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Behavioral Sleep Medicine
ISSN: 1540-2002 (Print) 1540-2010 (Online) Journal homepage: http://www.tandfonline.com/loi/hbsm20
Social Support as a Mediator Between Insomnia
and Depression in Female Undergraduate
Students
Soohyun Kim & Sooyeon Suh
To cite this article: Soohyun Kim & Sooyeon Suh (2017): Social Support as a Mediator Between
Insomnia and Depression in Female Undergraduate Students, Behavioral Sleep Medicine, DOI:
10.1080/15402002.2017.1363043
To link to this article: http://dx.doi.org/10.1080/15402002.2017.1363043
Accepted author version posted online: 07
Aug 2017.
Published online: 07 Aug 2017.
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Social Support as a Mediator Between Insomnia and Depression in
Female Undergraduate Students
Soohyun Kim
a
and Sooyeon Suh
a,b
a
Department of Psychology, Sungshin Women’s University, Seoul, Korea;
b
Department of Psychiatry and Behavioral
Sciences, Stanford University, Stanford, California
ABSTRACT
Objectives/Background: Despite findings that insomnia and depression have
a bidirectional relationship, the exact psychological mechanisms that link
these disorders are largely unknown. The goal of this study was to identify
whether social support mediates the relationship between insomnia and
depression. Methods: The study sample (N= 115) consisted of females only,
and all participants (mean age 21.77 ± 1.80) completed self-report measures
of insomnia severity, depression, and social support. Results: Insomnia
severity was significantly associated with low levels of social support
(B=−1.04, SE = .27, p< .001) and high levels of depression (B= .18,
SE = 0.05, p< .001). Social support mediated the effects of insomnia on
depression (95% CI [.03, .15]). However, social support did not mediate the
effects of depression on insomnia (95% CI [–.01, .32]). Conclusions: These
findings suggest that interpersonal factors such as social support may be an
important factor to consider in female insomnia patients in the context of
preventing depression in this population.
Insomnia and depression are major problems of public health and are highly comorbid. Sixty-seven
percent of individuals with major depressive disorder (MDD) also meet criteria for insomnia
(Franzen & Buysse, 2008). A number of studies have shown that insomnia can lead to the develop-
ment of depression (Baglioni et al., 2011; Baglioni, Spiegelhalder, Lombardo, & Riemann, 2010;
Riemann, 2009). In a meta-analysis by Baglioni et al., (2011), nondepressed individuals with sleep
difficulties have a twofold risk of developing depression compared to individuals without insomnia.
In addition, insomnia patients with depression have worse clinical outcomes compared to patients
who have insomnia only (Buysse et al., 2008; Staner, 2010). For instance, each disorder may serve to
exacerbate or maintain one another (Staner, 2010). Thus the strong bidirectional association between
insomnia and depression has been established (Alvaro, Roberts, & Harris, 2013; Buysse et al., 2008;
Jansson-Fröjmark & Lindblom, 2008; Kim et al., 2009; Tsuno, Besset, & Ritchie, 2005). Therefore,
research is needed to identify mechanisms of how insomnia confers to depression.
An increasing body of literature explores the impact of social support or interpersonal relation-
ships on psychological disturbance (Gunn, Troxel, Hall, & Buysse, 2014; Johnson, Cuellar, &
Gershon, 2016; Väänänen, Marttunen, Helminen, & Kaltiala-Heino, 2014). According to multiple
studies, social support has been shown to be significantly associated with depression, with low levels
of social support being a risk factor for depression (Bettge et al., 2008; Kaltiala-Heino, Rimpelä,
Rantanen, & Laippala, 2001; Newman, Newman, Griffen, O’Connor, & Spas, 2007) and high social
support playing a protective role against the development of depression (Denny, Fleming, Clark, &
Wall, 2004; Piko, Kovacs, & Fitzpatrick, 2009).
Social support has also been implicated as an important factor to consider in insomnia research.
While sleep has traditionally been viewed as an intrapersonal problem, recent research has gained
CONTACT Sooyeon Suh alysuh@sungshin.ac.kr #911 Sungshin Building, 2 Bomun-ro 34 da-gil, Seongbuk-gu, Seoul, Korea.
