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The Influence of Coaches and Support Staff on the Sleep Habits of Esports Athletes Competing at Professional and Semiprofessional Level
Abstract
The present study investigated the influence and perspective of esports coaches and support staff on the sleep habits of esports athletes competing at professional and semiprofessional levels. Eighty-four esports coaches and support staff from 19 countries completed an online questionnaire. The first section obtained demographic information. The second section evaluated sleep hygiene knowledge using the Sleep Beliefs Scale. The third section assessed sleep monitoring and sleep hygiene practices used by coaches and support staff with esports athletes, barriers to the use of these practices, and conditions that impact the sleep of esports athletes. Overall, sleep hygiene knowledge was inadequate (<75%, based on the study of Miles et al.). Sleep monitoring frequency was low (48.8%), while sleep hygiene practices were implemented more often (66.7%). The most common barrier to sleep monitoring and sleep hygiene practices was players not liking it (50% and 46.3%, respectively). Night competitions (64.6%), congested competition times (51.2%), and night training schedules (47.6%) all rated highly as having an impact on esports athletes’ sleep. Sleep education and training for coaches and support staff in the optimal use of sleep monitoring and sleep hygiene practices may increase the frequency and quality of sleep health support provided to esports athletes.
... Sleep monitoring and practices additionally play a significant role in the practice of esports, as a recent study found that esports athletes reported a high impact on sleep due to night competitions and night training schedules. The same study found it plausible that like traditional athletes increased arousal levels and evening light exposure could interfere with the sleep of esports athletes (Bonnar et al., 2023). Furthermore, sleep characteristics in esports players and in-game performance association have been investigated, as esports players with better performance spend an average of 55 more minutes on sleep compared with esports players with poor in-game performance (Moen et al., 2022). ...
... Therefore, it cannot be argued whether sleep practicing should be implemented. Nevertheless, 40% of players do not like sleep-monitoring practices, which adds complexity to the debate (Bonnar et al., 2023). ...
Electronic sports (esports) refer to competitive video gaming at professional and amateur levels. The increasing popularity of esports may lead to an increased tendency toward inactivity and sedentary behavior among players. Currently, 150 min of physical activity (PA) of moderate to high intensity per week is recommended to main a healthy lifestyle. The aim of this study was to investigate whether young esports players are offered to participate in PA and what type of PA they would like to participate in. The level of PA, bodily pain, and sleeping habits were also investigated through a self-reported questionnaire. The median score for PA was 2,850 metabolic equivalent of task minutes per week. One in every five esports players was offered PA by their esports association, and most of them have used this offer. For participants who were not offered PA, the most often called-for type of PA was resistance training, ballgames, and cardiovascular training.
... Compared to casual gaming, esports requires greater cognitive demand and psychophysiological stress (Leis & Lautenbach, 2020;Palanichamy et al., 2020). In addition, some professional esports athletes now have access to better health and wellness resources as well as coaching which has been shown to improve lifestyle behaviors such as sleep habits and reduced stress (Bonnar et al., 2023;Leis et al., 2023). To accommodate the differences in stress, resources, and demand, esports athletes might have different lifestyle behaviors than casual gamers and should be examined separately (Garg et al., 2013;McNulty et al., 2023;Toth et al., 2020). ...
... Another explanation could perhaps be due to the fact that esports athletes on a team or club have more available resources than ever before (Cooke, 2023;Leporati, 2022;Marshall, 2017). Indeed, professional and amateur esport affiliations are hiring dedicated coaches and trainers to oversee health and performance among their esports athletes (Abbott et al., 2022;Bonnar et al., 2023;Leporati, 2022;Marshall, 2017). In addition, there seems to be increased awareness of musculoskeletal injuries and "gamer fatigue" associated with long, competitive gaming sessions and lifestyle behaviors (Baena-Riera et al., 2023;Forman & Holmes, 2023;Leporati, 2022;Marshall, 2017;McNulty et al., 2023;Pereira et al., 2022;Rossoni et al., 2023). ...
Literature and governing agencies refer to gamers who partake in esports as “esports athletes,” and research suggests that exercise may be a beneficial component of esports training. Yet esports athletes are stereotyped similarly to casual gamers, for example, sedentary and not physically active. The purpose of this research was to compare physical activity and sedentary behavior between esports athletes on a team or club and casual gamers. Data were collected via an online survey ( N = 532 total; n = 172 women). The survey assessed physical activity behaviors (i.e., International Physical Activity Questionnaire), time spent playing games, and esports affiliation. Independent samples t tests and analysis of variance were used for comparisons. Esports athletes on a team or club reported significantly more ( F = 67.99, p < .001) physical activity (5,706 ± 4,558 metabolic equivalent min/week) compared to casual gamers (2,738 ± 2,792 metabolic equivalent min/week). There was a significant interaction between the effects of gender and group ( F = 5.680, p = .018) on vigorous physical activity. Esports athletes on a team or club also reported significantly less ( F = 77.436, p < .001) sedentary behavior compared to casual gamers. There was no reported difference in time spent playing video games between groups ( t = 1.416, p = .157). In conclusion, esports athletes on a team or club were more physically active and less sedentary than their casual counterparts.
... In two studies, 49%-53% of esports athletes reported experiencing a sleep disturbance (i.e., sleep initiation, maintenance, or early awakening) the night before competition within the last 12 months (Bonnar et al., 2022;Lee et al., 2021). These findings were later supported by another study, which found that coaches and support staff working with esports athletes rated night competitions and congested competition times as having an impact on the sleep of esports athletes (Bonnar et al., 2023). Comparatively, in the sports science literature, not all studies have found an impact of competition on traditional athletes' sleep (Roberts et al., 2019), although some studies have (Erlacher et al., 2011;Lastella et al., 2014). ...
... Notably, Lee et al. (2021) and Bonnar et al. (2022) did not prospectively measure sleep behavior around competition in their studies and, instead, used a single-item retrospective question, which is prone to recall bias (Mallinson et al., 2019). Furthermore, in the subsequent study by Bonnar et al. (2023), coaches and support staff provided indirect evidence of an effect of competition on esports athletes' sleep. Hence, the impact of competition on the sleep of esports athletes remains to be established using more robust study designs. ...
