The Effects of Pandemic-Related Fear on Social Connectedness Through Social Media Use and Self-Disclosure

Abstract

In light of the prolonged period of social distancing and highly mediated communication patterns during the COVID-19 pandemic, this study sought to understand how pandemic-related fear affects social connectedness. Drawing from the Internet-enhanced self-disclosure and fear-eliciting affiliation hypotheses, survey findings from a stratified sample collected among Hong Kong university students (N = 310) revealed that pandemic-related fear positively influences social connectedness not only through self-disclosure but also through the combination of information seeking and self-disclosure. Social interaction, however, does not mediate the relationship between fear and social connectedness on its own. Overall, we argue that fear motivated people to seek information, self-disclose, and articulate connectedness with society. During this process, social media provided an essential ground and self-disclosure proved a viable tool. This study demonstrated that negative emotions aroused in crisis situations might result in constructive behaviors, which is contingent on how people react to mitigate the negative consequences.

Full text

RUNNING HEAD: EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS
The Effects of Pandemic-related Fear on Social Connectedness
through Social Media Use and Self-disclosure
Biying Wu-Ouyang and Yang Hu
School of Journalism and Communication, The Chinese University of Hong Kong
Author Note
Biying Wu-Ouyang https://orcid.org/0000-0003-4114-6367
Yang Hu https://orcid.org/0000-0003-4533-8382
Acknowledgements:
We would like to claim that in Figure 2 (the published version), there was a typo in notes, we
have revised in this version. We feel sorry for the typo.
This version of the article may not completely replicate the final authoritative version published
in Journal of Media Psychology at 10.1027/1864-1105/a000347. Please go to the original
website for direct citation:
Wu-Ouyang, B.& Hu, Y. (2022). The Effects of Pandemic-related Fear on Social
Connectedness through Social Media Use and Self-disclosure. Journal of Media Psychology.
35(2), 63-74. https://doi.org/10.1027/1864-1105/a000347

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 2
Abstract
In light of the prolonged period of social distancing and highly mediated communication patterns
during the COVID-19 pandemic, this study sought to understand how pandemic-related fear
affects social connectedness. Drawing from the Internet-enhanced self-disclosure and fear-
eliciting affiliation hypotheses, survey findings from a stratified sample collected among Hong
Kong university students (N = 310) revealed that pandemic-related fear positively influences
social connectedness not only through self-disclosure but also through the combination of
information seeking and self-disclosure. Social interaction, however, does not mediate the
relationship between fear and social connectedness on its own. Overall, we argue that fear
motivated people to seek information, self-disclose, and articulate connectedness with society.
During this process, social media provided an essential ground and self-disclosure proved a
viable tool. This study demonstrated that negative emotions aroused in crisis situations might
result in constructive behaviors, which is contingent on how people react to mitigate the negative
consequences.
Keywords: pandemic-related fear, social connectedness, social media, self-disclosure,
COVID-19

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 3
The outbreak of COVID-19 has caused a severe global health crisis. In an effort to slow
down the spread of diseases, there have been a spate of recommendations or requirements for
people to socially distance themselves from others. Since mobility has become ingrained in
people’s everyday life, such isolating experiences have posed considerable challenges. Many
people lack knowledge about how to handle the pandemic situation and are potentially
susceptible to psychological disorders such as depression and fear (Brooks et al., 2020).
Among the various self-relevant negative emotions, fear has been the most salient one
(Lench & Levine, 2005). This study focuses primarily on pandemic-related fear – the fear
evoked by pandemic situations, such as the COVID-19 pandemic. Prior research has shown that
being exposed to a fearful condition may motivate individuals to connect to others (e.g., Dunlop
et al., 2008). However, these studies have mainly highlighted offline influence, with few
investigating the online setting. Additionally, little is known about the explanatory mechanism
underpinning the relationship between pandemic-related fear and social connectedness. These
crucial but inadequately addressed problems highlight the need for an inquiry into whether and
how fear is related to social connectedness in an online environment.
To scrutinize the relationship between fear and social connectedness in the online setting,
we emphasize the critical role of online technologies – social media – and people’s online
behavior in terms of information seeking, social interaction, and self-disclosure. The rationale
rests on the rapid growth and high penetration of social media, especially among young people
(Nic et al., 2020), as well as on the special circumstances that have emerged following the
COVID-19 pandemic. As a result of strict social-distancing measures, offline activities have
sharply decreased. Across the board, people’s communication behaviors have changed
drastically. People have been adapting to the transition to social distancing by connecting to

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 4
others through social media (Nabity-Grover et al., 2020). In light of the situation where a
substantial body of communicative behaviors has become mediated, notably on social media, the
study further asks: Will fear motivate people to seek information and socially interact with others
through social media, have more disclosure behaviors, which in turn promotes their social
connectedness?
Tackling these questions has both theoretical and practical significance. On the
theoretical level, the study aims to account for how fear affects people’s social connection
through a range of online communicative activities from information seeking or social
interaction to self-disclosure, which also fills in the aforementioned gaps in prior research. On
the practical level, we seek to provide insight into how to prevent losing social connections in the
midst of the ongoing worldwide health crisis marked by social distancing.
Research Context
The study was situated in Hong Kong during the city’s third wave of the COVID-19
outbreak. We selected this specific context for three major reasons. First, since early 2020, Hong
Kong has undergone three waves of the COVID-19 outbreak. In particular, the third wave of the
outbreak (from July 2020) caused sustained community transmission. The government
implemented strict social distancing measures such as the social gathering ban of over two
people to pre- vent the spread of the virus. Second, the social media penetration rate in Hong
Kong is considerably high, since around 80% of the Hong Kong population is well connected in
the world of social media (Digital Reportal, 2020). Third, the COVID-19 pandemic has revived
fears of the SARS epidemic among the Hong Kong public (The Guardian, 2020), the traumatic
memory of which instigated a high level of public awareness and risk perception (Lei &
Klopack, 2020). Hong Kong residents began taking social- distancing measures immediately as

