Dataset Information

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

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.

SUBMITTER: Christensen MA

PROVIDER: S-EPMC5102460 | biostudies-other | 2016

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

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

Christensen Matthew A MA Bettencourt Laura L Kaye Leanne L Moturu Sai T ST Nguyen Kaylin T KT Olgin Jeffrey E JE Pletcher Mark J MJ Marcus Gregory M GM

PloS one 20161109 11

<h4>Background</h4>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.<h4>Aims</h4>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.<h4>Methods</h4>We perfo ...[more]

PMID: 27829040

Similar Datasets

Project description:BACKGROUND:Previous research examining the relationship between screen time (ST) and psychological health outcomes have primarily focused on one type of ST (i.e., television), while little research has considered other types of screens (e.g., videos, movies, social media), screen content (e.g., violent video games), or potential mediating variables. Therefore, the purpose of the present study was to assess ST types and content and their association with problem behaviors, and to determine whether these relationships were mediated by sleep duration. METHODS:Parents and children provided cross-sectional baseline data (2016-18) as part of the Adolescent Brain Cognitive Development study, a broadly US representative sample of 11,875 children aged 9 to 10?years. Parents self-reported their children's emotional and behavioral syndromes via the Child Behavior Checklist and sleep duration using one item from the Parent Sleep Disturbance Scale. Children self-reported their ST behavior, which comprised ST types (television/movies, videos, video games, and social media) and content (mature-rated video games and R-rated movies). RESULTS:Time spent in various ST types was positively associated with problem behaviors: watching television/movies was associated with a 5.9% increase in rule-breaking behavior (incidence rate ratio [IRR]?=?1.059), 5% increase in social problems (IRR?=?1.050), 4% increase in aggressive behavior (IRR?=?1.040), and 3.7% increase in thought problems (IRR?=?1.037). Greater time spent playing mature-rated video games was associated with greater somatic complaints (IRR?=?1.041), aggressive behavior (IRR?=?1.039), and reduced sleep duration (IRR?=?.938). Sleep duration mediated the relationship between ST (type and content) and problem behaviors, albeit the effect sizes were small. The largest effects were observed between sleep duration and all problem behaviors, with greater sleep duration predicting an 8.8-16.6% decrease in problem behaviors (IRRs ranging from .834 to .905). CONCLUSION:Greater time spent in ST behavior was associated with greater problem behaviors among children. There was strong evidence that longer sleep duration was associated with reduced problem behaviors. While sleep duration mediated the effects of ST on problem behaviors, other potential mediating variables need to be investigated in future research.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure