Evaluation of sleep quality among nursing faculty: Application of the Pittsburgh Sleep Quality Index—A descriptive correlational study

Abstract Aim The aim of this study was to describe the overall sleep quality, sleep patterns and severity of sleep difficulties among nursing faculty using the Pittsburgh Sleep Quality Index (PSQI). Design Cross‐sectional descriptive and correlational study. Methods A survey of faculty recruited from Texas Board of Nursing approved colleges/schools was used. A purposive, convenience sample of 105 faculty completed the PSQI, a reliable and valid instrument, in an online setting. Data was collected from January 2019 through April 2019. Results Nursing faculty reported sleep difficulty across all components, with more problems in sleep latency, sleep disturbances and subjective sleep quality. Overall, 70.5% of participants were reportedly “poor” sleepers, a salient finding. Faculty experienced poor sleep quality across all academic ranks and age groups. Sleep latency and subjective sleep quality were components that presented higher in severity for the youngest faculty.


| INTRODUC TI ON
Restorative sleep is a basic condition for enhanced wellbeing through the renewal of the body, mind and soul (Helvig et al., 2016). The Sleep Quality Consensus Panel agreed that sleep latency, number of awakenings >5 min, wake after sleep onset and sleep efficiency were appropriate indicators of sleep quality across the life-span (Ohayon et al., 2017) while Buxton et al. (2009) identified sufficient sleep duration and quality as key components of adequate sleep practices. Epidemiological and laboratory evidence has found that decreased sleep duration and poor sleep quality are associated with several negative health outcomes, such as obesity and chronic disease (Bowman et al., 2019;Chouchou et al., 2013;Zuraikat et al., 2020). Among health science students, healthcare workers and emergency personnel, poor sleep quality and sleep deficiencies have been linked to decreased work performance, poor decision-making, medical errors, personal health challenges and burnout (Greeson et al., 2015;Melnyk, 2020;Wolkow et al., 2015;Xu et al., 2016). There has been some research on sleep quality among nurses (Fang & Li, 2015) and nursing professors' quality of life (Cruz et al., 2015), but very little research about nursing faculty.

| BACKG ROU N D
There has been a significant amount of research on the impact of irregular work schedules, such as shiftwork, on sleep among nurses.
Several studies using the Pittsburgh Sleep Quality Index (PSQI) (Buysse et al., 1989) in nurses reported poor quality of sleep for shift workers in the USA (Colditz et al., 2016), Taiwan (Lee et al., 2015), Turkey (Baskent et al., 2017), Ankara (Karahan et al., 2020), and Italy (Giorgi et al., 2017). Poor sleep quality has been associated with insomnia and emotional disturbances (Huang & Zhu, 2020;Lee et al., 2015), and sleep deprivation, irregular sleep patterns and sleepiness were significant issues for shiftwork nurses (Debbia et al., 2021;Zhang et al., 2016). In a systematic review, longer shift patterns, such as consecutive night shifts, were associated with poor sleep quality and fatigue (Querstret et al., 2020). Melnyk's et al. (2018) study also reported poorer mental and physical health in nurses who work longer shifts. Research has also shown that shiftwork is associated with sleep deprivation and a decrease in psychomotor skills, attention, concentration, processing speed and quality of performance (Kaliyaperumal et al., 2017;Karahan et al., 2020).
Medical errors have been linked to sleep disturbances and fatigue (Karahan et al., 2020) and hypersomnolence, excessive daytime sleepiness, have been associated with increased risk of accidents (Garbarino et al., 2016).
The work of nursing faculty involves clinical practice, academic responsibilities and a heavy workload, all likely to impact their worklife balance and sleep (Fang & Li, 2015;Santos et al., 2019). Mintz-Binder and Sanders (2012) described the workload demands of 242 associate degree nursing program directors in the USA and their association with sleep problems, decreased overall physical health and burnout. A study of non-nursing university professors working full time found that females and faculty between ages 45 and 54 reported more frequent fatigue, inability to sleep and poor concentration than males and those 35-44 years old (Tacca Huamán & Tacca Huamán, 2019). These few studies indicate the need to examine sleep quality and the extent of sleep difficulties among nursing faculty. The significance of this study was to address this gap and contribute to building an evidence base that will guide future research and interventions to mitigate potential negative implications of sleep difficulties among nursing faculty. This study was conducted to be the foundational work in evaluating sleep quality among nursing faculty leading to a larger study with a more diverse population.