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 5
soon as the virus began spreading in Wuhan in January 2020. Moreover, their daily routines
underwent radical changes, and they grew dependent on social media. Therefore, the COVID- 19
outbreak in Hong Kong fits well with the study’s objective of examining the interplay among
pandemic-related fear, social media use, and social connectedness.
Fear and Its Psychosocial Impacts
Among the range of self-relevant negative emotions, fear is the most salient and is
activated when people perceive the consequences of risks as unclear or uncertain (Lench &
Levine, 2005). Early researcher Janis (1967) claimed that too much fear was maladaptive for
people’s social affiliation, but that too little fear meant an insufficient amount of motivation for
social connection. However, Janis’s work did not garner significant empirical support (Goodall
et al., 2012). Kirkpatrick and Shaver (1988) explained the consequences of fear from the stress
and coping perspective. In their view, people tend to affiliate to others to reduce fear when
coping with a stressful event (i.e., a fearful situation).
More recent studies tended to favor the hypothesis of fear-eliciting affiliation (Luminet et
al., 2000). One line of research found that being exposed to an ambient fearful condition imposes
a crucial social influence on an individual’s motivation to seek the company of others (Dunlop et
al., 2008) and their ability to systematically process information (Dillard et al., 2020). These
methods aim to help people deepen their understanding of risks, reduce uncertainty, and learn
how to cope with them. Another line of thought showed that exposure to fear may have negative
cognitive consequences such as intrusive and recurrent thoughts or images toward the emotional
state. Luminet et al. (2000) summarized that these two consequences would result in a similar
interpersonal situation involving the social sharing of emotion. By social sharing of emotion, we
refer to online self-disclosure involving the requirements of an addressee and a shared language

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 6
about emotions. People may not use direct channels to share private emotions with others, but
under specific circumstances, they may disclose to friends through online technologies. Jiang et
al. (2011) found that due to interpersonal attributions, people feel more intimate when the self-
disclosure is received online rather than offline. As such, we may anticipate that the relationships
between fear and social connectedness are in line with the fear-eliciting hypothesis. These
relationships are characterized by the use of social media and self-disclosure. In what follows,
we will first unpack the relationships between pandemic-related fear and two specific dimensions
of social media use – namely, social interaction and information seeking. Then, we explicate
how social media use may impact social connectedness through self-disclosure.
Social Media Use for Social Interaction and Information Seeking
Premised on its rich technological affordances, social media provides users with a
platform to engage in a wide range of interactional and informational tasks. This study focuses
on two specific dimensions of social media use – social interaction and information seeking –
which are the two most prevalent motives of mobile phone use among Hong Kong adults (Chan,
2015).
Social interaction, the most common motivation for using social media, has been
extensively examined in the communication literature (Ling & Lai, 2016). However, a tension
exists between over-encompassing and over-restrictive conceptualizations of social interaction
(Hall, 2020). One stream of research opts for a broad definition of social interaction. For
instance, Johnston and Lane (2021) identified five levels of social interaction ranging from non-
interaction (i.e., single iteration and one-way communication) up to the highest level of
interaction (i.e., deep and focused interaction). Another stream of work (e.g., Hall, 2020) restricts
social interaction to focused interactions with the satisfaction of mutual acknowledgment,

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 7
conversational exchange, and focused attention by all parties involved. In this vein, social
interactions are treated only as relationally consequential practices. Since unfocused interaction
with relatively low iteration (e.g., liking) can also indicate relational development (Ellison et al.,
2020; Johnston & Lane, 2021), this study follows a broad definition of social interaction to
capture the complex and diversified nature of social interaction. Accordingly, we suggest a
flexible definition of social interaction on social media that describes a plurality of
communicative actions that people take for connecting with others through multiple social media
platforms, which appear to have influences on their social relatedness (Rhee et al., 2021).
Information seeking can generally be defined as people’s data collection behavior to
reduce discrepancy (Dillard et al., 2020). It often involves deliberate and purposive actions
oriented toward certain expectations, such as uncertainty reduction, relationship maintenance,
and bridging social capital (Frampton & Fox, 2021). In this sense, information seeking can be
conceptualized as an action of browsing or searching for information and is related not only to
communication frames but also to social and relational components of information management.
Pandemic-related Fear and Social Media Use
Although few empirical studies have directly explored how pandemic-related fear
influences people’s social interaction and information seeking behaviors on social media, the
relationship between fear and social media use has been documented. For example, Ali and her
colleagues (2019) found that fear enables social media engagement such as reaction, comments,
and shares during the Zika outbreak in 2016. Therefore, based on the aforementioned theoretical
discussion of pandemic-related fear and social media use, we argue that fear motivates people to
interact with others and seek information on social media. First, communicating with others
assists in a better understanding of the risk and generates more knowledge of how to handle it

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 8
(Dunlop et al., 2008). Second, fear is often accompanied by uncertainty. In order to reduce
uncertainty, people usually engage in interactive and active ways of interaction and information
seeking from external sources (Schwartz & Grimm, 2016). Notably, in the COVID-19 pandemic
situation, information seeking and social interaction emerged as the major motivation for using
social media (Kaya, 2020). Individuals utilized social media to follow news updates, learn about
different views, and retrieve medical information. Third, social media fosters a secure and
favorable environment in times of social distancing, allowing people to counteract negative
emotions and seek information and peer support (Zhong et al, 2021). As such, the link between
pandemic-related fear and social media use accords with the fear-eliciting affiliation framework
dis- cussed earlier. In brief, fear motivates people to seek con- tact through social media. We
thereby expect:
Hypothesis 1 (H1): Pandemic-related fear will posi- tively predict people’s willingness
to use social media for social interaction (H1a) and information seeking (H1b).
Social Media Use, Self-disclosure, and Social Connectedness
As an integral component of belongingness, social connectedness conveys a sense of
closeness with others, counter- balancing the feelings of loneliness, isolation, and alienation (Lee
& Robbins, 1995). A review study by Brooks et al. (2020) suggested that social connectedness is
positively associated with well-being and survival. Furthermore, researchers have agreed that
high-quality communication constitutes a significant element of social connectedness. More
specifically, having a close communication partner, frequent contact with friends, and self-
disclosure will lead to enhanced connectedness (Valkenburg & Peter, 2009).
With online technologies increasingly penetrating our everyday life, there are mounting
concerns about whether social media use can enhance social connectedness. The extant literature

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 9
generally follows two lines of thought. One strand of research views online technologies as
replacing face-to-face interactions, which negatively affects social connectedness (e.g., Hu,
2009). Without the presence of adequate nonverbal cues, senders may not fully express their
mood, while receivers may not capture the whole meaning, resulting in a lower density of
understanding and less social connectedness (Kraut et al., 1998). Yet another stream of work
views online technologies as a way to augment connectedness. Among these perspectives, the
communication bond belong (CBB) theory (Hall, 2020) emphasizes the management of human
energy and shows how online technologies efficiently enable people to establish and maintain
social relationships, which complements face-to-face communication. In addition, online
technologies allow people to use interactive strategies (e.g., self- disclosure), to reduce
uncertainty, resulting in a greater sense of social connectedness (Chan & Li, 2020).
Of note, additional studies have exhibited a more complicated picture. It has been
suggested that social media can contribute to the maintenance of friendships in both positive and
negative ways, depending on how individuals use it (McEwan, 2013). For example, those who
demonstrate caring and responsiveness to their connections may find that Facebook contributes
to desired friendships, whereas those who frequently share without being responsive to friends
may be adversely impacted by the use of Facebook. Moreover, Pennington (2020) posited that
relationship maintenance through social media is determined by various factors, including tie
strength, network size, and the frequency of use.
With the prevalence of social media, more studies tend to focus on how social media can
help build better relation- ships. Goodman-Deane et al. (2016), for instance, showed that mobile
talk and video calls contribute to relationship satisfaction. An interview-based study noted that
casual exchanges on Facebook can assist adolescents in maintaining a sense of belonging and

