Printer Friendly

The role of alcohol consumption and romantic attachment insecurity as risk factors for disrupted sleep and emotion regulation among underage and young adult drinkers.

Underage drinking is a public health concern within the US, and the prevalence of alcohol consumption among underage and young adult drinkers is very high. According to the Substance Use and Mental Health Administration (SAMHSA), alcohol is the most widely used substance among youth; in 2014, around 29% of 18-20 year olds and 43% of 21-25year olds engaged in binge drinking (SAMHSA, 2014). Alcohol consumption among underage drinkers accounts for 12% ($27 billion) of the 223 billion in economic costs to society and results in death, health care expenses, motor vehicle accidents, loss of productivity as well as increases in violence, homicide, risky sexual behavior, neurological impairment, alcohol use disorder, and thereby mental and physical health consequences (HHS, SAMHSA, 2016). Despite the impact of alcohol on health, the role of alcohol on biological (sleep patterns) and emotional states (emotion regulation) within this high-risk population have been underemphasized. This study uses a risk and resilience framework to examine the protective role of relationship factors, specifically attachment styles within romantic relationships that may buffer against the adverse impact of alcohol consumption on sleep and emotion regulatory strategies.

Alcohol Consumption and Health Behaviors

Excessive amounts of alcohol consumption or binge drinking has been defined as men having five or more drinks and women having four or more drinks on one occasion, typically over 2 hours (CDC, 2015). Poor mental health and alcohol consumption have been intricately connected with disturbances in sleep patterns (Kenney, Lac, LaBrie, Hummer, & Pham, 2013). In fact, sleep disruption is a common symptom of most mental health illnesses, and the links between sleep and mental health are complex (Weich, 2010). College students report high rates of disruptions in sleep quality and quantity, including daytime sleepiness, insomnia, onset latency, etc., which may be attributed to their lifestyle including consumption of alcohol and other substances (Roehrs & Roth, 2001). Excessive level of chronic alcohol consumption is a risk factor for sleep disturbances such as insomnia (Brower, 2003).

Alcohol Consumption and Sleep Patterns

Despite the close links between sleep disturbances and alcoholism, the associations between the two are complex. Alcohol could lead to a vicious cycle in which young people with sleep problems may use alcohol to self-medicate, thereby increasing existing sleep problems (Sivertsen, Skogen, Jakobsen, & Hysing, 2015). Although alcohol may be consumed due to its sedative effects on the brain, alcoholics or those who consume excessive levels of it may not experience the sedative effect of alcohol due to tolerance (Brower, 2003). Furthermore, the neurobiological processes underlying the effect of alcohol on sleep have not been widely explored. Sleep is regulated by neurobiological systems which may be affected by excessive drinking. Multiple neurotransmitters that impact sleep may be influenced by the use of alcohol. For instance, alcohol has been shown to increase noradrenergic activity and dopamine levels, leading to increased arousal (Brower, 2003). Alcohol effectively serves to depress central nervous system activity. The brain compensates for this depressive effect of alcohol by a change in activity that results in increased arousal (Brower, 2003). Thus, although alcohol may increase sleep during the first few hours of the night, there may be greater disruptions in sleep during the latter part of the night (Ebrahim, Shapiro, Williams, & Fenwick, 2013).

One of the earliest studies on the effects of alcohol has shown that high doses close to bedtime serve to impact rapid eye movement (REM) sleep and increase slow wave sleep (i.e., stages 3 and 4 of NREM; Kleitman, 1961, in Ebrahim et al., 2013). Sleep patterns most likely affected by high doses of alcohol include reduced onset latency (i.e., greater time in bed before sleep onset), increased wake after sleep onset in the latter part of the night, increase in slow wave sleep in the first part of the night, reduced percent of REM sleep, and increase in REM onset latency in the first part of the night (Ebrahim et al., 2013). Along with sleep onset latency (an indicator of insomnia), alcohol affects sleep continuity and quality (Fucito et al., 2015). Consumption of alcohol among nonalcoholic college students also affects daytime alertness, resulting in daytime sleepiness, possibly due to the sleep disruptions in the latter half of the night, and increases and sleep disturbed breathing and parasomnias at night (Roehrs & Roth, 2001). Singleton and Wolfson (2009) also showed that alcohol leads to disruptions in sleep-wake schedules among college students. Specifically, students who consumed alcohol reported less sleep at night, later bedtimes, and delayed weekday and weekend schedules. Sleep disruptions on account of alcohol were more pronounced among first- and second-year students (Singleton & Wolfson, 2008). Thus, the connections between sleep and alcohol are bidirectional and complex, despite the sedative nature of alcohol (Roehrs & Roth, 2001). There is a need to understand the links between the two, especially among young people who show comorbid symptoms of sleep and alcohol problems. Furthermore, since mental health disorders often co-occur among individuals with alcohol and sleep problems (Kenney, et al., 2013), there is a need for research on mental and emotional disturbances that may be linked to alcohol use.

Alcohol Consumption and Emotion Regulation

Alcohol use disorders have been linked to the dysregulation of emotions in the form of poor impulse control and limited access to emotion regulation strategies (Tripp, McDevitt-Murphy, Avery & Bracken, 2015). Alcohol consumption may affect emotional states due to its effects on regions of the brain such as the limbic system, which controls the experience and expressions of emotions, as well as the prefrontal cortex which maintains executive functions such as judgment, planning, and decision-making. Disruptions in these areas of the brain may explain the impulsive behaviors and emotional disturbances of those who consume excessive amounts of alcohol (Oscar-Berman & Marinkovic, 2003). Excessive drinking during adolescence and young adulthood has an impact on brain functioning, since regions of the brain, particularly the prefrontal cortex, continue to develop during this period (Tapert, Caldwell, & Burke, 2004/2005). Youth with alcohol use disorder have shown significantly lower hippocampal volume, reduced white matter in the corpus callosum, slower information processing, and reduced working memory (Tapert, Caldwell, & Burke, 2004/2005). Effects of alcohol include shrinkage of the cerebral cortex and increased vulnerability in the frontal lobes which communicate with other lobes of the cortex, thereby resulting in dysfunction in tasks pertaining to cognitive and emotional functioning. Furthermore, this damage continues as one ages, resulting in decreased brain cortical tissue in the prefrontal cortex among older alcoholics as compared to younger alcoholics (OscarBerman & Marinkovic, 2003). Thus, higher rates of drinking may impact the ability to control impulses, use effective emotion regulation strategies, and increase the likelihood of using emotion-focused strategies of coping with stressful situations, particularly at a stage when crucial areas of the brain are developing.

Although intervention programs on alcohol focus on multiple aspects of cognitive behavior therapy and abstinence, the relapse rates remain a recurring issue common to most substance use interventions (Moos & Moos, 2006). Interventions may emphasize social and environmental factors along with behavioral approaches. A large-scale study on risk for alcohol use disorder by Kendler and colleagues (2016) found that marriage (specifically first marriage) was a protective factor associated with a substantial decline in risk for alcohol use disorder. The authors speculate that the monitoring role of relationship partners (in this case spouses), as well as psychological and social aspects of the marriage (or relationship), may serve to protect individuals from alcohol use disorder (Kendler, Lonn, Salvatore, Sundquist, & Sundquist, 2016).

