SLEEP QUALITY IN PROFESSIONAL BALLET DANCERS

Sleep Characteristics in Dance Students Related to Psychological Inflexibility

Introduction: Dance, as a performance activity, is associated with various problems. Among these challenges, sleep disturbances are notably prevalent. Aims: This study aimed to explore the potential relationship between sleep characteristics-specifically chronotype and subjective sleep quality- and psychological inflexibility in dance students. Methods: This research adopted a cross-sectional design using non-probabilistic sampling. The data were collected in paper format by visiting public conservatories and private academies, and online. One hundred fourteen dance students, with a mean age of 23.87 years, participated in the study. Assessment tools included the Acceptance and Action Questionnaire-II, Pittsburgh Sleep Quality Index, and the Composite Scale of Morningness. Results: The results revealed that 80.7% of all students reported poor sleep quality, compared to 19.3% who reported good sleep quality. Differences emerged in both subjective sleep quality (F(2, 113) = 4.825, P = .010) and chronotype (F(2, 113) = 6.172, P = .003) when students were grouped according to low, medium, or high levels of psychological inflexibility. Those with low inflexibility, as opposed to those with high inflexibility, report better sleep quality, with no differences observed between medium and high inflexibility groups. Students with high-medium levels of psychological inflexibility showed a higher risk (OR = 6.373 times higher) of experiencing poor sleep quality compared to those with low psychological inflexibility. In terms of chronotype, the low inflexibility group is inclined to be more of a morning type than the medium and high inflexibility groups, with no differences between the latter 2 groups. Students categorized as having low inflexibility tend to have a longer history of dancing under the guidance of a teacher and dedicate more hours and days per week to rehearsal. Conclusion: Conservatories can become "healthy spaces." In this regard, sleep hygiene programs and Acceptance and Commitment Therapy interventions can provide guidance to professionals working with dancers in professional companies and conservatories.

Predicting sports performance of elite female football players through smart wearable measurement platform

Recent development of information technology and wearable devices has led to the analysis of multidimensional sports information and the enhancement of athletes' sports performance convenient and potentially more efficient. In this study, we present a novel data platform tailored for capturing athletes' cognitive, physiological, and body composition data. This platform incorporates diverse visualization modes, enabling athletes and coaches to access data seamlessly. Fourteen elite female football players (average age=20.6±1.3years; 3 forwards, 5 midfielders, 4 defenders, and 2 goalkeepers) were recruited from National Taiwan Normal University, Taiwan, as the primary observational group, and 12 female university students without regular sport/exercise habits (average age=21.6±1.3years) were recruited as control group. Through multidimensional data analysis, we identified significant differences in limb muscle mass and several cognitive function scores (e.g., reaction times of attention and working memory) between elite female football varsity team and general female university students. Furthermore, 1-month heart rate data obtained from wearable devices revealed a significant negative correlation between average heart rate median and cognitive function scores. Overall, this study demonstrates the potential of this platform as an efficient multidimensional data collection and analysis platform. Therefore, valuable insights between cognitive functions, physiological signals and body composition can be obtained via this multidimensional platform for facilitating sports performance.

The Impact of Inadequate Sleep on Overtraining Syndrome in 18-22-Year-Old Male and Female College Athletes: A Literature Review

Both male and female athletes experience acute fatigue and decreased performance from intense training sessions and training cycles with inadequate recovery. The concept of training with insufficient recovery time is known as overtraining syndrome (OTS). Primary stressors leading to OTS include excessive training, environmental factors, and inadequate levels of sleep. Sleep is a critical component of rest, recovery, memory, and cognitive function in collegiate athletes, known as male and female athletes between 18 and 22 years old. Collegiate athletes are more prone to inadequate levels of sleep, which can lead to elevated levels of fatigue, a lack of energy, motivation, alertness, and a weakened immune system. Additionally, inadequate levels of sleep lead to decreased glycogen stores in the body, affecting the functioning of physiological pathways. The processes of removing toxins and the release of growth hormones (GHs) are also impacted. GH is secreted as the rapid eye movement (REM) phase alternates with the non-REM phase and continues to rise until it peaks in the REM sleep stage, which is important for physical recovery, memory formation, and emotional regulation. This literature review aims to summarize current research on overtraining and the physiological changes that are present in both males and females from inadequate levels of sleep, emphasizing its importance in body homeostasis.

Quantifying hierarchy and prestige in US ballet academies as social predictors of career success

In the recent decade, we have seen major progress in quantifying the behaviors and the impact of scientists, resulting in a quantitative toolset capable of monitoring and predicting the career patterns of the profession. It is unclear, however, if this toolset applies to other creative domains beyond the sciences. In particular, while performance in the arts has long been difficult to quantify objectively, research suggests that professional networks and prestige of affiliations play a similar role to those observed in science, hence they can reveal patterns underlying successful careers. To test this hypothesis, here we focus on ballet, as it allows us to investigate in a quantitative fashion the interplay of individual performance, institutional prestige, and network effects. We analyze data on competition outcomes from 6363 ballet students affiliated with 1603 schools in the United States, who participated in the Youth America Grand Prix (YAGP) between 2000 and 2021. Through multiple logit models and matching experiments, we provide evidence that schools' strategic network position bridging between communities captures social prestige and predicts the placement of students into jobs in ballet companies. This work reveals the importance of institutional prestige on career success in ballet and showcases the potential of network science approaches to provide quantitative viewpoints for the professional development of careers beyond science.

Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture

Due to the high demands of competitive sports, the sleep architecture of adolescent athletes may be influenced by their regular training. To date, there is no clear evidence on how training characteristics (intensity, time of day, number of sessions) influence sleep quality and quantity. 53 male soccer players (M = 14.36 years, SD = 0.55) of Austrian U15 (n = 45) and U16 elite teams (n = 8) were tested on at least three consecutive days following their habitual training schedules. Participants completed daily sleep protocols (7 a.m., 8 p.m.) and questionnaires assessing sleep quality (PSQI), chronotype (D-MEQ), competition anxiety (WAI-T), and stress/recovery (RESTQ). Electrocardiography (ECG) and actigraphy devices measured sleep. Using sleep protocols and an ECG-based multi-resolution convolutional neural network (MCNN), we found that higher training intensity leads to more wake time, that later training causes longer sleep duration, and that one training session per day was most advantageous for sleep quality. In addition, somatic complaints assessed by the WAI-T negatively affected adolescent athletes' sleep. Individual training loads and longer recovery times after late training sessions during the day should be considered in training schedules, especially for adolescent athletes. MCNN modeling based on ECG data seems promising for efficient sleep analysis in athletes.