© 2017 Taylor & Francis Group, LLC
BEHAVIORAL SLEEP MEDICINE
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attention on the interpersonal aspects of insomnia (Chu et al., 2016; Rogojanski, Carney, & Monson,
2013). Insomnia affects social support in several ways. First, insomnia affects one’s ability to
interpret social information (Beattie, Kyle, Espie, & Biello, 2015). For example, insomnia has an
effect on social cognition, including prejudice and perspective taking, which may in turn affect social
relationships and attenuate social support (Singer, 2012). Additionally, sleep loss has been associated
with impaired social functioning and neural systems such as mirror neuron systems related to social
emotions, compassion, and empathy (Anderson & Dickinson, 2010; Killgore et al., 2007; Libedinsky
et al., 2011; Singer, 2012). Second, poor sleepers have less chance to be supported from others
(Chu et al., 2016). It is common for insomnia patients to limit their social activities because of increased
fatigueandisolatethemselvesinanattempttoextendtheiropportunitytosleep.Inaddition,they
perceive daily stressors to be more stressful than do good sleepers (Morin, Rodrigue, & Ivers, 2003),
which may increase reactivity to interpersonal conflict. These processes demonstrate how insomnia is
associated with overall social functioning and social support.
Considering previous research, the impact of social support may be an underlying mechanism
through which insomnia is linked to depression. In considering the influence of sleep on social
support, one potential mechanism by which insomnia may lead to depression is low social support.
Despite evidence of this hypothesized pathway, the relation between insomnia, social support, and
depression has largely been understudied.
College years have especially been shown to be a high-risk period for insomnia and depression
because of challenges of varying schedules and environments (Gress-Smith, Roubinov, Andreotti,
Compas, & Luecken, 2015). Furthermore, females are more affected by depression and insomnia
compared to males (Roth, 2007; Van De Velde, Bracke, & Levecque, 2010). Females indicate twice
higher prevalence of depression and gender is identified as a risk factor of insomnia, with an
increased prevalence in females (Roth, 2007; Van De Velde et al., 2010). In addition, sleep dis-
turbance could lead to low levels of social support, primarily for females (Hasler & Troxel, 2010).
In order to better understand the psychological mechanisms that underlie the relationship
between insomnia and depression, the present study aimed to investigate the role of social support
in the relationship between insomnia and depression in female undergraduates, using a cross-
sectional study design. We hypothesized that social support will mediate the relationship between
insomnia and depression.
Methods
Participants and procedures
A sample of students was recruited from a university in Seoul, Korea. Data were collected in
September of 2015. All participants were currently enrolled in undergraduate psychology courses,
and they had the option of participating in the study or completing an alternative assignment for
course credit. Informed consent was obtained from all individual participants included in the study.
Participants identified times they were available, and were contacted via e-mail to set up an
appointment to visit the laboratory. All participants visited the laboratory and completed online
questionnaires of insomnia, depression, and social support along with other demographic informa-
tion, which took 15–20 min to complete.
The current study was approved by the institutional review boards from the institutions where the
samples were recruited.
Measures
Demographic information
Demographic information was collected from participants, including their gender, age, and
education.
2S. KIM AND S. SUH
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Insomnia Severity Index
The Insomnia Severity Index (ISI; Bastien, Vallieres, & Morin, 2001)is a 7-item self-report ques-
tionnaire designed to assess the subjective symptoms and consequences of insomnia (Bastien et al.,
2001). Each item is scored on a 0–4 Likert scale, with total scores ranging from 0 to 28. A higher
score suggests more severe insomnia. Scores higher than 15 on the ISI indicate clinical insomnia
(Bastien et al., 2001). Internal consistency was good in the current samples (Cronbach’sα= .82).
Hospital Anxiety and Depression Scale
The Hospital Anxiety and Depression Scale (HADS; Zigmond & Snaith, 1983)is a 14-item self-
report questionnaire designed to assess state of anxiety and depression (Zigmond & Snaith, 1983). It
composes two subscales, with seven anxiety and seven depression items. Each item is scored on a 0–3
Likert scale, with total scores ranging from 0 to 21. A higher score reflects higher levels of anxiety
and depression. For the current study, we used the 7-item depression subscale. Scores higher than 8
on the depression subscale are regarded as clinical depression. Internal consistency was good in the
current sample (Cronbach’sα= .86).
