuals initiate emotional venting coping by being engaged in several activities to alleviate
their negative feelings, such as updating their status primarily for the sake of disclosing
emotional information to others (Hampton et al.,2011), or engaging in relationship maintenance
activities on social media (Wendorf and Yang, 2015).
Individuals
coping COVID-
19-related
stress
Escapist theories of media use underscored that stressed individuals typically attempt to
emotionally escape their current stress levels via hedonically pleasant media choices
(Moskalenko and Heine, 2003), and this escapist coping via media is associated with a
negative effect (Eden et al., 2020). According to this perspective, when stressed individuals
turn to the media for escape, to avoid unpleasant associations with the source of their stress, it
may be a maladaptive coping technique for overall psychological well-being (Meier et al.,
2018;Young et al., 2017). This negative view is also typified as many studies have identified
escapism as a key predictor of media addiction (Kircaburun and Griffiths, 2019;Masur et al.,
2014). Contrary to the negative association with escapism, the present study’s findings
suggest that when stressed individuals attempt to cope with the stressors by employing
emotional venting strategy, they may expose themselves to entertainment media to distance
themselves from a stressor and thereby reduce negative affective states associated with the
stressors. Therefore, the escapist media use does not necessarily have a dysfunctional nature.
Meier et al. (2018) also pointed out that the escapist media use results from purposeful media
selection through which stressed individuals intend to forget about stressors and to obtain
substitute gratifications. Accordingly, escapism can be conceptualized as a functional
motivation, with beneficial effects on the well-being of the stressed; Halfmann and Reinecke
(2021) recently proposed the extension of their conceptualizations.
5.4 Avoidance coping and escapism, social interaction and entertainment motivations for
using social media
Supporting H4, the avoidance coping strategy significantly impacted escape seeking, which
entailed getting absorbed in social media activities, thereby allowing people to avoid
unpleasant thoughts related to the pandemic. This finding appears to sit well with a key tenet
of the compensatory Internet use theory (Kardefelt-Winther, 2014), which states that stress
may trigger individuals to use social media to escape negative feelings in the real world
(Kwon et al., 2013;Masur et al., 2014). When confronted with COVID-19-related stress,
individuals are likely to engage in activities on social media, disclosing personal feelings to
relieve negative emotions (Eden et al., 2020;Hofer and Eden, 2020). Reduced interaction with
others or loneliness caused by being stuck at home may trigger individuals to use social
media for social interaction, entertainment, and an escape from the psychological experience
of distress, leading to an increased stress reduction perception.
5.5 Social media use and stress reduction
Among the relevant disadvantages of communications on SNS, limited emotional and social
cues, inability to communicate material support, and physical absence are noteworthy
(Colvin et al., 2004). Studies suggest that online support seekers or escapists were at an
increased risk of addiction, depression, anxiety, and isolation, compared to the privileged
face-to-face networks of support (Gao et al., 2017;Hong and Chiu, 2016;Masur et al., 2014;
Primack et al., 2017). However, this study found that individuals coping with COVID-19-
related stress had great opportunities of increased sources of emotional and social support,
coming perhaps from people with greater diversity in life experience and knowledge than
what is available offline; this was suggested by Wright and Miller (2010) and Van Ingen and
Wright (2016). Similarly, others suffering because of the pandemic may show empathic
understanding, giving appropriate information and advice (Thoits, 2011;Van Ingen
et al., 2016).
Importantly, as discussed above, from the media addiction or problematic media use
perspective, the media-focused coping was typically evaluated as a dysfunctional or
maladaptive coping strategy (Eden et al., 2020;Kuss et al., 2017;Wolfers and Schneider, 2021).
However, the media-focused coping research has demonstrated that whereas approach- or
INTR
problem-focused coping (e.g. active coping and expressive support coping) is more effective
when individuals have control over the stressor, avoidance or emotional-focused coping
(e.g. emotional venting coping) is more effective when the situation is uncontrollable (Lazarus
and Folkman, 1984). However, the effects of media-focused coping should be understood by
exploring the coping process associated with motivations that predict social media use,
causing stress reduction.
So far, such coping processes have not been empirically explored either in studies on the
effects of coping strategies or in the research on social media effectiveness. To explain and
discover functional versus dysfunctional effects of media-focused coping in the uncontrollable
pandemic situation, this study further examined the psychological mechanism underlying how
decisionsaround the type of coping strategies used are related to motivations of media usage, in
turn leading to stress reduction in accordance withH5,H6,andH7. The findingsshowed that all
the paths were statistically significant (i.e. stress →active coping information
motivation →social media use →perceived stress reduction; stress →active
coping →social interaction →social media use →perceived stress reduction;
stress →expressive support coping →social interaction →social media use →perceived
stress reduction; stress →emotional venting →entertainment seeking →social media
use →perceived stress reduction; stress →emotional venting →social interaction →social
media use →perceived stress reduction; stress →emotional venting →escapism →social
media use →perceived stress reduction; stress →avoidance coping →escapism →
social media use →perceived stress reduction; stress →avoidance coping →social
interaction →social media use →perceived stress reduction; stress →avoidance
coping →entertainment seeking →social media use →perceived stress reduction). This
indicated that coping strategies and motivations had significant indirect effects on perceived
stress reduction via socialmedia use. In other words, both approach- or problem-focused coping
(e.g. active coping and expressive support coping) and avoidance or emotional-focused coping
(e.g. emotional venting coping) were functional rather than dysfunctional when they were well
adapted to social media usage. This finding is contrary to the basic assumption of the majority
of previous emotion-focused or avoidance coping studies that argued that the escapist media
use to avoid unpleasant thoughts associated with the source of the stress may be a maladaptive
coping technique for overallpsychological well-being outcomes(e.g. Young et al.,2017). It is also
likely that escapist entertainment use interacts advantageously with other strategies of coping
with stress, such as venting one’s emotions in an online group community. The media-focused
coping strategies would help individuals in reducing stress and gaining control over their
emotional states (Halfmann and Reinecke, 2021).
