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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,
1
Sierra Iwanicki, MA,
1
Dean Lauterbach, PhD,
1
David M. Giammittorio, MS,
1,2
and Kendal Maxwell, MS
1,3
Abstract
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.
Introduction
Face-to-face social support is clearly associated with
reduced symptoms of depression
1
and improved overall
quality of life (QOL).
2,3
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
relationships
4,5
and, to a lesser extent, developing new
friendships.
6
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.
6
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).
7
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).
8,9
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
1
Department of Psychology, Eastern Michigan University, Ypsilanti, Michigan.
2
University of Michigan Health System, Ann Arbor, Michigan.
3
Department of Psychology, University of North Texas, Denton, Texas.
CYBERPSYCHOLOGY,BEHAVIOR,AND SOCIAL NETWORKING
Volume 18, Number 9, 2015
ªMary Ann Liebert, Inc.
DOI: 10.1089/cyber.2014.0538
499
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-
tions.’’
10
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,
11
whereas received social support refers to the social support
actually utilized or obtained by an individual.
12,13
Received
support is composed of several subdomains (Directive Gui-
dance, Non-directive Support, Tangible Assistance, and
Positive Social Exchange).
14
Greater perceived social support is consistently predictive
of lower levels of depression.
15–17
Findings are somewhat
mixed regarding the association between received social
support and depressive symptoms,
15
with some investiga-
tions finding a similar buffering effect.
18
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.
19
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.’’
20
The majority of research exam-
ining the relationship between social support and QOL has
been conducted in the medical arena
21,22
with greater per-
ceived social support predicting improved QOL.
23
Received
social support does not appear to predict the same im-
provements in QOL
24
but is positively correlated with life
satisfaction, a related but not identical construct.
19
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 SixDegrees.com, which was
regarded as one of the first mass-appeal social networking
sites. Currently, Facebook dominates the landscape (1.3
billion registered users worldwide
25
) 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,
26
speed of communication,
8,26
and the ability to view/comment on user photos.
8
Facebook
users report logging onto the site for social support,
27
and
research suggests that Facebook is the only social networking
site to be associated with perceived social support.
8
The
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.
28
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
29–31
and are associated
with both reduced depressive symptoms
32
and improved
QOL.
33
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
46
255 Multidimensional Scale of Perceived
Social Support (MSPSS)
Adolescents
Asbury and Hall, 2013
47
126 MSPSS
Carpenter, 2012
33
292 Self-developed Seeking/offering social support
Cavello et al., 2012
48
134 Chogahara’s Social Influence on Physical Activity
High et al., 2014
49
84 Social Support Questionnaire (SSQ) 6 selected items
Indian and Grieve, 2014
30
299 Interpersonal Support Evaluation List (ISEL) Appraisal subscale
Liu and Yu, 2013
31
330 ISEL
Oh et al., 2013
34
291 Self-developed Health-related social support
Vitak and Ellison, 2012
50
18 Qualitative Interview
Wright et al., 2013
32
361 SSQ
Wright, 2012
51
274 Communication-Based Emotional
Support Scale (CBESS)
500 McCLOSKEY ET AL.
with unknown psychometric properties.
34,35
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.
Method
Participants
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.
35
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-
BREF).
31
Measures
In-person received and perceived social support. The
Inventory of Socially Supportive Behaviors (ISSB)
14
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
(MSPSS)
37
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)
38
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
39
) and changes in severity of de-
pression.
40
In the current study, internal consistency of the
PHQ-9 was high (a=0.91).
QOL. The WHOQOL-BREF
36
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.
36
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).
Procedures
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.
41,42
Results
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
DEVELOPMENT OF A MEASURE OF FACEBOOK-BASED SOCIAL SUPPORT 501
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
2
=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
43
), and parallel analysis using SPSS syn-
tax.
44
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
2
(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
a
*=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.