The overall aim of the present study was to examine the daily patterns and relationships between sleep behavior, anxiety, mood (i.e., depression symptoms) and cognitive performance (i.e., reaction time) in esports athletes competing in an Oceanic Rocket League Championship Series regional event. Sixteen participants completed a daily sleep diary, evening anxiety measure, and an afternoon mood measure and cognitive performance task. Measures were taken (i) pre-competition), (ii) across the competition days, and (iii) post-competition. We found that participants’ lights out time was earliest across the competition nights. Sleep onset latency gradually lengthened pre-competition and across the competition nights, eventually exceeding normal limits. Wake after sleep onset was longest across the competition nights but remained within normal limits. Wake-up time was earliest at the start of the competition period but consistently late on most other days. Total sleep time was generally adequate but mildly reduced the night before the first day of competition. There was no significant relationship between anxiety and subsequent sleep, nor a relationship between total sleep time and next day mood or cognitive performance. Future research should investigate whether these findings generalize to esports athletes from other games, at higher levels of competition, and different start times.
... video gaming (Lawley et al., 2019). The cardiovascular sequelae in esports have been hypothesized to be attributed to various factors, including sleep deprivation, psychological stress, altered arterial stiffness, hypertension, and changes in HR variability (HRV); these are among the proposed mechanisms (Bennett et al., 2022;Bonnar et al., 2023;Moen et al., 2021;Sanz-Milone et al., 2021;Yamagata et al., 2022). In addition, the extended periods of sitting during the esports competitions may contribute to cardiovascular concerns related to water retention and deep venous thrombosis (Chang et al., 2013;Rambaran & Alzghari, 2020;Schmidt et al., 2022). ...
Esports is a global competitive phenomenon in which gamers and spectating enthusiasts engage in virtual playing competition. The growth of esports has fostered so much prominence that the establishment of amateur intercollegiate competition has taken place across the United States. Numerous institutions have sanctioned esports teams and have welcomed players as student-athletes within athletics departments. Positioned as the recipient to a remarkable boom in global esteem, the appeal of esports has stimulated exponential growth in commercial value, patronage, and societal acceptance. Scholars have since assessed the entwining of the world of sport with competitive gaming, sparking debate arguing whether esports is an admissible form of sport, and its participants credited as athletes eligible for intercollegiate athletic scholarships. In this literature overview—perspective article—we present characteristics of mainstream allure, operational terminology, and fitness of participants to render the status of esports to be, or, not to be, a collegiate sport. It is this multidisciplinary point of analysis from which the authors conclusion is supplicated. While esports currently do not satisfy the philosophical principles from which sport is characterized, growing acceptance, economic value, and alternative exhibitions of athleticism suggests the prospective of the industry’s future embrace.
... Such an approach has already shown numerous advantages in improving health parameters and academic performance in adolescents [101] and may represent a future step to integrate sleep hygiene education in extensive gamers (e.g., esports athletes) and their coaches. Indeed, though coaches and support staff play an essential role in ensuring the overall well-being of esports athletes, a recent study highlighted their general under-knowledge of sleep hygiene [102]. ...
... A few studies report adequate sleep duration (53,54), while others do not (55,56). A recent study reported that esports coaches have suboptimal sleep hygiene knowledge, suggesting that esports coaches need more competence on how to monitor and advise their players for optimal sleep routines (57). ...
Aim
The current study aimed to explore grassroots esports in sports clubs in Norway from the perspective of volunteer esports leaders.
Method and results
Fifteen volunteers were recruited from grassroots esports initiatives in various sports clubs and were interviewed via online video conferencing using a pre-developed semi-structured interview guide. Data was analyzed using inductive thematic analysis with a realist approach, which generated the following themes: (1) Local community impact at the center of motivation, (2) lack of support threatens the operations of the initiatives, and (3) competency development to overcome barriers. The participants perceived the grassroots esports initiatives as essential for children in the local community and as the core of their motivation as volunteers. Several challenges were mentioned for sustaining the initiatives, such as maintaining motivation, resource management, and recruiting new volunteers. Finally, competency and qualified esports trainers were mentioned as necessary for a high-quality offer.
Conclusion
The grassroots esports initiatives in sports clubs are viewed by volunteer esports leaders to affect the local community positively. However, there are challenges tied to the operation of such initiatives, such as engaging volunteers and raising competence. Future research should investigate barriers to help develop strategies to support grassroots esports initiatives.
Introduction: Esports have evolved from unorganized activities into hyper-competitive and professionalized settings. Esports share similarities with professional sports where individuals and teams strive for optimal performance. The purpose of our paper is to systematically review and integrate the fast-growing research on individual and team effectiveness in gaming and esports. To the best of our knowledge, we provide the first systematic review of research on gaming and esports effectiveness.
Research Question: What are the individual, team, and organizational/environmental factors that are associated with effectiveness in gaming and esports?
Methodology: We leveraged a systematic literature review approach and conducted a structured keyword search in Web of Science, Google Scholar, and EBSCO. The sample was completed using forward-backward tracking. The resulting sample consists of 180 articles after full-text screening.
Results: Within our full paper we will leverage the input-mediator-outcome-input (IMOI) model to synthesize the existing findings on the multilevel factors that shape individual and team effectiveness in gaming and esports. In doing so, we will integrate previous findings from across the individual, team, and organizational/environmental levels into outcomes (e.g., win/loss ratio and prize money winnings), mediators (e.g., team cohesion and communication), and inputs (e.g., individual athlete skills, team compositional variables). Building on our integration, we
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will discuss blind spots and contradicting findings within this model, and outline an agenda for future research.
Implications: Scholars can leverage our work by systematically targeting the identified blind spots and contradicting findings that exist within the literature. Practitioners will find value in focusing on factors shown to positively impact effectiveness within this setting.
Coaching behaviours often derive from sporting traditions, instinct and previous experiences. Practitioners tend to follow traditional, inherited methods rather than adopt new evidence-based approaches associated with athlete development. This article reviews literature relating to theoretical constructs of a novel coach education framework (CEF) developed by the Irish Rugby Football Union. The three constructs included are: self-determination theory (SDT), explicit learning theories (ELT) and implicit learning theories (ILT). A total of 82 publications met the inclusion criteria (SDT: n = 18, ELT: n = 28, ILT: n = 36). This review supports the efficacy of these constructs in isolation for promoting effective coaching practices and provides a justification for future implementation of the framework and its evaluation. This framework may have the potential to address a shortfall in current coach education formats, which have traditionally focused on What content should be used for athlete development as opposed to How practitioners can coach more effectively.
While scientific interest in electronic sports (esports) is steadily growing, there remains an absence of research evidence concerning training practices in specific esports such as League of Legends. Anecdotal evidence suggests that current approaches to training may be suboptimal in terms of performance and, concerningly, linked to negative consequences for player health and well-being. In order to address the lack of literature and aid understanding of the (in)effectiveness of current training practices in esports, our study sought to qualitatively examine the experiences and perceptions of training in a sample of professional and semiprofessional League of Legends players. Through interviews with 10 players who ranked in the top 0.24% of the playing population, three core themes were identified: (a) the state of training, (b) training experiences, and (c) motivational change. This study provides important insights into current training practices in esports and players’ perceptions of the (in)effectiveness of these practices. The paper concludes with practical recommendations for coaches and support staff working in esports.