On social media, individuals may feel that they have a safe space to find useful
information to cope with the pandemic, interact, be entertained, distract themselves, and find
inspiration without any risk of contagion. Notably, SNS can play multiple roles in the
reduction of COVID-19-related stress.
6. Implications
6.1 Theoretical implications
The findings provide several theoretical implications. First, this study extends previous
literature by directing academic attention toward coping strategies, social media use
motivation, and stress reduction perception as a result of social media use. It further
strengthens the uses and gratifications theory and self-determination theory by providing
robust evidence of how motivations to use social media, associated with the coping strategies,
influence users’response to social media. This finding sheds light on the active and purposive
roles of media users in their media selection process, engaging in certain media types to fulfill
certain needs, and cope with stressful life events.
Individuals
coping COVID-
19-related
stress
Second, the study found that mood maintenance theory can be applicable in
understanding how stressed individuals regulate their unpleasant feelings by utilizing
various activities on SNS. The use of social media benefits psychological well-being by
regulating the users’distress from COVID-19-related stressful experiences.
Third, the matching effect between coping strategies and media use motivations on stress
reduction has important implications. Achieving psychological well-being is considered
critical for gaining repeated SNS use and loyalty. Problem-focused active coping is often
considered the most effective strategy to deal with stress (Lazarus and Folkman, 1984;
Sonnentag and Frese, 2003). However, this study found a significant effect of emotion-
oriented coping strategies (i.e. expressive social support and emotional venting coping) on
stress reduction through the social interaction- and entertainment-seeking activities on social
media. This is remarkable in light of social media’s potential positive role for online support
seekers or escapists to cope, by establishing social connection with others, which has also
been blamed for creating an increased risk for potential psychological problems.
Furthermore, this study found beneficial effects of avoidance coping on the well-being of
social media users. If one chooses to avoid a problem, one will likely engage in tactics to
escape, such as visiting online communities, sharing negative life events anonymously, and
finding emotional relief in one another’s stories about coping with the pandemic (Wu and
Bernardi, 2021). By extending the mood management theory, this study relabels avoidance
coping using media with functional coping strategy.
The transactional theory of stress has been a suitable starting point to study media use for
coping as it provides a framework for dynamic processes (Biggs et al., 2017). From this
perspective, how media use can be positioned within the coping process remains unclear. By
providing empirical evidence, this study extends the transactional theory of coping.
6.2 Practical implications
There are several practical implications. Findings showed social interaction associated with
expressive support coping strategy has proven the most powerful tool to reduce stress
perception during the pandemic. Individuals turn to social media to encourage others and
receive encouragement and care about other’s feelings, using an active coping strategy. Social
media and health care are a powerful combination. Healthcare professionals on social media
can provide trustworthy information on immunization, therapy, vaccine, and so on to help
individuals in actively dealing with the pandemic and related issues, leading to their physical
and psychological well-being. Social interactions can be beneficial for people under stress,
enabling them to relieve negative emotions and receive emotional support in online
communities. As there may be privacy concerns when discussing health-related issues or
negative life events online, communities such as Facebook secret groups can be beneficial.
Moreover, individuals intentionally consume social media entertainment to manage the
negative effects of COVID-19-related stress by disrupting the cognitive preoccupation with
affective experience (Leung, 2007). Tailored services such as Netflix,Prime Video, and other
platforms can produce better algorithms for improved content suggestions to help such
individuals replenish their positivity and actively deal with the pandemic. As social media
provides emotional and hedonic benefits during the pandemic, social media managers can
reap benefits by providing a value-added service platform and a community along with
entertaining and informational contents.
7. Limitations and directions for future research
Although this study attempted to unveil important links between coping strategies for
COVID-19-related stress, motivations, social media use, and perceptions of stress reduction,
INTR
it has merely touched the surface of the psychological mechanism underlying the relationship
between coping strategies and motivations of individuals under COVID-19-related stress.
Future studies should explore the specific type of stressors elicited by the pandemic and its
influences on the type of coping strategy employed.
Second, this study took a standardized approach in asking participants about their coping
strategies and motivations, limiting the unraveling of unique coping strategies and
motivations employed by each participant to cope with stress. In future, more heterogeneous
coping strategies can be added. Social media can be used for social support and for career
networking and job search during the pandemic. For a more comprehensive understanding of
motivation for social media use initiated by various coping strategies, further research should
be conducted to examine users’primary purpose of social networking.