Sleep and Sport Performance

SUMMARY

Elite athletes and coaches believe sleep is the most important recovery strategy and widely consider it critical to optimal performance. Despite this perceived importance, there are numerous circumstances that can reduce sleep quantity and quality in athletic populations. Because of the effects of sleep loss on various physical, neurophysiological, and cognitive parameters, such perturbations can have consequences for performance and recovery outcomes. Although peer-reviewed literature examining the interaction between sleep, performance, and recovery in athletes is increasing, understanding of these issues remains equivocal. Perhaps most pertinently, the effect of sleep on sport performance does not align with a one-size-fits-all approach and rather depends on numerous factors such as type of sport, scheduling, time of the season, and the intraindividual requirements for sleep. The relationship between brain plasticity and memory, which in turn can influence learning processes and long-term memory consolidation, suggests that sleep may play an important role in learning new skills and tactics for both elite and developing athletes. The aim of this special issue review was to analyze the evidence of sleep loss on sport performance and recovery, with a specific focus on elite athletes. An assessment of these sleep-compromising situations that elite athletes may face during a typical season and practical considerations for alleviating these issues is also provided to further the understanding for medical professionals, scientists, and applied sporting practitioners alike.

Translation and Validation of the Arabic Version of the Athlete Sleep Screening Questionnaire

Sleep improves the cognitive and physical performance of athletes. A detailed questionnaire that detects sleep disruptions is required to identify sleep-deprived athletes. This study evaluates the translated Athlete Sleep Screening Questionnaire (ASSQ), a tool suggested by the International Olympic Committee, among Arabic-speaking athletes. The ASSQ was translated into Arabic and examined for floor or ceiling effects, internal consistency, and validity among Arabic-speaking athletes. The Arabic Pittsburgh Sleep Quality Index (PSQI) was employed to assess convergent validity. Ninety athletes (28.9% women) participated and completed this study's questionnaires. The Cronbach's alpha for the ASSQ-Sleep Difficulty Score (SDS) was 0.435, and that of the ASSQ-chronotype was 0.632. The SDS and chronotype subset of the ASSQ demonstrated excellent test-retest reliability, with intraclass correlation coefficients of 0.84 and 0.938, respectively. The ASSQ-SDS correlated positively with the PSQI (0.734, p = 0.001). The ASSQ-chronotype was inversely associated with the PSQI (p = 0.001). This study's findings can assist clinicians in assessing sleep disorders in sports. The Arabic version of the ASSQ has satisfactory psychometric qualities and can identify clinically relevant sleep problems in athletes.

Chronotype and quality of sleep in alpine skiers

Alpine skiing is among the most demanding sporting activities in terms of physical effort and mental workload. The aim of the study was to compare sleep quality and chronotype distribution between 84 highly trained alpine skiers and a control sample of 84 non-athletes matched by age and sex ratio. Quality of sleep was assessed by the Pittsburgh Quality of Sleep Index (PSQI), and chronotype was assessed by the Morningness-Eveningness Questionnaire (MEQ). Additional questions assessed sleep management during training or competitions. The results showed a marked skewed chronotype distribution towards morningness in alpine skiers (52.4% morning type, 42.8% intermediate, and 4.8% evening type) in comparison to the control group. The midpoint of sleep was significantly anticipated among alpine skiers. Differently from the previous literature that showed poor sleep quality and quantity in competitive athletes, the quality and quantity of sleep in alpine skiers was within the normal range in all the PSQI subcomponents.

Subjective and objective sleep quality does not predict behavioural episodic foresight in younger or older adults

Episodic foresight refers to one's capacity to use imagined scenarios to guide future-directed behaviors. It is important in facilitating complex activities of daily living, such as managing finances. Broader literature shows that older adults perform more poorly on tests of episodic foresight relative to their younger counterparts. At the same time, age-related changes in sleep often contribute to age-related decline in other cognitive abilities known to support episodic foresight, such as memory. No study to date has tested whether sleep quality is associated with episodic foresight when it is measured behaviorally; or whether this relationship is moderated by age. To address this, in the present study healthy younger (n = 39) and older (n = 41) adults were asked to wear an actigraphy watch and self-report their sleep quality for seven nights. Participants then completed the virtual-week foresight task-a behavioral assessment of episodic foresight. Neither objective or subjective sleep quality predicted episodic foresight outcomes, and this was not moderated by age group. Bayesian analyses provided evidence in favour of the null hypotheses. These results suggest that sleep quality (at least in healthy adult populations) may not be linked to episodic foresight.

Effect of Training/Competition Load and Scheduling on Sleep Characteristics in Professional Rugby League Athletes

ABSTRACT

Conlan, G, McLean, B, Kemp, J, and Duffield, R. Effect of training/competition load and scheduling on sleep characteristics in professional rugby league athletes. J Strength Cond Res 36(12): 3390-3397, 2022-This study examined the effect of training/competition load, scheduling, and associated factors on sleep behavior in professional rugby league athletes. Sleep characteristics were assessed in 26 professional rugby league athletes using wrist-mounted actigraphy and nightly sleep diaries. Sleep actigraphy assessed the time into and out of bed, the duration in bed, sleep duration, efficiency, latency, wake after sleep onset, number of awakenings, and the awakening length. Sleep was measured during 3 different weeks: (a) preseason low training load (TL) (2,356 ± 322 AU), (b) preseason high TL (3,542 ± 445 AU), and (c) in-season match week (1,526 ± 409 AU). The influences of internal TL (session rating of perceived exertion load), training schedule, age, and training location on sleep behavior were analyzed. Repeated-measures 2-way analysis of variance and effect size analyses (d) compared sleep variables between training weeks. The mean weekly sleep duration was significantly lower during high TL week (5 hours 53minutes ± 14 min/night; p = 0.015, d = 0.59) compared with the low TL (6 hours 25minutes ± 8 min·night -1 ) or match weeks (6 hours 26minutes ± 10 min·night -1 ; p = 0.02, d = 2.04). Reduced sleep duration in the high TL week occurred alongside earlier out-of-bed times compared with the low TL ( p = 0.003, d = 1.46) and match weeks ( p = 0.001, d = 5.99). Regardless, the lowest sleep duration was on match night ( p = 0.0001, d = 1.22). Earlier training start times resulted in earlier wake times ( p = 0.003, d = 4.84), shorter in-bed durations ( p = 0.0001, d = 0.62), and shorter sleep durations ( p = 0.002, d = 0.32). Younger athletes slept for longer durations ( p = 0.029, d = 1.70) and perceived their sleep quality to be superior ( p = 0.006, d = 14.94) compared with older athletes. Sleep attained by rugby league athletes is influenced by training and competition schedules, with early training start times and late-night matches being primary drivers of sleep behavior. Coaching staff should have awareness surrounding the implications of training and playing schedules on athlete sleeping patterns.