Athletes display differing sleep habits to non-athletic populations; similarly, differences occur in sleep habits between athletes from different sports. There is currently limited research investigating the differences in sleep habits and behaviors between different levels of competition within the same sport. A total of 224 rugby union athletes (109 academy, 38 semi-professional, 84 professional) completed the Athlete Sleep Behavior Questionnaire and the Pittsburgh Sleep Quality Index. Professional athletes displayed a significantly longer self-reported sleep duration compared to semi-professional and academy athletes (7 h 52 min ± 51 min vs. 7 h 16 min ± 1 h 15 min vs. 7 h 19 min ± 1 h 12 min, p < 0.01). Pittsburgh Sleep Quality Index global scores revealed a significantly lower (p = 0.04, d = 0.3) score for professional athletes (5.2 ± 2.5 AU) than academy athletes (6.0 ± 2.7 AU). Individual components of the Pittsburgh Sleep Quality Index revealed significant differences (p < 0.05) between groups for sleep duration and daytime dysfunction. No significant differences (p > 0.05) were observed between levels of competition for the Athlete Sleep Behavior Questionnaire global score; however, significant differences (p < 0.05) were observed for 6 of the 18 items. This study was the first to investigate sleep behaviors across multiple levels of competition in rugby union athletes. Professional athletes displayed longer sleep duration compared to semi-professional and academy level athletes. Additionally, results highlighted that differences exist between levels of competition for specific sleep behaviors. This study identified that sleep behaviors could be improved for all levels of rugby union athletes.
The popularity of electronic sports (esports) has increased over the last decade, and knowledge has been shared between sports and esports. Yet, research on esports coaching remains conspicuously absent. From this position, sport coaching researchers and practitioners lack an evidenced base to inform their critical consideration of esports coaching. In response, this study describes the experiences and contexts of 14 head coaches in professional teams competing in “League of Legends”. Analysis identified themes including; 1) uncodified career and education pathways for coaches; 2) coaches practice by a review-plan-do cycle shaped by the pressure to win; 3) coaches practice in a complex, technological and global environment; and 4) coaches practice amongst challenges and paradoxes. The findings present an original analysis of esports coaching and provide a platform for sport coaching researchers and practitioners to critically consider the relevance, development, practice and context of esports coaching in relation to their own work.
Light is necessary for human health and well-being. As we spend more time indoors, we are being increasingly exposed to artificial light. The development of artificial lighting has allowed us to control the brightness, colour, and timing of our light exposure. Yet, the widespread use of artificial light has raised concerns about the impact of altering our light environment on our health. The widespread adoption of personal digital devices over the past decade has exposed us to yet another source of artificial light. We spend a significant amount of time using digital devices with light-emitting screens, including smartphones and tablets, at close range. The light emitted from these devices, while appearing white, has an emission spectrum with a peak in the blue range. Blue light is often characterised as hazardous as its photon energy is higher than that of other wavelengths of visible light. Under certain conditions, visible blue light can cause harm to the retina and other ocular structures. Blue light can also influence the circadian rhythm and processes mediated by melanopsin-expressing intrinsically photosensitive retinal ganglion cells. While the blue component of sunlight is necessary for various physiological processes, whether the low-illuminance artificial blue light emitted from digital devices presents a risk to our health remains an ongoing area of debate. As technological advancements continue, it is relevant to understand how new devices may influence our well-being. This review examines the existing research on artificial blue light safety and the eye, visual performance, and circadian functions.
This study evaluated a brief sleep intervention designed to improve the sleep, mood, and cognitive performance of professional electronic sports (esports) athletes from three major esports regions (i.e., Asia, North America, and Oceania). Fifty-six esports athletes from South Korea (N = 34), the United States (N = 7), and Australia (N = 15) completed the study. Participants completed an initial 2-week pre-intervention phase to establish a baseline, followed by a 2-week intervention phase that involved a group sleep education class, 1:1 session with a trained clinical psychologist, and daily biofeedback. A wrist activity monitor and daily sleep diary were used to monitor sleep during both phases, while at pre- and post-intervention, participants completed a battery of sleep and mood questionnaires and underwent cognitive performance testing. Sleep knowledge increased from pre- to post-intervention (d = 0.83 [95% CI −1.21, −0.43], p =< 0.001), while there were modest improvements in sleep diary estimates (i.e., sleep onset latency (Mdiff = −2.9 min, p = 0.02), sleep onset time (Mdiff = −12 min, p = 0.03), and sleep efficiency (Mdiff = 1.1%, p = 0.004)) and wrist activity monitor estimates (i.e., sleep onset time (Mdiff = −18 min, p = 0.01)). Insomnia severity scores decreased significantly (d = 0.47 [95% CI 0.08, 0.84], p = 0.001), while sleepiness scores increased but not meaningfully (d = 0.23 [95% CI −0.61, 0.14], p = 0.025). However, there was no significant change in mood (i.e., depression and anxiety) or cognitive performance scores (i.e., mean reaction time or lapses). Sleep interventions for esports athletes require further investigation. Future research should examine whether a stepped-care model, whereby increasing therapeutic input is provided as needed, can optimize sleep, mood, and cognitive performance outcomes.
Young athletes must contend with the constraints of elite sports on top of school commitments and the physiological processes associated with adolescence. This study assessed week and weekend sleep and schedule of activities in elite adolescent rugby players during the in‐season competitive phase compared with age‐matched non‐athlete controls. 32 adolescents (GR: 16 elite rugby players, GC: 16 controls) from the same boarding school filled out a daily schedule of activities and a sleep diary, and wore a multichannel electroencephalogram for 14 days. They later filled out questionnaires on their sleep quality, sleepiness, and perceived stress. Both groups showed insufficient sleep duration during the week (<7 h). Only GC caught up on their sleep debt during the weekend (increased TIB, TST and time spent in REM sleep, all p < 0.001). Weekend TIB, TST and, N3 sleep remained similar to that for weekdays in GR. However, GR experienced lower sleep quality (decreased SE, increased WASO, all p < 0.01) and a decrease in REM sleep ( p < 0.01). Schedules of activities showed an increase in time spent on overall activities during the weekend, mainly due to competition and sport‐specific travel, which resulted in a decrease in sleep opportunity time compared with GC ( p < 0.001). Δ sleep opportunity time (weekend‐week) was associated with Δ TST (weekend‐week), and Δ TST (weekend‐week) was associated with sleepiness and perceived stress. Busy schedules during the competitive season decreased sleep opportunity time and prevented elite adolescent rugby players from catching up on their sleep at weekends.
