Attachment Style and Sleep: Examining the Association Between Relationship Functioning and Physiological Arousal Before Sleep

Attachment style and Sleep: Examining the Association between Relationship Functioning and Physiological Arousal Before Sleep

Antonio Pagan, B.A.

A Thesis

Clinical Psychology

Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfillment of the Requirements for the Degree of

MASTER OF ARTS

Approved

Matthew R. Cribbet, Ph.D. Co-Chair of Committee

Gregory H. Mumma, Ph.D. Co-Chair of Committee

Adam Schmidt, Ph.D.

Mark Sheridan Dean of the Graduate School

August, 2020

Texas Tech University, Antonio Pagan, August 2020

TABLE OF CONTENTS

ABSTRACT...... iii

CHAPTER 1...... 1

INTRODUCTION...... 1

Attachment Style & Sleep...... 2

Measuring Physiological Arousal Prior to Sleep...... 7

The Present Study...... 10

CHAPTER 2...... 12

METHODS...... 12

Participants...... 12

Measures...... 13

Procedures………………………………………………………………..18

Data Analyses Plan...... 18

Data Analytic Strategy and Preparation...... 19

Regression analyses...... 21

CHAPTER 3...... 23

RESULTS...... 23

CHAPTER 4...... 27

DISCUSSION...... 27

LIMITATIONS AND FUTURE DIRECTIONS...... 29

CLINICAL IMPLICATIONS...... 31

CONCLUSIONS...... 33

REFERENCES...... 34

ii Texas Tech University, Antonio Pagan, August 2020

ABSTRACT

Recent theoretical models of relationship functioning and sleep propose that positive (e.g. support, closeness, security) and negative aspects (e.g. conflict, hyperarousal, vigilance, negative emotions) of close relationships, which can be conceptualized as secure and insecure attachment styles, are associated with dimensions of sleep through behavioral, psychological and physiological pathways (Troxel, 2010).

Prior research on adult attachment styles and sleep has produced mixed findings.

Therefore examining both cognitive and physiological arousal prior to sleep may provide a pathway to better understand the associations between attachment style and sleep. The present study used a multi-trait multimethod approach to examine pre-sleep arousal through objective and subjective indices, including the underlying determinants of heart rate (e.g. HF-HRV and PEP), in addition to self-report measures of cognitive and somatic activation prior to sleep onset. Hypothesis 1a & 1b were that anxious and avoidant attachment styles would be negatively associated with objective measures of arousal.

Hypothesis 2 was that anxious attachment would be positively associated with subjective measures of arousal. Finally, hypothesis 3 was that avoidant attachment would not be associated with subjective arousal. Hypothesis 1a, 2, and 3 were supported with hypothesis 1b being partially supported. These findings suggest that anxiously and avoidantly attached individuals experience signifcanly different phsyciological processes prior to sleep with anxiously attached individuals also experiencing significantly greater cognitive arousal prior to sleep.

iii Texas Tech University, Antonio Pagan, August 2020

CHAPTER 1

INTRODUCTION

Attachment theory proposes that early interactions with caregivers creates a working relational framework used to appraise and interact with others (Bowlby, 1969;

Hazan & Shaver, 1987; Bretherton, 1992; Pietromonaco & Barrett, 2000; Brennan et al.,

1998; Fraley & Shaver, 2000). According to attachment theory, securely attached children experience safe, engaged and emotionally available parents, which is associated with a more flexible engagement with and regulation of emotions in close relationships as adults. Insecurely attached children experience emotionally unavailable and/or anxious parents, which is associated with anxiety and avoidance in close relationship as adults.

Insecure attachment can be further dichotomized into avoidant and anxious attachment.

Anxiously attached individuals tend to experience higher levels of anxiety in close relationships and avoidantly attached individuals tend to withdraw from and not depend on close relationships as a source of support. Importantly, attachment style is hypothesized to influence physical and mental health, through key pathways such as stress regulation and sleep (Diamond & Fagundes, 2010; Pietromonaco & Powers, 2015;

Troxel et al., 2007).

Recent theory and research has highlighted associations between adult attachment and dimensions of sleep (Troxel, et al., 2007; Adams & McWilliams, 2015; Verdecias et al., 2009). In fact, theoretical models of relationship functioning and sleep propose that positive (e.g. support, closeness, security) and negative aspects (e.g. conflict, hyperarousal, vigilance, negative emotions) of close relationships are associated with

Texas Tech University, Antonio Pagan, August 2020 dimensions of sleep through behavioral, psychological and physiological pathways

(Troxel, 2010). The positive and negative aspects of relationship functioning outlined by this model can be conceptualized as secure and insecure attachment respectively. Sleep has been hypothesized as an attachment behavior in which a securely attached individual, in order to effectively transition into a more relaxed physiological state, trusts his or her surroundings thereby downregulating vigilance and arousal (Troxel, 2010). The transition from wake to sleep includes not only psychological downregulation associated with trust and relaxation (Gunn et al., 2017), but physiological downregulation that is characterized by predominantly parasympathetic nervous system control of heart rate (Burgess et al.,

1999). Considering differences in how the parasympathetic and sympathetic nervous system work in healthy adults prior to sleep onset, both processes are important for identifying the mechanisms influencing sleep through arousal. The present study will examine associations between attachment style and physiological and psychological downregulation prior to sleep onset.

Attachment Style and Sleep

A recent review reveals that attachment and sleep are consistently associated across the lifespan (Adams et al., 2014). Given that adults’ primary attachment relationships occur within the context of marriage (Troxel, 2010), much of the work on attachment and sleep in adults has been examined in married couples. Insecurely attached married adults report impaired global sleep quality scores on the Pittsburgh Sleep Quality

Index (PSQI; Maunder et al., 2011). Married adults with high levels of attachment anxiety report greater numbers of sleep disruptions compared to individuals with avoidant attachment styles (Carmichael & Reis, 2005). Furthermore, anxiously attached

Texas Tech University, Antonio Pagan, August 2020 adults who experience a naturalistic separation from a partner, report more sleeping problems than securely and avoidantly attached individuals (Diamond et al., 2008). In summary, anxious attachment in married adults is associated with poor subjective ratings of sleep when compared to adults with secure and avoidant attachment styles. However, avoidantly attached married adults do not seem to report difficulties with sleep and may even look better on objective sleep outcomes when compared to married adults with secure and anxious attachment styles (Troxel & Germain, 2011).