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 10
connection with their closest peers (Davis, 2012). Besides, through analyzing actual Face- book
communication traces, another study by Sosik and Bazarova (2014) revealed the mechanism by
which social media can be effective in “signifying co-presence and the existence of ties to
others” (p. 131), thereby supporting relationship maintenance and even further development. In a
nutshell, social media interactions may help people convey certain emotional states such as fear
or affection, reinforce the content of a message, and improve the quality of their relationships
(Kaye et al., 2016). This is consistent with the fear-eliciting affiliation hypothesis that fear-
arousing social contact helps maintain social connectedness. Thus, we hypothesize the following:
Hypothesis 2 (H2): People’s social media use for social interaction is positively
associated with their social connectedness.
Information seeking constitutes the other crucial dimension of social media use. The
relationship between information seeking and social connectedness is also noteworthy. Given the
pandemic context, the study focuses particularly on public information. Public information, or
more specifically news, is well established as an essential component of fostering public
connection. It brings an orientation toward a public world in which shared concerns are
discussed or addressed (Couldry et al., 2007). In other words, news information, as part of the
social fabric of everyday life, performs as a common ground for people to maintain relations
with others and the wider society (Schrøder, 2014). In the process of news-based information
seeking, people are motivated to interact with others to find shared references, engage in society,
and act based on such collective references, in effect enhancing the sense of connectedness.
Information seeking has thus been incorporated into the fear-eliciting affiliation process. In a
similar vein to H2, we predict:

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 11
Hypothesis 3 (H3): People’s social media use for information seeking is positively
associated with their social connectedness.
The Internet-enhanced Self-disclosure Hypothesis
In addition to the direct effect, several studies have demonstrated indirect effects relating
to social media use and connectedness. Valkenburg and Peter (2009) initially examined how the
effects of instant messaging use on positive relationships with existing friends can be achieved
through self-disclosure – an act of revealing personal information about emotions, thoughts, and
experiences to others (Taylor et al., 1973). The Internet-enhanced self-disclosure hypothesis
argues that self-disclosure fully mediates the relationship between online communication and
connectedness (Valkenburg & Peter, 2009), which has been corroborated in several studies (e.g.,
Chan & Li, 2020; Wang et al., 2011). According to this hypothesis, self-disclosure behav- iors
assume that senders trust receivers and value their opinions. It is posited that such interpersonal
attribution will lead to a process of reciprocal self-disclosure, which is conducive to relationship
development (Jiang et al., 2011).
Although the model initially examined individuals’ instant messaging as a way of social
interaction, its idea can be applied to other dimensions of social media use. Chen and Li (2017)
noted that, compared to instant messaging, social media allows users to update, amend account
profiles, and publish personal information as a means of self-disclosure, thereby signaling
attention, building trust, and desiring favorability from friends. Consequently, social
connectedness can be established. Therefore, it is plausible to anticipate that social interaction
would enhance one’s willingness to share their personal thoughts with others, especially to
reduce uncertainty under the pandemic situation, in turn contributing to social connectedness.
There- fore, we propose the following hypothesis:

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 12
Hypothesis 4 (H4): Self-disclosure mediates the relationship between people’s social
media use for social interaction and their social connectedness.
Moreover, the Internet-enhanced self-disclosure hypothesis can also be applied to the
information-seeking dimension of social media use. That is, sharing and disclosing act as con-
duits between communicative practices and relational out- comes. In more detail, social media
creates an environment where news can perfectly perform its role as social glue (Picone et al,
2016). Sharing news content enables people to engage in society and act based on a collective
frame- work (Swart et al., 2016). As a result, the sense of social connectedness can be developed
through self-disclosure. In addition to the self-focus, pandemic-related self-disclosure
encapsulates an “other-focus” that considers the social benefits of sharing information (Nabity-
Grover et al., 2020). Through self-disclosure – the sharing behavior that considers the public
good such as discussing one’s health status and health tips – people engage with certain
information to stay connected with others and society during the pandemic. Correspondingly, we
hypothesize as follows:
Hypothesis 5 (H5): Self-disclosure mediates the relationship between people’s social
media use for information seeking and their social connectedness.
To summarize, we notice that the Internet-enhanced self- disclosure hypothesis adds to
the fear-eliciting affiliation process by specifying social sharing of emotion in the con- text of
online self-disclosure. Guided by an integrative framework of the fear-eliciting affiliation and
Internet- enhanced self-disclosure hypotheses, we expect that people with a high level of
pandemic-related fear will interact with others, seek information, and disclose their personal
thoughts on social media to seek comfort and reduce uncertainty, all of which contribute to their
social connectedness. This also means that the effects of fear on social connected- ness might

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 13
proceed sequentially through social media use and self-disclosure or exclusively through social
media use. Given the various possible pathways, we put forward the following research question:
Research Question 1 (RQ1): To what extent does pandemic-related fear indirectly
influence social connectedness through social media use and self- disclosure?
Figure 1 summarizes the research model in this study.
[Figure 1 near here]
Method
The data were collected through online questionnaires using Qualtrics. We employed
multistage stratified sampling and distributed questionnaires to undergraduate students in Hong
Kong from October 7 to November 2, 2020. Three universities were randomly chosen, followed
by random selections of three faculties and three departments at each stage. Requests for
approval were made to instructors of randomly selected courses in the respective departments. A
total of 592 responses were obtained, with 20.5% of the students who had registered for the
selected courses completing the questionnaire. After deleting invalid responses and answers from
those who had not lived in Hong Kong for the preceding 3 months, our final sample size
amounted to 310. We removed responses from those who had not lived in Hong Kong in the past
3 months so as to ensure that the participants were in the same pan- demic context. Although the
survey was administered in Hong Kong universities, due to all courses being moved online, 89
students were physically out of Hong Kong, which might have resulted in different contexts.
Social media use for social interaction and information seeking
Following the perspective that people actively and purposively swing between different
platforms in a poly-social media environment (Tandoc et al., 2019), social media use was
measured in terms of different frequencies of social media platform use for information seeking

