This study has shown that the removal of electronic devices for a period of two nights (48 hours) during a judo camp does not affect sleep quality or quantity or influence athletic or cognitive performance.

Accurate measurement of time at lights out is essential for calculation of several measures of sleep in wrist-activity monitors. While some devices use subjective reporting of time of lights out from a sleep diary, others utilise an automated proprietary scoring algorithm to calculate time at lights out, thereby negating the need for a sleep diary. This study aimed to compare sleep-measures from two such devices to polysomnography (PSG) measures (In-Laboratory) and against each other when worn at home (At-Home). Fifty middle-aged adults from the Raine Study underwent overnight PSG during which they wore an ActiGraph™ and a Readiband™. They also wore both devices at home for 7 nights. The Readiband uses an automated proprietary algorithm to determine time at lights out whereas the ActiGraph requires completion of a sleep diary noting this time. In laboratory, compared to PSG: Readiband underestimated time at lights out, sleep onset, and wake after sleep onset, overestimated sleep latency and duration (p<0.001 for all); while ActiGraph underestimated sleep latency and wake after sleep onset and overestimated sleep efficiency and duration (p<0.001 for all). Similar differences between devices were observed on the laboratory night and when at home. In conclusion, an automated algorithm such as the Readiband may be used in the same capacity as the ActiGraph for the collection of sleep measures including time at sleep onset, sleep duration and time at wake. However, Readiband and ActiGraph measures of sleep latency, efficiency and wake after sleep onset should be interpreted with caution.

ObjectivesWe investigated the management of travel fatigue and jet lag in athlete populations by evaluating studies that have applied non-pharmacological interventions (exercise, sleep, light and nutrition), and pharmacological interventions (melatonin, sedatives, stimulants, melatonin analogues, glucocorticoids and antihistamines) following long-haul transmeridian travel-based, or laboratory-based circadian system phase-shifts.DesignSystematic reviewEligibility criteriaRandomised controlled trials (RCTs), and non-RCTs including experimental studies and observational studies, exploring interventions to manage travel fatigue and jet lag involving actual travel-based or laboratory-based phase-shifts. Studies included participants who were athletes, except for interventions rendering no athlete studies, then the search was expanded to include studies on healthy populations.Data sourcesElectronic searches in PubMed, MEDLINE, CINAHL, Google Scholar and SPORTDiscus from inception to March 2019. We assessed included articles for risk of bias, methodological quality, level of evidence and quality of evidence.ResultsTwenty-two articles were included: 8 non-RCTs and 14 RCTs. No relevant travel fatigue papers were found. For jet lag, only 12 athlete-specific studies were available (six non-RCTs, six RCTs). In total (athletes and healthy populations), 11 non-pharmacological studies (participants 600; intervention group 290; four non-RCTs, seven RCTs) and 11 pharmacological studies (participants 1202; intervention group 870; four non-RCTs, seven RCTs) were included. For non-pharmacological interventions, seven studies across interventions related to actual travel and four to simulated travel. For pharmacological interventions, eight studies were based on actual travel and three on simulated travel.ConclusionsWe found no literature pertaining to the management of travel fatigue. Evidence for the successful management of jet lag in athletes was of low quality. More field-based studies specifically on athlete populations are required with a multifaceted approach, better design and implementation to draw valid conclusions.PROSPERO registration numberThe protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42019126852).

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.

Esports is becoming increasingly professionalized, yet research on performance management is remarkably lacking. The present study aimed to investigate the sleep and mood of professional esports athletes. Participants were 17 professional esports athletes from South Korea (N = 8), Australia (N = 4), and the United States (N = 5) who played first person shooter games (mean age 20 ± 3.5 years, 100% male). All participants wore a wrist-activity monitor for 7–14 days and completed subjective sleep and mood questionnaires. Participants had a median total sleep time of 6.8 h and a sleep efficiency of 86.4% per night. All participants had significantly delayed sleep patterns (median sleep onset 3:43 a.m. and wake time 11:24 a.m.). Participants had a median sleep onset latency of 20.4 min and prolonged wake after sleep onset of 47.9 min. Korean players had significantly higher depression scores compared to the other groups (p < 0.01) and trained longer per day than the Australian or United States teams (13.4 vs. 4.8 vs. 6.1 h, respectively). Depression scores were strongly correlated with number of awakenings, wake after sleep onset, and daily training time (p < 0.05). As the first pilot sleep study in the esports field, this study indicates that esports athletes show delayed sleep patterns and have prolonged wake after sleep onset. These sleep patterns may be associated with mood (depression) and training time. Sleep interventions designed specifically for esports athletes appear warranted.