Sleep and Academic Performance in Undergraduates: A Multi-measure, Multi-predictor Approach

Abstract

The present study examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students and tested whether sleep variables emerged as significant predictors of subsequent academic performance when other potential predictors, such as class attendance, time devoted to study, and substance use are considered. A sample of 1654 (55% female) full-time undergraduates 17 to 25 yrs of age responded to a self-response questionnaire on sleep, academics, lifestyle, and well-being that was administered at the middle of the semester. In addition to self-reported measures of academic performance, a final grade for each student was collected at the end of the semester. Univariate analyses found that sleep phase, morningness/eveningness preference, sleep deprivation, sleep quality, and sleep irregularity were significantly associated with at least two academic performance measures. Among 15 potential predictors, stepwise multiple regression analysis identified 5 significant predictors of end-of-semester marks: previous academic achievement, class attendance, sufficient sleep, night outings, and sleep quality (R² = 0.14 and adjusted R² = 0.14, F(5, 1234) = 40.99, p < .0001). Associations between academic achievement and the remaining sleep variables as well as the academic, well-being, and lifestyle variables lost significance in stepwise regression. Together with class attendance, night outings, and previous academic achievement, self-reported sleep quality and self-reported frequency of sufficient sleep were among the main predictors of academic performance, adding an independent and significant contribution, regardless of academic variables and lifestyles of the students. (Author correspondence: [email protected])

Keywords:

• Academic performance
• Adolescents
• Chronotype
• Multiple regression
• Questionnaire
• Sleep
• Students

ACKNOWLEDGMENTS

Student participation and lecturers cooperation are gratefully acknowledged. The assistance of colleagues in data collection was precious. The present work is currently financially supported by the IBILI (Institute of Biomedical Research in Light and Image; Fundação para a Ciência e a Tecnologia [FCT]), Faculty of Medicine, University of Coimbra, Portugal. The University of Aveiro, Department of Educational Sciences, now Department of Education, provides logistic support (note: work partially based on a larger research project formerly supported by F.C. Gulbenkian [LEIES Project] and by FCT-Portugal [SPASHE project; UI-CCPSF research Unit]).

Declaration of Interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.