| Research question
The purpose of this study was to describe the overall sleep quality, sleep patterns and severity of sleep difficulties among nursing faculty using the PSQI and examine demographic factors. The study aims were to (a) describe the overall sleep quality and sleep patterns of nursing faculty using the component scores of the PSQI and (b) describe the severity of sleep difficulties in this sample (in terms of poor and good sleepers).

| Design
The study design was a cross-sectional descriptive and correlational study of sleep quality.

| Participants
A survey of nursing faculty recruited from Texas Board of Nursing approved colleges or schools of nursing was used to conduct a crosssectional descriptive and correlational study of sleep quality. The Institutional Review Board from the University approved the study, which was conducted between January and April of 2019. Inclusion criteria were the following: (a) nursing faculty who worked in a Texas Board of Nursing approved college or school of nursing, (b) 21 years of age or older and (c) able to read and understand English. Pregnant women were also eligible.
Recruitment to participate in the nursing faculty sleep quality study began with development of a purposive sampling of nursing faculty emails from accredited schools and colleges in Texas.
Processes in developing the list included email requests sent to deans and directors of accredited Texas Board of Nursing programs and direct email invitations to faculty. This procedure yielded 681 nursing faculty email addresses. A cover letter and consent were sent by the researcher via email to eligible faculty. Among the 681 targeted faculty, 126 accessed the survey using a Survey Monkey password protected account. Electronic consent had to be provided before the online survey would advance. Of the 126 respondents, 21 did not complete all components required for data inclusion, resulting in a final sample of 105 (15.42% response rate). This study was motivated by the lack of information surrounding sleep habits in nursing faculty to eventually study health consequences of nursing faculty. We had ample sample size to estimate response rates in this study and will be able to use results from this study to aid in designing a future hypothesis-driven study.

| Procedures and instruments
The study used Survey Monkey software to collect nursing faculty data on basic demographics and a validated measure of sleep quality. A secure, reliable and encrypted website was used to host the survey and collect the data. After consent was obtained, a greeting script from the researcher was presented which contained instructions for filling out the survey. The greeting script was followed by the Demographic Form, and PSQI survey. Each subject created their own five-digit self-assigned identification number, which appeared at the top of the demographic form. The study data were encrypted for added security. The survey allowed only one attempt.
A final page displayed a thank you message for completing the survey with an option for eligibility to receive one of eight $25 Visa gift cards upon completion. All survey questions had to be completed to be eligible for a gift card. Two-week and 3-day reminders were sent after the beginning of the study, and again at the 1-day mark for completion of the survey. Gift cards were not issued until the study was completed.

| Demographic form
Participants filled out basic demographic information including their gender, age range, race/ethnicity, employment status and academic rank.