Third, this study examines social media as a homogeneous channel offering numerous
opportunities distinguishable from those offered by other Internet services. Future studies
should take cross-platform differences into consideration while examining these motivations.
Finally, despite a number of benefits offered, the inherent differences observed between an
MTurk sample and a sample collected using traditional methods might present significant
challenges in generalizing the results. Future studies should employ a more generalizable
sample.
Despite these limitations, this study analyzed the mediating effects of several types of
coping strategies and social media use motivations that would alleviate distress. Given the
pandemic’s dramatic impact on social media usage, understanding how a stress-induced
coping strategy influences social media users’specific motivations and reduce their distress
will help communicators understand how they can encourage individuals to better cope with
stress by presenting them with more effective social media features, resulting in their stress
reduction and improved well-being.
References
Agichtein, E., Castillo, C., Donato, D., Gionis, A. and Mishne, G. (2008), “Finding high-quality content
in social media”,paper presented at the International Conference on Web Search and Data
Mining (WSDM’08), February 11-12, Paolo Alto, California, doi: 10.1145/1341531.1341557
(accessed 10 March 2020).
Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and
recommended two-step approach”,Psychological Bulletin, Vol. 103 No. 3, pp. 411-423.
Anderson, D.R., Collins, P.A., Schmitt, K.L. and Jacobvitz, R.S. (1996), “Stressful life events and
television viewing”,Communication Research, Vol. 23 No. 3, pp. 243-260.
Aust, F., Diedenhofen, B., Ullrich, S. and Musch, J. (2013), “Seriousness checks are useful to improve
data validity in online research”,Behavior Research Methods, Vol. 45, pp. 527-535.
Bae, M. (2018), “Understanding the effect of the discrepancy between sought and obtained
gratification on social networking site users’satisfaction and continuance intention”,Computers
in Human Behavior, Vol. 79, pp. 139-153.
Bagozzi, R.P. and Yi, Y. (1988), “On the evaluation of structural equation models”,Journal of the
Academy of Marketing Science, Vol. 16, pp. 74-94.
Baker, J.P. and Berenbaum, H. (2007), “Emotional approach and problem-focused coping: a comparison
of potentially adaptive strategies”,Cognition and Emotion, Vol. 21 No. 1, pp. 95-118.
Baker, L.R. and Oswald, D.L. (2010), “Shyness and online social networking services”,Journal of Social
and Personal Relationships, Vol. 27 No. 7, pp. 873-889.
Banjanin, N., Banjanin, N., Dimitrijevic, I. and Pantic, I. (2015), “Relationship between internet use and
depression: focus on physiological mood oscillations, social networking and online addictive
behavior”,Computers in Human Behavior, Vol. 43, pp. 308-312.
Individuals
coping COVID-
19-related
stress
Barrick, M.R., Steward, G.L. and Piotrowski, M. (2002), “Personality and job performance: test of the
mediating effects of motivation among sales representatives”,Journal of Applied Psychology,
Vol. 87 No. 1, pp. 43-51.
Barry, C.T., Sidoti, C.L., Briggs, S.M., Reiter, S.R. and Lindsey, R.A. (2017), “Adolescent social media
use and mental health from adolescent and parent perspectives”,Journal of Adolescence,
Vol. 61, pp. 1-11.
Berryman, C., Ferguson, C.J. and Negy, C. (2018), “Social media use and mental health among young
adults”,Psychiatric Quarterly, Vol. 89, pp. 307-314.
Biggs, A., Brough, P. and Drummond, S. (2017), “Lazarus and Folkman’s psychological stress and
coping theory”, in Cooper, C.L. and Quick, J.C. (Eds), The Handbook of Stress and Health: A
Guide to Research and Practice, Wiley-Blackwell, London, UK, pp. 351-364.
Brand, M., Laier, C. and Young, K.S. (2014), “Internet addiction: coping styles, expectancies, and
treatment implications”,Frontiers in Psychology, Vol. 5, pp. 1-14.
Browne, M.W. and Cudeck, R. (1992), “Alternative ways of assessing model fit”,Sociological Methods
and Research, Vol. 21 No. 2, pp. 230-257.
Carver, C.S. and Connor-Smith, J. (2010), “Personality and coping”,Annual Review of Psychology,
Vol. 61, pp. 679-704.
Carver, C.S. (2011), “Coping”, in Contrada, R.J. and Baum, A. (Eds), The Handbook of Stress
Science: Biology, Psychology, and Health, Springer Publishing Company, New York, NY,
pp. 221-229.
Chandler, J.J. and Paolacci, G. (2017), “Lie for a dime: when most prescreening responses are honest
but most study participants are impostors”,Social Psychological and Personality Science, Vol. 8
No. 5, pp. 500-508.
Chandler, J.J., Mueller, P. and Paolacci, G. (2014), “Nonnnaivet
e among Amazon Mechanical Turk
workers: consequences and solutions for behavioral researchers”,Behavior Research Methods,
Vol. 46, pp. 112-130.
Cheung, J.H., Burns, D.K., Sinclair, R.R. and Sliter, M. (2017), “Amazon Mechanical Turk in
organizational psychology: an evaluation and practical recommendations”,Journal of Business
and Psychology, Vol. 32, pp. 347-361.
