Meta-Analysis of The Relationships Between Social Support and Well-Being in Children and Adolescents
Meta-Analysis of The Relationships Between Social Support and Well-Being in Children and Adolescents
Meta-Analysis of The Relationships Between Social Support and Well-Being in Children and Adolescents
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SOCIAL SUPPORT AND WELL-BEING
Research has started to explore the associations between social support and wellbeing among children and adolescents, but the overall relationship is still unclear. This study explored: (1) the overall association between social support and
well-being, (2) the association differences among categories of well-being, (3)
the association differences among different types of social support measures, (4)
the association differences among different support sources, and (5) whether the
association between social support and well-being changed with participants
age. Two hundred forty-six studies were collected and analyzed, and the results
indicated a positive but small association between social support and well-being.
Additionally, moderator analyses indicated that social support was more strongly
associated with self-concept, perceived support was more strongly associated
with well-being, support from teachers and school personnel was more strongly
associated with well-being, and the association between social support and wellbeing increased with age. The implications and possible applications of the relationship between social support and well-being among children and adolescents
are discussed.
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ert control over them (Russell, Pettit, & Mize, 1998). Hartup (1989)
stated that vertical and horizontal relationships have somewhat
different impacts on children and adolescents, and thus the social
support they receive and perceive, and its effects, may be different
as well.
Because the overall magnitude of the relationship between social
support and well-being is not well-established for children and adolescents, and because children tend to experience support differently than adults (e.g., vertical vs. horizontal), a synthesis of studies
to investigate these issues is beneficial. Furthermore, Barrera (1986)
showed that the outcome variables examined among children and
adolescents across studies were very diverse. This suggests that a
moderator analysis is necessary. In Amato and Keiths (1991) metaanalysis on parental divorce and the well-being of children, they
coded outcome measures into 8 categories (e.g., academic achievement, conduct problems of children and adolescents, psychological adjustment) and performed a moderator analysis across these
categories. In our current meta-analysis, we adopted and adjusted
their coding schemes to examine and compare different categories
of outcomes across studies.
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Method
Locating Studies
We located studies for potential inclusion using the PsycINFO
(1900-2008) and Eric databases (1966-2008). First, the key word social support was used to search for studies (articles, book chapters,
and dissertations) that specifically used participants of childhood,
preschool age, school age, or adolescence as samples. Studies had
to be written in English, be published in the United States,1 and be
quantitative studies. A total of nearly 1,400 articles, abstracts, or texts
were scanned or reviewed. Reference lists of studies we retrieved
were examined to identify other studies for potential inclusion.
1. We set this criterion in order to control the variable of culture. Evidence suggests
that the relationships between social support and well-being are influenced by culture.
Kim, Sherman, and Taylor (2008) stated that the study of social support should take
the social relationships patterns of different cultures into account, because how
people sense and utilize social support depends on how they see the self and their
relationships with others, and different cultures have different assumptions and
expectations on these aspects. In other words, people of different cultures have different
perceptions of social support, and inclusion of those people could cause potential
confounds. This was the same reason we excluded studies of immigrant samples.
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Inclusion Criteria
Correlational studies that met the following inclusion criteria were
included. First, participants must have been children and/or adolescents, including preschoolers, kindergarteners, elementary students, middle school students, and high school students. Second,
studies were conducted in the United States. Third, correlations,
means and standard deviations, p values, or other statistics sufficient for the calculation of an effect size of the relationship between
social support and well-being were included. If a study did not
have information adequate for the calculation of effect sizes (e.g.,
only reported multivariate statistics), it was excluded. Fourth,
samples were not sojourners or immigrants. Finally, the measure
of social support was derived directly from self-reports of the samples instead of from parent-report or lab-observation. For example,
Wertlieb, Weigel, and Feldstein (1987) realized the limitation of obtaining childrens social support from their mothers and suggested
childrens self-report was a more valid index of their own social
support. This opinion is shared by other researchers (e.g., Cauce &
Srebnik, 1990; Compas, 1987; Dubow & Ullman, 1989).
Sample of Studies
Two hundred forty-six published (N = 199) and unpublished (N
= 47) studies met the inclusion criteria and were included in the
analyses.2 The sample sizes of individual studies ranged from 21
to 14,211, and samples ages ranged from 3 to 20 years.3 The total
number of participants across all studies was 121,432. The publication years ranged from 1980 to 2008, with a mean publication year
of 2000.94.
Coding Procedures
Each study was coded for the following characteristics: name of the
first author, publication year, number of total participants, mean age
2. All the studies included in the meta-analysis are available from the authors.
3. Though our maximum age limit was high school students only, 8 studies (k =
26) reported students in high schools up to the age of 20. Because the number of high
school students over age 18 was very small, in order to preserve the information the
studies could provide we decided to retain those studies.
