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Greater social support is predictive of lower depression and higher quality of life (QOL). However, the way in which social support is provided has changed greatly with the expanding role of social networking sites (e.g., Facebook). While there are numerous anecdotal accounts of the benefits of Facebook-based social support, little empirical evidence exists to support these assertions, and there are no empirically validated measures designed to assess social support provided via this unique social networking medium. This study sought to develop an empirically sound measure of Facebook-based social support (Facebook Measure of Social Support [FMSS]) and to assess how this new measure relates to previously established measures of support and two outcome variables: depression and QOL. Following exploratory factor analysis, the FMSS was determined to assess four factors of social support on Facebook (Perceived, Emotional, Negative, Received/Instrumental). The Negative Support factor on the FMSS was most strongly related to both depression and QOL with magnitudes (and direction of relationships) comparable to a traditional measure of perceived social support. However, two FMSS factors (Received/Instrumental and Perceived) were unrelated to both mental health outcomes. Contrary to expectations, elevations in one FMSS factor (Emotional) was associated with worse symptoms of depression and poorer psychological QOL. When taken together, only the absence of negative social support on Facebook is significantly predictive of mental health functioning. Consequently, those hoping to use Facebook as a medium for reducing depression or improving QOL are unlikely to realize significant therapeutic benefits.
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Are Facebook ‘‘Friends’’ Helpful?
Development of a Facebook-Based Measure
of Social Support and Examination of Relationships
Among Depression, Quality of Life, and Social Support
Wilfred McCloskey, MS,
Sierra Iwanicki, MA,
Dean Lauterbach, PhD,
David M. Giammittorio, MS,
and Kendal Maxwell, MS
Greater social support is predictive of lower depression and higher quality of life (QOL). However, the way in
which social support is provided has changed greatly with the expanding role of social networking sites (e.g.,
Facebook). While there are numerous anecdotal accounts of the benefits of Facebook-based social support, little
empirical evidence exists to support these assertions, and there are no empirically validated measures designed
to assess social support provided via this unique social networking medium. This study sought to develop an
empirically sound measure of Facebook-based social support (Facebook Measure of Social Support [FMSS])
and to assess how this new measure relates to previously established measures of support and two outcome
variables: depression and QOL. Following exploratory factor analysis, the FMSS was determined to assess four
factors of social support on Facebook (Perceived, Emotional, Negative, Received/Instrumental). The Negative
Support factor on the FMSS was most strongly related to both depression and QOL with magnitudes (and
direction of relationships) comparable to a traditional measure of perceived social support. However, two FMSS
factors (Received/Instrumental and Perceived) were unrelated to both mental health outcomes. Contrary to
expectations, elevations in one FMSS factor (Emotional) was associated with worse symptoms of depression
and poorer psychological QOL. When taken together, only the absence of negative social support on Facebook
is significantly predictive of mental health functioning. Consequently, those hoping to use Facebook as a
medium for reducing depression or improving QOL are unlikely to realize significant therapeutic benefits.
Face-to-face social support is clearly associated with
reduced symptoms of depression
and improved overall
quality of life (QOL).
However, social interaction is
changing with the increasing popularity of social networking
Web sites (e.g., Facebook). Research suggests people use
Facebook for maintaining previously established, in-person
and, to a lesser extent, developing new
As such, Facebook may logically be conceptu-
alized as a medium through which social support is pro-
vided. There are numerous anecdotal accounts of Facebook
‘‘support,’’ and there are more than 200 Facebook created
condition-specific support groups. Research findings support
anecdotal accounts, with Facebook users reporting a rela-
tionship between Facebook users’ ‘‘number of friends’’ and
perceived support.
This association has been shown to be
stronger for Facebook users than for users of other online
social networking sites (e.g., LinkedIn, MySpace, Twitter).
These findings suggests Facebook affords users social sup-
port that other avenues do not offer (e.g., ease/speed of
contact, simultaneous interaction with multiple friends, un-
limited access, news feed, photographs).
While Facebook appears to be an important, and unique,
medium for provision of social support, research examining
this phenomenon is notably absent. No studies to date have
used a measure of social support that captures some of the
more unique aspects of Facebook as a social medium. As
Facebook is booming in popularity and appears to be a un-
ique context for perceived social support provision, this
paucity of data is particularly concerning. Therefore, to ad-
dress these issues, the current study aimed to develop a
Department of Psychology, Eastern Michigan University, Ypsilanti, Michigan.
University of Michigan Health System, Ann Arbor, Michigan.
Department of Psychology, University of North Texas, Denton, Texas.
Volume 18, Number 9, 2015
ªMary Ann Liebert, Inc.