HIGHLIGHTS
Adolescent rugby players have insufficient sleep during both week and weekend of the in‐season competitive phase
Congested schedule prevented elite adolescent rugby players from catching up on their sleep at weekends.
Sleep considerations are necessary when planning the weekend sporting schedules
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.
Study Objectives
To synthesise original articles exploring the effects of sleep restriction on cognitive performance specifically for Elite Cognitive Performers; i.e. those who engage in cognitively demanding tasks with critical or safety-critical outcomes in their occupation or area of expertise.
Methods
Backward snowballing techniques, grey literature searches, and traditional database searches (Embase, MEDLINE, Web of Science, Google Scholar, PSYCinfo, and SportDiscus) were used to obtain relevant articles. A quality assessment was performed, and risk of training effects was considered. Results were narratively synthesised. Fourteen articles fit the criteria. Cognitive outcomes were divided into three categories defined by whether cognitive demands were ‘low-salience’, ‘high-salience stable’, or ‘high-salience flexible’.
Results
Low-salience tests (i.e., psychomotor vigilance tasks & serial reaction tests), mainly requiring vigilance and rudimentary attentional capacities, were sensitive to sleep restriction, however this did not necessarily translate to significant performance deficits on low-salience occupation-specific task performance. High-salience cognitive outcomes were typically unaffected unless when cognitive flexibility was required.
Conclusions
Sleep Restriction is of particular concern to occupations whereby individuals perform (a) simple, low-salience tasks or (b) high-salience tasks with demands on flexible allocation of attention and working memory, with critical or safety-critical outcomes.
Background and Objective Although sleep is a potentially important determinant of performance in esports, there have been no published data on the sleep behavior of professional esports athletes. The aim of this study is to investigate sleep aspects and sleep risk factors in esports athletes. Methods Thirty-four esports athletes were compared with 21 nonathletes from the general population to assess their sleep patterns and mood. Study 1 is a quantitative study with a 2-week observation period of sleep that was performed after evaluating insomnia severity, daytime sleepiness, sleep knowledge, and mood state. During the sleep observation period, participants recorded sleep diaries. In study 2, qualitative research was conducted with in-depth interviews from 6 participants. Results The esports athlete group reported significantly delayed sleep phase compared to the nonathlete group (d = 2.10 hours, p < 0.001). The esports athlete group reported significantly lower sleep quality and scores for feeling refreshed upon awakening, higher depression scores and significantly higher proportion of individuals with clinical symptoms of depression compared to the nonathlete group (ps < 0.01). In study 2, six themes emerged from the interviews: sleep risk factors, sleep protective factors, lifestyle, stressors, organizational management, and demands for sleep/psychological intervention. Conclusions The professional esports athletes showed more depressed mood and more delayed sleep phase compared to the non-athletes. A wide range of interventions tailored to esports athletes should be developed and implemented on both individual and organizational levels.
Study Objectives
Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We therefore tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG).
Methods
In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three non-wearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG.
Results
Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18-0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep.
Conclusions
Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.
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).
The number of video game and eSports players is steadily rising. Since little is known about their health behavior to date, the present study examines the demographics and health behavior of video game and eSports players. In this cross-sectional study, data on demographics, health status, physical activity, nutrition, sleep, and video game usage were assessed via a web-based survey of n = 1066 players (91.9% male; 22.9 ± 5.9 years; body mass index (BMI): 24.6 ± 4.8 kg/m 2) in Germany in 2018. The majority of respondents (95%) reported a good to excellent health status. Two thirds (66.9%) engaged in moderate to vigorous physical activity for more than 2.5 h/week. The average duration of sitting and sleep time was 7.7 ± 3.6 h/day and 7.1 ± 1.3 h/day, respectively. Mean fruit and vegetable consumption was 2.7 ± 1.8 portions/day. Video games were played for 24.4 ± 15.9 h/week on average. Partial Spearman correlations revealed poor positive associations of video game play time to sedentary behavior (rho = 0.15; p < 0.01) and BMI (rho = 0.11; p < 0.01), as well as a poor negative association to self-reported health status (rho = −0.14; p < 0.01). These results indicate the good subjective health of this target group. Nevertheless, the high amount of video game play time and its poor negative association to health status indicate a need for specific health promotion strategies for this target group.
Competitive gaming, better known as electronic sports (esports), is rapidly growing in popularity. We systematically reviewed the available literature regarding the psychological aspects of esports using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) evidence-based reporting checklist and a Population, Intervention, Comparator, and Outcomes (PICO) framework with the following inclusion criteria: (i) published between 1994 and 2018; (ii) empirical investigation (as the current state of research is dense with positions and opinions but has few empirical investigations); and (iii) focussed on esports games that are associated with either cognitive performance or game performance. The goal of our research was twofold: to present a summary of the empirical evidence addressing the psychological characteristics of both cognitive and game performance in esports, and to integrate esports in the field of sport psychology. More specifically, our goals were to highlight the interplay of psychological aspects of performance and esports and to clearly define the theoretical foundations of the psychological aspects of esports performance. Underlining the differences from video gaming will inform future research directions and stimulate the development of high-quality practice in the applied field of sports and exercise psychology.
Esports is a booming global industry and has been officially included in the lead-up to the 2020 Olympics in Tokyo. Given that esports is a cognitive based activity, and sleep is well known to be critical for optimal cognitive functioning, our research group recently proposed that sleep might be an important determinant of esports performance. The focus of the current review was to expand our limited understanding regarding the role of sleep in esports by exploring risk factors for suboptimal sleep and developing an associated intervention framework. More specifically, we aimed to 1) examine how gaming culture and game genre might negatively influence sleep behaviour, 2) describe a conceptual model to explain how sub-optimal sleep occurs in esports, and 3) outline sleep intervention considerations that specifically meet the needs of esports athletes. We conclude that gaming culture and game genre could both impact the sleep behaviour of esports athletes, via cognitive and behavioural mechanisms. Furthermore, adapting Spielman’s three-factor model to esports may provide a useful and easy to understand conceptualisation for sub-optimal sleep in esports. Lastly, sleep interventions for traditional athletes can be suitably modified for esports but must be comprehensive and extend from a theoretically grounded conceptual model.
Purpose
The sleep diary is the gold standard of self-reported sleep duration, but its comparability to sleep questionnaires is uncertain. The purpose of this study was to compare self-reported sleep duration between a sleep diary and a sleep questionnaire and to test whether sleep-related disorders were associated with diary-questionnaire differences in sleep duration.
