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Perceived Partner Responsiveness Predicts Better Sleep Quality Through Lower Anxiety


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The present study investigated whether perceived partner responsiveness—the extent to which individuals feel cared for, understood, and validated by their partner—predicted subjective sleep problems and objective (actigraph-based) sleep efficiency through lower anxiety and depression symptoms. A life span sample of 698 married or cohabiting adults (35–86 years old) completed measures of perceived partner responsiveness and subjective sleep problems. A subset of the sample (N = 219) completed a weeklong sleep study where actigraph-based measures of sleep efficiency were obtained. Perceived partner responsiveness predicted lower self-reported global sleep problems through lower anxiety and depression and greater actigraph-assessed sleep efficiency through lower anxiety. All indirect associations held after controlling for emotional support provision to the partner, agreeableness, and demographic and health covariates known to affect sleep quality. These findings are among the first to demonstrate how perceived partner responsiveness, a core aspect of romantic relationships, is linked to sleep behavior.
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Perceived Partner Responsiveness
Predicts Better Sleep Quality
Through Lower Anxiety
Emre Selcuk
, Sarah C. E. Stanton
, Richard B. Slatcher
and Anthony D. Ong
The present study investigated whether perceived partner responsiveness—the extent to which individuals feel cared for,
understood, and validated by their partner—predicted subjective sleep problems and objective (actigraph-based) sleep efficiency
through lower anxiety and depression symptoms. A life span sample of 698 married or cohabiting adults (35–86 years old)
completed measures of perceived partner responsiveness and subjective sleep problems. A subset of the sample (N¼219)
completed a weeklong sleep study where actigraph-based measures of sleep efficiency were obtained. Perceived partner
responsiveness predicted lower self-reported global sleep problems through lower anxiety and depression and greater actigraph-
assessed sleep efficiency through lower anxiety. All indirect associations held after controlling for emotional support provision to
the partner, agreeableness, and demographic and health covariates known to affect sleep quality. These findings are among the
first to demonstrate how perceived partner responsiveness, a core aspect of romantic relationships, is linked to sleep behavior.
perceived partner responsiveness, sleep, marriage, well-being, anxiety
Sleep is a critical health behavior reducing the risk for morbid-
ity and mortality (e.g., Dew et al., 2003; Reid et al., 2006).
Given the well-established link between social relationships
and health (e.g., Holt-Lunstad, Smith, & Layton, 2010),
research has increasingly focused on the role of close relation-
ships in sleep. Although both sleep quality (Dew et al., 2003)
and total sleep duration (Shen, Wu, & Zhang, 2016) have been
linked to health outcomes, social relationships or lack thereof
have typically been found to be linked with sleep quality—for
instance, subjective evaluations of how well individuals sleep
or how much daytime dysfunction they experience, or objec-
tive assessments of sleep efficiency (the ratio of time spent
sleeping to the time spent in bed)—rather than total duration
(Bordeleau, Bernier, & Carrier, 2012; Cacioppo et al., 2002).
These findings suggest that social relationships are associated
with reduced nonrestorative sleep, which is defined as sleep
that is interrupted with frequent awakenings and not refreshing,
despite normal duration (Hawkley, Preacher, & Cacioppo,
2010). Restorative sleep depends on perceived absence of
threat in the environment and downregulation of arousal. Per-
sistent high arousal—a marker of anxiety—disrupts sleep by
increasing nightly awakenings and resulting in poorer daytime
functioning. Social relationships are thought to counteract this
process, as they are a potent source of safety and protection,
and they downregulate perceptions of threat (Eisenberger
et al., 2011) and physiological arousal (Slatcher, Selcuk, &
Ong, 2015).
Given that adult sleep is typically a shared activity between
romantic partners (National Sleep Foundation, 2013) and
romantic relationships have a unique capacity to influence the
quality of human health and well-being (Loving & Slatcher,
2013), the role of marital and cohabiting relationships in sleep
quality has received increased research attention (Troxel,
2010). Although studies have established that individuals’
sleep quality is closely linked to how happy (or unhappy) they
are in their relationship, the psychological processes through
which relationships affect sleep are still not well understood
(Troxel, 2010). Growing work, primarily led by social psychol-
ogists, aiming at explaining the psychological pathways by
which long-term romantic relationships are linked to physical
health demonstrates that relationship processes (e.g.,
Middle East Technical University, Ankara, Turkey
Wayne State University, Detroit, MI, USA
Cornell University, Ithaca, NY, USA
Corresponding Author:
Emre Selcuk, Middle East Technical University, B45 Human Sciences Building,
Ankara 06800, Turkey.
Social Psychological and
Personality Science
ªThe Author(s) 2016
Reprints and permission:
DOI: 10.1177/1948550616662128
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responsiveness, support provision) predict psychological
symptoms (e.g., anxiety, depression) and well-being (e.g., life
satisfaction), which in turn predict physical health (for reviews,
see Slatcher, 2010; Slatcher & Selcuk, in press). In the few
studies taking this approach (e.g., the links between self-
disclosure to one’s partner and sleep quality; Kane, Slatcher,
Reynolds, Repetti, & Robles, 2014), the small sample sizes
limited the ability to detect between-person differences and
sleep quality was measured only with self-reports. However,
a multimethod approach to measuring sleep is important
because self-reported sleep quality is at best weakly correlated
with objective measures such as actigraphy (Grandner, Kripke,
Yoon, & Youngstedt, 2006), suggesting that the two types of
measures tap different aspects of sleep quality. Whereas self-
reports typically measure subjective (dis)satisfaction about
sleep quality, actigraphy provides indices of objective sleep
disruptions during a night’s interval. The two measures are also
differentially related to health and well-being (e.g., Lemola,
Ledermann, & Friedman, 2013; Liu et al., 2013). It may be the
case that romantic relationships may be associated with one
type of sleep measure but not the other, or they may predict
both subjective and objective sleep quality but through differ-
ent psychological mechanisms.
Perceived partner responsiveness (i.e., the extent to which
individuals perceive their partner as caring, understanding, and
appreciative; Reis, 2007) may be one important process by
which romantic relationships affect sleep quality. In this study,
we investigated the associations between perceived partner
responsiveness and sleep quality in a large sample using both
self-report measures of sleep problems and an objective
actigraph-based measure of sleep efficiency. The large sample
size provided us with sufficient statistical power to investigate
the potential psychological mechanisms through which partner
responsiveness is associated with sleep. Specifically, we tested
two potential mediators of the link between perceived partner
responsiveness and sleep quality—anxiety and depressed affect
two classes of psychological symptoms that are among the
most common predictors of sleep disturbances (Koffel & Wat-
son, 2009)—hypothesizing that perceived partner responsive-
ness would positively predict sleep quality through lower
anxiety and depressive symptoms.
Perceived Partner Responsiveness and
Perceived partner responsiveness has been identified as a key
process that influences the extent to which romantic relation-
ships are satisfying and intimate. It focuses on partners’ posi-
tive responses to each other in contrast to negative responses
or indifference (Reis, 2007). When one perceives her or his
partner as caring, understanding, and appreciative, one is more
likely to self-disclose and also to react responsively to the part-
ner’s disclosures. When this process is enacted reciprocally and
mutually, it reinforces the development and maintenance of
intimacy in the relationship (Reis & Patrick, 1996).
Of particular relevance to the present study, a central func-
tion of perceived partner responsiveness involves downregulat-
ing anxiety and arousal and instilling a sense of security and
quiescence (Selcuk, Zayas, & Hazan, 2010). When individuals
encounter threats and stressors, the primary coping strategy for
most adults is to turn to their partners for safety and protection
(Mikulincer & Shaver, 2007). Responsive partner support dur-
ing these times alleviates distress and downregulates anxious
arousal. Indeed, when individuals were faced with an
anxiety-provoking experience in the laboratory (e.g., talking
about a stressful problem or anticipating giving a public
speech), their partner’s responsive support alleviated both
self-reported (Collins & Feeney, 2000) and observer-rated
(Simpson, Rholes, & Nelligan, 1992) anxiety. Repeated
responsive interactions with partners translate over time to a
long-term decline in anxiety, both psychologically and physio-
logically (e.g., endocrine functioning; Feeney & Collins,
2015). For instance, a recent daily experience study (Slatcher
et al., 2015) demonstrated that high partner responsiveness pre-
dicts a steeper decline in diurnal cortisol a decade later, sug-
gesting that the effect of responsiveness goes beyond the
immediate stressful context and may potentially be associated
with lower chronic levels of anxiety over the long term. This
finding is important in the present context also given that prior
work has linked steeper diurnal cortisol slopes to lower anxious
arousal (Doane et al., 2013), which would be expected to pre-
dict higher quality sleep.
