The relationship between social media use and sleep quality among undergraduate students

ABSTRACT

Insufficient sleep is a growing health problem among university students, especially for freshmen during their first quarter/semester of college. Little research has studied how social media technologies impact sleep quality among college students. This study aims to determine the relationship between social media use and sleep quality among freshman undergraduates during their first quarter in college. Specifically, we explored whether variations in Twitter use across the time of day and day of the week would be associated with self-reported sleep quality. We conducted a study of freshman Twitter-using students (N = 197) over their first quarter of college, between October and December of 2015. We collected students’ tweets, labeled the content of the tweets according to different emotional states, and gave theme weekly surveys on sleep quality. Tweeting more frequently on weekday late nights was associated with lower sleep quality (β = −0.937, SE = 0.352); tweeting more frequently on weekday evenings was associated with better quality sleep (β = 0.189, SE = 0.097). Tweets during the weekday that were labeled related to the emotion of fear were associated with lower sleep quality (β = −0.302, SE = 0.131). Results suggest that social media use is associated with sleep quality among students. Results provided can be used to inform future interventions to improve sleep quality among college students.

KEYWORDS:

• Sleep quality
• university students
• social media
• Twitter
• emotions/mood

Acknowledgements

We want to thank Lynwood Lord for the help in editing the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Renee Garett is a licensed clinical social worker and the Founding Director of ElevateU, an organization that conducts research and development on technologies to address at-risk populations, particularly youth [email: [email protected]].

Dr Sam Liu received his PhD from University of Toronto in public health and health promotion. His research focuses studying the effects of digital communication technology on health behaviors [email: [email protected]].

Dr Sean Young received his PhD in Psychology and MS in Health Services Research from Stanford University. Dr Young is the Executive Director of the University of California Institute for Prediction Technology and an Associate Professor in the Department of Family Medicine at the University of California, Los Angeles [email: [email protected]].

Additional information

Funding

This work was supported by National Human Genome Research Institute: [grant number U01HG008488]; National Institute of Allergy and Infectious Diseases: [grant number R56AI125105]; National Institute of Mental Health: [grant number R01MH106415].