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CC BY-NC-ND 4.0 · Sleep Sci
DOI: 10.1055/s-0043-1777778
Original Article

Sink or Swim? Sleep Patterns in Highly Trained Adolescent Swimmers during the In-Season Phase of Training

Claudia Ashby
1   School of Health, University of Waikato, Hamilton, Waikato, New Zealand
,
Matthew W. Driller
2   Sport, Performance, and Nutrition Research Group, School of Allied Health, Human Services, and Sport, Melbourne, La Trobe University, Victoria, Australia
,
Haresh Suppiah 
2   Sport, Performance, and Nutrition Research Group, School of Allied Health, Human Services, and Sport, Melbourne, La Trobe University, Victoria, Australia
,
Shannon O'Donnell
1   School of Health, University of Waikato, Hamilton, Waikato, New Zealand
› Institutsangaben Funding The author(s) received no financial support for the research.
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Abstract

Objectives The aim of this study was to investigate the sleeping patterns of highly-trained adolescent swimmers. Further objectives were to compare subjective and objective measures of sleep and to evaluate the relationship between electronic device use and sleep in this cohort.

Methods Fifteen national-level swimmers (age: 16.4 ± 1.0 years) wore wrist actigraphs while completing sleep diaries over a two-week training period. Types of nights were classified as early morning training (≤7am - EARLY), day training (>7am - DAY), and no training (REST). Information on electronic device use before bed and other sleep behaviors was collected via questionnaires.

Results Total sleep time (TST) was significantly (p < 0.05) shorter on nights preceding EARLY (5:53 ± 1:06 hour:min) compared with nights preceding DAY (7:40 ± 1:12 hour:min) and REST (7:59 ± 1:19 hour:min). Participants overestimated subjective TST by ∼54 minutes when compared with objectively measured TST (p < 0.05).

Discussion Adolescent athletes obtained a greater amount of sleep prior to later training the next day or before rest days, when compared with early morning swim training the next day. Adolescents also overestimated their sleep duration by ∼1 hour per night. There were no significant relationships between electronic device use at night and measured sleep indices.