Responsiveness (or lack thereof) is also thought to be one
key process that explains how social relationships affect
depression across the life span (Bowlby, 1980). More specif-
ically, relationships are argued to reduce an individual’s risk
for depression to the extent that a partner’s support (a) effec-
tively meets the demands of the stressful life situations and (b)
does not undermine the individual’s sense of autonomy
(Ibarra-Rovillard & Kuiper, 2011). Those who are perceived
as responsive are more likely to engage in support behaviors
that are appropriately contingent on the demands of the situ-
ation (Collins, Guichard, Ford, & Feeney, 2006) and, more-
over, their support also enhances the partner’s autonomy,
self-efficacy, and independent goal pursuit (Feeney, 2007).
Thus, it is not surprising that perceived partner responsiveness
is a strong predictor of lower symptoms of depression in daily
life (Fekete, Stephens, Mickelson, & Druley, 2007; Khan
et al., 2009).
Prior studies have illuminated consistent associations
between anxiety, depression, and sleep quality as well
(Alvaro, Roberts, & Harris, 2013; Koffel & Watson, 2009;
Magee & Carmin, 2010; Revenson, Marı´n-Chollom, Rundle,
Wisnivesky, & Neugut, 2016). Increasing research indicates
that disruptions in nighttime sleep is associated with indica-
tors of physiological hyperarousal such as increased meta-
bolic rates, heart rate variability, and cortisol output (for a
review, see Stepanski & Rybarczyk, 2006). Watson and
colleagues (1995) referred to these indicators as anxious
arousal, and in extensive work with both clinical and noncli-
nical samples of adults from different age-groups, they
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showed that these symptoms are specific to anxiety (and not
to depression). In a similar vein, they found that loss of
interest and low positive affect, which are collectively
referred to as anhedonic depression, are specific to depres-
sion (and not anxiety; Watson et al., 1995). Focusing on
these nonoverlapping aspects of anxiety and depression is
important to identify specifically through which symptoms
partner responsiveness would be linked to different aspects
of sleep quality.
The Present Research
The present study aimed to further extend our conceptual
understanding of how partner responsiveness is linked to health
and well-being by investigating the role of perceived partner
responsiveness in sleep. Importantly, we tested the associations
of perceived partner responsiveness with both self-report mea-
sures of sleep problems and an objective actigraph-based
assessment of sleep efficiency—that is, the ratio of total sleep
time to the total time spent in bed. Based on prior theorizing
and empirical work on social relationships and sleep (Borde-
leau et al., 2012; Cacioppo et al., 2002; Hawkley et al.,
2010), we prioritized testing the links between partner respon-
siveness and sleep quality, although we included sleep duration
in analyses as well.
Moreover, we investigated the potential mechanisms by
which perceived partner responsiveness was linked to sleep.
Specifically, we chose anxiety and depression, given their
well-established links to both perceived partner responsive-
ness (Selcuk et al., 2010; Slatcher et al., 2015) and sleep
quality (Alvaro et al., 2013; Koffel & Watson, 2009;
Revenson et al., 2016). Given the theoretical function of
partner responsiveness in downregulating arousal and anxi-
ety (Selcuk et al., 2010) and prior empirical work docu-
menting that perceived partner responsiveness predicts
lower depression and anxiety (e.g., Fekete et al., 2007;
Simpson et al., 1992), we expected that perceived partner
responsiveness would be meaningfully linked to sleep qual-
ity via its associations with those two symptomologies, a
hypothesis hitherto unexplored in the relationships and
health literatures. Previous research indicated that individu-
als project their own support provision to their partner, that
is, individuals who provide more support to their partner
are more likely to perceive their partner as responsive
(Lemay, Clark, & Feeney, 2007). Moreover, individuals
who perceive their partner as responsive may be more
agreeable people in general. Thus, following prior work
on partner responsiveness (Slatcher et al., 2015), we con-
trolled for emotional support provision to the partner and
agreeableness in the analyses. In addition, our analysis con-
trolled for demographic factors (age, gender, race, and edu-
cation) and physical health factors (perceived health, health
symptoms, and body mass index [BMI]) known to affect
sleep quality (Mezick, Wing, & McCaffery, 2014; Ong
et al., 2013).
Sample and Procedure
The data for the present study came from the National Survey
of Midlife Development in the United States II (MIDUS II), a
study on health and aging conducted in 2004–2006 (N¼4,963;
age range ¼32–84). The MIDUS II survey consisted of a
phone interview and a self-administered questionnaire (Ryff
et al., 2007). Upon completion of MIDUS II, a subset of
respondents (N¼1,255) participated in the Biomarkers Study
(Dienberg Love, Seeman, Weinstein, & Ryff, 2010), which
included sleep assessments. Mean time lag between the
MIDUS II self-administered questionnaire and the Biomarkers
Study was 25 months (SD ¼14 months). The current sample
consisted of 698 married or cohabiting adults (mean age ¼
57 years, range ¼35–86 years) who completed the perceived
partner responsiveness measure, all covariates, and at least one
of the sleep measures (self-reported global quality or objective
sleep efficiency) and reported still being together with their
partner over the course of data collection (i.e., between the
MIDUS II phone interview and the Biomarkers Study). Of
these participants, 50%were female and 50%male; 94%were
White and 6%were from other racial backgrounds; 24%grad-
uated from high school or less and 76%had some college edu-
cation or more. In the final sample, 479 participants completed
only the self-reported global sleep quality measure, 16 com-
pleted only the objective sleep efficiency measure, and 203
completed both measures. Thus, analyses testing the associa-
tions of perceived partner responsiveness with global sleep
quality and objective sleep efficiency were based on 682 and
219 adults, respectively. Participants who had data for objec-
tive sleep efficiency were slightly younger (M¼56.22, SD
¼10.86 vs. M¼58.03, SD ¼11.28, p¼.048, d¼.16, 95%
CI [0.02, 3.59]) and scored slightly lower on anxiety (M¼
20.84, SD ¼4.20 vs. M¼21.54, SD ¼4.41, p¼.047, d¼
.16, 95%CI [0.01, 1.40]). The two groups, however, did not
differ on other variables of interest including perceived partner
responsiveness, global sleep quality, depression, or any of the
covariates (ps > .071).
Perceived partner responsiveness. Following prior work (Selcuk,
Gunaydin, Ong, & Almeida, 2016; Selcuk & Ong, 2013;
Slatcher et al., 2015), perceived partner responsiveness was
measured with 3 items in the MIDUS II self-administered ques-
tionnaire. Participants indicated the extent to which their part-
ner or spouse cares about them, understands the way they feel
about things, and appreciates them (1 ¼alotto 4 ¼not at all,
a¼.82). Responses were reverse scored, so that higher scores
reflected greater partner responsiveness.
Anxiety and depression symptoms. Anxiety and depression were
assessed in the Biomarker Study using the Anxious Arousal
subscale of the Mood and Symptom Questionnaire (MASQ;
Watson et al., 1995), measuring specific anxiety symptoms
Selcuk et al. 3
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(somatic tension and hyperarousal) that are critical for sleep
quality (Stepanski & Rybarczyk, 2006), and the Anhedonic
Depression subscale measuring specific depression symptoms
(low positive affect and loss of interest). Prior work showed
that these subscales are less correlated with each other (r¼
.369, p< .001 in the current sample) and show higher discrimi-
nant validity compared to other measures of anxiety and
depression while maintaining convergent validity, in both clin-
ical and nonclinical samples (Watson et al., 1995). Participants
indicated how much they experienced each symptom during
the past week (1 ¼not at all to 5 ¼extremely). The Anxious
Arousal subscale consisted of 17 items (e.g., ‘‘heart was racing
or pounding’’) and the Anhedonic Depression subscale con-
sisted of 22 items (e.g., ‘‘felt nothing was very enjoyable’’).
Anxiety and depression scores were computed by summing
across all items for participants who had no missing value (for
participants who had a missing value for only 1 item, mean sub-
stitution was used for the item), a¼.73 for anxiety and .93 for
Sleep outcomes. All sleep assessments were obtained in the Bio-
marker Study. Global sleep quality was measured with the
widely used Pittsburgh Sleep Quality Index (PSQI; Buysse,
Reynolds, Monk, Berman, & Kupfer, 1989). The PSQI
includes subjective assessments of seven sleep components:
sleep quality (overall assessment of sleep quality), sleep
latency (time and difficulty to fall asleep at night), sleep dura-
tion (hours of sleep gotten at night), habitual sleep efficiency
(the ratio of actual sleep to the time spent in bed), sleep distur-
bance (trouble staying asleep), use of sleeping medication, and
daytime dysfunction (trouble staying awake during daytime).
Each category receives a score between 0 and 3, with higher
scores reflecting worse sleep quality. Although the components
measure different aspects of sleep, the PSQI is typically ana-
lyzed using a global score, especially given that all components
reflect an underlying subjective (dis)satisfaction with sleep
(e.g., Grandner et al., 2006). Thus, in line with prior work using
the PSQI, a global sleep problems index was computed by sum-
ming the seven sleep components for each participant with
complete data (a¼.69; see Online Supplemental Material for
supplemental analyses using the component scores separately).