DOI: 10.1089/cyber.2014.0538
measure of Facebook-based social support, assess the in-
strument’s convergent validity, and examine the effect of
Facebook social support on depression and QOL. The liter-
ature review that follows will first outline the relationship
between social support and two mental health outcomes
(depression and QOL). Next, it will outline the nature of
social support on the Internet and the absence of a measure
developed specifically to assess support on Facebook.
Social support and depression
A widely accepted definition of social support is ‘‘the
perception or experience that one is loved and cared for and
part of a social network of mutual assistance and obliga-
There are two related yet distinct types of social
support of interest in the current study: perceived and re-
ceived social support. Perceived social support comprises aid
one believes to be available if it were to be needed,
whereas received social support refers to the social support
actually utilized or obtained by an individual.
support is composed of several subdomains (Directive Gui-
dance, Non-directive Support, Tangible Assistance, and
Positive Social Exchange).
Greater perceived social support is consistently predictive
of lower levels of depression.
Findings are somewhat
mixed regarding the association between received social
support and depressive symptoms,
with some investiga-
tions finding a similar buffering effect.
However, Finch
et al. found two dimensions of received social support
(Tangible Assistance and Directive Guidance) were posi-
tively correlated with depression whereas Positive Social
Exchange was negatively correlated and, when aggregated,
the association between received social support and depres-
sion became nonsignificant.
These mixed findings suggest
received social support is likely a weaker predictor of de-
pressive symptoms relative to perceived social support.
Given the rapid growth in online social networking, it is
important to assess the possible palliative effects of social
support on Facebook. In other words, does social support on
Facebook translate into reduced depression?
Social support and QOL
QOL is defined as ‘‘an individual’s perception of their
position in life in the context of the culture and value systems
in which they live, and in relation to their goals, expectations,
standards and concerns.’’
The majority of research exam-
ining the relationship between social support and QOL has
been conducted in the medical arena
with greater per-
ceived social support predicting improved QOL.
social support does not appear to predict the same im-
provements in QOL
but is positively correlated with life
satisfaction, a related but not identical construct.
So, while
it is clear that perceived social support is important in im-
proving QOL, the association with received social support is
more dubious. The question remains: does social support
provided on Facebook predict improved QOL?
Social support on the Internet
Social networking sites have been expanding in popularity
since 1997 with the advent of, which was
regarded as one of the first mass-appeal social networking
sites. Currently, Facebook dominates the landscape (1.3
billion registered users worldwide
) of social networking
sites in no small part due to the number of options afforded to
users that aid in social connectedness, including high utili-
zation by ‘‘real-life’’ friends,
speed of communication,
and the ability to view/comment on user photos.
users report logging onto the site for social support,
research suggests that Facebook is the only social networking
site to be associated with perceived social support.
actual mechanism of benefit of this social support, however,
is unclear. For example, research indicates that greater
number of Facebook friends is predictive of worse emotional
adjustment among first year students but better emotional
adjustment among advanced students.
Few studies (N=11)
have empirically assessed Facebook-based social support. Of
these studies, investigators typically assessed Facebook-
based social support by using versions of established mea-
sures of social support modified to reflect Facebook-specific
support (see Table 1). The majority of extant research in this
area suggests that Facebook-based social support and ‘‘off-
line’’ support are highly correlated
and are associated
with both reduced depressive symptoms
and improved
It is important to reiterate, however, that the extant
research in the area of Facebook-based social support has
utilized adapted versions of existing measures to assess so-
cial support on Facebook or used ‘‘home grown’’ measures
Table 1. Existing Research Examining Facebook-Based Social Support
Study NAdapted social support measure Notes
Akbulut and Gunuc, 2012
255 Multidimensional Scale of Perceived
Social Support (MSPSS)
Asbury and Hall, 2013
Carpenter, 2012
292 Self-developed Seeking/offering social support
Cavello et al., 2012
134 Chogahara’s Social Influence on Physical Activity
High et al., 2014
84 Social Support Questionnaire (SSQ) 6 selected items
Indian and Grieve, 2014
299 Interpersonal Support Evaluation List (ISEL) Appraisal subscale
Liu and Yu, 2013
330 ISEL
Oh et al., 2013
291 Self-developed Health-related social support
Vitak and Ellison, 2012
18 Qualitative Interview
Wright et al., 2013
361 SSQ
Wright, 2012
274 Communication-Based Emotional
Support Scale (CBESS)
with unknown psychometric properties.
While online
social support may appear analogous to traditional forms
of in-person social support, the unique aspects of sup-
port provided using Facebook (e.g., postings, acceptance of
friend requests, and ‘‘likes’’ of posts) may not be captured
by current measures of social support, which highlights the
need for a specific measure of Facebook-based social sup-
port. To date, there are no empirically validated measures
specifically assessing social support provided on Facebook.
The current study
The goals of this study were to develop a measure of
Facebook social support, examine the convergent validity of
this instrument, and examine the potential buffering effect
of greater Facebook social support on symptoms of depres-
sion and QOL.