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 14
and social interaction, which was revised and adopted from previous studies (e.g., Gil de Ziga
et al., 2017). The respondents were asked to report the average time spent on the five most
popular social media platforms in Hong Kong (Face- book, WhatsApp, YouTube, Instagram,
Facebook Messenger; see We Are Social, 2021) for news information seeking and social
interaction per day. The responses included six options representing different lengths of time
usage ranging from 1 (= never) to 6 (= above 4 hrs). The responses were averaged for each 5-
item group in order to form the measures for information seeking (M = 2.64, SD = 0.89, α = .70)
and social interaction (M = 2.13, SD = 0.79, α = .71). Although the reliability estimates were not
high, they were still acceptable according to the criteria (> .70) proposed by Stempel et al.
(2003). A similar study measuring different levels of social media use could also be found in
Diehl et al. (2016), whose Cronbach α was equal to .72.
Social connectedness
Based on the Social Connectedness Scale (Lee & Robbins, 1995), five parallel items
were modified for this study to measure the respondents’ collective-level connectedness to the
society: (1) I feel a sense of closeness with other peo- ple; (2) I feel related to society; (3) I feel
accepted by society; (4) I feel like I fit into society; (5) I feel connected with society. The items
were rated on a 5-point scale ranging from 1 (= never) to 5 (= always). The responses were aver-
aged (M = 2.67, SD = 0.79, α = .89).
Self-disclosure on social media
The self-disclosure scale was adopted from Schouten et al. (2007). The respondents were
asked to indicate the extent to which they agreed with the following statements, on a 5-point
scale from 1 (= never) to 5 (= always), regarding COVID-19-related social-distancing measures
and their social media use: How much do you usually tell about (1) your personal feelings, (2)

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 15
the things you are worried about or afraid of, (3) your secrets, (4) being in love, (5) moments in
your life you are ashamed of, and (5) moments in your life you are happy about? The responses
were averaged to form the measure for self-disclosure (M = 2.41, SD = 0.82, α = .88).
Pandemic-related fear
The measure for pandemic-related fear was revised based on the scale from Zhang et al.
(2015), with six questions asking participants to indicate their fear-related feelings regarding
COVID-19 on a 5-point scale ranging from 1 (= never) to 5 (= always): (1) I am concerned that I
may be infected with COVID-19; (2) I am concerned that my family and friends may be infected
with COVID-19; (3) I am concerned that I may die from COVID-19; (4) I am concerned that
family and friends may die from COVID-19; (5) I don’t want to leave my home because of the
risk of getting infected with COVID-19; (6) In general, I am fearful of COVID-19. The
responses were averaged (M = 2.42, SD = 0.85, α = .92).
Control variables
To minimize the confounding effects, seven control variables were included as
covariates: gender (male = 31%), age (M = 20.20, SD = 2.61, age range = 17–30 years), monthly
expenditure (1 = less than 2000 HKD, 2 = 2,000–4,000 HKD, 3 = 4,000–6,000 HKD, 4 = 6,000–
8,000 HKD, 5 = 8,000–10,000 HKD, 6 = more than 10,000 HKD; M = 2.03, SD = 1.27), length
of residence in Hong Kong (measured on a 8-point scale with the following categories: 1 = less
than 6 months, 2 = 6 months to 1 year, 3 = 1–2years,4=2–4years,5=4–7years,6=7–10years,7=10–
15 years, 8 = more than 15 years; M = 7.10, SD = 1.70), relationship status (in a relationship =
25%), whether they themselves, their family members, or friends had contracted COVID-19 (yes
= 5%), and health condition (M = 3.53, SD = 0.90), which was measured by a 5-point self- rated
scale ranging from 1 (= bad) to 5 (= good).

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 16
Results
By exploring the zero-order correlations, a number of significant correlations can be
identified in Table 1. Specifically, pandemic-related fear was positively related to social
interaction (r = .18, p < .01), information seeking (r = .31, p < .01), and self-disclosure (r = .20, p
<. 001) but did not predict social connectedness. In addition, information seeking was positively
associated with social interaction (r = .55, p < .01), self-disclosure (r = .15, p < .01), and
connectedness (r = .14, p < .05), while social media use for interaction did not correlate with
self-disclosure. Moreover, social media use for interaction (r = .18, p < .01) was positively
correlated with social connectedness, and the relationship between self-disclosure and social
connectedness was initially supported (r = .33, p < .001).
[Table 1 near here]
In the second step, multiple linear regression analyses (see Table 2) were performed. In
total, four rounds of analyses were introduced to examine social media use for social interaction,
information seeking, self-disclosure, and social connectedness. Model 1 and Model 2 examined
how pandemic-related fear related to the two dimensions of social media use respectively. The
results demonstrated that fear significantly predicted information seeking but did not predict
social interaction. Moreover, information seeking significantly predicted social interaction (see
Model 2). Subsequently, Model 3 was conducted to examine how social media use and
pandemic-related fear predict self-disclosure. The results showed that pandemic-related fear and
social media use for information seeking were significant predictors of self-disclosure. However,
the relationship between social media use for social interaction and self-disclosure was not
significant. Finally, Model 4 was created to predict social connectedness. The results illustrated
that social media use for information seeking and pandemic-related fear did not predict social