Objective sleep outcomes were measured by collecting acti-
graphy data. Participants wore a Mini Mitter Actiwatch1-64
activity monitor on their nondominant wrist for 7 consecutive
days and nights starting on a Tuesday morning at 7:00 a.m. and
ending the next Tuesday morning. Using a built-in sensor, the
monitor detects the number of movements made by the wearer.
The start and end times of actigraphic records were determined
using diary logs in which participants entered their bedtime and
risetime. Activity counts within 30-s epochs were used to esti-
mate sleep statistics. Whether participants were asleep or
awake was estimated by comparing activity counts in each
epoch and the epochs surrounding it to a predetermined thresh-
old value. Sleep duration was computed by summing the
epochs, in minutes, marked as sleep during a night’s interval
(the difference between the start and end times logged in the
diary). Sleep efficiency was computed as the percentage ratio
of total sleep time to the total time spent in bed. Sleep effi-
ciency may suffer due to two reasons: difficulty to fall asleep
or difficulty to stay asleep. Therefore, sleep onset (a measure
of difficulty falling asleep) and wake after sleep onset (a mea-
sure of difficulty staying asleep) were also included in the anal-
yses to figure out which aspects of sleep efficiency were linked
with partner responsiveness. Sleep onset corresponded to the
time required, in minutes, for the onset of sleep after attempting
to get to sleep. Finally, wake after sleep onset corresponded to
the total time of awakenings during the night’s interval after
falling asleep.
Demographic covariates. Demographic covariates included age
at completion of the Biomarker study, and gender (0 ¼male,
1¼female), race (0 ¼White,1¼Non-White), and education
(1 ¼no school/some grade school to 12 ¼doctoral degree)
assessed at MIDUS II.
Physical health covariates. We controlled for three physical health
predictors of sleep quality: perceived physical health, health
symptoms, and BMI. Perceived physical health was measured
in the MIDUS II phone interview via a single item asking par-
ticipants to evaluate their physical health (1 ¼excellent to 5 ¼
poor). Participants also completed a health symptoms checklist
(e.g., ‘‘ever had heart disease?’’ ‘‘ever had cancer?’’) in the
Biomarker Study. The total number of health symptoms ever
experienced was included in the analyses. Finally, the BMI was
computed by dividing weight in kilograms by height squared in
meters. These measurements were obtained by clinical staff
during a physical exam as part of the Biomarker Study.
Relationship covariates. Emotional support provision to the part-
ner was measured by a single item asking how many hours per
month participants give emotional support to their partner (e.g.,
comforting, lending a listening ear, giving advice; Rossi,
2001). Given the open-ended nature of the item, there were
some outliers with very high values on this variable. Responses
higher than 2.5 standard deviations of the mean were recoded
to the highest value below 2.5 standard deviations to reduce the
influence of the outliers on the results.
Agreeableness was measured by asking participants the
extent to which each of five adjectives (helpful, warm, caring,
softhearted, sympathetic) described them (1 ¼alotto 4 ¼not
at all; Rossi, 2001). Responses were reverse coded, so that
higher scores indicated greater agreeableness (a¼.81).
Table 1 provides the correlations among variables of interest.
As in prior work (Grandner et al., 2006), the PSQI global score
showed weak correlations with the actigraph assessments (all
rs < .24), suggesting that the two measures tap different aspects
of sleep quality. Looking at the specific PSQI components that
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Table 1. Descriptive Statistics and Correlations Among Variables.
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1. Partner
2. Sleep problems
.144*** –
3. Sleep efficiency
.015 .159* –
4. WASO (actigraph) .118 .242*** .608*** –
5. Sleep onset
.039 .089 .728*** .197**
6. Sleep duration
.036 .068 .549*** .032 .358*** –
7. Anxiety .148*** .359*** .186** .294*** .053 .008 –
8. Depression .212*** .401*** .070 .054 .042 .042 .369*** –
9. Agreeableness .110** .005 .097 .026 .168* .035 .071 .212*** –
10. Provision of
emotional support
.142*** .046 .092 .041 .067 .134* .002 .045 .106** –
11. Poor perceived
.049 .256*** .195** .218** .153* .009 .340*** .346*** .044 .039 –
12. Health symptoms .001 .254*** .131 .193** .175** .070 .308*** .164*** .076* .056 .345***
13. BMI .069 .062 .176** .114 .151* .147* .104** .092* .014 .048 .240*** .151***
14. Age .137*** .073 .138
.150* .086 .002 .021 .172*** .086* .069 .022 .355*** .004
15. Education .028 .033 .011 .071 .012 .077 .124*** .066 .094* .110** .119** .006 .059 .059 –
16. Race
.046 .015 .031 .035 .035 .068 .038 .067 .031 .029 .162*** .014 .080* .108** .031 –
17. Gender
.151*** .162*** .313*** .126 .230*** .316*** .096* .012 .221*** .101** .034 .068 .100** .167*** .049 .014
M3.592 5.640 82.975 42.522 24.001 384.913 21.321 50.534 3.420 27.546 2.280 3.930 29.092 57.460 7.830
SD 0.538 3.357 7.887 18.391 20.921 62.514 4.356 12.338 0.496 38.758 0.909 2.807 5.565 11.174 2.449
Note. PSQI ¼Pittsburgh Sleep Quality Index; WASO ¼wake after sleep onset; BMI ¼body mass index. The sample size was 682 for estimates including the PSQI, 219 for estimates including actigraph assessments, and 698
for the remaining estimates.
*p< .05. **p< .01. ***p< .001.
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map onto the actigraph-based measures, PSQI sleep efficiency
was unrelated to the actigraph sleep efficiency (r¼.104,
p¼.140) and the PSQI sleep duration was moderately related
to actigraph sleep duration (r¼.379, p< .001; see Table S1 in
Online Supplemental Materials for all pairs of correlations
between the actigraphy indices and the PSQI components).
Perceived Partner Responsiveness and Self-Reported
Sleep Problems
Participants who perceived their partner as responsive reported
lower sleep problems as measured by the global PSQI score
(B¼.901, SE ¼.237, p< .001). Partner responsiveness also
indirectly predicted lower global sleep problems through lower
anxiety (indirect association [IA] ¼.223, 95%CI: [0.426,
0.081]) and depression (IA ¼.406, 95%CI: [0.620,
0.251]; Figure 1A; see Online Supplemental Materials for
complete details on the data analytic approach for testing indi-
rect associations). Once anxiety and depression were included
in the model, the direct association between partner responsive-
ness and self-reported sleep problems was not significant
(although the effect size was similar to that of the IA through
anxiety, B¼.272, SE ¼.218, p¼.213). The indirect asso-
ciations between perceived partner responsiveness and global
sleep problems held even when the analyses were repeated
by controlling for emotional support provision to the partner,
agreeableness, demographic factors, and physical health fac-
tors (IA ¼.129, 95%CI [0.297, 0.027] for anxiety and
IA ¼.280, 95%CI [0.465, 0.143] for depression; see
Table S2 in Online Supplemental Materials for all direct and
indirect associations between partner responsiveness and the
PSQI subcomponents).
Perceived Partner Responsiveness and Actigraph-
Assessed Sleep Efficiency
Partner responsiveness was not directly associated with
actigraph-assessed sleep efficiency or sleep duration (Table
1). However, partner responsiveness indirectly predicted
greater objective sleep efficiency via lower anxiety (IA ¼
.678, 95%CI [0.100, 2.014]) but not depression (IA ¼.052,
95%CI [0.398, 0.504]; Figure 1B). Improved sleep
Figure 1. The indirect associations of perceived partner responsiveness with global sleep problems (Panel A) and actigraph-assessed sleep
efficiency (Panel B) through anxiety and depression. Numbers outside the parentheses are unstandardized regression coefficients and numbers
inside the parentheses are standard errors. The sample size was 682 in analyses predicting global sleep problems and 219 in analyses predicting
sleep efficiency. PSQI ¼Pittsburgh Sleep Quality Index. **p<.01. ***p< .001.
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efficiency could be due to faster sleep onset or lower wake after
sleep onset. Our findings supported the latter possibility.
Whereas perceived partner responsiveness indirectly predicted
lower wake after sleep onset through lower anxiety (IA ¼
2.495, 95%CI [5.650, 0.728]), it was not associated with
sleep onset (IA ¼.529, 95%CI [03.052, 0.630]). The indi-
rect associations between perceived partner responsiveness and
objective sleep quality through anxiety held, even after adjust-
ing for emotional support provision to the partner, agreeable-
ness, demographic factors, and physical health covariates (IA
¼.566, 95%CI [0.013, 1.856] for sleep efficiency and IA ¼
1.796, 95%CI [4.656, 0.140] for wake after sleep onset).
