Predictors of sleep quality: Depression, anxiety, and sleep self-efficacy

The objective of the current study was to examine the relationship between depression, anxiety, sleep self-efficacy, and sleep quality among college students by using both objective measures and self-reported data. Participants included 27 undergraduate students from a small liberal arts college who wore ActiGraph wristbands for a period of seven nights. Participants also completed anxiety, depression, sleep self-efficacy, and subjective sleep quality scales. Results indicated that higher sleep self-efficacy scores were associated with lower anxiety and depression scores. Higher subjective sleep quality was associated with higher sleep self-efficacy scores and lower depression and anxiety scores. This study supports the need for emphasis on the importance of improving subjective sleep quality which in turn may influence mental health issues. PREDICTORS OF SLEEP QUALITY 2 Predictors of Sleep Quality: Depression, Anxiety, and Sleep Self-Efficacy Poor sleep quality and sleep disorders pose a significant problem in the United States. In 2014, the National Sleep Foundation reported that almost half of Americans are affected by poor sleep at least once a week, and the impact of sleep deprivation on cognition and daily functioning has been studied extensively across many populations (Pilcher & Huffcutt, 1996). Up to 60% of college students have reported sleeping poorly (Lund, Reider, Whiting, & Prichard, 2010), which has been shown to have a negative impact on students’ academic endeavors (Chiang, Arendt, Zheng, & Hanisch, 2014). Academic pursuits are further hindered by mental health issues in college students. In 2003, roughly 50% of college students qualified for at least one disorder according to the DSM-IV (Blanco et al., 2008). The purpose of the current study was to examine relationships between college students’ sleep quality, anxiety, depression, and sleep self-efficacy – that is, an individual’s confidence that they can sleep well. Self-efficacy plays a significant role in an individual’s ability to successfully tackle a problem and has been shown to be relevant to sleep – a daily task that can present significant difficulty to a large population of people (Suh et al., 2012; Lund et al., 2010). Bandura’s theory of self-efficacy (1977) suggests that an individual’s expectations and perceptions of a task significantly influence the quality of a person’s effort at a task, and therefore impacts their ability to perform that task. Bandura’s (1977) study utilized behavioral tasks of varying difficulty to demonstrate the impact of self-efficacy, where tasks were ordered according to the amount of effort required to complete them. Higher self-efficacy was correlated with greater perseverance at tasks and therefore greater success at those tasks. While Bandura (1977) studied general self-efficacy, Rutledge, Guardia, and Bluestein (2013) specifically depicted the relationship between sleep self-efficacy and overall sleep PREDICTORS OF SLEEP QUALITY 3 quality. Rutledge et al. (2013) included participants with clinically significant insomnia. Results indicated that insomnia severity, dysfunctional beliefs, and depressive symptoms all negatively correlated with sleep self-efficacy. These outcomes support Bandura’s theory (1977) and suggest that patients with a stronger belief in their treatment are more likely to see positive results. Furthermore, Rutledge et al. (2013) provided support for the link between low sleep self-efficacy and depression – depression sufferers were more likely to have lower self-efficacy, inhibiting improvement of sleep quality. Lund and colleagues (2010) demonstrated the prevalence of poor sleep in college students aged between 17 and 24 years. The study indicated that physical and psychological health problems were more common (i.e., 60% of the sample) in students with poorer sleep quality. Poor sleepers also reported more negative moods, including higher rates of fatigue, tension, confusion, anger, and depression. The study also indicated that poor sleep was best explained by perceived stress. This was consistent with findings by Buboltz and colleagues (2009), in which 60% of 742 undergraduate students at public universities reported occasional sleep problems, and over half reported morning tiredness. Cognitive functioning is also known to be markedly different in poor sleepers (Harvey, 2000; Suh et al., 2012), which is particularly relevant for college students. Harvey (2000) hypothesized that pre-sleep worries and concerns would be more prevalent in insomniacs as opposed to their well-sleeping counterparts. Participants included 30 people, who met the diagnostic criteria for insomnia as stated in the DSM-III, as well as 30 controls. The primary sleep complaint of the experimental group were delays in sleep-onset; participants with other primary sleep concerns were excluded. Researchers found that compared to good sleepers, insomniacs had a