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Gender Differences in Social Support on Social Network Sites: A Meta-Analysis

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Social network sites (SNS) have become an increasingly popular platform for providing and receiving social support. Traditionally, females are believed to offer more social support. However, investigations of both the offline and online domains have revealed mixed findings. This meta-analysis attempts to assess the presence and magnitude of gender differences in social support on SNS. A literature review produced a sample of 30 independent studies with 17,000 participants. Results showed that females on SNS give (d = 0.36) and receive (d = 0.14) greater social support than do males. This is the first meta-analysis to test for and demonstrate gender differences in social support, either offline or online.
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Gender Differences in Social Support on Social Network Sites: A Meta-Analysis
Manuscript prior to peer review and publication.
For the updated paper see:
Tifferet, S. (2020). Gender Differences in Social Support on Social Network Sites: A Meta-
Analysis. Cyberpsychology, Behavior, and Social Networking, 23(4), 199209.
https://doi.org/10.1089/cyber.2019.0516
Abstract
Social network sites (SNS) have become an increasingly popular platform for providing
and receiving social support. Traditionally, females are believed to offer more social support.
However, investigations of both the offline and online domain have revealed mixed findings.
This meta-analysis attempts to assess the presence and magnitude of gender differences in social
support on SNS. A literature review produced a sample of 30 independent studies with 17,000
participants. Results showed that females on social network sites give (d = 0.36) and receive (d =
0.14) greater social support than do males. This is the first meta-analysis to test for and
demonstrate gender differences in social support, either offline or online.
Keywords: Facebook, literature review, sex, social support, social media, meta-analysis.
Introduction
Social support has significant psychological and health consequences 1. People with low
levels of support are more likely to suffer from loneliness 2, depression 3 and health problems 2.
Social network sites (SNS) have become an increasingly popular platform for giving and
receiving social support 4,5. Thus, it is important to study social support in this new domain and
examine its predictors. Traditionally, females are believed to grant more social support to others
6,7. However, the empirical findings in both the offline 810 and online realms 1113 are mixed.
This study aims to assess the presence and magnitude of gender differences in both giving and
receiving social support on SNS, using a meta-analytic assessment. To the best of my
knowledge, this is the first meta-analytic review of gender differences for either offline or online
social support.
Social support
Social support has many conceptualizations and definitions 1417. Some characterize it as an
antecedent of health 18,19. Others classify social support together with adjacent terms, such as
social capital, social integration, and social networks 2022. Still others delineate the various
subtypes of support that can be offered 2325. The present study aims to summarize a wide range
of studies using Heaney and Israel’s 16 inclusive definition of social support: aid and assistance
exchanged through social relationships and interpersonal transactions.” Similar definitions have
been commonly used in the study of social support, both offline 14,26 and online 27.
Social support is not a uniform construct; it can be classified into subtypes such as
emotional, instrumental, informational, and appraisal 25. It can also be classified by its level of
objectivity: Perceived support is the subjective perception, whereas enacted support comprises
actual behaviors 28,29. Last, social support is bi-directional and can be given and received 30,31.
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Most studies have focused on the receiving side of social support, whereas fewer have addressed
the giving of support. This imbalance may be due to the established significance of receiving
social support. In this study, I seek to assess social support inclusively, and therefore, I assess
both the giving and the receiving of social support on SNS in all their forms.
Gender differences in social support
In her theory of tend-and-befriend, Taylor 6,32 claimed that in the face of stress, females
give and receive social support more than do males. She suggested that these gender differences
arise from a biological response to stress. Whereas men are likely to react to stress using the
fight or flight response, women react to stress using the tend-and-befriend response. Tending
refers to the caring for offspring, whereas befriending refers to creating and maintaining social
networks. Taylor suggested that the tend-and-befriend response was evolutionarily selected to
increase the survival chances of mothers and their offspring in times of danger.
The claim that females seek and give more social support than do males is common 1,7,33,34
and has been attributed to both biological and social foundations. However, empirical findings
are equivocal. While some studies have shown that females indeed give and receive more
support 3538, some scholars have reported mixed results 8,10,39, whereas others report no gender
difference 4045.
