Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep
Christensen MA, Bettencourt L, Kaye L, Moturu ST, Nguyen KT, Olgin JE, Pletcher MJ, Marcus GM
PloS one · 152 citations
Review labels
Neutral facts our review recorded about how this study was done. They describe method, never whether we like the result.
How it was studied
- Design
- Cohort study (indexed by PubMed)
- Studied in
- People
- Main outcome
- Health markers and function
Who paid for it
- Funding
- Industry funded
- Nonprofit
- Sarnoff Cardiovascular Research Foundation
- Government
- National Institutes of Health
- University or hospital
- University of California, San Francisco
- Government
- National Institute on Alcohol Abuse and Alcoholism
- Government
- National Heart, Lung, and Blood Institute
- Government
- National Institute of Neurological Disorders and Stroke
- Government
- National Institute of Biomedical Imaging and Bioengineering
- Government
- Office of Behavioral and Social Sciences Research
- Government
- National Institute on Minority Health and Health Disparities
- Government
- NIMHD NIH HHS
- Government
- NIBIB NIH HHS
- Authors
- At least one author declares a financial tie to industry
- Grants
- National Institute of Biomedical Imaging and Bioengineering (1U2CEB021881); National Institute of Biomedical Imaging and Bioengineering (U2C EB021881); National Institute on Minority Health and Health Disparities (R25MD006832); National Institutes of Health (R25MD006832)
Based on 11 listed funder(s) and full-text disclosure statement.
Publication
- Published
- 2016-11-09 · PLoS One · vol. 11 · issue 11 · p. e0165331
- Publisher
- Public Library of Science
- Cited
- 335 citations · more than 100% of similar papers · 25.1× the field average
- Impact
- Top 10% most cited in its field
- References
- 22 works
- Access
- Open access (journal) · CC-BY
- Research areas
- Mobile Health and mHealth Applications · Technology Use by Older Adults · Child Development and Digital Technology
- Keywords
- smartphone screen time, sleep quality, sleep duration, sleep efficiency, sleep latency, bedtime screen use, age differences, racial and ethnic differences, socioeconomic status
- MeSH
- humans, multivariate analysis, linear models, prospective studies, cross-sectional studies, sleep, geography, time factors, internet, adult, middle aged, united states, female, male, self report, smartphone, surveys and questionnaires
8 authors
From US
- Matthew A. ChristensenUniversity of California, San Francisco
- Laura BettencourtUniversity of California, San Francisco
- Leanne Kaye
- Sai T. Moturu
- Kaylin T. NguyenUniversity of California, San Francisco
- Jeffrey E. OlginUniversity of California, San Francisco
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.
Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY).
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