The participants (N=633) for this study were recruited
from undergraduate classes at a mid-sized Midwestern uni-
versity. Participants were required to be at least 18 years old
but were not required to have a Facebook account to par-
ticipate, though the vast majority of participants reported
having at least one active Facebook page (91%). A college
sample was chosen because of the high prevalence of
Facebook use within this population.
Participants had a
median age of 21 years and were primarily female (70.1%),
Caucasian (64.8%), and single (53.4%). Regarding the var-
iables of interest for the study, participants on average re-
ported mild levels of depression (mean PHQ-9 score 6.33;
SD =5.62). Participants reported average QOL scores for the
Physical (M=27.99, SD =4.44), Psychological (M=21.25,
SD =4.35), and Social (M=10.68, SD =2.61) domains and
above average QOL for the Environmental domain
(M=29.16, SD =5.17) when compared with norms estab-
lished by an international field trial of the World Health
Organization Quality of Life- Short Form (WHOQOL-
In-person received and perceived social support. The
Inventory of Socially Supportive Behaviors (ISSB)
is a
40-item self-report questionnaire of received social support
assessing six domains of support: material aid, behavioral
assistance, intimate interaction, guidance, feedback, and
positive social interaction. Respondents rate the frequency
each behavior occurs on a 5-point Likert-type scale (0 =‘‘not
at all’’ to 4 =‘about every day’’), with higher scores re-
presenting more frequent receipt of social support. The ISSB
demonstrates strong internal consistency (a=0.94), which
was replicated in the current study (a=0.97).
The Multidimensional Scale of Perceived Social Support
is a 12-item self-report measure designed to as-
sess respondent’s perception of available social support from
three sources: family, friends, and significant other. Partici-
pants rate how supportive they view others on a 7-point
Likert-type scale (1 =‘‘very strongly disagree’ to 7 =‘‘very
strongly agree’’), with higher values reflecting greater per-
ceived support. The MSPSS displays good internal consis-
tency in college student samples (a=0.88), which was
replicated in the current study (a=0.94).
Depression. The Patient Health Questionnaire 9 (PHQ-9)
is a 9-item self-report measure assessing frequency of de-
pressive symptoms and associated functional impairment.
Respondents rate how often they have been bothered by each
symptom over the last 2 weeks on a 4-point Likert-type scale
(0 =‘‘not at all’’ to 3 =‘‘nearly every day’’), with higher
values indicating more severe depressive symptoms. The
PHQ-9 showed satisfactory internal consistency reliability in
primary care settings (a=0.89) and is predictive of health-
related QOL scores (r=0.33 for bodily concerns, r=0.73 for
mental health problems
) and changes in severity of de-
In the current study, internal consistency of the
PHQ-9 was high (a=0.91).
is a 26-item self-report
QOL scale composed of 24 questions that assess the inten-
sity, capacity, frequency, and evaluation of an individual’s
QOL and two items assessing overall QOL and general
health. Items are scored on a 5-point Likert-type scale with a
variety of anchors (1 =‘‘not at all/very poor/very dissatisfied/
never’’ to 5 =‘‘completely/very good/very satisfied/ex-
tremely/always’’), with higher scores denoting better QOL.
Scores on the 24 items are summed into four domains:
Physical Health, Psychological, Social Relationships, and
Environment. The WHOQOL-BREF showed satisfactory
internal consistency reliability on all domains, ranging from
a=0.68 to 0.82.
Internal consistency for the subscales on
the WHOQOL-BREF in the present study were similar,
ranging from a=0.76 (Social) to 0.81 (Physical Health).
Subject recruitment occurred in undergraduate psychol-
ogy courses and via fliers placed in prominent locations
across campus. During in-class recruitment, students were
informed of the study aims, potential risks/benefits of study
participation, and time requirements. Interested individuals
completed instruments via online study management soft-
ware, which has been shown to be a satisfactory alternative
to traditional pencil and paper measures.
Development of the Facebook Measure
of Social Support
The Facebook Measure of Social Support (FMSS) was
developed to assess social support on Facebook. The initial
item pool consisted of 40 items that roughly corresponded to
perceived and received social support. A review of the items
by a panel composed of one professor of clinical psychology
and four doctoral students yielded a final pool of 23 items to be
examined using exploratory factor analysis (EFA). The pur-
pose of the EFA was to (a) identify items for inclusion in the
instrument, and (b) identify latent classes (factors) of items.
Prior to conducting the analyses, data were inspected for
missingness to ensure that assumptions of statistical tests were
met. Missing data were below 2% for each item, so all indi-
viduals with missing data were included. Inspection of skew
and kurtosis showed moderate non-normality, so weighted
least squares means and variance adjusted (WLSMV) esti-
mation was chosen for the EFA. Both the Kaiser–Meyer–
Olkin (KMO) measure of sampling adequacy (0.88) and
Bartlett’s test of sphericity (v
=4006.95, df =253, pp0.000)
supported factorability of the 23 items.