In the offline realm, many of the studies on gender differences in social support are carried
out on married couples 8,3638,41,44,45. In this context, the bi-directional nature of social support
makes interpreting these findings challenging. For instance, in cancer patients, male patients
report receiving more spousal support than do females 38. It is unclear whether this finding is due
to men’s lower support-giving as caregivers or their higher need for support as patients. Studies
on same-sex friends exhibit similar problems. For instance, women are more likely to offer social
support to their same-sex friends than are men to their same-sex friends 35. Here, again, it is
unclear if this is due to female dominance in giving social support or in seeking it.
Social support on SNS
SNS include an extensive network of friends, acquaintances, and family, usually from both
genders. For this reason, studying social support on SNS examines a multitude of same- and
different-sex support patterns, both inside and outside the family. With the rising popularity of
social media, social support has an important role in the online realm 4,5,46,47. Users who post on
SNS expect to receive feedback and support 48, and indeed they are likely to receive it 4,49,50
perhaps more so on Facebook than on Instagram 51,52. SNS provide support for people who are
geographically distant from their primary support group, such as international students 53 and
facilitate adaptation to stressful life events 54,55. Receiving social support on SNS is associated
with SNS satisfaction 56, enhanced life satisfaction 57, lower depression 57, happiness, and self-
esteem 58.
Gender differences in SNS
Females and males behave differently online in general 59,60, and on SNS, specifically. In
comparison with males, females upload more photos 61,62, and post more status updates 63 . Their
SNS activity notwithstanding, females tend to express more concern about their privacy than do
males and are more cautious regarding the information they share 64.
Females also present themselves differently than males. In their profile photos, males
highlight their status 65,66, whereas females highlight family relations 65 and emotional
expressivity 65,66. Similar findings have been found in the language females use on SNS. In
comparison to males, females language is warmer, more positive, compassionate, cooperative,
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and polite 6769. I suggest that females’ inclination to warmth, expressivity, compassion, and
family relations finds expression in the increased giving of social support.
The present study
In the present study, I meta-analyze gender differences in giving and receiving social
support on SNS. Single-sample studies are limited to a single population and methodology and
are at risk for spurious results due to typically small samples. These sample characteristics are
prone to produce mixed findings in the field, which allow readers to cherry-pick findings that are
congruent with their viewpoint. Adopting a meta-analytic approach enables us to resolve existing
controversies and draw inferences from these conflicting empirical studies 70. A key feature of a
meta-analysis is its ability to quantitatively summarize the effect sizes of many studies, with
higher weightings assigned to larger samples. Due to these advantages, meta-analysis is
considered a powerful and dominant research approach 7072.
Several single-study papers have sought to assess the gender difference in online social
support 12,73; even more have assessed this difference with no a priori gender hypothesis 74,75.
Most studies have measured receiving social support 76,77, whereas fewer have measured giving
support 78,79. Following the tend-and-befriend theory and the empirical findings on increased
female warmth and cooperativeness, I posit the following hypotheses:
H1: Females give more social support on SNS than do males.
According to the tend-and-befriend theory 6, befriending is seen as “the creation of
networks of associations that provide resources and protection for the female and her offspring
under conditions of stress.” 6. Thus, it includes both giving and receiving social support.
Following H1, and due to the reciprocal nature of social support 80,81, I also posit the following
hypothesis:
H2: Females receive more social support on SNS than do males.
Methods
Search strategy
The search covered the databases of APA PsycNet, EBSCO, Emerald, Google Scholar,
Primo, Sage, ScienceDirect, and Taylor & Francis for English-language papers, from database
inception to October 2018. Search strings included terms related to the three constructs: social
support (e.g., social support, support), gender (e.g., gender, sex, sex difference, gender
difference), and social network sites (e.g., social network site, social media, Facebook, online),
using both free text and controlled language of indexing databases (i.e., database keywords). The
search was then repeated without gender-related search strings to find secondary data. We also
screened the bibliographies of pertinent reviews. Finally, we searched the websites of relevant
journals for recently added content, including Computers in Human Behavior, and
Cyberpsychology, Behavior, and Social Networking.