Scale of Social Support
The Scale of Social Support (SSS; Park, 1985)is a 25-item self-report questionnaire designed to
measure perceived support through others, including four types of social support behavior; appraisal
support, emotional support, informational support, and material support (Park, 1985). Appraisal
support means affirmation or positive feedback from others, while emotional support is the form of
affective behaviors including love, trust, listening, and caring. Informational support is advice or
suggestion and material support is a tangible resource or aid such as money, time, or labor (Park,
1985). Each item is scored on a 1–5 Likert scale, with total scores ranging from 25 to 125. A higher
score indicates higher social support from others. The SSS demonstrated excellent internal consis-
tency in the present study samples (Cronbach’sα= .96).
Statistical analysis
Prior to analysis, data were cleaned and checked for technical errors. All 115 participants completed
every item in the study and no cases were removed.
Analyses were conducted using SPSS software version 21.0 (SPSS Inc., Chicago, IL, USA).
Descriptive statistics and frequency analysis were used to analyze demographic variables.
Correlations were used to examine relationships of major factors such as insomnia, depression,
and social support.
To estimate the mediating effect of social support on the association between insomnia and
depression, we conducted the mediation model with one mediator (Hayes, 2013) and bootstrap
analysis using SPSS PROCESS (Hayes, 2013). Sobel’s method has usually tested the significance of
the Baron and Kenny style mediation effect by multiple regression. However, this method might
have increased the likelihood of Type I error and caused decreased power in small samples
(MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002; MacKinnon, Lockwood, & Williams,
2004). Thus, we conducted the bootstrap analysis to estimate the mediation effect that was recom-
mended when the sample size and mediating effect are both small (Cheung, 2007). For bootstrap
analysis, 100 is a justifiable minimum sample size to lower statistical errors (Koopman, Howe,
Hollenbeck, & Sin, 2015). In addition, a bootstrapping procedure was performed to examine for
mediation effect without assuming normality of sampling distribution (MacKinnon et al., 2002).
When the confidence interval (CI) does not include the value 0, the indirect effect is significant
(Hayes, 2013). In the current study, bootstrapping was done with 5,000 resamples and bias-corrected
95% CIs were used to investigate the indirect effects.
BEHAVIORAL SLEEP MEDICINE 3
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Results
Descriptive statistics and correlates
We conducted analyses on 115 students who completed questionnaires (mean age 21.77 ± 1.80;
100% females). Fifty-six participants (48.7%) reported no insomnia and depression, 19 (16.5%)
reported insomnia only, 19 (16.5%) reported depression only, and 21 (18.3%) reported both
insomnia and depression. In addition, there were significant correlations between all major factors,
including insomnia, depression, and social support (all ps < .01). Insomnia and depression were
positively correlated and social support was negatively correlated with insomnia and depression
(see Table 1 for descriptive statistics and correlates).
Social support as a mediator in the effect of insomnia on depression
Figure 1 presents results of the bootstrapped regression and mediation model for the effects of
insomnia on depression through social support. The overall model accounted for approximately 18%
of the variance in depression (R
2
= .18, F[1, 113] = 26.36, p< .001). Insomnia significantly predicted
social support (B=−1.04, standard error [SE] = .27, p< .001) and social support significantly
predicted depression (B=–.07, SE = .01, p< .001). The direct effects of insomnia on depression
remained significant after controlling for the effects of social support (B= .18, SE = 0.05, p< .001).
The confidence intervals for the indirect effect of social support did not contain 0 (95% confidence
interval (CI [.03, .15]), suggesting that social support was a significant mediator in the relationship
between insomnia and depression. The effect size (kappa-squared) for the mediating effect was .13
(CI [.05, .23]), yielding a medium-range effect size.
Table 2 shows that indirect effect of insomnia on depression through four types of social
support using the four subscales of the material support, emotional support, appraisal support,
and informational support. All types of social support (material support, emotional support,
Table 1. Descriptive statistics and correlations of indicators of insomnia, depression, and social support (N= 115).
1. ISI 2. HADS 3. SSS
1. ISI 1
2. HADS .44** 1
3. SSS −.34** −.49** 1
M(SD) 12.81 (5.32) 6.26 (3.28) 97.27 (16.33)
Range 4–26 0 –18 49 –125
**p< .01.
Note. Abbreviations: ISI = Insomnia Severity Index; HADS = Hospital Anxiety and Depression Scale; SSS = Scale of Social Support.