Keywords

actigraphy - sports - athletes


Publikationsverlauf

Artikel online veröffentlicht:
09. April 2024

© 2024. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • References

  • 1 Sheehan CM, Frochen SE, Walsemann KM, Ailshire JA. Are U.S. adults reporting less sleep?: Findings from sleep duration trends in the National Health Interview Survey, 2004-2017. Sleep 2019; 42 (02) zsy221
    CrossrefPubMedGoogle Scholar
  • 2 Fullagar HH, Skorski S, Duffield R, Hammes D, Coutts AJ, Meyer T. Sleep and athletic performance: the effects of sleep loss on exercise performance, and physiological and cognitive responses to exercise. Sports Med 2015; 45 (02) 161-186
    CrossrefPubMedGoogle Scholar
  • 3 Halson SL. Nutrition, sleep and recovery. Eur J Sport Sci 2008; 8 (02) 119-126
    CrossrefGoogle Scholar
  • 4 Walsh NP, Halson SL, Sargent C. et al. Sleep and the athlete: narrative review and 2021 expert consensus recommendations. Br J Sports Med 2020; 55 (07) 356-368
    CrossrefPubMedGoogle Scholar
  • 5 Skein M, Duffield R, Edge J, Short MJ, Mündel T. Intermittent-sprint performance and muscle glycogen after 30 h of sleep deprivation. Med Sci Sports Exerc 2011; 43 (07) 1301-1311
    CrossrefPubMedGoogle Scholar
  • 6 Oliver SJ, Costa RJS, Laing SJ, Bilzon JLJ, Walsh NP. One night of sleep deprivation decreases treadmill endurance performance. Eur J Appl Physiol 2009; 107 (02) 155-161
    CrossrefPubMedGoogle Scholar
  • 7 Simpson NS, Gibbs EL, Matheson GO. Optimizing sleep to maximize performance: implications and recommendations for elite athletes. Scand J Med Sci Sports 2017; 27 (03) 266-274
    CrossrefPubMedGoogle Scholar
  • 8 Teece AR, Argus CK, Gill N, Beaven M, Dunican IC, Driller MW. Sleep and performance during a preseason in elite rugby union athletes. Int J Environ Res Public Health 2021; 18 (09) 4612
    CrossrefPubMedGoogle Scholar
  • 9 Leeder J, Glaister M, Pizzoferro K, Dawson J, Pedlar C. Sleep duration and quality in elite athletes measured using wristwatch actigraphy. J Sports Sci 2012; 30 (06) 541-545
    CrossrefPubMedGoogle Scholar
  • 10 Venter R. Role of sleep in performance and recovery of athletes: A review article. SA J Res Sport Phys Educ Recreat 2012; 34 (01) 167-184
    Google Scholar
  • 11 Brown GA, Veith S, Sampson JA, Whalan M, Fullagar HHK. Influence of training schedules on objective measures of sleep in adolescent academy football players. J Strength Cond Res 2020; 34 (09) 2515-2521
    CrossrefPubMedGoogle Scholar
  • 12 Gudmundsdottir SL. Training schedule and sleep in adolescent swimmers. Pediatr Exerc Sci 2020; 32 (01) 16-22
    CrossrefPubMedGoogle Scholar
  • 13 Steenekamp T, Zaslona J, Gander P, Rowlands D, Leigh Signal T. Sleep/wake behaviour of competitive adolescent athletes in New Zealand: insight into the impact of early morning training. Sleep Med 2021; 77 (01) 88-95
    CrossrefPubMedGoogle Scholar
  • 14 Crowley SJ, Wolfson AR, Tarokh L, Carskadon MA. An update on adolescent sleep: New evidence informing the perfect storm model. J Adolesc 2018; 67: 55-65
    CrossrefPubMedGoogle Scholar
  • 15 Carskadon MA, Vieira C, Acebo C. Association between puberty and delayed phase preference. Sleep 1993; 16 (03) 258-262
    CrossrefPubMedGoogle Scholar
  • 16 Pillion M, Gradisar M, Bartel K, Whittall H, Kahn M. What's “app”-ning to adolescent sleep? Links between device, app use, and sleep outcomes. Sleep Med 2022; 100: 174-182
    CrossrefPubMedGoogle Scholar
  • 17 Bartel K, Scheeren R, Gradisar M. Altering adolescents' pre-bedtime phone use to achieve better sleep health. Health Commun 2019; 34 (04) 456-462
    CrossrefPubMedGoogle Scholar
  • 18 Bartel KA, Gradisar M, Williamson P. Protective and risk factors for adolescent sleep: a meta-analytic review. Sleep Med Rev 2015; 21: 72-85
    CrossrefPubMedGoogle Scholar
  • 19 Galland BC, de Wilde T, Taylor RW, Smith C. Sleep and pre-bedtime activities in New Zealand adolescents: differences by ethnicity. Sleep Health 2020; 6 (01) 23-31
    CrossrefPubMedGoogle Scholar
  • 20 Figueiro M, Overington D. Self-luminous devices and melatonin suppression in adolescents. Light Res Technol 2015; 48 (08) 966-975
    CrossrefGoogle Scholar
  • 21 Mazzer K, Bauducco S, Linton SJ, Boersma K. Longitudinal associations between time spent using technology and sleep duration among adolescents. J Adolesc 2018; 66: 112-119
    CrossrefPubMedGoogle Scholar
  • 22 Copenhaver EA, Diamond AB. The value of sleep on athletic performance, injury, and recovery in the young athlete. Pediatr Ann 2017; 46 (03) e106-e111
    CrossrefPubMedGoogle Scholar
  • 23 Suppiah HT, Low CY, Chia M. Effects of sports training on sleep characteristics of Asian adolescent athletes. Biol Rhythm Res 2015; 46 (04) 523-536
    CrossrefGoogle Scholar
  • 24 Milewski MD, Skaggs DL, Bishop GA. et al. Chronic lack of sleep is associated with increased sports injuries in adolescent athletes. J Pediatr Orthop 2014; 34 (02) 129-133
    CrossrefPubMedGoogle Scholar
  • 25 von Rosen P, Frohm A, Kottorp A, Fridén C, Heijne A. Too little sleep and an unhealthy diet could increase the risk of sustaining a new injury in adolescent elite athletes. Scand J Med Sci Sports 2017; 27 (11) 1364-1371
    CrossrefPubMedGoogle Scholar