Along with peer-reviewed papers, the study incorporated a dataset from the Pew Research
Center. Datasets from the Pew Research Center have been the subject of analysis in peer-
reviewed journals 82. Each of the Pew Internet and Tech datasets 83 were scanned in search of
reports of gender differences on the study variables. This search produced a single dataset 84. We
also included the results from a highly cited Swedish report by the Gothenburg Research Institute
78.
Inclusion criteria
Together, these searches yielded 1,670 papers (including many duplicates). Based on their
titles and abstracts, 237 papers were identified as potentially eligible for inclusion. These papers
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were then fully screened for the following inclusion criteria: (a) an empirical quantitative study,
(b) published in peer-reviewed journals or at a large research center, (c) measuring gender and
social support on SNS, (d) not based on a gender-dependent sample (e.g., mothers), and (e) not
limited to a specific support group (e.g., health support groups). The last two criteria were used
to eliminate an inherent gender bias within the sample. For instance, a study on a Facebook
support group for autism included about 90% females 85; a study on a support group for surgeries
included 80% females 86. Applying the five inclusion criteria resulted in 55 eligible papers.
Of these 55 eligible papers, only 13 reported data appropriate for computing an effect size.
The remaining 42 papers did not include appropriate data. Some of the 42 reported gender-
related results using beta coefficients. This data is inappropriate since beta coefficients are partial
coefficients that may misrepresent the zero-order correlation between gender and social support
87. Other papers measured gender but did not report its relationship with social support. Thus, I
sent email requests and reminders to the authors of these 42 papers, of which 15 (36%)
responded. The final sample of the current meta-analysis thus included 28 papers reporting data
from 30 independent sample studies 11,12,84,8896,57,97104,7379. See the full selection process in
Figure 1.
Coding
Several variables were coded for each of the identified studies: year of publication,
author(s), country, number of participants, and the name of the SNSs. It was also recorded
whether the finding was related to an a priori hypothesis or was reported as secondary data. For
each finding, we coded the gender effect size or descriptive statistics. Each finding was
associated with either giving or receiving social support, and the specific measure it used was
coded.
Giving social support
Several self-report measures have been used to assess the levels of social support given by
the participants. The most common research strategy was to ask the participant to report the
likelihood of him or her responding supportively to a hypothetical post 12,73,74,88. The second
most common strategy was to ask the participants to report on actual past support-giving
behaviors 79,84,89. Last, one study used self-reports to measure the importance of using Facebook
to support others 78, and another to measure the social overload created by supporting others 11.
Receiving social support
The level of social support received by the participants was primarily assessed using
perceived support scales (82%). The most popular scale was an adaptation of the
Multidimensional Scale of Perceived Social Support 105. However, 12 additional scales were also
used 106118, and two additional studies used author-created items 84,90. Only four studies (18%)
attempted to measure enacted support using objective observational measures, such as the
number of likes received for a post 91 or the likelihood that a friend would respond to a request
for online assistance 100.
Statistical analyses
First, after examining studies’ findings, at times calculating research outcomes from the
descriptive statistics, we recorded Cohen’s d, odds ratio (OR), and Pearson’s r. For the second
stage, effect sizes were converted into Cohen’s d 119; thus, stronger social support on behalf of
females was indicated by a positive Cohen’s d value . In cases of several reported effect sizes
concerning the same topic, the average effect size was used. Third, we conducted two separate
meta-analyses: one for giving and one for receiving social support. The R software package
‘meta’ 120, using a random-effect model was employed for all analyses.
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In order to assess the variation in true effect sizes, their heterogeneity was assessed using Q
(measure of weighted squared deviations), τ (a measure of the between-studies standard
deviation), and I2 (the proportion of variance explained by the heterogeneity of the data statistics)
72: Publication bias was estimated using the trim-and-fill adjustment method 120,121.
Results
Sample description
The dataset included 30 independent samples from 28 papers, with 17,000 participants.
Studies from eight samples reported findings on gender differences in giving social support on
SNS, studies from 21 samples reported findings on receiving it, and a study from one sample
reported both 84 (see Tables 1 and 2). From these, 16 studies (53%) used undergraduate student
samples, 12 (40%) were conducted in the United States, and 27 (90%) employed a survey
methodology.
