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  • Author: Michele Lastella x
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Amazing Athletes With Ordinary Habits: Why Is Changing Behavior So Difficult?

Shona L. Halson and Michele Lastella

Open access

How Much Sleep Does an Elite Athlete Need?

Charli Sargent, Michele Lastella, Shona L. Halson, and Gregory D. Roach

Purpose: Anecdotal reports indicate that many elite athletes are dissatisfied with their sleep, but little is known about their actual sleep requirements. Therefore, the aim of this study was to compare the self-assessed sleep need of elite athletes with an objective measure of their habitual sleep duration. Methods: Participants were 175 elite athletes (n = 30 females), age 22.2 (3.8) years (mean [SD]) from 12 individual and team sports. The athletes answered the question “how many hours of sleep do you need to feel rested?” and they kept a self-report sleep diary and wore a wrist activity monitor for ∼12 nights during a normal phase of training. For each athlete, a sleep deficit index was calculated by subtracting their average sleep duration from their self-assessed sleep need. Results: The athletes needed 8.3 (0.9) hours of sleep to feel rested, their average sleep duration was 6.7 (0.8) hours, and they had a sleep deficit index of 96.0 (60.6) minutes. Only 3% of athletes obtained enough sleep to satisfy their self-assessed sleep need, and 71% of athletes fell short by an hour or more. Specifically, habitual sleep duration was shorter in athletes from individual sports than in athletes from team sports (F 1,173 = 13.1, P < .001; d = 0.6, medium), despite their similar sleep need (F 1,173 = 1.40, P = .24; d = 0.2, small). Conclusions: The majority of elite athletes obtain substantially less than their self-assessed sleep need. This is a critical finding, given that insufficient sleep may compromise an athlete’s capacity to train effectively and/or compete optimally.

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Effect of Match Schedule Density on Self-Reported Wellness and Sleep in Referees During the Rugby World Cup

Nathan Elsworthy, Michele Lastella, Aaron T. Scanlan, and Matthew R. Blair

Purpose : To examine the effect of match schedule on self-reported wellness and sleep in rugby union referees during the 2019 Rugby World Cup. Methods : Following an observational design, 18 international-level male referees participating in the 2019 Rugby World Cup completed a daily questionnaire to quantify wellness status (sleep quality, mood, stress, fatigue, muscle soreness, and total wellness) and sleep characteristics (bedtime, wake-up time, and time in bed) from the previous night across the tournament. Linear mixed models and effect sizes (Hedges g av) assessed differences in wellness and sleep characteristics between prematch and postmatch days surrounding single-game and 2-game congested match schedules (prematch1, postmatch1, prematch2, and postmatch2 days). Results: During regular schedules, all self-reported wellness variables except stress were reduced (g av = 0.33–1.05, mean difference −0.32 to −1.21 arbitrary units [AU]) and referees went to bed later (1.08, 1:07 h:min) and spent less time in bed (−0.78, 00:55 h:min) postmatch compared with prematch days. During congested schedules, only wellness variables differed across days, with total wellness reduced on postmatch1 (−0.88, −3.56 AU) and postmatch2 (−0.67, −2.70 AU) days, as well as mood (−1.01, −0.56 AU) and fatigue (−0.90, −1.11 AU) reduced on postmatch1 days compared with prematch days. Conclusion: Referees were susceptible to acute reductions in wellness on days following matches regardless of schedule. However, only single-game regular match schedules negatively impacted the sleep characteristics of referees. Targeted strategies to maximize wellness status and sleep opportunities in referees considering the match schedule faced should be explored during future Rugby World Cup competitions.

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The Sleep of Elite Australian Rules Footballers During Preseason: A Comparison of Men and Women

Spencer S.H. Roberts, Emma Falkenberg, Alysha Stevens, Brad Aisbett, Michele Lastella, and Dominique Condo

Purpose: Australian football has elite men’s (Australian Football League; AFL) and women’s (Australian Football League Women’s; AFLW) competitions. This study compared AFL and AFLW players’ sleep and characterized players’ sleep in the context of current sleep recommendations. Methods: A total of 70 players (36 AFL, 34 AFLW) had their sleep monitored via actigraphy over a 10-day preseason period. Sleep outcomes and their intraindividual variation, were compared between AFL and AFLW players using linear mixed models. Proportions of players sleeping ≥7 and ≥8 hours per night, and achieving ≥85% sleep efficiency, were compared using chi-square analyses. Results: Compared with AFL players, AFLW players slept less (7.9 [0.5] vs 7.1 [0.6] h, P = .000), had lower sleep efficiency (89.5% [2.8%] vs 84.0% [4.4%], P = .000), and greater intraindividual variation in sleep efficiency (3.1% [0.9%] vs 5.1% [2.1%], P = .000). A total of 47% of AFLW versus 3% of AFL players averaged <7 hours sleep (χ 2 = 18.6, P = .000). A total of 88% of AFLW versus 50% of AFL players averaged <8 hours sleep (χ 2 = 11.9, P = .001). A total of 53% of AFLW versus 14% of AFL players averaged <85% sleep efficiency (χ 2 = 12.1, P = .001). Conclusions: AFLW players slept less and had poorer sleep quality than AFL players. Many AFLW players do not meet current sleep duration or sleep quality recommendations. Research should test strategies to improve sleep among Australian rules footballers, particularly among elite women.

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The Impact of Sleep Inertia on Physical, Cognitive, and Subjective Performance Following a 1- or 2-Hour Afternoon Nap in Semiprofessional Athletes

Georgia Romyn, Gregory D. Roach, Michele Lastella, Dean J. Miller, Nathan G. Versey, and Charli Sargent

Purpose: This study examined the impact of sleep inertia on physical, cognitive, and subjective performance immediately after a 1- or 2-hour afternoon nap opportunity. Methods: Twelve well-trained male athletes completed 3 conditions in a randomized, counterbalanced order—9 hours in bed overnight without a nap opportunity the next day (9 + 0), 8 hours in bed overnight with a 1-hour nap opportunity the next day (8 + 1), and 7 hours in bed overnight with a 2-hour nap opportunity the next day (7 + 2). Nap opportunities ended at 4:00 PM. Sleep was assessed using polysomnography. Following each condition, participants completed four 30-minute test batteries beginning at 4:15, 4:45, 5:15, and 5:45 PM. Test batteries included a warm-up, self-ratings of readiness to perform, motivation to perform and expected performance, two 10-m sprints, 2 agility tests, a 90-second response-time task, and 5 minutes of seated rest. Results: Total sleep time was not different between conditions (P = .920). There was an effect of condition on readiness (P < .001), motivation (P = .001), and expected performance (P = .004)—all 3 were lower in the 8 + 1 and 7 + 2 conditions compared with the 9 + 0 condition. There was no effect of condition on response time (P = .958), sprint time (P = .204), or agility (P = .240), but a large effect size was observed for agility. Conclusions: After waking from a nap opportunity, agility may be reduced, and athletes may feel sleepy and not ready or motivated to perform. Athletes should schedule sufficient time (∼1 h) after waking from a nap opportunity to avoid the effects of sleep inertia on performance.