  • 26 Hirshkowitz M, Whiton K, Albert SM. et al. National Sleep Foundation's sleep time duration recommendations: methodology and results summary. Sleep Health 2015; 1 (01) 40-43
    CrossrefPubMedGoogle Scholar
  • 27 Driller MW, Suppiah H, Rogerson D, Ruddock A, James L, Virgile A. Investigating the sleep habits in individual and team-sport athletes using the Athlete Sleep Behavior Questionnaire and the Pittsburgh Sleep Quality Index. Sleep Sci 2022; 15 (01) 112-117
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 28 Caia J, Thornton HR, Kelly VG. et al. Does self-perceived sleep reflect sleep estimated via activity monitors in professional rugby league athletes?. J Sports Sci 2018; 36 (13) 1492-1496
    CrossrefPubMedGoogle Scholar
  • 29 Lastella M, Memon AR, Vincent GE. Global research output on sleep research in athletes from 1966 to 2019: A bibliometric analysis. Clocks Sleep 2020; 2 (02) 99-119
    CrossrefPubMedGoogle Scholar
  • 30 Lakens D. Sample size justification. Collabra Psychol 2022; 8 (01) 33267
    CrossrefGoogle Scholar
  • 31 Buysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989; 28 (02) 193-213
    CrossrefPubMedGoogle Scholar
  • 32 Mastin DF, Bryson J, Corwyn R. Assessment of sleep hygiene using the Sleep Hygiene Index. J Behav Med 2006; 29 (03) 223-227
    CrossrefPubMedGoogle Scholar
  • 33 Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 1991; 14 (06) 540-545
    CrossrefPubMedGoogle Scholar
  • 34 Chervin RD, Aldrich MS, Pickett R, Guilleminault C. Comparison of the results of the Epworth Sleepiness Scale and the Multiple Sleep Latency Test. J Psychosom Res 1997; 42 (02) 145-155
    CrossrefPubMedGoogle Scholar
  • 35 Driller MW, Mah CD, Halson SL. Development of the athlete sleep behavior questionnaire: A tool for identifying maladaptive sleep practices in elite athletes. Sleep Sci 2018; 11 (01) 37-44
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 36 Sadeh A. The role and validity of actigraphy in sleep medicine: an update. Sleep Med Rev 2011; 15 (04) 259-267
    CrossrefPubMedGoogle Scholar
  • 37 Driller MW, O'Donnell S, Tavares F. What wrist should you wear your actigraphy device on? Analysis of dominant vs. non-dominant wrist actigraphy for measuring sleep in healthy adults. Sleep Sci 2017; 10 (03) 132-135
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 38 Driller M, McQuillan J, O'Donnell S. Inter-device reliability of an automatic-scoring actigraph for measuring sleep in healthy adults. Sleep Sci 2016; 9 (03) 198-201
    CrossrefPubMedGoogle Scholar
  • 39 Dunican IC, Murray K, Slater J. et al. Laboratory and home comparison of wrist-activity monitors and polysomnography in middle-aged adults. Sleep Biol Rhythms 2017; 16: 85-97
    CrossrefGoogle Scholar
  • 40 Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Earlbaum Associates; 1988
    Google Scholar
  • 41 Evans JD. Straightforward statistics for the behavioral sciences: Thomson Brooks/Cole. 1996
    PubMedGoogle Scholar
  • 42 Samuels C. Sleep, recovery, and performance: the new frontier in high-performance athletics. Neurol Clin 2008; 26 (01) 169-180 , ix–x
    CrossrefPubMedGoogle Scholar
  • 43 Setyowati A, Chung M-H, Yusuf A, Haksama S. Psychometric properties of sleep hygiene index in Indonesian adolescents. J Public Health Res 2020; 9 (02) 1806
    CrossrefPubMedGoogle Scholar
  • 44 Short MA, Gradisar M, Lack LC, Wright H, Carskadon MA. The discrepancy between actigraphic and sleep diary measures of sleep in adolescents. Sleep Med 2012; 13 (04) 378-384
    CrossrefPubMedGoogle Scholar
  • 45 Short MA, Gradisar M, Lack LC, Wright HR, Chatburn A. Estimating adolescent sleep patterns: parent reports versus adolescent self-report surveys, sleep diaries, and actigraphy. Nat Sci Sleep 2013; 5: 23-26
    CrossrefPubMedGoogle Scholar
  • 46 Sun W, Ling J, Zhu X, Lee TM-C, Li SX. Associations of weekday-to-weekend sleep differences with academic performance and health-related outcomes in school-age children and youths. Sleep Med Rev 2019; 46: 27-53
    CrossrefPubMedGoogle Scholar
  • 47 Becker SP, Sidol CA, Van Dyk TR, Epstein JN, Beebe DW. Intraindividual variability of sleep/wake patterns in relation to child and adolescent functioning: A systematic review. Sleep Med Rev 2017; 34: 94-121
    CrossrefPubMedGoogle Scholar
  • 48 Díaz-Morales JF, Escribano C. Social jetlag, academic achievement and cognitive performance: Understanding gender/sex differences. Chronobiol Int 2015; 32 (06) 822-831
    CrossrefPubMedGoogle Scholar
  • 49 O'Donnell S, Driller MW. Sleep-hygiene education improves sleep indices in elite female athletes. Int J Exerc Sci 2017; 10 (04) 522-530
    PubMedGoogle Scholar
  • 50 Fullagar H, Skorski S, Duffield R, Meyer T. The effect of an acute sleep hygiene strategy following a late-night soccer match on recovery of players. Chronobiol Int 2016; 33 (05) 490-505
    CrossrefPubMedGoogle Scholar
  • 51 Mireku MO, Barker MM, Mutz J. et al. Night-time screen-based media device use and adolescents' sleep and health-related quality of life. Environ Int 2019; 124: 66-78
    CrossrefPubMedGoogle Scholar
  • 52 Chang A-M, Aeschbach D, Duffy JF, Czeisler CA. Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proc Natl Acad Sci U S A 2015; 112 (04) 1232-1237
    CrossrefPubMedGoogle Scholar