Schlafqualität und kardialer autonomer Tonus bei Leistungssporttreibenden und in einer Referenzgruppe Gesunder

Leistungssportlerinnen und Leistungssportler sind hohen physischen und psychischen Anforderungen ausgesetzt, um optimale Ergebnisse zu erzielen. Dafür ist auch die Funktion der Regenerationsphase wichtig, zu der maßgeblich ein erholsamer Schlaf beiträgt. Es gibt jedoch Hinweise, dass bei Leistungssportlerinnen und Leistungssportlern aufgrund verschiedener Belastungen im Rahmen des Trainings und der Wettkämpfe gehäuft eine Insomniesymptomatik auftreten kann. Zur objektiven Untersuchung der Schlafstruktur, Schlafqualität und Funktion des kardialen autonomen Tonus wurden Leistungssporttreibende (LS) und eine Gruppe ebenfalls gesunder Kontrollen (GK) mit einer vereinfachten ambulanten Schlafmessung untersucht.

Es wurde in der Gruppe LS bei n = 12 Probanden (Alter 25,1 ± 4,3 Jahre) und in der Gruppe GK bei n = 17 Probanden (Alter 26,1 ± 3,2 Jahre) jeweils weiblichen und männlichen Geschlechts erfolgreich im häuslichen Umfeld eine vereinfachte Schlafmessung einschließlich 1‑Kanal-EKG (SOMNOtouch™) durchgeführt. Mittels Fragebögen wurden die Tagesschläfrigkeit (Epworth Sleepiness Scale, ESS), Insomnieschwere (Insomnia Severity Index, ISI) und Symptome für Schlafapnoe (Aktualisierter STOP-Bang-Fragebogen, aSBF) erhoben. Es wurden visuell die Schlafstadien gescort und aus dem EKG mittels Zeitreihenanalyse Parameter der Herzfrequenz und Herzfrequenzvariabilität (HRV) ausgewertet.

Es traten keine Unterschiede zwischen den Gruppen LS und GK hinsichtlich der ESS und aSBF auf, jedoch war die ISI in der Gruppe LS gegenüber GK erhöht (5,7 ± 4,1 vs. 2,4 ± 2,0; p < 0,02). In Auswertung der Schlafstruktur gab es keine Unterschiede für die Einschlaflatenz (ESL), Gesamtschlafzeit (TST), Schlafeffizienz (SE) sowie für die prozentualen Anteile von Leicht- (N1 + N2), Tief- (N3) und REM-Schlaf (REM), jedoch war die Bettzeit (TIB) in der Gruppe LS erhöht (503,2 ± 52,7 vs. 445,5 ± 45,4 min; p < 0,02). In der Gruppe LS waren gegenüber der Gruppe GK die mittlere nächtliche Herzfrequenz verringert (48,5 ± 6,8 vs. 56,1 ± 5,4; p < 0,01) sowie die HRV-Parameter HRV-Standardabweichung (HRV-SD) (166,0 ± 33,2 vs. 138,2 ± 38,7; p < 0,04), HRV-SD1 (78,8 ± 11,7 vs. 63,2 ± 36,5; p < 0,01) und HRV-SD2 (220,6 ± 48,0 vs. 183,8 ± 45,8; p < 0,05) erhöht.

In der von uns untersuchte Gruppe von Leistungssportlerinnen und Leistungssportlern gibt es Anhaltspunkte für eine leichte Insomnie, wobei die objektiv gemessene Schlafstruktur sich nicht von der gesunder Kontrollen unterscheidet. Dabei ist die TST, mit einem Mittelwert von 6,8 h sowohl in der Gruppe LS als auch in GK, geringer als die von den Fachgesellschaften American Academy of Sleep Medicine (AASM), Sleep Research Society (SRS) und National Sleep Foundation (NSF) empfohlene Schlafdauer für junge Erwachsene. Dagegen war die kardiale autonome Regulation im Schlaf in der Gruppe LS signifikant besser als in der Gruppe GK und ist in Übereinstimmung mit Befunden aus 24-Stunden-Holter-EKG-Studien. Die Entwicklung objektiver, mobiler und belastungsarmer Messverfahren vereinfacht die Erfassung der Schlafstruktur und charakteristischer vegetativer Parameter und könnte zunehmend im personalisierten Gesundheits- und Leistungsmanagement bei Leistungssporttreibenden eingesetzt werden.

Four Weeks of a Neuro-Meditation Program Improves Sleep Quality and Reduces Hypertension in Nursing Staff During the COVID-19 Pandemic: A Parallel Randomized Controlled Trial

The purpose of this study was to examine the effectiveness of a neuro-meditation program to support nurses during the COVID-19 pandemic. Forty-five (10 men and 35 women) nurses were classified into three groups based on their systolic blood pressure: normotensive (G-nor; n = 16, 43.8 ± 11.0 year), hypertensive (G-hyp; n = 13, 45.2 ± 10.7 year) and control (G-con; n = 16, 44.9 ± 10.6 year). Using a parallel, randomly controlled design across a 4-week period, 10 × 30-min sessions using the Rebalance© Impulse were completed. Sleep was assessed by wrist actigraphy and subjective sleep questionnaires; perceived sleep quality, Ford Insomnia Response to Stress Test questionnaire and the Spiegel Sleep Quality questionnaire (SSQ). Blood pressure, resting heart rate, mean heart rate (HRmean), heart rate variability index (RMSSD), cortisol, and alpha-amylase were also measured. Statistical analysis was completed using factorial ANOVA. Sleep improved in the G-hyp group; SSQ (p < 0.01); perceived sleep quality (p < 0.01); sleep efficiency and fragmentation index (p < 0.05). In the G-nor group, sleep was improved to a lesser extent; perceived sleep quality (p < 0.01). A significant time-group interaction was reported in resting heart rate (p < 0.01), systolic blood pressure (p < 0.01), and diastolic blood pressure (p < 0.05) with these measures being significantly reduced in the G-hyp group. RMSSD increased in the G-nor group (p < 0.01). This initial evidence suggests that neuro-meditation reduces excessive sympathetic activity, promoting enhanced sleep quality and autonomic control during periods of increased work-related stress.

Clinical Trial Registration

The study was conducted at Bioesterel, Sophia-Antipolis, France as a clinical trial: Neuro-meditation improves sleep quality, https://www.drks.de/ui_data_web/DrksUI.html?locale=en, DRKS00025731.

