Title
Does Emotional Support Matter? An Empirical
Title
Study of User’s Self-Disclosure on RED
Student Name
Luo Qianxi
Student No.
2019052419
Major
Journalism (International Journalism)
Supervisor
Gao Li
Date (dd/mm/yyyy) 30/04/2023
暨 南 大 学
本科生毕业论文
论文题目
社交媒体情感支持对小红书用户自我披露行为
的影响研究
学
院
学
系
专
业
新闻学（国际新闻）
姓
名
罗芊曦
学
号
2019052419
指导教师
国际学院
高丽
2023 年 4 月 30 日
Statement of Originality
I hereby declare that the thesis presented is the result of research performed by me personally,
under guidance from my supervisor. This thesis does not contain any content (other than those
cited with references) that has been previously published or written by others, nor does it
contain any material previously presented to other educational institutions for degree or
certificate purpose to the best of my knowledge. I promise that all facts presented in this thesis
are true and creditable.
Signed:
Date:
Does Emotional Support Matter? An Empirical Study of User’s
Self-Disclosure on RED
Abstract: Emotional support on social media has become a significant predictor of online
behaviors today. With a growing body of literature on online emotional support, it is necessary
to explore its characteristics and effects in a Chinese setting. This study aims to generalize the
features of emotional support on Chinese social media RED and examine the influence
mechanism of RED users’ perceived emotional support on their self-disclosure via attachment.
The results suggest that (1) people's perceived emotional support on RED is positively related
to their extent of self-disclosure; (2) people's perceived emotional support on RED is positively
related to the level of attachment security; (3) the level of attachment security is positively
related to people's general extent of self-disclosure; (4) attachment security partially mediates
the relationship between perceived emotional support and self-disclosure on RED.
Key Words: Emotional Support, Self-Disclosure, Attachment, RED
Contents
1. Introduction ............................................................................................................................ 1
1.1 Overview ...................................................................................................................... 1
1.2 Significances ................................................................................................................. 2
2. Literature Review ................................................................................................................... 3
2.1 Emotional Support Offline and Online ......................................................................... 3
2.2 Online Self-disclosure and Emotional Support ............................................................ 5
2.3 The Role of Attachment in Online Behaviors .............................................................. 8
2.4 Relations between Emotional Support, Attachment, and Self-disclosure .................. 10
3. Methodology......................................................................................................................... 14
3.1 Methods ...................................................................................................................... 14
3.2 Participants ................................................................................................................. 14
3.3 Measurements ............................................................................................................. 15
3.4 Procedure .................................................................................................................... 18
3.5 Data Analysis .............................................................................................................. 19
4. Results of Data Analysis ....................................................................................................... 20
4.1 Descriptive Statistics .................................................................................................. 20
4.2 Measurement Model ................................................................................................... 22
4.3 Common Method Variance ......................................................................................... 22
4.4 Structural Model ......................................................................................................... 24
4.5 Mediation Analysis ..................................................................................................... 25
4.6 Impact of Interaction Frequency and Gender Differences ......................................... 26
5. Findings and Discussions ..................................................................................................... 27
5.1 Findings ...................................................................................................................... 28
5.2 Interpretation of Findings ........................................................................................... 28
5.2.1 Emotional Support on RED ............................................................................. 28
5.2.2 The Role of Social Media Emotional Support................................................. 29
5.2.3 Attachment Security and Its Mediation Effect ................................................ 31
5.2.4 Influence of Interaction Frequency.................................................................. 33
5.2.5 The Gender Matters ......................................................................................... 34
5.3 Implications ................................................................................................................ 34
5.3.1 Theoretical Contributions ................................................................................ 34
5.3.2 Practical Implications ...................................................................................... 35
5.4 Limitations and Future Research ................................................................................ 37
5.4.1 Limitations in Research Design ....................................................................... 37
5.4.2 Prospects for Future Research ......................................................................... 37
6. Conclusion ............................................................................................................................ 38
Acknowledgements .................................................................................................................. 40
Appendix .................................................................................................................................. 41
References ................................................................................................................................ 44
1. Introduction
1.1 Overview
Emotional support refers to a supportive message that contains feelings of trust, understanding,
sympathy, or caring. Historically, the phrase has been used in psychology studies to better
understand how people's emotional support affects others and their social well-being. In
face-to-face communications, emotional support is delivered through both verbal and
nonverbal expressions such as facial reactions, hugs, or eye contact. With the popularity of
social media, online communications have gradually occupied a large part of human social life,
which lead to an increasing academic interest in understanding emotional support in an online
setting. A growing body of recent literature has combined emotional support to understand
people’s social behaviors in online communities. In this case, emotional support not only
consists of conditional supportive messages closely related to emotions but also contains online
interactions such as liking, commenting, and reprinting.
In recent years, a large number of preceding works in the disciplines of psychology and
communication have examined the function of online emotional support. Unlike psychological
research which directly refers to emotional support, communication scholars tend to measure
the concept under the title of social support. Multiple studies have found that online social
support, which includes instrumental, informational, and emotional support, is related to
people's mental health and future use of online support groups, socio-commerce platforms, and
social media (Yoo et al, 2014; Malecki & Demaray, 2003). People's perceived social support
online, in particular, can increase their propensity to disclose personal information with other
media users, with emotional support serving as an important predictor of their self-disclosure
purpose, breadth, and depth (Weber et al., 2004). While Western scholars tend to notice the
crucial role of emotional support in online interactions, Chinese researchers are more likely to
focus on social support as a whole, suggesting the necessity to look closer into the specific
emotional support in a Chinese setting.
Regarding the emotional support literature to date, earlier studies have confirmed a
positive and direct relationship between online emotional support and self-disclosure. However,
few of them examined how these two variables might be impacted by additional variables,
particularly adult attachment. Research on the relationship between emotional support,
1
attachment, and self-disclosure is also conducted independently (Hunter et al., 2006;
Mikulincer & Nachshon, 1991), thus providing a new idea to investigate the indirect effect of
emotional support on self-disclosure via attachment.
Collectively, this study aims to examine the impact mechanism of emotional support on
people's self-disclosing behavior through attachment security and to identify the features of
emotionally supportive messages on Chinese social media by investigating RED users with an
online questionnaire. As one of the most popular social media apps, RED has more than
170,780,000 monthly active users and experienced a fast growth of downloads in the past two
years (iiMedia Ranking, 2022). The media is also famous for its amicable platform atmosphere
which triggers a high frequency of emotional support exchange. Therefore, conducting the
research on RED can not only target a diverse sample but can explore the role of emotional
support on Chinses social media more precisely. Since previous works on RED mostly
emphasized its characteristic as a socio-commerce platform, this study offers further insights
into its social media functions.
1.2 Significances
The particular significances of this study lie in its contributions to the existing emotional
support and self-disclosure literature and a deepening of understandings about the role of online
emotional support in people’s social life. First, it presents an overview of emotional support on
RED and provides suggestions for future academics in the field. The present study indicates
that RED users mostly exchange emotionally supportive messages on rational topics like
knowledge popularization, showing the unique preferences of Chinese people to express
sympathy or approval online. On the other hand, the findings of this study confirm that the
positive effects of social media emotional support on secure attachment as well as
self-disclosure can still apply to Chinese media, which further verifies the universality to
predict people’s online activities by an irrational factor.
Second, the findings of this study explain how emotional support can affect people’s
online activities in a psychological process. Specifically, this study highlights the increasing
importance of emotional factors in online interactions and its role in reducing people’s concerns
about sharing personal details with unfamiliar others. It is noted that emotionally supportive
messages not only encourage people to participate in media content creation but also satisfy
2
their multiple social needs by providing timely responses as well as a sense of safety within the
socialization.
2. Literature Review
2.1 Emotional Support Offline and Online
Emotional support is originally mentioned as a psychological concept within the context of
social support, which mainly consists of two crucial parts: structural and functional support.
Theoretically, structural support refers to the number of relationships within social interactions
whereas functional support is more concerned with the quality of these relationships (e.g.,
emotional support) (Reblin & Uchino, 2008). Furthermore, functional social support can be
divided into two types: received support and perceived support. In this case, emotional support
refers to the perceived availability of caring, trusting individuals with whom life experiences
can be shared (Brinker & Cheruvu, 2017).
A large body of literature has investigated the definition of emotional support and its role
in face-to-face communications. According to Burleson (1984), emotional support is an
approach to help other people cope with depression by listening, empathizing, and rationalizing
their feelings through conversations. Buhrmester et al. (1988) suggested that emotional support
is a domain of people's interpersonal competence which can provide comfort when others are
undergoing problems and distress. Being emotionally supported is also viewed as the
determinant of intimacy development and people’s satisfaction with interpersonal relationships
with friends, lovers, families, and colleagues at work (Cunningham & Barbee, 2012; Burleson,
2008).
With the emerging use of the Internet and social media, online communications gradually
extend face-to-face communications and thus change the landscape of how people exchange
social support and emotional support with each other. Since the absence of nonverbal cues such
as facial expressions and touch (Wright, 2012), online social support that may help social media
users has greatly relied on messages and is naturally intangible. Previous research states that
social support from the internet generally covers at least three aspects: instrumental,
informational, and emotional support (X. Li et al., 2015). Specifically, instrumental support is
the provision of tangible help including financial and material assistance as well as needed
3
services. Informational support encompasses the given messages from online communities that
could help people cope with their problems in the form of advice, knowledge, or referrals.
Emotional support refers to providing messages that involve emotional concerns like trust,
caring, understanding, encouragement, affirmations, or sympathy (Malecki & Demaray, 2003;
Taylor et al., 2004). Different from instrumental and informational support that offer helps to
other users directly, emotional support in the virtual environment is expected to be beneficial in
an indirect way (Liang et al., 2011). Within a social media context, likes, favorites, and upvotes
are all examples of ways in which emotional support is provided (Liu & Ma, 2020). In the
current study, online emotional support is defined as a form of emotionally supportive message
that encompasses an individual’s perceived feelings of trust, understanding, caring, sympathy,
or encouragement, and also includes social interactive behaviors such as likes, favorites, and
collections.
