Digital media use in the 2 h before bedtime is associated with sleep variables in university students

Kathryn Orzech (Lead / Corresponding author), Michael Grandner, Brandy Roane, Mary Carskadon

    Research output: Contribution to journalArticlepeer-review

    103 Citations (Scopus)

    Abstract

    Digital media use is widespread in University students, and use of digital media near bedtime has a broadly negative effect on sleep outcomes. Adequate and good quality sleep is important for physical and mental health, but few studies have rigorously measured both sleep and digital media use. In this study, we investigated whether self-reported sleep patterns were associated with digital media use in a first- year University student (N 1⁄4 254, 48% male) population. Students tracked their sleep through daily online diaries and provided digital media use data in 15-min blocks for 2 h prior to bedtime on nine occasions. A longer duration of digital media use was associated with reduced total sleep time and later bedtime, while greater diversity of digital media use was associated with increased total sleep time and earlier bedtime. Analysis of activities in the last hour before bedtime indicated that activity type plays a role in digital media's effect on sleep, with computer work, surfing the Internet, and listening to music showing the strongest relationship to multiple sleep variables. These findings have implications for physical and mental health of University students and can inform design of devices to minimize negative effects of digital media on sleep.
    Original languageEnglish
    Pages (from-to)43-50
    Number of pages8
    JournalComputers in Human Behavior
    Volume55
    Issue numberPart A
    Early online date14 Sept 2015
    DOIs
    Publication statusPublished - Feb 2016

    Keywords

    • Digital media
    • Sleep
    • Mental health
    • Technology
    • University students

    Fingerprint

    Dive into the research topics of 'Digital media use in the 2 h before bedtime is associated with sleep variables in university students'. Together they form a unique fingerprint.

    Cite this