Factors That Predict Levels of Sleepiness of Advanced Practice Nursing Students

Background: Graduate students are at increased risk of sleep deprivation. There are many detrimental outcomes associated with sleep deprivation on leaning, health and overall wellbeing. The relationship between academic performance and sleep deprivation is gaining importance nationwide (Sullivan, 2015). There is a substantial amount data documenting the need for healthy sleep particularly students to optimize physical and psychological health (Azad et al., 2015). Factors contributing to sleep deprivation include the demands of graduate programs, stress, challenges managing family and personal life amongst others.

Purpose: The purpose of this study was to examine the relationship of APN students’ grade-point average (GPA), gender, and employment status with predicted levels of daytime sleepiness.

Theoretical Framework. The Psychological Well-Being (PWB) model developed by. Ryff (1989) is a set of measured scales representing multiple facets. The PWB in guiding this study theorized that sleep is a resource essential to well-being; adequate sleep is the resource needed to optimally manage stressful life demands. (Gedefaw, Tilahun, & Asefa, 2015; Goel et al., 2014; Wells & Vaughn, 2012).

Methods: This study is a quantitative, correlation study, to determine the predictors of APN students’ levels sleep deprivation and its effects on academic performance (GPA). Using a nonprobability convenience sampling method, participants recruited were graduate students from a public university. The Epworth Sleepiness Scale a commonly used instrument in research measures sleepiness (Kendzerska et al., 2014) and a demographic questionnaire were used to collect the data.

Results. A total of 123 participants completed the study. Results indicated the ESS and GPA were negatively correlated and statistically significant (r = -.24, p < .05) indicating that as sleepiness increased, GPAs decreased.

Discussion: Study data provide a better understanding of significant predictors of APN students’ levels of sleepiness and academic performance. This data is important to nursing educations when designing curricula. With this understanding, alongside other sleep research, future studies will provide important data to guide APN educators in developing curricula and educational policies to improve student well-being, patient care, and safety.