Participants and methods
We compared self-reported sleep duration from 5,432 questionnaire-sleep diary pairs in a longitudinal cohort of 1,516 adults. Participants reported sleep information in seven-day sleep diaries and in questionnaires. Research staff abstracted average sleep durations for three time periods (overall; weekday; weekend) from diaries and questionnaires. For each time period, we evaluated diary-questionnaire differences in sleep duration with Welch's two-sample t-tests. Using linear mixed effects regression, we regressed overall diary-questionnaire sleep duration difference on several participant characteristics: reporting any insomnia symptoms, having sleep apnea, sex, body mass index, smoking status, Short Form-12 Physical Health Composite Score, and Short Form-12 Mental Health Composite Score.
Results
The average diary-reported overall sleep duration (7.76 hrs) was longer than that of the questionnaire (7.07 hrs) by approximately 41 mins (0.69 hrs, 95% confidence interval: 0.62, 0.76 hrs). Results were consistent across weekday- and weekend-specific differences. Demographic-adjusted linear mixed effects models tested whether insomnia symptoms or sleep apnea were associated with diary-questionnaire differences in sleep duration. Insomnia symptoms were associated with a 17 min longer duration on the diary relative to the questionnaire (β=0.28 hrs, 95% confidence interval: 0.22, 0.33 hrs), but sleep apnea was not significantly associated with diary-questionnaire difference. Female sex was associated with greater diary-questionnaire duration differences, whereas better self-reported health was associated with lesser differences.
Conclusion
Diaries and questionnaires are somewhat disparate methods of assessing subjective sleep duration, although diaries report longer duration relative to questionnaires, and insomnia symptoms may contribute to greater perceived differences.
To examine the cognitive and physical changes associated with consuming an energy drink concurrent to video gaming, we examined a convenience sample of nine elite League of Legends (LoL) e-sport players (21 ± 2 y, BMI 25.6 ± 3.4 kg/m 2) consuming an energy drink (Reload TM) or placebo (Placebo) in a randomized, double-blind, placebo-controlled cross-over trial. Participants completed the same test battery prior to treatment consumption and after playing each of three competitive LoL games. Primary outcomes included measures of attention (Erikson Flanker Test), reaction time (Go/No-Go test) and working memory (n-back test). Secondary outcomes examined fatigue (hand grip strength and finger tap speed). Statistical analysis was performed by repeated-measures analysis of variance (RM-ANOVA) and reported as the mean (standard deviation [SD]) or mean change (95% confidence interval [CI]). Participants reported sleeping 8.1 (1.2) h/night, playing LoL 10.3 (2.1) h/d, playing other video games 1.8 (2.8) h/d, and exercising 4.2 (1.7) times per week. Overall, we observed no significant time, group, or group-by-time interactions for any measured performance index with the exception of a significant improvement for the n-back test, where the Reload group demonstrated a significant within-group improvement: Reload [−171 ms (95% CI, −327.91, −14.09), p < 0.004], Placebo [−92 ms (95% CI, −213.63, 29.63)]. However, no between-group differences were noted (38.50 ms, 95% CI, −141.89, 64.89, p = 0.803). Our findings suggest that elite eSport athletes do not demonstrate a mental or physical improvement in performance relative to the treatment supplement or indices measured in this study.
Over the last decade, Esports, defined as a form of organized video game competition, has emerged as a global phenomenon. The professional players who compete in Esports, namely, Eathletes, share many similarities with their traditional athlete counterparts. However, in sharp contrast to traditional athletes, there is a paucity of research investigating the factors that influence the performance of Eathletes. This gap in the literature is problematic because Eathletes are unable to make informed and empirically supported decisions about their performance management, unlike traditional athletes. Sleep is an important factor that influences athletic performance in traditional sports, particularly those that require a high level of cognitive demand. Research is yet to examine whether sleep also plays an important function in optimal performance and success of Eathletes in Esports. Accordingly, the aim of this opinion piece is to review the broader sleep and sports medicine literature and provide theoretically grounded suggestions as to how existing findings may apply to Eathletes competing professionally in Esports. Overall, it appears that Eathlete performance may be vulnerable to the deleterious effects of sleep restriction. Furthermore, Eathletes are likely at risk of sleep disturbances due to the unique situations and conditions that characterize Esports.
It is increasingly recognised that many athletes have poor sleep quantity and/or quality despite the advances in knowledge regarding the importance of sleep for an athletic population. The majority of research in sleep assessment and treatment (within the general population) focuses on the medical disorder insomnia, and therefore may not be specifically relevant for athletes. Further, there are currently no guidelines for the standardisation of assessment, intervention, feedback and behaviour change strategies in athletes. This review outlines potential reasons for sleep disturbances in athletes, advantages and disadvantages of a range of methods to assess sleep (polysomnography, activity monitoring, consumer sleep technology, sleep diaries and questionnaires), considerations for the provision of feedback, a description of potential interventions and behaviour change challenges and strategies. The objective of this review is to provide practitioners with the latest scientific evidence in an area rapidly progressing in awareness, consumerism and athlete engagement.
The aim of the current study was to evaluate the effect of personalized sleep hygiene education on sleep indices in elite athletes. Nine elite male cricket players performed 3 weeks of baseline sleep monitoring (PRE), followed by group and individualized sleep hygiene education and a further 3 weeks of sleep monitoring (POST). Subjective sleep questionnaires included the Athlete Sleep Behaviour Questionnaire (ASBQ), the Epworth Sleepiness Scale (ESS) and the Pittsburgh Sleep Quality Index (PSQI). Objective sleep indices were monitored via wrist actigraphy. There were significant improvements (p < 0.05) in two of the sleep questionnaires (ESS and PSQI) and in sleep efficiency (+5%), sleep latency (−29 min) and sleep onset variance (−28 min) following the intervention, all associated with large or very large effect sizes (d= 1.38, −0.85 and −0.88, respectively). The current study reports that personalized sleep hygiene education using the ASBQ to target maladaptive sleep behaviours may be effective in acutely improving sleep indices in elite male athletes.
Objectives:
The primary aims of the present study were to assess the sleep hygiene knowledge of high performance team sport coaches and sports science support staff; the sleep practices these individuals implement with athletes; and the barriers to the more frequent use of these practices.
Design:
Cross-sectional observational study.
Methods:
A sample of 86 Australian coaches and sports science support staff working within high performance team sport volunteered to complete a four-part questionnaire, including the Sleep Beliefs Survey used to assess sleep hygiene knowledge.
Results:
Overall sleep hygiene knowledge was adequate (15.3±2.9, score range 0-20; mean±SD), however knowledge of sleep-wake cycle behaviours (score 4.9±1.6 out of 7) and thoughts and attitudes about sleep (3.6±1.0 out of 5) were inadequate. Over half (56%) of coaches and support staff had monitored athlete sleep, while 43% had promoted sleep hygiene. Lack of resources (response range 44-60%) and knowledge (16-41%) were the two main barriers to the implementation of sleep monitoring and sleep hygiene practices.
