The basics of sleep physiology and behavior

Tubbs, Andrew; Dollish, Hannah K.; Fernandez, Fabian-Xosé; Grandner, Michael

doi:10.1016/b978-0-12-815373-4.00001-0

Cited by 22 publications

(23 citation statements)

References 10 publications

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“…These analyses make use of six available reported sleep parameters from this representative cohort, which do allow a rounded picture of timing and quality, but future research would benefit from including validated measures of sleep duration and quality, as well as circadian preference. The current self-reported sleep measures offer valuable insight into adolescents’ subjective experience of sleep, which is one important component of sleep, but this can diverge from verifiable objective measures of sleep parameters provided by other methods, such as the gold-standard polysomnography 52 53. In particular, sleep state misperception in both good and poor sleepers can result in poor self-report estimates of sleep onset latency,53 although these differences in sleep onset latency estimates from self-report and polysomnography tend to be small 54.…”

Section: Discussionmentioning

confidence: 92%

“…In particular, sleep state misperception in both good and poor sleepers can result in poor self-report estimates of sleep onset latency,53 although these differences in sleep onset latency estimates from self-report and polysomnography tend to be small 54. The current analyses therefore contribute one part of the picture, with a continued need to triangulate insight from multiple methodologies (both subjective and objective) to build a more nuanced, holistic understanding of adolescent social media use and sleep 52 55…”

Section: Discussionmentioning

confidence: 96%

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Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study

2019

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ObjectivesThis study examines associations between social media use and multiple sleep parameters in a large representative adolescent sample, controlling for a wide range of covariates.DesignThe authors used cross-sectional data from the Millennium Cohort Study, a large nationally representative UK birth cohort study.ParticipantsData from 11 872 adolescents (aged 13–15 years) were used in analyses.MethodsSix 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.ResultsAverage 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).ConclusionsThis 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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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 96%

Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study

2019

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“…This type of self-report estimate is common in the literature, but is subject to bias in recall and reporting (Althubaiti, 2016), for example with sleep state misperception resulting in less accurate estimates of sleep parameters compared to objective measures (Fernandez-Mendoza et al, 2011;Silva et al, 2007). The current findings therefore offer valuable insight into the subjective experience of sleep from an adolescent perspective, with the potential for future work to combine the iNOD's insight alongside more objective, verifiable measures of social media activity and sleep parameters to build a more holistic understanding of adolescent sleep that unites physiology, behaviour and experience (Gregory & Sadeh, 2012;Tubbs et al, 2019).…”

Section: Strengths and Limitationsmentioning

confidence: 94%

Nodding off but can’t disconnect: development and validation of the iNOD index of Nighttime Offline Distress

Scott¹,

Biello²,

Woods³

2020

Preprint

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There is a pressing need to update sleep models, education and treatment to better reflect the realities of sleep in a 24/7 connected social world. Progress in this area has been limited to date by available measurement tools, which have largely restricted their focus to recording the frequency or duration of individuals’ social media use, without capturing crucial sleep-relevant aspects of this inherently social and interactive experience. This study uses data from 3,008 adolescents (aged 10-18 years) to rigorously develop and validate a new 10-item self-report measure that quantifies the extent to which individuals struggle to disengage from social media interactions at night: the index of Nighttime Offline Distress (iNOD). The current findings indicate considerable individual differences, with most participants reporting little difficulty disconnecting but a minority experiencing unhelpful bedtime concerns around Staying Connecting and Following Etiquette to varying extents. Those with higher scores on these subscales tended to report using social media for longer after they felt they should be asleep, with shorter sleep duration and poorer sleep quality. Results also indicated that extended periods of wakefulness in bed before attempting to sleep are common amongst today’s adolescents, pointing towards a potentially fragmented process of sleep displacement for those who may struggle to disconnect - and to stay disconnected - from social interactions in order to allow sufficient uninterrupted sleep opportunity. These findings can inform current models for understanding normal and disordered sleep during adolescence, whilst highlighting specific social concerns as important potential targets for sleep education efforts. The iNOD equips researchers and clinicians with a short validated self-report measure that can support efforts to move evidence and practice in this area forwards.

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“…(8) Acredita-se que o workaholism afete a qualidade do sono, pois o ritmo de trabalho é um dos fatores que mais afeta a arquitetura dos estágios de sono. (9) Nesse sentido, as longas jornadas laborais e a carga horária semanal elevada associam-se a prejuízos a qualidade do sono. (10,11) O sono é um estado biocomportamental naturalmente recorrente e reversível, caracterizado por imobilidade relativa, desengajamento perceptivo e consciência moderada, (9) que é um dos principais responsáveis pela restauração da energia e dos recursos mentais do ser humano.…”

Section: Introductionunclassified

“…(9) Nesse sentido, as longas jornadas laborais e a carga horária semanal elevada associam-se a prejuízos a qualidade do sono. (10,11) O sono é um estado biocomportamental naturalmente recorrente e reversível, caracterizado por imobilidade relativa, desengajamento perceptivo e consciência moderada, (9) que é um dos principais responsáveis pela restauração da energia e dos recursos mentais do ser humano. Desse modo, dormir bem possibilita às pessoas capacidade e prontidão para atender as demandas de trabalho atuais e novas.…”

Section: Introductionunclassified