Gender differences in social support on SNS
As hypothesized, the meta-analyses revealed that females give and receive more social
support on SNS than do males (see Table 3, Figure 2, and Figure 3). However, the effect size of
giving support was small (d = 0.36, 95% CI [0.26, 0.47]) and that of receiving support was even
smaller (d = 0.14, 95% CI [0.06, 0.22]).
Heterogeneity
For both giving support (Q (8) = 19.94, p = .01) and receiving support (Q(21) = 81.69, p
< .001), heterogeneity was statistically significant. The proportion of the observed variance
reflected by real differences in effect sizes between studies (I2) was moderate for giving support
(60%) and high (74%) for receiving it 72 (see Table 3). These results suggest that there are real
differences between the effect sizes of the various studies in the meta-analysis. These differences
may stem from study differences, such as culture, measure, or the subtype of support (emotional,
instrumental, or informational).
Publication bias
Using the trim-and-fill adjustment method 120,121, no publication bias was revealed in the
meta-analysis of giving support: no studies were added, and Cohen’s d remained identical after
the adjustment (see Table 3). However, the trim-and-fill method did suggest a possible
publication bias in the meta-analysis of receiving support: eight studies were added, and Cohen’s
d decreased (see Table 3). Nonetheless, there is reason to believe that publication bias did not
play a major role in the gender difference of receiving social support. Of the 22 studies on
receiving support, only one (5%) considered gender differences in privacy as an a priori
hypothesis 97, whereas the others reported them only as secondary results. This high rate of
secondary data was due to the pervasive nature of gender as a standard demographic variable,
reported in most studies. Since the statistical significance of the gender difference was not an a
priori hypothesis in the vast majority of studies, publication bias seems unlikely.
Discussion
In today’s digital world, much of our social support has moved from the offline to the
online domain 4. Social support is indeed one of the motives for using SNS 122. Many studies
have assessed gender differences in social support, both offline and online. However, to the best
of my knowledge, this is the first study to systematically evaluate these differences by
performing a meta-analysis. Meta-analyses can quantitatively summarize the results of single-
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sample studies and correct for sample size. I hypothesized that a meta-analytic study would show
that females both give and receive more social support on SNS than males.
Gender differences in giving social support
As hypothesized, the meta-analysis showed that females give more support on SNS than do
males (Cohen’s d = 0.36). The study findings are in line with other gender differences found on
SNS. First, female’ language on SNS is warmer and more compassionate than that of males 67.
This suggests that they will also support others more often. Second, compared with males,
females spend more time on SNS 78,123 and are more active in them 124. This enhanced activity
can be manifested in any SNS behavior we examine. Hence, increased social support could be
attributed to females’ larger online presence: they are more active on SNS; hence, they are more
likely to embark on any SNS behavior, including supporting others.
Gender differences in receiving social support
As hypothesized, the meta-analysis showed that females also receive more support on SNS
than do males, albeit with a small effect size (Cohen’s d = 0.14), and a high heterogeneity
between studies (I2 = 75%). It appears that the major gender difference in social support on SNS
is in giving support, and less so in receiving it. Here too, females’ increased SNS activity can
explain their relatively high level of perceived support. Since SNS serve as a significant source
of social support 4, individuals who are more active on them can be expected to receive more
support. Since social support is reciprocal 80,81, it is plausible that the females’ higher social
support is reciprocated back to them from their friends and family members.
Limitations and Future studies
As social support is a bi-directional construct, it is difficult to disentangle the giving and
receiving sides. Although the networks on SNS usually include friends and family members of
both genders, it is still unlikely that their proportions would be equal. As individuals tend to have
more same-sex friends than opposite-sex friends, it remains unclear whether the small female
advantage in receiving support was not an artifact of the more substantial female advantage in
giving support. Hence, females may receive more support (as compared with males) as a result
of having a higher proportion of female friends in their SNS.
Although an effort was made to collect data from all eligible papers, 28 papers (51% of the
total eligible papers) were not included in the study since their authors did not respond to the
email request for supplementing their data. This absent information adversely affected the ability
of the current study to accurately assess gender differences. It is worth noting that the
compliance rate of the authors to the email requests was quite high (15 of 42 requests; 36%), in
comparison with similar reported requests 125,126. To promote future meta-analyses, authors
should be encouraged to include a full correlation table when reporting their results.