Considerable research attention has been devoted to the effect of emotional support on
individuals’ psychological health and social well-being within online communities. Wang and
colleagues (2012) claimed that emotional support people obtained in online support groups can
strengthen their perceived bond with support providers and is strongly associated with their
increased group commitment. In a study of members’ mental health outcomes in an online
breast cancer support community, Yoo and the team (2014) found that breast cancer patients
who participate in exchanging emotional support show better performance in their emotional
well-being. Emotional support is also found to be helpful with teacher-student interactions
through the internet. An analysis of online collaborative learning demonstrated that emotional
support can establish strong socio-emotional bonds within a work team and can create a climate
of trust as well as a sense of belonging among team members (Hernández-Sellés et al., 2019).
In an e-commerce setting, emotional support is proven to be strongly associated with
customers' behaviors. Liang et al. (2011) yielded that emotional support from other users is
positively related to people's perceived relationship quality on social commerce platforms and
thus has a significant effect on their continuous use of online shopping sites. Scholars have also
noted that emotional support on social commerce sites can generate familiarity among
customers which promotes their relationship intimacy (Li, 2017). According to Hammouri and
Abu-Shanab (2017), emotional social support provided by other consumers on online
4
communities can establish a long-term trust toward specific brands and promote purchase
behavior in online market.
Despite a massive number of studies centered on various online forums, numerous studies
have also attempted to explain the provision of emotional support in a more general type of
online communities such as Social Networking Sites (SNSs) and social media (e.g., Facebook
and Microblog). Past work indicated that emotional support from online friends can promote
people's satisfaction with their online social life, and thus lead to better online well-being and
affect their continuous use and commitment to SNSs (Lee et al., 2013; Lin et al., 2016). In an
analysis of the impact of Facebook emotional support on college students' perceived stress,
Wright (2012) reported that online emotional support can greatly reduce an individual's
perceived life stress and is strongly associated with the homophily they perceived with others.
However, some scholars have argued that online emotional support may also generate negative
feelings at the same time (Shensa et al., 2020). For example, McCloskey et al. (2015) reported
in a newly developed measure of Facebook social support that emotional support from social
media is associated with higher depression and loneliness. Shensa et al. (2020) similarly
claimed that Facebook emotional support is associated with greater depression risks among
young adults. Furthermore, being emotionally supported online can also contribute to people's
internet addiction and media dropout (Liu & Ma, 2020; Chang et al., 2019).
Collectively, prior studies have outlined the critical role of online emotional support in
people's social interactions and media use behaviors. Receiving emotional support from the
internet is not only associated with human emotional needs (e.g., fighting against passive
feelings) but is significantly related to people's social demands (e.g., building up relationships).
Since past works have devoted less attention to examining the impact of emotional support on
media users' behavior than other influence factors, it is necessary to explore how online
emotional support can change people's media use especially in a Chinese context.
2.2 Online Self-disclosure and Emotional Support
Self-disclosure has been mentioned by Jourard and Lasakow (1958) as an approach to an
individual making the self known to others and was redefined as a process of telling one’s
self-related information, honestly sharing one’s personal, private thoughts and feelings with
another person (Jourard, 1971). Traditionally, scholars have used the term as a personality
5
construct in research or to describe the process within social interactions simultaneously
(Cozby, 1973). In face-to-face communications, self-disclosure not only promotes
interpersonal relationships but also acts as a crucial part of developing intimacy and trust
between couples. Researchers have also highlighted that self-disclosure is a reciprocal process
where one person's disclosure can encourage other people to disclose the self responsively
(Greene et al., 2006). To this end, the reciprocity of disclosure appears to be a norm of social
interactions today, especially with the growing popularity of social media.
With the integration of social media, people today can connect and interact with each other
across geographic and time limits. Compared to the counterpart in face-to-face communication,
self-disclosure on social media is granted with new patterns due to the strong connectivity as
well as anonymous environment of internet. Typically, online self-disclosure is aimed at
multiple people where as self-disclosure of offline communication occurs in a relatively smaller
group. By liking, commenting, and sharing multiple media content, individuals disclose their
identity, social networks, and social interactions purposefully and publicly. Self-disclosure,
therefore, becomes the core behavior on social media and is recognized as a promotor of
people’s communication frequency in online contexts (Caplan, 2007).
Considerable research attention has been devoted to understanding the determinants of
self-disclosure. For example, Rime et al. (1998) reported in a study about the social sharing of
emotions that people tend to disclose themselves when experiencing emotionally intense events.
Collins and Miller (1994) have noted that liking can motivate people to self-disclose during
interactions. Partners’ responsive disclosure can also be a strong predictor of people’s
disclosive behaviors (Reis & Shaver, 1988). Collectively, an individual's disclosive behaviors
are greatly affected by various motives including internal, social, and contextual factors.
Internal factor, in this case, is related to one person's psychological state which may reflect
on their psychological needs and thus influence the disclosure productions online (Luo &
Hancock, 2020). Study of disclosure reported that those with psychological distress may show a
greater desire to express themselves through the internet to cope with stress and work off steam
(Pennebaker, 1997). It is also proved that people who perceive higher levels of stress can trigger
greater amounts of self-disclosure on social media than those with less pressure.
Unlike the one motivated by internal reasons, self-disclosure driven by social factors such
6
as relational development aims to develop relational connection and intimacy with others. As
stated by Lai and Yang (2015), interpersonal needs of relational maintenance have a significant
effect on individuals’ self-disclosure behavior. More specifically, people who are in need of
interacting or contacting with online friends show higher propensity to disclose the self at a
great extent on social media. According to Luo and Hancock (2020), people who are lonely and
socially anxious in real life self-disclose more through online networking to compensate for a
lack of interpersonal interactions. Previous researches have also shown that self-disclosure on
social media is strongly associated with interpersonal closeness in which social media users can
express affinity to make up for the textual environment in an online setting (Hollenbaugh &
Ferris, 2014).
Drawing on an extensive range of sources, Desjarlais et al. (2015) yielded in a literature
review that the context factor, which refers to the online environment, also contributes to
people's self-disclosure online. The absence of identity cues and anonymity on social media
make it easier for users to disclose any kind of content across the board compared to real-name
setting offline. People’s perceptions of network responsiveness, on the other hand, also
contribute to their disclosive behaviors with which people may disclose themselves more
openly if they think their social media network is more responsive (Walsh et al., 2020). Prior
studies also found a positive effect between trust and self-disclosure in which trust can predict
an individual's self-disclosure online (Taddei & Contena, 2013). In an analysis of customer
self-disclosure on sci-commerce sites, Bansal et al. (2010) indicated that customers show
greater proneness to reveal information if they have a higher level of trust in brands and
websites via perceived customer care. The finding, which highlighted the role of customer care,
may suggest that people's self-disclosure can be affected by emotional elements.
To date, a number of studies have examined the impact of emotional support on people’s
disclosive behaviors. Y. Lin and Chu (2021) investigated the association between online
self-disclosure and intimacy development on social media and found that users who have a
sense of emotional support from the sites tend to engage in self-disclosure with considerable
depth and breadth. Weber et al. (2004) similarly demonstrated that emotional support has a
positive effect on people’s intent to self-disclose online. It is also proved that a favorable social
support environment as well as positive emotional support can significantly encourage people
7
to share information and reveal personal stories online (Zhou, 2017). Despite the growing body
of research drawing attention to how emotional support can predict people’s disclosure, most
studies, however, centered on emotional support as the benefit and result of self-disclosing
online (Lu & Hampton, 2017; Wang et al., 2015). In this case, to further explore the impact of
emotional support on an individual's self-disclosure can not only fill in the gaps of relevant
research but establish a better understanding of how emotional elements can facilitate people’s
media use. Therefore, the following hypothesis is proposed:
H1: The user's perceived emotional support is positively related to his/her self-disclosure
on RED.
2.3 The Role of Attachment in Online Behaviors
The term “attachment” is a psychological construct which initially developed by Bowlby (1969)
in the study of parent-child relationships. Accordingly, Bowlby (1969) concluded that
attachment is a unique emotional bond between infants and mothers or caregivers and
highlighted that infants will react strongly when being departed from their mothers. The finding
then established a foundation for attachment research today. In an analysis of how childhood
attachment styles help form adult attachment styles, Ainsworth et al. (1978) concluded that
people can be divided into secure individuals, anxious-ambivalent individuals, and
anxious-avoidant individuals based on different levels of attachment anxiety and avoidance. To
this end, attachment has multiple characteristics of which to seek support and comfort from
attached partners when being frightened or afraid and becoming anxious when being separated
from the partners (Cao et al., 2016).
Based on the attachment framework above, considerable scholars have applied the theory
to adult relationships. For example, Hazan and Shaver (1987) yielded in the study of couples
and found that attachment styles formed by parent-child attachments are significantly
associated with the caretaking behaviors between romantic partners. The exploration of adult
attachment was then extended to the domain of friendship, in which Fraley and Davis (1997)
reported that secure friendships are not only beneficial to a secure romantic attachment but can
also provide single individuals with primary attachment. Along with the increasing number of
attachment researches, recent studies have shifted attention from interpersonal attachment to
place attachment, brand attachment, and so forth. For example, Hidalgo et al. (2001) developed
8
the term “place attachment” to explain a positive emotional tie between individuals and specific
spots, emphasizing the effect of emotional elements within attachment as well as an individual's
action intent on strong emotional attachments. In the marketing domain, prior study reported
that consumers with a higher level of attachment toward the brand or products are more willing
to maintain a long-term relationship with the firm and purchase their products repeatedly (Liu,
2020).