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 17
connectedness, while social media use for social interaction and self-disclosure significantly
predicted social connectedness.
[Table 2 near here]
Structural Equation Modeling (SEM)
To test the proposed model in Figure 1, SEM was used to incorporate all the control and
study variables. After residualizing the control variables, the summary data of all the study
variables were entered into Mplus 8 using maximum likelihood estimation. Criteria suggested by
Hu and Bentler (1999) were used to evaluate the model fit: Cut-off values of the comparative fit
index (CFI) and the Tucker–Lewis index (TLI) should be larger than .95, the root mean square
error of approximation (RMSEA) should be .06 or lower, and the standardized root mean square
residual (SRMR) should be .08 or lower.
Estimations of the relationships showed a good model fit: χ2(1) = 0.61, p = .43; CFI =
1.00; TLI = 1.02; RMSEA = .00; SRMR = .01. To further refine the model, the non-significant
paths (p > .05) were deleted and depicted in dash-dot lines in Figure 2, resulting in the final
model: χ2(4) = 4.89, p = .30; CFI = .10; TLI = .99; RMSEA = .03; SRMR = .03. Table 3
provides a summary of the hypothesis testing from H1 to H5 and concludes with our decisions.
When all the variables were incorporated, much clearer relationships were detected because
several relationships had become insignificant in comparison with the preliminary analysis.
[Figure 2 near here]
[Table 3 near here]
H1 proposed a relationship between pandemic-related fear and social media use. The
results showed that fear significantly predicted social media use for information seeking (β = .22,
p < .001) but not for social interaction. Therefore, H1a was rejected, and H1b was supported.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 18
Moreover, the direct relationship between social media use for social interaction and
social connectedness was significant, while the indirect relationship through self-disclosure was
not significant. Therefore, H2 was supported, and H4 was rejected.
Conversely, self-disclosure successfully mediated the relationship between people’s
social media use for information seeking and their social connectedness, while the direct
relationship between information seeking and their social connectedness was insignificant.
Therefore, H5 was supported, while H3 was rejected.
Further analyses examined the indirect effect of pandemic-related fear on social
connectedness (RQ1). Table 3 details the indirect effect. Two pathways were identified.
Specifically, the relationship between pandemic-related fear and social connectedness was
mediated by self-disclosure (β = .05, p < .01) and a two-step process through information
seeking and self-disclosure (β = .01, p < .05).
Discussion
Motivated by the question of how pandemic situations – characterized by increased fear –
impact people’s connectedness, this study probed the complex relationships between pandemic-
related fear and social connectedness. Our results indicated that the relationship between pan-
demic-related fear and social connectedness was not direct and that it materialized through two
pathways. The first pathway was significantly mediated by self-disclosure on social media,
suggesting that pandemic-related fear provokes people’s self-disclosure intentions, with self-
disclosure leading to the greater social connectedness. Second, the effect could also be achieved
through a sequential pro- cess: Fear first elicits information seeking on social media; afterward,
information seeking enhances social connected- ness through self-disclosure. However, social
interaction does not mediate the relationship between fear and social connectedness on its own.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 19
To start with, our data supported the hypothesis that pan- demic-related fear increases
information-seeking behaviors on social media, which confirms our expectation that information
is crucial in risk scenarios, especially when individuals are faced with threats of potential harm
and uncertainty about the situation (Dillard et al., 2020). There- fore, fear motivates individuals
to actively seek information through social media. Nevertheless, fear does not provoke more
intensive interaction on social media. There are multiple explanations for this.
First, the relationship between fear and social interaction can be determined by the nature
and intensity of the fear experienced. It has been suggested that moderate and non-emotional
conditions of fear cannot effectively facilitate the social sharing of emotions (Luminet et al.,
2000) and that only intense fear will elicit affiliation. Therefore, for people who are not fearful of
contracting COVID-19, the linkage between fear and social sharing might not be sufficiently
salient. Moreover, Jenkins and Andrewes (2012) found that the younger participants in their
study demonstrated lower levels of emotional valence against fear stimuli compared to older
adults. Therefore, age differences do exist. In the current study, as the average score for
pandemic-related fear among young adults was 2.42 on a 5-point scale standing at a moderate
level, their levels of fear may not have elicited social interaction to a significant degree. Future
studies can be conducted to compare age cohorts so as to uncover the specificities of the
differences regarding the effects of fear on social inter- action. Another explanation relates to the
intricacies of social interaction as fear may provoke differentiated effects on different levels of
social interaction. For example, being exposed to a fearful condition may increase people’s
intention to engage in deep communication with others (Luminet et al., 2000), while it may also
decrease people’s unfocused interaction intentions because they may find that these activities do
not satisfy their psychological needs. In this sense, the influence of fear on social interaction may

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 20
be offset by the positive effect of fear on focused interactions and the negative effect of fear on
unfocused interactions, thus resulting in the nonsignificant overall relationship between fear and
social interaction.
Regarding the relationship between social media use and connectedness, social
interaction directly contributed to connectedness, which supported our hypothesis. However, the
direct relationship between information seeking and social connectedness was insignificant. We
speculate that opinion polarization and the flood of misinformation on social media may have
hindered the formation of common ground and a collective framework regarding certain societal
issues, thereby driving people away from being socially connected (Tucker et al., 2018).
Furthermore, Ytre-Arne and Moe (2021) suggested that pandemic news experience may occur as
“doomscrolling” – scrolling continuously through dark, unnerving news and struggling to stop,
resulting in a sense of escape and disconnection. Researchers may examine this specific form of
news use and how it affects social connections in the future.
Notwithstanding, information seeking did not directly predict social connectedness; the
effect became significant when self-disclosure was included in the analysis, which implies that
self-disclosure fully mediated the relationship between information seeking and social
connectedness. This result validated the Internet-enhanced self-disclosure model and reaffirmed
that self-disclosure plays a critical role in enhancing a person’s connection with society.
Likewise, social interaction had a similar mediating effect on the relationship between
information seeking and social connectedness. To recapitulate, individuals are impelled toward
common interests and common decoding positions by means of social interaction and self-
disclosure, which form the basis of an interpretive community (Lindlof, 1998). This phenomenon
can be further explored with qualitative strategies such as focus groups.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 21
Moreover, the association between social interaction and self-discourse lacked empirical
support. An explanation for this could be that self-disclosure is often triggered by specific social
goals (Omarzu, 2000). On social media, unfocused interactions that lack such goals may occur
more frequently than focused interactions. Apart from real-time communication, social media
also provides an asynchronous space for young adults to avoid deep interactions and initiate
more self-presentation behaviors on social media platforms. Nevertheless, our data were
incapable of providing conclusive evidence. Future studies may probe different forms of
interaction and their associations with self-disclosure.
Overall, we argue that fear motivated people to seek information, disclose personal
feelings to others, and articulate connectedness with society. During this process, social media
afforded an essential ground, and self-disclosure acted as a viable channel. As such, these two
communication elements were substantially integrated into the building of social connectedness
during COVID-19.
Theoretical and Practical Implications
Our findings have two major theoretical implications. First, the study provided evidence
confirming that fear eliciting affiliation is possible in online communication. More importantly,
the study adds to the literature by examining how devising the fear-eliciting affiliation
framework can help understand the communication processes, as we have depicted two
significant pathways through which fear motivates people’s social connection. In more detail,
our findings underscored the twofold role of communication, namely, social media use and self-
disclosure. We also concluded with a two-step mediation model to illustrate fear- motivated
communication and its social outcomes, which can extend beyond the uniqueness of the COVID-