Evaluation of environmental, social, and behavioral modulations of the circadian phase of dancers trained in shifts

The interplay of environmental, social, and behavioral factors influencing human circadian phase in ecological conditions remains elusive. The Uruguayan national dance school END-SODRE operating in two shifts (morning: 8:30–12:30 and night: 20:00–24:00) allowed us to evaluate how social demands, chronotype, environmental light, physical activity, and sleep patterns affected individual circadian phase measured by the onset of the nocturnal increase of melatonin (DLMO) in a single study. The DLMO was 1.5 h earlier in morning-shift dancers (n = 7) compared to night-shift dancers (n = 11). Sleep time and chronotype (only in night-shift dancers) were associated with the circadian phase. In training days, during each participant’s phase-advance and phase-delay time windows, light exposure was similar between morning and night-shift dancers and did not correlate with DLMO. In contrast, the time spent in moderate-vigorous physical activity during each participant’s phase-lag time window was higher in night-shift dancers than in morning-shift dancers and positively correlated with DLMO.

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Circadian phase was earlier in morning than in night dancers in real-life conditions

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Sleep time (and night-shift chronotypes) correlated with the circadian phase

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In the phase-advance and phase-lag windows, light was not associated with DLMO

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In the phase-lag time window, the longer the intense exercise the later the phase

Validierung des Fragebogens zum Schlafverhalten von Sportlerinnen und Sportlern (FSVS)

Zusammenfassung. Der Athlete Sleep Behavior Questionnaire ist ein englischsprachiger Fragebogen zur Erhebung des individuellen Schlafverhaltens von Sportler_innen. Ziel dieser Studie war die Übersetzung des Athlete Sleep Behavior Questionnaire ins Deutsche sowie die wissenschaftliche Validierung dieser deutschen 18-Item-Version, dem Fragebogen zum Schlafverhalten von Sportlerinnen und Sportlern (FSVS). Die Validierungsstichprobe umfasste 450 Teilnehmende. Mittels eines dichotomen Items zur regelmäßigen Wettkampfteilnahme (ja/nein) wurde in Wettkampfsportler_innen ( n = 209) und Kontrollgruppe ( n = 241) unterteilt. Cronbach-α des FSVS-Gesamtwerts ergab .66. Die Pearson-Produkt-Moment-Korrelationsanalysen ergaben moderate Korrelationen zwischen FSVS-Gesamtwert, der Epworth-Sleepiness-Scale ( r = .33) und dem Pittsburgh-Sleep-Quality-Index ( r = .30). Es wurden signifikante Gruppenunterschiede für den FSVS-Gesamtwert gefunden, t‍(448) = 4.47, p < .001, d = 0.42, bei deskriptiv höheren Werten der Gruppe der Wettkampfsportler_innen. In einer separaten Stichprobe, die 13 Ruderer_innen der deutschen Junioren-Nationalmannschaft umfasste, wurden die Fragebogenwerte anschließend mit objektiven Schlafparametern korreliert. Dabei ließ sich eine hohe Korrelation zwischen FSVS-Gesamtwert und Einschlaflatenz ( rs = .68, p = .011) erkennen. Zusammenfassend ist der FSVS ein schnelles und valides Werkzeug, um dysfunktionale Schlafverhaltensweisen bei Wettkampfsportler_innen zu identifizieren. In Anlehnung an die Originalversion wird die Ableitung von Interventionen anhand einzelner Items empfohlen.

The impact of daytime napping on athletic performance - A narrative review

Mid-day napping has been recommended as a countermeasure against sleep debt and an effective method for recovery, regardless of nocturnal sleep duration. Herein, we summarize the available evidence regarding the influence of napping on exercise and cognitive performance as well as the effects of napping on athletes' perceptual responses prior to or during exercise. The existing studies investigating the influence of napping on athletic performance have revealed equivocal results. Prevailing findings indicate that following a normal sleep night or after a night of sleep loss, a mid-day nap may enhance or restore several exercise and cognitive performance aspects, while concomitantly provide benefits on athletes' perceptual responses. Most, but not all, findings suggest that compared to short-term naps (20-30 min), long-term ones (>35-90 min) appear to provide superior benefits to the athletes. The underlying mechanisms behind athletic performance enhancement following a night of normal sleep or the restoration after a night of sleep loss are not clear yet. However, the absence of benefits or even the deterioration of performance following napping in some studies is likely the result of sleep inertia. The present review sheds light on the predisposing factors that influence the post-nap outcome, such as nocturnal sleep time, mid-day nap duration and the time elapsed between the end of napping and the subsequent testing, discusses practical solutions and stimulates further research on this area.

Sleep Behaviors and Handedness in Gifted and Non-Gifted Children

Patterns of sleep behaviors appear to differ across students with special needs including those classified with developmental disorders, attention-deficit/hyperactivity disorder, and autism. One understudied segment of the special needs population is that of gifted children, students who bring their own unique set of behavioral characteristics. In the present study, it was hypothesized that because of unique cognitive and socio-emotional intensities, gifted children would experience elevated levels of sleep disturbance in comparison to their non-gifted peers. Handedness was also surveyed for additional insight into cerebral organization. The study's participants were 35 gifted and 23 non-gifted students between the ages of 8-12. To measure sleep behaviors, data from the Child Sleep Habits Questionnaire (Abbreviated), Sleep Self-Report, and a sleep diary were collected. To assess handedness, the Edinburgh Handedness Inventory was administered. Results indicated that although gifted students did trend toward experiencing more sleep disturbance, when compared to non-gifted students, no significant differences were found in mean bedtime, hours slept, sleeping problems, or use of electronic devices before bedtime. In terms of handedness, gifted participants displayed more left-hand bias. Although no differences were found between sleep patterns of gifted vs. non-gifted children, this study adds to the limited evidential base on gifted children, handedness, and sleep. Additional research on sleep behaviors within this special needs cohort may be warranted.

Deconstructing athletes' sleep: A systematic review of the influence of age, sex, athletic expertise, sport type, and season on sleep characteristics

PURPOSE

This systematic review aimed to describe objective sleep parameters for athletes under different conditions and address potential sleep issues in this specific population.

METHODS

PubMed and Scopus were searched from inception to April 2019. Included studies measured sleep only via objective evaluation tools such as polysomnography or actigraphy. The modified version of the Newcastle-Ottawa Scale was used for the quality assessment of the studies.

RESULTS

Eighty-one studies were included, of which 56 were classified as medium quality, 5 studies as low quality, and 20 studies as high quality. A total of 1830 athletes were monitored over 18,958 nights. Average values for sleep-related parameters were calculated for all athletes according to sex, age, athletic expertise level, training season, and type of sport. Athletes slept on average 7.2 ± 1.1 h/night (mean ± SD), with 86.3% ± 6.8% sleep efficiency (SE). In all datasets, the athletes' mean total sleep time was <8 h. SE was low for young athletes (80.3% ± 8.8%). Reduced SE was attributed to high wake after sleep onset rather than sleep onset latency. During heavy training periods, sleep duration and SE were on average 36 min and 0.8% less compared to pre-season and 42 min and 3.0% less compared to in-season training periods, respectively.