With regard to information system domains, prior researchers have noted the applicability
of using attachment theory to explain people’s online behaviors. Similar to place attachment,
people can form attachment relationships with virtual communities through their interactions
online (Goel et al., 2011), which further leads to their continuous use of the medium. Choi
(2013) claimed in an empirical study that online user attachments have a positive effect on
people’s intention to participate in online communications. In the context of social media,
people's attachment styles are significantly associated with people's engagement with the media.
Theoretically, one person's attachment styles can reflect his or her unique cognitions, emotions,
and behaviors in close relationships. Ren et al. (2012) yielded that different types of attachment
styles can result in variance between people's informational behaviors. According to Shaver
and Mikulincer (2007), individual attachment styles predict the way how people interact with
acquaintances and strangers. An empirical study of young people's interactive behaviors in
virtual social networks reported that secure individuals are more likely to develop more social
ties and initiate web-based relationships (Yaakobi & Goldenberg, 2014). They also revealed
that a decreased avoidance score can result in an increased willingness to information
dissemination online.
Despite a large body of studies about individual variance in attachment styles to important
others, some scholar devoted their attention to intrapersonal variability of attachments across
relational partners (La Guardia et al., 2000). In line with Self-Determination Theory, La
Guardia and colleagues (2000) established the A-R-C model to explain the mechanism of how
people form secure attachment in communications and noted that attachment security is
significantly linked with psychological need fulfillment. To this end, the degree of an
individual's secure attachment is well predicted by how much they are satisfied with the needs
of autonomy, relatedness, and competence (La Guardia et al., 2000). Accordingly, autonomy
9
need refers to one person's recognition and choice of behavior when he or she perceives the
external environment as satisfied. Relatedness need relates to an individual's desire to pursue a
sense of belonging in a group and to form strong relationships with others. Competence need is
people's perceived feeling of capability and increased effectiveness when accomplishing
certain tasks. Past work has applied the A-R-C model and proved that users' emotional
attachment, determined by three primary demands, can effectively explain and predict their
stickiness toward social networks through online interactions (X. Ren, 2018).
2.4 Relations between Emotional Support, Attachment, and Self-disclosure
A growing body of research today has indicated that there is a correlation between emotional
support, attachment as well as self-disclosure. With regard to the workplace domain, prior
researchers have investigated the mechanism of how workers' perceived emotional support can
generate a sense of attachment in organizations. For example, Nelson and Quick (1991) noted
that newcomers who need help will form attachments with others who provide them with
protection and nurturance. In the context of social media, people can seek emotional benefits
through online interactions with other people (X. Ren, 2018). Past work has found that
members from virtual communities can receive emotional support from each other with a high
frequency of commenting or liking (Tu & Chen, 2015). In a qualitative study of online
supportive content, K. Huang et al. (2010) examined the characteristics of informational and
emotional support provided in support communities and suggested that emotional support from
other members may generate emotional comfort and attachment. In the same vein, Hunter et al.
(2006) found that emotional support from caregivers is positively correlated with the degree to
which recipients are securely attached. Yet, multiple studies have reported a positive
relationship between emotional support and individual attachment; however, few draw their
attention to investigating whether people's perceived emotional support from social media
makes a difference to their level of attachment security. To this end, the current study plans to
further verify the influence relationship between these two factors and examine how much can
emotional support promote people’s overall attachment security. Hence, the following
hypothesis is proposed:
H2: The user's perceived emotional support is positively related to the level of his/her
attachment security.
10
Referring to individual attachment and self-disclosure online, scholars to date have
considered the role of attachment in predicting the way in which people disclose themselves in
an internet setting. Shang and colleagues reported in 2015 that people’s attachment style can
change their posting and interactive behaviors on social network. According to C. Huant et al.
(2019), attachment security is effective in measuring individuals' numbers of social ties as well
as the intention to develop web-based relationships with others through online communications.
Prior works have also indicated that secure people not only show more self-disclosure but also
feel more comfortable interacting with other people online (Mikulincer & Nachshon, 1991;
Keelan et al., 1998; Wei et al., 2005). Grabill and Kerns (2000) similarly reported a positive
effect of secure attachment to self-disclosure in a short-term adult relationship. According to
Welch and Houser (2010), a securely attached individual is demonstrated to be more satisfied
with relationships and disclose more about the self to their interactive partner. In contrast to
previous studies, Aharony (2016) argued that there is a negative correlation between attachment
security and people’s self-disclosure online and highlighted that insecurely attached people
disclose themselves more on Facebook due to their avoidance of face-to-face communications.
Similarly, Keelan and colleagues (1998) reported in a study of individuals’ online relationship
satisfaction that people with an insecure attachment style disclose more intimate information to
strangers through social networking sites. In view of all that has been mentioned so far, one may
suppose that the level of attachment security is a strong predictor of people's self-disclosing
behaviors within the online environment. Since there are conversed findings about how
people's degree of security can result in less or more self-disclosure, it is necessary to
re-examine the association between these two elements. Hence, the following hypothesis is
proposed:
H3: The level of the user's attachment security is positively related to his/her
self-disclosure.
Along with past works that involve attachment in investigations about emotional support
as well as self-disclosure, several studies have identified a mediating effect of attachment in
people's emotional experiences and their future behaviors. For example, Cai et al. (2013)
reported a mediating effect of attachment within the relationship between authoritative
parenting to Chinese adolescent-parent communications, indicating that a lack of emotional
11
support from parents predicts adolescents' less frequency to disclose themselves with parents
via a lower degree of secure attachment. Collectively, previous investigations on the role of
attachment in relation to emotional support and self-disclosure are mutually independent, and
less is known about whether attachment can affect the influence path from an individual's
perceived emotional support and the act of self-disclosing. To this end, the following research
question is proposed:
RQ1: Does the level of users' attachment security mediate the relationship between their
perceived emotional support and online self-disclosure?
In light of the fact that people are likely to spend more time on social media, it becomes
important to discuss how the frequency of participating in online interactions may impact a
person's online behavior. In the e-commerce domain, scholars have indicated that the more
consumers participate in social interactions through social media, the more likely they are to
purchase certain products online in the future (Kozinets et al., 2010). Further, the number of
individuals’ interpersonal communication within online communities is also closely related to
their emotional bonding as well as an attachment to other members, which therefore motivates
them to join online value co-creation (Shen et al., 2020). With regard to communication studies,
a considerable body of work has indicated that the time people spent on online interactions
negatively correlates with their perception of emotional support (Shensa et al., 2016) and is
positively associated with increasing media addiction (Liu & Ma, 2020). Yet, little evidence is
found to support the correlations between the frequency of online interactions, perceived
emotional support, and self-disclosure. Therefore, it is of great significance to discuss and
further explore how people’s frequency to interact with other social media users can change
their perceptions of online emotional support, the overall level of attachment security, and the
extent to which they self-disclose information on social emdia. Thus, the following research
question is proposed:
RQ2: What are the effects of online interaction frequency on RED users’ perceived
emotional support, attachment security, and self-disclosure?
Gender is found to be an important factor in people’s perception of emotional support and
self-disclosure online (Nelson & Quick, 1991; Cosby, 1973). Prior studies indicated that gender
not only affects people’s attitude to emotional support but also influences their choices of what
12
and how much to disclose in online interactions (Burleson, 2003; Bond, 2009). Traditionally,
females are thought to be more considerate and have a greater desire to tell personal stories.
Males are generally thought to be tougher and stronger, as they tend to withhold personal
feelings when communicating with others. In an online environment, women are more sensitive
to emotional support and more likely to disclose multiple topics than men. However, men show
a greater desire to start intimate communication with new friends online than women do (Bond,
2009). Despite multiple studies that found significant differences between women and men in
perceived support and self-disclosure, some scholars argued that there are no obvious
distinctions between genders in online communications, especially for those who come from
the same cultural background (Burleson, 2003). Thus, there is a need to explore gender
variances in perceived emotional support and self-disclosure on Chinese social media RED. In
this study, gender differences are explored through the following research question:
RQ3: What are the differences in perceived emotional support, attachment security, and
self-disclosure as reported by males versus females?
Taken together, the present study aims to generalize the characteristics of emotional
support on RED and investigate the mechanism by which RED user’s perceived emotional
support affects their online self-disclosure. Additionally, the study also intends to examine the
mediation effect of attachment security within the relationship of emotional support and
self-disclosure. Based on the above hypothesizes and research questions, a conceptual model of
this study is proposed (see Figure 2.4.1).
R 1
ttachment
Security
H2
Emotional
Support
H
H1
Gender
Interaction requency
R 2, R
Figure 2.4.1 The conceptual model.
13
Self
disclosure
3. Methodology
3.1 Methods
A quantitative method was conducted to provide a generalizable knowledge base to explain the
impact mechanism of perceived emotional support on individuals' online self-disclosure. To
ensure participant diversity and time efficiency, the study used an online questionnaire to
collect information. Figure 3.1.1 presents an overview of research process.
Figure 3.1.1 Research process
3.2 Participants
Respondents were recruited from online communities of Jinan University and RED by random
sampling. Since this study centered on the impact of perceived emotional support from RED on
its user’s self-disclosure, participants selected for the survey were RED users who perceived the
media as a social platform for daily use.
A total of 402 individuals completed the survey but 84 cases were excluded due to the low
quality of answers (see Table 4.1.1). The final data set included 318 RED users, consisting of
179 females (56.3%) and 139 males (43.7%). All of them were from mainland China. The
majority of participants were aged between 18 and 25 years (N = 222, 69.8%), followed by
people from the 26-30 years group (N = 68, 21.4%) and those who were over 30 years (N = 25,
7.9%). Only 3 people were under 18 years old (0.9%). All of the participants have joined in
14
social interactions with other people on RED before, including liking (N = 302, 95%),
favoriting (N = 300, 94.3%), commenting (N = 283, 89%), and notes creations (N = 259, 81%).