45
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
Item
Rotated factor
loading
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
FMSS factor MSPSS
a
ISSB
b
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**
a
n=504.
b
n=482.
*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.
502 McCLOSKEY ET AL.
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).
Discussion
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.
52,53
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
30,31
and with in vivo social support.
6,29–31
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
support.
9
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
WHOQOL-BREF domains
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**
FMSS:
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.
DEVELOPMENT OF A MEASURE OF FACEBOOK-BASED SOCIAL SUPPORT 503
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,
54,55
re-
ceived social support moderates coping with stress
55
). 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.
Acknowledgments
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
E-mail: Dlauterba@emich.edu
DEVELOPMENT OF A MEASURE OF FACEBOOK-BASED SOCIAL SUPPORT 505
... Many researchers have discussed how the greater tendency towards social comparison might increase Facebook use, motivated by the search for information about others, influencing self-esteem and depression (Nesi & Prinstein, 2015;Tartaglia, 2016). McCloskey et al. (2015) found that minimal "likes" and Facebook "friends" were predictive of greater depressive symptoms due to a lack of emotional support users received. Additionally, Phu and Gow (2019) found that, although persistent Facebook usage is associated with high loneliness levels, the number of Facebook "friends" is highly associated with subjective happiness, due to emotional connectedness. ...
... For example, it was found that only the importance of "likes" was negatively associated to Facebook usage, whilst age and the importance of "followers" were negatively related to problematic Instagram use. The number of Facebook "friends" was also significantly positively associated with depressive symptoms, which reflected a stark contrast in direction from previous studies (Park et al., 2013;McCloskey et al., 2015). A potential explanation could be regarding the difference in the functionalities of these social media platforms and different usage. ...
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Although the association of well-being (e.g., self-esteem, depression symptoms, and loneliness) with Facebook usage (i.e., number of friends and frequency of use) has been investigated by many researchers, only a limited number of studies have scrutinised Facebook against Instagram use. The aim of this study is not only to address this literature gap but also to explore whether problematic use and well-being differ between Facebook and Instagram users in relation to the number of received “likes” and Facebook friends/Instagram followers, as well as the importance of these “likes” and friends/followers. Sixty-nine Facebook users and 66 Instagram users completed an online questionnaire, including self-esteem, loneliness, depression, and problematic Internet use items. Overall, Instagram users exhibited significantly higher problematic use behaviour compared to Facebook users. Age and importance of “followers” were negatively associated with problematic use of Instagram, whilst only the importance of “likes” was negatively associated with Facebook. The number of Facebook “friends” was positively associated with depressive symptoms, but this was not the case for the number of Instagram “followers”. It is important to note that the number of “likes” was only negatively associated with self-esteem, but there was no association with loneliness. A potential explanation between the differences in the two platforms and well-being might be related to their different functionalities, for example, Instagram is an image-oriented platform that may boost users’ self-esteem through post “likes” but only when the users are strongly connected.
... Online social support was measured using a modified version of the 14-item Facebook Measure of Social Support (FMSS; Mccloskey et al., 2015). Specifically, items were adapted to be extended to all social networking sites instead of to Facebook only. ...
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Within the Compensatory Internet Use Theory (CIUT) framework, online activities may compensate for psychosocial problems. However, those who attempt to satisfy their needs or mitigate their fears via SNSs may be at heightened risk for problematic use of SNSs (PSNSU), especially in cases when these fears have an interpersonal base, and the individual effectively finds online social support. The current study hypothesizes that interpersonally-based fears predict PSNSU, and online social support will moderate these associations. Four hundred and fifty Italian participants (Mage= 27.42 ± 7.54; F = 73.5%) take part in the study. As examined by path analysis, fear of no mattering, fear of intimacy, and fear of negative evaluations were positively associated with PSNSU, and online social support significantly moderates the relationship between fear of negative evaluation and PSNSU. The model accounted for 19% of the variance of PSNSU and showed good fit indices. The associations' strengths decrease as age increases. Overall, the current study finds further support for the theory that motivations need to be taken into account when it comes to internet use (i.e., CIUT) and extends our understanding by highlighting that online social support might reinforce the link between the fear of being negatively evaluated and PSNSU. Keywords: Fear of not mattering, fear of intimacy, fear of negative evaluation, mattering, online social support, problematic social network sites use.