Three procedures were employed to determine factor re-
tention: examination of the scree plot, Kaiser’s criterion (i.e.,
eigenvalue >1.0
), and parallel analysis using SPSS syn-
Visual inspection of the scree plot revealed a clear break
and subsequent leveling at the fifth factor. Based on an un-
rotated solution, Kaiser’s criterion identified four factors ac-
counting for 52.27% of the total variance. However, parallel
analysis based on raw data vector permutation suggested re-
tention of seven factors. As a result, geomin-rotated EFA
using MLR estimation was conducted to produce solutions
between one and seven factors. Model statistics indicated that
the four-factor solution was the most parsimonious and best
fitting model. Although the absolute fit of the four-factor so-
lution was rejected, v
(167) =430.22, p<0.0001, information
and residual fit statistics indicated overall good model fit
(CFI =0.96; RMSEA =0.06; SRMR =0.04).
To evaluate further the items in the four-factor model, the
individual factor loadings were evaluated using their stan-
dard errors to determine whether they were statistically
significant. Using a correction procedure from Cudeck and
O’Dell for correlated factors, a new a*-level was computed
to be 0.000625 (z
*=3.42). Next, items were examined to
determine whether to retain or eliminate based on statistical
hypothesis testing of the factor pattern loadings (see Cudeck
and O’Dell) and magnitude of the factor loadings.
In ad-
dition to the aforementioned practical rationale, items with a
strong theoretical rationale were also retained. The final in-
strument is a 14-item measure composed of four factors. The
final items, rotated factor loadings, and values for Cron-
bach’s alpha are presented in Table 2. Internal consistency of
the entire scale was good (a=0.81).
Convergent validity
The strength of relationships between the FMSS and the
two traditional measures of social support ( MSPSS and
ISSB) were examined to assess convergent validity. Three
factors of the FMSS (Perceived Social Support, Emotional
Social Support, and Instrumental Social Support) were sig-
nificantly correlated with the ISSB. Two factors of the FMSS
(Negative Social Support and Perceived Social Support)
were significantly correlated with the MSPSS (see Table 3).
Social support, depression, and QOL
Pearson correlations were computed to assess how per-
ceived (MSPSS) and received (ISSB) social support are re-
lated to depression (PHQ9) and QOL (WHOQOL-BREF).
As expected, perceived social support was negatively asso-
ciated with depression severity and positively associated
with all domains of QOL. Received social support was not
significantly related to depression but was positively related
Table 2. Rotated Factor Loadings and Test Statistics for Hypothesis Testing
Rotated factor
Criterion value for
significance testing
Factor: Perceived Support (a=0.74)
For me, Facebook isn’t good for getting any kind
of real help or support. (Reverse-scored)
0.59 -10.57
The support I get on Facebook is of practical help to me. 0.53 8.78
The support I get on Facebook makes me feel better. 0.41 6.41
Factor: Emotional Support (a=0.74)
I’m happy when people comment on my posts. 0.82 25.02
I’m happy when people ‘‘Like’’ my posts. 0.81 25.02
I get excited when I get a Facebook notification. 0.72 19.41
I’m disappointed if I log on and don’t have any new notifications. 0.51 10.40
Factor: Negative Social Support (a=0.64)
I get a lot of negative responses on Facebook. 0.80 20.84
It freaks me out if my friend number decreases. 0.64 12.20
I get upset if somebody doesn’t accept my friend request. 0.57 12.24
Facebook actually makes me feel less close to people. 0.52 9.81
Factor: Received Informational/Instrumental Support (a=0.75)
If I needed help with something, I could post
it on Facebook and I’d get the help I need.
0.91 30.75
If I needed information about something, I could post
it on Facebook and I’d get the information I need.
0.87 27.29
People respond to me on Facebook as much as I want them to. 0.53 11.19
Table 3. Correlations Among Facebook Measure
of Social Support Factors and Traditional
Measures of Social Support
Instrumental social support -0.017 0.092*
Emotional social support 0.075 0.113*
Negative social support -0.280** 0.070
Perceived social support 0.151** 0.139**
*p<0.05; **p<0.01.
FMSS, Facebook Measure of Social Support; MSPSS, Multi-
dimensional Scale of Perceived Social Support; ISSB, Inventory of
Socially Supportive Behaviors.
to three domains of QOL (Psychological, Social Relation-
ships, and Environment; see Table 4).
Pearson correlations were computed to assess the rela-
tionship between the FMSS factors, depression, and QOL.
Scores on the Emotional Support factor were positively
correlated with level of depression, suggesting greater emo-
tional support as measured by the FMSS is associated with
higher levels of depression. Scores on the Emotional Support
factor were negatively correlated with WHOQOL-BREF
domain examining psychological QOL and were not sig-
nificantly related to any other WHOQOL-BREF domains.