3.3 Measurements
The survey questionnaire used a variety of established measures. Overall, it included 9
non-scale items for general information and 33 scale items for specific measured dimensions:
Emotional Support (ES), Attachment Security (AS), and Self-Disclosure (SD). Participants
were asked to complete the questionnaire referring to their interactive experience on RED. In
the current study, Cronbach's alpha of 42 items in total was 0.953. Descriptions and reliabilities
for each scale are reported below.
Emotional Support. The current study assessed perceived emotional support from RED
using the Communication-Based Emotional Support Scale (CBESS) developed by Weber and
Patterson (1996) to specifically measure people’s perceptions of communication-based
emotional support adequacy (see 3.4.1). The CBESS was originally used to measure emotional
support within romantic relationships and has been successfully conducted to measure
individuals' perceived emotional support in different contexts, including online support groups
and other online communities. Wright (2012) applied the CBESS to measure undergraduate
students' perceived emotional support on Facebook and examine how their perceived emotional
support online can impact their trust in others and self-disclosure behaviors. In a study of
relationships between individual Facebook use and emotional support, Rethwish (2018)
conducted the CBESS to observe people’s perceived emotional support from
acebook
networks. Specifically, CBESS consists of 1 items including statements like “He/she is a good
listener when I am upset” and “He/she shows genuine concern for my problems” after the
re-examination for better validation and reached a Cronbach’s alpha of 0.9 in general (Weber
& Patterson, 1996). The current study translated the original English version of CBESS into
Chinese and changed all converse statements into positive items for a more convenient data
analysis. Collectively, the measurement of RED users' perceived emotional support contained
13 items in total through a 5-point Likert scale. Participants were required to rate each
statement to the degree from which they "strongly disagree” (1) to “strongly agree” (5).
15
Table 3.4.1 Items of emotional support measurement
onstruct
Emotional Support
tems
eference
ES01 There are people on RED who help me work through my thoughts
and feelings about ma or life decisions (e.g., career choice).
Weber and Patterson (1996)
ES02 There are people on RED who patiently and sensitively listen to
me let off steam about an outside problem that I am having.
ES0 When I tell other RED users about a problem that I am having,
they seem to be paying attention to me.
ES0 There are people on RED who help me cope with problems
concerning my friends and/or family members.
ES05 There are people on RED who come to me when I am depressed.
ES06 There are people on RED who are a good listener when I am upset.
ES07 There are people on RED who say and do supportive things for me
when I am feeling down.
ES08 When I want to talk to other RED users about what is bothering
me, they seem to be with full concentration.
ES09 There are people on RED who show genuine concern for my
problems.
ES10 There are people on RED who gives me good advice when I ask
for it.
ES11 There are people on RED who makes it very easy to discuss my
personal feelings.
ES12 There are people on RED who listen to my side of the story even if
they think that I am wrong.
ES1 There are people on RED who make an effort to make me feel
better when I am depressed.
Self-Disclosure. The current study adopted a modified version of Self-Disclosure Scales
which was originally developed by Wheeless and Gotz in 1976 (see 3.4.2). Originally,
Wheeless and Gotz’s scale (1976) refers to an individual's self-reported disclosure within
interpersonal relationships and is measured by 21 items ranging from five different dimensions:
the amount of self-disclosure, consciously intended disclosure, honesty-accuracy of disclosure,
positiveness-negativeness of disclosure, and depth-intimacy of disclosure. Although the scale is
beneficial in measuring people’s self-disclosure model within multiple settings, it fails to
involve new patterns of online interactions in an anonymous environment. With the popularity
of social media, individuals tend to establish weak-tie relationships with others and avoid
disclosing personal details deeply and openly. To this end, Park and colleagues (2011) excluded
the dimension of depth-intimacy of disclosure and revised the primary statements into a
17-item scale to measure online users' self-disclosure on Facebook, covering dimensions of
self-disclosure amount, honesty, intent, and positivity. The Cronbach’s alpha of Park’s
instrument was ranged from 0.68 to 0.79. To ensure the validity of data collection, some items
from Park's self-disclosure scale were combined and deleted after translation from English to
Chinese and the pilot test in this study. The Chinese version of the self-disclosure scale
referenced Cao's revised general self-disclosure scale in investigating Chinese students'
16
disclosing behaviors on Microblog (Y. Cao, 2014). Overall, this study's survey retained two to
three items under each dimension and developed an 11-item scale to measure RED users'
self-disclosure. Participants were required to complete the questionnaire by scoring from
"strongly disagree" (1) to "strongly agree" (5). Reverse statements were modified to positive
descriptions.
Table 3.4.2 Items of self-disclosure measurement
onstruct
Self Disclosure
tems
eferences
SD01 I frequently talk about myself on RED.
SD02 I usually write about myself extensively on RED.
SD0
Wheeless and Gotz (1976 ),
. Cao (201 )
I am always honest in my self disclosure on RED.
SD0 I always feel completely sincere when I reveal my own feelings,
emotions, and behaviors on RED.
SD05 I always feel completely sincere when I share my own experiences
on RED.
SD06 When I express my personal feelings on RED, I am always aware
of what I am doing and saying.
SD07 When I reveal my feelings about myself on RED, I consciously
intend to do so.
SD08 When I wish, my self disclosures in RED are always accurate
reflections of who I really am.
SD09 I usually disclose positive things about myself on RED.
SD10 n the whole, my disclosures about myself on RED are more
positive than negative.
SD11 I don t often disclose negative things about myself on RED.
Attachment Security. The current study applied the 9-item Need Satisfaction Scale
developed by La Guardia and the team (2000) to measure the degree of people's attachment
security on RED (see 3.4.3). In line with Self Determination Theory, the need satisfaction scale
involved within-person factors to predict how much people are securely attached to relational
others and is centered on three primary demands of individuals in interpersonal
communications, including needs for autonomy, relatedness, and competence (La Guardia et al.,
2000). It is noted that the more one person's three basic demands are satisfied, the higher level
of attachment security he or she develops. Generally, the Cronbach’s alpha of La Guardia’s
instrument was ranged from 0.91 to 0.97. Referring to empirical study domains, X. Ren (2018)
has adopted the need satisfaction scale to access social media users' emotional attachment to
online interactions. Xiao (2022) also applied the scale to measure sports fitness APP users'
emotional attachment to the medium and further examine how people's attachment predicts
their intention of continuous use. In the current study, participants were presented with a
Chinese version of the 9-item need satisfaction scale along with a modification of reversed
descriptions. Participants were required to score each statement from "strongly disagree" (1) to
17
"strongly agree" (5).
Table 3.4.3 Items of attachment security measurement
onstruct
ttachment Security
tems
eferences
S01 When I am using RED, I feel free to be who I am.
S02 When I am using RED, I have a say in what happens and can
voice my opinion.
S0
When I am using RED, I feel free to be certain ways.
S0
When I am using RED, I feel like a competent person.
La Guardia et al. (2000 ),
iao (2022)
S05 When I am using RED, I often feel adequate and competent.
S06 When I am using RED, I feel very capable and effective.
S07 When I am using RED, I feel loved and cared about.
S08 When I am using RED, I often feel little distance in my
relationship with other users.
S09 When I am using RED, I feel a lot of closeness and intimacy.
3.4 Procedure
Questionnaire distribution and recovery were implemented through an online crowdsourcing
platform Wenjuanxing.com. This platform can generate exclusive link and QR code for each
survey, facilitating the current study to forward and spread the questionnaire through multiple
platforms including WeChat and RED. Based on personal social networks and online
chatgroups, this study distributed the survey with a snowball sampling approach and obtained
massive first-hand data conveniently. Before the formal questionnaire was issued, a preliminary
survey was conducted on the target population. 56 valid responses were gathered and no items
were changed or deleted. Formal data were collected from March 10 to March 15 in 2023.
Participants in this study were asked to complete all survey items after providing informed
consent. If there was a missing answer, participants would not be able to submit the answers.
Past experience using RED was measured first, followed by a battery of questions referring to
participants' perceptions of emotionally supportive messages on RED. In the first four
questions, participants were asked to report the frequency of how often they like, comment,
collect others' notes and create their own media content on RED. The following questions
examined the specific topics (“which of the following topics provide you with emotionally
supportive messages the most”) and strategies (“which of the following expressions describe
the emotionally supportive messages you encounter or receive the best”) that participants
received emotionally supportive messages from, which specifically related to their experience
on RED. These two questions served to establish a general picture of individuals' perceived
18
emotional support online.
Next, participants completed a multidimensional scale by rating the degree to which
statements best described their feelings and behaviors in online interactions. 13 items like
“There are people on RED who are a good listener when I am upset” were applied to measure
people’s perceived emotional support. Another 9 items formed a composite approach for
people’s attachment security, including “When I am using RED, I feel loved and cared about”.
Self-disclosure was measured by 11 items including “I frequently talk about myself on RED”.
After completing the current scale, participants were debriefed and thanked for their
participation.
As part of the follow-up phase of the investigation, ethical considerations and answer
validity problems were discussed. Firstly, respondents' data were only used for academic
purposes and destroyed when the study was completed to ensure anonymity and confidentiality.
Secondly, all of the responses were screened according to two basic criteria: (1) the response
time should not be less than 60 seconds, and (2) all of the options for the survey questions must
not be identical.
3.5 Data Analysis
The first stage of the current study centers on measuring the reliability and validity of the
current questionnaire. Subsequently, descriptive statistics and correlation statistics are applied
to make further insight into different genders' patterns of using RED and to establish a general
picture of emotional support sources. Since the current study used a self-reported online survey
as a single instrument to collect data, Harman’s one-factor test is employed in the following
stage to check the possibility of common method bias and eliminate systematic errors caused by
artificial and latent elements. Next, the current study applied structural equation modeling
(SEM) to test the hypotheses and establish a theoretical model based on three variables
including emotional support, attachment security, and self-disclosure. As a powerful technique
in scientific investigations, SEM is increasingly used to examine and evaluate multivariate
casual relationships through path analysis, providing a convenient method to verify direct and
indirect effects between variables in the present study. Finally, mediation analysis is conducted
to answer the research question through a bootstrap methodology that examines the mediate
effect of attachment security by repeated sampling and 95% confidence intervals.