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 22
19 con- text, with the potential of being applied to other public crises such as environmental
issues and social movements.
Second, we tested the Internet-enhanced self-disclosure model by categorizing social
media use into two subdimensions: information- and interaction-based use. As expected,
informational social media use also has the capacity to activate the disclosure–connectedness
link. Moreover, the informational use of social media demonstrated a larger observed effect on
stimulating self-disclosure and building connectedness than the interactional use of social media.
Such findings underscore the importance of news and public information in maintaining social
cohesion, which can be best achieved through interpersonal communication (Goh et al., 2019).
Furthermore, the context of the study represents a highly mediated communication sphere where
off- line interactions are lacking, and it advanced our understanding of the conditional social
media effect, that is, the way in which social media can create better social connectedness.
Practically speaking, the study addressed the imperative question of how not to lose
social connectedness in times of social distancing. It showed that it is feasible for people to stay
connected despite being physically apart. The study illustrates a process embedded in everyday
communication. First, as information is vital for a person to manage uncertainty in risk contexts,
the quality of information should be a shared concern among the diverse actors in the
information ecosystem, including the government, content providers, and users. Second,
individuals should be encouraged to self-disclose when they are fearful in difficult times, which
can assist them in coping with the cycle of pandemic information and becoming emotionally
involved in an interpretive community.
Research Limitations

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 23
The present findings should be interpreted in light of the following limitations. First, the
study limited its scope to pandemic-related fear only. As the pandemic prolonged, other
prevalent emotional factors (such as anxiety, anger, and depression) can be explored to achieve a
more comprehensive understanding of how people’s social connected- ness is impacted by the
pandemic. Second, the study employed a multistage stratified sampling procedure among
university students. The formation of the final sample was determined by various unaccounted
factors such as whether the course instructor permitted the survey. Also, the response rate of the
survey might have been discounted by the online distribution method. Students who showed
higher interest in the survey topic would be more willing to take part in the survey, which may
bias the results. More- over, those included in the sample are all young adults, who had a
relatively high level of social media engagement in everyday life. Therefore, the generalizability
of the findings may be compromised. Third, the survey instruments of social interaction could be
improved. In this study, social interaction was measured only by asking how often people
interacted with others through various social media plat- forms in everyday life, which may not
adequately represent people’s social interaction behaviors when the pandemic struck. With social
interaction existing at various levels and types, we may notice different relationships emerging
when we examine the differences between merely attention, click-based interaction, and deep
communication (e.g., McEwan, 2013). Addressing this question requires a more fine-grained
operationalization of social interaction during the pandemic situation. Finally, the study offers
pre- liminary insights and contributes to a more detailed under- standing of how fear influences
social connectedness, but it is inconclusive to draw causality from cross-sectional data, although
there is a solid theoretical framework in place. It is possible, for instance, that fear comes from

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 24
information seeking or that there is a bidirectional relationship. It is still necessary to use a
multiwave panel design to ascertain causality.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 25
References
Ali, K., Zain-ul-abdin, K., Li, C., Johns, L., Ali, A. A., & Carcioppolo, N. (2019). Viruses going
viral: Impact of fear-arousing sensationalist social media messages on user engagement.
Science Communication, 41(3), 314-338. https://doi.org/10.1177/1075547019846124
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin,
G. J. (2020). The psychological impact of quarantine and how to reduce it: Rapid review
of the evidence. The Lancet, 395, 912-920. https://doi.org/10.1016/s0140-
6736(20)30460-8
Chan, M. (2015). Examining the influences of news use patterns, motivations, and age cohort on
mobile news use: The case of Hong Kong. Mobile Media & Communication, 3(2), 179-
195. https://doi.org/10.1177/2050157914550663
Chan, M., & Li, X. (2020). Smartphones and psychological well-being in China: Examining
direct and indirect relationships through social support and relationship satisfaction.
Telematics and Informatics, 54. https://doi.org/10.1016/j.tele.2020.101469
Chen, H. T., & Li, X. (2017). The contribution of mobile social media to social capital and
psychological well-being: Examining the role of communicative use, friending and self-
disclosure. Computers in Human Behavior, 75, 958-965.
https://doi.org/10.1016/j.chb.2017.06.011
Couldry, N., Livingstone, S., & Markham, T. (2007). Media consumption and public
engagement. Basingstoke: Palgrave Macmillan.
Davis, K. (2012). Friendship 2.0: Adolescents' experiences of belonging and self-disclosure
online. Journal of Adolescence, 35(6), 1527-1536.
https://doi.org/10.1016/j.adolescence.2012.02.013

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 26
Diehl, T., Weeks, B. E., & Gil de Zúñiga, H. (2016). Political persuasion on social media:
Tracing direct and indirect effects of news use and social interaction. New Media &
Society, 18(9), 1875-1895. https://doi.org/10.1177/1461444815616224
Digital Reportal. (2020, February 13). Digital 2020: Hong Kong.
https://datareportal.com/reports/digital-2020-hong-kong.
Dillard, J. P., Li, R. B., & Yang, C. (2020). Fear of Zika: Information seeking as cause and
consequence. Health Communication, 36(13), 1785-1795.
https://doi.org/10.1080/10410236.2020.1794554
Dunlop, S., Wakefield, M., & Kashima, Y. (2008). Can you feel it? Negative emotion, risk, and
narrative in health communication. Media Psychology, 11(1), 52-75.
https://doi.org/10.1080/15213260701853112
Ellison, N. B., Triệu, P., Schoenebeck, S., Brewer, R., & Israni, A. (2020). Why we don’t click:
Interrogating the relationship between viewing and clicking in social media contexts by
exploring the “non-click”. Journal of Computer-Mediated Communication, 25(6), 402-
426. https://doi.org/10.1093/jcmc/zmaa013
Frampton, J. R., & Fox, J. (2021). Monitoring, creeping, or surveillance? A synthesis of online
social information seeking concepts. Review of Communication Research, 9, 1-42.
https://doi.org/10.12840/ISSN.2255-4165.025
Gil de Zúñiga, H., Diehl, T., Huber, B., & Liu, J. (2017). Personality traits and social media use
in 20 countries. Cyberpsychology, Behavior, and Social Networking, 20(9), 540-552.
https://doi.org/10.1089/cyber.2017.0295