Conclusions:
Team sport coaches and sports science support staff have adequate overall sleep hygiene knowledge, yet some specific areas (e.g. sleep-wake cycle behaviours) warrant improvement. There appear to be limited sleep practices implemented with athletes, particularly regarding the promotion of sleep hygiene. The development of educational sleep resources for coaches and support staff to implement with athletes may help address the identified barriers and improve sleep knowledge.
Objectives
To characterise the sleep of elite athletes and to identify factors associated with training and competition that negatively affect sleep.
Design
Prognosis systematic review.
Data sources
Three databases (PubMed, SCOPUS and SPORTDiscus) were searched from inception to 26 February 2018.
Eligibility criteria for selecting studies
Included studies objectively reported total sleep time (TST) and/or sleep efficiency (SE) in elite athletes. Studies were required to be observational or to include an observational trial.
Results
Fifty-four studies were included. During training, many studies reported athletes were unable to achieve TST (n=23/41) and/or SE (n=16/37) recommendations. On the night of competition, most studies reported athletes were unable to achieve TST (n=14/18) and/or SE (n=10/16) recommendations. TST was shorter (60 min) the night of competition compared with previous nights. SE was lower (1%) the night of competition compared with the previous night. TST was shorter the night of night competition (start ≥18:00; 80 min) and day competition (20 min) compared with the previous night. SE was lower (3%–4%) the night of night competition but unchanged the night of day competition compared with previous nights. Early morning training (start <07:00), increases in training load (>25%), late night/early morning travel departure times, eastward air travel and altitude ascent impaired sleep.
Conclusion
Athletes were often unable to achieve sleep recommendations during training or competition periods. Sleep was impaired the night of competition compared with previous nights. Early morning training, increases in training load, travel departure times, jet lag and altitude can impair athletes’ sleep.
PROSPERO registration number
CRD42017074367.
Whilst the effects of sleep loss on performance have previously been reviewed, the effects of disturbed sleep on recovery following exercise are less reported. Specifically, the interaction between sleep and physiological and psychological recovery in team-sport athletes is not well understood. Accordingly, the aim of the present review is to examine the current evidence of sleep and the potential role it may play in post-exercise recovery, with a tailored focus on professional team-sport athletes. Recent studies show that team-sport athletes are at high risk of poor sleep during and following competition. Although limited published data is available, these athletes also appear particularly susceptible to reductions in both sleep quality and duration following night competition and periods of heavy training. However, studies examining the relationship between sleep and recovery in such situations are lacking. Indeed, further observational sleep studies in team-sport athletes are required to confirm these concerns. Naps, sleep extension and sleep hygiene practices appear advantageous to performance; however, future proof of concept studies are now required to determine the efficacy of these interventions on the post-exercise recovery. Moreover, more research is required to understand how sleep interacts with numerous recovery responses within team-sport environments. This is pertinent given the regularity at which these teams encounter challenging scenarios during the course of a season. Therefore, this review will examine the factors that compromise sleep during a season and following competition, and discuss strategies which may help improve sleep in team-sport athletes.
The Sleep Hygiene Index was developed to assess the practice of sleep hygiene behaviors. The Sleep Hygiene Index was delivered to 632 subjects and a subset of the subjects participated in a readministration of the instrument. Test-retest reliability analyses suggested that sleep hygiene behaviors are relatively stable over time for a nonclinical population. Results confirmed that sleep hygiene is strongly related to sleep quality and modestly related to perceptions of daytime sleepiness. As predicted, support of the sleep hygiene construct was also provided by strong correlations with the associated features of a diagnosis of inadequate sleep hygiene. The Sleep Hygiene Index, a much shorter sleep hygiene instrument than previously published, demonstrated comparable psychometric properties with additional evidence of validity and a clear item selection rationale.
Organized electronic-sport competitions (e-Sport) is related to several health problems, including sleep disorders. The objective of this study was to evaluate the characteristics of the sleep-wake cycle of League of Legends (LoL) athletes during their pre-training, training, pre-competition, and competition routines. Twenty male elite LoL players completed the questionnaires related to sleep pattern (Pittsburgh Sleep Quality Index), sleepiness (Epworth Sleepiness Scale), and chronotype (Morningness–Eveningness Questionnaire), and they wore an actigraph for 7 days. Pre-training and pre-competition assessments were carried out by questionnaires (n = 20) and training and competition assessments by actigraph (n = 16). The chronotype that most Eathletes presented was a moderately evening type. They presented a poor sleep quality and were borderline for excessive daytime sleepiness. Sleep onset and offset times were significantly prolonged during the competition condition (t = 2.11, p < .05; t = 2.51, p < .05). Correlations showed a relationship between PSQI and Sleepiness in the pre-training and pre-competition conditions (r = 0.50, p = .02) and chronotype with sleep onset (r = 0.61, p = .01), total sleep time (r = 0.55, p = .02), and time awake (r = 0.49, p = .04) in the competition condition. Linear regression analysis indicated associations between the PSQI and sleepiness (25%; p = .02) during pre-training and pre-competition. During the competition there were associations between chronotype and sleep onset (37%; p = .01), chronotype and time awake (24%; p = .04), and chronotype and TST (30%; p = .02). In general, the findings support the conclusion that LoL athletes presented an altered sleep pattern during their training routines.
Objectives: Competition is related to psychophysiological stress responses and is a key aspect of esports. Yet, while competition may indeed have an impact on performance, little is known about competition-related psychophysical stress responses in esports. Accordingly, this review aims to investigate whether playing esports in competitive (and non-competitive) settings is related to psychological and/or physiological stress.
Design: A systematic literature review was performed. Study inclusion criteria included: assessment of psychological and/or physiological stress in esports, study of healthy individuals over 12 years of age, and published in peer-reviewed journals in English or German.
Method: The literature search comprised EBSCOhost, PubMed, and Web of Science up until August 2019. An additional search was performed on Science Direct, Google Scholar, and Sponet.
Results: Seventeen studies met inclusion criteria. In publications investigating the non-competitive setting, it can be assumed that merely playing esports games is unrelated to psychophysiological stress reactions. While three out of five studies on stress in competitive settings demonstrated no hormonal reaction, one study reported an increase in anxiety levels in winners as well as an increase cortisol levels from baseline to postgame conditions, and two studies found an activation of the sympathetic nervous system. Overall, the studies revealed theoretical and methodological limitations, which are discussed in the present review.
Conclusions: Although the existing literature contributes to an initial understanding of psychophysiological stress in esports, further in-depth studies of stress responses in actual competition are needed.