19
4. Results of Data Analysis
4.1 Descriptive Statistics
A gross sample of 402 RED users was collected from the online survey and none of them
participated in the pretest. After excluding unusable data based on time and quality criteria, the
final sample of the current investigation contained 318 respondents, including 179 female
participants (56.3%) and 139 male participants (43.7%). The average age of the participants
was 26.05 years (SD = 11.60). The composition of the sample's educational background was
79.6% with a bachelor's degree, 11.3% with a college degree or less, and 9.1% with a master's
degree. None of the respondents had a doctorate degree. As far as interaction frequency
(including the act to like, favorite, comment, and content creation) is concerned, 8.5% never or
rarely liked, favorited, commented, or created media content on RED, 41.8% sometimes
engaged in these activities, 40% reported a higher frequency to do so, and 9.7% reported
interacting with others on RED most often. Table 4.1.1 shows the respondents' characteristics
regarding demographic details and online interactions.
With regard to sources of the emotionally supportive message, media content related to
knowledge sharing as well as popular science (M = 2.78) was ranked as the most frequently
seen topic that provide participants with emotional support, followed by topics related to daily
life sharing and product recommendation (M = 2.69), emotion and relationships consulting (M
= 2.27), and hobbies (M = 2.26). Table 4.1.2 shows the ranking of each topic by their average
score. Nevertheless, participants also rated on emotional support strategy according to how
often did they receive emotional support through six types of expressions (see Table 4.1.3).
These various expressions represented six different emotional supportive strategies from S. Liu
et al.'s (2021) Emotional Support Conversation Framework. In this case, reflecting on others'
feelings (M = 4.05), responding with self-disclosure (M = 4.00), and providing affirmation and
assurance (M = 3.60) were the top 3 most frequently used strategies to convey emotional
support on RED. Table 4.1.3 presents the ranking of each strategy by its average score.
20
Table 4.1.1 Descriptive statistics of the participant demographic information
ate ory
tems
um er
ender
ale
1 9
emale
179
.7
56.
e
18
0.9
18 25
222
69.8
26 0
68
21.
0
25
7.9
6
11.
Bachelor degree
25
79.6
aster degree
29
9.1
0
0
27
8.5
Education
College degree or less
Dotorate
nteraction requency
ever or rarely
Sometimes
ften
lways
ote s
umber of respondents
1
1.8
127
0
1
9.7
18
Table 4.1.2 Frequency ranking of emotional support sources (topics)
tems
um er for
st
nowledge related
um er for
nd
um er for
rd
um er for
t
A era e Score
an in
116
8
52
67
2.78
1
Sharing and recommendation
75
105
10
5
2.69
2
Emotions and relations
81
6
69
122
2.27
9
9
2.26
Hobbies
ote s
6
umber of respondents
8
18
Table 4.1.3 Frequency ranking of emotional support strategies (expressions)
tems
um er for
st
um er for
nd
um er for
rd
um er for
t
um er for
t
A era e Score
an in
Reflection of feelings
67
61
8
51
Self disclosure
60
77
57
71
59
65
60
56
8
0
52
59
6
57
56
7
77
.17
5
26
28
9
125
2.87
6
ffirmation and Reassurance
uestions
59
Guiding or others
Restatement or Parapharasing
ote s
umber of respondents
7
51
9
18
21
9
um er for
t
17
.05
1
19
.00
2
.60
. 1
4.2 Measurement Model
A reliability test was employed to examine the credibility of the completed scale and each
construct in the present study. Cronbach's alpha of the 33-item measurement is 0.953
(emotional support = 0.939, attachment security = 0.913, self-disclosure = 0.934), showing
good consistency and stability of this instrument (see Table 4.2.1).
Table 4.2.1 Construct reliability
Confirmatory factor analysis (CFA) was applied to test measurement accuracy by
convergent validity as well as discriminant validity. Convergent validity was measured by
average variance extracted (AVE) and composite reliability (CR) (see Table 4.2.2). In general,
AVE values of each construct are greater than a recommended level of 0.5 and all CR values are
higher than a marginal value of 0.7, indicating that the current instrument has satisfactory
reliability and convergence validity. In addition, all factor loadings from CFA results are
significant in the t-test and well above 0.60, providing strong evidence of good convergent
validity. Discriminant validity was examined through the inter-construct correlations by
comparing the square root of AVE for each dimension with a correlation of latent elements.
Table 4.2.3 illustrates that all AVEs are higher than the maximum correlation coefficient
between factors, which is supported for discriminant validity.
4.3 Common Method Variance
Since the data was collected from a single survey measurement, there was potential for
common method bias in the present study. Common method bias can exist when independent
and dependent variables are measured by one survey and through the same response method. To
this end, Harman’s single factor test was applied to eliminate this systematic error. The results
indicate that the first factor with an eigenvalue greater than 1 explains 40.2% of the covariance
in the current study, and is lower than the threshold of 50% (Hair et al., 1988), providing
evidence of the absence of a common method bias.
22
Table 4.2.2 Results of confirmatory factor analysis
onstructs
ndicators
Emotional support
ttachment Security
Self Disclosure
ote s CR
oadin s
ES01
0.71
ES02
0.8 2
ES0
0.72
ES0
0.716
ES05
0.7 5
ES06
0.759
ES07
0.71
ES08
0.7 6
ES09
0.697
ES10
0.681
ES11
0.7 7
ES12
0.77
ES1
0.751
S01
0.69
S02
0.818
S0
0.695
S0
0.72
S05
0.785
S06
0.768
S07
0.72
S08
0.679
S09
0.721
SD01
0.788
SD02
0.8 6
SD0
0.7
SD0
0.727
SD05
0.725
SD06
0.799
SD07
0.687
SD08
0.8 5
SD09
0.705
SD10
0.719
SD11
0.7
Composite Reliability
E
A E
0.9
0.5 8
0.91
0.5
0.9 7
0.579
verage ariance Extracted.
23
p
0.001
Table 4.2.3 Inter-construct correlations
4.4 Structural Model
After the preliminary steps of data analysis (measurement model and common method variance)
were carried out, structural equation modeling (SEM) was employed to test the proposed
hypothesized relationships through AMOS 25.0. As one of the most popular methods in
quantitative investigations, SEM is capable of providing a precise evaluation of measurement
errors, assessing latent variables through observed variables, and conducting a model test on the
proposed structure in which data fit can be evaluated (Kaplan, 2008).
Results of structural equation modeling including model fit as well as path estimates are
shown in Figure 4.4.1. In general, the structural model obtains acceptable model fit (X2 =
649.173, df = 492, p < 0.001, X2/df = 1.320, RMSEA = 0.032, CFI = 0.975, NFI = 0.906, TLI =
0.974, IFI = 0.976), indicating that it can be processed through path analysis. As shown in
Figure 4.4.1, RED users' perceived emotional support online accounts for 33% of the variance
in their level of attachment security (R2 = 0.33) and explains 37% of the variance together with
the level of secure attachment in the extent of self-disclosure (R2 = 0.37). Both of the model fits
(R2) are greater than 0.33 which indicates that the proposed structural model achieves an
acceptable level of explanatory power.
R
0.
ttachment
Security
0.57
Emotional
Support
0. 20
0.26
Self
disclosure
R
ote s
0.0 2, C I
18,
0.975,
p 0.001 2 6 9.17 , df
I 0.906, TLI 0.97 , I I
92, p
0.976
0.001,
2/df
0. 7
1. 20, R SE
Figure 4.4.1 Results of path analysis of the proposed structural model
24
Table 4.4.1 indicates the path estimates and significance values of each proposed
hypothesis in the structural model. As illustrated in the table, standardized coefficients of path
estimates indicate a positive and significant relationship between perceived emotional support
and self-disclosure (β= 0.263, t = 4.079, p < 0.001), which provides strong evidence for
Hypothesis 1. Perceived emotional support is also found to be positively related to the level of
attachment security (β= 0.574, t = 8.282, p < 0.001), thus supporting the proposed Hypothesis 2.
In addition, the relationship between the level of attachment security and self-disclosure is
established (β= 0.420, t = 6.044, p < 0.001), confirming the proposed Hypothesis 3. Collectively,
these findings demonstrated that people's perceived emotional support on RED can not only
lead to their greater desire to self-disclose but also a higher level of attachment security while
interacting with each other.
Table 4.4.1 Path estimates of the proposed structural model
elations ips
Standardi ed oefficient
H1. Emotional Support
Self Disclosure
alue
ypot esi es
0.26
.079
Supported
H2. Emotional Support
ttachment Security
0.57
8.282
Supported
H . ttachment Security
Self Disclosure
0. 20
6.0
Supported
ote s
p
0.001
4.5 Mediation Analysis
Mediation analysis examined whether the proposed independent variable affects the dependent
variable directly or indirectly (Rucker et al., 2011). In the present study, perceived emotional
support is modeled as the independent variable of people's self-disclosure online. Based on the
theoretical review, the level of attachment security is involved as a proposed mediator within
the relationship between perceived emotional support and self-disclosure. This study referred to
Baron and
enny’s (1986) guidelines as well as Preacher and Hayes’s (2008) bootstrap
approach to test the mediating effect of attachment security and further examine its
significance.