CONCLUSION

Athletes' sleep duration was found to be short with low SE, in comparison to the general consensus for non-athlete healthy adults. Notable sleep issues were revealed in young athletes. Sleep quality and architecture tend to change across different training periods.

A daytime 40-min nap opportunity after a simulated late evening soccer match reduces the perception of fatigue and improves 5-m shuttle run performance

The effect of a 40-min nap opportunity was investigated during the day following a late evening simulated soccer match. Twelve male amateur soccer players (23 ± 3 years; 77.3 ± 5.3 kg; 1.76 ± 0.04 m) performed the Loughborough-intermittent-shuttle test at 21h00 and the following day they completed the sleepiness scale after either a nonap (N0) or 40-min nap (N40) opportunity that began at 14h00. At 17h00, participants performed the 5-m shuttle run test (5mSRT) (6 × 30-s with 35-s in-between; best distance (BD) and total distance (TD) were calculated). After performing the 5mSRT, they provided their rating of the perceived exertion (RPE) and rated their muscle soreness. Sleepiness scores were significantly lower in N40 in comparison with N0 (P < 0.05). A significant increase of TD (+64.5 m) and BD (+9.6 m) after N40 compared to N0 was observed (P < 0.05). The improved performance was associated with reduced levels of muscle soreness and lower RPE. In conclusion, a daytime 40-min nap opportunity after a late evening simulated soccer match improves short-term repetitive maximal performance in soccer players, and has positive effects on perception of sleepiness, muscle soreness, and RPE.

Meta-analysis of age and actigraphy assessed sleep characteristics across the lifespan

STUDY OBJECTIVES

Sleep quantity and continuity vary across the lifespan. Actigraphy is a reliable and widely-used behavioral measure of sleep in research and personal health monitoring. This meta-analysis provides a novel examination of whether age (in years) is associated with actigraphy-assessed sleep across the lifespan.

METHODS

A systematic search of PubMed, Embase.com, Cochrane CENTRAL, and PsycINFO using "actigraphy" and "sleep" terms provided 7,079 titles/abstracts; studies of individuals with known psychiatric or medical comorbidities were excluded. Ninety-one articles (N = 23,365) provided data for six meta-analyses examining sleep duration (k = 89), sleep efficiency (k = 58), bedtime (k = 19) and waketime (k = 9) for individuals ages 6-21, and bedtime (k = 7) and waketime (k = 7) for individuals ages 22 and older.

RESULTS

At older ages, sleep duration was shorter (r = -0.12) and sleep efficiency was lower (r = -0.05). Older age was associated with later bedtime (r = 0.37) and wake-up time (r = 0.24) from ages 6-21, whereas older age was associated with earlier bedtime (r = -0.66) and wake-up time (r = -0.59) for ages 22 and above. The strength of these associations was modified by study continent, but not by any other moderator.

CONCLUSIONS

Age was negatively associated with actigraphy-assessed sleep duration and efficiency, but the effects were small in magnitude. On the other hand, large associations were observed between age and sleep timing, despite a smaller literature and the absence of analyzable data for ages 30-60. Changes in sleep timing, rather than changes in sleep duration or continuity, may better characterize the effects of age on human sleep.

"When I Sleep Poorly, It Impacts Everything": An Exploratory Qualitative Investigation of Stress and Sleep in Junior Endurance Athletes

On their journeys toward senior athletic status, junior endurance athletes are faced with a multitude of stressors. How athletes react to stressors plays a vital part in effective adaptation to the demanding, ever-changing athletic environment. Sleep, the most valued recovery strategy available to athletes, has the potential to influence and balance athletic stress, and enable optimal functioning. However, sleep is sensitive to disturbances by stress, which is described by the concept of sleep reactivity. Among athletes, poor sleep quality is frequently reported, but our understanding of the associations between stress and sleep in junior athletes is currently incomplete. The present study therefore investigated the themes of stress and sleep, and the associations between these variables with the use of in-depth semi-structured interviews in six junior endurance athletes (three men and three women, mean age 17.7 ± 0.5 years). Data was analyzed qualitatively based on the Grounded Theory. The qualitative material was supplemented with quantitative data on subjective sleep quality (Pittsburg Sleep Quality Index), sleep reactivity (Ford Insomnia Response to Stress Test), and mental strain (visual analog scale). The main results showed that stress could be differentiated into relevant stressors (encompassing poor performance, uncertainty in relation to training, school, daily hassles, and sleep) and reactions to stress (with sub-categories facilitative and maladaptive). Sleep could be differentiated into sleep benefits (encompassing energy levels and athletic functioning) and sleep quality (with sub-categories satisfactory and inadequate). All athletes identified relevant stressors, and all athletes were aware of the benefits of sleep for athletic functioning. However, athletes formed two distinctive categories based on the interactions between stress and sleep: three exhibited facilitative reactions to stress and good sleep quality, as well as low sleep reactivity, and low mental strain. The remaining participants exhibited maladaptive reactions to stress and poor sleep quality, as well as high sleep reactivity and high mental strain. Conceptualizing sleep quality based on the evaluation of stressors, reactions to stress, degree of mental strain, and the propensity to stress-related sleep disturbance may offer a plausible explanation for why the occurrence of stressors leads to poor sleep quality in some athletes, but not others.

Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden

Wearable sensors enable the real-time and non-invasive monitoring of biomechanical, physiological, or biochemical parameters pertinent to the performance of athletes. Sports medicine researchers compile datasets involving a multitude of parameters that can often be time consuming to analyze in order to create value in an expeditious and accurate manner. Machine learning and artificial intelligence models may aid in the clinical decision-making process for sports scientists, team physicians, and athletic trainers in translating the data acquired from wearable sensors to accurately and efficiently make decisions regarding the health, safety, and performance of athletes. This narrative review discusses the application of commercial sensors utilized by sports teams today and the emergence of descriptive analytics to monitor the internal and external workload, hydration status, sleep, cardiovascular health, and return-to-sport status of athletes. This review is written for those who are interested in the application of wearable sensor data and data science to enhance performance and reduce injury burden in athletes of all ages.

Self-reported current sleep behaviors of adult athletes from different competitive levels and sports

Objectives

To quantify self-reported current sleep behaviors in a range of adult athletes. In addition, to determine any differences in sleep duration and sleep quality, depending on sport type and competitive level.