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 27
Goh, D., Ling, R., Huang, L., & Liew, D. (2019). News sharing as reciprocal exchanges in social
cohesion maintenance. Information, Communication & Society, 22(8), 1128-1144.
https://doi.org/10.1080/1369118X.2017.1406973
Goodall, C., Sabo, J., Cline, R., & Egbert, N. (2012). Threat, efficacy, and uncertainty in the first
5 months of national print and electronic news coverage of the H1N1 virus. Journal of
Health Communication, 17(3), 338-355. https://doi.org/10.1080/10810730.2011.626499
Goodman-Deane, J., Mieczakowski, A., Johnson, D., Goldhaber, T., & Clarkson, P. J. (2016).
The impact of communication technologies on life and relationship satisfaction.
Computers in Human Behavior, 57, 219-229. https://doi.org/10.1016/j.chb.2015.11.053
Hall, J.A. (2020). Relating through technology. Cambridge University Press.
https://doi.org/10.1017/9781108629935
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis:
conventional criteria versus new alternatives. Structural Equation Modeling-a
Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
Hu, M. (2009). Will online chat help alleviate mood loneliness?. Cyberpsychology & Behavior,
12(2), 219-223. https://doi.org/10.1089/cpb.2008.0134
Janis, I. L. (1967). Effects of fear arousal on attitude change: Recent developments in theory and
experimental research. In L. Berkowitz. (Ed.), Advances in experimental social
psychology (Vol. 3, pp. 166-225). Academic Press.
Jenkins, L. M., & Andrewes, D. G. (2012). A new set of standardised verbal and non-verbal
contemporary film stimuli for the elicitation of emotions. Brain Impairment, 13(2), 212-
227. https://doi.org/10.1017/BrImp.2012.18

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 28
Jiang, L.C., Bazarova, N. N., & Hancock, J. T. (2011). The disclosure-intimacy link in computer-
mediated communication: An attributional extension of the hyperpersonal model. Human
Communication Research, 37(1), 58-77. https://doi.org/10.1111/j.1468-
2958.2010.01393.x
Johnston, K. A., & Lane, A. B. (2021). Communication with intent: A typology of
communicative interaction in engagement. Public Relations Review, 47(1).
https://doi.org/10.1016/j.pubrev.2020.101925
Kaya, T. (2020). The changes in the effects of social media use of Cypriots due to COVID-19
pandemic. Technology in Society, 63. https://doi.org/10.1016/j.techsoc.2020.101380
Kaye, L. K., Wall, H. J., & Malone, S. A. (2016). “Turn that frown upside-down”: A contextual
account of emoticon usage on different virtual platforms. Computers in Human Behavior,
60, 463–467. https://doi.org/10.1016/j.chb.2016.02.088
Kirkpatrick, L. A., & Shaver, P. (1988). Fear and affiliation reconsidered from a stress and
coping perspective. Journal of Social and Clinical Psychology, 7(2-3), 214-233.
https://doi.org/10.1521/jscp.1988.7.2-3.214
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukopadhyay, T., & Scherlis, W. (1998,
Sep). Internet paradox - A social technology that reduces social involvement and
psychological well-being?. American Psychologist, 53(9), 1017-1031.
https://doi.org/10.1037/0003-066x.53.9.1017
Lee, R. M., & Robbins, S. B. (1995). Measuring belongingness - the social connectedness and
the social assurance scales. Journal of Counseling Psychology, 42(2), 232-241.
https://doi.org/10.1037/0022-0167.42.2.232

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 29
Lei, M.-K., & Klopack, E. T. (2020). Social and psychological consequences of the COVID-19
outbreak: The experiences of Taiwan and Hong Kong. Educational Publishing
Foundation.
Lench, H. C., & Levine, L. J. (2005). Effects of fear on risk and control judgements and
memory: Implications for health promotion messages. Cognition & Emotion, 19(7),
1049-1069. https://doi.org/10.1080/02699930500203112
Lindlof, T. R. (1998). Media audiences as interpretive communities. In J. Anderson (Ed.),
Communication Yearbook 11 (pp. 81-107). Routledge.
Ling, R. & Lai, C. (2016). Microcoordination 2.0: Social coordination in the age of 7
smartphones and messaging apps. Journal of Communication, 66(5), 834-856.
https://doi.org/10.1111/jcom.12251
Luminet, O., Bouts, P., Delie, F., Manstead, A. S. R., & Rime, B. (2000). Social sharing of
emotion following exposure to a negatively valenced situation. Cognition & Emotion,
14(5), 661-688. https://doi.org/10.1080/02699930050117666
McEwan, B. (2013). Sharing, caring, and surveilling: An actor-partner interdependence model
examination of Facebook relational maintenance strategies. Cyberpsychology, Behavior,
and Social Networking, 16(12), 863-869. https://doi.org/10.1089/cyber.2012.0717
Nabity-Grover, T., Cheung, C. M. K., & Thatcher, J. B. (2020). Inside out and outside in: How
the COVID-19 pandemic affects self-disclosure on social media. International Journal of
Information Management, 55. https://doi.org/10.1016/j.ijinfomgt.2020.102188
Nic, N., Richard, F., Anne, S., Simge, A., & Rasmus, K. N. (2020, January 18). Reuters Institute
Digital News Report 2020.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 30
https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2020-
06/DNR_2020_FINAL.pdf
Omarzu, J. (2000). A disclosure decision model: Determining how and when individuals will
self-disclose. Personality and Social Psychology Review, 4(2), 174-185.
https://doi.org/10.1207/s15327957pspr0402_05
Pennington, N. (2020). An examination of relational maintenance and dissolution through social
networking sites. Computers in Human Behavior, 105.
https://doi.org/10.1016/j.chb.2019.106196
Picone, I., De Wolf, R., & Robijt, S. (2016). Who shares what with whom and why? News
sharing profiles amongst Flemish news users. Digital Journalism, 4(7), 921-932.
https://doi.org/10.1080/21670811.2016.1168708
Rhee, L., Bayer, J. B., Lee, D. S., & Kuru, O. (2021). Social by definition: How users define
social platforms and why it matters. Telematics and Informatics, 59.
https://doi.org/10.1016/j.tele.2020.101538
Schouten, A. P., Valkenburg, P. M., & Peter, J. (2007). Precursors and underlying processes of
adolescents' online self-disclosure: Developing and testing an "Internet-attribute-
perception" model. Media Psychology, 10(2), 292-314.
https://doi.org/10.1080/15213260701375686
Schrøder, K. C. (2014). News media old and new: Fluctuating audiences, news repertoires and
locations of consumption. Journalism Studies, 16(1), 60-78.
https://doi.org/10.1080/1461670x.2014.890332
Schwartz, J., & Grimm, J. (2016). Uncertainty in online U.S. news coverage of Truvada. Health
Communication, 31(10), 1250-1257. https://doi.org/10.1080/10410236.2015.1055051