| Pittsburgh Sleep Quality Index
The PSQI (Buysse et al., 1989) is a widely used self-report questionnaire that assesses overall sleep quality and sleep components along seven domains based on the past month: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication and daytime dysfunction. The PSQI consists of 19 items, most of them with a Likert response format. Items are combined to produce the component scores using authors' recommended formulas. Each derived component has a range from 0-3 whereby "0" indicates no sleep difficulties and "3" represents more severe sleep problems. For instance, the daytime dysfunction score is the sum score on two items (how often taking medication to help sleep; how often having trouble staying awake during daily activities such as driving and eating), coded on the 0-3 scale (0 = 0, 1-2 = 1, 3-4 = 2, and 5-6 = 3). The subjective sleep quality component (1 item) refers to the person's rating of their overall sleep quality on a scale of 0 (very good) to 3 (very bad). Sleep latency represents how long it takes for the person to go to sleep, whereas sleep duration refers to how many hours of sleep a person actually gets at night. Habitual sleep efficiency is calculated as a ratio of number of hours slept/number of hours spent in bed multiplied by 100, which translates into a percentage (˃85% indicates no sleep problems, scored as "0"; <65% indicates more severe sleep problems, scored as "3"). The sleep disturbances component is derived from the sum of eight item scores indicating how often the person had trouble sleeping (e.g., waking up during the night, having pain or feeling too cold/hot). The global PSQI score is the sum of the seven components and ranges from 0-21, with a total score above 5 indicating a "poor" sleeper. The PSQI also includes an open question on "other reasons" for having trouble sleeping. The original authors found a diagnostic sensitivity of 89.6% and specificity of 86.5% in differentiating poor and good sleepers; a sensitivity of 98% and specificity of 55% were found in the Chinese population (Tsai et al., 2005).
The PSQI has been used in numerous studies of adult populations internationally to assess sleep quality and its relation to a variety of outcomes (Bowman et al., 2019;Huang & Zhu, 2020;Karahan et al., 2020). For instance, the PSQI was used as part of the Midlife in the United States (MIDUS) study, which includes the general adult population. A higher global PSQI score was associated with a higher risk of depressive symptoms (Huang & Zhu, 2020). Baseline data for the American Heart Association (AHA) Go Red Women prospective cohort study (Zuraikat et al., 2020) also included the PSQI, and results indicated that poor sleep quality was associated with greater food intake and lower quality diet, which are risk factors for cardiovascular disease. The PSQI was also used in a large cross-sectional community-based study of the Korean Medicine Data Center which showed an association between sleep problems and digestive symptoms (Hyun et al., 2019). In academic populations, the PSQI has been primarily utilized in studies with students, including nursing students (Liu et al., 2021). A recent literature review of determinants of sleep quality in college students (Wang & Biro, 2021) found that physical activity and healthy social relations related to improved sleep quality, while caffeine intake, stress and irregular sleep-wake patterns were associated with decreased sleep quality.
A comprehensive meta-analysis of observational studies of sleep quality among medical students in four continents (Rao et al., 2020) found a pooled prevalence of poor sleep quality of 52.7% using the PSQI and a mean PSQI score of 6.1. Sleep quality was more prevalent in Europe and the Americas. Very few studies have examined sleep quality among university faculty using the PSQI. A few studies have been conducted in Brazil and Portugal, which investigated contributing factors to sleep quality among university professors and related poor sleep quality to physical and emotional symptoms (Crepaldi & Carvalhais, 2020;Santos et al., 2019;Silva et al., 2018;Sousa et al., 2018).

| Analysis
Overall sleep quality as measured by the global PSQI score was assessed numerically and nominally ("good" vs. "poor" sleeper) in terms of severity of sleep difficulties. Numerical data for PSQI and its component scores were presented as means (M), standard deviations (SD), and quartiles and ranges. Component scores (0-3) are ordinal categories; thus, quartiles, 25th, 50th (median) and 75th percentiles, and/or interquartile ranges (IQR = 75th percentile-25th percentiles) are appropriate to report measures of central tendency and spread.
Overall sleep quality was defined based on a cut-off of 5 on the global PSQI score (poor sleepers: >5; good sleepers: ≤5). Spearman correlation was used to assess the relationship between component scores and overall PSQI. From the demographic questionnaire, age was reported in six categorical ranges (under 25; 26-35; 36-45; 46-55; 56-65; and >66 years) and further collapsed into the following four age groups deemed meaningful for analysing sleep patterns in this population: ≤45; 46-55; 56-65, and ≥66 years. Among relevant demographic populations, Kruskal-Wallis test was used to evaluate PSQI scores (numerical) and Fisher's exact test was used to evaluate severity of sleep difficulties (nominal). Overall differences in severity of sleep difficulties among all nursing faculty were analysed using the binomial test of proportions. All statistical tests were conducted using an alpha level of 0.05. Statistical analysis was performed using Stata statistical software, version 14.0 (StataCorp., 2015). Buysse et al. (1989) report an internal consistency reliability (Cronbach's alpha) of 0.83 for the seven components. A recent study conducted among 923 Chinese nurses found a Cronbach's alpha reliability coefficient of 0.73 (Li et al., 2019). In the current sample of nursing faculty, the estimated Cronbach's alpha coefficient was 0.68, with domain by overall score correlations ranging from 0.446-0.736.