Material and Methods

In this cross-sectional study, 313 athletes (243 male, 70 female), competing in a variety of sports and competitive level, completed the Pittsburgh sleep quality index (PSQI) and a questionnaire which captured current sleep behaviors. Sleep quality was calculated using the global PSQI score (≥ 5 indicative of poor sleep quality).

Results

On average, athletes self-reported sleep duration was 7:34 ± 1:00 h:min. Overall, 19% of athletes achieved less than 7 h of sleep, 50% achieved less than 8 h. Global PSQI score was 5.0 ± 2.4, with poor sleep quality found in 55% of athletes. Sleep duration was significantly shorter in runners compared to basketball, soccer and rugby players (p < 0.05). Recreational athletes slept significantly less (7:08 ± 0:54 h:min) than competitive (7:32 ± 1:00 h:min), national (7:50 ± 1:00 h:min) and elite level athletes (7:49 ± 0:51 h:min). No differences in sleep quality were found between sport or competitive level.

Discussion

Half of the athletes failed to achieve 8 h of sleep per night and the majority reported compromised sleep quality. Sport type and competitive level may influence sleep duration; however, these factors do not seem to cause discrepancies in sleep quality. This study provides novel data into the sleep behaviors of adult athletes, and suggests strategies to improve sleep duration and quality may be warranted.

A Call for Active Resilience Training in Dance

Dancers represent a unique subset of athletes who face physical and psychological stressors throughout their careers. These challenges pose risks for injury, burnout, and diminished performance capacity. This article proposes a proactive intervention. The Active Resilience Training in Dance curriculum would provide dancers with useable instruction at key career inflection points (amateur to preprofessional, preprofessional to professional, and professional to retirement) to bolster the 4 pillars of their resilience (emotional, cognitive, spiritual, and physical).

A critical review on sleep assessment methodologies in athletic populations: factors to be considered

A growing body of research focus on athletes' sleep in order to investigate the effects of sleep in sports performance and recovery or the prevalence of sleep disorders in athletes. At the same time, several sleep monitoring tools have been developed and used in athletic populations for fulfilling these purposes. This review aimed to provide critical assessment to the most used by athletes' methodological approaches and compared them with the gold standard approach. Advantages and disadvantages of the various sleep monitoring tools were critically discussed. Literature related to aspects of athletes' sleep was reviewed. From the shortlisted studies, several factors that seem to affect sleep in athletes were identified using objective methods such as polysomnography/electroencephalography and actigraphy. These factors were associated to sleep (eg such as sleep environment, familiarization procedures and napping) and daily habits (eg nutrition, fluid consumption, alcohol and caffeine intake, tobacco use). The selected studies that evaluated sleep objectively were screened according the reporting rates of these variables. The majority of the screened studies were found to underreport these variables. Practical issues were addressed and recommendations about reporting sleep-related factors were made in order to improve studies' quality assessment and allow for more robust comparisons between studies.

Influence of Sleeping Patterns in Health and Academic Performance Among University Students

Sleep problems in university students are important and have implications for health, quality of life, and academic performance. Using an ex post facto design, a total sample of 855 students (55.7% women) participated in the study. Sleep assessment was conducted using the Pittsburgh Sleep Quality Index, the Nightmare Frequency Scale, the Nightmare Proneness Scale, and the Composite Morningness Scale. Women show a higher risk [OR = 2.61] of presenting poor sleep quality (> 5 points on the PSQI) compared with men (p < 0.001). Similarly, women reported a greater frequency of nightmares (p < 0.001, d = 0.60), greater propensity for nightmares (p < 0.001, d = 0.70) and a higher score on Item-5h of the PSQI regarding nightmares (p < 0.001, d = 0.59). Women, compared with men, show higher risk [OR = 2.84] for a sleep disorder related to nightmares (p = 0.012). Women need more time to reach a state of alertness after getting up (p = 0.022), and there was an interaction between sex and the alertness factor when evaluating the subjective quality of sleep (p = 0.030). Women show worse sleep quality and a higher frequency and propensity for suffering nightmares. When considering the relationship between sleep quality and academic performance, it is observed that students with poor sleep quality obtain lower academic scores (M = 7.21, SD = 0.805) than those with good sleep quality (M = 7.32, SD = 0.685), an effect that reaches significance (t = 2.116, p = 0.035). Regarding the relationship between the categorized chronotype and academic performance, students with a morning chronotype achieve better academic results (M = 7.41, SD = 0.89) than their evening counterparts (M = 7.15, SD = 0.76), although these differences have a small effect size (d = 0.31).

Overnight polysomnography and the recording of sleep and sleep-related respiration in orchestra musicians - possible protective effects of wind instruments on respiration

Our study is the first to objectively assess sleep and sleep-related respiration in orchestra musicians. We hypothesized low sleep quality due to high work demands and irregular work-sleep schedules, and a better respiration for wind instrument (WI) players than string instrument (SI) players due to habitual upper airway muscles training. We recorded overnight polysomnography with 29 professional orchestra musicians (21 men, 14 WI/ 15 SI). The musicians presented a sleep efficiency of 88% (IQR 82-92%) with WI having a significant higher sleep efficiency than SI (89%, 85-93% vs. 85%, 74-89%; p = 0.029). The group had a total sleep time around 6 hours (377min, 340-421min) with signs of increased NREM 1 (light sleep) and decreased REM (dream sleep). The musicians displayed an apnea-hypopnea-index of 2.1events/hour (0.7-5.5) and an oxygen saturation of 98% (97-100%). While SI player exhibited declining sleep-related respiration with age (breathing events: r = 0.774, p = 0.001, oxygen: r = -0.647, p = 0.009), WI player showed improved respiration with age (breathing events: r = -0.548, p = 0.043; oxygen: r = 0.610, p = 0.020). Our study is the first objective investigation of sleep pattern and respiration during sleep with overnight polysomnography in professional orchestra musicians. While sleep and respiration were unexpectedly good, our results revealed possible signs of sleep deprivation and an interesting age-related pattern on respiration depending on instrument. While sample size was small and results modest, these findings present first objective evidence towards the assumption that habitual playing of a WI-and training of the upper airway muscles-may have a protective effect on respiration.

A sleep intervention study comparing effects of sleep restriction and fragmentation on sleep and vigilance and the need for recovery

PURPOSE

Sleep deprivation is present not only in sleep disorders but also in numerous high demanding jobs and negatively affects cognition, performance and health. We developed a study design to distinguish the effects and need for recovery of two short-term disturbances - intermittent sleep fragmentation and partial sleep restriction.