The Protective Role of Attachment Styles

The attachment theory (Bowlby, 1969) shows that relationship factors, specifically attachment, serve a regulatory function. Hazan and Shaver (1987) applied Bowlby's three category attachment styles from childhood to later romantic relationships. Later research by Bartholomew and Horowitz (1991) categorized four attachment styles, namely secure (i.e., low on dimensions of anxiety and avoidance), preoccupied (high on anxiety and low on avoidance), dismissive (low on anxiety and high on avoidance), and finally the fearful style (high on anxiety and avoidance). Within romantic relationships, individuals with insecure-anxious styles use hyperactivating regulatory strategies which emphasize vigilance in response to threat and thereby may elicit comfort and attention from their partners. However, individuals with an insecure-avoidant style use deactivating regulatory strategies which reduce distress and maintain distance from others. Securely attached individuals, who expect their partners to be responsive, use flexible regulatory strategies (Mikulincer & Shaver, 2008; Pietromonaco & Powers, 2015).

Secure individuals use constructive coping strategies that may directly resolve the conflict to change the situation that elicits the emotions or use reappraisal as a way to regulate emotions. Alternatively, insecure attachment strategies (i.e., hyperactivating or deactivating) may be maladaptive (Mikulincer & Shaver, 2008). Avoidant individuals attempt to down-regulate their emotions in the face of threats due to a perceived unavailability of the attachment partner which makes them unaware of their emotional reactions and causes them to be less likely to use this in their processing of information about the problem (Mikulincer & Shaver, 2008). Anxiously attached individuals maintain an increased sense of helplessness to acquire the attention of the attachment figure, assume pessimistic beliefs about self and others, and engage in rumination of the threat which may serve to amplify distress. These findings suggest that strategies employed by securely attached individuals may protect them by enabling them to effectively maintain the relationship without being overwhelmed (Mikulincer & Shaver, 2008). This protective role of attachment for emotion regulatory outcomes in the face of risk factors such as alcohol consumption has not been explored within the attachment theory literature.

One reason to expect that attachment may also serve a protective role in the connections between risk factors and sleep patterns is that previous research has shown support for common hormones and biomarkers for attachment and sleep. For instance, certain hormones such as oxytocin and vasopressin which play an important role in attachment behaviors in both children and adults also play a crucial role in sleep regulation (Born, Kellner, Uthgenant, Kern, & Lehm, 1992). Oxytocin is often called the intimacy or social hormone since it is associated with attachment behaviors such as physical contact. Interestingly, oxytocin also plays an important role in regulating the stress response, immune system, and the endocrine system (Troxel, 2010). Furthermore, oxytocin serves an important function for sleep due to its sedating properties (UvnasMoberg, Ahlenius, Hillegaart, & Alster, 1994) and its activity in the hypothalamus which regulates sleep and wakefulness (Lancel, Kromer, & Neumann, 2003). Another hormone, arginine vasopressin, which is important for attachment, also plays a role in regulating REM sleep (Born, et al., 1992). Finally, both attachment and sleep have been associated with a common immune system marker, IL-6. Insecure attachment systems have been linked to disruptions in immune functions. For example, avoidant spouses demonstrated heightened IL-6 responses to conflict. Anxious attachment styles have also been associated with higher levels of IL-6 after surgery (Pietromonaco & Powers, 2015). Since attachment and sleep patterns are linked to common neurobiological processes including hormonal and immune system regulatory states, there is good reason to expect that attachment styles may serve a risk buffering role for sleep outcomes in the face of risk factors.

Furthermore, drinking behavior has been closely associated with insecure patterns of attachment (Brennan & Shaver, 1995). In recent studies, it was found that individuals who were at risk for alcohol dependence (Wyrzykowska, Glogowska, & Mickiewicz, 2014) were less likely to show secure attachment, although attachment anxiety and avoidance were more common among those who were dependent on alcohol. Alcohol dependence was also associated with lower security and higher levels of fearful attachment (Reis, Curtis, & Reid, 2012). However, other research has found no support for main effects of attachment styles (especially insecure styles) with alcohol use outcomes (Levitt, 2010). Given the mixed findings in the links between attachment and alcohol consumption, and the possibility of a protective function of attachment styles for risk behaviors, the goals of the current study were to explore this function of attachment styles within the associations of alcohol with sleep and emotion regulatory patterns.

Current Study

As discussed earlier, the role of attachment relationships as a protective factor of the effect of alcohol consumption on sleep and emotion regulatory states has not been adequately explored. The goals of the current study are to examine the risk-buffering role of secure attachment styles and the risk-enhancing role of insecure attachment styles (i.e., preoccupied, dismissive, and fearful attachment styles) in the links between alcohol consumption and sleep and emotion regulatory outcomes. The first hypothesis was that attachment styles would moderate the links between alcohol consumption and sleep. The second hypothesis was that attachment styles would moderate the links between binge drinking and sleep patterns. The third hypothesis was that attachment styles would moderate the links between alcohol consumption and emotion regulatory states. Finally, the fourth hypothesis was that attachment styles would moderate the links between binge drinking and emotion regulatory states. For all hypotheses, it was expected that secure attachment styles would serve a protective role in that even under conditions of alcohol consumption or binge drinking, their sleep patterns and emotion regulation would be less disrupted than those who showed insecure attachment styles. Additionally, there were no specific hypotheses about the effects of alcohol for those who did not drink alcohol or were not binge drinkers. It was expected that those with attachment styles indicative of higher anxiety (i.e., preoccupied and fearful) would show worse sleep and emotion regulatory outcomes with and without alcohol consumption or binge drinking.

METHOD

Participants

The sample consisted of 164 undergraduate students (ages 17 -25; M = 19 years) recruited from a public midwestern university. The study received approval from the Internal Review Board (IRB). Participants were recruited from the Psychology Department participant pool in Introduction to Psychology courses and received course credit for their participation. About 80% were freshmen students, with 11% sophomores, 5% juniors, and 4% seniors. The sample consisted of 96% whites, 4% were from other ethnic backgrounds (Hispanic, Asian, and Multiracial), and 68% were females with 32% males.

Procedure

Participants who signed up for the study completed an online survey form on the Qualtrics program. They reported on their demographic information, alcohol consumption, and binge drinking behavior. They also reported on their attachment patterns, sleep patterns (sleep/wake problems, daytime sleepiness, onset latency, perceived sleep quality, and insomnia), and emotion and emotion regulatory skills (emotion awareness, poor impulse control, limited access to emotion regulatory strategies, positive affect, negative affect, and emotion-focused coping).

Measures

Alcohol. Alcohol consumption was measured using the Behavioral Risk Factor Surveillance System Questionnaire (BRFSS) measure by the Centers for Disease Control (CDC, 2015). Participants reported whether they consumed any alcohol in the last 30 days by answering the following questions: 'One drink is equivalent to a 12-ounce beer, a 5ounce glass of wine, or a drink with one shot of liquor. During the past 30 days, on the days when you drank, about how many drinks did you drink on the average?' Alcohol consumption was defined as participants reporting at least one drink (1=alcohol consumed and 0=did not consume alcohol). Participants reported on their binge drinking behavior by answering the question: 'Considering all types of alcoholic beverages, how many times during the past 30 days did you have 5 (for males) or 4 (for females) or more drinks on an occasion?' Binge drinking was measured by indicating whether they reported binge drinking one or more times (i.e., 1= Binge drinking, 0 = no binge drinking).

