Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep
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. The aim of this study was to characterize smartphone use by measuring screen-time directly, deter...
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| creator | Christensen, Matthew A Bettencourt, Laura Kaye, Leanne Moturu, Sai T Nguyen, Kaylin T Olgin, Jeffrey E Pletcher, Mark J Marcus, Gregory M |
| description | 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.
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.
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.
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.
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. |
| doi_str_mv | 10.1371/journal.pone.0165331 |
| format | Article |
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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.
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.
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.
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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0165331</identifier><identifier>PMID: 27829040</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Adults ; Biology and Life Sciences ; Cardiology ; Cardiovascular disease ; Causation ; Census of Population ; Comparative analysis ; Computation ; Cross-Sectional Studies ; Demographics ; Demography ; Diabetes ; Engineering and Technology ; Epidemiology ; Ethnicity ; Family medical history ; Female ; Geography ; Habits ; Humans ; Hypotheses ; Internet ; Latency ; Linear Models ; Male ; Measurement ; Medical screening ; Medicine ; Medicine and Health Sciences ; Middle Aged ; Minority & ethnic groups ; Mortality ; Multivariate Analysis ; Pediatrics ; People and Places ; Physical Sciences ; Prospective Studies ; Quality ; Race ; Regression analysis ; Research and Analysis Methods ; Self Report ; Sleep ; Sleep - physiology ; Sleep apnea ; Smart phones ; Smartphone - statistics & numerical data ; Smartphones ; Studies ; Surveys and Questionnaires ; Time Factors ; United States ; Variables ; Windows (intervals)</subject><ispartof>PloS one, 2016-11, Vol.11 (11), p.e0165331-e0165331</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Christensen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2016 Christensen et al 2016 Christensen et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c725t-86ea85589b2517ae133ba2b7d5271abdd9e2cf5349d5012482eff5d5ea30cffe3</citedby><cites>FETCH-LOGICAL-c725t-86ea85589b2517ae133ba2b7d5271abdd9e2cf5349d5012482eff5d5ea30cffe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5102460/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5102460/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79569,79570</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27829040$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Christensen, Matthew A</creatorcontrib><creatorcontrib>Bettencourt, Laura</creatorcontrib><creatorcontrib>Kaye, Leanne</creatorcontrib><creatorcontrib>Moturu, Sai T</creatorcontrib><creatorcontrib>Nguyen, Kaylin T</creatorcontrib><creatorcontrib>Olgin, Jeffrey E</creatorcontrib><creatorcontrib>Pletcher, Mark J</creatorcontrib><creatorcontrib>Marcus, Gregory M</creatorcontrib><title>Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>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.
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.
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.
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.
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.</description><subject>Adult</subject><subject>Adults</subject><subject>Biology and Life Sciences</subject><subject>Cardiology</subject><subject>Cardiovascular disease</subject><subject>Causation</subject><subject>Census of Population</subject><subject>Comparative analysis</subject><subject>Computation</subject><subject>Cross-Sectional Studies</subject><subject>Demographics</subject><subject>Demography</subject><subject>Diabetes</subject><subject>Engineering and Technology</subject><subject>Epidemiology</subject><subject>Ethnicity</subject><subject>Family medical history</subject><subject>Female</subject><subject>Geography</subject><subject>Habits</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Internet</subject><subject>Latency</subject><subject>Linear Models</subject><subject>Male</subject><subject>Measurement</subject><subject>Medical 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One</addtitle><date>2016-11-09</date><risdate>2016</risdate><volume>11</volume><issue>11</issue><spage>e0165331</spage><epage>e0165331</epage><pages>e0165331-e0165331</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>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.
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.
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.
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.
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><cop>United States</cop><pub>Public Library of Science</pub><pmid>27829040</pmid><doi>10.1371/journal.pone.0165331</doi><tpages>e0165331</tpages><oa>free_for_read</oa></addata></record> |
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| issn | 1932-6203 1932-6203 |
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| recordid | cdi_plos_journals_1837599224 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Adult Adults Biology and Life Sciences Cardiology Cardiovascular disease Causation Census of Population Comparative analysis Computation Cross-Sectional Studies Demographics Demography Diabetes Engineering and Technology Epidemiology Ethnicity Family medical history Female Geography Habits Humans Hypotheses Internet Latency Linear Models Male Measurement Medical screening Medicine Medicine and Health Sciences Middle Aged Minority & ethnic groups Mortality Multivariate Analysis Pediatrics People and Places Physical Sciences Prospective Studies Quality Race Regression analysis Research and Analysis Methods Self Report Sleep Sleep - physiology Sleep apnea Smart phones Smartphone - statistics & numerical data Smartphones Studies Surveys and Questionnaires Time Factors United States Variables Windows (intervals) |
| title | Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-14T04%3A50%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Direct%20Measurements%20of%20Smartphone%20Screen-Time:%20Relationships%20with%20Demographics%20and%20Sleep&rft.jtitle=PloS%20one&rft.au=Christensen,%20Matthew%20A&rft.date=2016-11-09&rft.volume=11&rft.issue=11&rft.spage=e0165331&rft.epage=e0165331&rft.pages=e0165331-e0165331&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0165331&rft_dat=%3Cgale_plos_%3EA471841430%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1837599224&rft_id=info:pmid/27829040&rft_galeid=A471841430&rft_doaj_id=oai_doaj_org_article_a775ea91a6b94699a28170acb0f4855b&rfr_iscdi=true |