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Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep

Author

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  • Matthew A Christensen
  • Laura Bettencourt
  • Leanne Kaye
  • Sai T Moturu
  • Kaylin T Nguyen
  • Jeffrey E Olgin
  • Mark J Pletcher
  • Gregory M Marcus

Abstract

Background: Smartphones are increasingly integrated into everyday life, but frequency of use has not yet been objectively measured and compared to demographics, health information, and in particular, sleep quality. Aims: The aim of this study was to characterize smartphone use by measuring screen-time directly, determine factors that are associated with increased screen-time, and to test the hypothesis that increased screen-time is associated with poor sleep. Methods: We performed a cross-sectional analysis in a subset of 653 participants enrolled in the Health eHeart Study, an internet-based longitudinal cohort study open to any interested adult (≥ 18 years). Smartphone screen-time (the number of minutes in each hour the screen was on) was measured continuously via smartphone application. For each participant, total and average screen-time were computed over 30-day windows. Average screen-time specifically during self-reported bedtime hours and sleeping period was also computed. Demographics, medical information, and sleep habits (Pittsburgh Sleep Quality Index–PSQI) were obtained by survey. Linear regression was used to obtain effect estimates. Results: Total screen-time over 30 days was a median 38.4 hours (IQR 21.4 to 61.3) and average screen-time over 30 days was a median 3.7 minutes per hour (IQR 2.2 to 5.5). Younger age, self-reported race/ethnicity of Black and "Other" were associated with longer average screen-time after adjustment for potential confounders. Longer average screen-time was associated with shorter sleep duration and worse sleep-efficiency. Longer average screen-times during bedtime and the sleeping period were associated with poor sleep quality, decreased sleep efficiency, and longer sleep onset latency. Conclusions: These findings on actual smartphone screen-time build upon prior work based on self-report and confirm that adults spend a substantial amount of time using their smartphones. Screen-time differs across age and race, but is similar across socio-economic strata suggesting that cultural factors may drive smartphone use. Screen-time is associated with poor sleep. These findings cannot support conclusions on causation. Effect-cause remains a possibility: poor sleep may lead to increased screen-time. However, exposure to smartphone screens, particularly around bedtime, may negatively impact sleep.

Suggested Citation

  • Matthew A Christensen & Laura Bettencourt & Leanne Kaye & Sai T Moturu & Kaylin T Nguyen & Jeffrey E Olgin & Mark J Pletcher & Gregory M Marcus, 2016. "Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-14, November.
  • Handle: RePEc:plo:pone00:0165331
    DOI: 10.1371/journal.pone.0165331
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    Cited by:

    1. Amez, Simon & Denecker, Floor & Ponnet, Koen & De Marez, Lieven & Baert, Stijn, 2021. "Mobile DNA and Sleep Quality," IZA Discussion Papers 14816, Institute of Labor Economics (IZA).
    2. Jara-Díaz, Sergio R. & Rosales-Salas, Jorge, 2020. "Time use: The role of sleep," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 1-20.
    3. Kostadin Kushlev & Matthew R Leitao, 2020. "The Effects of Smartphones on Well-Being: Theoretical Integration and Research Agenda," Papers 2005.09100, arXiv.org.
    4. Simon Amez & Stijn Baert, 2019. "Smartphone Use and Academic Performance: a Literature Review," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/982, Ghent University, Faculty of Economics and Business Administration.
    5. Mohammad Aminul Islam & M. Rezaul Islam, 2023. "Exploring the impact of Covid-19 on children's social media usage: a pragmatic analysis of excessive screen time and its effects on child development," Journal of Community Positive Practices, Catalactica NGO, issue 2, pages 69-84.
    6. Sara Thomée, 2018. "Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure," IJERPH, MDPI, vol. 15(12), pages 1-25, November.
    7. Yu Par Khin & Yusuke Matsuyama & Takahiro Tabuchi & Takeo Fujiwara, 2021. "Association of Visual Display Terminal Usage with Self-Rated Health and Psychological Distress among Japanese Office Workers during the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(17), pages 1-10, September.
    8. Bruna Nichele da Rosa & Cláudia Tarragô Candotti & Luiza Rampi Pivotto & Matias Noll & Marcelle Guimarães Silva & Adriane Vieira & Jefferson Fagundes Loss, 2022. "Back Pain and Body Posture Evaluation Instrument for Children and Adolescents (BackPEI-CA): Expansion, Content Validation, and Reliability," IJERPH, MDPI, vol. 19(3), pages 1-10, January.
    9. Chelsea Carpenter & Sang-Eun Byun & Gabrielle Turner-McGrievy & Delia West, 2021. "An Exploration of Domain-Specific Sedentary Behaviors in College Students by Lifestyle Factors and Sociodemographics," IJERPH, MDPI, vol. 18(18), pages 1-11, September.
    10. Jeffrey Prince & Shane Greenstein, 2021. "Mobile Internet usage and usage‐based pricing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 30(4), pages 760-783, November.
    11. Daniel Monsivais & Asim Ghosh & Kunal Bhattacharya & Robin I M Dunbar & Kimmo Kaski, 2017. "Tracking urban human activity from mobile phone calling patterns," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-16, November.
    12. Simon Amez & Suncica Vujic & Lieven De Marez & Stijn Baert, 2019. "Smartphone Use and Academic Performance: First Evidence from Longitudinal Data," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/986, Ghent University, Faculty of Economics and Business Administration.

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