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Robert J. Brychta, Vaka Rögnvaldsdóttir, Sigríður L. Guðmundsdóttir, Rúna Stefánsdóttir, Soffia M. Hrafnkelsdóttir, Sunna Gestsdóttir, Sigurbjörn A. Arngrímsson, Kong Y. Chen and Erlingur Jóhannsson

Introduction: Sleep is often quantified using self-report or actigraphy. Self-report is practical and less technically challenging, but prone to bias. We sought to determine whether these methods have comparable sensitivity to measure longitudinal changes in adolescent bedtimes. Methods: We measured one week of free-living sleep with wrist actigraphy and usual bedtime on school nights and non-school nights with self-report questionnaire in 144 students at 15 y and 17 y. Results: Self-reported and actigraphy-measured bedtimes were correlated with one another at 15 y and 17 y (p < .001), but reported bedtime was consistently earlier (>30 minutes, p < .001) and with wide inter-method confidence intervals (> ±106 minutes). Mean inter-method discrepancy did not differ on school nights at 15 y and 17 y but was greater at 17 y on non-school nights (p = .002). Inter-method discrepancy at 15 y was not correlated to that at 17 y. Mean change in self-reported school night bedtime from 15 y to 17 y did not differ from that by actigraphy, but self-reported bedtime changed less on non-school nights (p = .002). Two-year changes in self-reported bedtime did not correlate with changes measured by actigraphy. Conclusions: Although methods were correlated, consistently earlier self-reported bedtime suggests report-bias. More varied non-school night bedtimes challenge the accuracy of self-report and actigraphy, reducing sensitivity to change. On school nights, the methods did not differ in group-level sensitivity to changes in bedtime. However, lack of correlation between bedtime changes by each method suggests sensitivity to individual-level change was different. Methodological differences in sensitivity to individual- and group-level change should be considered in longitudinal studies of adolescent sleep patterns.

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Natashia Swalve, Brianna Harfmann, John Mitrzyk and Alexander H. K. Montoye

, Claudatos, Colrain, & Baker, 2018 ), despite the growing demand for validation studies ( Russo, Goparaju, & Bianchi, 2015 ). While common sleep quality measures including wake after sleep onset (WASO) and sleep onset latency (SOL) are not explicitly reported by consumer-based activity monitors, they can be

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Michele Lastella, Gregory D. Roach, Grace E. Vincent, Aaron T. Scanlan, Shona L. Halson and Charli Sargent

factors that may impact their sleep. Adolescents have a higher physiological need for sleep (8–10 h per night) compared with adults (7–9 h per night) and frequently experience delays in sleep onset and awakening. 7 , 8 Furthermore, compared with elite, adult athletes, adolescents have additional

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Sigridur L. Gudmundsdottir

interventions aimed at promoting sleep ( 9 ). The aim of this study was to objectively investigate sleep duration and intraindividual night-to-night variability of sleep duration as well as wakening after sleep onset (WASO) and sleep efficiency in young Icelandic swimmers, to compare those sleep characteristics

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Benjamin G. Serpell, Barry G. Horgan, Carmen M.E. Colomer, Byron Field, Shona L. Halson and Christian J. Cook

determined by sleep latency, sleep duration, and sleep efficiency. Sleep duration was the actual time spent asleep as determined from the start to end of sleep time minus any time awake. 21 Sleep onset latency was the difference between bedtime as defined by the participant and sleep onset time. 21 Sleep

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Benita J. Lalor, Shona L. Halson, Jacqueline Tran, Justin G. Kemp and Stuart J. Cormack

was scored as “sleep.” Scoring was conducted using Philips Respironics’ Actiwatch algorithm with sensitivity set at medium. 6 The following information was collected from the activity monitors: bedtime (hh:mm), wake-up time (hh:mm), sleep-onset latency (min), sleep duration (h), wake time (min

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Jacopo A. Vitale, Giuseppe Banfi, Andrea Galbiati, Luigi Ferini-Strambi and Antonio La Torre

, min The period of time between bedtime and sleep-onset time Sleep efficiency, % The percentage of time in bed that was spent asleep Wake after sleep onset, min The amount of time spent awake after sleep has been initiated Total sleep time, % The percentage of sleep obtained during a sleep period

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Sarah Kölling, Rob Duffield, Daniel Erlacher, Ranel Venter and Shona L. Halson

) seem to be beneficial strategies. 17 , 37 Moreover, red light in the evening might support secretion of the sleep-regulating neurohormone melatonin, and thus promoting sleep onset as well as sleep quality. 38 For example, Zaho et al 38 have shown that a 2-week treatment of whole-body red light

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Laura E. Juliff, Jeremiah J. Peiffer and Shona L. Halson

, sleep duration (amount of time spent asleep), sleep onset latency (amount of time between bedtime and sleep onset), number of wake bouts, and sleep efficiency (sleep duration expressed as a percentage of time in bed) were calculated following the rest and night game. Neuroendocrine Assessment Salivary

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Júlio A. Costa, João Brito, Fábio Y. Nakamura, Eduardo M. Oliveira, Ovidio P. Costa and António N. Rebelo

); sleep onset time (time of the first epoch of sleep between time of trying to initiate sleep and time at wake-up); wake after sleep onset (number of min awake after sleep onset); sleep fragmentation index (sum of mobility and immobility accesses in 1 min, divided by the number of immobility accesses