Social support
Depression
Insomnia
.18 (.05)***
–1.04 (.27)
*** –.07 (.01)
***
Figure 1. Model with social support as a mediator in the effect of insomnia on depression.
Note. Unstandardized coefficients are presented with standard errors in parentheses. The indirect effect of insomnia
on depression through social support was significant (95% confidence interval [.03, .15]). ***p< .001.
4S. KIM AND S. SUH
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appraisal support, and informational support) mediated the relationship between insomnia and
depression.
Social support does not mediate the effect of depression on insomnia
Reverse mediation model for the effects of depression on insomnia through social support was
presented in Figure 2. The overall model accounted for approximately 18% of the variance in
insomnia (R
2
= .18, F[1, 113] = 26.36, p< .001). However, the confidence intervals for the indirect
effect of social support contained 0 (95% CI [–.01, .32]), suggesting that social support was not a
significant mediator in the effect of depression on insomnia.
Discussion
The current study examined social support as a mediator between insomnia and depression in
female undergraduates. The bidirectional relationship between insomnia and depression has been
established (Alvaro et al., 2013; Buysse et al., 2008; Jansson-Fröjmark & Lindblom, 2008; Kim et al.,
2009; Tsuno et al., 2005). But most studies have been focused on clarifying shared neurobiological
mechanisms (Benca & Peterson, 2008) and little is known about the underlying psychological
mechanisms. Our study results indicated that social support mediated the effect of insomnia on
depression. However, social support was not a significant factor in the effects of depression on
insomnia. These results suggest that low social support could be one pathway that insomnia confers
to high risk for depression.
There are several possible interpretations for the link between insomnia and social support. First,
poor sleep could affect an individual’s ability to interpret social information. Previous research
suggested that sleep loss associated with social decision making and social emotion such as fairness,
compassion, and empathy (Singer, 2012). The lack of ability to interpret social information may have
a negative effect on social interaction and these processes may further lead to social support deficits,
Table 2. Indirect effect of insomnia on depression through four types of social support (5,000 bootstrap samples).
BC 95% CI
Mediator BSELower Upper
Emotional Support .07 .03 .03 .15
Material Support .06 .02 .03 .13
Appraisal Support .06 .02 .02 .14
Informational Support .04 .02 .01 .11
Note. Abbreviations: B = Unstandardized coefficient; SE = Standard Error of indirect effect; BC = Bias Corrected; CI = Confidence
Interval.
Social support
Insomnia
Depression
.57 (.15)***
–2.43 (.40)
*** –.05 (.03)
Figure 2. Model with social support as a mediator in the effect of depression on insomnia.
Note. Unstandardized coefficients are presented with standard errors in parentheses. The indirect effect of insomnia
on depression through social support was not significant (95% confidence interval [–.01, .32]). ***p< .001.
BEHAVIORAL SLEEP MEDICINE 5
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resulting in low levels of social support. Second, poor sleepers tend to use ineffective coping skills
and they perceived daily stressors as more stressful than good sleepers did (Morin et al., 2003). It is
common for insomnia patients to limit their social activities when they experience insomnia
symptoms, as they may view social activities in the nighttime as interfering with their bedtime
routine. Additionally, increased fatigue due to insomnia symptoms may also limit their social
activities, which in turn may lead to social isolation. Finally, individuals who are sleep-deprived
look less attractive and trustworthy (Axelsson et al., 2010; Todorov, 2008). Such factors may affect
social interaction and social support negatively. Although we did not investigate these factors, it will
be important to examine the social behaviors that individuals with insomnia engage in that results in
deficits in social support in future research.
The current study expands the literature by suggesting the role of social support in the relation-
ship between insomnia and development of depression. This may partially be explained by the
shared biological mechanism of stress reactivity and activation of the hypothalamic-pituitary-adrenal
(HPA) axis (Buckley & Schatzberg, 2005). Both depression and insomnia have been associated with
HPA axis activation (McKay & Zakzanis, 2010; Vreeburg et al., 2009). And social support has a
buffering effect on stress and decrease activation of HPA axis (Hostinar, Sullivan, & Gunnar, 2014).
Thus, low levels of social support make individuals with insomnia more vulnerable to stressful life
events and increases the likelihood of depression to occur via activation of the HPA axis. It will be
informative for future studies to explore the role of physiological markers of social support, such as
oxytocin, in the role of insomnia and depression.
