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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.
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Sports Medicine (2021) 51:2029–2050
Managing Travel Fatigue andJet Lag inAthletes: AReview
andConsensus Statement
DinaC.JansevanRensburg1,2 · AudreyJansenvanRensburg1 · PeterM.Fowler3 · AmyM.Bender4 ·
DavidStevens5,6 · KieranO.Sullivan7,8 · HughH.K.Fullagar9 · Juan‑ManuelAlonso10 · MichelleBiggins7 ·
AmandaClaassen‑Smithers11 · RobCollins12,13· MichikoDohi14· MatthewW.Driller15 · IanC.Dunican16 ·
LukeGupta17· ShonaL.Halson18 · MicheleLastella19 · KathleenH.Miles20 · MathieuNedelec21 ·
TonyPage22· GregRoach19· CharliSargent19 · MeetaSingh23 · GraceE.Vincent19 · JacopoA.Vitale24 ·
Accepted: 7 June 2021 / Published online: 14 July 2021
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021
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 perfor-
mance 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 circa-
dian 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 con-
sensus 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.
* Dina C. Janse van Rensburg
Extended author information available on the last page of the article
1 Introduction
The modern-day athlete is often required to travel domes-
tically and internationally including high-frequency short
distances (< 3h) and low-frequency long distances (> 3h)
that may involve the crossing of numerous time zones. The
subsequent travel fatigue and jet lag experienced result in
a myriad of shared symptoms, such as daytime fatigue,
decreased concentration and alertness, sleep disruption
and gastrointestinal disturbances [1, 2]. These can lead to
increased illness and injury risk as well as adverse effects
on athletic performance [29].
Travel fatigue and jet lag are two distinct entities that
may co-occur when travelling east or west across three or
more time zones [2, 4, 1012]. Travel fatigue occurs in all
travelling athletes and can be acute following any individual
long journey, or chronic (cumulative) as a consequence of
repetitive travel within a season [4, 10]. It is a multi-domain
disturbance that generally occurs with any travel regard-
less of the direction of travel or the number of time-zones
crossed [2, 4, 10, 13]. It is caused by the demands of travel
itself, such as cramped conditions, prolonged mild hypoxia,
changes in the external environment (trans-latitudinal travel
i.e. winter–summer/summer–winter) and reduced physical
activity [10]. Jet lag is episodic with similar but more severe
and prolonged symptoms compared to travel fatigue and fol-
lows rapid travel across 3 or more time-zones (transmerid-
ian travel i.e. east–west/west–east) [4, 10]. It is typically
characterised by the desynchronisation between the internal
human circadian system and the time at the new destination
[2, 4, 10, 11, 14]. As a result, the circadian rhythm of sev-
eral psychological, physiological and behavioural variables
with a typical early morning nadir and late-afternoon peak is
misaligned with the new local time. Depending on the train-
ing or competition time, this could directly affect athletic
performance [2, 4, 5].
Although the circadian system is well understood and
described in the circadian physiology literature [5, 1519],
it remains difficult to translate and to apply this knowledge
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... Research on travel fatigue mitigation is currently lacking in athletes, but allowing time for recovery is important. 78 Traveling across time zones to compete at a high level requires a rapid shift in circadian rhythms to be able to maintain peak levels of performance, but resynchronization only occurs at a rate of 1 hour a day for easterly travel and 2 hours a day for westerly travel. 78 For performance, disruption can be seen in other biological systems, including blood pressure, cortisol, melatonin, body temperature, and grip strength, for several days after travel. ...
... 78 Traveling across time zones to compete at a high level requires a rapid shift in circadian rhythms to be able to maintain peak levels of performance, but resynchronization only occurs at a rate of 1 hour a day for easterly travel and 2 hours a day for westerly travel. 78 For performance, disruption can be seen in other biological systems, including blood pressure, cortisol, melatonin, body temperature, and grip strength, for several days after travel. 79 Travel can lead to large disruptions in sleep patterns, with western travel leading to difficulty waking up too early and eastern travel leading to difficulty initiating sleep. ...