Attachment. Attachment styles were measured by the Revised Adult Attachment Scale (Collins, 1996), an 18-item measure reported on a 5point scale where 1='not at all characteristic of me' and 5='very characteristic of me.' The measure assessed their romantic relationship attachment style and included subscales of anxiety, closeness, and dependence. The anxiety composite indicated their likelihood of feeling abandoned within the romantic relationship. Closeness assessed their comfort with intimacy whereas dependence assessed the extent to which they trusted a romantic partner. Items from the closeness and dependent scale were also used to create the avoidance subscale. The anxiety and avoidant subscales were then used to create the fourfold attachment groups [i.e., secure (42.1%; n = 69) = low anxiety and low avoidance, preoccupied (29.9 %, n = 49) = high anxiety and low avoidance, dismissive (11.6%; n = 19) = low anxiety and high avoidance, and fearful (16.5%; n = 2) = high anxiety and high avoidance]. The measure has established reliability and validity in prior research and demonstrated good reliability in the current study (anxiety a = .90; avoidance a =.80).

Sleep patterns. The study assessed six indicators of sleep quality. Sleep/Wake Problems and Daytime Sleepiness were measured by the Sleep Habits Survey (Wolfson & Carskadon, 1988). The Sleep/Wake Problems measure (15-items) assessed whether they had sleep disruptions in the past two weeks (e.g., Awakened too early in the morning and could not go back to sleep). Responses were scored on a 5point scale (1 = Everyday / night, 2 = Several times, 3 = Twice, 4 = Once, 5 = Never) and reported good reliability consistent with prior research (a = .80). The daytime sleepiness scale (10-items) assessed whether participants struggled to stay awake (i.e., fought sleep) or had fallen asleep in specific situations during the past two weeks (e.g., a face to face conversation with another person). Items were rated on a 4-point scale (1=never, 2=struggled to stay awake, 3=fallen asleep, and 4=both struggled to stay awake and fallen asleep) and had good reliability in the current study ([alpha] = .81).

Sleep onset latency (how long it takes to fall asleep) was measured using two questions. Participants were asked: 'On school days, after you get to bed at night about how long does it take you to fall asleep (in minutes)?' They also reported on their onset latency overall using the Pittsburgh Sleep Quality Index (PSQI; Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). Specifically, they were asked: 'How long in minutes has it taken for you to fall asleep each night?' Sleep quality was measured by asking them "During the past month how do you rate your sleep quality overall?" Their responses were recorded on a 4-point scale from 1='Very Good' to 4='Very Bad'. The PSQI assesses overall sleep habits and quality and has shown good test-retest reliability and internal consistency (Buysee et al., 1989). Finally, insomnia was measured by the SLEEP-50 Questionnaire subscale (8-items) which uses the DSM-IV criteria to assesses the intensity of an individual's perceived sleep complaints and sleep disorders (Spoormaker, Verbeek, van den Bout, & Klip, 2005). Items were reported on a 4-point scale where 1=not at all, 2=somewhat, 3=rather much, and 4=very much. An example item was: 'I have difficulty falling asleep.' The measure had excellent reliability in prior research and in the current study ([alpha] = .84).

Emotions and emotion regulation. The Difficulty in Emotion Regulation Scale by Gratz and Roemer (2004) was used to assess indexes of emotion regulation, i.e., emotion awareness (6 items), impulse control (5 items), and limited access to emotion regulation strategies (7 items). Items were rated on a 5-point scale (1='almost never' and 5='almost always'). Emotion awareness assessed awareness and attentiveness to their feelings and emotions (e.g., 'I am attentive to my feelings'), and had excellent reliability ([alpha] = .92). The impulse control measure indicated difficulties with impulse control (e.g., 'When I'm upset, I lose control over my behaviors') and had excellent reliability in the current study ([alpha] = .88). The limited access to emotion regulation strategies subscale was a measure of limited strategies utilized to regulate emotions (e.g., 'When I'm upset, I believe that I'll end up feeling very depressed') and showed excellent reliability ([alpha] = .92).

Affect was measured by the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Participants indicated the extent to which they felt that way in the past week on a 5-point scale (1='very slightly or not at all' and 5='extremely'). The positive affect scale (10 items; [alpha] = .91) included items such as 'interested; and 'enthusiastic' whereas the negative affect (10 items; [alpha] = .88) scale had items such as 'distressed' and 'irritable.' Finally, the emotion-focused coping subscale (12 items) was used from the Brief COPE Scale (Carver, 1997). This subscale was created using the self-distraction, venting, self-blame, behavioral disengagement, denial, and substance use subscales of the Brief COPE and is an index of coping strategies focused on dealing with emotions. The subscale had good reliability in the current study ([alpha] = .85) consistent with prior research.

Analytic Plan

Descriptive statistics and correlations, as well as tests of reliability, were examined to determine the trends in the data. For each hypothesis, a 2 X 4 between subjects factorial ANOVA was used (factor 1: consumed alcohol/binge drinking or did not consume alcohol/engaged in binge drinking and factor 2: attachment styles secure, preoccupied, dismissive, and fearful). The outcome measures were sleep patterns and emotion regulation strategies. For all analyses, bootstrapping was used to test the significance of the pairwise comparisons and simple effects test. Bootstrapping estimates bias corrected standard errors, confidence intervals, and accounts for any violations of the assumptions of the ANOVA (Field, 2013).

RESULTS

Preliminary Analyses

Bivariate correlations among key study variables are reported in Table 1. As expected, attachment security, avoidance, and anxiety had small to moderate associations with all indicators of sleep quality and disruptions with the exception of onset latency (overall) with anxious attachment.

All attachment variables had small to moderate associations with indicators of emotion regulation with the exception of emotion awareness with anxious attachment and avoidant attachment with emotion-focused coping. Alcohol consumption was also associated with poor sleep quality, insomnia, poor impulse control, and emotion-focused coping. Binge drinking was associated with sleep/wake problems, poor sleep quality, insomnia, poor impulse control, lower positive affect, and emotion-focused coping.

The majority of the participants (93.90%; n = 154) were below the legal drinking age; among these participants, 80 (48.78% overall) consumed alcohol, whereas 74 (45.12% overall) did not consume alcohol. Of the participants who were above the legal drinking age (n = 10), most consumed alcohol (n = 9; 5.49% overall). With regard to binge drinking among underage participants, 65 (39.63%) engaged in binge drinking at least once during the last 30 days, whereas 89 participants (54.27%) did not engage in binge drinking. Among participants above the legal drinking age, 6 out of 10 reported engaging in binge drinking (3.66% overall). With regard to attachment styles, differences could not be compared across the younger (i.e., < 21 years) and older participants (i.e., >= 21 years), since as mentioned earlier, a majority of the participants were younger than 21 years of age (93.90%). Among the younger participants (n = 154), 65 were secure (42.2%), 46 were preoccupied (29.9%), 18 were dismissive (11.7%), and 25 were fearful (16.2%). Among older participants (n =10), 4 were secure, 3 were preoccupied, 1 was dismissive, and 2 were fearful.