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After scanning and reviewing the 246 articles, we found that the
outcome variables that were studied generally fit this categorization, and therefore we adopted this categorization with some modifications. The first 5 categories (a-e) were adopted, and 4 additional
categories were added: health (e.g., exercise frequency, eating habits, Body Mass Index (BMI), healthy habits such as diet and avoiding
substance use); coping skills (e.g., with anger, burnout); career (e.g.,
career planning, career outcome expectation, self-efficacy in finding
a good career path after graduation); and other (included different
overall measurements, such as overall life satisfaction, overall adaptive/maladaptive behaviors, quality of life, self-concept combined
with academic achievement, or some variables that did not belong
to any category, such as capacity for reflection).
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Types of Measures
Social support measurements were coded into 5 categories: first,
size (those that measure the number of people in participants social
network, such as number of friends); second, enacted (those that ask
participants perception of how much help they actually received
for a certain period of time in the past, such as participants estimation of the frequency of parents praising or listening to them in
the past month); third, perceived (those that measure participants
perception of availability of help if they need it, such as how much
the participants believe they can rely on their parents when they
are in trouble); fourth, seeking (those that measure how much participants seek social support when they are depressed or anxious);
and fifth, other (those measures that failed to differentiate different aspects of social support such as The Network of Relationships
Inventory by Furman and Buhrmester (1985), or the measures that
access size and satisfaction of social support but the studies failed
to report them separately).
Sources of Support
We also coded the sources of support into 4 categories: family/relative support, friend support, teacher and school support, and others
(e.g., counselors, other adults, and communities).
Other Moderators
Age. We coded participants mean age in order to examine the relationship between age and effect sizes using a continuous moderator
analysis. Some studies did not provide the mean age of the participants, but almost all provided participants grade levels in school,
therefore we used that information to estimate the mean age.
Publication Years. Finally, we were interested in examining whether the relationships remained stable over time. Therefore, the publication years of the studies were tested as moderators of the relationship between social support and well-being.
A study may contribute more than one effect size because social
support was often used to correlate with more than one outcome.
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A total of 901 effect sizes were extracted from the 246 studies and
included in the analysis. Forty-four studies (17.89%) contributed 1
effect size, 72 studies (29.27%) contributed 2 effect sizes, 44 studies
(17.87%) contributed 3 effect sizes, 26 studies (10.57%) contributed
4 effect sizes, 5 studies (2.03%) contributed 5 effect sizes, 27 studies
(10.98%) contributed 6 effect sizes, 8 studies (3.25%) contributed 8
effect sizes, 12 studies (4.88%) contributed 9 effect sizes, 3 studies
(1.22%) contributed 12 effect sizes, 2 studies (0.81%) contributed 15
effect sizes, 1 study (0.41%) contributed 16 effect sizes, and 2 studies
(0.81%) contributed 18 effect sizes.
Most of the coding of the variables was straightforward, but the
classification of well-being variables and types of support into categories was somewhat more subjective. Therefore, we performed
reliability tests in which the first and third authors independently
coded 50 well-being variables and types of support. The Cohens
Kappa was .71 (p < .05) for well-being variables and .80 (p < .01) for
types of support. The disagreements were resolved by discussion.
Results
DSTAT (Johnson, 1989), a computer software program for the metaanalytic review of research literature, was utilized to analyze the
effect sizes. The overall effect size was calculated using two methods. First, when one study provided more than one effect size, the
studys effect sizes were first synthesized and corrected based on
sample sizes, such that each study contributed only one effect size.
Second, all 901 effect sizes were analyzed for an overall effect size.
A histogram of the distribution of all 901 effect sizes is presented
in Figure 1. As Figure 1 illustrated, the distribution approximates a
normal distribution.
Based on the analysis of only one effect size per study, both the
overall unweighted and weighted effect sizes have the same value
when rounded to two decimal places, r = .18, p < .0001. Using all 901
effect sizes, both the overall unweighted and weighted effect sizes
have the same value when rounded to two decimal places, r = .17,
p < .0001. These results indicated that the relationship between perceived social support and overall well-being was positive in direction but only small in magnitude. Because the results of one effect
size per study and all effect sizes were very close, we used all 901
effect sizes for all following analyses.4
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TABLE 1. Mean Weighted Effect Sizes by Categories of Outcomes of Well-Being
Categories
90% CI
Academic achievement
164
.105a
.101 / .108
Conduct
141
.141b
.137 / .145
Psychological adjustment
262
.199c
.195 / .202
Self-concept
138
.265d
.259 / .270
Social adjustment
68
.212c, e
.204 / .220
Health
45
.238e, f
.230 / .247
Coping skills
17
.098a, b
.081 / .116
Career
14
.215c, e, f
.199 / .231
Other
34
.252d, f
.241 / .262
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90% CI
Size
53
.01a
.004 / .017
Enacted
147
.143b
.139 / .147
Perceived
604
.201c
.199 / .204
Seeking
21
.069d
.056 / .082
Other
76
.191e
.183 / .199
significantly more strongly associated with well-being than the other measures of social support.