Conclusion
Social support is one of the motives for SNS activity 78. SNS users receive social support 4,
which is associated with both SNS satisfaction 56 and life satisfaction 57. The present study
carried out a meta-analysis to summarize the mixed findings on gender differences in providing
and receiving SNS social support. The findings show that females on social network sites give
more social support to other users than do men, and to some extent, also receive more support.
This is the first meta-analysis to document gender differences in social support.
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Table 1
Meta-analysis study characteristics: Giving support.
Study
Country
SNS
A priori
hypothesis
Email
response
n
d
Denti et al., 2012
SWE
FB
No
1,011
0.43
High, Oeldorf-Hirsch & Bellur, 2014
USA
FB
Yes
Yes
84
0.27
Joiner et al., 2016
GBR
FB
Yes
522
0.54
Joiner et al., 2014
GBR
FB
Yes
600
0.33
Macháčková, Dedkova, Sevcikova,
& Cerna, 2018
CZE
G
Yes
441
0.51
Maier, Laumer, Eckhardt, & Weitzel,
2015
DEU
FB
Yes
571
0.10
Pew Research Center, 2014
USA
G
No
241
0.38
Thelwall & Vis, 2017
GBR
FB, IN
Yes
Yes
288
0.20
Vogel, Rose, & Crane, 2018
USA
FB
No
Yes
289
0.45
Note. CZE = Czech Republic; DEU = Germany; FB = Facebook; G = General; GBR = United Kingdom; IN = Instagram; SWE = Sweden; USA = United States
of America. Positive d values indicate females providing greater support.
Table 2
Meta-analysis study characteristics: Receiving support
Study
Countr
y
SNS
A priori
Hypothesis
Measure
Email
Response
n
d
Aten, DiRenzo & Shatnawi,
2017
USA
LI
No
Direct assistance by network friends
Yes
366
0.22
Blight, Jagiello, & Ruppel,
2015
USA
FB
No
Measurement of Enacted Social Support
(Goldsmith et al., 2000) and number of likes
105
0.10
Frison & Eggermont, 2016
BEL
FB
No
Adaptation of the Multidimensional Scale of
Perceived Social Support (Zimet, Dahlem, Zimet,
& Farley, 1988)
910
-0.07
15
Frison, Bastin, Bijttebier, &
Eggermont, 2019
BEL
FB
No
Adaptation of the Multidimensional Scale of
Perceived Social Support (Zimet et al., 1988)
1,840
0.07
Haslam, Tee, & Baker, 2017
AUS
G
No
Adaptation of the Multidimensional Scale of
Perceived Social Support (Zimet et al., 1988)
353
0.30
High & Buehler, 2019
USA
FB
No
Informational, emotional, and esteem support,
adapted from Xu & Burleson (2001)
Yes
549
0.10
Li, Wang, Lin, & Hajli, 2018
(Study 1)
CHN
G
No
Emotional and informational support based on
Hajli (2014)
Yes
156
0.16
Li, Wang, Lin, & Hajli, 2018
(Study 2)
ITA
G
No
Emotional and informational support based on
Hajli (2014)
Yes
137
0.40
Lin et al., 2018
TWN
G
No
Revised Social Support Scale (Yeh et al., 2008)
Yes
1,922
0.30
Manago, Taylor, & Greenfield,
2012
USA
FB
No
Adaptation of the Interpersonal Support
Evaluation List (Cohen & Hoberman, 1983)
Yes
85
0.14
Mazzoni, Baiocco, Cannata, &
Dimas, 2016
ITA
G
No
Online Social Support Scale (Wang & Wang,
2013)
Yes
819
0.11
Misra, Dangi, & Patel, 2015
IND
G
Yes
Multidimensional Scale of Perceived Social
Support Assessment (Zimet, Powell, Werkman &
Berkoff, 1990)
100
0.40
Olson, Liu, & Shultz, 2012
USA
FB
No
Adaptation of the Inventory of Social Supportive
Behaviors (ISSB; Barrera, Sandler, & Ramsay,
1981)
Yes
178
-0.07
Park, et al., 2016 (Study 1)
USA
FB
No
Abbreviated version of the Social Provision Scale
(SPS; Cutrona & Russell, 1987) and actual
support
Yes
61
0.42
Park, et al., 2016 (Study 2)
USA
FB
No
Abbreviated version of the Social Provision Scale