Outside of marriage, there are similar associations between attachment style and sleep outcomes in adults. For example, in a sample of post-deployed service members, securely attached individuals experienced significantly less restless sleep, when compared to insecurely attached individuals (Vincenzes et al., 2014). Anxiously attached women (married and unmarried) spent a significantly smaller percentage of time in stage

3−4 sleep compared to securely attached women (Troxel et al., 2009). Furthermore, other studies find that attachment anxiety is significantly associated with a high percentage of

α-EEG intrusion throughout the night (Sloan et al., 2007). Taken together, these data suggest that anxiously attached individuals have more restless sleep, spend less time in deep sleep and even experience a greater amount of α-EEG intrusion throughout the night. Thus, anxiously attached individuals tend to have worse sleep across subjective and objective indices when compared to securely attached individuals.

When examined broadly across all adult relationships, attachment avoidance is associated with difficulty initiating sleep, difficulty maintaining sleep, early morning awakening, daytime sleepiness (Adams & McWilliams, 2015), and poor sleep quality in wives, but not husbands (Carmichael & Reis, 2005). However, subjective indices of sleep

Texas Tech University, Antonio Pagan, August 2020 often do not differ between anxious and avoidantly attached adults (Mcnamara et al.,

2011). Avoidantly attached adults have poorer sleep quality when compared to securely attached adults, and more sleep difficulties (Adams & McWilliams, 2015), but better overnight sleep on objective measures (Troxel & Germain, 2011). In fact, avoidant attachment in adults may be a protective factor, as one study indicates it is positively associated with sleep depth (Troxel & Germain, 2011).

The mixed results on attachment avoidance in adults could be attributed to the emotional inhibition and minimal emotional reactivity they experience (Adams et al.,

2014). Avoidantly attached adults may not attend to environmental cues in the same way that anxiously attached adults do, and thus may not be as psychologically reactive to stress and negative emotional states that accompany poor sleep. Compared to avoidantly attached adults, those with attachment anxiety may have poor sleep outcomes due to the chronic state of physiological hyperarousal and cognitive vigilance they experience.

Anxiously attached adults may also have poorer psychological and physiological downregulation in preparation for and maintaining sleep.

In summary, while there are clear differences between anxious and avoidantly attached adults on subjective sleep outcomes, differences between these two groups on objective outcomes are less clear. One way to better understand the mixed results would be to examine physiological and psychological arousal prior to sleep onset (Troxel et al.,

2010). As physiological and psychological arousal prior to sleep are not only important predictors of sleep (Fernandez-Mendoza et al., 2010; Harvey, 2000; Morin et al., 2003;

Tang & Harvey, 2004), but may also contribute to poor mental and physical health

(Gangwisch et al., 2006; Hall et al., 2008; Ferrie, et al., 2007; Li et al., 2013).

Texas Tech University, Antonio Pagan, August 2020

Studies examining associations between attachment style and arousal have largely been limited to heightened physiological and psychological responses to stress during the day. Specifically, these studies find that compared to secure attachment, insecure attachment is associated with heightened physiological and psychological responses to stressful sitations (Mikulincer et al., 2003; Mikulincer & Shaver, 2007, 2012; Permuy et al., 2010). Moreover, research has consistently revealed key differences between avoidantly and anxiously attached individuals in their responses to stress (Diamond &

Fagundes, 2010). For example, during a laboratory-based stress reactivity study, only anxious attachment was associated with stress-related changes in subjective arousal; whereas only avoidant attachment was associated with stress-related decreases in high- frequency heart rate variability (HF-HRV), an underlying component of heart rate that may provide an index of parasympathetic nervous system functioning (Maunder et al.,

2006). In marital interaction studies, avoidantly attached individuals often demonstrate a lack of awareness and incongruence between their self-report and their physiology

(Seedall & Lachmar, 2016; Seedall & Wampler, 2012). Specifically, in a marital interaction study, avoidantly attached individuals were more likely to report positive feelings toward their partners despite their physiological distress (Seedall & Wampler,

2012). Thus, while anxiously attached individuals display both heightened physiological and psychological reactivity to stress, avoidantly attached individuals display heightened physiological reactivity to stress despite their tendency to report lower levels of subjective distress. These findings provide some initial evidence that objective indices of arousal may help us to understand key differences between anxious and avoidantly attached individuals prior to sleep onset.

Texas Tech University, Antonio Pagan, August 2020

Physiological and cognitive arousal are antithetical to sleep (Wuyts, et al., 2012;

Tang, & Harvey, 2004; Morin et al., 2003), and if these states persist, they can lead to downstream sleep problems such as insomnia (Edinger et al., 2000; Fernandez-Mendoza et al., 2010; Riemann et al., 2010). The majority of studies examining arousal during the pre-sleep period have utilized self-report measures of cognitive and somatic pre-sleep arousal either to distinguish patients with insomnia and good sleepers (Bonnet & Arand,

2010; Harvey, 2010; Morin et al., 2003) or to understand the role of pre-sleep arousal as a vulnerability factor for primary insomnia (Drake et al., 2004; Fernandez-Mendoza et al.,

2010). While numerous studies have examined associations between attachment and overnight sleep (Adams & McWilliams, 2015; Carmichael & Reis, 2005; Diamond et al.,

2008; Sloan et al., 2007; Troxel et al., 2009; Troxel & Germain, 2011; Vincenzes et al.,

2014), only a few studies have examined associations between attachment style and pre- sleep arousal. In a study of women with depression, attachment anxiety was associated with longer polysomnography assessed sleep onset latency in the laboratory (Troxel et al., 2007). Moreover, in a study of patients with insomnia and good sleepers, attachment style was unrelated to self-reported pre-sleep arousal among good sleepers, but insecure attachment was associated with self-reported cognitive and somatic pre-sleep arousal

(Palagini et al., 2018). These studies provide support for examining associations between attachment syle and pre-sleep arousal (Palagini et al., 2018; Troxel et al., 2007).

However, these studies are limited in several ways. Primarily, these studies included clinical samples, did not differentiate between avoidant and anxious attachment, and did not utilize objective physiological measures that link back to the larger literature on attachment and daytime arousal. One way to address these limitations would be to utilize

Texas Tech University, Antonio Pagan, August 2020 a multi-method approach for measuring pre-sleep arousal that would include both self- report questionnaires and physiological indices of arousal.