Regression analysis was conducted first to test whether the mediating effect is complete or
partial. According to Baron and Kenny (1986), three conditions should be met in the results to
support mediation: (1) the independent variable significantly impacts the dependent variable in
the first regression analysis; (2) the independent variable significantly impacts the mediator in
25
the second regression analysis; (3) the mediator significantly impacts the dependent variable in
the third regression analysis, in which both independent variable and mediator are entered as
predictors. In this case, completed mediation is supported if all conditions are met and the
independent variable no longer affects the dependent variable when the mediator is controlled.
Partial mediation presents if the independent variable’s influence on the dependent variable is
reduced after the mediator is controlled (Baron and Kenny, 1986). Table 4.5.1 presents the
results of the mediation analysis to support each condition. As shown, the direct effect without
the mediator established a significant correlation between emotional support and
self-disclosure (β= 0.520, p < 0.001). When the mediator is involved, the direct effect of
emotional support on self-disclosure (β= 0.292, p < 0.001) sees a decrease, thus providing
evidence of partial mediation.
Table 4.5.1 Results of mediation analysis
elations ips
Emotional Support
ttachment
Security Self Disclosure
ote s
p
.001 95
Direct Effect
it out Mediator
Direct Effect it
Mediator
ndirect Effect
0.520
0.292
(0.175 to 0. 08)
0.228
(0.158 to 0. 19)
bootstrap confidence in parentheses, CI
Mediation
ypot eses
Partially supported
confidence interval.
Bootstrapping method was employed to assess the significance of mediating effect in the
next stage. In line with Preacher and Hayes’s (2008), the current study applied 5,000 bootstrap
iterations and 95% confidence intervals as the measurement. If the confidence interval excludes
zero, the indirect effect is significant. Moreover, if the direct effect of the mediator is significant
at the same time, the mediation is not completed. As shown in Table 4.5.1, attachment security
significantly and partially mediates the path from emotional support to self-disclosure (β=
0.228, p < 0.001, CI = 0.158 to 0.319).
4.6 Impact of Interaction Frequency and Gender Differences
A Pearson correlation coefficient was computed to assess the linear relationship between
people’s online interaction frequency, their perception of emotional support, attachment
security, and self-disclosure. As presented in Table 4.6.1, the frequency of people participating
in online interactions on RED (like, favorite, comment, and content creation) presents a small
positive correlation with both perceived emotional support (r = 0.194, p < 0.001) and
self-disclosure (r = 0.190, p < 0.001). However, no significant relationship is found between the
26
frequency of interaction and attachment security (r = 0.043, p > 0.1).
Table 4.6.1 Results of the Pearson correlation
Interaction requency
Emotional Support
ttachment Security
Self Disclosure
ote s
18,
M
SD
2.85
0.78
.5
0.71
0.19
.71
0.65
0.0
. 8
0.77
0.19
ean, SD
Interaction requency
(0. 8)
Standard Deviation,
Emotional Support
Self Disclosure
0.5 1
0. 75
p
ttachment Security
0.5 5
0.001
Table 4.6.2 Results of the independent-sample t-test
Males
M
Emotional Support
ttachment Security
Self Disclosure
ote s
18,
emales
SD
M
SD
test
.77
0.71
. 5
0.65
5.517
.9
0.69
.5
0.56
5.5 5
.79
0.71
.25
0.7
6.600
ean, SD
Standard Deviation,
p
0.001
Gender differences regarding perceived emotional support, attachment security, and
self-disclosure were examined by independent-sample t-test. One difference was found in terms
of emotional support, as males reported emotional support from other RED users as more
adequate than did females (t = 5.517, p < 0.001). With respect to attachment security, men
reported a higher level of attachment security compared to women (t = 5.545, p < 0.001).
Referring to self-disclosure, the extent to which men self-disclose on RED is greater than that
of females (t = 6.600, p < 0.001).
5. Findings and Discussions
The constantly updating social media has brought about new changes in people's online
behaviors and triggered increasing academic attention to exploring the motives that may
contribute to the change. In this case, emotional support as a psychological term is introduced to
communication studies and shows substantial power to predict individuals' online behaviors.
Despite a growing body of literature studying the causes and possible impact of emotional
support, less is known about how emotional support from social media can affect people's
self-disclosure behaviors online. Therefore, the current study centers on the role of emotional
support on Chinese social media RED in fostering people to participate in online interactions
27
and self-disclosure. In general, this study aims to generalize the characteristics of emotional
support on RED and examine the impact mechanism of social media emotional support on RED
users’ self-disclosure. A research model involving online emotional support, attachment
security, and self-disclosure has been proposed and evaluated.
5.1 Findings
The table below shows an overview of hypothesis verification (Table 5.1.1). As can be seen
from the results, this study indicates that (1) people's perceived emotional support online has a
significant positive effect on their self-disclosure extent; (2) people's perceived emotional
support has a positive effect on their attachment security, which in turn affects their
self-disclosing behaviors; (3) the level of attachment security plays a partial mediating role in
the relationship between perceived emotional support and self-disclosure on social media; (4)
people's interaction frequency is significantly related to the perception of emotional support and
the general extent of self-disclosure; (5) males show higher scores in emotional support,
attachment security, and self-disclosure than females.
Table 5.1.1 Results of hypothesis verification
5.2 Interpretation of Findings
5.2.1 Emotional Support on RED
The present study investigated sources of emotionally supportive messages on RED and its
specific messaging strategies. In general, the emotional support that RED users received is
mainly from popular science sharing and delivered through a reflection of feelings like “I
understand you” and so forth.
Regarding support sources, participants reported that they received emotional support
mostly from knowledge-related topics like job seeking and school enrollment, followed by
daily sharing and emotional counseling. In contrast to expectations, RED users elicit care and
28
understanding of content related to close relationships the least compared to the other two types.
Several possible explanations may account for the results. First, the large number of contents
related to shopping advice, life skills, and other useful tips makes it easier for RED users to get
access to emotional assistance under those knowledge-based topics. As a platform originating
from a consumer community, RED is commonly viewed as a unique search engine by its users
to search for assonance from those who encounter the same troubles. In addition, the trait of
Chinese people as conservative and implicative also hold back RED users to involve in others'
relationship problems. For some Chinese media users, emotional issues should only be
discussed privately with close friends or families, resulting in their avoidance of commenting
on other people's emotional experiences or sharing their real thoughts publicly on social media.
More importantly, exchanging emotional support under more neutral topics reduces the risk of
establishing close relationships and maintaining a weak-tie connection with others online,
Concerning support strategies, the results of the study indicate that most RED users
provide emotional assistance through the reflection of others' feelings, followed by the
strategies of self-disclosure and affirmation. It seems that conveying understanding and
agreement directly is the most convenient way for one person to show goodwill while
preventing information leakage. Unlike this approach, the self-disclosure strategy is less
popular among media users since it requires people to tell their stories against human nature to
withhold real thoughts in front of a stranger. However, its irreplaceable power in expressing
sincerity and sharing companionship still makes it the top 2 choices for people to exchange
emotional support in a nonverbal social media context.
5.2.2 The Role of Social Media Emotional Support
The present study discussed the role of emotional support in both individuals’ self-disclosure as
well as the enhancement of attachment security in online communications. In line with previous
works on emotional support (Y. Lin & Chu, 2021; Weber et al., 2004; Zhou, 2017), the findings
of this study confirmed a significant positive relationship between people’s perceived
emotional support and their self-disclosure on RED. More specifically, it suggests that if one
person perceives himself or herself as being adequately emotionally supported, he or she will
become more willing to disclose personal stories deeper and with higher frequency. According
to the Social Exchange Theory and the Social Penetration Theory, emotional support from
29
interactive partners can encourage one person to reveal more about the self by promoting
intimacy and trust. This positive impact of emotional support remains strong within online
communications through social media. Prior studies have reported that emotional support from
interactive partners online is as effective as that from face-to-face communication to
establishing trust and intimacy between unfamiliar people and fostering online self-disclosure
(Taddei & Contena, 2013; Y. Lin & Chu, 2021; Zhou, 2017). As Y. Lin and Chu (2021) yielded
in the study of Facebook self-disclosure, social media users can be facilitated by a sense of
emotional support to engage in online self-disclosing behaviors with meaningful breath and
depth. It is also proved that social media emotional support can play an important role in
enhancing self-disclosure development. Beyond, since online emotional support can be
delivered through self-disclosure, people may be motivated to reveal their details reciprocally
as a response to others' self-disclosive emotional support.
The results of this study also confirm a positive correlation between social media
emotional support and the degree of individuals’ attachment security. To be more specific, it is
suggested that the more one persona feels emotionally supported online, the stronger he or she
is securely attached to online interactions. In accordance with the present literature, this finding
is consistent with previous researchers which demonstrated the significant role of emotional
support in promoting attachment (K. Huang et al., 2010; Hunter et al., 2006; X. Ren, 2018). In a
study of online support groups, Hunter et al. (2006) indicated that emotional support from
online group members can bring comfort and attachment. X. Ren (2018) further claimed that a
high frequency of emotional support transformation has a positive effect on enhancing overall
satisfaction with the need for autonomy, relatedness, and competence, thus forming strong
emotional attachments. In the case of RED, emotional support provided by other users can
satisfy all three basic needs (autonomy, relatedness, and competence) respectively through likes,
favorites, and comments. In general, this finding not only verifies the positive impact of
emotional support on the secure attachment but also explains the reason why people show a
strong reliance on social media today. First, seeking emotional support on social media can
gather massive responses from others in a relatively short time, which is effective and efficient.
Secondly, people can easily connect to those who share similar interests and personalities with
the powerful social media network and get access to more emotional support messages. Further,
30
since social media provides people with a weak-tied anonymous environment, individuals can
maintain a comfortable emotional distance from others while interacting frequently for support
and understanding (Colineau & Paris, 2010). In this case, people can realize their social goals
while avoiding the responsibility of maintaining a relationship, thus leading to a sense of
security.