(SPS; Cutrona & Russell, 1987) and actual
support
Yes
42
-0.10
Pew Research Center, 2014
USA
G
No
General and parenting support for mothers
240
0.47
Stefanone, Kwon and Lackaff,
2012
USA
FB
No
Assistance in an online task
49
0.39
Ul-Malik and Rafiq, 2016
PAK
G
No
Online social support (Moody, 2001)
Yes
301
0.04
Utz and Breuer, 2017
NLD
G
No
Adaptation of the UCLA Social Support
Inventory (Dunkel-Schetter, Feinstein, & Call,
1986)
Yes
3,367
-0.06
Wright, et al., 2013
USA
FB
No
Social Support Questionnaire (SSQ; Sarason,
Sarason, Shearin, & Pierce, 1987)
361
0.26
Zhang, et al., 2015
USA
G
No
Adaptation of The Social Influence on Physical
Activity Questionnaire (Chogahara, 1999)
Yes
439
-0.15
16
Zhang, 2017
HKG
FB
No
Frequency of receiving social support (Li, Chen,
& Popiel, 2015)
Yes
573
0.24
Note. AUS = Australia; BEL = Belgium; CHN = China; FB = Facebook; G = General; HKG = Hong Kong; IND = India; ITA = Italy; LI = LinkedIn; NLD =
Netherlands; PAK = Pakistan; TWN = Taiwan; USA = United States of America. Positive d values indicate female receiving greater support.
Table 3
Meta-analyses testing gender differences in social support on SNS
Variable
Effect size
Heterogeneity
T&F
k
N
d
LL
UL
τ
Q
df
p
I2
k
d
Giving Support
9
4,047
0.36
0.26
0.47
0.14
19.94
8
0.01
60%
0
0.36
Receiving Support
22
12,953
0.14
0.06
0.22
0.02
81.69
21
< 0.001
74%
8
0.04
Note. d = Cohen’s d (positive d values show greater female support); I2 = percentage of variance beyond sampling error; k = number
of samples, LL = 95% CI for Cohen’s d lower limit; N = combined sample size; Q = chi-square test for homogeneity of observed
validities; T&F k = number of effect sizes imputed by trim-and-fill analysis; T&F d = trim-and-fill estimate of Cohen’s d (positive d
values show greater female support); UL = 95% CI for Cohen’s d upper limit; τ = between-studies standard deviation.
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... Các triệu chứng của trầm cảm nặng đã được tìm thấy ở những cá nhân dành phần lớn thời gian cho các hoạt động trực tuyến và quản lý hình ảnh trên các trang mạng xã hội [4,15]. Mặc dù việc sử dụng mạng xã hội thiếu kiểm soát sẽ có xu hướng dẫn đến trầm cảm, cô đơn nói chung, nhưng có sự khác biệt giới về mức độ ảnh hưởng này [16][17][18]. Mối liên hệ giữa tình trạng nghiện mạng xã hội với các vấn đề tâm lý thường được mô tả ở nữ giới. Tuy nhiên, phân tích về cảm giác cô đơn cho thấy có 45,3% nam giới và 36,4% nữ giới phải chịu mức độ cô đơn trung bình đến cao và có sự khác biệt về giới trong tương quan giữa cô đơn với tần suất sử dụng mạng xã hội [19]. ...
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... In general, girls develop more communal social orientations, including having more intimate and dyadic friendships involving self-disclosure, feeling that relationships are more central to their sense of self, and experiencing more friendship stress (e.g., jealousy) and concern about self-presentation (Rose & Rudolph, 2006). In the context of social media, these differences likely explain why girls report more investment in their social media self-presentation, more investment in online peer experiences (e.g., 'likes'), more online appearance concerns, and more giving and receiving of online social support Marsh, Fogleman, Langberg, & Becker, 2022;Tifferet, 2020). However, boys are more likely to use online gaming platforms (Rideout et al., 2022) which offer opportunities for social interactions. ...