Role of Alcohol Consumption and Attachment Styles in the Prediction of Sleep Patterns

The first hypothesis was that individuals who consumed alcohol and had insecure attachment styles would have greater sleep disruptions (see Table 2). Alcohol did not have a main effect on sleep patterns. There was a significant interaction between alcohol consumption and attachment styles on overall and weekday sleep onset latency (see Figure 3*). Individuals with a secure attachment were protected with regard to sleep onset latency (regardless of alcohol consumption), whereas those with a fearful attachment were protected only when they did not drink. Specifically, for overall sleep onset latency, bootstrapped simple effect tests for the interaction showed that when alcohol was consumed, individuals with a fearful attachment style (M = 38.33, SD = 31.09) had higher onset latency than participants who were secure and preoccupied (secure, M = 18.55, SD = 12.07; preoccupied, M = 19.72, SD = 16.18). However, for those who did not consume alcohol, only those with secure attachment styles (M = 15.75, SD = 9.25) had lower onset latency than those with preoccupied and dismissive styles (preoccupied, M = 28.75, SD = 26.94; dismissive, M = 28.57, SD = 15.74).

Additionally, among individuals with a fearful attachment style, onset latency was higher if they consumed alcohol (M = 38.33, SD = 31.09) than if they did not drink (M = 21.63, SD = 17.32). Findings for weekday onset latency were similar to that for overall onset latency with the exception that when individuals consumed alcohol, those with a fearful style only had higher onset latency than those with a secure attachment.

For all other sleep measures, there was a main effect of attachment styles, specifically for sleep/wake problems, daytime sleepiness, poor sleep quality, and insomnia. Specifically, secure individuals had lower sleep/wake problems than all other groups, lower daytime sleepiness than fearful individuals, and also had better sleep quality and less insomnia than preoccupied or fearful individuals.

Role of Binge Drinking and Attachment Styles in the Prediction of Sleep Patterns

The second hypothesis tested whether individuals who engaged in binge drinking and had insecure versus secure attachment styles would have greater disruptions in sleep patterns (see Table 3). Findings showed a significant interaction between binge drinking and attachment styles for daytime sleepiness (Figure 3). Specifically, among binge drinkers, those who were secure (M = 1.40, SD = 0.33) showed lower daytime sleepiness than dismissive and fearful individuals (dismissive, M = 1.77, SD = 0.50; fearful, M = 1.97, SD = 0.71). Among those that did not binge drink, sleepiness did not differ across attachment styles, suggesting that the absence of binge drinking was protective for all individuals regardless of attachment style. Additionally, daytime sleepiness was higher among dismissive individuals who engaged in binge drinking as compared to those who did not binge drink (binge drinker, M = 1.77, SD = 0.50; nonbinge drinker, M = 1.36, SD = 0.31). As noted in Table 3, there was a significant main effect of binge drinking and attachment for sleep/wake problems, sleep quality, and insomnia. Binge drinkers had higher sleep/wake problems, poorer sleep quality, and a greater likelihood of insomnia than those who were not binge drinkers (see Figure 1*). Findings for attachment are similar to results presented in Table 2 from the previous section and are not discussed further.

Role of Alcohol Consumption and Attachment Styles in the Prediction of Emotion Regulation

The third hypothesis was that individuals who consumed alcohol and had insecure versus secure attachment styles would report ineffective emotion regulation strategies (see Table 4). There was a significant interaction between alcohol and attachment for limited emotion regulation strategies (Figure 4). Securely attached participants were protected, regardless of alcohol, whereas those with a fearful style were at risk, regardless of alcohol consumption. Among those who did not consume alcohol, fearful individuals (M = 2.86, SD = 1.05) used more ineffective emotion regulation strategies than all other groups (Secure: M = 1.69, SD = 0.67; Preoccupied: M = 1.86, SD = 0.80; Dismissive: M = 1.76, SD = 0.74). However, among those who consumed alcohol, secure individuals (M = 1.53, SD = 0.55) had lower levels of ineffective emotion regulation strategies than all other groups (Preoccupied: M = 2.58, SD = 0.95; Dismissive: M = 2.01, SD = 0.75; Fearful: M = 2.62, SD = 0.94), indicating a protective effect of attachment security. Furthermore, preoccupied individuals who consumed alcohol were more likely to use ineffective emotion regulation strategies than those who did not consume alcohol.

Attachment styles differed across measures of emotion regulation (i.e., emotion awareness, poor impulse control, positive affect, negative affect, and emotion-focused coping). Individuals who were dismissive had lower emotion awareness than all other groups, whereas secure individuals had higher emotion awareness than preoccupied individuals. Individuals who were securely attached showed better impulse control than preoccupied or dismissive individuals. With regard to positive affect, fearful individuals had lower positive affect than those who were secure or preoccupied, and preoccupied individuals had lower positive affect than those who were securely attached. Individuals with a fearful attachment style reported higher negative affect than secure or dismissive individuals, and preoccupied individuals had higher negative affect than secure individuals. Finally, secure individuals were less likely to use emotion-focused coping as compared to preoccupied or fearful individuals.

Role of Binge Drinking and Attachment Styles in the Prediction of Emotion Regulation

The fourth hypothesis tested whether individuals who engaged in binge drinking and had insecure versus secure attachment styles would have greater disruptions in emotion regulation (see Table 5). There was a significant interaction between binge drinking and attachment for limited access to emotion regulation strategies showing findings similar to those reported for alcohol consumption in hypothesis 3. Furthermore, simple effect tests also showed that for both preoccupied (Binge: M = 2.73, SD = 1.04; Did not Binge: M = 1.92, SD = 0.71) and dismissive individuals (Binge: M = 2.25, SD = 0.70; Did not Binge: M =1.61, SD = 0.65), those who did binge drink had limited emotion regulation strategies compared to those who did not binge drink (see Figure 4). There was a main effect of binge drinking and attachment styles for poor impulse control, negative affect, and emotion-focused coping. With regard to attachment styles, for impulse control, attachment security was protective compared to insecure attachment, whereas for negative affect and emotion-focused coping, security was protective compared to preoccupied or fearful individuals. Finally, attachment styles differed for emotion awareness and positive affect; results are similar to those reported in Table 4 and are not discussed further.

DISCUSSION

The current study is among the first to examine the protective role of relationship factors, specifically romantic relationship attachment styles on the effects of alcohol consumption on sleep and emotion regulatory factors. The goal of the study was to assess whether relationship security would serve as a protective factor, and specific factors of relationship insecurity would increase the risk associated with alcohol consumption and binge drinking on sleep and emotion regulatory outcomes. Specifically, it was expected that when individuals consumed alcohol or were binge drinkers, secure attachment style would serve as a protective factor of the effect of alcohol on sleep and emotion regulatory factors. There was no specific hypothesis about the pattern of effects of alcohol on the outcomes for those who did not drink alcohol or were not binge drinkers. It was expected that those with attachment styles indicative of higher anxiety (i.e., preoccupied and fearful) would have worse sleep and emotion regulatory outcomes with and without alcohol consumption or binge drinking.