Chiaburu, D.S., Marinova, S.V. and Lim, A.S. (2007), “Helping and proactive extra-role behaviors: the
influence of motives, goal orientation, and social context”,Personality and Individual
Differences, Vol. 43 No. 8, pp. 2282-2293.
Chiu, C.M. and Huang, H.Y. (2015), “Examining the antecedents of user gratification and its effects on
individuals’social network services usage: the moderating role of habit”,European Journal of
Information Systems, Vol. 24, pp. 411-430.
Cohen, E.L. and Lancaster, A.L. (2014), “Individual differences in in-person and social media television
coviewing: the role of emotional contagion, need to belong, and coviewing orientation”,
Cyberpsychology, Behavior, and Social Networking, Vol. 17 No. 8, pp. 512-518.
Colvin, J., Chenoweth, L., Bold, M. and Harding, C. (2004), “Caregivers of older adults: advantages and
disadvantes of internet-based social support”,Family Relations, Vol. 53 No. 1, pp. 49-57.
Coyne, S.M., Rogers, A.A., Zurcher, J.D., Stockdale, L. and Booth, M. (2020), “Does time spent using
social media impact mental health?: An eight-year longitudinal study”,Computers in Human
Behavior, Vol. 104, pp. 106-160.
Crump, M.J.C., McDonnell, J.V. and Gureckis, T.M. (2013), “Evaluating Amazon’s Mechanical Turk as
a tool for experimental behavioral research”,PLos ONE, Vol. 8 No. 3, p. e57410.
Damian, E. and Ingen, E.V. (2014), “Social network site usage and personal relations of migrants”,
Societies, Vol. 4 No. 4, pp. 640-653.
Duhachek, A. (2005), “Coping: a multidimensional, hierarchical framework of responses to stressful
consumption episodes”,Journal of Consumer Research, Vol. 32 No. 1, pp. 41-53.
INTR
Durante, K.M. and Laran, J. (2016), “The effect of stress on consumer saving and spending”,Journal of
Marketing Research, Vol. 53 No. 5, pp. 93-97.
Dwivedi, A. and Lewis, C. (2021), “How millennials’life concerns shape social media behaviour”,
Behaviour and Information Technology, Vol. 40 No. 14, pp. 1467-1484.
Eden, A.L., Johnson, E.K., Reinecke, L. and Grady, S.M. (2020), “Media for coping during COVID-19
social distancing: stress, anxiety, and psychological well-being”,Frontiers in Psychology,
Vol. 11, pp. 1-21.
Ehrich, K.R. and Irwin, J.R. (2005), “Willful ignorance in the request for product attribute information”,
Journal of Marketing Research, Vol. 42 No. 3, pp. 266-277.
Fleischer, A., Mead, A.D. and Huang, J. (2015), “Inattentive responding in MTurk and other online
samples”,Industrial and Organizational Psychology, Vol. 8 No. 2, pp. 196-202.
Folkman, S. (2011), “Stress, health, and coping: synthesis, commentary, and future directions”,in
Folkman, S. (Ed.), The Oxford Handbook of Stress, Health, and Coping, Oxford University Press,
New York, NY, pp. 453-469.
Folkman, S. and Lazarus, R.S. (1985), “If it changes it must be a process: study of emotion and coping
during three stages of a college examination”,Journal of Personality and Social Psychology,
Vol. 48 No. 1, pp. 150-170.
Fornell, C. and Larcker, D.F. (1981), “Structural equation models with unobservable variables and
measurement error: algebra and statistics”,Journal of Marketing Research, Vol. 18 No. 3,
pp. 382-388.
Frison,E.andEggermont,S.(2015),“The impact of daily stress on adolescents’depressed mood: the role
of social support seeking through Facebook”,Computers in Human Behavior, Vol. 44, pp. 315-325.
Fritz, M.S. and Mackinnon, D.P. (2007), “Required sample size to detect the mediated effect”,
Psychological Science, Vol. 18 No. 3, pp. 233-239.
Gao, W., Liu, Z. and Li, K. (2017), “How does social presence influence SNS addiction? A belongingness
theory perspective”,Computers in Human Behavior, Vol. 77, pp. 347-355.
Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., Wang, Y., Fu, H. and Dai, J. (2020), “Mental health
problems and social media exposure during COVID-19 outbreak”,PloS One, Vol. 15 No. 4, p.
e0231924.
Gaskin, J., James, M. and Lim, J. (2020), “Indirect effects: AMOS plugin”, available at: http://statwiki.
gaskination.com/index.php?title5Plugins (accessed 1 April 2020).
George, D.R., Dellasega, C., Whitehead, M.M. and Bordon, A. (2013), “Facebook-based stress
management resources for first-year medical students: a multi-method evaluation”,Computers
in Human Behavior, Vol. 29, pp. 559-562.
Goodman, J.K., Cryder, C.E. and Cheema, A. (2013), “Data collection in a flat world: the strengths and
weaknesses of Mechanical Turk samples”,Behavioral Decision Making, Vol. 26 No. 3,
pp. 213-224.
Granow, V.C., Reinecke, L. and Ziegele, M. (2018), “Binge-watching and psychological well-being:
media use between lack of control and perceived autonomy”,Communication Research Reports,
Vol. 35 No. 5, pp. 392-401.