5.2.3 Attachment Security and Its Mediation Effect
In the current study, the relationship between attachment security and self-disclosure was
further examined. As stated by prior works (Keelan et al., 1998; Wei et al., 2005; C. Huang et
al., 2019; Mikulincer &
achshon, 1991), the results of this investigation agree that people’s
attachment security is positively and significantly related to their self-disclosure on social
media. Referring to the adult attachment theory, people can be divided into four groups based
on different scores on attachment anxiety and avoidance. As explained in the literature review,
people who are anxiously attached are characterized by a preoccupation with connection
maintenance whereas avoidant people tend to refuse to form close relationships with others. In
contrast to these two types, people with a considerable level of attachment security are more
likely to positively view themselves as lovable and others as trustworthy (Smith et al., 1999;
Oldmeadow et al., 2013). C. Huang et al. (2019) claimed that people with a higher level of
attachment security show a stronger desire to develop relationships and share personal stories
with partners. This positive relationship between attachment security and self-disclosure not
only exists in face-to-face communications but is confirmed within interactions on social media
(Grabill & Kerns, 2000; Keelan et al., 1998). Compared to attachment anxiety and avoidance,
attachment-secure people feel more comfortable and open to disclosing the self online (Wei et
al., 2005).
Although the finding in the present study agrees with most works to date, some researchers
highlighted a negative relationship between attachment security and self-disclosing behaviors.
According to Aharony (2016), people with insecure attachment styles are more likely to reveal
personal information on Facebook. A possible explanation for these contradictory results may
be the variance in platform atmosphere, which also predict an individual’s willingness to share
personal information with others or not. It is reasonable that social media users will tell their
stories actively to the public if they perceive the general atmosphere of the platform as friendly
31
and respectful. According to Shan and Yi (2022), a harmonious and fair communicative
environment can influence the process of people building mental connections with the platform
and further affect their intention to disclose personal information. Another potential reason for
the controversy may relate to people’s traits, for example, the Big ive Personality Types.
ccording to Hollenbaugh and
erris (201 ), individuals’ personality is an important
contributor to their disclosure on social media, together with the effect of attachment.
Specifically, extravert persons are found to disclose the self in greater amounts and be more
likely to form secure attachments within online communications.
Compared with previous research in figuring how emotional support can increase
attachment security (Hunter et al., 2006; K. Huang et al., 2010) and past examinations in
predicting individuals’ self-disclosure through secure attachment (Mikulincer & Nachshon,
1991; Grabill & Kerns, 2000), the present study integrated these findings as to the whole and
further explored the role of attachment security within the path from emotional support to
self-disclosure. Accordingly, the results of the present investigation suggest that attachment
security mediates the correlation between emotional support and online self-disclosure,
verifying prior studies’ ideas of emotional elements indirectly affecting people’s media use
through attachment (Zhang & Chen, 2022; C. Huang et al., 2019). As Zhang and Chen (2022)
reported in the study of social media users' content-sharing behaviors, recognition, and
encouragement from other users can enhance people's attachment security by fulfilling basic
needs and predict a stronger desire for them to share media content. On the other hand, the
finding of attachment security's mediator role also agrees with the concept of social media
attachment. Specifically, a secure attachment to social media may appear if one person is
assured by others and able to increase their connectedness and presence by publishing media
content through the medium (Altuwairiqi et al., 2019). Referring to RED, this process might be
triggered by other users responding to one person's comment or RED notes with emotionally
supportive messages and ending in the motivation to tell personal stories in return. Those who
perceive themselves as adequately emotionally supported on RED are more likely to feel
securely attached online and disclose information more no matter in depth or breath. Overall,
the verification of attachment security as a mediator highlights the necessity of employing
irrational factors to predict one person’s self-disclosure and potential media use.
32
5.2.4 Influence of Interaction Frequency
Since media use is associated with people’s perception of emotional support and can predict
their future media use (Shensa et al., 2020; Lee et al., 2013; Lee et al., 2013; Lin et al., 2016), it
is reasonable to examine how the frequency of people to participate in online interactions can
influence their recognition of perceived emotional support and self-disclosure. In this study,
interaction frequency is measured by the number of times that people like, favorite, comment,
and create media content on RED.
In line with a prior study (Shensa et al., 2016), people’s interaction frequency on RED was
found to be associated with their perceived emotional support and self-disclosure. It is evident
that the more people interact with others online, the more they feel emotionally supported and
the more they are willing to disclose information. According to X. Ren (2018), interactions
among social media users can facilitate shared emotional experiences and create a sense of
belonging which strengthen people's desire for self-expression and sharing personal stories.
Traditionally, humans as social animals tend to establish relationships with the external world
through communication, in which interacting with verbal and nonverbal messages is a crucial
means. In the context of social media, people can get desirable information and get to know
each other through frequent interactions, which in turn enhances their perceived level of
closeness to strangers. Compared with those who rarely participate in online interactions,
people with a higher frequency of communication through likes, favorites, or comments
generate stronger feelings of being understood, empathy, and affirmation, thus perceiving
emotional support from social media as more adequate.
In contrast to the positive correlations between interaction frequency, emotional support,
and self-disclosure, the times that people socialize with each other on RED showed no
significant association with their degree of attachment security. A possible explanation for this
result might be that frequent interactions can only explain a greater number of online
communications but fail to ensure good quality of them. To be more specific, one person may
like or favorite others' media content many times but have never commented on or produced
any posts online, which leads to a lack of two-way interactions and failure to meet three basic
needs. In this case, interaction frequency has no obvious impact on the degree of individuals'
attachment security.
33
5.2.5 The Gender Matters
Genders as a crucial demographic factor are commonly discussed within communication
literature. Consistent with previous research (Nelson & Quick, 1991; Cosby, 1973), the results
of the current study reported a gender variance in perceived emotional support, attachment
security, and self-disclosure. Beyond expectations, male participants who completed the scale
reported a higher degree of feeling emotionally supported by others and being securely attached
during interactions. A possible explanation for these results may be a discrepancy in emotional
support received in offline social life. Compared to females, males receive relatively less
emotional support from daily communications due to a conventional view in which men
seeking comfort or sympathy is considered to be weak. In this case, male users may become
more sensitive and suggestible to emotional support than female users and may report a greater
amount of perceived emotional support on RED. Another possible explanation for the
covariances lies in the privileges that men enjoy in daily life. Since men are empowered with
priorities in society for a long time, they tend to feel less uncertainty in the process of growing
up and be securely attached to others in relationships, which also ends in higher attachment
security during social media interactions.
It is also surprising to find that male RED users have a greater desire to tell personal stories
and preferences than their counterparts. Contradict to previous studies indicating females are
the ones to disclose themselves more (Snell et al., 1988), men in the current study show a
stronger willingness to release private details and share real thoughts on multiple topics. This
result may be explained by the fact that males are more narcissistic and used to presenting
themselves to others, leading to a higher extent of self-disclosure online (Stokes et al., 1980;
Hollenbaugh & Ferris, 2014). In addition, a social tendency of gender equality in which males
are encouraged to oppose traditional disciplines of manliness and express emotional demands
freely may also contribute to this finding.
5.3 Implications
5.3.1 Theoretical Contributions
Theoretically, this study establishes a new self-disclosure model by integrating psychological
factors to explore how social media emotional support can influence users’ extent to disclose
intimate information about the self on social media. Specifically, the current study synthesizes
34
past work’s conclusions on the role of emotional assistance and examines its indirect effect on
individuals’ self-disclosure via attachment security. According to the results, it is noted that
irrational motives (e.g., emotional support) are positively correlated with people's activities on
social media.
This study also revalidates the relationships among online emotional support, attachment,
and self-disclosure in a Chinese setting. Prior works have demonstrated that emotional support
can enhance relationship quality among online users, foster their intention to continuously use
the medium, and encourage them to self-disclosing the self (Liang et al, 2011; Li, 2017; Y. Lin
& Chu, 2021). However, most of the emotional support literature centered on Western
applications (e.g., Facebook and Instagram); less is known about Chinese social media like
RED and examines the effect of emotional support in another cultural background. In this case,
the results of this study may enrich the research on emotional support by discussing the unique
patterns of Chinese media users and drawing a more general conclusion about the correlation
between emotional support on disclosive behaviors.
With respect to the implementation of attachment security, the findings extend the
application of attachment theory as well as La Guardia's A-R-C model (2000) in explaining the
communicative phenomenon. In previous research, the A-R-C model was only used to
represent individuals' general emotional attachment toward the platform in examinations of
continued use and information-sharing behaviors (X. Ren, 2018; Zhang & Chen, 2022). In this
study, participants were surveyed regarding their overall satisfaction with three basic needs
(autonomy, relatedness, competence) to provide an overview of how much they can feel
securely attached to the facilitation of emotional support during online interactions. Taking
advantage of the powerful online network, people can conveniently connect with those who
share similar interests and are more likely to believe that only relationships on social media can
provide them with favorable sympathy, respect, or patience, which strengthens their attachment
to social media (Yue, 2022).
5.3.2 Practical Implications
In terms of practical implications, the findings of this study suggest that emotional support from
social media plays a vital role in explaining new changes in people's interpersonal
communications during post-pandemic times and provides further insights for society, the
35
general public, as well as individuals.
Concerning society's benefits, the current study notices the strong power of social media
emotional support in changing the online climate and promoting active mass communication.
By encouraging emotional support exchanges in online interactions, mainstream media can
motivate the passion of the public and generate a sense of resonance as well as belonging.
Additionally, since emotional support is positively related to people’s self-disclosure,
mainstream media can also facilitate a free-flowing discussion by offering adequate emotional
support to the people.