Scores on the Negative Support factor were positively cor-
related with level of depression and negatively correlated
with all domains of QOL. Neither the Perceived Support nor
the Instrumental Support factors of the FMSS were signifi-
cantly associated with either depression or QOL (see Table 4).
One aim of this investigation was to develop a measure of
social support received on Facebook that incorporates unique
features of support provided in this medium (e.g., liking
posts, speed of communication). Further, the researchers
hypothesized that social support on Facebook would predict
respondents’ perception of QOL and depression.
Results of an exploratory factor analysis of Facebook-
related social support items yielded a four-factor solution
(Emotional Support, Perceived Support, Instrumental Sup-
port, and Negative Support). It is encouraging that the
hypothesized factors of the FMSS demonstrate convergent
validity with traditional measures of social support. Three
factors on the FMSS (Instrumental, Emotional, and Perceived
Social Support) were significantly correlated with the tradi-
tional measure of received social support (i.e., ISSB) in the
hypothesized direction, which suggests that the FMSS is an
adequate measure of social support received on Facebook.
Additionally, two FMSS factors assessing the perception of
social support on Facebook (Negative Social Support and
Perceived Social Support) were also significantly correlated
with the traditional measure of perceived social support (i.e.,
MSPSS) in the hypothesized direction, which suggests the
FMSS also captures perception of social support on Facebook.
Findings suggest support provided on Facebook is related
to QOL and depression, although not always in the hypoth-
esized direction. As expected, Negative Support was posi-
tively correlated with depressive symptoms, and negatively
correlated with QOL. However, the Emotional Support fac-
tor of the FMSS was unexpectedly associated with higher
depression and lower QOL. These curious findings suggest
that while individuals may report that support provided by
‘‘friends’’ on Facebook is beneficial, this support may not
translate to measurable reduction in depressive symptoms or
improvements in QOL. However, it may be the case that
online social support is impacted by an inherent confound of
social networking: individuals who are in more distress ac-
cess social support resources more often when compared
with those in less distress.
So, in cross-sectional re-
search, it is especially difficult to determine if social support
predicts worse depression and QOL or whether more dis-
tressed individuals access social support resources more
frequently to cope with this distress. This uncertainty may
account for these seemingly paradoxical study findings.
Limitations of the study and implications of findings
The current study had a number of limitations. Perhaps
most notably, the study sample consisted of college students,
most of whom have been exposed to Facebook and have a
high degree of comfort and familiarity with support provided
via this medium. Therefore, these findings may not gener-
alize to groups that are less comfortable/familiar with using
Facebook. Second, as the FMSS is newly developed, the
measure may not fully capture all types of social support
available on Facebook, an important issue given the rapidly
evolving nature of the medium. Third, the majority of the
sample was female, and it is unclear how findings from the
current study will generalize to a sample more representative
of the population. Lastly, criterion validity of the FMSS was
assessed via comparison with only two outcome measures.
Future research should seek to confirm (or disconfirm) the
criterion validity of the FMSS using other widely used
measures of depression (e.g., BDI-II) and QOL (e.g., Tem-
poral Satisfaction with Life Scale; TSWLS).
Despite these limitations, the development of the FMSS
has significant implications for the construct of social sup-
port in the 21st century. Research clearly suggests that Fa-
cebook use is correlated with improved mental health
and with in vivo social support.
However, as this study
demonstrates, Facebook-based social support is not com-
pletely analogous to more traditional constructs of social
support and thus may supplement but not supplant in-person
The FMSS provides a quantitative measure of this
new construct, which will enhance understanding of how
support may manifest on Facebook. More specifically, the
distinct factors of Facebook-based social support delineated
on the FMSS may be predictive of enacted coping strategies
Table 4. Relationship Between Types of Social Support, Depression, and QOL
Social support measure PHQ-9 Phy. Health Psych Social Rel. Environ.
MSPSS -0.204** 0.366** 0.358** 0.514** 0.448**
ISSB 0.043 0.024 0.108* 0.202** 0.138**
Perceived social support 0.070 -0.031 -0.026 -0.014 -0.042
Emotional social support 0.165** -0.020 -0.169** -0.067 -0.032
Negative social support 0.107* -0.303** -0.243** -0.172** -0.229**
Instrumental social support 0.052 0.031 -0.006 0.036 0.038
*p<0.05; **p<0.01.
on Facebook, as is the case with more traditional forms of
social support (e.g., increases in perceived emotional support
is predictive of problem-focused coping strategies,
ceived social support moderates coping with stress
). It is
clear that Facebook provides users with an ever-changing
social milieu. Therefore, it is crucial that the FMSS remain a
‘‘living’’ measure, able to be molded to reflect the state of the
science of psychology and changes in social networking sites
most accurately.