After adjusting for covariates, partner responsiveness was not
associated with actigraph-assessed sleep duration through anxi-
ety (IA ¼2.195, 95%CI [.719, 10.389]) or depression (IA ¼
1.148, 95%CI [1.113, 5.691]).
These findings are the first to demonstrate how perceived part-
ner responsiveness is linked to subjective and objective sleep
quality. Perceived partner responsiveness predicted lower glo-
bal sleep problems through lower anxiety and depression.
Importantly, perceived partner responsiveness was also associ-
ated with actigraph-assessed sleep efficiency through lower
anxiety (but not depression). These indirect associations
remained significant after we statistically controlled for emo-
tional support provision to the partner, agreeableness, and
demographic (age, gender, race, and education) and health cov-
ariates (perceived health, health symptoms, and BMI) that
could have potentially accounted for the findings.
An important strength of the present study was using a com-
bination of subjective (the PSQI) and objective (actigraph)
sleep measures. Past work showed that the PSQI, the most
widely used subjective sleep quality measure, and actigraph
assessments are not substitutes for each other but rather mea-
sure distinct aspects of sleep quality (Grandner et al., 2006;
Landry, Best, & Liu-Ambrose, 2015). The low correlations
between the PSQI and actigraphy assessments (also replicated
in the present work) have led researchers to suggest that both
measures should be included in sleep studies whenever possi-
ble (Landry et al., 2015). Using the two measures in the same
study enabled us to document the distinct pathways by which
perceived partner responsiveness is associated with sleep.
We found a direct association between partner responsive-
ness and sleep only for the PSQI but not for the actigraph-
assessed sleep quality. Indirect associations were much more
pronounced across both subjective and objective sleep mea-
sures. The more consistent pattern with indirect (vs. direct)
associations is in line with theoretical models explaining how
romantic relationships are associated with physical health
(Burman & Margolin; 1992; Kiecolt-Glaser & Newton, 2001;
Slatcher, 2010; Slatcher & Selcuk, in press). These models sug-
gest that romantic relationship processes are more likely to be
linked to physical health through psychological mechanisms
(e.g., psychological symptoms, well-being) rather than having
a direct effect. The present findings are in line with this theo-
rizing by showing that partner responsiveness is mainly linked
to sleep through psychological symptoms—particularly anx-
ious arousal but also anhedonic depression.
Although partner responsiveness predicted better actigraph-
assessed sleep efficiency through lower anxiety, there was no
such indirect association between partner responsiveness and
actigraph-assessed sleep duration. A prior study on parental
responsiveness and child sleep reached a similar conclusion,
with parental responsiveness predicting parent reports of child
sleep quality but not duration, although that study only focused
on the direct links (Bordeleau et al., 2012). Taken together with
the present findings, it seems that sleep duration is unrelated
to responsiveness of partners or caregivers, but individuals
with less responsive close others experience more disrupted
sleep. This qualitative difference between individuals who
have responsive versus unresponsive partners is important,
as chronic disruptions—that is, inefficient sleep—predicts
important physical health outcomes, including mortality
(Dew et al., 2003).
Depression also mediated the partner responsiveness–sleep
association but only for subjective sleep problems. This finding
replicates prior work on the association between depression
and the PSQI and extends a recent finding that depression med-
iates the association between quality of general social ties and
the global PSQI score (Kent, Uchino, Cribbet, Bowen, &
Smith, 2015). Given our finding that subjective evaluations
of sleep quality do not reflect actual sleep efficiency, depressed
individuals may be negatively biased in their perceptions of
their psychological and physiological states, which may extend
to sleep (Grandner et al., 2006). This is not to say that the PSQI
assessments are irrelevant to sleep quality; on the contrary, sub-
jective sleep quality does predict important health and well-
being outcomes (Lemola et al., 2013; Martin et al., 2011).
Rather, the present findings show the importance of using mul-
tiple measures to study the links between close relationships
and sleep, as the nature of the associations and the mediating
psychological mechanisms may be different across measures.
The present findings also dovetail with and extend past work
investigating the role of romantic attachment orientations in sleep
quality. Insecure (i.e., anxious or avoidant) attachment, which is
thought to result from closeothers’ failure to behave responsively,
has been linked to poor self-reported sleep quality and sleep dis-
turbances such as difficulty falling asleep and staying asleep
(e.g., Adams & McWilliams, 2015; Carmichael & Reis, 2005;
see also Adams, Stoops, & Skomro, 2014, for a review). There
was a significant direct association between perceived partner
responsiveness and subjectivesleep quality in the present sample
as well. In addition, the present study extended and complemen-
ted prior findings by documenting psychological mechanisms
through which partner responsiveness is linked to both self-
reported sleep problems and objectively assessed sleep efficiency.
Recent studies have shown that perceived partner respon-
siveness has relevance for health outcomes including
all-cause mortality (Selcuk & Ong, 2013). There is increasing
evidence that partner responsiveness predicts potential
Selcuk et al. 7
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mechanisms, including affective reactivity to stressors, trait
negative affect, depression, psychological well-being, and diur-
nal cortisol (Fekete et al., 2007; Selcuk et al., 2016; Selcuk,
Zayas, Gunaydin, Hazan, & Kross, 2012; Slatcher et al.,
2015), that may ultimately affect adult morbidity and mortality.
By showing that perceived partner responsiveness predicts self-
reported sleep problems through lower anxiety and depression,
and objective sleep efficiency through lower anxiety, the pres-
ent study extends the set of processes by which perceived part-
ner responsiveness potentially affects physical health.
The findings also have implications for therapy and inter-
vention design. The inherently interdependent nature of adult
romantic relationships means that romantic partners, as well
as perceptions of one’s romantic partner, play a meaningful
role in promoting better health and well-being. Our findings
suggest that enhancing perceived partner responsiveness has
the potential to increase the effectiveness of interventions
designed to reduce sleep disturbances in particular and improve
individual well-being in general.
Before concluding, we acknowledge some limitations of the
present research. These data are correlational, meaning that we
are unable to make claims about the causal direction of the asso-
ciations between partner responsiveness, anxiety and depression,
and sleep. For example, it is possible that partner responsiveness
may be linked to anxiety, depression, and sleep simultaneously,
or poor sleep could have affected scores on the MASQ as well as
individuals’ perceptions of their partner’s responsiveness. The
existing literature, however, makes a stronger theoretical case
for individuals who experience higher partner responsiveness
to have better sleep outcomes, rather than the other way around
(cf. Carmichael & Reis, 2005; Selcuk et al., 2015; Troxel,
Buysse, Hall, & Matthews, 2009). Moreover, the fact that part-
ner responsiveness was assessed on average 25 months before
both the mediating and outcome variables supports this possi-
bility, although we should note that we were not able to model
change in sleep behavior. Related to this point, it may be pos-
sible to observe stronger associations between partner respon-
siveness and sleep in a design with a smaller time interval
between the measurements. For instance, future daily experi-
ence studies may investigate whether daily perceptions of
responsiveness predicts sleep, especially on days participants
experience stressors and exhibit greater anxiety.
A second limitation of the current study involves the diver-
sity of the sample. The MIDUS sample is not racially diverse,
limiting our ability to generalize our findings to non-White
individuals. Furthermore, although the PSQI was administered
at three different study sites (University of California Los
Angeles, University of Wisconsin, and Georgetown Univer-
sity), the subset of participants who provided actigraph data
of sleep quality completed the study at only one site (University
of Wisconsin). Finally, participants were in their middle and
late adulthood, leaving the question of whether the results
would look similar for younger individuals open for future
research. Regardless, the emergence of the partner responsive-
ness–sleep link through lower anxiety in analyses that included
potentially meaningful covariates bolsters our confidence in
the findings. Future studies would benefit from replicating
these findings in a more heterogeneous sample.
In sum, the present study demonstrated the role of perceived
partner responsiveness in subjective and objective assessments
of sleep quality through lower anxiety and depression. Future
research should further elucidate the mechanisms by which
higher partner responsiveness exerts a salutary influence on
health and well-being.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.
The author(s) disclosed receipt of the following financial support for the
research, authorship, and/or publication of this article: The MIDUS II
research was supported by a grant from the National Institute on Aging
(P01-AG020166). The Biomarker Project was further supported by the
following grants: M01-RR023942 (Georgetown), M01-RR00865
(UCLA) from the General Clinical Research Centers Program and
UL1TR000427 (UW) from the National Center for Advancing Transla-
tional Sciences (NCATS), National Institutes of Health.
Supplemental Material
The online data supplements are available at
adult attachment style and sleep disturbances in a nationally repre-
sentative sample. Journal of Psychosomatic Research,79, 37–42.