Grieve, R. and Watkinson, J. (2016), “The psychological benefits of being authentic on Facebook”,
CyberPsychology, Behavior, and Social Networking, Vol. 19 No. 7, pp. 420-425.
Halfmann, A. and Reinecke, L. (2021), “Binge-watching as case of escapist entertainment use”,in
Vorderer, P. and Klimmt, C. (Eds), The Oxford Handbook of Entertainment Theory, Oxford
University Press, New York, NY, pp. 181-203.
Hampton, K.N., Goulet, L.S., Rainie, L. and Purcell, K. (2011), “Social networking sites and our lives”,
available at: http://pewinternet.org/Reports/2011/Technology-and-social-networks.aspx
(accessed 20 February 2020).
Individuals
coping COVID-
19-related
stress
Hauser, D.J. and Schwarz, N. (2016), “Attentive Turkers: MTurk participants perform better on online
attention checks than do subject pool participants”,Behavior Research Methods, Vol. 48,
pp. 400-407.
Hofer, M. and Eden, A. (2020), “Successful aging through television: selective and compensatory
television use and well-being”,Journal of Broadcasting and Electronic Media, Vol. 64 No. 2,
pp. 131-149.
Hoffmann, C.P., Lutz, C., M€
uller, S. and Meckel, M. (2017), “Facebook escapism and online political
participation”,paper presented at the 8th International Conference on Social Media and Society,
28-30 July, Toronto, ON, Canada, doi: 10.1145/3097286.3097327 (accessed 10 February 2020).
Hong, F.Y. and Chiu, S.L. (2016), “Factors influencing Facebook usage and Facebook addictive
tendency in university students: the role of online psychological privacy and Facebook usage
motivation”,Stress and Health, Vol. 32 No. 2, pp. 117-127.
Johnson, B.K., Eden, A., Reinecke, L. and Hartmann, T. (2021), “Self-control and need satisfaction in
primetime: television, social media, and friends can enhance regulatory resources via perceived
autonomy and competence”,Psychology of Popular Media, Vol. 10 No. 2, pp. 212-222.
Joinson, A.N. (2008), “Looking at, looking up or keeping up with people?: Motives and use of
Facebook”,paper presented at the SIGCHI Conference on Human Factors in Computing Systems,
5-10 April, Florence, Italy, doi: 10.1145/1357054.1357213, (accessed 10 February 2020).
Jung, E.H. and Sundar, S.S. (2016), “Senior citizens on Facebook: how do they interact and why?”,
Computers in Human Behavior, Vol. 61, pp. 27-35.
Jurgens, M. and Helsloot, I. (2018), “The effect of social media on the dynamics of (self) resilience
during disasters: a literature review”,Journal of Contingencies and Crisis Management, Vol. 26
No. 1, pp. 79-88.
Kaiser Family Foundation (2021), “The implications of COVID-19 for mental health and substance
use”, available at: https://www.kff.org/coronavirus-covid-19/issue-brief/the-implications-of-
covid-19-for-mental-health-and-substance-use/ (accessed 11 February 2021).
Kardefelt-Winther, D. (2014), “A conceptual and methodological critique of internet addiction research:
towards a model of compensatory internet use”,Computers in Human Behavior, Vol. 31,
pp. 351-354.
Katz, E., Blumler, J.G. and Gurevitch, M. (1973), “Uses and gratifications research”,The Public Opinion
Quarterly, Vol. 37 No. 4, pp. 509-523.
Kim, J.Y., Shim, J.P. and Ahn, K.M. (2011), “Social networking service: motivation, pleasure, and
behavioral intention to use”,Journal of Computer Information Systems, Vol. 51 No. 4, pp. 92-101.
Kircaburun, K. and Griffiths, M.D. (2019), “Problematic Instagram use: the role of perceived feelings of
presence and escapism”,International Journal of Mental Health and Addiction, Vol. 17,
pp. 909-921.
Kline, R.B. (2010), Principles and Practice of Structural Equation Modeling, The Guilford Press, New
York, NY.
Knobloch-Westerwick, S., Hastall, M.R. and Rossmann, M. (2009), “Coping or escaping?: Effects of life
dissatisfaction on selective exposure”,Communication Research, Vol. 36 No. 2, pp. 207-228.
Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D., Lin, N., Shablack, H., Jonides, J. and Ybarra, O.
(2013), “Facebook use predicts declines in subjective well-being in young adults”,PloS One,
Vol. 8, p. e69841.
Krueger, B.S. (2002), “Assessing the potential of internet political participation in the United States:
a resource approach”,American Politics Research, Vol. 30 No. 5, pp. 476-498.
Kuss, D.J., Dunn, T.J., W€
olfling, K., M€
uller, K.W., Hedzelek, M. and Marcinkowski, J. (2017), “Excessive
internet use and psychopathology: the role of coping”,Clinical Neuropsychiatry, Vol. 14 No. 1,
pp. 73-81.
INTR
Kwon, M.W., D’Angelo, J. and McLeod, D.M. (2013), “Facebook use and social capital: to bond, to
bridge, or to escape”,Bulletin of Science, Technology and Society, Vol. 33 Nos 1-2, pp. 35-43.