The authors would like to acknowledge Danny Jones for
his contributions to the development and implementation of
this project. The authors would like to acknowledge Danny
Jones for his contributions to the development and imple-
mentation of this project.
Author Disclosure Statement
No competing financial interests exist.
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Address correspondence to:
Dr. Dean Lauterbach
303a Mark Jefferson Science Complex
Department of Psychology
Eastern Michigan University
Ypsilanti, MI 48197
... Therefore, instrumental support is limited in online spaces. Notably, in text-based online networking services, such as Facebook, instrumental support is not practical (Trepte et al. 2015;McCloskey et al. 2015;Liu et al. 2018). Although there are diverse definitions of the types of social support, these converge on two types of social support, emotional and instrumental support (Shakespeare-Finch and Obst 2011;Obst et al. 2019). ...
... Perceived Social Support from Family, Offline Friends, and Online Friends We considered two types of social support and three types of social support sources because these change the buffering effects of social support on mental health (Malecki and Demaray 2003;Semmer et al. 2008;Rothon et al. 2011;McCloskey et al. 2015;Oriol et al. 2017;Trepte et al. 2015;Liu et al. 2018). ...
... Therefore, instrumental support from offline or online friends is associated with better mental health. The positive effect of online instrumental support is inconsistent with previous studies on asynchronous text-based online networking services (Trepte et al. 2015;McCloskey et al. 2015;Liu et al. 2018), in which instrumental support was not practical. The instrumental support effect of online friends in Pigg Party may result from embodiment in virtual worlds reinforcing social support (Collange and Guegan 2020). ...
Online social support via avatar communication is a powerful tool for bullying victims because they often lack offline social resources. Additionally, avatar communication allows users rich nonverbal interactions (e.g., emotional expressions) while maintaining online anonymity. This study investigates the role of online social support via avatars for victims and how to facilitate such support. Accordingly, we conducted an online questionnaire survey twice on an avatar communication application, Pigg Party, regarding mental health, offline and online social support, and offline bullying victimization (participants: 3,288 (1st wave) and 758 (2nd wave)). We found that online social support via avatars supplemented insufficient offline social resources, particularly when there was a high risk of offline bullying victimization. Furthermore, we investigated how online social support is improved by ego networks using social network data from Pigg Party. We demonstrated that belonging to large and closely connected communities can enhance online social support. Our findings suggest that avatar communication applications can improve players' mental health through online social support, reinforced by facilitating ego networks.
... 4,17,51,82,131 Timing or temporal dimensions are generally quite limited and studies span across acute disorders, subacute symptoms and trait/personality factors among a wide variety of ethnic, clinical and non-clinical populations. Broadly speaking, the studies looked at associations (n = 120; 85.7%), [17][18][19][20][21][22][23][25][26][27][28][29][31][32][33][36][37][38][39][40][41][43][44][45][46][47][48][49][50][51][52][53][55][56][57][58][59][60][61][63][64][65][66][67][68][69][70][71][72][73]75,76,[78][79][80][81][82][83][84][86][87][88][89][90][91][92][93][94][95][97][98][99][100]102,103,105,112,[114][115][116][117][118][119][120][121][122][123][124][125][126][127][129][130][131][133][134][135][136][137][138][139][140][141][142]144,146,148,149,154,155 and mediating (n = 16; 11.4%) 24,30,34,35,62,74,77,85,101,104,113,128,132,143,145 and causal (n = 4; 2.9%) 42,54,104,147 relationships between social media and behavioural health issues. ...
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Background Social media and other technologies are reshaping communication and health. AimsThis review addresses the relationship between social media use, behavioural health conditions and psychological well-being for youth aged <25 years. MethodA scoping review of 11 literature databases from 2000 to 2020 explored research studies in youth in five areas: clinical depression and anxiety, quantitative use, social media mode, engagement and qualitative dimensions and health and well-being. ResultsOut of 2820 potential literature references, 140 met the inclusion criteria. The foci were clinical depression and anxiety disorders (n = 78), clinical challenges (e.g. suicidal ideation, cyberbullying) (n = 34) and psychological well-being (n = 28). Most studies focused on Facebook, Twitter, Instagram and YouTube. Few studies are longitudinal in design (n = 26), had comparison groups (n = 27), were randomised controlled trials (n = 3) or used structured assessments (n = 4). Few focused on different youth and sociodemographic populations, particularly for low-income, equity-seeking and deserving populations. Studies examined association (n = 120; 85.7%), mediating (n = 16; 11.4%) and causal (n = 4; 2.9%) relationships. Prospective, longitudinal studies of depression and anxiety appear to indicate that shorter use (≤3 h/day) and purposeful engagement is associated with better mood and psychological well-being. Depression may predict social media use and reduce perception of support. Findings provide families, teachers and providers ways to engage youth. Conclusions Research opportunities include clinical outcomes from functional perspective on a health continuum, diverse youth and sociodemographic populations, methodology, intervention and privacy issues. More longitudinal studies, comparison designs and effectiveness approaches are also needed. Health systems face clinical, training and professional development challenges.