Measuring Physiological Arousal Prior to Sleep

Recent theory conceptualizes the autonomic nervous system as functioning in a two-dimensional autonomic space where target organs react to changes from both the sympathetic and parasympathetic nervous system along reciprocal and coactive dimensions rather than soley along a continuum from sympathetic to parasympathetic dominance (Berntson et al., 1994). The autonomic space theory expands on traditional models of autonomic nervous system activity in which sympathetic activity decreases and parasympathetic activity increases (reactive) while also incorporating modes in which both branches are actively innervating target organs simultaneously (Coactive; Berntson, et al., 1994). Any one point on the autonomic plane corresponds to a unique physiological effect on the target organ. As a result, heart rate provides researchers a glimpse at the underlying autonomic nervous system activity at any given point. Social relationships are associated with diverse physiological responses across many measures and studies (Thorsteinsson & James,1999) and may also be characterized by either coactive or reciprocal changes in parasympathetic and sympathetic activity on the heart wherein central control of the heart is flexibly managed through the vagus nerve

(Berntson et al., 1991) which, when stimulated, is positively, linearly associated with heart rate variability (Berntson, et al., 1994). Furthermore, stressors have been associated with changes in both branches of the autonomic nervous system illustrating the coactive component of the autonomic space model (Cacioppo et al., 1994). In summary, by

Texas Tech University, Antonio Pagan, August 2020 examining determinants of the autonomic nervous system through the heart we are more fully able to conceptualize the experiences individuals have in social relationships.

At rest, the heart is under tonic parasympathetic control by the vagus nerve. Heart rate responds to the natural patterns in the breathing cycle by rising and falling and is labeled respiratory sinus arrhythmia (RSA). The R-R interval is shortened during inspiration and prolonged during expiration. The frequency of measurement for high frequency heart rate variability (HF-HRV) lies between 0.12 and 0.40 Hz due to the variation related to the rising and falling occurring during the respiration cycle. RSA provides an index of parasympathetic nervous system activation on heart rate.

Cardiac pre‐ejection period during sleep is longer than during wake (Burgess &

Trinder 1997), which is indicative of lower sympathetic nervous system activity, which is particularly true for good sleepers compared to insomniacs (de Zambotti et al., 2014).

Higher sleep efficiency (the ratio of total time spent asleep compared to the total amount of time spent in bed) and sleep duration are associated with increases in PEP (less sympathetic nervous system activity) in emerging young adults over a three-year period

(El‐Sheikh et al., 2017). The few studies that examine the association between PEP levels before sleep and sleep outcomes find that adults’ PEP levels before a nap are negatively associated with sleep latency (the time it takes to fall asleep after entering bed) and wake after sleep onset (Cellini et al., 2018). Altogether, the existing literature highlights that lower sympathetic nervous system activity before sleep and during sleep are associated with better sleep outcomes.

Considering the role both systems of the autonomic nervous system play before and during the sleep-wake cycle is important due to some key differences found in the

Texas Tech University, Antonio Pagan, August 2020 literature. For instance, researchers have found that indices of the parasympathetic nervous system begin to change as early as two hours prior to sleep onset (Burgess et al.,

1999). In contrast to the results of the examination of sleep and parasympathetic nervous system activity, the index of sympathetic nervous system activity, PEP, tends to decrease after sleep onset has begun and it continues to decrease as the stage of sleep deepens

(Somers et al., 1993; & Burgess et al., 1999). As a result, sleep stages may influence the sympathetic nervous system, as measured by PEP, whereas cardiac HF-HRV may be linked to underlying circadian influences.

Importantly, clinical research should focus on psychopathology as a downstream outcome. In adolescents, self-reported attachment style, specifically those who identified as ambivalent in their attachment style, had significantly higher self-reported anxiety and depression scores when compared to both avoidantly and securely attached adolescents

(Muris et al., 2001). Significant positive associations between social anxiety level and preoccupied, fearful, and dismissing attachment styles have been found in college students (Öztürk & Mutlu, 2010). Furthermore, among men and women in couples, anxious but not avoidant attachment was signficnatly associated with symptoms of depression (Shaver et al., 2005). In a clinical sample of socially anxious individuals, anxious-preocupied individuals reported significantly more symptoms of depression

(Beck Depression Inventory) than securely attached individuals (Eng et al., 2001).

Furthermore, in a review of research on autonomic flebility and anxiety disorders, associations between panic disorder (PD), generalized anxiety disorder (GAD), and social anxiety disorder (SAD) and cardiac control were found (Friedman, 2007). Specifically, lower parasympathetic cardiac control has been associated with PD (Friedman, 2007),

Texas Tech University, Antonio Pagan, August 2020 while PTSD is not associated with HRV changes when presented with trama stimuli

(Friedman, 2007). Finally, phasic worry is associated with reductions in HF-HRV in both

GAD and control groups (Friedman, 2007). In conclusion, it appears autonomic inflexibility accounts for diminished HRV in anxiety disorders.

The Present Study

While the link between attachment style and overnight sleep is well-documented

(Adams et al., 2014) the associations between attachment style and arousal prior to sleep largely remain to be investigated. Specifically, prior research has demonstrated that avoidant attachment style is associated with more traditional objective indices of sleep and arousal, whereas anxious attachment is associated with more subjective indices of sleep and arousal. One way to disentangle the differences we are seeing in attachment style and sleep would be to examine physiological arousal when individuals are awake in order to ascertain both objective and subjective (psychological) indices of arousal. The present study employs a multi-trait multimethod approach to examine pre-sleep arousal through objective and subjective indices of arousal, including the underlying determinants of heart rate (e.g. HF-HRV and PEP), in addition to self-report measures of cognitive and somatic activation prior to sleep onset that were obtained using experience sampling methods.

The present study comes from a larger study examining stress regulation in daily life. The goal of the present study is to examine associations between the attachment style and both physiological and psychological arousal prior to sleep. The present study had one overarching research aim: Is there an association between attachment style and HF-

HRV, PEP, and self-reported pre-sleep arousal scores prior to sleep onset? It is

Texas Tech University, Antonio Pagan, August 2020 hypothesized that using partial regression and incremental analysis 1a) anxious and avoidant attachment styles will be negatively associated with RSA; 1b) anxious and avoidant attachment styles will be negatively associated with PEP scores; 2) anxious attachment will be positively associated with scores on the pre-sleep arousal scale; 3) avoidant attachment will not be associated with scores on the pre-sleep arousal scale total score.