Labroo, A.A. and Lee, A.Y. (2006), “Between two brands: a goal fluency account of brand evaluation”,
Journal of Marketing Research, Vol. 43 No. 3, pp. 374-385.
Lavine, H. and Snyder, M. (1996), “Cognitive processing and the functional matching effect in
persuasion: the mediating role of subjective perceptions of message quality”,Journal of
Experimental Social Psychology, Vol. 32 No. 6, pp. 580-604.
Lavine, H. and Snyder, M. (2000), “Cognitive processes and the functional matching effect in
persuasion: studies of personality and political behavior”, in Maio, G.R. and Olson, J.M. (Eds),
Why We Evaluate: Functions of Attitudes, Erlbaum, Mahwah, NJ, pp. 97-131.
Lazarus, R.S. and Folkman, S. (1984), Stress, Appraisal, and Coping, Springer, New York, NY.
Lee, C.S. and Ma, L. (2012), “News sharing in social media: the effect of gratifications and prior
experience”,Computers in Human Behavior, Vol. 28, pp. 331-339.
Leung, L. (2007), “Stressful life events, motives for internet use, and social support among digital
kids”,CyberPsychology and Behavior, Vol. 10 No. 2, pp. 204-214.
Leung, L. (2015), “Using tablet in solitude for stress reduction: an examination of desire for aloneness,
leisure boredom, tablet activities, and location of use”,Computers in Human Behavior, Vol. 48,
pp. 382-391.
Levenson, J.C., Shensa, A., Sidani, J.E., Colditz, J.B. and Primack, B.A. (2016), “The association between
social media use and sleep disturbance among young adults”,Preventive Medicine, Vol. 85,
pp. 36-41.
Li, D., Zhang, W., Li, X., Zhou, Y., Zhao, L. and Wang, Y. (2016), “Stressful life events and adolescent
internet addiction: the mediating role of psychological needs satisfaction and the moderating
role of coping style”,Computers in Human Behavior, Vol. 63, pp. 408-415.
Mackinnon, D.P., Lockwood, C.M. and Williams, J. (2004), “Confidence limits for the indirect effect:
distribution of the product and resampling methods”,Multivariate Behavioral Research, Vol. 39
No. 1, pp. 99-128.
Masur, P.K., Reinecke, L., Ziegele, M. and Quiring, O. (2014), “The interplay of intrinsic need
satisfaction and Facebook specific motives in explaining addictive behavior on Facebook”,
Computers in Human Behavior, Vol. 39, pp. 376-386.
Mathur, A., Moschis, G.P. and Lee, E. (2008), “A longitudinal study of the effects of life status changes
on changes in consumer preferences”,Journal of the Academy of Marketing Science, Vol. 36
No. 2, pp. 234-246.
Meier, A., Meltzer, C.E. and Reinecke, L. (2018), “Coping with stress or losing control? Facebook-
induced strains among emerging adults as a consequence of escapism versus procrastination”,
in K€
uhne, R., Baumgartner, S.E., Koch, T. and Hofer, M. (Eds), Youth and Media: Current
Perspectives on Media Use and Effects, Nomos, Baden-Baden, Germany, pp. 167-186.
Morelli, S.A., Ramson, L.T. and Lieberman, M.D. (2014), “The neural components of empathy: predicting
daily prosocial behaivor”,Social Cognitive and Affective Neuroscience,Vol.9No.1,pp.39-47.
Moskalenko, S. and Heine, S.J. (2003), “Watching your troubles away: television viewing as a stimulus for
subjective self-awareness”,Personality and Social Psychology Bulletin, Vol. 29 No. 1, pp. 76-85.
Muntinga, D.G., Moorman, M. and Smit, E.G. (2011), “Introducing COBRAs: exploring motivations for
brand-related social media use”,International Journal of Advertising, Vol. 30 No. 1, pp. 13-46.
Nabi, R.L. and Krcmar, M. (2004), “Conceptualizing media enjoyment as attitude: implications for mass
media effects research”,Communication Theory, Vol. 14 No. 4, pp. 288-310.
Nabi, R.L., Prestin, A. and So, J. (2016), “Could watching TV be good for you? Examining how media
consumption patterns relate to salivary cortisol”,Health Communication, Vol. 31 No. 11, pp.
1345-1355.
Individuals
coping COVID-
19-related
stress
Nabi, R.L., Torres, D.P. and Prestin, A. (2017), “Guilty pleasure no more”,Journal of Media Psychology,
Vol. 29 No. 3, pp. 126-136.
Nielsen (2020), “Staying put: consumers forced indoors during crisis spend more time on media”,
available at: https://www.nielsen.com/us/en/insights/article/2020/staying-put-consumers-forced-
indoors-during-crisis-spend-more-time-on-media/ (accessed 3 August 2020).
Ong, A.D., Bergeman, C.S., Bisconti, T.L. and Wallace, K.A. (2006), “Psychological resilience, positive
emotions, and successful adaptation to stress in later life”,Journal of Personality and Social
Psychology, Vol. 91 No. 4, pp. 730-749.