METHODS

The randomized within-subjects design contained two weeks each with a baseline night, an intervention night of either sleep deprivation (5 h) or sleep fragmentation (light on every hour) and two undisturbed recovery nights. Twenty healthy male participants (mean age: 39.9 ± 7.4 years, mean BMI: 25.5 ± 2.2 kg/m²) underwent polysomnography, a psychomotor vigilance task (PVT), and subjective questions on well-being and sleep efficiency.

RESULTS

Percentage-wise, the restriction night had significant less wake times, less light sleep (stage 1), less REM sleep, but more deep sleep (stage 3) than the fragmentation night. The restriction week displayed a significant recovery effect regarding these sleep stages. The sleep fragmentation week presented a significant recovery effect regarding sleep onset times. PVT performance showed only a slight recovery effect after sleep restriction. Subjective sleep quality was reduced after both interventions with a significant recovery effect during restriction week only.

CONCLUSIONS

Short-term sleep restriction presented as a stronger sleep disturbance than short-term intermittent sleep fragmentation, including a stronger need for recovery. Already a one night sleep deprivation had an effect beyond two recovery days. The PVT was not sensitive enough to reveal significant changes. Next, autonomic parameters as possible biomarkers will be investigated.

Effect of Diagnosed Sleep Disorders on Baseline Concussion Symptom, Cognitive, and Balance Assessments in Collegiate Athletes

BACKGROUND

Symptoms, cognition, balance, and other domains are commonly assessed at baseline testing as part of comprehensive preseason evaluations among collegiate student-athletes. Although approximately 27% of college students have at least 1 sleep disorder, researchers have yet to examine the role of a preexisting sleep disorder on preinjury baseline performance.

PURPOSE

To compare athletes with and without a reported history of diagnosed sleep disorders on commonly used baseline concussion assessments.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

A total of 666 National Collegiate Athletic Association student-athletes completed baseline measures including the Balance Error Scoring System (BESS), Brief Symptom Inventory-18 (BSI-18), Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), Post-Concussion Symptom Scale (PCSS), Sport Concussion Assessment Tool-5th Edition (SCAT5), and Standardized Assessment of Concussion (SAC). There were 333 athletes with a history of diagnosed sleep disorders who were matched on age, sex, sport, and concussion history to 333 athletes with no history of diagnosed sleep disorders. Participants in both groups had a mean age of 19.89 ± 1.36 years and included 182 (54.7%) male athletes, and 126 (37.8%) reported a history of ≥1 concussions.

RESULTS

A series of 1-way analyses of covariance with Bonferroni corrections revealed significant group differences on the BESS (F_1,559 = 8.88; P < .01); BSI-18 somatization (F_1,640 = 18.48; P < .01), depression (F_1,640 = 18.78; P < .01), anxiety (F_1,640 = 19.42; P < .01), and global severity index (F_1,640 = 27.18; P < .01); PCSS (F_1,424 = 29.42; P < .01); SCAT5 symptom number (F_1,634 = 28.79; P < .01) and symptom severity (F_1,634 = 31.74; P < .01); and SAC (F_1,578 = 4.36; P = .037). Specifically, while the sleep disorder group did perform better on the BESS, they also reported higher symptoms on the BSI-18, PCSS, and SCAT5 and performed worse on the SAC. There were no group differences on ImPACT performance.

CONCLUSION

Collegiate student-athletes with diagnosed sleep disorders reported elevated affective and concussion symptoms at baseline that could affect the interpretation of postinjury impairments and symptoms. Based on the small effect sizes of our findings, however, the magnitude of these differences is of questionable clinical significance. Still, clinicians should consider diagnosed sleep disorders as reported during preparticipation sports physical examinations when interpreting baseline and postinjury concussion assessments.

Gender differences in sleep patterns and sleep complaints of elite athletes

OBJECTIVE

The present study aimed to investigate the gender differences for sleep complaints, patterns and disorders of elite athletes during preparation for the Rio 2016 Olympic Games.

METHODS

The study included 146 athletes from the Brazilian Olympic Team (male: n=86; 59%; female: n=60; 41%). The assessment of the Olympic athletes' sleep took place in 2015, during the preparation period for the Rio Olympic Games. The athletes underwent a single polysomnography (PSG) evaluation. Sleep specialists evaluated the athletes and asked about their sleep complaints during a clinical consultation. In this evaluation week, the athletes did not take part in any training or competitions.

RESULTS

The prevalence of sleep complaints was 53% of the athletes during the medical consultation, the most prevalent being insufficient sleep/waking up tired (32%), followed by snoring (21%) and insomnia (19.2%). In relation to the sleep pattern findings, the men had significantly higher sleep latency and wake after sleep onset than the women (p=0.004 and p=0.002, respectively). The sleep efficiency and sleep stages revealed that men had a lower percentage of sleep efficiency and slow wave sleep than the women (p=0.001 and p=0.05, respectively).

CONCLUSION

Most athletes reported some sleep complaints, with men reporting more sleep complaints than women in the clinical evaluation. The PSG showed that 36% of all athletes had a sleep disorder with a greater reduction in sleep quality in men than in women.

Sleep-Related Issues for Recovery and Performance in Athletes

The body of research that reports the relevance of sleep in high-performance sports is growing steadily. While the identification of sleep cycles and diagnosis of sleep disorders are limited to lab-based assessment via polysomnography, the development of activity-based devices estimating sleep patterns provides greater insight into the sleep behavior of athletes in ecological settings. Generally, small sleep quantity and/or poor quality appears to exist in many athletic populations, although this may be related to training and competition context. Typical sleep-affecting factors are the scheduling of training sessions and competitions, as well as impaired sleep onset as a result of increased arousal prior to competition or due to the use of electronic devices before bedtime. Further challenges are travel demands, which may be accompanied by jet-lag symptoms and disruption of sleep habits. Promotion of sleep may be approached via behavioral strategies such as sleep hygiene, extending nighttime sleep, or daytime napping. Pharmacological interventions should be limited to clinically induced treatments, as evidence among healthy and athletic populations is lacking. To optimize and manage sleep in athletes, it is recommended to implement routine sleep monitoring on an individual basis.

Effects of training and competition on the sleep of elite athletes: a systematic review and meta-analysis

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.

Sleep Quality and Chronotype Differences between Elite Athletes and Non-Athlete Controls

Previous research has found that elite athletes have insufficient sleep, yet the specific kinds of sleep disturbances occurring as compared to a control group are limited. Here we compare the subjective sleep quality and chronotype of elite athletes to a control group of non-athlete good sleepers. Sixty-three winter Canadian National Team athletes (mean age 26.0 ± 0.0; 32% females) completed the Pittsburgh Sleep Quality Index (PSQI) and the Athlete Morningness Eveningness Scale. They were compared to 83 healthy, non-athlete, good-sleeper controls (aged 27.3 ± 3.7; 51% females) who completed the PSQI and the Composite Scale of Morningness. The elite athletes reported poorer sleep quality (PSQI global score 5.0 ± 2.6) relative to the controls (PSQI global score 2.6 ± 1.3), despite there being no group difference in self-reported sleep duration (athletes 8.1 ± 1.0 h; controls 8.0 ± 0.7 h). Further, athletes’ chronotype distribution showed a greater skew toward morningness, despite there being no group differences in self-reported usual bedtime and wake time. These results suggest that a misalignment of sleep times with circadian preference could contribute to poorer sleep quality in elite athletes.