| Characteristics of sample
Nursing faculty demographics and characteristics are presented in Table 1. The majority of the nursing faculty was female (97%), white

| Overall sleep quality and patterns
The global PSQI score for sleep quality among nursing faculty was on average 8.14 (SD = 3.81) (range: 1-17), with a median score of 7 and IQR: six points (Table 2)  Global PSQI scores were lower among the middle age groups (46-55 and 56-65 year olds) and, on average, were worse among the youngest and oldest age groups (Table 3)

| Severity of sleep difficulties
Study results demonstrated that a large percentage (70.5%) of the nursing faculty reported as poor sleepers (total PSQI>5) (p < .05) ( Figure 2). No significant effects of age group were found to be associated with severity of sleep difficulties ("poor" vs. "good" sleepers; p = .835) as depicted in Figure 2. Severity of sleep difficulties did not significantly differ across gender, race, work status or academic rank (p > .05).

| D ISCUSS I ON
The aim of this study was to describe the overall sleep quality, sleep patterns and severity of sleep difficulties among nursing faculty using the PSQI. Our results showed that over 70.5% of nursing faculty reported poor sleep quality ("poor sleepers") as compared to     (Lee et al., 2017;Wolkow et al., 2015).
Therefore, our youngest faculty members may be at increased risk of cumulative effects harmful to their health. Finding the aetiologies and targeted interventions of the nursing faculty's poor sleep quality must be individualized. Melnyk (2020) (Wu et al., 2020). Some possible causes from the literature are irregular schedules, mental health issues, such as, anxiety and depression, chronic health conditions, such as, a respiratory condition, gastroesophageal reflux disease, or pain, and sleep apnea.  et al., 2018), the combination of objectively and subjectively assessed sleep being recommended (Bowman et al., 2019).

| Limitations
This study has limitations that may affect generalizability of findings including a homogenous sampling of white, females, working fulltime as faculty members, although it reflects the basic demographics of nursing faculty. There is possible selection bias with using a purposive sampling from schools of nursing in Texas and with invitations being forwarded by a person holding a position of authority, such as a Dean or Director of a nursing program. PSQI is a well-validated measure of sleep quality, but may be limited by retrospective selfreport biases. The response rate was low at 15% for the online survey which is slightly below the 20%-30% expected rate (Sauermann & Roach, 2013). Self-selection bias could also have inflated the results by respondents that were interested in reporting their sleep problems. No definitive conclusions can be drawn from this study without a larger sample of faculty with more diversity.

| CON CLUS ION
Nursing faculty in this study reported poor sleep quality, which is likely to compromise their health and well-being. Work-family conflict was identified by faculty as interfering with their sleep and is important factors to address in intervention development. Evidencebased interventions to balance personal and work life, as described by Melnyk (2020), are needed. Developing a culture of wellness in academia, which promotes self-care and sleep health, is essential to sustaining healthy nursing faculty and academic programs.

ACK N OWLED G M ENTS
This work was supported by a grant from the Phi Chi Chapter of Sigma. We wish to thank the Nursing faculty who participated in this study, Earline Moreland from the University of Houston College of Nursing who assisted with data management, Rachel Helbing and Stefanie Lapka with the University of Houston Libraries.

CO N FLI C T O F I NTE R E S T
No conflict of interest has been declared by the authors.

AUTH O R CO NTR I B UTI O N S
SC involved in study design and acquisition of data; SC, JB, CB and TM took part in analysis and interpretation of data; SC, JB, CB and TM participated in drafting of the manuscript; SC, JB, CB and TM involved in critical revisions of the manuscript for important intellectual content. All authors read and approved the final manuscript.

E TH I C A L A PPROVA L
This study was reviewed and approved by the University's Institutional Review Board (IRB). The greeting script, demographic form, data collection procedures and questionnaire were approved by the IRB. The IRB identification number STUDY00001376 was approved. Participation in the study was voluntary. Each study participant self-selected their own participant identification number. There were no foreseeable risks related to the procedures conducted as part of this study. Data were encrypted for additional security.

DATA AVA I L A B I L I T Y S TAT E M E N T
Research data are not shared. The data are not publicly available due to privacy and compliance with the Institutional Review Board protocol approval.