Palmgreen, P., Rosengren, K. and Wenner, L.A. (1985), “Uses and gratifications research: the past ten
years”, in Rosengren, K., Wenner, L.A. and Palmgreen, P. (Eds), Media Gratifications Research:
Current Perspective, SAGE, Beverly Hills, CA, pp. 11-37.
Papacharissi, Z. and Mendelson, A. (2011), “Toward a new(er) sociability: uses, gratifications, and
social capital on Facebook”, in Papathanassopoulos, S. (Ed.), Media Perspectives for the 21st
Century, Routledge, New York, NY, pp. 225-243.
Park, C.L. and Folkman, S. (1997), “Meaning in the context of stress and coping”,Review of General
Psychology, Vol. 1 No. 2, pp. 115-144.
Poll, H. (2020), “COVID-19 wave 10”, available at: http://theharrispoll.com/wp-content/uploads/2020/
05/Wave-2-10_tabs_Banner-11.pdf (accessed 1 January 2021).
Primack,B.A.,Shensa,A.,Escobar-Viera,C.G.,Barrett,E.L.,Sidani,J.E.,Colditz,J.B.andJames,A.E.(2017),
“Use of multiple social media platforms and symptoms of depression and anxiety: a nationally
representative study among U.S. young adults”,Computers in Human Behavior,Vol.69,pp.1-9.
Ramsey, S.R., Thompson, K.L., Mckenzie, M. and Rosenbaum, A. (2016), “Psychological research in the
internet age: the quality of web-based data”,Computers in Human Behavior, Vol. 58, pp. 354-360.
Reinecke, L. and Trepte, S. (2014), “Authenticity and well-being on social network sites: a two-wave
longitudinal study on the effects of online authenticity and the positivity bias in SNS
communication”,Computers in Human Behavior, Vol. 30, pp. 95-102.
Ruggiero, T.E. (2000), “Uses and gratifications theory in the 21st century”,Mass Communication and
Society, Vol. 3 No. 1, pp. 3-37.
Rui, J. and Stefanone, M.A. (2013), “Strategic self-presentation online: a cross-cultural study”,
Computers in Human Behavior, Vol. 29, pp. 110-118.
Ryan, R.M. and Deci, E.L. (2000), “Intrinsic and extrinsic motivations: classic definitions and new
directions”,Contemporary Educational Psychology, Vol. 25 No. 1, pp. 54-67.
Schneider, L.A., King, D.L. and Delfabbro, P.H. (2018), “Maladaptive coping styles in adolescents with
internet gaming disorder symptoms”,International Journal of Mental Health and Addiction,
Vol. 16 No. 4, pp. 905-916.
Schuur, W.A.V.D., Baumgartner, S.E. and Sumter, S.R. (2019), “Social media use, social media stress,
and sleep: examining cross-sectional and longitudinal relationships in adolescents”,Health
Communication, Vol. 34 No. 5, pp. 552-559.
Scott, H. and Woods, H.C. (2018), “Fear of missing out and sleep: cognitive behavioural factors in
adolescents’nighttime social media use”,Journal of Adolescence, Vol. 68, pp. 61-65.
Seidman, G. (2013), “Self-presentation and belonging on Facebook: how personality influences social
media use and motivations”,Personality and Individual Differences, Vol. 54 No. 3, pp. 402-407.
Shadish, W.R., Hedges, L.V., Horner, R.H. and Odom, S.L. (2015), “The role of between-case effect size
in conducting, interpreting, and summarizing single-case research”, available at: http://ies.ed.
gov/ncser/pubs/2015002/pdf/2015002.pdf (accessed 10 January 2021).
Sheldon, K.M., Abad, N. and Hinsch, C. (2011), “A two-process view of Facebook use and relatedness
need-satisfaction: disconnection drives use, and connection rewards it”,Journal of Personality
and Social Psychology, Vol. 100 No. 4, pp. 766-775.
INTR
Shiau, W.L. and Luo, M.M. (2013), “Continuance intention of blog users: the impact of perceived
enjoyment, habit, user involvement and blogging time”,Behaviour and Information Technology,
Vol. 32 No. 6, pp. 570-583.
Sippel, L.M., Pietrzak, R.H., Charney, D.S., Mayes, L.C. and Southwick, S.M. (2015), “How does social
support enhance resilience in the trauma-exposed individual?”,Ecology and Society, Vol. 20
No. 4, pp. 9-19.
Slater, M.D., Johnson, B.K., Cohen, J. and Comello, M.L.G. (2014), “Temporarily expanding the
boundaries of the self: motivations for entering the story world and implications for narrative
effects”,Journal of Communication, Vol. 64 No. 3, pp. 439-455.
Smock, A.D., Ellison, N.B., Lampe, C. and Wohn, D.Y. (2011), “Facebook as a toolkit: a uses and
gratification approach to unbundling feature use”,Computers in Human Behavior, Vol. 27,
pp. 2322-2329.
Snyder, V. (2020), “What marketers need to know about people’s social media patterns during the
pandemic”, available at: https://www.business.com/articles/social-media-patterns-during-the-
pandemic/ (accessed 3 March 2021).
Sonnentag, S. and Frese, M. (2003), “Stress in organizations”, in Weiner, R.B. (Ed.), Handbook of
Psychology, Wiley, Hoboken, NJ, pp. 453-491.