Texas Tech University, Antonio Pagan, August 2020

CHAPTER 2

METHODS

Participants

Participants were 79 adults from a University of Utah participant pool and the greater Salt Lake City community. Participants were recruited using flyers and by word of mouth for both undergraduate and community samples. Recruitment methods for the undergraduates also included being posted on the subject line. Participants were compensated for their participation and were a part of a larger study examining stress regulation and cognitive functioning in daily life. Inclusion criteria were: a) age within of

20-45 years old; b) first language had to be English; c) reported clinical insomnia symptoms on the Insomnia Severity Index (Bastien et al., 2001) total score had to be below the clinical cutoff score; d) no left hand dominance; e) no motor or sensory impairments that could interfere with cognitive task performance; f) no current use of tobacco; g) not pregnant; h) no history of renal failure, i) no pulmonary disorder, j) no hypertension, k) no major orthopedic surgery, l) no Multiple Sclerosis, m) no heart surgery, brain surgery, brain tumor, cerebral vascular accident, seizures, and brain injury; and no current use of neuroleptic, cardiovascular, or hypnotic medications. Drs. Matthew

Cribbet and Holly Rau collected measures using eprime and data were downloaded, examined for outliers, agregated self-report scores, and data were moved to SPSS for analysis.

Texas Tech University, Antonio Pagan, August 2020

Measures

Experiences in Close Relationships-Revised Questionnaire (ECR-R; Fraley et al., 2000). The Experience in Close Relationships-Revised Questionnaires a 36-item self- report questionnaire that assesses adult attachment orientation. Items are rated on a likert-type scale that ranges from 1 "Strongly Disagree" to 7 "Strongly Agree". The ECR-

R contains two 18-item subscales, one assessing attachment anxiety and the other assessing attachment avoidance. Scores on individual items can range from 1 to 7 with higher scores on both scales indicating higher attachment-related anxiety and attachment- related avoidance. Our data revealed strong internal consistency for the attachment related avoidance (α = .813) items and moderate internal consistency for the attachment related anxiety (α = .454) items. Due to the low alpha for the anxiety dimension, supplemental analyses were completed to examine whether LDS church affiliation explained the low alpha. Individuals who identified as LDS in the attachment related anxiety dimension revealed strong internal consistency (α = .873, N=20). When individuals who idenfity as LDS were excluded, our sample also revealed strong internal consistency in the attachment related anxiety dimension (α = .862, N=59). Other studies have found strong internal consistency (N=478) for the attachment related avoidance (α =

.94) items and the attachment related anxiety (α = .93) items and highly stable (85% shared variance) indicators of latent attachment during a 3-week period (Sibley et al.,

2005).

Adult romantic attachment style historically has been measured with several instruments (Hazan & Shaver, 1987; Bartholomew & Horowitz, 1991; Brennan et al.,

1998; Gillath et al., 2009; & Fraley et al., 2000). A review of attachment related

Texas Tech University, Antonio Pagan, August 2020 instruments reveals many possible measures of attachment with good reliability and validity (Ravitz et al., 2010) with multi-item dimensional measures demonstrating greater precision and validity (Brennan et al., 1998; Fraley & Waller, 1998). The stability of attachment style from infancy to adulthood is associated with negative life events

(McConnell & Moss, 2011). In a large (N=370) longitiduinal study of attachment style over a 6 year period, individuals reporting as “secure” and “fearful” in their attachment style reported the least fluctuations of their attachment style (Zhang & Labouvie-Vief,

2004). Furthermore, adult attachment style predicted 20% of the variance in attachment style 6 years later (Zhang & Labouvie-Vief, 2004).

Pre-sleep Arousal Scale (PSAS; Nicassio et al., 1985). The Pre-sleep Arousal

Scale is a 16-item self-report questionnaire that includes items for both cognitive (worry, reviewing the day, excessive thoughts, easily distracted by environment, mentally alert, etc.) and somatic (heart racing, shortness of breath, dry mouth, upset stomach, tension in muscles, etc.) arousal. Items were answered prior to bedtime and rated from 1 (not at all) to 5 (extremely), with higher scores indicating higher levels of cognitive or somatic arousal before bed. A total score was obtained by summing all items, with higher scores indicating greater pre-sleep arousal. Average of scores were calculated and used in the analyses. Cronbach’s alphas were .89 for the total score, .88 for the cognitive arousal subscale, and .71 for the somatic arousal subscale. The total score will be used to account for all of the variability in both cognitive and somatic anxiety that individuals experience. If the association between attachment styles and the PSAS total score is significant, follow-up analyses will be conducted in order to determine if somatic or

Texas Tech University, Antonio Pagan, August 2020 cognitive arousal are driving associations between attachment style and self-reported pre- sleep arousal.

Sleep Diary. A modified version of the Pittsburgh Sleep Diary (Monk et al.,

1994) was used to assess daytime activities, sleep behaviors, and sleep parameters. The participants completed information about bed time and rise time, sleep latency, wakefulness after sleep onset, and sleep quality upon arising (0 to 3 scale). The recorded sleep parameters were used to calculate time in bed, total sleep time, and sleep efficiency

(calculated as total sleep time/time in bed x 100). Total sleep time, sleep latency, wakefulness after sleep onset, sleep latency following a nighttime awakening, and sleep efficiency were used as outcome variables. Similar items appear on other validated sleep diaries, such as the Consensus Sleep Diary (Carney et al., 2012).

Actigraphy. Participants wore actigraphs (Actigraph GTIM, The Actigraph,

Pensacola, Florida) on their non-dominant wrists for three consecutive days. Actigraphs were programmed to collect data in 60-second epochs. Actigraphy data were cleaned by a scorer who used a standardized approach to set rest intervals (periods when the participant was sleeping) based on input from the participants sleep diary (Patel et al.,

2015). For each day, the beginning and end of rest period was identified as the primary period for sleep based on information from the sleep diary and movement tracked by the actigraph. After setting rest intervals manually, a medium-sensitivity scoring algorithm from Actiware 5 software was used to separate sleep onset and sleep offset and a wake threshold activity count of 1000 was applied to garner sleep/wake from each epoch (Cole et al., 1992). Data from the actigraphs were used to determine the sleep onset.