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 31
Sosik, V. S., & Bazarova, N. N. (2014). Relational maintenance on social network sites: How
Facebook communication predicts relational escalation. Computers in Human Behavior,
35, 124-131. https://doi.org/10.1016/j.chb.2014.02.044
Stempel, G. H., Weaver, D. H., & Wilhoit, G. C. (2003). Mass communication research and
theory. Allyn and Bacon.
Swart, J., Peters, C., & Broersma, M. (2016). Repositioning news and public connection in
everyday life: A user-oriented perspective on inclusiveness, engagement, relevance, and
constructiveness. Media, Culture & Society, 39(6), 902-918.
https://doi.org/10.1177/0163443716679034
Tandoc, E. C., Lou, C., & Min, V. L. H. (2019). Platform-swinging in a poly-social-media
context: How and why users navigate multiple social media platforms. Journal of
Computer-Mediated Communication, 24(1), 21-35. https://doi.org/10.1093/jcmc/zmy022
Taylor, D. A., Wheeler, L., & Altman, I. (1973). Self-disclosure in isolated groups. Journal of
Personality and Social Psychology, 26(1), 39-47. https://doi.org/10.1037/h0034233
The Guardian. (2020, January 4). Mystery viral outbreak in Hong Kong revives fears of SARS
epidemic. https://www.theguardian.com/world/2020/jan/04/mystery-viral-outbreak-in-
hong-kong-revives-fears-of-sars-epidemic.
Tucker, J., Guess, A., Barbera, P., Vaccari, C., Siegel, A., Sanovich, S., Stukal, D., & Nyhan, B.
(2018). Social media, political polarization, and political disinformation: A review of the
scientific literature. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3144139
Valkenburg, & Peter. (2009). The effects of instant messaging on the quality of adolescents'
existing friendships: A longitudinal study. Journal of Communication, 59(1), 79-97.
https://doi.org/10.1111/j.1460-2466.2008.01405.x

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 32
Wang, J., Jackson, L., & Zhang, D. (2011). The mediator role of self-disclosure and moderator
roles of gender and social anxiety in the relationship between Chinese adolescents' online
communication and their real-world social relationships. Computers in Human Behavior,
27(6), 2161-2168. https://doi.org/10.1016/j.chb.2011.06.010
We Are Social. (2021, March 26). Hong Kong: social network penetration 2020. Statista.
https://www.statista.com/statistics/412500/hk-social-network-penetration/
Ytre-Arne, B., & Moe, H. (2021). Doomscrolling, monitoring and avoiding: News use in
COVID-19 pandemic lockdown. Journalism Studies, 22(13), 1739-1755.
https://doi.org/10.1080/1461670X.2021.1952475
Zhang, L. l., Kong, Y., & Chang, H. (2015). Media use and health behavior in H1N1 flu crisis:
The mediating role of perceived knowledge and fear. Atlantic Journal of Communication,
23(2), 67-80. https://doi.org/10.1080/15456870.2015.1013101
Zhong, B., Huang, Y., & Liu, Q. (2021). Mental health toll from the coronavirus: Social media
usage reveals Wuhan residents' depression and secondary trauma in the COVID-19
outbreak. Computers in Human Behavior, 114. https://doi.org/10.1016/j.chb.2020.106524

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 33
Tables
Table 1
Zero-order Correlation Matrix of Study Variables
1
2
3
4
5
1 Social media use for social interaction
-
2 Social media use for information seeking
.55***
-
3 Social connectedness
.18**
.14*
-
4 Self-disclosure
.10
.15**
.33***
-
5 Pandemic-related fear
.18**
.31***
.06
.20***
-
Note. N = 310. *p < .05. **p < .01. ***p < .001.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 34
Table 2
The Multiple Regression Models on Main Study Variables
Model 1
Model 2
Model 3
Model 4
Information
seeking
Social
interaction
Self-disclosure
Social
connectedness
Predictors
Pandemic-related
Fear
.24***
-.05
.19**
.04
Information seeking
-
.48***
.13*
.08
Social interaction
-
-
.04
.24***
Self-disclosure
-
-
.23***
Control Variables
Age
-.08
-.13*
-.01
.12#
Male
.17**
-.19*
-.15**
.07
Length of residence
in Hong Kong
.23**
.15*
-.25 **
-.14*
Monthly expenditure
.02
.04
.03
.06
Relationship status
.09
.08
.13*
-.15**
Health condition
-.01
.04
.14*
.27***
Contact with virus
.05
.02
-.08
.01
R2 change (%)
5.5***
19.2***
6.6***
14.3***
Final adjusted R2(%)
16.6***
32.9***
14.5***
28.1***
Note. All betas are final-entry standardized coefficients. # p <.10 *p < .05. **p < .01. ***p < .001.
(N = 288).

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 35
Table 3
Summary of Hypotheses Testing in SEM
Direct and Indirect Effect Keys
Coefficient
Decision
H1a
Fear → Social Interaction
NA
×
H1b
Fear → Information Seeking
.22***
√
H2
Social Interaction → Connectedness
.28***
√
H3
Information Seeking → Connectedness
NA
×
H4
Social Interaction → Self-disclosure → Connectedness
NA
×
H5
Information Seeking → Self-disclosure → Connectedness
.04*
√
RQ1
Fear → Self-Disclosure → Connectedness
.05**
√
Fear → Information Seeking → Self-disclosure →
Connectedness
.01*
√
Total indirect effect
.06***
Notes. N = 310. Coefficients are standardized. *p < .05. **p < .01. ***p < .001 (two-tailed). Fear
= Pandemic-Related Fear; Connectedness = Social Connectedness; Information Seeking = Social
Media Use for Information Seeking; Social Interaction = Social Media Use for Social
Interaction.

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 36
Figures
Figure 1
Proposed Conceptual Framework
Note. The link between social media use for social interaction and information seeking is
indicated with a dash-dot line because these two dimensions of social media use may covariate
with each other. The study does not pose it as a formal hypothesis because we primarily focus on
the assumptions of fear-eliciting affiliation and the Internet-enhanced self-disclosure hypothesis.
Pandemic-related
fear
Social media use for
social interaction
Social media use for
information seeking
Self-disclosure
Social
connectedness
H1a
H1b
H2
H3
H4
H4
H5
H5

EFFECTS OF FEAR ON SOCIAL CONNECTEDNESS 37
Figure 2
The Final SEM Model on Main Study Variables.
Notes. N = 310. Coefficients are standardized. χ2(4) = 4.89, p = .30; CFI = 1.00; TLI = .99;
RMSEA = .03; SRMR = .03. **p < .01. ***p < .001 (two-tailed).
Pandemic-related
fear
Social media use for
social interaction
Social media use for
information seeking
Self-disclosure
Social
connectedness
.19**
.48***
.26***