An education intervention in a professional female basketball team and coaching staff improves sleep and alertness

Dunican, Ian C.; Caldwell, John A.; Morgan, Darrell; Stewart, Andy; Eastwood, Peter R.

doi:10.1002/tsm2.218

Cited by 7 publications

(7 citation statements)

References 26 publications

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“…Overall, the findings of this study and those reported in other studies [14,33,34] suggest female basketball players attain adequate sleep durations (>7 h per night), according to the National Sleep Foundation's recommendations for adults [2]. Indeed, semiprofessional, female basketball players in the present study attained a nightly sleep duration of 7.3 ± 0.3 h (marginal mean ± SE) across all nights, which is comparable to average total sleep times reported previously in professional, female basketball players (8.1 ± 1.6 h [33], 7.6 ± 1.5 h [34], and 7.4 ± 1.5 h per night [14]).…”

Section: Discussionsupporting

confidence: 89%

“…Specifically, Taber et al [32] reported that first-division collegiate players (n = 16) attained 6.7 ± 0.9 h of sleep per night, measured using a wrist-worn device (WHOOP; Boston, MA, USA) across 3 weeks of the off-season and 6 weeks of the pre-season combined. In turn, Dunican et al [33] documented that professional players (n = 12) competing in the Australian Women's National Basketball League (WNBL) attained 8.1 ± 1.6 h of sleep at an efficiency (i.e., measure of sleep quality whereby sleep duration is expressed as a percentage of time in bed) of 92 ± 5% per night, measured using wrist-worn activity monitors (Readiband TM ; Fatigue Science Inc, Vancouver, Canada) during 4 weeks of the in-season, before undergoing an educational intervention. Considering game schedules, Staunton et al [34] observed that WNBL players (n = 17) attained 7.6 ± 1.5 h of sleep at 92 ± 4% efficiency per night across two consecutive in-seasons using wrist-worn activity monitors (GT3-X; ActiGraph, Pensacola, FL, USA), but experienced significant (p < 0.05) reductions in sleep duration on nights following the second game in double-headers (i.e., two games in one week) compared to nights following games in single-game weeks [34].…”

Section: Introductionmentioning

confidence: 98%

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Sleep Patterns Fluctuate Following Training and Games across the Season in a Semi-Professional, Female Basketball Team

et al. 2023

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Quantifying athlete sleep patterns may inform development of optimal training schedules and sleep strategies, considering the competitive challenges faced across the season. Therefore, this study comprehensively quantified the sleep patterns of a female basketball team and examined variations in sleep between nights. Seven semi-professional, female basketball players had their sleep monitored using wrist-worn activity monitors and perceptual ratings during a 13-week in-season. Sleep variables were compared between different nights (control nights, training nights, training nights before games, nights before games, non-congested game nights, and congested game nights), using generalized linear mixed models, as well as Cohen’s d and odds ratios as effect sizes. Players experienced less sleep on training nights before games compared to control nights, training nights, nights before games, and congested game nights (p < 0.05, d = 0.43–0.69). Players also exhibited later sleep onset times on non-congested game nights compared to control nights (p = 0.01, d = 0.68), and earlier sleep offset times following training nights before games compared to all other nights (p < 0.01, d = 0.74–0.79). Moreover, the odds of players attaining better perceived sleep quality was 88% lower on congested game nights than on nights before games (p < 0.001). While players in this study attained an adequate sleep duration (7.3 ± 0.3 h) and efficiency (85 ± 2%) on average across the in-season, they were susceptible to poor sleep on training nights before games and following games. Although limited to a team-based case series design, these findings suggest basketball coaches may need to reconsider scheduling team-based, on-court training sessions on nights prior to games and consider implementing suitable psychological and recovery strategies around games to optimize player sleep.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 98%

Sleep Patterns Fluctuate Following Training and Games across the Season in a Semi-Professional, Female Basketball Team

et al. 2023

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“…However, on the night before doubleheaders, TST was approximately one hour greater compared with baseline (p = 0.022) and match-day (p = 0.007) [ 48 ]. Across a four-week period encompassing five games (three home, two away), 12 basketball players experienced TST of 8.1 ± 1.6 h, SE of 92.0 ± 5.0% and SOL of 30.0 ± 29.0 min [ 49 ].…”