Texas Tech University, Antonio Pagan, August 2020

High-frequency heart rate variability (HF-HRV). Each participant wore an ambulatory physiology monitor continuously for 1 day (MW1000A ambulatory heart rate variability and impedance cardiography monitor; Mindware Technologies; Gahanna,

Ohio). Sleep onset was determined through wrist actigraphy and sleep diary (Monk et al.,

1994) to determine the 30-minute time period prior to sleep onset. ECG data were collected continuously at a sampling rate of 500Hz from participants using a standard lead II configuration. The raw ECG data were inspected using automated software and then visually inspected according to the guidelines for detecting artifacts and abnormal beats (Bernston, et.al., 1997). HRV analysis software (Mindware version 3.0.12,

Mindware Cardiography system, Gahanna, Oh) was used to verify, edit and summarize cardiovascular data. ECG data were ensemble averaged for each participant in 60 second epochs. Heart rate variability was derived by applying spectral analysis to the IBI series

(interbeat interval series – time in milliseconds between successive R-peaks). Next, the

IBI series was time sampled at 4 Hz in order to produce an equal time series. The time series was detrended and submitted to a fast Fourier Transformation (Bernston et al.,

1997). Spectral analysis was used to identify high frequency heart rate variability (0.12 to

0.40 Hz). HF-HRV was calculated for each minute of all periods as the natural log of the area under the heart period power spectrum. RSA was averaged across the thirty minutes prior to sleep onset.

Pre-ejection Period (PEP). The ambulatory impedance cardiograph (MindWare

1000A, MindWare Technologies Ltd) was used to obtain cardiac PEP. Seven spot electrodes were placed on the front and back torso in a tetrapolar configulation

(Sherwood et al., 1990). Three spot electrodes were placed in the standard lead II

Texas Tech University, Antonio Pagan, August 2020 configuration. Four spot electrodes were placed according to guidelines for impedance cardiography (Sherwood et al. 1990). One spot electrode was placed at the base of the neck, one at the xiphisternal junction, one over the fourth cervical vertebra, and one over the ninth thoracic vertebra. The electrode wires were subsequently connected to a battery- powered PDA in a protected carrying case. MindWares’s PDA acquisition software, PDA

ACQ was used to acquire the data. The ECG was measured continuously at a sampling rate of 500Hz.

The impedance signal (Zo) and the derivative of time (dZ/dt) were digitized at

500 Hz. The raw ECG data was initially inspected by automated software and subsequently visually inspected according to established guidelines (Berntson et al.,

1997; Sherwood et al., 1990). ECG complexes were ensemble averaged for each minute.

Ensemble averaging uses the R-point of the ECG as a reference for the successive averaging of the ECG and subsequent dZ/dt signals. PEP was calculated as the time interval in ms between the Q-point of the ECG and the B-point and X-point of the dZ/dt signal.

Given that pre-ejection period (PEP) is heavily influenced by sympathetic innervation of the heart (Sherwood et al., 1986), it can be used as an index of sympathetic nervous system (SNS) arousal. Specifically, PEP refers to the interval between electrical stimulation of the ventricles and the opening of the aortic valve. Impedance data were inspected, edited, and summarized with the use of ICG analysis software (IMP 3.0.12,

MindWare Technologies Ltd.). The ECG and impedance waves were visually inspected within 60-second epochs. PEP was calculated as the time between the Q-point in an

Texas Tech University, Antonio Pagan, August 2020 electrocardiogram (ECG) signal and the B-point in the derived impedance signal

(Sherwood et al., 1990; Vrijkotte et al., 2004).

Procedures

The study was approved by the University of Utah Institutional Review Board.

After signing informed consent, participants completed a laboratory assessment that included self-reported measures of attachment style. Subsequently, participants wore an ambulatory cardiac impedence monitor continuously for two consecutive nights while also providing nighttime ratings of pre-sleep arousal. Participants wore wrist actigraphy for three days and were compensated for their participation. The PSAS was assessed at the participants home. Participants were sent a link to an online survey along with a reminder phone call. Survey completion times were time-stamped and times were verified by a trained research assistant.

Data Analysis Plan

Normality of the data were assessed and corrected for skew and kurtosis (using

QQ-plots), bimodality (using histograms and density plots) and outliers (using boxplots).

Extreme scores were examined to determine if there is measurement or data-entry error.

Furthermore, skew that cannot be corrected through outlier corrections, data were transformed using the ladder of roots and powers (Mosteller & Tukey,1977) to correct monotonicity. Multiple linear regression was used to assess associations among attachment style, sleep and both psychological and physiological pre-sleep arousal. The hypothesis are that 1a) anxious and avoidant attachment styles will be negatively associated with RSA, and PEP; 1b) anxious and avoidant attachment styles will be negatively associated with PEP; 2) anxious attachment will be positively associated with

Texas Tech University, Antonio Pagan, August 2020 scores on the Pre-sleep Arousal Scale; and 3) avoidant attachment will not be associated with scores on the Pre-sleep Arousal Scale.

Power analyses were conducted to test whether the sample size was sufficient to detect a medium effect. A post-hoc power analysis for a multiple regression was conducted in G*power (Faul et al., 2007). A total of four variables were used as predictors in all multiple regression analyses. These variables included age, sex, and both avoidant and anxious attachment style as the predictor variables. In order to detect a small effect, alpha was set to .05, power was set to .80, and Cohen’s f2 was set to .02

(Cohen, 1988; Faul, et al., 2007). The power analysis indicated that a samples size of 602 participants would be required to detect a small effect with 4 predictors. To determine a medium effect, alpha was set to .05, the power was set to .80, and the effect size was

Cohen’s f2 was set to .18 (Cohen, 1988; Faul, et al., 2007). The power analysis indicated that a sample size of 72 participants would be necessary to detect a medium effect with 4 predictors. The sample in the present study has a total of 79 participants, meaning the sample is large enough to detect a medium effect. The present study is underpowered to detect a small effect.

Data Analytic Strategy and Preparation

Statistical assumptions of multiple linear regression were tested in IBM SPSS

(Version 26.0; 2019). Preliminary analyses revealed some minor departures from normality. Visual inspection of histograms revealed that all variables except for age and

PEP were normally distributed. Boxplots were used to examine whether outliers existed for any variables of interest. PEP had one outlier. To assess the impact of this outlier,

Cook’s D was used to test the assumption of normally distributed data. After examining

Texas Tech University, Antonio Pagan, August 2020 the above values Cook’s D value, the value was not three times the mean of Cook’s D, therefore it was not imputed. Five other values were greater than three times the mean of

Cook’s D. However, the removal of these values had no significant effect on correlation coefficients, standard error of correlation coefficients, or p-values involving PEP as a variable and therefore the values were retained. Homoscedasticity was assessed in order to test the assumption that the variance around the regression line is the same for all values of the predictor variable. Homoscedasticity was assessed through a visual inspection by plotting studentized residuals against unstandardized predicted values. It was determined that there were no visible patterns of heteroscedasticity in any models.

