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Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study
OBJECTIVES: This study examines associations between social media use and multiple sleep parameters in a large representative adolescent sample, controlling for a wide range of covariates. DESIGN: The authors used cross-sectional data from the Millennium Cohort Study, a large nationally representati...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830469/ https://www.ncbi.nlm.nih.gov/pubmed/31641035 http://dx.doi.org/10.1136/bmjopen-2019-031161 |
Sumario: | OBJECTIVES: This study examines associations between social media use and multiple sleep parameters in a large representative adolescent sample, controlling for a wide range of covariates. DESIGN: The authors used cross-sectional data from the Millennium Cohort Study, a large nationally representative UK birth cohort study. PARTICIPANTS: Data from 11 872 adolescents (aged 13–15 years) were used in analyses. METHODS: Six self-reported sleep parameters captured sleep timing and quality: sleep onset and wake times (on school days and free days), sleep onset latency (time taken to fall asleep) and trouble falling back asleep after nighttime awakening. Binomial logistic regressions investigated associations between daily social media use and each sleep parameter, controlling for a range of relevant covariates. RESULTS: Average social media use was 1 to <3 hours per day (31.6%, n=3720). 33.7% were classed as low users (<1 hour; n=3986); 13.9% were high users (3 to <5 hours; n=1602) and 20.8% were very high users (5+ hours; n=2203). Girls reported spending more time on social media than boys. Overall, heavier social media use was associated with poorer sleep patterns, controlling for covariates. For example, very high social media users were more likely than comparable average users to report late sleep onset (OR 2.14, 95% CI 1.83 to 2.50) and wake times (OR 1.97, 95% CI 1.32 to 2.93) on school days and trouble falling back asleep after nighttime awakening (OR 1.36, 95% CI 1.10 to 1.66). CONCLUSIONS: This study provides a normative profile of UK adolescent social media use and sleep. Results indicate statistically and practically significant associations between social media use and sleep patterns, particularly late sleep onset. Sleep education and interventions can focus on supporting young people to balance online interactions with an appropriate sleep schedule that allows sufficient sleep on school nights. |
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