Retrieved from
Exploring the relationship between sleep and attachment style
across the life span. Sleep Medicine Reviews,18, 495–507.
Retrieved from
review assessing bidirectionality between sleep disturbances, anxi-
ety, and depression. Sleep,36, 1059–1068. Retrieved from http://
Bordeleau, S., Bernier, A., & Carrier, J. (2012). Longitudinal associa-
tions between the quality of parent–child interactions and chil-
dren’s sleep at preschool age. Journal of Family Psychology,26,
254–262. Retrieved from
Bowlby, J. (1980). Attachment and loss: Loss, sadness and depression.
New York, NY: Basic Books.
Burman, B., & Margolin, G. (1992). Analysis of the association
between marital relationships and health problems: An interac-
tional perspective. Psychological Bulletin,112, 39–63. doi:10.
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R., & Kupfer,
D. J. (1989). The Pittsburgh Sleep Quality Index: A new instru-
ment for psychiatric practice and research. Psychiatry Research,
28, 193–213. Retrieved from
8Social Psychological and Personality Science
by guest on August 18, 2016spp.sagepub.comDownloaded from
Cacioppo, J. T., Hawkley, L. C., Berntson, G. G., Ernst, J. M., Gibbs, A.
C., Stickgold, R., & Hobson, J. A. (2002). Do lonely days invade the
nights? Potential social modulation of sleep efficiency. Psychologi-
cal Science,13, 384–387. doi:10.1111/1467-9280.00469
and depressed affect. Health Psychology,24, 526–531. Retrieved
Collins, N. L., & Feeney, B. C. (2000). A safe haven: An attachment
theory perspective on support seeking and caregiving in intimate
relationships. Journal of Personality and Social Psychology,78,
1053–1073. Retrieved from
Collins, N. L., Guichard, A. C, Ford, M. B., & Feeney, B. C. (2006).
Responding to need in intimate relationships: Normative processes
and individual differences. In M. Mikulincer & G. S. Goodman
(Eds.), Dynamics of romantic love: Attachment, caregiving, and
sex (pp. 149–189). New York, NY: Guilford Press.
Dew, M. A., Hoch, C. C., Buysse, D. J., Monk, T. H., Begley, A. E.,
Houck, P. R., ...Reynolds, C. F. (2003). Healthy older adults’
sleep predicts all-cause mortality at 4 to 19 years of follow-up. Psy-
chosomatic Medicine,65, 63–73.
(2010). Bioindicators in the MIDUS national study: protocol, mea-
sures, sample, and comparative context. Journal of Aging and
Health,22, 1059–1080. Retrieved from
Doane, L. D., Mineka, S., Zinbarg, R. E., Craske, M., Griffith, J. W., &
Adam, E. K. (2013). Are flatter diurnal cortisol rhythms associated
with major depression and anxiety disorders in late adolescence?
The role of life stress and daily negative emotion. Development
and Psychopathology,25, 629–642.
Eisenberger, N. I., Master, S. L., Inagaki, T. K., Taylor, S. E., Shirin-
yan, D., Lieberman, M. D., & Naliboff, B. D. (2011). Attachment
figures activate a safety signal-related neural region and reduce
pain experience. Proceedings of the National Academy of Sciences
of the United States of America,108, 11721–11726. doi:10.1073/
Feeney, B. C. (2007). The dependency paradox in close relationships:
Accepting dependence promotes independence. Journal of Person-
ality and Social Psychology,92, 268–285. Retrieved from http://
Feeney, B. C., & Collins, N. L. (2015). Thriving through relationships.
Current Opinion in Psychology,1,2228.Retrievedfromhttp://
(2007). Couples’ support provision during illness: The role of
perceived emotional responsiveness. Families, Systems, &
Health,25, 204–217. Retrieved from
(2006). Criterion validity of the Pittsburgh Sleep Quality Index:
Investigation in a non-clinical sample. Sleep and Biological
Rhythms,4, 129–136. doi:10.1111/j.1479-8425.2006.00207.x
Hawkley, L. C., Preacher, K. J., & Cacioppo, J. T. (2010). Loneliness
impairs daytime functioning but not sleep duration. Health Psy-
chology,29, 124–129. doi:10.1037/a0018646.
Holt-Lunstad, J., Smith, T. B., & Layton, J. B. (2010). Social relation-
ships and mortality risk: A meta-analytic review. PLoS Medicine,
7,e1000316. doi:10.1371/journal.pmed.1000316
Ibarra-Rovillard, M. S., & Kuiper, N. A. (2011). Social support and
social negativity findings in depression: Perceived responsiveness
to basic psychological needs. Clinical Psychology Review,31,
342–352. Retrieved from
Kane, H. S., Slatcher, R. B., Reynolds, B. M., Repetti, R. L., & Robles,
T. F. (2014). Daily self-disclosure and sleep in couples. Health
Psychology,33, 813–22. Retrieved from
Kent, R. G., Uchino, B. N., Cribbet, M. R., Bowen, K., & Smith, T. W.
(2015). Social relationships and sleep quality. Annals of Beha-
vioral Medicine,49, 912–917. doi:10.1007/s12160-015-9711-6
Khan, C. M., Iida, M., Stephens, M. A. P., Fekete, E. M., Druley, J. A.,
& Greene, K. A. (2009). Spousal support following knee surgery:
Roles of self-efficacy and perceived emotional responsiveness.
Rehabilitation Psychology,54, 28–32. Retrieved from http://doi.
Kiecolt-Glaser, J. K., & Newton, T. L. (2001). Marriage and health:
His and hers. Psychological Bulletin,127, 472–503. doi:10.1037/
Koffel, E., & Watson, D. (2009). The two-factor structure of sleep
complaints and its relation to depression and anxiety. Journal of
Abnormal Psychology,118, 183–194. Retrieved from http://doi.
Landry, G. J., Best, J. R., & Liu-Ambrose, T. (2015). Measuring sleep
quality in older adults: A comparison using subjective and objec-
tive methods. Frontiers in Aging Neuroscience,7, 166.
Lemay, E. P., Clark, M. S., & Feeney, B. C. (2007). Projection of
responsiveness to needs and the construction of satisfying commu-
nal relationships. Journal of Personality and Social Psychology,
92, 834–853. doi:10.1037/0022-3514.92.5.834
Lemola, S., Ledermann, T., & Friedman, E. M. (2013). Variability of
sleep duration is related to subjective sleep quality and subjective
well-being: An actigraphy study. PLoS ONE,8, e71292.
Liu, L., Fiorentino, L., Rissling, M., Natarajan, L., Parker, B. A.,
Dimsdale,J.E.,...Ancoli-Israel, S. (2013). Decreased health-
related quality of life in women with breast cancer is associated
with poor sleep. Behavioral Sleep Medicine,11, 189–206. doi:
Loving, T. J., & Slatcher, R. B. (2013). Romantic relationships and
health. In J. A. Simpson & L. Campbell (Eds.), The Oxford hand-
book of close relationships (pp. 617–637). New York, NY: Oxford
University Press.
Magee, J. C., & Carmin, C. N. (2010). The relationship between sleep
and anxiety in older adults. Current Psychiatry Reports,12, 13–19.
Retrieved from
Martin, J. L., Fiorentino, L., Jouldjian, S., Mitchell, M., Josephson,
K. R., & Alessi, C. A. (2011). Poor self-reported sleep quality
predicts mortality within one year of inpatient post-acute rehabi-
litation among older adults. Sleep,34, 1715–1721. doi:10.5665/
Mezick, E. J., Wing, R. R., & McCaffery, J. M. (2014). Associations
of self-reported and actigraphy-assessed sleep characteristics with
body mass index and waist circumference in adults: Moderation by
Selcuk et al. 9
by guest on August 18, 2016spp.sagepub.comDownloaded from
gender. Sleep Medicine,15, 64–70. Retrieved from
Mikulincer, M., & Shaver, P. R. (2007). Attachment patterns in adult-
hood: Structure, dynamics, and change. New York, NY: Guilford
National Sleep Foundation. (2013). International bedroom poll: Sum-
mary of Findings. Arlington, VA: Author.
Ong, A. D., Exner-Cortens, D., Riffin, C., Steptoe, A., Zautra, A., &
Almeida, D. M. (2013). Linking stable and dynamic features of
positive affect to sleep. Annals of Behavioral Medicine,46,
52–61. Retrieved from
Reid, K. J., Martinovich, Z., Finkel, S., Statsinger, J., Golden, R., Har-
ter, K., & Zee, P. C. (2006). Sleep: A marker of physical and men-
tal health in the elderly. The American Journal of Geriatric
Psychiatry,14, 860–866. Retrieved from
Reis, H. T. (2007). Steps toward the ripening of relationship science.
Personal Relationships,14, 1–23. Retrieved from
Reis, H. T., & Patrick, B. C. (1996). Attachment and intimacy: Com-
ponent processes. In E. T. Higgins & A. W. Kruglanski (Eds.),
Social psychology: Handbook of basic principles (pp. 523–563).
New York, NY: Guilford Press.
Revenson, T. A., Marı´n-Chollom, A. M., Rundle, A. G., Wisnivesky,
J., & Neugut, A. I. (2016). Hey Mr. Sandman: Dyadic effects of
anxiety, depressive symptoms and sleep among married couples.
Journal of Behavioral Medicine,39, 225–232.
Rossi, A. S. (2001). Caring and doing for others: Social responsibility
in the domains of family, work, and community. Chicago, IL: Uni-
versity of Chicago Press.
Ryff, C. D., Almeida, D. M., Ayanian, J. S., Carr, D. S., Cleary, P. D.,
Coe, C., ...Williams, D. (2007) Midlife Development in the United
States (MIDUS II), 2004–2006 [Computer file]. ICPSR04652-v1.
Ann Arbor, MI: Inter-university Consortium for Political and
Social Research [distributor]. doi:10.3886/ICPSR04652
Selcuk, E., Gunaydin, G., Ong, A. D., & Almeida, D. M. (2016). Does
partner responsiveness predict hedonic and eudaimonic well-
being? A 10-year longitudinal study. Journal of Marriage and
Family,78, 311–325.
Selcuk, E., & Ong, A. D. (2013). Perceived partner responsiveness
moderates the association between received emotional support and
all-cause mortality. Health Psychology,32, 231–235. Retrieved
Selcuk, E., Zayas, V., Gunaydin, G., Hazan, C., & Kross, E. (2012).
Mental representations of attachment figures facilitate recovery
following upsetting autobiographical memory recall. Journal of
Personality and Social Psychology,103, 362–378. doi:10.1037/
Selcuk, E., Zayas, V., & Hazan, C. (2010). Beyond satisfaction: The
role of attachment in marital functioning. Journal of Family The-
ory & Review,2, 258–279. Retrieved from
Shen, X., Wu, Y., & Zhang, D. (2016) Nighttime sleep duration, 24-
hour sleep duration and risk of all-cause mortality among adults:
A metaanalysis of prospective cohort studies. Scientific Reports,
6, 21480. doi:10.1038/srep21480
Simpson, J. A., Rholes, W. S., & Nelligan, J. S. (1992). Support seek-
ing and support giving within couples in an anxiety-provoking sit-
uation: The role of attachment styles. Journal of Personality and
Social Psychology,62, 434–446. Retrieved from
Slatcher, R. B. (2010). Marital functioning and physical health: Impli-
cations for social and personality psychology. Social and Person-
ality Psychology Compass,4, 455–469. doi:10.1111/j.1751-9004.
Slatcher, R. B., & Selcuk, E. (in press). A social psychological per-
spective on the links between close relationships and health. Cur-
rent Directions in Psychological Science.
Slatcher, R. B., Selcuk, E., & Ong, A. D. (2015). Perceived partner
responsiveness predicts diurnal cortisol profiles 10 years later. Psy-
chological Science,26, 972–982. Retrieved from
Stepanski, E. J., & Rybarczyk, B. (2006). Emerging research on the
treatment and etiology of secondary or comorbid insomnia. Sleep
Medicine Reviews,10, 7–18. doi:10.1016/j.smrv.2005.08.002
Troxel, W. M. (2010). It’s more than sex: Exploring the dyadic nature
of sleep and implications for health. Psychosomatic Medicine,72,
578–586. Retrieved from
Marital happiness and sleep disturbances in a multi-ethnic sample
of middle-aged women. Behavioral Sleep Medicine,7, 2–19.
Retrieved from
Watson, D., Weber, K., Assenheimer, J. S., Clark, L. A., Strauss, M. E.,
& McCormick, R. A. (1995). Testing a tripartite model: I.
Evaluating the convergent and discriminant validity of anxiety
and depression symptom scales. Journal of Abnormal Psychol-
ogy,104, 3–14. Retrieved from
Author Biographies
Emre Selcuk is an assistant professor in the Department of Psychol-
ogy at Middle East Technical University, Turkey. His research focuses
on the formation, maintenance, and functions of attachment relation-
ships across the life span.
Sarah C. E. Stanton is a postdoctoral fellow at Wayne State Univer-
sity. She uses a social psychological approach to understand the cog-
nitive and affective aspects of close relationships and their effects on
behavior, physiology, and health and well-being.
Richard B. Slatcher is an associate professor of social psychology at
Wayne State University. His research has two main facets: basic
research on close relationship processes and investigations of the links
between close relationships, biological processes, and physical health.
Anthony D. Ong is an associate professor of human development at
Cornell University and an associate professor of gerontology in med-
icine at Weill Cornell Medical College. His research focuses on the
dynamic processes that underlie expressions of vulnerability and
adaptation across the life span.
Handling Editor: Nickola Overall
10 Social Psychological and Personality Science
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... In non-patient samples, perceived partner responsiveness has been associated with health outcomes including all-cause mortality [23], diurnal cortisol profiles [24], and sleep quality [25]. This relationship between perceived partner responsiveness and sleep quality may be due in part to a reduction in anxious arousal when one feels understood, validated, and cared for thus creating an optimal environment for sleep [25]. ...
... In non-patient samples, perceived partner responsiveness has been associated with health outcomes including all-cause mortality [23], diurnal cortisol profiles [24], and sleep quality [25]. This relationship between perceived partner responsiveness and sleep quality may be due in part to a reduction in anxious arousal when one feels understood, validated, and cared for thus creating an optimal environment for sleep [25]. Moreover, research suggests that partner responsiveness may also benefit the responding partner (attempted partner responsiveness), such that compassionate acts like demonstrating understanding and acceptance are associated with greater emotional well-being for both the provider and recipient [26]. ...
... The observed actor effects are consistent with the limited body of research in non-patient samples on partner responsiveness and sleep, suggesting that greater perceived partner responsiveness is associated with better sleep outcomes [25]. In the current study, the degree to which the survivor or partner went to bed feeling validated, understood, or cared for was associated with better subjective sleep that same night. ...
Full-text available
Purpose Breast cancer (BC) survivors and their intimate partners face several adverse consequences from the cancer experience, including sleep disturbance, which is a common side effect of BC and its treatment. Sleep has been conceptualized and examined as an individual phenomenon despite most adults sharing a bed/room with a partner. Limited research has examined the associations between daily relationship processes and sleep in couples coping with cancer. Using an intensive longitudinal design, the present study examined the daily, within-person links between attempted and perceived partner responsiveness and subjective sleep. Methods Immediately following adjuvant treatment, 72 early-stage BC survivors and their intimate partners (144 paired individuals) reported on daily attempted and perceived partner responsiveness each evening and subjective sleep each morning for 21 consecutive days. Results Survivor and partner reports of partner responsiveness were associated with their own subjective sleep, such that greater attempted and perceived partner responsiveness were associated with improvements in one’s own subjective sleep. Effects of one participant’s partner responsiveness on their partner’s sleep were not observed. Conclusions Findings suggest that among couples coping with early-stage BC, increased partner responsiveness is associated with subsequent improvements in subjective sleep. Implications for cancer survivors Sleep disturbance is a serious concern for BC survivors and their intimate partners. Future research should assess intimacy processes as a potential method to improve BC survivor and partner sleep.
... Interpersonal security contributes to psychophysiological responses that could impact sleep onset and quality (Palagini et al., 2018). For instance, partner responsiveness, as a characteristic of interpersonal security, predicts lower arousal and consequently contributes to better sleep outcomes (Selcuk et al., 2017). Additionally, for most adults, sleep is a dyadic behavior. ...
... The role of social factors in sleep outcomes among older adults has also been explored. These studies show that social support such as partner responsiveness predicts better sleep outcomes (Selcuk et al., 2017) and social strain is associated with poorer sleep (Chung, 2017). Although sleep has been characterized in numerous publications in MIDUS datasets, the moderating role of gender in the association between quality of social relationships and sleep is lacking. ...
Full-text available
To determine whether the association between perceived social support or strain in close relationships and sleep outcomes varies by gender. Participants were selected from the Biomarker projects of either the MIDUS II or MIDUS Refresher study if they were in a married-or married-like relationship and shared a bed with their partner ( N = 989). A subsample also participated in a seven-day sleep study ( n = 282). Perceived social support and strain from partner, family, and friends were examined by self-report questionnaires. We used the Pittsburgh Sleep Quality Index, sleep daily diary, and actigraphy to measure both subjective and objective sleep. Social support and strain were both associated with sleep outcomes. Specifically, higher social support was associated with fewer daily reports of light sleep and feeling more rested in the morning, while higher social strain was associated with higher clinical sleep disturbance. For women, but not men, social support was significantly associated with lower daily sleep disturbance while perceived social strain was significantly associated with higher daily sleep disturbance, lighter sleep, feeling less rested in the morning, lower sleep efficiency, and longer sleep onset latency. Mainly among women, social support and strain are associated with an important transdiagnostic health outcome–sleep–which may have implications for a wide range of health disparities. Interpersonal stressors may increase health risks differently for women compared to men and one mechanism that may link social relationships to long-term health outcomes is sleep.