... Furthermore, making time to reconnect with trusted friends is beneficial to a person's overall wellbeing because it acts as a reference in making decisions and a stress reliever during periods of breakdown. According to studies, individuals with a rich social life are often more likely to live longer than those with fewer friends, according to studies (McCloskey, 2015). ...
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This research aimed to look into the cultural values and symbols of Generation Z Students as implications for contextualizing Physical Education courses in one of the leading State Universities in the Philippines to make learning more engaging and responsive to the needs and interests of students. This research employed a qualitative ethnographic research design with 205 research participants who participated in focus group discussions, extensive field observations, in-depth interviews, and field notes. The findings revealed seven (7) cultural values, namely: bonding, relaxing, being able to share, knowing how to get along, being updated with trends, being aware of surroundings, and open-mindedness; and three (3) symbols: gadget, online games, and social media were identified as essential implications in the contextualization of Physical Education course. This resulted in the conceptualization of a contextualized course syllabus in Tertiary Physical Education as a potential reference for effective delivery of instruction in Tertiary Physical Education.
... It is reported that when SNS users' express negative emotions online, they are less likely to receive supportive comments and likes. 26 Lack of response 27,28 may lead to feelings of loneliness, while negative responses on SNSs are reported to be associated with anxiety, 28 unhappiness, 29 and feelings of disconnectedness 30,31 in users. However, SNS users may mitigate the envy and feelings of inadequacy that arise due to comparison with their idealized peers upon viewing their images on SNS if they perceive that they have family, friends, and others on whom to rely. ...
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Young people are increasingly using social networking site (SNS) smartphone applications (apps), necessitating research on the effects of such use on the users’ emotional health. The present study recruited 360 college students across mainland China and recorded their smartphone usage for one week using an automatic tracking app. Surveys assessing social support perception and emotional health were subsequently conducted. The study examined the relationship between SNS smartphone app usage (frequency and duration) and emotional health, as well as the moderating role of perceived social support in SNS smartphone usage and emotional health. Among individuals with high social support, SNS smartphone use was more strongly associated with better emotional health. These results suggest conditional benefits of using SNS smartphone apps, depending on the user's perceived social support. The implications for designing and using SNS smartphone apps are also discussed.
... It was also found to reduce mental illness, including depression, anxiety, and loneliness [20]. However, some evidence showed that social support from social media was related to more significant mental health conditions, e.g., a higher likelihood of depression and poorer quality of life [12,21]. The inconsistent findings regarding the relationship between OSS and adolescents' mental health were partly because of the varied conceptualization and operationalization of OSS [22]. ...
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Supportive interactions on social media have great potential to benefit adolescents’ development. However, there is no instrument to measure online social support (OSS) in China. The study aimed to develop and validate a Chinese short version of the Online Social Support Scale (OSSS). The original scale was translated into Chinese through multiple forward and backward translation protocols. The calibration sample (N = 262) was used to select items and test the reliability, validity, and internal structure of the short form. The cross-validation sample (N = 267) was then used to assess measurement invariance by multigroup confirmatory factor analysis and examine criterion validity based on its relationships with life satisfaction, depression, and time on social media. The 20-item Chinese short version of OSSS (OSSS-CS) includes four factors: esteem/emotional support, social companionship, informational support, and instrumental support. Our results suggest that the OSSS-CS has high internal consistency, construct validity, and criterion validity. Furthermore, evidence of partial cross-validity demonstrated invariance of the variance–covariance matrices, factor structure, factor loadings, and factor variance across independent samples. The results also revealed that the original OSSS could be replicated across cultures. Finally, the short form developed in the study can be used as a reliable and valid measure of online social support among the Chinese adolescent population.
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Social networking sites (SNS), with Facebook as a prominent example, have become an integral part of our daily lives and more than four billion people worldwide use SNS. However, the (over-)use of SNS also poses both psychological and physiological risks. In the present article, we review the scientific literature on the risk of Facebook (over-)use. Addressing this topic is critical because evidence indicates the development of problematic Facebook use (“Facebook addiction”) due to excessive and uncontrolled use behavior with various psychological and physiological effects. We conducted a review to examine the scope, range, and nature of prior empirical research on the negative psychological and physiological effects of Facebook use. Our literature search process revealed a total of 232 papers showing that Facebook use is associated with eight major psychological effects (perceived anxiety, perceived depression, perceived loneliness, perceived eating disorders, perceived self-esteem, perceived life satisfaction, perceived insomnia, and perceived stress) and three physiological effects (physiological stress, human brain alteration, and affective experience state). The review also describes how Facebook use is associated with these effects and provides additional details on the reviewed literature, including research design, sample, age, and measures. Please note that the term “Facebook use” represents an umbrella term in the present work, and in the respective sections it will be made clear what kind of Facebook use is associated with a myriad of investigated psychological variables. Overall, findings indicate that certain kinds of Facebook use may come along with significant risks, both psychologically and physiologically. Based on our review, we also identify potential avenues for future research.