Findings show partial support for hypothesis 1 with regard to the outcome measures of sleep onset latency (weekdays and overall latency). Results show that in the context of alcohol consumption, fearful individuals show greater time in bed before sleep onset (i.e., about 38-40 minutes) than secure and preoccupied persons. Therefore, alcohol consumption is a risk factor for individuals with fearful attachment as compared to those with secure or preoccupied styles. When alcohol is not consumed, being secure is protective, i.e., they take less time to fall asleep than those with preoccupied or dismissive attachment. These findings indicate that secure attachment is protective whether or not they consume alcohol. Individuals who were securely attached were more likely to report lower sleep/wake problems than all other groups, lower daytime sleepiness than those who were fearful, and better sleep quality and fewer symptoms of insomnia than fearful or preoccupied individuals.

Past research shows that individuals with alcohol problems are more likely to exhibit insecure attachment styles than those without alcohol problems (Wyrzykowska et al., 2014). However, the current study was novel in its focus on the protective role of attachment security. The study is consistent with past research (e.g., Scharfe & Eldredge, 2001) which shows that individuals who were fearful had the worst sleep outcomes and those who were securely attached had the best sleep outcomes. Furthermore, they showed that preoccupied individuals had fewer sleep problems than those who were fearful, whereas the dismissive attachment style was not linked to sleep problems (Scharfe & Eldredge, 2001). Current study findings are also consistent with non-clinical studies which showed that individuals who were securely attached had the least sleep problems and lowest sleep activity; this was followed by dismissive, fearful, and preoccupied. The current study findings that individuals with attachment styles indicative of anxiety would have worse sleep than the other insecure styles (e.g., dismissive) was also consistent with past research (Adams, Stoops, & Skomro, 2014). However, the differences between insecure patterns were only noted in the current study when alcohol was consumed. In the absence of alcohol consumption, attachment security was protective for sleep problems.

Results partially supported hypothesis 2, showing a significant interaction between binge drinking and attachment styles for daytime sleepiness. Specifically, an absence of binge drinking was protective for all attachment styles, i.e., they reported no differences in daytime sleepiness across attachment. When individuals engaged in binge drinking, secure attachment was protective in terms of daytime sleepiness, i.e., attachment security predicted less daytime sleepiness as compared to dismissive or fearful styles. Additionally, daytime sleepiness was important for dismissive individuals in the context of binge drinking, i.e., they were more likely to report higher sleepiness when they resorted to binge drinking. Furthermore, binge drinkers had higher levels of sleep/wake problems, poor self-reported sleep quality, and greater symptoms of insomnia than those who did not binge drink. Findings are consistent with research by Roehrs and Roth (2001), who found that nonalcoholic college students were affected in terms of daytime alertness due to higher alcohol consumption. They found that daytime sleepiness was often caused by sleep disruptions in the latter part of the night, sleep-related breathing problems, or parasomnia (abnormal sleep behaviors) that are often the result of excessive drinking. Furthermore, the current study sampled students who were predominantly in the freshmen year; past research shows that this sample is at greater risk for sleep disruptions due to alcohol consumption (Singleton & Wolfson, 2009).

Hypothesis 3 received partial support with regard to the outcome measure of limited access to emotion regulation strategies. The findings are promising in that individuals with attachment security have better emotion regulation strategies irrespective of whether they consume alcohol. However fearful individuals were at risk for dysregulated emotion regulation strategies whether or not they consumed alcohol. This finding is consistent with prior research which shows that alcohol disorders are linked with limited access to emotion regulation strategies. Interestingly, there was no support for alcohol predicting poor impulse control, which has been noted in past research (Tripp et al., 2015). However, findings can be explained by neurobiological studies (e.g., Oscar-Berman & Marinkovic, 2003) which show that alcohol affects regions of the brain that control emotions such as the amygdala and other limbic system areas. Furthermore, the prefrontal cortex functions, such as planning and problem-solving, may be disrupted, which accounts for disruptions in a wide repertoire of problem-solving abilities seen in individuals who have limited access to emotion regulation strategies.

When individuals did not consume alcohol, those who had a preoccupied and dismissive attachment style were protected, i.e., they used more effective emotion regulation strategies than fearful individuals. When individuals did consume alcohol, all the insecure styles of attachment (preoccupied, dismissive, and fearful) were at risk for ineffective emotion regulation strategies. Additionally, regardless of alcohol consumption, individuals with secure attachment styles were protected with regard to emotion awareness more than all insecure styles of attachment. Securely attached individuals also had better impulse control than preoccupied or dismissive individuals and were less likely to use emotion-focused coping than those who were fearful or preoccupied. Additionally, dismissive individuals had lower emotion awareness than all other groups. Fearful individuals showed lower positive affect than secure or preoccupied individuals and higher negative affect than secure or dismissive individuals. Finally, preoccupied individuals showed lower emotion awareness and lower positive affect than securely attached individuals. Although bivariate associations showed no links between emotion awareness and the attachment anxiety dimension, results of the hypotheses showed that preoccupied individuals were lower on emotion awareness than securely attached individuals, although they were higher than dismissive individuals. Additionally, although there were no bivariate links between emotion-focused coping and the avoidant attachment dimension, results showed that securely attached individuals did use less emotion focused coping than fearful individuals (who were high on the avoidance and anxiety dimension).

Thus, findings suggest that attachment security serves as a risk buffering factor for emotional awareness and dysregulation. Although it is not clear why attachment security may protect against emotion dysregulation even when alcohol is consumed, past research on marriage has shown that relational factors such as monitoring of relationship factors and social aspects of the relationship may be protective for individuals (Kendler et al., 2016). This benefit of relationship characteristics may also apply within committed relationships among securely attached unmarried couples. Within the context of the relationship, individuals may learn effective conflict resolution skills. Individuals who are securely attached may trust and depend on their partner when faced with a stressful situation. This process allows them to be more aware of their emotions, whether positive or negative. Furthermore, past research is consistent with the current study in showing that securely attached individuals had better impulse control and emotional stability. They showed less distress in the context of a threatening situation as compared to anxious or avoidant individuals who displayed increased distress and poor well-being as indicated by psychiatric disorders (Mikulincer & Shaver, 2008). Research also shows that anxious individuals show problems with anger management and uncontrollable emotions following a conflict. Conversely, avoidant individuals do not show overt anger but may display intense physiological arousal (Diamond & Hicks, 2005).

Findings show partial support for hypothesis 4. The findings for the interactive role of binge drinking and attachment styles in the prediction of limited emotion regulation strategies are consistent with the findings reported for alcohol consumption. Specifically, as in the case of alcohol consumption, those with a fearful style were at risk and individuals with a secure style were protected in terms of access to effective emotion regulation strategies. When individuals did not binge drink, preoccupied and dismissive individuals were protected as compared to those who were fearful. However, when individuals did binge drink, all those who reported insecure attachment styles used disrupted emotion regulation strategies. Furthermore, binge drinking was riskier for preoccupied and dismissive individuals as compared to those who did not binge drink. Binge drinking also impacted impulse control, negative affect, and emotion-focused coping regardless of attachment styles, i.e., binge drinkers showed poor impulse control, higher negative affect, and greater emotion-focused coping strategies than those who did not engage in binge drinking. The above findings are supported by research which shows that alcohol dependence is linked with specific patterns of emotional disturbances (Petit et al., 2015). Furthermore, research on alcohol use across attachment styles has shown that anxious individuals are more likely to use alcohol to cope than avoidant individuals (Levitt & Leonard, 2015). In the current study, however, abstinence from binge drinking protected both preoccupied (high anxiety) and dismissive (high avoidance) individuals as compared to those who were fearful (high anxiety and high avoidance).

