Next Article in Journal
The Association between Sexual Orientation and Sleep Problems: Are there Racial and Ethnic Differences?
Previous Article in Journal
Light Modulation of Human Clocks, Wake, and Sleep
Open AccessReview

Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression

1
Ministry of Health, Juffair 340, Kingdom of Bahrain
2
College of Medicine and Medical Sciences, Arabian Gulf University, Manama 329, Kingdom of Bahrain
3
Department of Occupational Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada
*
Author to whom correspondence should be addressed.
Clocks & Sleep 2019, 1(2), 209-219; https://doi.org/10.3390/clockssleep1020018
Received: 6 February 2019 / Revised: 26 March 2019 / Accepted: 9 April 2019 / Published: 11 April 2019
(This article belongs to the Section Clocks & Sleep in Human Basic Research)
  |  
PDF [448 KB, uploaded 11 April 2019]
  |  

Abstract

Excessive daytime sleepiness (EDS) is highly prevalent among medical students and can have serious negative outcomes for both students and their patients. Little is known about the magnitude and predictors of EDS among medical college students. A meta-regression analysis was conducted to achieve these two targets. A systematic search was performed for English-language studies that reported the prevalence of EDS among medical students using the Epworth sleepiness scale (ESS), age, sex, sleep duration and sleep quality as predictive variables. A total of nine observational studies (K = 9, N = 2587) were included in the analyses. Meta-regression analyses were performed using mean age (years), sex (proportion of male subjects), sleep duration (hours/night) and sleep quality index score (continuous scale) as moderators for EDS—with the prevalence of EDS as an outcome variable. An interaction term of sleep duration X sleep quality was created to assess if these two variables simultaneously influenced the outcome variable. Utilizing the ESS, the pooled prevalence of EDS among medical students was 34.6% (95% Confidence Interval (CI) 18.3–50.9%). Meta-regression models of age, sex, sleep duration and sleep quality alone revealed poor predictive capabilities. Meta-regression models of sleep duration–sleep quality interaction revealed results with high statistical significance. The findings from this review contribute supporting evidence for the relationship between sleep duration and sleep quality scores (i.e., sleep duration X sleep quality score) in predicting EDS in medical students. View Full-Text
Keywords: sleepiness; university students; Epworth sleepiness scale; medical school sleepiness; university students; Epworth sleepiness scale; medical school
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Jahrami, H.; Alshomili, H.; Almannai, N.; Althani, N.; Aloffi, A.; Algahtani, H.; Brown, C.A. Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression. Clocks & Sleep 2019, 1, 209-219.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Clocks & Sleep EISSN 2624-5175 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top