Section: Resultsmentioning

confidence: 99%

What are the sleep characteristics of elite female athletes? A systematic review with meta-analysis

Miles¹,

Clark²,

Fowler³

et al. 2022

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With the recent growth in female sport, practitioners need to be able to provide specific support to female athletes to ensure their sleep, health and athletic performance are optimised. Examine the patterns, duration and quality of sleep among elite female athletes, and consider the impact of situational challenges and their effects on the sleep of elite female athletes. Data was located through a search of SPORTDiscus, MEDLINE and Scopus from inception up to May 2021. Studies needed to be peer-reviewed research reporting quantitative sleep outcomes for female athletes ≥ 18 years of age and competing at a predefined elite level. A meta-analysis was performed on habitual sleep outcomes (e.g. total sleep time [TST] and sleep efficiency [SE]) measured with actigraphy. A total of 38 studies were included. Meta-analysis showed habitual TST (n = 14) was 7.8 h [7.4, 8.2] (mean [95% CI]), and SE was 86.7% [84.7, 88.6], with high variability among studies (I 2 = 97.8–98.2%). Subjective sleep complaints are common before a competition, as do post-training sleep disturbances (63% studies report TST decrease), and post-competition sleep disturbances (75% studies report TST decrease). Female athletes achieve satisfactory objective sleep quantity and quality during habitual periods, but experience sleep disturbances pre- and post-situational challenges. There is high variability of objective sleep outcomes, demonstrating the individual nature of habitual female athlete sleep. Overall, future research must focus on optimising the sleep appraisal methods and creating high-quality study designs in a broader number of sports.

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“…In addition, to optimise sleep – including sleep following evening training - swimmers may benefit from a “ sleep hygiene education program”, which has been shown to improve measures of sleep in other athletic groups. 38,39 Such education could also help to limit the potential negative effects of alcohol consumption on sleep, which may be pertinent in this population given five swimmers (21%) consumed alcohol to hazardous and harmful levels although no statistical relationships were found in this study.…”

Section: Discussionmentioning

confidence: 71%

Understanding the sleep of ultra-marathon swimmers: Guidance for coaches and swimmers

Dunican

Perry

Maisey³

et al. 2022

International Journal of Sports Science & Coaching

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Open water swimming ultra-marathon events ≥10 km have become increasingly popular amongst master athletes. However, very little is known about the timing of training sessions and the impact on sleep. This study aimed to examine sleep behaviours, sleep problems and disorders and the relationship with training timings. This study used a longitudinal observational design for 42 nights with 24 masters' swimmers (n = 13 females), aged 39 ± 11 years, body mass index of 26 ± 3 kg/m2 during a training squad for an ocean ultra-swim (19.7 km) in Western Australia. Objective measures of sleep were obtained from a wrist-activity monitor, the Readiband™ (Fatigue Science Inc., Canada). Swimmers completed a survey instrument related to sleep problems, disorders, chronotype, anthropometric and demographic information. Generalised linear mixed models were fitted to examine relationships between predictor variables and sleep responses. Body mass index was associated with a decline in Total Sleep Time (TST), each one-unit increase in BMI was associated with 5 min less TST (p = 0.04). Swimmers with a “high risk” of sleep apnea had 21 min more wake time (p = 0.04) and 5% lower Sleep Efficiency (p = 0.04). Sleep Offset on the morning of a morning training session was earlier by 48 min (p < 0.001) resulting in less TST by 39 min (p < 0.001). This study provides evidence that coaches need to consider sleep behaviours and problems before designing training schedules. Swimmers need to plan and allocate an adequate sleep opportunity and those who have a suspected sleep disorder or problem should seek the support of a sleep physician.

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An education intervention in a professional female basketball team and coaching staff improves sleep and alertness

Cited by 7 publications

References 26 publications

Sleep Patterns Fluctuate Following Training and Games across the Season in a Semi-Professional, Female Basketball Team

Sleep Patterns Fluctuate Following Training and Games across the Season in a Semi-Professional, Female Basketball Team

What are the sleep characteristics of elite female athletes? A systematic review with meta-analysis

Understanding the sleep of ultra-marathon swimmers: Guidance for coaches and swimmers

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