... Extensive research has demonstrated the relevance of perceived partner responsiveness to relationship well-being. For example, perceived partner responsiveness has been shown to underlie effective social support (Maisel & Gable, 2009) and its role in lowering all-cause mortality (Selcuk & Ong, 2013), while promoting gratitude (Algoe & Zhaoyang, 2016), caregiving (Canevello & Crocker, 2010;Lemay & Clark, 2008), attraction to potential romantic partners (Birnbaum & Reis, 2012;Reis, 2020), constructive conflict resolution (Overall & McNulty, 2017), beneficial outcomes of sharing personal good news (Gable, Gosnell, & Maisel, 13 Sociability Matters & Strachman, 2012;Reis et al., 2010), sexual satisfaction and desire (Birnbaum et al., 2016), forgiveness (Pansera & La Guardia, 2012), security-enhancing interactions (Simpson, Rholes, Oriña, & Grich, 2002), effective partner support of goal-directed activity (Rusbult, Kumashiro, & Reis, 2010), sleep quality (Selcuk, Stanton, Slatcher, & Ong, 2017), pain management (O'Neill, Mohr, Bodner, & Hammer, 2020), marital conversations about end-of-life care (Moorman, 2011), and coping with COVID-related stress (Slatcher et al., 2021). Partner responsiveness is likely to be a key variable not only in personal relationships, but also in all forms of human sociability in general. ...
Extensive research has documented people’s desire for social partners who are responsive to their needs and preferences, and that when they perceive that others have been responsive, they and their relationships typically thrive. For these reasons, perceived partner responsiveness is well-positioned as a core organizing theme for the study of sociability in general, and close relationships in particular. Research has less often addressed the downstream consequences of perceived partner responsiveness for cognitive and affective processes. This gap in research is important, because relationships provide a central focus and theme for many, if not most, of the behaviors studied by social psychologists. This chapter begins with an overview of the construct of perceived partner responsiveness and its centrality for relationships. We then review programs of research demonstrating how perceived partner responsiveness influences three core social-psychological processes: self-enhancing social cognitions, attitude structure, and emotion regulation. The chapter concludes with a brief overview of how deeper incorporation of relationship processes can enhance the informativeness and completeness of social psychological theories.
... It may be that regular relationships are associated with greater comfort and partner responsiveness (i.e. feeling understood, cared for, and validated), which leads to more positive sleep outcomes 32 . Further, shorter sleep latency may result from reduced physiological arousal, as sleeping next to a regular partner can improve physical and emotional security, causing a down regulation of arousal levels and an increase in sleep quality and duration 24 . ...
Full-text available
Objective: Insufficient sleep, and particularly difficulties initiating sleep, are prevalent in the community. Treatment for poor sleep typically consists of pharmacological intervention, or cognitive behavioural therapies - which can be both costly and time-consuming. Evidence suggests that sexual activities may positively impact sleep. However, little is known about relationship types, sexual activities, and perceived sleep outcomes. The aim of this study was to explore the association between relationship type (e.g., having a regular, occasional, or casual partner), sexual activity and satisfaction, and perceived sleep outcomes, to identify potential strategies to improve sleep. Methods: Seven-hundred and seventy-eight participants aged 18 years and over (442 females, 336 males; mean age 34.5 ± 11.4 years) responded to a cross-sectional online anonymous survey at their convenience. Participants were asked about their sleep, sexual activity and satisfaction, and relationship type. Results: Results from multiple regression analyses with age and gender covariates revealed that shorter sleep latencies were associated with regular relationships (p = 0.030), greater emotional satisfaction with sexual activity (p = 0.029), and increased frequency of orgasm (p < 0.001). Men reported a greater frequency of orgasm than women (p < 0.001). Discussion: Findings indicate that relationship type may be associated with improved sleep outcomes, including sleep latency. Relationship type should therefore be taken into consideration by clinicians when developing treatment plans for individuals with poor sleep.
... Perceived partner responsiveness has been shown to predict numerous beneficial outcomes, such as intimacy (Laurenceau et al., 2004), emotional well-being and happiness (Selcuk & Karagobek, 2018), emotional openness , personal growth and sleep efficiency (Selcuk, Stanton, Slatcher, & Ong, 2017), self-esteem (Cortes & Wood, 2018;Murray et al., 2000), and even lower mortality risk (Selcuk & Ong, 2013). In this vein, and supporting our proposal about the relevance of responsiveness to interpersonal emotion dynamics, research shows that perceived partner responsiveness to emotional self-disclosures are more strongly tied to important relational outcomes such as intimacy than to factual selfdisclosures (Laurenceau, Barrett, & Pietromonaco, 1998). ...
Emotions are not only fundamentally dynamic in nature in the sense of varying across time, but they are also fundamentally social, originating in and shaping our interpersonal processes. Interpersonal emotion dynamics refer to the ways in which emotions and emotional self-regulation are dynamically influenced by interactional partners, given the interdependence that exists between them. We begin this chapter by describing the premise for interpersonal emotion dynamics in intimate relationships, what interpersonal emotion dynamics constitute, and the state of the art in the fields of emotion science, relationship science, and interpersonal emotion dynamics. Next, we discuss two key themes that we believe promote theoretical integration among seemingly disparate strands of research (in emotion and relationship research), emphasizing the importance of interdependence and perceived partner responsiveness in the interpersonal emotion dynamics that characterize intimate relationships. The chapter concludes with recommendations for future research in this promising area.
Chronotype can be defined as an overt expression of circadian rhythmicity in an individual that dictates tendencies towards being a morning or evening person - also referred to as 'morningness' or 'eveningness.' Chronotypes generally impact preferred bed and wake times, in addition to a range of personal and social factors. This study examined how matching/mismatching chronotypes within relationships impact sexual satisfaction and sleep quality. A sample of 32 couples (52% females, 38.3 ± 11.7 years) each completed an online survey that assessed chronotype (reduced Morningness Eveningness Questionnaire), sleep (Pittsburgh Sleep Quality Index), and sexual satisfaction (Index of Sexual Satisfaction). Partner surveys were matched to identify whether chronotypes were matching or mismatching. Couples with matched chronotypes reported greater sexual satisfaction than those with mismatched chronotypes, F(1, 58) = 19.57, p < .001. Matched couples also reported better sleep quality than couples whose chronotypes were mismatched, F(1,62) = 48.02, p < .001. The individual chronotype did not seem to impact on sleep quality or sexual satisfaction. To improve sleep quality and sexual satisfaction, strategies (e.g., circadian phase advance or delay) could be used to increase circadian alignment between members of a couple.
This study examines the associations between marital quality and anxiety using meta‐analytic techniques. A total of k = 151 effects published between the years 2000 and 2019 were analyzed. It was hypothesized that better overall marital quality would be associated with less anxiety. Results showed significant associations between marital quality and anxiety in such a way that higher overall marital quality was associated with lower anxiety. Post hoc analyses revealed that higher levels of positive marital behaviors (e.g., communication and intimacy) and fewer negative marital behaviors (e.g., criticism) were associated with lower anxiety. Additional results examined potential moderators of the association between marital quality and anxiety, including study design, direction of longitudinal associations (i.e., marital quality predicting anxiety or vice versa), gender, assessment of anxiety, and the use of control variables to account for comorbidities and demographic factors. Findings from this study provide a comprehensive review of the associations between marital quality and anxiety, which may be used to inform future research and treatment. 本研究利用荟萃分析技术研究了婚姻质量和焦虑之间的关联性。一共分析了2000‐2019年期间发表的K = 151影响因子文章。本研究的假设为整体婚姻质量和焦虑两者有相关性。结果显示,婚姻质量和焦虑之间有明显的关联性,即婚姻整体质量较高,相应的焦虑较低。事后分析显示,更高水平的积极婚姻行为(如沟通、亲密关系)和更少的消极婚姻行为(如批评)都与低焦虑水平有关联性。其他研究结果探讨了婚姻质量和焦虑之间关联的潜在调节因素,包括研究设计、纵向关联的方向(即婚姻质量预测焦虑或反之)、性别、焦虑的评估,以及使用控制变量来说明合并症和人口统计因素。这项研究的结果对婚姻质量和焦虑之间的关联进行了全面的回顾,可用于指导未来的研究和治疗。
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This study examines the impact of bereavement on self-esteem and life satisfaction in both partners of a romantic couple. We investigate the moderating effects of the type of the lost relationship (close family, close friends/others) and romantic relationship characteristics (daily social support, responsiveness-closeness, self-disclosure). We examined 1238 individuals in 619 male–female couples from the ages 18 to 81 ( M [ SD] = 31.97 years [13.26]). Both partners completed questionnaires at two assessments that were 20 months ( SD = 2.02 months) apart, in between which n = 216 individuals were bereaved. Actor–partner interdependence models showed that bereavement did not predict later self-esteem or life satisfaction in either of the partners. The relationship characteristics and the type of lost relationship did not moderate the effects. The subjective meaning and distress of the loss predicted later self-esteem and life satisfaction. The self-esteem increase was larger for bereaved with a positive/neutral than for bereaved with a negative meaning of the bereavement. We found a partner effect on self-esteem for the group of bereaved who reported a negative meaning of the bereavement. The findings demonstrate that bereavement can impact romantic partners' self-esteem and that the subjective experience of bereavement helps understand individual differences in the effect of bereavement on self-esteem and life satisfaction.
