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).

Purpose The objective of this systematic review was to 1) determine how studies evaluated napping behavior in athletes (frequency, duration, timing and measurement); 2) explore how napping impacted physical performance, cognitive performance, perceptual measures (eg, fatigue, muscle soreness, sleepiness and alertness), psychological state and night-time sleep in athletes. Methods Five bibliographic databases were searched from database inception to 11 August 2020. Observational and experimental studies comprising able-bodied athletes (mean age ≥12 years), published in English, in peer-reviewed journal papers were included. The Downs and Black Quality Assessment Checklist was used for quality appraisal. Results Thirty-seven studies were identified of moderate quality. Most studies did not include consistent information regarding nap frequency, duration, and timing. Napping may be beneficial for a range of outcomes that benefit athletes (eg, physical and cognitive performance, perceptual measures, psychological state and night-time sleep). In addition, napping presents athletes with the opportunity to supplement their night-time sleep without compromising sleep quality. Conclusion Athletes may consider napping between 20 to 90 min in duration and between 13:00 and 16:00 hours. Finally, athletes should allow 30 min to reduce sleep inertia prior to training or competition to obtain better performance outcomes. Future studies should include comprehensive recordings of nap duration and quality, and consider using sleep over a 24 hour period (daytime naps and night-time sleep period), specifically using objective methods of sleep assessment (eg, polysomnography/actigraphy).

The Covid-19 outbreak forced many governments to enter a nationwide lockdown. The aim of this study was to evaluate, by means of a survey, changes in sleep parameters and physical activity characteristics of elite track and field athletes in three periods: before the lockdown (T0), during the lockdown (09th March – 03rd May 2020, T1) and the first month after the lockdown (T2). This study was conducted from May 2020 to June 2020 and data were collected using an offline survey with 89 elite track and field athletes (mean age: 24.7 ± 5.4; n = 43 males; n = 46 females). The survey consisted of demographic data and questions on physical activity and sleep behavior at T0, T1 and T2. Athletes reported lower sleep quality scores at T1 compared to T0 and T2 (p < 0.0001) and registered delayed bedtime, wake-up time and longer sleep latency during the lockdown compared to pre-lockdown and post-lockdown whereas no changes in total sleep time were reported. No inter-group differences were detected in sleep characteristics between short- and long-term disciplines and between genders. The weekly training volume decreased from 16.1 ± 5.7 hours at T0 to 10.7 ± 5.7 hours at T1 (p < 0.0001) whereas no significant differences were detected in training volume during the lockdown in relation to the square footage of the house (p = 0.309). Alcohol (p = 0.136) and caffeine intake (p = 0.990) and use of electronic devices (p = 0.317) were similar pre-, during, and post-lockdown. The unprecedented circumstances of the Covid-19 pandemic had negative impacts on the Italian track and field athletes’ sleep and training volumes.

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Introduction Sleep restriction is associated with impairments to cognitive performance. A current strategy to improve cognitive performance at work is breaking up prolonged sitting with light-intensity walking. However, it is unknown whether this strategy can counteract the impact of sleep restriction. This study investigated the effect of breaking up sitting on cognitive performance under conditions of sleep restriction. Method 84 healthy adults (age M± SD 23.1±4.5 years; 41 females) participated in a 7-day laboratory study, with 5 simulated workdays (0900-1700). Participants were randomly allocated to a condition: Breaking up sitting and 9-h sleep (Break9; n=20), Breaking up sitting and 5h sleep (Break5; n=20), Sedentary and 9-h sleep (Sit9; n=22), Sedentary and 5-h sleep (Sit5; n=22). Sleep opportunity prior to each workday was 9-h (2200-0700) or 5-h (0200-0700) depending on condition. Every 30-min during the workday participants in the breaking up sitting conditions completed 3-min bouts of light-intensity walking, while participants in the sedentary conditions remained sitting. At 0900, 1100, 1300, 1500, and 1700, participants completed a 10-min Psychomotor Vigilance Task and the Karolinska Sleepiness Scale. Results Mixed model ANOVAs revealed no significant 2-way or 3-way interactions between condition (Break9, Break5, Sit9 and Sit5), time of day, and workday for vigilant attention (reciprocal mean response time and mean lapses) or subjective sleepiness. Discussion Breaking up prolonged sitting with light-intensity walking did improve cognitive performance. Higher doses of physical activity may be needed to counteract the effects of sleep restriction on cognitive performance. Findings highlight the acute cognitive deficits associated with inadequate sleep.