In terms of the general public, the findings of this study note that social media emotional
support not only activates people’s participation in online activities but serves as a significant
predictor of individuals' increasing social media addiction. With the advantages of quantity and
efficiency, emotional support from other media users can satisfy people's multiple social needs
better compared to that offline partners. By providing a perceived feeling of understanding and
comfort, online emotional support helps realize individuals' need for belonging, esteem as well
as self-actualization, thus encouraging them to express the self confidently on social media. On
the other hand, the positive relationship between emotional support and attachment security
also reflects on the fact about lack of emotional assistance in offline interactions. In this case,
people are forced to seek accompany from online networks which in turn strengthens their
reliance and trust on social media.
This study also highlights the irreplaceable value of online emotional support for younger
generations today. Growing up with the development of the internet, young people are used to
spending more effort in maintaining online relationships and view social media as a tree hole to
pour out troubles. In this case, online emotional support has long been an integral part of their
social lives to receive desirable responses. Moreover, it also provided young people, who were
greatly affected by the only-child policy, with abundant companionship to reduce the loneliness
they felt in real life.
Apart from the above implications, the study also offers valuable information for both
social media users and operators. On the one hand, the results suggest that media users should
improve their media intimacy while benefiting from online emotional support and participating
in online interactions. Since social media emotional support can also promote people's
36
attachment to the platform, users should also be aware of its harm to exacerbate the addiction to
the virtual world and separate them from real life. On the other hand, the findings of this study
also offer some advice for media operators to enhance individuals' enthusiasm in public
discussion as well as user-generated content creation by making good use of the correlation
between emotional support and self-disclosure.
5.4 Limitations and Future Research
5.4.1 Limitations in Research Design
The results of this study should be interpreted with caution for multiple reasons. First, most
respondents of the present investigation were from the younger generation. Although the ratio
of males to females is relatively even, the overall sample is not as representative as designed.
Compared to the older generations, this group of people is grown up with the development of
the internet, which contributes to their greater desire to seek emotional support and self-disclose
on social media. Future studies should attempt to recruit a more comprehensive sample
consisting of people from multiple age groups to test the general effect of perceived emotional
support on self-disclosure. Second, the measurement of the present work may have a few
discrepancies with the original English scales due to linguistic differences. In this case, future
studies should invite communication specialists in the preliminary stage and carefully adjust the
scales to ensure that participants can understand the actual meaning of each item and complete
the questionnaire. Third, the single self-reported instrument in the current study may result in a
potential side effect of massive subjective factors such as bias and errors. Different groups of
people (e.g., males and females, adolescents and adults) may interpret the survey items in
different ways and with different understanding levels. People’s responses may also be affected
by the order of survey items and their characteristics. In future investigations, it might be
possible to use a combined method of questionnaires and situational experiments to conduct a
more precise measurement of people's attitudes toward certain variables.
5.4.2 Prospects for Future Research
Apart from the inadequacies in research design, there are several questions thrown up in need of
further investigation. Since this study has only examined the effect of perceived emotional
support on self-disclosure as well as attachment security, some potential impact factors may be
ignored within the current research model. or example, people’s perceived emotional support
37
may also enhance their social media self-efficacy to achieve desirable social goals online and
thus strengthen the willingness to disclose while indirectly affecting self-disclosure via
attachment security. In this case, more research should be undertaken to examine whether there
is another potential path from emotional support to disclosing behaviors. Besides, it is also
suggested to involve prior experiences as a control variable in identifying the differences
between new and existing users on the perception of social media emotional support as well as
the general extent of self-disclosure.
6. Conclusion
The current study extends research about online emotional support and social media
self-disclosure on a Chinese social media RED as it has integrated attachment security as an
irrational factor to explore the impact path from perceived emotional support to online
self-disclosure. The study proposed that the former element would affect the latter directly and
the relationship between these two would be mediated by the individual's secure attachment.
Results of the investigation suggested that (1) people's perceived emotional support on RED is
positively related to their extent of self-disclosure; (2) people's perceived emotional support on
RED is positively related to the level of attachment security; (3) the level of attachment security
is positively related to people's general extent of self-disclosure; (4) attachment security
partially mediates the relationship between emotional support and self-disclosure on RED.
These findings confirmed prior studies’ identifying a significant positive correlation
between emotional support and self-disclosing behaviors and highlighted that adult attachment
plays an important role in the influence of emotional factors on individual media use. More
specifically, if people are exposed to adequate emotional support and feel comfortable on social
media, they may develop a higher level of attachment security while interacting with others,
therefore in turn promoting their desire to disclose the self more honestly and frequently.
Furthermore, the study presented an overview of emotional supportive messages on RED and
reported that knowledge-based topics and lifestyle sharing are better at gathering emotional
support from others whereas emotional topics may hinder people's impulsion to exchange
support related to actual feelings. Additionally, expressions with greater reciprocity such as
reflection of feelings and self-disclosure are the most frequently used strategies for people to
38
offer emotional support compared to other four types.
However, this study also has certain limitations in both research procedures and design.
First, it fails to recruit as multiple participants as possible during data collection. Since most
respondents are from younger generations, different patterns of media use and perceptions
toward online emotional support from older age groups may be neglected. Second, data from
the present questionnaire in this study may not be as accurate as expected due to a discrepancy
between the original English scales and the modified Chinese version. Although this instrument
achieved favorable reliability and validity, future studies should ask communication specialists
for better suggestions on item setting. Third, this study did not involve objective factors while
conducting the research. All data were collected from a single survey instrument by participants
self-reporting their experiences and first impressions on certain items. Although the approach is
useful for quickly gathering a large amount of information from samples, it can also be biased
and prone to errors. Forth, the present study only considered the direct effect of emotional
support on attachment security which may ignore certain moderating or mediating factors
within the path. Further, it also failed to include prior experience of using RED as a control
variable into the research model and did not identify a potential variance in perceived emotional
support, attachment security, and self-disclosure between new and existing RED users. In this
case, more researches are needed to explore other potential factors within the impact
mechanism of emotional support on self-disclosure. Collectively, future studies should not only
target the sample carefully and thoroughly but apply a combined method to study the
relationship between emotional factors and individual media use. It is also important to
incorporate more variables while investigating the effect of emotional support in Chinese social
media settings to cope with a more complex and changeable media environment.
39
Acknowledgements
I would like to express my deepest appreciation to my supervisor for her professional and
timely help with this thesis. As an experienced professor, she can always hit the right nail on the
head with mistakes in my research and offer effective guidance. I would also like to extend my
sincere gratitude to my friends and family for being by my side whenever I'm lost, down, or
tired. My last and most important thank you is to myself for not giving up. Without the
persistence and pain of the past, I could not finish this thesis and bring my four-year journey at
Jinan University to a satisfactory end.
Once again, thanks to all those who have taught me, helped me, encouraged me, and guided
me over the past four years.
40
Appendix
General Information
1. Have you liked others’ notes before?
Never, Rarely, Sometimes, Often, Always
2. Have you favorited others’ notes before?
Never, Rarely, Sometimes, Often, Always
. Have you commented on others’ notes before?
Never, Rarely, Sometimes, Often, Always
4. Have you posted notes on RED before?
Never, Rarely, Sometimes, Often, Always
Descriptions below may relate to your experience while interacting with other people on RED.
Please indicate the degree to which the following statements describe your experience by
marking whether you (5) strongly agree, (4) agree, (3) are undecided, (2) disagree, (1) strongly
disagree
1. There are people on RED who help me work through my thoughts and feelings about major
life decisions (e.g., career choice)
2. There are people on RED who patiently and sensitively listen to me “let off steam” about an
outside problem that I am having
3. When I tell other RED users about a problem that I am having, they seem to be paying
attention to me.
4. There are people on RED who help me cope with problems concerning my friends and/or
family members
5. There are people on RED who come to me when I am depressed.
6. There are people on RED who are a good listener when I am upset
7. There are people on RED who say and do supportive things for me when I am feeling down
8. When I want to talk to other RED users about what is bothering me, they seem to be with full
concentration.
9. There are people on RED who show genuine concern for my problems
41
10. There are people on RED who gives me good advice when I ask for it
11. There are people on RED who makes it very easy to discuss my personal feelings
12. There are people on RED who listen to my side of the story even if they think that I am
wrong
13. There are people on RED who make an effort to make me feel better when I am depressed
Descriptions below may relate to your feelings while using RED. Please indicate the degree to
which the following statements describe your experience by marking whether you (5) strongly
agree, (4) agree, (3) are undecided, (2) disagree, (1) strongly disagree.
1. When I am using RED, I feel free to be who I am.
2. When I am using RED, I have a say in what happens and can voice my opinion.
3. When I am using RED, I feel free to be certain ways.
4. When I am using RED, I feel like a competent person.
5. When I am using RED, I often feel adequate and competent.
6. When I am using RED, I feel very capable and effective.
7. When I am using RED, I feel loved and cared about.
8. When I am using RED, I often feel little distance in my relationship with other users.
9. When I am using RED, I feel a lot of closeness and intimacy.
Descriptions below may relate to your performance while interacting with other people on RED.
Please indicate the degree to which the following statements describe your experience by
marking whether you (5) strongly agree, (4) agree, (3) are undecided, (2) disagree, (1) strongly
disagree.
1. I frequently talk about myself on RED
2. I usually write about myself extensively on RED
3. I am always honest in my self-disclosure on RED.
4. I always feel completely sincere when I reveal my own feelings, emotions, and behaviors on
RED.
5. I always feel completely sincere when I share my own experiences on RED.
6. When I express my personal feelings on RED, I am always aware of what I am doing and
42
saying.
7. When I reveal my feelings about myself on RED, I consciously intend to do so.
8. When I wish, my self-disclosures in RED are always accurate reflections of who I really am.
9. I usually disclose positive things about myself on RED.
10. On the whole, my disclosures about myself on RED are more positive than negative.
11. I don’t often disclose negative things about myself on RED.
Basic Information
1. Your Gender：
male, female
2. Your Age (years):
<18，18-25，26-30，>30
3. Your Education background:
College or less, bachelor degree, master degree, doctorate
43
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