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Purpose: To evaluate the effects of sporting activities, training loads, and athletes' characteristics on sleep among high-level adolescent athletes, in a controlled training and academic environment., Methods: A total of 128 high-level adolescent athletes (age = 15.2 [2.0] y), across 9 different sports, completed common sleep questionnaires and were monitored daily (7.3 [2.7] d) during a typical in-season training period. Sleep was analyzed using actigraphy and sleep diaries, whereas training load was evaluated using the session rating of perceived exertion, and muscle soreness and general fatigue were reported with the aid of visual analog scales. Separate linear mixed-effects models were fitted, including the athlete as a random effect and the following variables as fixed effects: the sport practiced (categorical predictor), daily training load, age, and sex. Different models were used to compare sleep variables among sports and to assess the influence of training load, age, and sex., Results: The mean total sleep time was 7.1 (0.7) hours. Swimmers presented increased sleep fragmentation, training loads, perceived muscle soreness, and general fatigue compared with athletes who engaged in other sports. Independent of any sport-specific effects, a higher daily training load induced an earlier bedtime and reduced total sleep time and perceived sleep quality, with higher sleep fragmentation. Moreover, female athletes experienced increased total sleep time and worse sleep quality in response to stress compared with those in males., Conclusion: In a controlled training and academic environment, high-level adolescent athletes did not achieve the recommended sleep duration. Impaired sleep quality and quantity could be partially explained by increased training loads.

Purpose: Short sleep duration and poor sleep quality are common in swimmers. Sleep-hygiene strategies demonstrated beneficial effects on several sleep parameters. The present study assessed the impact of a multisession sleep-hygiene training course on sleep in elite swimmers. Methods: Twenty-eight elite swimmers (17 [2] y) participated. The sleep-hygiene strategy consisted of 3 interventions. Sleep was measured by actigraphy for 7 days before the beginning of the intervention (baseline), after the first collective intervention (postintervention), after the second collective intervention (postintervention 2), and, finally, after the individual intervention (postintervention 3). The Epworth Sleepiness Scale (ESS) was completed concurrently. Swimmers were classified into 2 groups: nonsomnolent (baseline ESS score ≤ 10, n = 13) and somnolent (baseline ESS score ≥ 11, n = 15). Results: All swimmers had a total sleep time of <8 hours per night. Sixty percent of swimmers were moderately morning type. Later bedtime, less time in bed, and total sleep time were observed in the somnolent group compared with the nonsomnolent group at baseline. An interaction between training course and group factors was observed for bedtime, with a significant advance in bedtime between baseline, postintervention 2, and postintervention 3 for the somnolent group. Conclusions: The present study confirms the importance of implementing sleep-hygiene strategies, particularly in athletes with an ESS score ≥11. A conjunction of individual and collective measures (eg, earlier bedtime, napping, and delaying morning training session) could favor the total sleep time achieved. [ABSTRACT FROM AUTHOR]

Summary: The present study aimed to: (1) investigate sleep architecture in response to an overload training and taper periods among endurance runners; and (2) assess the sleep benefits of a high‐heat‐capacity mattress topper. Twenty‐one trained male endurance runners performed a 2‐week usual training regimen (baseline) followed by 2‐week overload and taper periods. From overload to the end of the taper period, they were assigned into two groups based on the mattress topper used: high‐heat‐capacity mattress topper (n = 11) or low‐heat‐capacity mattress topper (n = 10). Training load was assessed daily using the session rating of perceived exertion. Following each period, sleep was monitored by polysomnography, and nocturnal core body temperature was recorded throughout the night. Irrespective of the group, awakening episodes > 5 min decreased following overload compared with baseline (−0.48, p = 0.05). Independently of mattress topper, each 100 A.U. increase in 7‐day training load prior to polysomnographic recording was associated with higher slow‐wave sleep proportion (β = +0.13%; p = 0.05), lower sleep‐onset latency (β = −0.49 min; p = 0.05), and a reduction in the probability of transition from N1 sleep stage to wakefulness (β = −0.12%; p = 0.05). Sleeping on a high‐heat‐capacity mattress topper did not affect any sleep variable compared with a low‐heat‐capacity mattress topper. Increased training loads promote slow‐wave sleep and sleep propensity, highlighting the adaptative nature of sleep to diurnal activity and the role of sleep in physiological recovery. Further studies are required on the potential benefits of high‐heat‐capacity mattress toppers on sleep architecture among athletes. [ABSTRACT FROM AUTHOR]