... 80 Whenever possible, athletes should optimize their travel schedules to facilitate their circadian shift; for example, if flying east, they should have early morning flights. 78 For very short trips, maintaining the home rhythm is recommended, based on a potential greater disruption for attempts to shift and for the avoidance of jet lag when returning home. 80 For longer trips, best results will occur if there are attempts to shift circadian rhythms and banking of sleep before the onset of travel. ...
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Sleep is vital for optimal mental and physical health. For athletes, optimizing sleep is becoming a popular strategy to enhance athletic performance. Athletes often complain of sleep problems including insufficient sleep and insomnia symptoms and are also at a higher risk for sleep disordered breathing. Sleep disorders and insufficient sleep can contribute to excessive sleepiness, daytime dysfunction, and performance problems. In contrast, better sleep provides benefits for physical health and athletic performance. For athletes, multiple factors can contribute to insufficient sleep. Sport-specific factors include frequent travel across time zones, competition and training schedules, high training loads, and sleeping in an unfamiliar environment. Non-sport-related factors include work, social, and family commitments; attitudes and sleeping beliefs; individual characteristics, such as chronotype or preference for morning or evening; and lifestyle choices. Fortunately, there are strategies that can be implemented to improve sleep in athletes including (a) education and emphasis on the importance of sleep; (b) sleep screening; providing extra sleep opportunities like (c) banking sleep and (d) napping; improving sleep hygiene like (e) proper light exposure; (f) a good pre-sleep routine; (g) a conducive sleep environment; (h) a strategy for supplementation; (i) utilizing circadian timing adjustments; and (j) jet lag management. Increased recognition of the importance of sleep from sport professionals and screening for sleep disorders and disturbances will be key for future athlete health, well-being, and performance.
... It is commonly accepted that traveling across time zones affects sports performance via "jet lag". [1][2][3][4][5][6][7] This concept has likely gained broad acceptance because non-athletes often traverse multiple time zones and experience a perception that "something is off" or have irregular sleep patterns, so it is straightforward for non-athletes to accept the premise that jet lag affects sports performance with minimal resistance. One complication is distinguishing travel fatigue from jet lag. ...
... One complication is distinguishing travel fatigue from jet lag. 6 Travel fatigue is a non-medical condition resulting from frequent travel with minimal recovery, resulting in persistent fatigue, generalized recurrent illness, and potential mood changes. 8 Jet lag is a medical condition and specific to the travel direction (east→west/west→east) and the number of time zones crossed, resulting in distinctive sleep disturbances, daytime fatigue/sleepiness, and impaired mental/physical concentration. ...
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Introduction It is commonly accepted that traveling across time zones affects sport performance (i.e. via jet lag). This belief is based on poor quality evidence for team sports and simplistic analyses, such as t-tests and linear regression, to explore complex phenomena. For instance, Roy & Forest used such analyses to examine win percentages for the NFL, NBA, and NHL, concluding that East Coast teams were disadvantaged. Similarly, Smith et al. primarily used t-tests to show that West Coast NFL teams were more likely than East Coast teams to beat the Vegas spread in evening games (non-coastal teams were omitted). Neither analysis considered time zone change or game time as continuous constructs nor did they account for important contextual information. We used modern causal inference methods and a decade of Collegiate Football games to determine if jet lag and kickoff time have any causal effect on beating the Vegas spread. This required fitting nonlinear splines for both data re-weighting and analysis; however, using weights in a generalized additive model (GAM) presents challenges for standard frequentist inferences. Thus, non-parametric simulations were developed to obtain valid causal inferences via randomization inference (RI). Methods Pro Football Focus data from college football seasons 2013-2022 were paired with time zone data from Google Maps, weather data from gridMET, and Vegas spread data from GAM-based propensity scores were calculated from turf type, stadium type, precipitation, humidity, temperature, and wind speed. These propensity scores orthogonalized these variables relationship to the treatments (i.e., game time and hours gained due to time zone change) consistent with the Potential Outcomes framework. The propensity scores were used to weight the observations in a GAM logistic regression, which modeled beating the Vegas spread as a function of a splined interaction for game time and hours gained in travel. Since valid standard errors cannot be calculated from GAMs with weights, we used RI to compare the interaction effect to random chance. We simulated 5,000 datasets of random treatments under the positivity assumption. Each RI dataset was analyzed with the same GAM used for the observed data to obtain a distribution of noise F-statistics. The real data F-statistic was contrasted to the RI distribution for inferences. Results The real data were highly compatible with the null hypothesis of no effect for hours lost/gained in travel and game time (p = 0.471). Conclusion We need to rigorously interrogate assumptions regarding what affects performance in team sports. There is no clear indication that jet lag and game time affect team performance when appropriate analyses are performed in a causal inference framework. Similarly rigorous analysis should be undertaken to confirm or refute other assumptions in sport science, such as workload management, sleep practices, and dietary/supplementation regimens.