Effect Sizes Across Sources of Support
The mean weighted effect sizes for support sources were also calculated (see Table 3). The mean effect sizes ranged from .098 (other)
to .209 (teacher and school personnel support), which suggests that
the relationships between different sources of support and wellbeing vary from somewhat weak to moderate in magnitude. Post
hoc contrasts were also performed and the results are indicated in
Table 3. The results of the contrasts show that the mean effect size of
teacher and school personnel support is significantly stronger than
the rest of the effect sizes, and the support of other sources is significantly weaker than the rest.
Other Moderator Analyses
Age. Average age was used as a continuous moderator. The mean
age was 13.75, and the moderator analysis revealed a positive significant correlation between age and effect sizes, z = 3.93, p < .0001.
This indicated that the strength of the relationship between social
support and overall well-being increases with the age of participants across the studies.
Publication Year. The publication year was analyzed as a continuous moderator. The result was significant, z = 2.55, p < .05, suggesting that the effect sizes have increased significantly over the years.
Gender Difference. Finally, there were 18 studies measuring male
and female participants relationships between support and well-
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TABLE 3. Mean Weighted Effect Sizes by Sources of Support
Categories
90% CI
Family/Relative
297
.192a
.189 / .195
Friend
213
.100b
.096 / .103
Teacher/School
125
.209c
.204 / .213
Other
42
.098b
.087 / .109
Discussion
This meta-analysis explored the relationships between social support and childrens and adolescents well-being. The results indicated a significantly positive but small association, and that was moderated by different outcomes of well-being (e.g., academic achievement, conduct problems, psychological adjustment). Additional
moderator analyses revealed that measures of perceived social support are more strongly associated with well-being than other types
of measures. Different sources of support had different strengths
of relationships with well-being, with teacher and school personnel support being stronger than other sources of support. Age was
a significant moderator in the relationship between social support
and well-being, which indicated that the effect sizes increased as the
average age of the children and adolescents increased. Studies that
reported effect sizes across genders were analyzed and the results
suggested female children and adolescents have stronger relationships between support and well-being than do male children and
adolescents. Finally, publication year was a significant moderator
between social support and well-being, suggesting that effect sizes
increased significantly over the years.
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The effect sizes have increased significantly over the years. Speculatively, because the number of studies of children and adolescents
social support has been growing over the years (Wolchik et al.,
1989), the increasing of the effect sizes may imply that better measures were developed later that evaluated the relationship between
support and well-being more effectively.
Regarding gender differences, though some studies of children
and adolescents showed no gender differences in the correlation
between support and well-being (e.g., Santos, Richards, & Bleckley,
2007), and some found the relationship to be significant only for
male participants (e.g., Cumsille & Epstein, 1994), our analysis of 42
studies (k = 98) suggested that the mean effect size for female participants was stronger than was the mean effect size for male participants. This may indicate that teenage girls rely more on interdependent relationships for well-being (Caselman, Self, & Self, 2006).
This seems to be consistent with the adult literature. For example,
Belle (1987) indicated that women use and receive more support
than do men. Miller and Stiver (1997) stated that womens health
development is associated with their interpersonal relationships.
Kendler, Myers, and Prescotts (2005) longitudinal study involving
more than 1,000 opposite-sex dizygotic twin pairs also found that
supportive relationships are more protective against depression for
women. Thus, it appears that women may have learned to rely on
their relationships for well-being at a young age. However, given
the diverse outcome variables of well-being studied in social support literature, the same pattern of gender difference may not be
consistent across all outcomes of well-being. We believe more research is needed on these gender differences.
Conclusion
We believe the results found in this meta-analysis have practical
implications. First, to our knowledge, this meta-analysis is the first
attempt to synthesize the literature assessing the relationship between social support and well-being among these age groups. Consequently, the findings should offer new knowledge and direction
for future research on the well-being of children and adolescents.
Furthermore, Cohen and Wills (1985) suggested that social support
is a significant contributor to the well-being of individuals. Therefore, the finding that social support is positively linked to the well-
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being of children and adolescents may indicate possibilities for intervention. We also have suggested potential research directions in
regard to moderators such as measures of social support, sources of
social support, different outcomes of well-being, and age and genders of children and adolescents. In conclusion, this meta-analysis
has provided a further understanding of social support and wellbeing among children and adolescents, and may serve as a foundation for future research on the benefits of social support for the
well-being of children and adolescents.
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