To conclude, the current study was a novel exploration of the protective role of romantic relationships attachment with regard to the effect of alcohol on sleep and emotion regulatory strategies using multiple measures of sleep quality and emotion-related factors. Findings contribute to the literature on attachment styles as they relate to alcohol consumption and sleep patterns. Study findings serve to inform prevention and intervention studies on sleep, alcohol, and relationshipbased therapy. The study analyses used bootstrapping, which accounted for any violations of the assumptions of ANOVA. The study also had a few limitations. The study sample was relatively small, which could have indicated lower power to detect findings for the interactive effects. Due to the relatively small sample size, extraneous factors which may have played an important role in sleep and emotion regulation in the current college sample, could not be controlled. Since this was a younger sample (18-25 years), many participants may not have honestly reported on their alcohol intake since they were below the drinking age (i.e., < 21 years). Furthermore, participants only reported on their own attachment styles but did not report the attachment style of their partner. Past research on attachment styles has shown effects of attachment styles across partners.

Future research could emphasize the protective role of attachment styles for the effect of alcohol on sleep and emotions when dyadic partners show similar versus different attachment styles. Furthermore, future research could also emphasize whether the presence of attachment security was protective even if the partner (but not the participant) displayed this style of attachment. The study has implications for intervention and prevention research that seeks to target sleep disorders as well as alcohol use disorders within a young-adult population. Given that sleep disruptions, alcohol problems, and mental health problems are often comorbid, there is a need for programs focused on prevention or interventions for sleep disorders among young people to emphasize the role of alcohol and emotional and mental dysfunction. Intervention research with such an emphasis could focus on relationship and communication skills directed towards effective conflict resolution skills, given the protective role of relationship factors. Future research on prevention of alcohol and other risky behaviors should also focus on building effective emotion regulatory and coping skills. Finally, future research could focus on married couples and the role of alcohol and attachment styles on sleep and emotion regulation among couples.

REFERENCES

Adams, G., Stoops, M., & Skomro, R. (2014). Sleep tight: Exploring the relationship between sleep and attachment style across the lifespan. Sleep Medicine Reviews, 18(6), 495-507. http://dx.doi.org/10.1016/ j.smrv. 2014. 03.002

Bartholomew, K., & Horowitz, L. (1991). Attachment styles among young adults: A test of a four-category model. Journal of Personality and Social Psychology, 61(2), 226-244. http://dx.doi.org/10.1037//0022-3514.61.2.226

Born, J., Kellner, C., Uthgennant, D., Kern, W., & Fehm, H. (1992). Vasopressin regulates human sleep by reducing rapid-eye-movement sleep. American Journal of Physiology: Endocrinology and Metabolism, 262(3), E295-E300.

Bowlby, J. (1969). Attachment and loss (2nd ed.). New York: Basic Books. Brennan, K. A., & Shaver, P. R. (1995). Dimensions of adult attachment, affect regulation, and romantic relationship functioning. Personality and Social Psychology Bulletin, 21, 267-283.

Brower, K. (2003). Insomnia, alcoholism and relapse. Sleep Medicine Reviews, 7(6), 523-539. http://dx.doi.org/10.1016/s1087-0792(03)90005-0 Buysse, D., Reynolds, C., Monk, T., Berman, S., & Kupfer, D. (1989). The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193-213. http://dx.doi.org/ 10.1016/ 0165-1781(89)90047-4

Carver, C. (1997). You want to measure coping but your protocol's too long: Consider the brief cope. International Journal of Behavioral Medicine, 4(1), 92-100. http://dx.doi.org/10.1207/s15327558ijbm0401_6

Center for Disease Control and Prevention. (2015). Behavioral Risk Factor Surveillance System Questionnaire. Retrieved 17 March 2017, from https:// www.cdc.gov/brfss/questionnaires/pdf-ques/2016_brfss_questionnaire_final.pdf

Collins, N. (1996). Working models of attachment: Implications for explanation, emotion, and behavior. Journal of Personality and Social Psychology, 71(4), 810-832. http://dx.doi.org/104 037//0022-3514.71.4.810

Diamond, L., & Hicks, A. (2005). Attachment style, current relationship security, and negative emotions: The mediating role of physiological regulation. Journal of Social and Personal Relationships, 22(4), 499-518. http://dx.doi.org/ 10.1177/0265407505054520

Ebrahim, I., Shapiro, C., Williams, A., & Fenwick, P. (2013). Alcohol and sleep I: Effects on normal sleep. Alcoholism: Clinical and Experimental Research, 37(4), 539'-549. http://dx.doi.org/10.1111/acer.12006 Field, A. (2013). Discovering Statistics using IBM SPSS (4th ed.). London: SAGE.

Fucito, L., DeMartini, K., Hanrahan, T., Whittemore, R., Yaggi, H., & Redeker, N. (2015). Perceptions of heavy-drinking college students about a sleep and alcohol health intervention. Behavioral Sleep Medicine, 13(5), 395-411. http://dx.doi.org/10.1080/15402002.2014.919919

Gratz, K., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral Assessment, 26(1), 41-54. http://dx. doi.org/10.1023/b: joba. 0000007455.08539.94

Hazan, C., & Shaver, P. (1987). Romantic love conceptualized as an attachment process. Journal of Personality and Social Psychology, 52(3), 511-524. http://dx.doi.org/10.1037//0022-3514.52.3.511

Kendler, K., Lonn, S., Salvatore, J., Sundquist, J., & Sundquist, K. (2016). Effect of marriage on risk for onset of alcohol use disorder: A longitudinal and corelative analysis in a swedish national sample. American Journal of Psychiatry, 173(9), 911-918. http://dx.doi.org/10.1176/ appi.ajp. 2016. 15111373

Kenney, S., Lac, A., LaBrie, J., Hummer, J., & Pham, A. (2013). Mental health, sleep quality, drinking motives, and alcohol-related consequences: A pathanalytic model. Journal of Studies on Alcohol and Drugs, 74(6), 841-851. http://dx.doi.org/10.15288/jsad.2013.74.841

Lancel, M., Kromer, S., & Neumann, I. (2003). Intracerebral oxytocin modulates sleep-wake behaviour in male rats. Regulatory Peptides, 114(2-3), 145-152. http ://dx.doi.org/10.1016/s0167-0115(03)00118-6

Levitt, A. (2010). Adult Attachment Dynamics as a Predictor of Daily Alcohol use and Romantic Relationship Functioning. [Unpublished doctoral dissertation]. University of Missouri.

Levitt, A., & Leonard, K. (2015). Insecure attachment styles, relationshipdrinking contexts, and marital alcohol problems: Testing the mediating role of relationship-specific drinking-to-cope motives. Psychology of Addictive Behaviors, 29(3), 696-705. http://dx.doi.org/10.1037/adb0000064

Mikulincer, M., & Shaver, P. (2008). Adult attachment and affect regulation. In J. Cassidy & P. Shaver, Handbook of Attachment: Theory, research and clinical applications (2nd ed., pp. 503-531). New York, NY: Guilford Press.