Insufficient sleep has been argued to result in deleterious changes to mood in adolescents and offers promise as a modifiable risk factor. A systematic review of the literature regarding sleep duration and mood in adolescents was conducted using the academic databases PsycINFO, PubMed, Medline, Scopus, and EMBASE to identify relevant literature. Seventy-four studies, including 361,505 adolescents were sourced out of the 1534 references identified, 73 of which were appropriate for meta-analysis. Pooled results indicated that less sleep was associated with a 55% increase in the likelihood of mood deficits. Positive mood showed the largest relationship with sleep duration, followed by anger, depression, negative affect and anxiety. Effect sizes also varied according to study design, how sleep was operationalised, and geographical region, but not according to the inclusion of covariates. Sleep duration has a significant negative impact on a range of mood states in healthy adolescents. These effects were witnessed across all geographical regions, highlighting that sleep is a universal and modifiable risk factor for preventing mood deficits in this at-risk population.
Objectives:
Recent evidence indicates that adolescents' motivation to change sleep-wake patterns is low, despite significant impact of adolescent sleep problems on many areas of daytime functioning. The aim of the present study is to evaluate components of adolescents' motivation, and subsequent changes in behaviour.
Methods:
Fifty-six adolescents, aged 13-23 (M = 15.8 ± 2.3 y; 38% m) diagnosed with Delayed Sleep-Wake Phase Disorder (DSWPD) underwent three therapy sessions involving bright light therapy to phase advance sleep patterns. Adolescents were instructed to advance wake-up times by 30-min daily. Motivation ratings of desire, ability, reason, need and commitment to change sleep patterns were taken at baseline. Sleep diaries were taken at the end of treatment session 1, with sequentially earlier wake-up times in 30-min intervals indicating compliance.
Results:
At the outset of therapy, adolescents indicated strong desire, reasons and need, yet moderate ability and commitment to advance their sleep-wake patterns. Following therapy, sleep-onset times were significantly advanced, total sleep time increased and sleep latency decreased (all p < 0.05). Therapy lasted 6-27 days (M = 13.9 ± 4.5) and clients complied for approximately half the time (between 3 and 15 days; M = 8.8 ± 2.7). Commitment was associated with ability (r = 0.66, p < 0.001) but not desire, reason or need (all p > 0.05). Adolescents' desire to change (r = 0.30, p = 0.03) and commitment (r = 0.30, p = 0.03) were positively correlated with behaviour change, but their need, ability and reasons were not. A mediation analysis showed that ability and desire were important in predicting behaviour change, by total effects through commitment (ie, indirectly and directly).
Conclusion:
Our findings suggest that the total effects of ability (ie, confidence) and desire to change are the best predictors of behavioural changes, thus clinicians should focus on these components of the readiness to change model when undertaking treatments with sleep-disordered adolescents.
The advent of stepped-care and the need to disseminate cognitive behavioral therapy for insomnia (CBT-I) has led to novel interventions, which capitalize on non-specialist venues and/or health personnel. However, the translatability of these CBT-I programs into practice is unknown. This review evaluates the current state of CBT-I programs that are directly implemented in primary care and/or community settings. A literature search was conducted through major electronic databases (N = 840) and through snowballing (n = 8). After removing duplicates, 104 full-texts were extracted and evaluated against our initial inclusion criteria. Twelve studies including data from 1625 participants were subsequently evaluated for its study design and methodological quality. CBT-I program components varied across studies and included cognitive therapy (n = 6), relaxation (n = 7), sleep restriction therapy (n = 9), stimulus control therapy (n = 11) and sleep psychoeducation (n = 12). The respective interventions produced small-moderate post-treatment weighted effect sizes for the Insomnia Severity Index (0.40), Pittsburgh Sleep Quality Index (0.37), Sleep Efficiency (0.38), Sleep Onset Latency (0.38), and Wake time After Sleep Onset (0.46) but Total Sleep Time (0.10) did not reach statistical significance. While non-specialist community settings can potentially address the demands for CBT-I across clinical contexts, intervention heterogeneity precluded the full impact of the 12 CBT-I programs to be evaluated.
Objectives:
To improve well-being and performance indicators in a group of Australian Football League (AFL) players via a six-week sleep optimisation programme.
Design:
Prospective intervention study following observations suggestive of reduced sleep and excessive daytime sleepiness in an AFL group.
Methods:
Athletes from the Adelaide Football Club were invited to participate if they had played AFL senior-level football for 1-5 years, or if they had excessive daytime sleepiness (Epworth Sleepiness Scale [ESS] >10), measured via ESS. An initial education session explained normal sleep needs, and how to achieve increased sleep duration and quality. Participants (n = 25) received ongoing feedback on their sleep, and a mid-programme education and feedback session. Sleep duration, quality and related outcomes were measured during week one and at the conclusion of the six-week intervention period using sleep diaries, actigraphy, ESS, Pittsburgh Sleep Quality Index, Profile of Mood States, Training Distress Scale, Perceived Stress Scale and the Psychomotor Vigilance Task.
Results:
Sleep diaries demonstrated an increase in total sleep time of approximately 20 min (498.8 ± 53.8 to 518.7 ± 34.3; p < .05) and a 2% increase in sleep efficiency (p < 0.05). There was a corresponding increase in vigour (p < 0.001) and decrease in fatigue (p < 0.05).
Conclusions:
Improvements in measures of sleep efficiency, fatigue and vigour indicate that a sleep optimisation programme may improve athletes' well-being. More research is required into the effects of sleep optimisation on athletic performance.
Objectives: As major actors in sports activities, sports coaches can play a significant role in health education and contribute to the psychological well-being of young people. However, not all participants in sports activities experience sports positively, which reduces the potential benefits for health. The present study investigates if coaches’ efforts to promote health increase young athletes’ enjoyment, self-esteem and perceived health in daily life and decrease sport dropout.
Design: To control for the variability between teams and between clubs, multilevel modeling was applied.
Methods: A sample of 342 young football players completed questionnaires assessing their perceptions of coaches’ HP activities, enjoyment of sports, dropout intentions, self-esteem and perceived health in daily life.
Results: Health Promotion general score was positively related to enjoyment and perceived health as well as negatively dropout intentions. Players perceiving their coaches as promoting fair and play (Respect for oneself and others) scored higher on their perceptions of enjoyment in sport, self-esteem and self-reported health, and lower on dropout intentions. Moreover, players recognizing their coaches as encouraging their healthy lifestyle also reported higher perceptions of sport enjoyment, whereas player’s perceived coaches’ activities on substance use were associated with lower participants’ enjoyment.
Conclusions: These results support the importance of developing HP in sports clubs. Especially, promoting respect of oneself and others seems to be the more beneficial to sport participants.