Interestingly, social support did not mediate the effects of depression on insomnia. There can be several
explanations for this. With few exceptions, a number of studies have shown that depressed individuals
report less social support compared to nondepressed individuals (Dobson & Dozois, 2011;Lakey&
Orehek, 2011; Väänänen et al., 2014). Because depressed individuals already have low levels of social
support, social support may be a less important factor to consider in the relationship from depression to
insomnia, as these individuals are already socially isolated. A study by Cacioppo, Hawkley, and Thisted
(2010) which investigated the effects of social isolation and depression in a five-year longitudinal study
found that social isolation at an earlier time point significantly predicted depression at a later time point,
but not vice versa (Cacioppo et al., 2010). Additionally, considering the cross-sectional nature of our study
design, the strong associations between depression, insomnia, and social support may have obscured the
weaker association between insomnia and social support. Further longitudinal studies will be needed to
clarify the mediation effect of social support between insomnia and depression.
The role of social support in the relationship of insomnia leading to higher risk of depression has
several important clinical implications. Previous studies have shown that insomnia patients with
depression have worse clinical outcomes compared to patients who have insomnia only (Buysse
et al., 2008; Staner, 2010). Each disorder may serve to maintain or exacerbate one another and these
processes may impede recovery (Staner, 2010). From a clinical point of view, our findings suggest
that addressing social support could contribute to preventing development of depression throughout
insomnia treatment. For example, including therapeutic components to enhance social support, such
as social skills training, in an insomnia treatment program would be useful. Additionally, emphasiz-
ing treatment modalities such as behavioral activation in insomnia treatment could help prevent
insomnia patients from isolating themselves by limiting social activities due to insomnia symptoms.
Further, the current study indicated that four types of social support—material support, emotional
support, appraisal support, and informational support—all mediated the relationship between
insomnia and depression. These findings suggest that various type of social support could have an
effect on the development of depression for individuals who have insomnia.
This study has several limitations. The current study was conducted on female undergraduates.
Therefore, the result may not be generalizable to general or clinical populations. Our sample
especially showed a relatively high average score on the ISI (M= 12.81, SD = 5.32) compared to
other studies. This was slightly higher than other studies that measured ISI scores in Korean
undergraduates (mean age = 21.53, 74.5% female, ISI average score = 8.45; Chu et al., 2016)and
6S. KIM AND S. SUH
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U.S. undergraduates (mean age = 18.7, 55% female, ISI average score = 10.7; Gress-Smith et al.,
2015). This difference does not appear to be explained by cross-cultural differences, but may be
due to our sample consisting of females only. Females indicate twice higher prevalence of
insomnia and a number of studies have shown that females are more affected by depression or
insomnia compared to men (Roth, 2007; Van De Velde et al., 2010). We speculate that the higher
average of ISI scores in our sample may be due to these gender differences. Additionally, Hasler
and Troxel found that sleep disturbance predicted negative social interactions, primarily for
females, but not males (Hasler & Troxel, 2010). Insomnia, depression, and the role of social
support should also be examined in both genders in future studies. Second, there may have been
cultural differences. Considering that South Korea is a collectivistic culture, it is possible that
individuals who grow up in collectivistic cultures seek for more social support networks (Kim,
Sherman, & Taylor, 2008) and have higher social sensitivity (Way & Lieberman, 2010). Future
studies should be conducted on populations of various ages, genders, and cultures. Third,
although Koopman and colleague (2015) suggested that 100 is a good minimum sample size to
lower statistical errors for bootstrapping methods, the sample size was relatively small in this
study. It would be helpful to test a larger sample size to generalize the findings. Fourth, insomnia
in our study was measured by self-report assessment. Although previous studies indicated that ISI
is useful to assess the subjective symptoms and consequences of insomnia (Bastien et al., 2001),
including objective measurements such as polysomnography, actigraphy, or sleep diaries in future
studies may help to measure sleep deprivation or sleep patterns more objectively and consistently.
Finally, the current study was cross-sectional design. Thus, it precluded inferences verifying
causality related to insomnia, social support, and depression. Utilizing a longitudinal design in
future studies may be informative to assess a causal relationship among insomnia, social support,
and depression.
Funding
This work was supported by the Sungshin University Research Grant of 2017 (2017-1-11-021).
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