Moos, R., & Moos, B. (2006). Rates and predictors of relapse after natural and treated remission from alcohol use disorders. Addiction, 101(2), 212-222. Oscar-Berman, M., & Marinkovic, K. (2003). Alcoholism and the brain: An overview. Alcohol Research and Health, 27(2), 125-133.

Petit, G., Luminet, O., Maurage, F., Tecco, J., Lechantre, S., & Ferauge, M., . . .de Timary,. P. (2015). Emotion regulation in alcohol dependence. Alcoholism: Clinical and Experimental Research, 39(12), 2471-2479. http://dx.doi.org/10.1111/ acer.12914

Pietromonaco, P., & Powers, S. (2015). Attachment and health-related physiological stress processes. Current Opinion in Psychology, 1, 34-39. http://dx.doi.org/10.1016/j.copsyc.2014.12.001

Reis, S., Curtis, J., & Reid A. (2012). Attachment styles and alcohol problems in emerging adulthood: A pilot test of an integrative model. Mental Health and Substance Use: Dual Diagnosis 5,115-131. http://dx.doi.org/10.1080/ 17523281.2011.619503

Roehrs, T., & Roth, T. (2001). Sleep, sleepiness, sleep disorders and alcohol use and abuse. Sleep Medicine Reviews, 5(4), 287-297. http://dx.doi.org/ 10.1053/smrv.2001.0162

Scharfe, E., & Eldredge, D. (2001). Associations between attachment representations and health behaviors in late adolescence. Journal of Health Psychology, 6(3), 295-307. http://dx.doi.org/10.1177/135910530100600303

Singleton, R., & Wolfson, A. (2009). Alcohol consumption, sleep, and academic performance among college students. Journal of Studies on Alcohol and Drugs, 70(3), 355-363. http://dx.doi.org/10.15288/jsad.2009.70.355

Sivertsen, B., Skogen, J., Jakobsen, R., & Hysing, M. (2015). Sleep and use of alcohol and drug in adolescence. A large population-based study of Norwegian adolescents aged 16 to 19 years. Drug and Alcohol Dependence, 149, 180-186. http://dx.doi.org/10.1016/j.drugalcdep.2015.01.045

Substance Abuse and Mental Health Services Administration. (2014). Results from the 2013 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series H-48, HHS Publication No. (SMA) 144863. Retrieved 17 March 2017, from https://www.samhsa.gov/data/sites/ default/files/ NSDUHresultsPDFWHTML2013/Web/NSDUHresults2013.pdf

Tapert, S. F., Caldwell, L. & Burke, C. (2004/2005). Alcohol and the adolescent brain: Human studies. Alcohol Research and Health, 28(4), 205-212

Tripp, J., McDevitt-Murphy, M., Avery, M., & Bracken, K. (2015). PTSD symptoms, emotion dysregulation, and alcohol-related consequences among college students with a trauma history. Journal of Dual Diagnosis, 11(2), 107-117. http://dx.doi.org/10.1080/15504263.2015.1025013

Troxel, W. (2010). It's more than sex: Exploring the dyadic nature of sleep and implications for health. Psychosomatic Medicine, 72(6), 578-586. http://dx. doi.org/10.1097/psy.0b013e3181 de7ff8

U.S. Department of Health and Human Services (HHS), Substance Abuse and Mental Health Services Administration (SAMHSA). (2016). Report to Congress on the Prevention and Reduction of Underage Drinking. Retrieved 17 March 2017, from https://www.stopalcoholabuse.gov/ resources/ report tocongress/ rtc2016.aspx

Uvnas-Moberg, K., Ahlenius, S., Hillegaart, V., & Alster, P. (1994). High doses of oxytocin cause sedation and low doses cause an anxiolytic-like effect in male rats. Pharmacology Biochemistry and Behavior, 49(1), 101-106. http://dx.doi.org/10.1016/0091-3057(94)90462-6

Watson, D., Clark, L., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. http://dx.doi.org/ 10.1037//0022-3514.54.6.1063

Weich, S. (2010). The epidemiology of sleep and depression. In F. Cappuccio, M. Miller & S. Locklet, Sleep, Health and Society: From Aetiology to Public Health (1st ed., pp. 178-190). Oxford: Oxford University Press.

Wolfson, A., & Carskadon, M. (1998). Sleep Schedules and Daytime Functioning in Adolescents. Child Development, 69(4), 875. http://dx.doi.org/ 10. 2307/1132351

Wyrzykowska, E., Glogowska, K., & Mickiewicz, K. (2014). Attachment relationships among alcohol dependent persons. Alcoholism and Drug Addiction, 27(2), 145-161. http://dx.doi.org/10.1016/s0867-4361(14)70010-0

Note: The asterisks (*) placed by the mention of figures is to indicate that these figures have been removed to save space. They are available upon request from the author.

Dilbur D. Arsiwalla

University of Northern Iowa

Author info: Correspondence should be sent to: Dr. Dilbur D. Arsiwalla, University of Northern Iowa, Department of Psychology, 1062 Bartlett Hall, Cedar Falls, IA 50614. Email: dilbur.arsiwalla@uni.edu North American Journal of Psychology, 2017, Vol. 19, No. 2, 499-524.

Caption: FIGURE 3 Figure Indicating Interaction of Attachment Styles by Alcohol or Binge Drinking Across Sleep Outcomes. Error Bars Indicate 95% Confidence Intervals.

Caption: FIGURE 4 Figure Indicating Interaction of Attachment Styles by Alcohol or Binge Drinking Across Emotion Regulatory Outcomes. Error Bars Indicate 95% Confidence Intervals
TABLE 1 Bivariate Correlations Among Key Study Variables

                                         Binge
          Age      Male     Ethnicity   Drinking

S/WP     -.02    -.21 **       .02       .24 **
DS       -.10    -.29 ***      .07        .14
OL(w)     .07      -.11        .11        .03
OL        .03      -.08        .11        -.00
SQ       -.08    -.25 **       .04       .25 **
Insom.   -.02    -.25 **      -.02       .22 **
EA        .04      -.14       -.02        -.08
PIC      .16 *     -.09        .06       .19 *
LER       .02      -.12       -.05        .15
PA        .03      .14        -.03       -.19 *
NA       -.07     -.16 *      -.05        .11
EFC       .05    -.23 **      -.09       .23 **

                    Secure    Avoidant   Anxious
         Alcohol   Attach.    Attach.    Attach.