Nonlinearity was assessed in order to test the assumption that the relationship between dependent and independent variables is a straight line. Nonlinearity was assessed by plotting standardized predicted values and standardized residuals for each hypothesis.

The residuals in all models were normally distributed. It was determined that the assumption of linearity was met for all models with the exception of some deviations visible in model with anxious and avoidant attachment styles regressed on PEP scores, in that some of the observed values were greater than expected values. Finally, multicollinearity was assessed in order to assess the assumption that the independent variables are not highly correlated. Multicollinearity was assessed by examining the variance inflation factor (VIF) and tolerance of each model. No independent variables and covariates had variance inflation factors exceeding 4.0, or tolerance levels less than

0.2 (Hair et al., 2010) meaning multicollinearity was not violated.

Texas Tech University, Antonio Pagan, August 2020

Regression analyses

Multiple linear regression analyses were conducted in IBM Amos 26 (Arbuckle,

2017). Multiple linear regression models were calculated using full information maximum likelihood (FIML) estimation with AMOS software (Arbuckle, 2017). FIML is superior to listwise deletion for handling missing data (Akaike, 1998; Enders, 2001;

Jelicic et al., 2009). FIML is robust to departures from normality and performs well even with low sample sizes (Graham, 2009). As a result, FIML was used to handle all missingness in the data. A total of 26 participants had attachment style and PEP 10 minutes before actigraph indicated sleep data available; 28 had attachment style and HF-

HRV 10 minutes before actigraph indicated sleep data available; 68 had attachment style and PSAS data available, 64 had baseline PEP data available, and 69 baseline HF-HRV data available. Ambulatory physiology data were missing due to signal quality during recording, failure, faulty or insufficient pre-sleep psychophysiology data, or removed electrodes due to discomfort. Analysis of variance was conducted in order to ensure that participants with PEP data or HF-HRV data did not demonstrate significant differences in self-reported attachment style in comparison to participants without PEP or HF-HRV data.

Separate multiple linear regression analyses were performed to explore associations between attachment style and objective (HF-HRV and PEP) and subjective

(PSAS) measures of arousal prior to sleep with results provided as unstandardized coefficients and r-squared provided as measure of effect size. For all analyses of objective arousal, we controlled for attachment style, age, sex, and baseline HF-HRV or

PEP, as appropriate. For all analyses of subjective arousal, we controlled for attachment

Texas Tech University, Antonio Pagan, August 2020 style, age, and sex. Attachment avoidance or anxiety was included as a covariate when attachment avoidance or anxiety is primary the independent variable. Including both attachment style variables in all analyses that include the other attachment style is a conservative approach related to the conceptualization of attachment style as dimensional rather than categorical (Fraley & Waller, 1998).

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CHAPTER 3

RESULTS

Table 1 shows descriptive statistics for demographic characteristics, attachment style, and physiological data. The mean participant age was 27 years old, most participants were

Caucasian, and in a committed relationship.

Table 1. Descriptive Statistics for Demographic Characteristics, attachments style, and physiological data among Participants Mean Variables (SD) N = 78 Age 26.97(5.92) ECR-R Avoidant Attachment 3.72(.29) ECR-R Anxious Attachment 3.51(.72) Baseline PEP 138.65(11.88) Baseline HF-HRV 6.15(1.28) PEP 10 min Prior to Sleep 132.31(10.42) HF-HRV 10 min Prior to Sleep 6.02(1.61) PSAS Score 52.07(11.33) PSAS Cognitive Score 19.85(4.01) PSAS Somatic Score 32.22(9.20) Note. ECR-R = Experiences in Close Relationships- Revised Questionnaire. PEP = Pre-ejection Period. HF- HRV = High-frequency heart rate variability. PSAS = Pre-sleep Arousal Scale.

Hypothesis 1a & 1b

Multiple linear regression was conducted to examine the association between attachment anxiety and objective indices of arousal 10 minutes prior to sleep. As presented in Table 2., attachment anxiety was significantly negatively associated with participant’s HF-HRV scores 10 minutes prior to actigraph indicated sleep even after controlling for attachment avoidance, age, sex, and baseline HF-HRV ( = -.23, SE=

.19, p = .013). Participant’s HF-HRV decreased .23 units for every one unit increase in

Texas Tech University, Antonio Pagan, August 2020 attachment anxiety controlling for attachment avoidance, age, sex, and baseline HF-

HRV. Semi-partial r-squared revealed that anxioius attachment accounted for 2.1% of the variance in HF-HRV. Furthermore, attachment anxiety was significantly associated with participant’s PEP scores 10 minutes prior to actigraph indicated sleep even after controlling for attachment avoidance, age, sex, and baseline PEP ( = .38, SE= 1.80, p =

.006). Participant’s PEP increased .38 units for every one unit increase in attachment anxiety controlling for attachment avoidance, age, sex, and baseline PEP. Semi-partial r- squared revealed that anxious attachment accounted for 11.7% of the variance in PEP

(Table 2).

Table 2. Association of Attachment Style with Arousal Variables Estimate S.E. P DV: PEP 10 Minutes Prior to Sleep Anxiety 0.38 1.8 0.006 Avoidance 0.011 3.76 0.94 Age 0.37 0.21 0.006 Baseline PEP 0.37 0.01 0.006 Sex 0.34 0.01 0.011 R2 = .536 DV: HF-HRV 10 Minutes Prior to Sleep Avoidance 0.321 0.409 0.0001 Anxiety -0.232 0.196 0.013 Age -0.124 0.023 0.18 Baseline HF-HRV 0.765 0.133 0.0001 Sex 0.09 0.325 0.34 R2 = .766 DV: PSAS_Total Avoidance -0.088 3.903 0.45 Anxiety 0.303 1.852 0.009 Age -0.083 0.219 0.47 Sex 0.008 3.062 0.94 R2 = .106 DV: PSAS Cognitive Total Avoidance -0.08 1.322 0.49 24

Texas Tech University, Antonio Pagan, August 2020

Table 2 Continued Anxiety 0.299 0.628 0.009 Age -0.179 0.074 0.11 Sex -0.094 1.037 0.41 R2 = .137 DV: PSAS Somatic Total Avoidance -0.079 3.029 0.51 Anxiety 0.258 1.439 0.029 Age -0.03 0.17 0.8 Sex 0.054 2.376 0.65 R2 = .077 Note. PEP = Pre-ejection Period. HF-HRV = High-frequency heart rate variability. PSAS = Pre-sleep Arousal Scale.