... However, the opportunity to share experiences and connect with peers in similar situations has been reported to outweigh risks related to privacy as well as concerns about web-based negativity and potentially low-quality information [20]. Reaching out to others on the web requires a certain level of candidness and honesty that can sometimes prompt negative support; messages perceived by the receiver as negative or unsupportive are known to lead to poorer overall mental health [21]. Despite the risks associated with sharing personal stories and issues on the web, parents of children and youth with CCN have reported fewer instances of judgment within Facebook support groups than in offline interactions [22]. ...
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Background: Caregivers of children and youth with complex care needs (CCN) often require considerable support to ensure the well-being of their families. Social media presents an opportunity to better support caregivers through computer-mediated communication for social support. Peer-to-peer (P2P) support groups are one way that caregivers are accessing needed support; however, the experiences of caregivers who use these groups and the perceived impact that participation has on caregivers of children and youth with CCN is not known. Objective: This study aimed to: (1) explore the experiences of caregivers of children and youth with CCN who use a Facebook-based P2P support group to communicate; (2) understand their motivations to use the group; and (3) investigate its perceived impact on knowledge of programs and services and sense of community belonging in caregivers. Methods: A qualitative descriptive design was used to explore the experiences and perceived impact of a Facebook-based P2P support group for caregivers of children and youth with CCN in New Brunswick, Canada. The group was launched online in October 2020, during the COVID-19 pandemic, and resulted in 108 caregivers joining the group. An online survey was distributed, and semi-structured interviews were conducted in February 2021 with a sub-sample of members. Thematic analysis was used to identify, and report patterns related to caregiver experiences and perceived impacts of participation. Results: A sub-sample of members in the Facebook group completed the online survey (n=39) and interviews (n=14). Five themes emerged from interviews: (1) Safe Space; (2) Informational Support and Direction; (3) Virtually Connect with Peers; (4) Impact on Knowledge of Programs and Services; and (5) Degree of Community Belonging. Participants reported joining the group to obtain geographic-specific information support and to connect with peers. Many participants reported an improvement in knowledge of programs and services and felt connected to the community; however, the short observation period and diversity among the caregiver population were cited as barriers to community belonging. Conclusions: Social media presents an important opportunity to facilitate the exchange of support between patients and caregivers in an accessible and curated environment. Findings from this study suggest that involvement in online, geographic-specific P2P support groups can influence perceived knowledge of services and resources and sense of community belonging among caregivers of children and youth with CCN. This work further provides insight into the experiences and motivations of caregivers of children and youth with CCN who participate in a private social media environment.
... However, the opportunity to share experiences and connect with peers in similar situations has been reported to outweigh risks related to privacy as well as concerns about web-based negativity and potentially low-quality information [20]. Reaching out to others on the web requires a certain level of candidness and honesty that can sometimes prompt negative support; messages perceived by the receiver as negative or unsupportive are known to lead to poorer overall mental health [21]. Despite the risks associated with sharing personal stories and issues on the web, parents of children and youth with CCN have reported fewer instances of judgment within Facebook support groups than in offline interactions [22]. ...
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... 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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... Chang (2017) showed that adolescents commonly use Snapchat to chat with friends, socialize, and share media. McCloskey et al. (2015) indicated that using social networking sites to communicate with friends can help reduce depression and improve QOL, as well as provide other major therapeutic benefits and social support. ...