Social media is an infinite box of mystery and the more curious you are, the more it holds you. As youth uses different modes of social media on a regular basis, knowingly or unknowingly they develop a dependency on social media. Gaming, instant texts, constant need of stimulation leads to the addiction that marks a longer lasting impact that is being portrayed in the research below. As much as social media helps youth to connect with people despite the distance, the phubbing leads to creating more of a communication gap with people around. Multitasking, avoiding physical activities, seeking constant social validation through social media make youth much more vulnerable and hamper youth’s wellbeing.
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Aim: study was to investigate the relationship between High-risk behavior and virtual space and quality of life in the tenth among grade boys and girls in Boukan city in the Academic year 96-97. Method: The research was applied in terms of purpose and in terms of collecting descriptive information of correlation type. The statistical population of this study included all 10th grade boys and girls in Boukan. A total of 400 students (170 boys and 230 girls) were selected based on multi-stage cluster sampling. The research tools were Mohammad Khani's High Risk Behavior Questionnaire, Purgholami's Cluster Questionnaire and Global Health's Quality of Life Questionnaire. Analysis method was Pearson correlation coefficient and multiple regression. Results: The results showed that there is a reverse and significant relationship between high risk behaviors and cyber dimensions with quality of life of students in the tenth grade. Also, the results of multiple regression showed that among the high risk behaviors, consumption of alcoholic beverages with the highest variance and relationship with the opposite sex with the least variance, as well as the dimensions of cyberspace, the conflict of values with the highest variance and social isolation with the least variance predicted. Changes in quality of life. Conclusion: Therefore, Incompatibility technological changes and problems with emotional communication with parents increase high-risk behaviors such as consumption of alcoholic beverages and illicit sex. These behaviors, in turn, will reduce the quality of life and increase social isolation. Keywords: High-risk behaviors-virtual space-quality of life. ‫اﭘﺮوز‬ ‫ﮐﻤﺎل‬ ‫ﻣﺴﺌﻮل‬ ‫)ﻧﻮﯾﺴﻨﺪه‬ (‫ﮐﺎرﺷﻨﺎﺳﯽ‬ ‫ارﺷﺪرواﻧﺸﻨﺎﺳﯽ‬ ‫ﺑﺎﻟﯿﻨﯽ،‬ ‫واﺣﺪ‬ ‫ﺑﻮﮐﺎن‬ ، ‫داﻧﺸﮕﺎه‬ ‫آزاد‬ ‫اﺳﻼﻣﯽ،‬ ‫ﺑﻮﮐﺎن،‬ ‫اﯾﺮان.
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Covariance structure analyses were carried out on the Inventory of Socially Supportive Behaviors (ISSB; Barrera, Sandler, & Ramsey, 1981) to corroborate a hypothesized four-factor measurement model of received social support. Examination of the influence of the separate dimensions of the ISSB indicated that the four dimensions correlated in opposite directions with depression. Aggregation across the full set of ISSB items yielded a composite ISSB score that failed to predict depression and obscured the dynamics of these differential relations. By contrast, all four dimensions of the ISSB exhibited positive relations with life satisfaction, and total ISSB scores explained as much variance in life satisfaction as did the individual subscales. In general, the four ISSB dimensions proved to be differentially related to depression and life satisfaction in ways that were predictable, informative, and theoretically meaningful. The results of the present investigation illustrate the utility of a multidimensional conceptualization of the construct of enacted social support.
The World Health Organization (WHO) is developing an international quality of life assessment instrument (WHOQOL) which will allow an enquiry into the perception of individuals of their own position in life in the context of the culture and value systems in which they live, and in relation to their goals, expectations, standards and concerns. The WHOQOL will measure quality of life related to health and health care. It is being developed in the framework of a collaborative project involving numerous centres in different cultural settings. In addition it will have proven psychometric properties of validity, reliability and responsiveness to change and will be sensitive to the cultural setting in which it is applied, while maintaining comparability of scores across different cultural settings. This chapter outlines the methodology for the development of the instrument and sets out the characteristics and uses of the WHOQOL.
This chapter considers the measurement of supportive functions that are perceivedto be available if needed (perceived support) or functions that are reportedto be recently provided (received support). The basic assumption for the choiceof such measures is that they tap the availability of resources provided throughsocial relationships that should help persons to cope with acute or chronic stressors.