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Social media have drastically changed the context of adolescent development. To date, the majority of research investigating the effects of these changes has measured time spent on social media, yielding inconclusive results—likely because this approach conceptualizes social media as a monolith. Social media experiences are complex and diverse, as are adolescents themselves. Emerging research has identified several specific components of social media that have varied associations with adolescent mental health, as well as individual difference factors that may alter these associations across adolescents. In this annual research review, we synthesize evidence regarding heterogeneity in social media effects related to (a) specific components of social media and (b) adolescents' individual differences regarding social media use and effects. We first focus on the specific social media components—content, features, and functions—that may be especially relevant for adolescent development. These include functions designed to foster relationships and social connections (e.g., social media feeds, ‘friends’), hateful content, notifications, risky content, and algorithmically curated content, among others. Next, we provide an overview of for whom these effects may matter most. We review research on individual differences that may explain some heterogeneity in social media effects, including gender/sex, age, marginalized status, neurobiological and social sensitivities, and other preexisting vulnerabilities to mental health concerns. The nascent work in these areas suggests many specific constructs and considerations that could drive future research examining nuanced and precise questions that go beyond ‘screen time’. We discuss avenues for researchers to leverage methodological advancements and address how specific social media experiences and individual differences shape developmental outcomes.
... However, the presence of offline and external social support networks may reduce their reliance on smartphones for these purposes. In contrast, males may not experience the same protective benefit, due to differences in how they use smartphones or expect support from their social networks [78]. ...
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Introduction Despite the many benefits of smartphones, researchers have raised concerns over problematic smartphone use (PSU) and its negative effects on physical and psychological well-being. Studies examining PSU and its impact among adults remain limited. Hence, we aim to examine the prevalence of PSU among adults in Singapore, and explore its associations with smartphone activities, sleep quality, and psychological well-being, as well as age and gender-related differences in these associations. Methods A household survey (n = 1200) was conducted among multi-ethnic Singapore adults aged 21 to 60. The survey employed a proportionate stratified random sampling approach. The Smartphone Addiction Scale–Short Version was used to determine risk of PSU. Adjusted multivariable logistic regressions, age-stratified (21–30, and above 30) analyses and sensitivity analyses were performed. Results The survey response rate was 45.7%. PSU prevalence rate was estimated to be 34.0%. Adults at risk were younger (OR = 3.72, p < 0.001), had poor sleep quality (OR = 2.94), reported depressive (OR = 2.84, p = 0.001) or anxiety symptoms (OR = 2.44, p < 0.001), tend to use smartphones for social media (OR = 2.81, p = 0.002) or entertainment (OR = 2.72, p < 0.001). Protective factors include higher levels of social support (OR = 0.76, p = 0.007), using smartphones for calling family (OR = 0.39, p = 0.003) and friends (OR = 0.53, p = 0.030), and spending four hours or less of smartphone usage duration (OR = 0.40, p < 0.001). Sensitivity analyses confirmed these findings. Associations between PSU and poor sleep quality (OR = 3.72, p < 0.001), depressive (OR = 3.83, p < 0.001), and anxiety symptoms (OR = 2.59, p = 0.004) and social media usage (OR = 3.46, p < 0.001) were more pronounced in adults over 30. PSU was more prevalent among females in those aged 21–30 (OR = 2.60, p = 0.022). Social support appears to be a protective factor for adults over 30 (OR = 0.64, p < 0.001) but was not observed in those aged 21–30. Among males, younger age (21–30 years), poor sleep quality, depressive symptoms, and anxiety symptoms, and using social media and entertainment apps were significantly associated with PSU. Females showed similar associations. Social support appears to be a protective factor for females (OR = 0.70, p = 0.018), but this association was not observed for males. Shorter smartphone usage times were inversely associated with PSU in both genders. Conclusion A substantial proportion of adults exhibited PSU. Findings highlight the differential associations between PSU and psychological well-being, social support, interactions with technology, and sleep quality. These associations are influenced by age which has implications for preventive efforts.
... Additionally, we didn't nd differences in the perception of social and institutional support between genders. Other studies indicate that women report better quality of social support than men (Kneavel 2021) and both give and receive more social support (Tifferet 2020). One hypothesis to explain these results relates again to patient support associations. ...
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