The COVID‐19 pandemic, an external stressor with multiple stressful sequelae, has fundamentally changed people's lives over multiple years. In this article, we first review research demonstrating that the pandemic has negatively impacted people's sense of belonging and health over time. Next, we draw upon decades of theoretical and empirical work demonstrating that threats to belonging and mental health problems are highly interrelated, with increases in the former driving increases in the latter. We then extend this discussion to physical health, drawing upon a wealth of theoretical and empirical work demonstrating that threats to belonging are a risk factor for longer term health problems and premature mortality. We also highlight potential mechanisms linking threats to belonging and health, with a focus on sleep and immune function. Throughout, we review how pre‐existing vulnerabilities may moderate these processes. We conclude with empirically supported recommendations for policymakers interested in addressing these issues.
The study of intimate relationships and health is a fast-growing discipline with numerous well-developed theories, many of which outline specific interpersonal behaviors and psychological pathways that may give rise to good or poor health. In this article, we argue that the study of relationships and health can move toward interrogating these mechanisms with greater precision and detail, but doing so will require a shift in the nature of commonly used research methods in this area. Accordingly, we draw heavily on the science of behavior change and discuss six key methodologies that may galvanize the mechanistic study of relationships and health: dismantling studies, factorial studies, experimental therapeutics, experimental mediation research, multiple assessments, and recursive modeling. We provide empirical examples for each strategy and outline new ways in which a given approach may be used to study the mechanisms linking intimate relationships and health. We conclude by discussing the key challenges and limitations for using these research strategies as well as novel ideas about how to integrate this work into existing paradigms within the field.
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The association between the quality of people’s close relationships and their physical health is well established. But from a psychological perspective, how do close relationships impact physical health? This article summarizes recent work seeking to identify the relationship processes and psychological mediators and moderators of the links between close relationships and health, with an emphasis on studies of married and cohabitating couples. We begin with a brief review of a recent meta-analysis of the links between marital quality and health. We then describe our strength and strain model of marriage and health, homing in on one process—partner responsiveness—and one moderator—adult attachment style—to illustrate ways in which basic relationship science can inform our understanding of how relationships impact physical health. We conclude with a brief discussion of promising directions in the study of close relationships and health.
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A dose-response meta-analysis was conducted to summarize evidence from prospective cohort studies about the association of nighttime sleep duration and 24-hour sleep duration with risk of all-cause mortality among adults. Pertinent studies were identified by a search of Embase and PubMed databases to March 2015. A two-stage random-effects dose–response meta-analysis was used to combine study-specific relative risks and 95% confidence intervals [RRs (95% CIs)]. Thirty-five articles were included. Compared with 7 hours/day, the RRs (95% CIs) of all-cause mortality were 1.07 (1.03–1.13), 1.04 (1.01–1.07), 1.01 (1.00–1.02), 1.07 (1.06–1.09), 1.21 (1.18–1.24), 1.37 (1.32–1.42) and 1.55 (1.47–1.63) for 4, 5, 6, 8, 9, 10 and 11 hours/day of nighttime sleep, respectively (146,830 death cases among 1,526,609 participants), and the risks were 1.09 (1.04–1.14), 1.05 (1.02–1.09), 1.02 (1.00–1.03), 1.08 (1.05–1.10), 1.27 (1.20–1.36), 1.53 (1.38–1.70) and 1.84 (1.59–2.13) for 4, 5, 6, 8, 9, 10 and 11 hours/day of 24-hour sleep, respectively (101,641 death cases among 903,727 participants). The above relationships were also found in subjects without cardiovascular diseases and cancer at baseline, and other covariates did not influence the relationships substantially. The results suggested that 7 hours/day of sleep duration should be recommended to prevent premature death among adults.
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This study examined associations among anxiety, depressive symptoms, and sleep duration in a sample of middle-aged couples using the actor-partner interaction model with dyadic data. Self-report measures were completed independently by both partners as part of the health histories obtained during their annual preventive medical examinations in 2011 and 2012. Results showed that husbands' anxiety and depressive symptoms had a stronger effect on their wives' anxiety and depression than the other way around, but this was not moderated by one's own sleep duration. For both wives and husbands, higher levels of depressive symptoms and anxiety predicted shorter sleep duration for their partner 1 year later, although the effect of husbands' mental health on their wives' was again stronger. The findings suggest that sleep problems might better be treated as a couple-level phenomenon than an individual one, particularly for women.
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Sleep quality decreases with aging and thus sleep complaints are prevalent in older adults, particularly for those with cognitive impairment and dementia. For older adults, emerging evidence suggests poor sleep quality increases risk of developing cognitive impairment and dementia. Given the aging population—and the impending economic burden associated with increasing numbers of dementia patients—there is pressing need to improve sleep quality among older adults. As such, research efforts have increased focus on investigating the association between age-related sleep changes and cognitive decline in older adults. Sleep quality is a complex construct to evaluate empirically, and yet the Pittsburg Sleep Quality Index (PSQI) is commonly used in studies as their only measure of sleep quality. Furthermore, the PSQI may not be the best sleep quality measure for older adults, due to its reliance on the cognitive capacity to reflect on the past month. Further study is needed to determine the PSQI's validity among older adults. Thus, the current study examined sleep quality for 78 community dwelling adults 55+ to determine the PSQI's predictive validity for objective sleep quality (as measured by actigraphy). We compared two subjective measures of sleep quality—the PSQI and Consensus Sleep Diary (CSD)—with actigraphy (MotionWatch 8©; camntech). Our results suggest perceived sleep quality is quite different from objective reality, at least for adults 55+. Importantly, we show this difference is unrelated to age, gender, education, or cognitive status (assessed using standard screens). Previous studies have shown the PSQI to be a valuable tool for assessing subjective sleep quality; however, our findings indicate for older adults the PSQI should not be used as a substitute for actigraphy, or vice versa. Hence, we conclude best practice is to include both subjective and objective measures when examining sleep quality in older adults (i.e., the PSQI, CSD, and actigraphy).
This report examines the development of nonmetallic fiber based reinforcement in the United States. Much of the research is original and some is influenced or supported by international activities. The current lack of use of these materials in the United States belies the fact that considerable knowledge exists regarding FRP characterization and performance. To put the combined experience into perspective, FRP applications are grouped into functional categories. These categories include; characterization of FRP reinforcement, reinforced concrete structures, prestressed concrete beams, and the mechanics and design of FRP reinforced members. Research needs are identified based on the current development of FRP reinforcement both in the United States and worldwide research.
Motivated by attachment theory and recent conceptualizations of perceived partner responsiveness as a core feature of close relationships, the authors examined change in hedonic and eudaimonic well-being over a decade in a sample of more than 2,000 married adults across the United States. Longitudinal analyses revealed that perceived partner responsiveness-the extent to which individuals believe that their partner cares for, appreciates, and understands them-predicted increases in eudaimonic well-being a decade later. These results remained after controlling for initial hedonic and eudaimonic well-being, age, gender, extraversion, neuroticism, and perceived responsiveness of family and friends. Affective reactivity, measured via an 8-day diary protocol in a subset of the sample, partially mediated this longitudinal association. After controlling for covariates, perceived partner responsiveness did not prospectively predict hedonic well-being. These findings are the first to document the long-term benefits of perceived partner responsiveness on eudaimonic well-being.
This study examined how adult attachment styles moderate spontaneous behavior between dating couples when 1 member of the dyad is confronted with an anxiety-provoking situation. Eighty-three dating couples were unobtrusively videotaped for 5 min in a waiting room while the woman waited to participate in an "activity" known to provoke anxiety in most people. Independent observers then evaluated each partner's behavior on several dimensions. Results revealed that persons with more secure attachment styles behaved differently than persons with more avoidant styles in terms of physical contact, supportive comments, and efforts to seek and give emotional support. Findings are discussed in the context of theory and research on attachment.