Objective:
To make scientifically sound and practical recommendations for daily sleep duration across the life span.
Methods:
The National Sleep Foundation convened a multidisciplinary expert panel (Panel) with broad representation from leading stakeholder organizations. The Panel evaluated the latest scientific evidence and participated in a formal consensus and voting process. Then, the RAND/UCLA Appropriateness Method was used to formulate sleep duration recommendations.
Results:
The Panel made sleep duration recommendations for 9 age groups. Sleep duration ranges, expressed as hours of sleep per day, were designated as recommended, may be appropriate, or not recommended. Recommended sleep durations are as follows: 14-17 hours for newborns, 12-15 hours for infants, 11-14 hours for toddlers, 10-13 hours for preschoolers, 9-11 hours for school-aged children, and 8-10 hours for teenagers. Seven to 9 hours is recommended for young adults and adults, and 7-8 hours of sleep is recommended for older adults. The self-designated basis for duration selection and critical discussions are also provided.
Conclusions:
Consensus for sleep duration recommendations was reached for specific age groupings. Consensus using a multidisciplinary expert Panel lends robust credibility to the results. Finally, limitations and caveats of these recommendations are discussed.
Objectives: The current study aimed to evaluate school-based motivational sleep education programs (SEP) with adjunct bright light therapy (BLT) and/or parental involvement (PI).
Design: Randomized controlled trial.
Setting: Six high schools, matched on SES.
Participants: 193 adolescents (mean age = 16.3±0.4yrs, 79%f)
Intervention: Classes were randomly assigned to either: (i) SEP+BLT, (ii) SEP+PI, (iii) SEP+BLT+PI, or (iv) classes-as-usual (CAU). SEP involved 4 x 50 min classes (over 4 weeks) based on a Motivational Interviewing (MI) framework (Cain et al., 2011). Students in BLT groups attempted a weekend phase advance using portable green light LED glasses (500nm; 506 lux). Parents of PI groups watched a series of four YouTube clips (2-3 min in length) outlining their adolescent’s learning in class and how they could assist. Students in the CAU groups continued their regular classes.
Measurements: Online questionnaires measuring sleep knowledge, sleep patterns (bedtime, sleep latency, total sleep time, etc.) and mood at pre- and post-intervention and 6-week follow-up. Intervention groups also completed a motivation-to-change questionnaire and provided qualitative feedback.
Results: Improvements in sleep knowledge (d=0.59–0.88), sleep onset latency (d=0.45–0.50), total sleep time (d=0.32–0.57), and mood (d=0.24–0.46), were observed in all intervention groups relative to the CAU group. Similar improvements were observed in a subgroup of students identified as having delayed sleep timing (i.e. sleep knowledge: d=0.45-0.92; sleep onset latency: d=0.59–0.82; total sleep time: d=0.82–1.18). Increases in motivation to regularize out of bedtimes, obtain morning bright light (BLT groups), and avoid sleeping-in on weekends occurred (all p<.005).
Conclusions: This motivational SEP produced meaningful and similar benefits for adolescents in all intervention groups. Longer bright light therapy (i.e., over school holidays) and more intensive parental inclusion should be investigated in future studies.
There is a large body of evidence that Cognitive Behavioral Therapy for insomnia (CBT) is an effective treatment for persistent insomnia. However, despite two decades of research it is still not readily available, and there are no immediate signs that this situation is about to change. This paper proposes that a service delivery model, based on "stepped care" principles, would enable this relatively scarce healthcare expertise to be applied in a cost-effective way to achieve optimal development of CBT services and best clinical care. The research evidence on methods of delivering CBT, and the associated clinical leadership roles, is reviewed. On this basis, self-administered CBT is posited as the "entry level" treatment for stepped care, with manualized, small group, CBT delivered by nurses, at the next level. Overall, a hierarchy comprising five levels of CBT stepped care is suggested. Allocation to a particular level should reflect assessed need, which in turn represents increased resource requirement in terms of time, cost and expertise. Stepped care models must also be capable of "referring" people upstream where there is an incomplete therapeutic response to a lower level intervention. Ultimately, the challenge is for CBT to be delivered competently and effectively in diversified formats on a whole population basis. That is, it needs to become "scalable". This will require a robust approach to clinical governance.
The aim of this work was to present the Sleep Beliefs Scale (SBS), a 20-item reviewed version of the Sleep Hygiene Awareness by Lacks and Rotert. We also examined for the first time the influence of circadian typology in sleep beliefs. Voluntary and unpaid psychology students participated in the study (n = 510; 182 men and 328 women), from Italy and Spain, aged between 18 and 33 (22.80 +/- 4.14 years). The mean score of SBS was 13.05 (SD = 3.46; range 2-20) in the total sample, with a distribution positive skewness to high score (correct beliefs) (Z = 1.82; P = 0.003). The internal consistency was good (Cronbach's alpha = 0.714) and factor analysis extracted three factors labelled 'Sleep-incompatible behaviours' (eight items), 'Sleep-wake cycle behaviours' (seven items) and 'Thoughts and attitudes to sleep' (five items). Circadian typology influences the total score and that of the three factors, as well the majority of the items that compose the SBS. The morning-type showed the best scores, the evening-type the worst, and the neither-type the medium scores. Moreover, in the men sample, the differences between circadian typology groups were higher than in the women sample. The SBS showed good psychometric properties; however, further studies in other countries, with clinical and non-student samples, and more aged subjects are needed so as to validate this psychometric instrument. The circadian typology is an individual difference that presented significant relationships with the sleep beliefs, the possibility of the evening-type being a risk factor for a worse sleep hygiene, and the maintenance of sleep problems such as insomnia may all be investigated in depth in future research.
Sleep and the athlete: Narrative review and 2021 expert consensus recommendations
- N P Walsh
- S L Halson
- C Sargent
- G D Roach
- M Nédélec
- L Gupta
- J Leeder
- H H Fullagar
- A J Coutts
- B J Edwards
- S A Pullinger
- C M Robertson
- J G Burniston
- M Lastella
- Y L Meur
- C Hausswirth
- A M Bender
- M A Grandner
- C H Samuels
Walsh, N.P., Halson, S.L., Sargent, C., Roach, G.D., Nédélec, M., Gupta,
L., Leeder, J., Fullagar, H.H., Coutts, A.J., Edwards, B.J., Pullinger,
S.A., Robertson, C.M., Burniston, J.G., Lastella, M., Meur, Y.L.,
Hausswirth, C., Bender, A.M., Grandner, M.A., & Samuels, C.H.
(2021). Sleep and the athlete: Narrative review and 2021 expert
consensus recommendations. British Journal of Sports Medicine,
55(7), 356-368. https://doi.org/10.1136/bjsports2020-102025