Next, multiple linear regression was conducted to examine the association between attachment avoidance and objective indices of arousal 10 minutes prior to sleep.

As presented in Table 2., attachment avoidance was significantly associated with participant’s HF-HRV scores 10 minutes prior to actigraph indicated sleep even after controlling for attachment anxiety, age, sex, and baseline HF-HRV ( = .32, SE=

.41, p = .001). Participant’s HF-HRV increased .32 units for every one unit increase in attachment avoidance controlling for attachment anxiety, age, sex, and baseline HF-HRV.

Semi-partial r-squared revealed that avoidant attachment accounted for 5% of the variance in HF-HRV. Furthermore, attachment avoidance was not significantly associated with participant’s PEP scores 10 minutes prior to actigraph indicated sleep controlling for attachment anxiety, age, sex, and baseline PEP ( = .011, SE= 3.76, p =

.936). Semi-partial r-squared revealed that avoidant attachment accounted for 13.3% of the variance in PEP.

Hypothesis 2

Next, multiple linear regression was conducted to examine the associations between attachment anxiety and subjective indices of arousal prior to sleep. As presented 25

Texas Tech University, Antonio Pagan, August 2020 in Table 2., attachment anxiety was significantly associated with participant’s PSAS total score after controlling for attachment avoidance, age, and sex ( = .30, SE= 1.85, p =

.009). Participant’s PSAS total score increased .303 units for every one unit increase in attachment anxiety controlling for attachment avoidance, age, and sex. Follow up multiple linear regression indicated attachment anxiety was significantly associated with participant’s cognitive subscale of the PSAS after controlling for attachment avoidance, age, and sex ( = .30, SE= .63, p = .009). Participant’s cognitive subscale scores of the

PSAS increased .30 units for every one unit increase in attachment anxiety controlling for attachment avoidance, age, and sex. Attachment anxiety was also significantly associated with participant’s somatic subscale of the PSAS after controlling for attachment avoidance, age, and sex ( = .26, SE= 1.44, p = .029). Participant’s somatic subscale scores of the PSAS increased .26 units for every one unit increase in attachment anxiety controlling for attachment avoidance, age, and sex.

Hypothesis 3

Finally, multiple linear regression with maximum likelihood estimation was used to examine the associations between attachment avoidance and subjective indices of arousal prior to sleep. As presented in table 2, attachment avoidance was not significantly associated with participant’s PSAS total score after controlling for attachment anxiety, age, and sex ( = -.088, SE = 3.90, p = .450).

Supplemental analysis were conducted in order to examine participants anxiety and depression scores. Participants average scores on the Beck Anxiety Inventory (BAI) fell into the minimal range (M = 6.24, SD = 5.93). Participants average scores on the

Beck Depression Inventory-II (BDI-II) fell into the minimal range (M = 8.18, SD = 7.89).

Texas Tech University, Antonio Pagan, August 2020

CHAPTER 4

DISCUSSION

Theoretical models of relationship functioning and sleep propose that positive

(e.g. support, closeness, security) and negative aspects (e.g. conflict, hyperarousal, vigilance, negative emotions) of close relationships are associated with dimensions of sleep through behavioral, psychological and physiological pathways (Troxel, 2010). The positive and negative aspects of relationship functioning are probably best captured by broad categories of secure and insecure attachment. The goal of the present study sought to test a part of the overall theory that adult attachment styles and dimensions of sleep are related through physiological and psychological pathways by examining adults physiological and cognitive arousal prior to sleep. Previous research revealed clear associations between attachment anxiety and poor objective and subjective indices of sleep (Diamond et al., 2008; Carmichael & Reis, 2005), however the associations between avoidant attachment style and objective and subjective indices of sleep were less clear. Avoidantly attached married adults’ objective sleep outcomes often look better than those with secure or anxious attachment styles (Troxel & Germain, 2011). To address this gap in the literature, the present study examined the associations between attachment style and objective and subjective indices of pre-sleep arousal in a naturalistic setting.

The aims of the current study were to: 1) examine the associations between attachment styles and objectives indices of physiological arousal (PEP and HF-HRV) prior to sleep; and 2) examine the associations between attachment style and subjective indices of psychological arousal (PSAS) prior to sleep.

Texas Tech University, Antonio Pagan, August 2020

Anxious attachment was significantly associated with physiological and psychological indices of physiological arousal prior to sleep. Evidence across the lifespan has revealed associations between attachment and difficulties in sleep broadly (Adams et al., 2014). Considering healthy individuals experience changes in indices of parasympathetic nervous system activity as early as two hours prior to sleep onset

(Burgess et al., 1999), the results of the present study provide further evidence that anxiously attached individuals may not be physiologically prepared or “ready” for sleep likely due to their higher levels of cognitive and somatic arousal.

Anxious attachment is associated with worse sleep objectively (Troxel et al.,

2009; & Sloan et al., 2007) and subjectively (Carmichael & Reis, 2005; & Diamond et al., 2008). The results of the present study corroborates mounting evidence that not only is anxious attachment associated with overall greater levels of subjective distress

(Ciechanowski et al., 2002a; & Ciechanowski et al., 2002b), but also objective arousal prior to sleep. The implications of these findings cannot be overstated considering pre- sleep cognitive and physicological arousal are important predictors of overnight sleep

(Wuyts, et al., 2012; Tang & Harvey, 2004; Morin et al., 2003). These results are also important because several studies have revealed that sympathetic dominance during sleep is associated with decreased sleep maintenance and disturbances in sleep architecture in healthy individuals (Hall, et al., 2004). The association between attachment anxiety and subjective and objective arousal is consistent with attachment theory which conceptualizes anxiously attached individuals as interpersonally vulnerable, fragile, and as inviduals who signal distress as a tool for interpersonal closeness (Bartholomew &

Horowitz, 1991).