This study investigates the impact of a training program on sleep among endurance runners and the benefits of chronically using a high-heat-capacity mattress topper (HMT). Twenty-one trained male athletes performed a 2-week usual training regimen, sleeping on a Low-heat-capacity Mattress Topper (LMT), followed by 2-week overload and taper periods. From overload, participants were assigned into two groups based on the mattress topper used: HMT (n = 11) or LMT (n = 10). Irrespective of the group, overload increased general stress and stress-reaction symptoms evaluated by questionnaires, with no decline in performance on a graded-exercise treadmill test, the majority of participant being "non-overreached" (n = 14). From a daily perspective, each additional 100 A.U. in training load, assessed using the session rating of perceived exertion, was associated with an impairment in subsequent sleep efficiency (β = -0.2%; p < 0.01), wake after sleep onset (β = +0.4 min; p < 0.05) and sleep onset latency (β = +0.5 min; p < 0.05), which was unaffected by HMT use. Practitioners should be aware of sleep needs, especially during excessive training loads, whereas implementing individualised sleep strategies. Further studies should be conducted on potential benefits of HMT among athletes in various sleep conditions. [ABSTRACT FROM AUTHOR]

Athletes are increasingly required to travel domestically and internationally, often resulting in travel fatigue and jet lag. Despite considerable agreement that travel fatigue and jet lag can be a real and impactful issue for athletes regarding performance and risk of illness and injury, evidence on optimal assessment and management is lacking. Therefore 26 researchers and/or clinicians with knowledge in travel fatigue, jet lag and sleep in the sports setting, formed an expert panel to formalise a review and consensus document. This manuscript includes definitions of terminology commonly used in the field of circadian physiology, outlines basic information on the human circadian system and how it is affected by time-givers, discusses the causes and consequences of travel fatigue and jet lag, and provides consensus on recommendations for managing travel fatigue and jet lag in athletes. The lack of evidence restricts the strength of recommendations that are possible but the consensus group identified the fundamental principles and interventions to consider for both the assessment and management of travel fatigue and jet lag. These are summarised in travel toolboxes including strategies for pre-flight, during flight and post-flight. The consensus group also outlined specific steps to advance theory and practice in these areas. [ABSTRACT FROM AUTHOR]

Purpose: Using a mixed-method approach, this investigation aimed to examine athletes' sleeping patterns along with the socio-physiological acute and chronic stressors affecting their sleep. Methods: Fifteen elite athletes (M age = 21.7 years; SD = 2.2) were monitored daily during a typical in-season training period (20 ± 1 days) and completed individual semi-structured interviews. Their sleep was analyzed using actigraphy and sleep diaries. A content analysis method was used to assess qualitative interviews. Results: Three factors influencing sleep emerged from the qualitative interview analyses, i.e., sleep environment, training and study requirements. Half the athletes (8/15) complained about their sleeping environment with noise and/or bedroom temperature and/or mattress quality and/or light exposure presented as an issue. "Complainers" notably exhibited impaired (p < 0.05) sleep efficiency and wake after sleep onset compared with "non-complainers." Daily training load showed correlations (p < 0.05) with wake after sleep onset and sleep onset latency. "Student athletes" exhibited later bedtime and earlier wake-up time compared with "non-student athletes," leading to a reduced total sleep time (6:50 ± 1:13 vs. 7:06 ± 0:53; p < 0.05; d = 0.20). Conclusion: An individualized assessment of sleep using actigraphy and interviews, with consideration to various socio-physiological factors, is recommended. Individualized sleep interventions with consideration to physiological (e.g., training load), behavioral (e.g., screen use) and environmental factors (e.g., room temperature, noise, mattress), can then be provided to each athlete. [ABSTRACT FROM AUTHOR]