higher propensity for worrying and cognitive interference – defined as how often participants’ thoughts kept them awake on a typical night in the previous month. PREDICTORS OF SLEEP QUALITY 4 Insomniacs experienced worrying thoughts for an extended period of time and found the thoughts to be more preoccupying when compared to the good sleepers. In the experimental group, 77% indicated cognitive interference as a primary factor in poorer sleep quality, supporting the notion that cognitive processes have some impact on sleep. Suh and colleagues (2012) expanded on the relationship between cognition and sleep disturbance by exploring cognitive predictors of multiple symptoms of insomnia: difficulty with sleep initiation, maintenance, and early morning awakenings. The study consisted of a multiple symptom group and a single symptom group. Measures for potential predictors of insomnia symptoms included indices for insomnia severity, content of thoughts, dysfunctional attitudes toward sleep, sleep self-efficacy, depression, and morningness-eveningness preference. Sleep self-efficacy served as a significant predictor of multiple insomnia symptoms. Of the patients who scored lower sleep self-efficacy, 73.4% of the sample were also a part of the multiple insomnia symptom subgroup. These participants had longer sleep onset latency and showed worse depression symptoms. Bluestein, Rutledge, and Healey (2010) demonstrated a correlation between insomnia severity and depression, as well as dysfunctional beliefs and sleep self-efficacy. The study consisted of adult participants with diagnosed insomnia. Health, depression, dysfunctional beliefs, and self-efficacy correlated significantly with insomnia severity – lower self-efficacy and higher depressive scores predicted insomnia severity the best. Nyer and colleagues (2013) additionally demonstrated the relationship between depressive symptomology, intense anxiety, and sleep disturbance. The study’s sample consisted of 287 students who indicated significant depression symptoms as determined by a score of 13 or greater on the Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961). Of this sample 220 participants PREDICTORS OF SLEEP QUALITY 5 also indicated disturbed sleep. Results showed that the group with both depressive symptoms and sleep disturbance experienced a higher level of impairment (both physical and cognitive) as well as increased anxiety. Although some studies regarding sleep, anxiety, and depressive symptomatology utilize measures such as the EEG to record sleep (e.g., Riemann, Berger, & Voderholzer, 2001) the bulk of research relies on self-reported sleep questionnaires. Self-report can be easily influenced by factors outside of the researchers’ control, such as the honesty of participants, subjective understandings about a question, or the reliability of a participant’s memory. Furthermore, mere expectations about an event or situation can alter a participant’s self-report. For example, O’Donnell, Silva, Münch, Ronda, Wang, and Duffy (2009) compared the objective and subjective sleep measures of older adults. Responses from 24 older adult subjects (age ranged from 55-74 years old) were collected over the course of 32 days of inpatient participation void of time-telling devices and windows. Sleep was monitored using an EEG as well as post-sleep questionnaires that asked participants to self-report sleep quality. O’Donnell et al. (2009) found that the association between subjective and objective sleep measures were modest. Participants were recorded as rating their baseline sleep as “good”, despite the fact that the objective measure indicated poor sleep quality. This is consistent with research by Buysse, Reynolds, Monk, Hoch, Yeager, and Kupfer (1991) who theorized that the perception of sleep by older adults may be altered by gradual sleep quality changes associated with aging. Similarly, self-report data collected from college students may be affected by general expectations about being in college – poor sleep may be considered commonplace and may, therefore, be misinterpreted as “good” sleep. The current study will seek to explore this potential problem by utilizing both objective and subjective sleep quality measures. PREDICTORS OF SLEEP QUALITY 6 The aforementioned studies have demonstrated the effects of anxiety, depression, and sleep self-efficacy on overall sleep quality. However, most of these studies are similar in that they utilized questionnaires to measure these variables. The present study contributes to this field by utilizing a questionnaire, as well as a sleep monitor that objectively measures each participant’s quality of sleep. The device used in this study–the ActiGraph wGT3X-BT–has been shown to be similar in accuracy to polysomnography (PSG; a well-established measure of sleep) for measuring the sleep quality of non-clinical patients (Quante et al., 2018). The benefit of utilizing both a questionnaire and an objective sleep measure is the potential to indicate which