Texas Tech University, Antonio Pagan, August 2020

Avoidant attachment was positively associated with parasympathetic nervous system activity prior to sleep, but not sympathetic arousal and no self-reported cognitive or somatic arousal. These results are consistent with research that avoidant attachment is associated with altered autonomic functioning, but not with subjective measures of arousal (Maunder et al., 2006). While anxiously or fearfully attached individuals consistently report greater levels of self-reported distress of various kinds (Ciechanowski et al., 2002; & Ciechanowski et al., 2002), avoidantly attached individuals appear to fail to signal distress. The current findings may be explained by the theoretical assumption that avoidantly attached individuals tend to withdraw from and not depend on close relationships as a source of support and as a result do not signal distress to significant others (Fraley & Shaver, 2000).

LIMITATIONS AND FUTURE DIRECTIONS

While one of the many strengths of the current study was its ecological validity, in that participant’s physiological data were collected in their naturalistic setting (i.e. in their own beds with their partners if applicable), a limitation was the amount of days physiology data were collected. Collecting ambulatory physiology data for more than two days may increase the reliability of these findings. The current sample size was large enough to detect a medium effect in the data. Furthermore, although data was missing, advanced statistical procedures were used to handle missing data and results did not indicate that data were missing due to some systematic component. As a result, it can be assumed outcome data using FIML closely approximates population statistics.

The present study was also limited by the demographics of the sample being predominantly white, which may limit the representativeness of the sample. Providing an

Texas Tech University, Antonio Pagan, August 2020 opportunity for future researchers to examine the methods of the present study with a more heterogeneous and diverse sample will be an important future consideration. While the sample was limited in some ways, the present study included mostly physically healthy individuals which allows for the present findings to be free from spurious associations found in a non-healthy sample. Another strength of the current study was that it employed a multi-trait multi-method approach to examining physiological arousal prior to sleep. Multi-trait multi-method approaches provide discriminate and convergent validity which can help researchers more accurately converge on subjective and psychological when researching sleep variables. Future studies should build on the multi- trait multi-method design of this study which examined both subjective and objective physiological arousal by using dyads and married couples.

In the current study neither attachment style nor sleep were experimentally manipulated, which limits the ability to make causal inferences. Furthermore, the present study only examined attachment style as an index of relationship functioning and its association with physiological and psychological arousal prior to sleep. Prior research suggests that other aspects of close relationships such as relationship quality may have a bidirectional association with nighttime sleep (Hasler & Troxel, 2010). Future studies could examine dynamic associations between attachment style, relationship quality, sleep and pre-sleep arousal over the course of multiple days. Finally, only one member of the romantic dyad provided daily sleep diary, actigraphy and pre-sleep arousal data. Recent research suggests that close relationships and sleep may actually function through coregulatory processes (Gunn et al., 2017). Future studies on adult attachment and sleep

Texas Tech University, Antonio Pagan, August 2020 should examine concordance between physiological and psychological measures prior to sleep onset both between and within couples.

Considering the results of the present study, mainly that anxious attachment is associated with both objective and subjective physiological arousal prior to sleep, future studies should focus on interventions that reduce cognitive and somatic arousal by increasing parasympathetic nervous system activity prior to sleep. Diaphragmatic breathing (DB), a breathing technique that encouarages the contraction of the diaphragm muscle to move air downward into the body, has been shown to have a relaxing and stabilizing effect on the autonomic nervous system (Subbalakshmi et al., 2014). As a result, DB strategies prior to bedtime as an intervention for anxiously attached individuals may increase parasympathetic nervous system activity prior to sleep in order to improve objective and subjective sleep.

CLINICAL IMPLICATIONS

The results of the current study may provide helpful information for clinicians making important diagnostic decisions regarding treatment for individuals with sleep or attachment related problems. If a client presents with sleep problems, clinicians can have clients fill out questionnaires assessing their attachment style. If a clinician determines after assessment that a client has an anxious attachment style, a clinician can focus on anxiety related to relationships, should the client find this important for their clinical goals. On the other hand, if a client presents with sleep problems, attachment style may provide information on what is contributing to or maintaining these sleep problems. As a result, mindfulness based treatments may be beneficial for the treatment of both attachment and sleep problems. Estimates of effect sizes for mindfulness based therapies

Texas Tech University, Antonio Pagan, August 2020 for anxiety and depression reveal moderate effectiveness for improving anxiety

(Hofmann et al., 2010) and downstream sleep quality or duration (Winbush et al., 2007).

While individuals who are avoidantly attached do not display objective difficulties downregulating their physiological arousal prior to sleep, research supports some subjective downstream associations between avoidant attachment style and sleep problems (Adams & McWilliams, 2015). The mechanisms through which mindfulness based treatments works suggests that individuals who practice mindfulness regularly develop the ability to “observe and describe present-moment experiences” possibly developing downstream “self-focused attention that reduces rumination and emotional avoidance and improves behavioral self-regulation” (Baer, 2009). Therefore, mindfulness based treatments may aid avoidantly attached individuals find more comfortable mechanisms to share their emotions improving downstream sleep problems.

Attachment style may provide unique information on early childhood experiences that shape how individuals appraise and interact with significant others. From a cognitive behavioral therapy (CBT) framework, a core belief of “others are untrustworthy” may be associated with an anxious attachment style and downstream sleep problems. As a result, knowing an individual’s attachment style may provide clinicians with information on the schema associated with their interpersonal relationships. Furthermore, individuals who received a package of CBT plus an interpersonal/emotional processing segment with higher scores on a measure of attachment associated with dismissing or avoidant style had significantly better outcomes at-post treatment in symptoms of generalized anxiety disorder (Newman et al., 2015).

Texas Tech University, Antonio Pagan, August 2020

CONCLUSIONS

The current study makes several important contributions to the existing literature, as it is the first study to assess the associations between attachment style and pre-sleep arousal using a multi-trait, multi-method approach with a healthy, adult sample.

Moreover, the present study examined physiology and psychological states prior to sleep in participants’ homes. The present study found that anxious attachment was associated with difficulty downregulating physiologically and cognitively prior to sleep. However, avoidant attachment was as positively associated with HF-HRV prior to sleep onset but not significantly associated with either cardiac pre-ejection period or self-reported arousal prior to sleep onset. These findings may suggest that avoidantly attached individuals may be better than anxiously attached individuals at downregulating their affect and physiology prior to sleep onset. Future studies should continue to test this hypothesis by examining how associations between attachment, physiology and self-reported arousal prior to sleep occur across multiple days. In conclusion, the present study provides further evidence that the associations between relationship functioning and sleep are closely tied to one psychological and physiological experiences.

Texas Tech University, Antonio Pagan, August 2020

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