... Evidence-based countermeasures: how to mitigate the impact of travel on studentathletes and traveling staff Travel across time zones results in a mismatch between internal circadian time and local light, sleep opportunities, and mealtimes in the new time zone. Furthermore, short sleep duration before, during, and after travel contributes to jet lag symptoms such as daytime fatigue and sleepiness and impaired physical and cognitive performance (van Rensburg et al., 2021). It is therefore not surprising that meta-analyses of studies of sleep interventions on athletic performance have shown that sleep extensions through timing and naps are effective in improving athletic performance and recovery (Cunha et al., 2023;Bonnar et al., 2018). ...
Collegiate athletes must satisfy the academic obligations common to all undergraduates, but they have the additional structural and social stressors of extensive practice time, competition schedules, and frequent travel away from their home campus. Clearly such stressors can have negative impacts on both their academic and athletic performances as well as on their health. These concerns are made more acute by recent proposals and decisions to reorganize major collegiate athletic conferences. These rearrangements will require more multi-day travel that interferes with the academic work and personal schedules of athletes. Of particular concern is additional east-west travel that results in circadian rhythm disruptions commonly called jet lag that contribute to the loss of amount as well as quality of sleep. Circadian misalignment and sleep deprivation and/or sleep disturbances have profound effects on physical and mental health and performance. We, as concerned scientists and physicians with relevant expertise, developed this white paper to raise awareness of these challenges to the wellbeing of our student-athletes and their co-travelers. We also offer practical steps to mitigate the negative consequences of collegiate travel schedules. We discuss the importance of bedtime protocols, the availability of early afternoon naps, and adherence to scheduled lighting exposure protocols before, during, and after travel, with support from wearables and apps. We call upon departments of athletics to engage with sleep and circadian experts to advise and help design tailored implementation of these mitigating practices that could contribute to the current and long-term health and wellbeing of their students and their staff members.
... 2 Nevertheless, sleep in elite athletes may actually be inferior when compared with the recommendations for this specific population 3 due to different factors: increase in postmatch or posttraining muscle pain, cortisol levels and core temperature, precompetition anxiety, unfavorable training sessions schedule, travel fatigue and jet lag, and/or social media use. 4,5 Poor sleep, in general, may be characterized by insufficient sleep time, excessive nocturnal awakenings, long sleep onset latency, daytime fatigue, and sleepiness. A recent review of Walsh et al 6 showed that 50% to 78% of elite athletes experienced general sleep disturbances and 22% to 26% suffered from a severe sleep disturbance. ...
Purpose: Few data are available on sleep characteristics of elite track-and-field athletes. Our study aimed to assess (1) differences in sleep between sexes and among different track-and-field disciplines, (2) the effect of individualized sleep-hygiene strategies on athletes' sleep parameters, and (3) daytime nap characteristics in track-and-field athletes. Methods: Sleep characteristics of 16 elite Olympic-level track-and-field athletes (male: n = 8; female: n = 8) were assessed during the preseason period, at baseline (T0), and during the in-season period, after the adoption of individualized sleep-hygiene strategies (T1). Sleep parameters were objectively monitored by actigraphy for a minimum of 10 days, for each athlete, at both T0 and T1. A total of 702 nights were analyzed (T0 = 425; T1 = 277). Results: Female athletes displayed better sleep efficiency (88.69 [87.69-89.68] vs 91.72 [90.99-92.45]; P = .003, effect size [ES]: 0.44), lower sleep latency (18.99 [15.97-22.00] vs 6.99 [5.65-8.32]; P < .001, ES: 0.65), higher total sleep time (07:03 [06:56-07:11] vs 07:18 [07:10-07:26]; P = .030, ES: 0.26), earlier bedtime (00:24 [00:16-00:32] vs 00:13 [00:04-00:22]; P = .027, ES: 0.18), and lower nap frequency (P < .001) than male athletes. Long-distance runners had earlier bedtime (00:10 [00:03-00:38] vs 00:36 [00:26-00:46]; P < .001, ES: 0.41) and wake-up time (07:41 [07:36-07:46] vs 08:18 [08:07-08:30]; P < .001, ES: 0.61), higher nap frequency, but lower sleep efficiency (88.79 [87.80-89.77] vs 91.67 [90.95-92.38]; P = .013, ES: 0.44), and longer sleep latency (18.89 [15.94-21.84] vs 6.69 [5.33-8.06]; P < .001, ES: 0.67) than athletes of short-term disciplines. Furthermore, sleep-hygiene strategies had a positive impact on athletes' total sleep time (429.2 [423.5-434.8] vs 451.4 [444.2-458.6]; P < .001, ES: 0.37) and sleep latency (14.33 [12.34-16.32] vs 10.67 [8.66-12.68]; P = .017, ES: 0.19). Conclusions: Sleep quality and quantity were suboptimal at baseline in Olympic-level track-and-field athletes. Large differences were observed in sleep characteristics between sexes and among different track-and-field disciplines. Given the positive effect of individualized sleep-hygiene strategies on athlete's sleep, coaches should implement sleep education sessions in the daily routine of top-level athletes.
... 4 Despite the need for increased sleep duration, research has highlighted that athletes face several unique challenges that can affect the amount of sleep they gain each night. 5 Sleep challenges relevant to athletes are often associated with training, travel, and competition, 6,7 and they include waking up tired, excessive daytime sleepiness, 8 problems falling asleep, waking up throughout the night, and sleeping in unfamiliar environments (such as hotels). 9 Disturbed sleep has been repeatedly reported 2 to negatively affect daytime physical and cognitive performance; therefore, it is a relevant area of concern within athlete populations. ...
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Objective To evaluate the differences in subjective sleep quality, quantity, and behaviors among male and female elite rugby union athletes through two common sleep questionnaires. Materials and Methods A sample of 38 male and 27 female elite rugby union athletes filled out the Athlete Sleep Behavior Questionnaire (ASBQ) and the Pittsburgh Sleep Quality Index (PSQI). Global scores and individual items for each questionnaire were compared to assess differences between sexes. Results Male athletes reported significantly longer sleep duration (7 h 50 m ± 50 m versus 7h 12 m ± 58 m respectively; p ≤ 0.01; d = 0.70) and higher habitual sleep efficiency (88% versus 83% respectively; p < 0.05; d = 0.54) when compared with female athletes. Individual items of the ASBQ revealed significant differences between male and female athletes for five questions. Male athletes displayed higher instances of taking stimulants before training or competition and consuming alcohol within 4 hours of going to bed. Conversely, female athletes expressed greater thought or worry while in bed and a higher instance of training late at night. Discussion Male athletes displayed better self-reported sleep quality and quantity than female athletes; however, the present study highlighted that male and female elite rugby union athletes face specific challenges that differ. It appears that the differences observed between male and female elite rugby union athletes may be due to differing levels of professionalism or differences in training or competition schedules.
... In addition, the separation from families can also have a negative effect on the psychology of the away team players and this effect will increase with time. This psychological and emotional fatigue will impair the away team's performance in the game [25,29,30]. ...
... Our findings contribute to an emerging literature showing that manually delivered sleep recommendations can alter sleep-wake patterns in circadian misalignment, such as shift work, jetlag or a combination of the two (Åkerstedt et al., 2007;Booker et al., 2022;Flynn-Evans et al., 2020;Janse van Rensburg et al., 2021). This is the first study, however, to employ biomathematical models as a basis of delivering recommendations and addressing variability in shift hours. ...
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Sleep disturbances and circadian disruption play a central role in adverse health, safety, and performance outcomes in shift workers. While biomathematical models of sleep and alertness can be used to personalise interventions for shift workers, their practical implementation of is undertested. This study tested the feasibility of implementing two biomathematical models—the Phillips–Robinson Model and the Model for Arousal Dynamics—in 28 shift‐working nurses, 14 in each group. The study examined the overlap and adherence between model recommendations and sleep behaviours, and changes in sleep following the implementation of recommendations. For both groups combined, the mean (SD) percentage overlap between when a model recommended an individual to sleep and when sleep was obtained was 73.62% (10.24%). Adherence between model recommendations and sleep onset and offset times was significantly higher with the Model of Arousal Dynamics compared to the Phillips–Robinson Model. For the Phillips–Robinson model, 27% of sleep onset and 35% of sleep offset times were within ± 30 min of model recommendations. For the Model of Arousal Dynamics, 49% of sleep onset, and 35% of sleep offset times were within ± 30 min of model recommendations. Compared to pre‐study, significant improvements were observed post‐study for sleep disturbance (Phillips–Robinson Model), and insomnia severity and sleep‐related impairments (Model of Arousal Dynamics). Participants reported that using a digital, automated format for the delivery of sleep recommendations would enable greater uptake. These findings provide a positive proof‐of‐concept for using biomathematical models to recommend sleep in operational contexts.
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An editorial on "Practical tips to manage travel fatigue and jet lag in athletes". Most evidence on travel fatigue and jet lag management is from non-athletic populations in laboratory settings. We aimed to provide practical tips on pre-travel, during travel and post-travel settings, based on currently available evidence. We included an infographic for ease of reference.
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ABSTRACT Elite athletes are particularly susceptible to sleep inadequacies, characterised by habitual short sleep (<7 hours/night) and poor sleep quality (eg, sleep fragmentation). Athletic performance is reduced by a night or more without sleep, but the influence on performance of partial sleep restriction over 1–3 nights, a more real-world scenario, remains unclear. Studies investigating sleep in athletes often suffer from inadequate experimental control, a lack of females and questions concerning the validity of the chosen sleep assessment tools. Research only scratches the surface on how sleep influences athlete health. Studies in the wider population show that habitually sleeping <7 hours/night increases susceptibility to respiratory infection. Fortunately, much is known about the salient risk factors for sleep inadequacy in athletes, enabling targeted interventions. For example, athlete sleep is influenced by sport-specific factors (relating to training, travel and competition) and non-sport factors (eg, female gender, stress and anxiety). This expert consensus culminates with a sleep toolbox for practitioners (eg, covering sleep education and screening) to mitigate these risk factors and optimise athlete sleep. A one-size-fits-all approach to athlete sleep recommendations (eg, 7–9 hours/night) is unlikely ideal for health and performance. We recommend an individualised approach that should consider the athlete’s perceived sleep needs. Research is needed into the benefits of napping and sleep extension (eg, banking sleep).
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Air travel is a key factor in Super Rugby and can have a negative influence on players’ performance and well-being. The aim of this study was to identify the current practice to reduce the effects of air travel and to understand the rationale behind these interventions. “Travel managers” from eight Super Rugby teams were interviewed and answered a questionnaire. A qualitative description was performed to identify common themes and differences between participants’ answers. To protect the privacy and identity of the participants, all data have been de-identified and represented as two fictionalised amalgams (Bob and Peter). The rationale behind each intervention appeared to be based on a mix of anecdotal, practice and, occasionally, literature, confirming that scientific findings are not always easily translatable to applied settings. Two different approaches, clinical (Bob) and holistic (Peter), were identified. Even if both characters acknowledge that travel variables are too many to control, it appears that team culture and practices are perceived as important as biological interventions in controlling the negative effects of travel on players’ performance and well-being.
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The temporal organization of molecular and physiological processes is driven by environmental and behavioral cycles as well as by self-sustained molecular circadian oscillators. Quantification of phase, amplitude, period, and disruption of circadian oscillators is essential for understanding their contribution to sleep-wake disorders, social jet lag, interindividual differences in entrainment, and the development of chrono-therapeutics. Traditionally, assessment of the human circadian system, and the output of the SCN in particular, has required collection of long time series of univariate markers such as melatonin or core body temperature. Data were collected in specialized laboratory protocols designed to control for environmental and behavioral influences on rhythmicity. These protocols are time-consuming, expensive, and not practical for assessing circadian status in patients or in participants in epidemiologic studies. Novel approaches for assessment of circadian parameters of the SCN or peripheral oscillators have been developed. They are based on machine learning or mathematical model-informed analyses of features extracted from 1 or a few samples of high-dimensional data, such as transcriptomes, metabolomes, long-term simultaneous recording of activity, light exposure, skin temperature, and heart rate or in vitro approaches. Here, we review whether these approaches successfully quantify parameters of central and peripheral circadian oscillators as indexed by gold standard markers. Although several approaches perform well under entrained conditions when sleep occurs at night, the methods either perform worse in other conditions such as shift work or they have not been assessed under any conditions other than entrainment and thus we do not yet know how robust they are. Novel approaches for the assessment of circadian parameters hold promise for circadian medicine, chrono-therapeutics, and chrono-epidemiology. There remains a need to validate these approaches against gold standard markers, in individuals of all sexes and ages, in patient populations, and, in particular, under conditions in which behavioral cycles are displaced.
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Objectives We 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. Design Systematic review Eligibility criteria Randomised 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 sources Electronic 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. Results Twenty-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. Conclusions We 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 number The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42019126852).
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Research has demonstrated that induced mental fatigue impairs soccer-specific technical, tactical and physical performance in soccer players. The findings are limited by the lack of elite players and low ecological validity of the tasks used to induce mental fatigue, which do not resemble the cognitive demands of soccer. The current study collected survey data from English academy soccer players (n = 256; age groups - U14 – U23), with questions comprising of five themes (descriptors of physical and mental fatigue, travel, education, match-play and fixture congestion). The survey consisted of multiple choice responses, checkboxes and blinded/unblinded (for duration based questions) 0-100 arbitrary unit (AU) slider scales. Listening to music (81.6% of players), using social media (58.3%) and watching videos (34.3%) were the most common pre-match activities. Pre-match subjective mental fatigue was low (18.7±18.8 AU), and most frequently reported at the end of a match (47±26 AU) and remained elevated 24-hours post-match (36±27 AU). Travel (29±24 AU), fixture congestion (44±25 AU) and education (30±26 AU) demonstrated a low to moderate presence of subjective mental fatigue. These findings provide an overview of activities performed by English academy soccer players pre-match, and demonstrate that mental fatigue is experienced as a result of match-play.
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The sentiments and feelings like the aforementioned may clearly affect the balance between happiness and wellness (Calleja-Gonzalez et al., 2018). In that way, coaches focus on respecting, valuing, involving, engaging in dialogue with, listening to, and supporting players, as well as treating them as human beings, giving them the confidence and feelings of responsibility to try (BarkerRuchti et al., 2014). There is a clear need for more research in this area, although some advances were already made by examining empathy using qualitative methods and identifying factors of empathy between athletes and coaches (David and Larson, 2018). Furthermore, a period of constructive reflection considering the relationship between performance analysis and recovery is strongly recommended (Calleja-González et al., 2018). Thus, there is a gap between research and reality (Buchheit, 2017), because players express that they are more fatigued from traveling than from training or competition, which is the focus of this letter.A shift in the approach to sports performance research seems to be necessary. For example, sleep quality and quantity (Gupta et al., 2017), burden associated to traveling (Fowler et al., 2014), chronobiological disturbance (Drust et al., 2005) are often cited as limiting factors of performance in high level sport, and their impact should be considered and assessed. Further, the additive effect or the means by which one factor influence another should be taken into account (Tobias et al., 2013).Elite athletes are exposed to substantial training loads , however, that is only a (small) part of the key determinants of performance. Current trends in expertise describe the concept as a dynamically varying relationship captured by the constraints of the environment and those of the performer of a task (RW.ERROR -Unable to find reference:4304). Using this approach, the context is key and should not be detached from the content, thus, the guidelines for designing and implementation of a training program will benefit from incorporating environmental information, integrated periodization, mental performance, skill acquisition, or nutrition (Mujika et al., 2018). In addition, using the aforementioned methods in combination with athlete monitoring of training, competition and psychological load, and pooled with assessments of recovery, well-being, and illness . It may enable the achievement of enhanced performance levels.Since extended traveling is common in elite sport (Flatt et al., 2019), it is recommended that coaches and applied sports scientists consider the following key points in order to minimize injury risk, enhance recovery, optimize performance and bring down the effect of traveling and sleep disturbance on performance (Vitale et al., 2019):-Monitor external training load (before, during and after competition) using tracking systems (Fox et al., 2017) with the least possible invasion.-Monitor Internal responses using heart rate measures and biomarkers in blood, saliva and/or urine before, during and after competition (Halson, 2014).-Monitor daily sleep quality, sleep duration, and player wellbeing to inform same day adjustments to training and competition workload (Fox et al., 2019).-Arrive early to competition destination in order to include sufficient time on-site to recover from traveling and adjust to new time-zones, altitudes, climates and environments (Lastella et al., 2019).-Avoid environmental changes because changing physical sleep environments may increase susceptibility to altered sleep responses, which may negatively affect performance (Pitchford et al., 2017).-Develop and apply consistent strategies (pre, during and post-traveling) that may help prevent or ease jet lag (Fowler et al., 2014).-Develop and apply an ad-hoc nutrition plan for traveling .Stress on the body is probably cumulative (Issurin, 2009). Therefore, the development of new variables, such as ratios, that might relate player's fatigue, training demands, match performance, environmental conditions, at home or away, could be an interesting open window to explore. Further, the creation and validation of a travel fatigue scale would enhance an understanding of the travelling effect. Also, a scale of mental fatigue (Russell et al., 2019) that informs about the stress derived from training, competition and environmental stress would be most useful.With the increasing popularity of sport, number of contests, and travel demands on the rise, the importance of athlete load monitoring in combination with nutritional programming, implementation of recovery methods, and proper sleep practices cannot be underestimated. Taking these steps will make for a more effective travel experience and support athlete health and playing career longevity. In the same page, rationalizing the use of measurement instruments and procedures seems also a need, as anecdotally suggests that "strict data-led regimes undermine trust and stifle creativity, shackling a player's natural empathy with the game", thus, "it is vital that those who oversee performance in elite sport consider the consequences on players of such intense surveillance". • Bus/plane traveling (seats ergonomic, number of disposable seats in bus/plane).• Seating positions/dangerous seating positions (players education and control).• Muscle activation during traveling.• Intellectual activity during traveling.• Problem with sleep medicaments (hypotonic effects).• Sleep banking between travels and games.• Designing individual players traveling profile.• Plane/bus vibration effect on athlete's bodies.• Plane/bus engine noise stressor effect.
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To accommodate daily recurring environmental changes, animals show cyclic variations in behaviour and physiology, which include prominent behavioural states such as sleep–wake cycles but also a host of less conspicuous oscillations in neurological, metabolic, endocrine, cardiovascular and immune functions. Circadian rhythmicity is created endogenously by genetically encoded molecular clocks, whose components cooperate to generate cyclic changes in their own abundance and activity, with a periodicity of about a day. Throughout the body, such molecular clocks convey temporal control to the function of organs and tissues by regulating pertinent downstream programmes. Synchrony between the different circadian oscillators and resonance with the solar day is largely enabled by a neural pacemaker, which is directly responsive to certain environmental cues and able to transmit internal time-of-day representations to the entire body. In this Review, we discuss aspects of the circadian clock in Drosophila melanogaster and mammals, including the components of these molecular oscillators, the function and mechanisms of action of central and peripheral clocks, their synchronization and their relevance to human health. Animal circadian rhythms are controlled by central and peripheral molecular clocks, whose components generate oscillations in their own abundance and activity. Insights into how these clocks time the function of organs and tissues is increasing our understanding of animal physiology.
Caffeine is considered a cognitive enhancer at low to moderate doses because it improves alertness, vigilance, attention, and reaction time. However, no previous investigation has assessed the effect of acute caffeine intake on e-sports-specific performance. The aim of this investigation was to determine the effect of the ingestion of 3 mg per kg of body mass on simple reaction time in a color test and on hit accuracy and reaction time during a first-person shooting game. Fifteen professional e-gamers (age= 22 ± 3 years) participated in a double-blind, cross-over, randomized experimental trial. In two trials 3 days apart, participants either ingested a placebo (cellulose) or 3 mg/kg of caffeine in an opaque and unidentifiable capsule. After a 45-min wait for substance absorption, participants performed 5 attempts at a simple reaction time test and completed a first-person shooting game that included 3 attempts at a 2-min game with 60 fixed targets (180 targets in total). Reaction times (in both tests) and accuracy in hitting the targets (only in the shooting game) were measured. In comparison to the placebo, caffeine decreased simple reaction time (0.20 ± 0.01 vs. 0.19 ± 0.01 s, P < 0.01), the mean time taken to hit the targets (0.92 ± 0.07 vs. 0.88 ± 0.07 s, P < 0.01) and enhanced hit accuracy (98.8 ± 0.92 vs. 99.8 ± 0.35% of targets hit, P < 0.01). In summary, the acute ingestion of 3 mg/kg of caffeine reduced the time taken to react to a simple stimulus, decreased the time taken to hit a fixed target and improved accuracy in hitting the target in a first-person shooting game in professional e-gamers. Thus, the caffeine ingestion (3 mg/kg) might be considered as an ergogenic aid for e-sports gamers based on its effect to enhance hit accuracy and time.
Objective measures of circadian disruption are difficult to capture in a free-living environment hence the importance of validating subjective measures of jetlag. We aimed to assess the internal consistency of the 15-item Liverpool Jetlag Scale and its convergent and divergent validity with indicators of fatigue and anxiety in a large sample of air passengers. Online survey of passengers was conducted after travel on a range of long-haul flights. Jetlag was captured using the Liverpool scale, fatigue was measured using the Vitality subscale of the Short-Form Health Survey (SF-36), and the presence of anxiety or worry before, during, and after flight was self-reported. Inter-item correlations and Cronbach’s alpha were calculated to assess the internal consistency of the scale. Exploratory factor analysis was used to examine whether the scale was consistent with one underlying construct of circadian disruption. Correlations between fatigue and anxiety (flying, situational, symptoms) with jetlag were used to assess convergent and divergent validity. Linear regression was used to determine the most important symptoms contributing to subjective jetlag rating. N = 460 passengers (57% female, mean age 50, SD 16 years) were surveyed. Cronbach’s alpha indicated high internal reliability (alpha = 0.85). Jetlag was more strongly correlated with fatigue (rho = 0.47) than any type of anxiety (rho = 0.10–0.22). Exploratory factor analysis indicated responses were consistent with four factors: (i) fatigue/daytime impairment, (ii) sleep disturbance, (iii) changes in appetite and (iv) changes in bowel function. Regression analysis indicated that only changes in concentration, sleep time, fatigue, sleep quality and frequency of bowel motions were independent correlates of subjective jetlag (R² = 27%). The Liverpool Jetlag Scale is internally consistent and demonstrates the expected relationships with fatigue and anxiety. Patterns of response are not consistent with all items being derived from one underlying factor, i.e. circadian disruption. Further, not all items contributed to the jetlag rating, suggesting the single-item rating may be useful for capturing the subjective experience of jetlag, whilst a total jetlag score is useful for also capturing circadian symptoms considered by passengers to be unrelated to jetlag. Validation of subjective jetlag against objective measures of circadian disruption is required.