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... In this study, the importance of -supportive shares‖ that caused positive effects was also mentioned. In line with the finding of this research, it was emphasized that in social media individuals could experience social support through active interactions such as texting and talking to people as well as passive interactions such as receiving likes and comments on photos or videos and having their shares reposted by someone else (McCloskey et al., 2015). In a study, it was highlighted that getting social support by other individuals on social media reduced the stress, loneliness and depression levels of the individuals and increased their well-being (Xavier, 2018). ...
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Stworzone w 1982 r. przez Williama Gibsona pojęcie „cyberprzestrzeń” w związku z ogromnym rozwojem technologicznym jaki widzimy na przełomie XX i XXI wieku, na stałe weszło do użycia i coraz częściej definiowane jest w dokumentach prawnych, a w rozważaniach politologicznych i militarnych wskazywane jako piąty – po ziemi, wodzie, powietrzu i przestrzeni kosmicznej – wymiar rywalizacji i współpracy państw. Jak słusznie zauważył najwybitniejszy polski pisarz gatunku hard science fiction Stanisław Lem „pociąg ludzi do zła ujawnia się zwłaszcza tam, gdzie pojawia się nowa technologia”. Opracowanie, już w samym założeniu, nie ma być przedstawieniem i analizą wszystkich zagadnień i ryzyk jakie niesie za sobą komputeryzacja oraz rozwój sieci informatycznych. Autorzy – studenci socjologii Collegium Civitas wraz z prowadzącym zajęcia z przedmiotu „Przestępczość w cyberprzestrzeni” – zdecydowali się zaprezentować jedynie wybrane aspekty zagrożeń dla społeczeństwa informacyjnego. Opisując Darknet i Deep Web wyselekcjonowali tylko niektóre elementy występujące w tej przestrzeni oraz opinie badaczy obserwujących tę część Internetu. Kolejnym elementem na który zwrócono uwagę to ciemna strona sieci społecznościowych. Przywykliśmy do codziennego korzystania z ulubionych portali społecznościowych. Dzięki rozwojowi technologicznemu jesteśmy podłączeni do sieci 24 godziny na dobę, przyzwyczailiśmy się do ogromnej ilości udostępnianych treści – przez co wielokrotnie nie dostrzegamy zagrożeń, jakie one ze sobą niosą. A będzie ich przybywać – miniaturyzacja, postęp technologiczny i rozwój technologiczny kierujący się w stronę „Internetu Rzeczy (IoT)” oraz sztucznej inteligencji (AI) powodują, że opisywane przed kilku laty jako futurologiczne drony dostarczające, bez udziału człowieka, produkty zamówione przez inteligentne i podłączone do infosieci lodówki stają się rzeczywistością.
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The high prevalence of depression among college students has a strong negative impact on individual physical and mental health, academic development, and interpersonal communication. This paper reviewed the extant literature by identifying nonpathological factors related to college students' depression, investigating the methods of predicting depression, and exploring nonpharmaceutical interventions for college students' depression. The influencing factors of college students' depression mainly fell into four categories: biological factors, personality and psychological state, college experience, and lifestyle. The outbreak of coronavirus disease 2019 has exacerbated the severity of depression among college students worldwide and poses grave challenges to the prevention and treatment of depression, given that the coronavirus has spread quickly with high infection rates, and the pandemic has changed the daily routines of college life. To predict and measure mental health, more advanced methods, such as machine algorithms and artificial intelligence, have emerged in recent years apart from the traditional commonly used psychological scales. Regarding nonpharmaceutical prevention measures, both general measures and professional measures for the prevention and treatment of college students' depression were examined in this study. Students who experience depressive disorders need family support and personalized interventions at college, which should also be supplemented by professional interventions such as cognitive behavioral therapy and online therapy. Through this literature review, we insist that the technology of identification, prediction, and prevention of depression among college students based on big data platforms will be extensively used in the future. Higher education institutions should understand the potential risk factors related to college students' depression and make more accurate screening and prevention available with the help of advanced technologies.
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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.
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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.