S/WP       .14     -.42 ***   .32 ***    .40 ***
DS         .07     -.22 **     .17 *      .21 **
OL(w)      .07     -.28 ***   .29 ***     .19 *
OL         .04     -.26 **    .28 ***      .15
SQ        .16 *    -.32 ***    .21 **    .34 ***
Insom.    .16 *    -.28 ***    .25 **     .23 **
EA         .01      .21 **    -.29 ***     -.06
PIC       .16 *    -.24 **     .24 **     .16 *
LER        .11     -.49 ***   .34 ***    .50 ***
PA        -.13     .32 ***    -.34 ***   -.20 ***
NA         .09     -.36 ***    .26 **    .36 ***
EFC       .18 *    -.27 **      .15      .31 ***

Note. * p < .05, ** p < .01, *** p < .001
For ethnicity (1=White American, 0= Non-White Americans),
for the variable Male (1=Male, 0=Female). S/WP = Sleep/Wake
Problems; DS = Daytime Sleepiness; OL = OL(w) = Onset Latency
(weekdays); Onset Latency; SQ = Sleep Quality; EA = Emotion
Awareness; PIC = Poor Impulse Control; LER = Limited Emotion
Regulation; PA = Positive Affect; NA = Negative Affect;
EFC = Emotion Focused Coping;

TABLE 2 Analysis of Covariance Summary for Alcohol Consumption
Predicting Sleep Patterns

Source            Sum of    df     Mean         F          Partial
                 Squares          Square                [[eta].sub.2]
S/WP
Alcohol            .656     1      .656       2.648         .017
Attachment        6.869     3     2.290     9.245 ***       .151
A xA               .143     3      .048       .192          .004
DS
Alcohol            .435     1      .435       2.332         .015
Attachment        1.993     3      .664      3.565 *        .064
A xA               .901     3      .300       1.612         .030
OL(w)
Alcohol          108.222    1    108.222      .322          .002
Attachment       4148.198   3    1382.733   4.109 **        .073
A xA             2859.878   3    953.293     2.833 *        .052
OL (overall)
Alcohol           26.961    1     26.961      .084          .001
Attachment       3727.047   3    1242.349    3.854 *        .069
A xA             3147.631   3    1049.210    3.255 *        .059
Sleep Quality
Alcohol           1.846     1     1.846       3.601         .023
Attachment        9.046     3     3.015     5.881 **        .102
A xA              4.092     3     1.364       2.660         .049
Insomnia
Alcohol            .915     1      .915       2.202         .014
Attachment        5.146     3     1.715     4.127 **        .074
A xA               .555     3      .185       .445          .008

* p <.05; ** p < 0.01; *** p <.001
S/WP = Sleep/Wake Problems; DS = Daytime Sleepiness;
OL(w) = Onset Latency (weekdays); OL = Onset Latency; SQ = Sleep
Quality; AxA = Alcohol by Attachment

TABLE 3 Analysis of Covariance Summary for Binge Drinking
Predicting Sleep Patterns

Source        Sum of    df     Mean        F          Partial
             Squares          Square               [[eta].sub.2]

S/WP
Binge         2.527     1     2.527     10.734 **       .064
Attachment    6.895     3     2.298     9.762 ***       .158
B xA           .445     3      .148       .630          .012
DS
Binge         1.294     1     1.294     7.179 **        .044
Attachment    2.322     3      .774     4.293 **        .076
B x A         1.446     3      .482     2.674 *         .049
OL(w)
Binge         42.433    1     42.433      .124          .001
Attachment   4276.661   3    1425.554   4.155 **        .074
B x A        1962.548   3    654.183     1.907          .035
OL
Binge          .389     1      .389       .001          .000
Attachment   3935.395   3    1311.798   3.982 **        .071
B xA         2018.667   3    672.889     2.042          .038
so_
Binge         4.604     1     4.604     9.127 **        .055
Attachment    9.812     3     3.271     6.484 ***       .111
B xA          2.262     3      .754      1.495          .028
Insomnia
Binge         2.525     1     2.525     6.195 *         .038
Attachment    5.242     3     1.747     4.287 **        .076
B xA           .254     3      .085       .208          .004

* p <.05; ** p < 0.01; *** p<.001
S/WP = Sleep/Wake Problems; DS = Daytime Sleepiness;
OL(w) = Onset Latency (weekdays); OL = Onset Latency; SQ = Sleep
Quality; B xA = Binge by Attachment

TABLE 4 Analysis of Covariance Summary for Alcohol Consumption
Predicting Emotion Regulation

Source       Sum of    df    Mean        F           Partial
             Squares        Square                [[eta].sub.2]

EA
Alcohol       .501     1     .501       .566           .004
Attachment   16.761    3    5.587    6.303 ***         .108
A xA          4.627    3    1.542      1.740           .032
PIC
Alcohol       .875     1     .875      2.307           .015
Attachment    3.577    3    1.192     3.145 *          .057
A xA          1.297    3     .432      1.140           .021
L ERS
Alcohol       .638     1     .638      1.025           .007
Attachment   27.660    3    9.220    14.820 ***        .222
A xA          6.539    3    2.180     3.504 *          .063
PA
Alcohol       .493     1     .493       .899           .006
Attachment   12.152    3    4.051    7.388 ***         .124
A xA          2.826    3     .942      1.718           .032
N A
Alcohol       .873     1     .873      1.747           .011
Attachment    9.533    3    3.178    6.359 ***         .109
A xA          .979     3     .326       .653           .012
EC
Alcohol       .754     1     .754      3.151~          .020
Attachment    3.031    3    1.010     4.225 **         .075
A xA          .457     3     .152       .637           .012

* p <.05; ** p < 0.01; *** p<.001
EA = Emotion Awareness; PIC = Poor Impulse Control;
LERS = Limited ER Strategies; PA = Positive Affect; NA = Negative
Affect; EC = Emotion Coping; A xA = Alcohol by Attachment

TABLE 5 Analysis of Covariance Summary for Binge Drinking
Predicting Emotion Regulation

Source       Sum of    df    Mean        F          Partial
             Squares        Square               [[eta].sub.2]

EA
Binge         .507     1     .507      .560           .004
Attachment   13.764    3    4.588    5.070 **         .089
B xA          1.437    3     .479      .529           .010
PIC
Binge         2.153    1    2.153     5.830 *         .036
Attachment    4.220    3    1.407     3.810 *         .068
B xA          2.310    3     .770      2.085          .039
LERS
Binge         3.020    1    3.020     5.056 *         .031
Attachment   30.734    3    10.245   17.151 ***       .248
B xA          9.219    3    3.073    5.144 **         .090
PA
Binge         1.982    1    1.982     3.614~          .023
Attachment   11.701    3    3.900    7.111 ***        .120
B xA          1.056    3     .352      .642           .012
N A
Binge         2.071    1    2.071     4.224 *         .026
Attachment    9.986    3    3.329    6.791 ***        .116
B xA          2.135    3     .712      1.452          .027
E FC
Binge         2.146    1    2.146    9.462 **         .057
Attachment    3.519    3    1.173    5.172 **         .090
B xA          1.435    3     .478      2.110          .039

* p <.05; ** p < 0.01; *** p <.001
EA = Emotion Awareness; PIC = Poor Impulse Control;
LERS = Limited ER Strategies; PA = Positive Affect; NA = Negative
Affect; EFC = Emotion Focused Coping; B xA = Binge by Attachment
COPYRIGHT 2017 North American Journal of Psychology
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2017 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Arsiwalla, Dilbur D.
Publication:North American Journal of Psychology
Article Type:Report
Date:Jun 1, 2017
Words:9430
Previous Article:Development and validation of a new parental authority instrument (PAI).
Next Article:The differential relationship among peer group indicators and internalizing symptoms in a problematic absenteeism population.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |