Dunican, IC, Martin, DT, Halson, SL, Reale, RJ, Dawson, BT, Caldwell, JA, Jones, MJ, and Eastwood, PR. The effects of the removal of electronic devices for 48 hours on sleep in elite judo athletes. J Strength Cond Res 31(10): 2832–2839, 2017—This study examined the effects of evening use of electronic devices (i.e., smartphones, etc.) on sleep quality and next-day athletic and cognitive performance in elite judo athletes. Over 6 consecutive days and nights, 23 elite Australian judo athletes were monitored while attending a camp at the Australian Institute of Sport (AIS). In 14 athletes, all electronic devices were removed on days 3 and 4 (i.e., for 48 hours: the “device-restricted group”), whereas 9 were permitted to use their devices throughout the camp (the “control group”). All athletes wore an activity monitor (Readiband) continuously to provide measures of sleep quantity and quality. Other self-reported (diary) measures included time in bed, electronic device use, and rate of perceived exertion during training periods. Cognitive performance (Cogstate) and physical performance (single leg triple hop test) were also measured. When considering night 2 as a “baseline” for each group, removal of electronic devices on nights 3 and 4 (device-restricted group) resulted in no significant differences in any sleep-related measure between the groups. When comparing actigraphy-based measures of sleep to subjective measures, all athletes significantly overestimated sleep duration by 58 ± 85 minutes (p = 0.001) per night and underestimated time of sleep onset by 37 ± 72 minutes (p = 0.001) per night. No differences in physical or cognitive function were observed between the groups. Conclusion: 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.

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.

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).

Objective: To examine the relationship between regular game‐related caffeine consumption on sleep after an evening Super Rugby game. Methods: Twenty elite rugby union players wore a wrist‐activity monitor to measure sleep for three days before, three days after and on the night of an evening Super Rugby game (19:00–21:00). Players ingested caffeine as they would normally (i.e. before and sometimes during a game) and saliva samples were collected before (17:00) and after (21:30) the game for caffeine concentration. Results: Compared to the nights leading up to the game, on the night of the game, players went to bed 3 h later (23:08 ± 66 min vs 02:11 ± 114 min; p < .001) and had 1:30 hh:mm less sleep (5:54 ± 2:59 vs 8:02 ± 1:24 hh:mm; p < .05) and four players did not sleep after the game. Post‐game caffeine saliva concentrations were greater than pre‐game levels in 17 players (Pre‐game 0.40 µg/mL vs Post‐game 2.77 µg/mL; p < .001). The increase in caffeine saliva concentrations was moderately associated with an increase in sleep latency (p < .05), a decrease in sleep efficiency (p < .05), and a trend for a decrease in sleep duration (p = .06) on game night. Conclusion: Caffeine consumption before a Super Rugby game markedly increases post‐game saliva caffeine levels. This may contribute to the observed 3.5 h delay in time at sleep onset and the 1.5 h reduction in sleep duration on the night of the game. This study highlights the need for a strategic approach to the use of caffeine within a Super Rugby team considering the potential effect on post‐game sleep.

Technological advances in sleep monitoring have seen an explosion of devices used to gather important sleep metrics. These devices range from instrumented ‘smart pyjamas’ through to at-home polysomnography devices. Alongside these developments in sleep technologies, there have been concomitant increases in sleep monitoring in athletic populations, both in the research and in practical settings. The increase in sleep monitoring in sport is likely due to the increased knowledge of the importance of sleep in the recovery process and performance of an athlete, as well as the well-reported challenges that athletes can face with their sleep. This narrative review will discuss: (1) the importance of sleep to athletes; (2) the various wearable tools and technologies being used to monitor sleep in the sport setting; (3) the role that sleep tracking devices may play in gathering information about sleep; (4) the reliability and validity of sleep tracking devices; (5) the limitations and cautions associated with sleep trackers; and, (6) the use of sleep trackers to guide behaviour change in athletes. We also provide some practical recommendations for practitioners working with athletes to ensure that the selection of such devices and technology will meet the goals and requirements of the athlete.