Stanton, A.L., Danoff-Burg, S., Cameron, C.L., Bishop, M., Collins, C.A., Kirk, S.B. and Sworowski, L.
(2000), “Emotionally expressive coping predicts psychological and physical adjustment to
breast cancer”,Journal of Consulting and Clinical Psychology, Vol. 68 No. 5, pp. 875-882.
Stevens, E.M. and Carpentier, F.R.D. (2017), “Facing our feelings: how natural coping tendencies
explain when hedonic motivation predicts media use”,Communication Research, Vol. 44 No. 1,
pp. 3-28.
Stevens, S., Humphrey, K., Wheatley, T. and Galliher, R.V. (2011), “Links among obsessive-compulsive
personality characteristics and Facebook usage”,Psi Chi Journal of Undergraduate Research,
Vol. 16 No. 3, pp. 106-112.
Sundar, S.S. and Limperos, A.M. (2013), “Uses and Grats 2.0: new gratifications for new media”,
Journal of Broadcasting and Electronic Media, Vol. 57 No. 4, pp. 504-525.
Thayer, R.E., Newman, J.R. and Mcclain, T.M. (1994), “Self-regulation of mood: strategies for changing
a bad mood, raising energy, and reducing tension”,Journal of Personality and Social Psychology,
Vol. 67 No. 5, pp. 910-925.
Thoits, P.A. (2011), “Mechanisms linking social ties and support to physical and mental health”,
Journal of Health and Social Behavior, Vol. 52 No. 2, pp. 145-161.
Twenge, J.M. (2017), iGen: Why Today’s Super-connected Kids are Growing up Less Rebellious, More
Tolerant, Less Happy - and Completely Unprepared for Adulthood, Atria Books, New York, NY.
Van Ingen, E. and Wright, K.B. (2016), “Predictors of mobilizing online coping versus offline coping
resources after negative life events”,Computers in Human Behavior, Vol. 59, pp. 431-439.
Van Ingen, E., Utz, S. and Toepoel, V. (2016), “Online coping after negative life events: measurement,
prevalence, and relation with internet activities and well-being”,Social Science Computer
Review, Vol. 34 No. 5, pp. 511-529.
Vitak, J. and Ellison, N.B. (2013), “There’s a network out there you might as well tap’: exploring the
benefits of and barriers to exchanging informational and support-based resources on
Facebook”,New Media and Society, Vol. 15 No. 2, pp. 243-259.
Wang, Y. and Fesenmaier, D.R. (2003), “Assessing motivation of contribution in online communities:
an empirical investigation of an online travel community”,Electronic Markets, Vol. 13 No. 1,
pp. 33-45.
Watson, B.R. (2018), “A window into shock, pain, and attempted recovery: a decade of blogging as a
coping strategy in New Orleans”,New Media and Society, Vol. 20 No. 3, pp. 1068-1084.
Individuals
coping COVID-
19-related
stress
Wendorf, J.E. and Yang, F. (2015), “Benefits of a negative post: effects of computer-mediated venting
on relationship maintenance”,Computers in Human Behavior, Vol. 52, pp. 271-277.
Whiting, A. and Williams, D. (2013), “Why people use social media: a uses and gratifications
approach”,Qualitative Market Research, Vol. 16 No. 4, pp. 362-369.
Wolfers, L.N. and Schneider, F.M. (2021), “Using media for coping: a scoping review”,Communication
Research, Vol. 48 No. 8, pp. 1210-1234.
Wright, K. (2000), “Computer-mediated social support, older adults, and coping”,Journal of
Communication, Vol. 50 No. 3, pp. 100-118.
Wright, K.B. and Bell, S.B. (2003), “Health-related support groups on the internet: linking empirical
findings to social support and computer-mediated communication theory”,Journal of Health
Psychology, Vol. 8 No. 1, pp. 39-54.
Wright, K.B. and Miller, C.H. (2010), “A measure of weak-tie/strong-tie support network preference”,
Communication Monographs, Vol. 77 No. 4, pp. 500-517.
Wu, P.F. and Bernardi, R. (2021), “Community attachment and emotional well-being: an empirical
study of an online community for people with diabetes”,Information Technology and People,
Vol. 34 No. 7, pp. 1949-1975.
Yoon, C. and Rolland, E. (2015), “Understanding continuance use in social networking services”,
Journal of Computer Information Systems, Vol. 55 No. 2, pp. 1-8.
Young, N.L., Kuss, D.J., Griffiths, M.D. and Howard, C.J. (2017), “Passive Facebook use, Facebook
addiction, and associations with escapism: an experimental vignette study”,Computers in
Human Behavior, Vol. 71, pp. 24-31.
Zillmann, D. (1988), “Mood management through communication choices”,American Behavioral
Scientist, Vol. 31 No. 3, pp. 327-340.
Zillmann, D. (2000), “Mood management in the context of selective exposure theory”,Annals of the
International Communication Association, Vol. 23 No. 1, pp. 103-123.
Further reading
He, H. and Harris, L. (2020), “The impact of Covid-19 pandemic on corporate social responsibility and
marketing philosophy”,Journal of Business Research, Vol. 116, pp. 176-182.
Corresponding author
Mikyeung Bae can be contacted at: clara.bae@okstate.edu
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com
INTR