The Variability of Sleep Among Elite Athletes

Practicing sport at the highest level is typically accompanied by several stressors and restrictions on personal life. Elite athletes’ lifestyle delivers a significant challenge to sleep, due to both the physiological and psychological demands, and the training and competition schedules. Inter-individual variability of sleep patterns (e.g., sleep requirements, chronotype) may have important implications not only for recovery and training schedules but also for the choice of measures to possibly improve sleep. This article provides a review of the current available literature regarding the variability of sleep among elite athletes and factors possibly responsible for this phenomenon. We also provide methodological approaches to better address the inter-individual variability of sleep in future studies with elite athletes. There is currently little scientific evidence supporting a specific influence of one particular type of sport on sleep; sleep disorders may be, however, more common in strength/power and contact sports. Sleep behavior may notably vary depending on the athlete’s typical daily schedule. The specificity of training and competition schedules possibly accounts for the single most influential factor leading to inconsistency in sleep among elite athletes (e.g., “social jet lag”). Additionally, athletes are affected by extensive exposure to electric light and evening use of electronic media devices. Therefore, the influence of ordinary sleep, poor sleep, and extended sleep as important additional contributors to training load should be studied. Future experimental studies on sleep and elite sport performance should systematically report the seasonal phase. Boarding conditions may provide a good option to standardize as many variables as possible without the inconvenience of laboratory. The use of interdisciplinary mixed-method approaches should be encouraged in future studies on sleep and elite sport. Finally, high inter- and intra-individual variability in the athletes’ sleep characteristics suggests a need for providing individual responses in addition to group means.

Use of Actigraphy for the Evaluation of Sleep Disorders and Circadian Rhythm Sleep-Wake Disorders: An American Academy of Sleep Medicine Systematic Review, Meta-Analysis, and GRADE Assessment

INTRODUCTION

The purpose of this systematic review is to provide supporting evidence for a clinical practice guideline on the use of actigraphy.

METHODS

The American Academy of Sleep Medicine commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies that compared the use of actigraphy, sleep logs, and/or polysomnography. Statistical analyses were performed to determine the clinical significance of using actigraphy as an objective measure of sleep and circadian parameters. Finally, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence for making recommendations.

RESULTS

The literature search resulted in 81 studies that met inclusion criteria; all 81 studies provided data suitable for statistical analyses. These data demonstrate that actigraphy provides consistent objective data that is often unique from patient-reported sleep logs for some sleep parameters in adult and pediatric patients with suspected or diagnosed insomnia, circadian rhythm sleep-wake disorders, sleep-disordered breathing, central disorders of hypersomnolence, and adults with insufficient sleep syndrome. These data also demonstrate that actigraphy is not a reliable measure of periodic limb movements in adult and pediatric patients. The task force provided a detailed summary of the evidence along with the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use considerations.

Risk factors for precompetitive sleep behavior in elite female athletes

BACKGROUND

Sleep is of major importance for the athletes' short and long-term health, performance and recovery; however, published studies on athletes' sleep and even fewer before competition are scarce. This study evaluated the risk factors of sleep in young female gymnasts before an international competition.

METHODS

Sixty-seven rhythmic gymnasts (M=18.7, SD=2.9 years) of high performance (M=36.6, SD=7.6 h/week) were evaluated regarding training and sport practice, body composition, sleep duration, daytime sleepiness by the Epworth Sleepiness Scale, sleep quality by the Pittsburgh Sleep Quality Index, precompetitive anxiety by the Sport Competition Anxiety Test form A, and detailed dietary intake just prior to a world competition.

RESULTS

The majority of the participants (83.6%) presented reduced body fat levels (M=9.1, SD=2.1%) and low energy availability (EA, M=31.5, SD=11.9 kcal/kgFFM/day). They slept 8h10±1h30/night on weekdays and 8h40±00h40/night on weekends, 67% suffered from mild daytime sleepiness and 78% had a reduced sleep quality. Precompetitive anxiety was on average moderate (M=22.7, SD=3.2). The risk factors for short sleep duration were: 1.92 for a training volume>30 hours/week (95% CI 0.84-4.39), 4.57 for menstruation (95% CI 1.17-17.77), 6.62 for bedtime ≥11:00 PM (95% CI 1.74-25.10), 1.40 for BF<12% (95% CI 1.03-1.92), 2.19 for FFM<30 kg (95% IC 0.94-4.94), 2.37 for BMR<1100 kcal/day (95% CI 1.06-5.32), 1.90 for EEE≥700 kcal (95% CI 0.92-3.93) and 3.17 for EA<45 kcal/kg FFM/day (95% CI 0.84-6.59). Age, performance, sleep duration on weekdays and precompetitive stress were also predictors for a reduced sleep quality and/or abnormal daytime sleepiness.

CONCLUSIONS

Age, training regime, menstruation, individual preferences for bedtime, body composition and energy were important predictors of gymnasts' precompetitive sleep with consequences upon their sleep duration, SQ and DS.

The Clinical Validation of the Athlete Sleep Screening Questionnaire: an Instrument to Identify Athletes that Need Further Sleep Assessment

Background

Previous research has established that general sleep screening questionnaires are not valid and reliable in an athlete population. The Athlete Sleep Screening Questionnaire (ASSQ) was developed to address this need. While the initial validation of the ASSQ has been established, the clinical validity of the ASSQ has yet to be determined. The main objective of the current study was to evaluate the clinical validity of the ASSQ.

Methods

Canadian National Team athletes (N = 199; mean age 24.0 ± 4.2 years, 62% females; from 23 sports) completed the ASSQ. A subset of athletes (N = 46) were randomized to the clinical validation sub-study which required subjects to complete an ASSQ at times 2 and 3 and to have a clinical sleep interview by a sleep medicine physician (SMP) who rated each subjects’ category of clinical sleep problem and provided recommendations to improve sleep. To assess clinical validity, the SMP category of clinical sleep problem was compared to the ASSQ.

Results

The internal consistency (Cronbach’s alpha = 0.74) and test-retest reliability (r = 0.86) of the ASSQ were acceptable. The ASSQ demonstrated good agreement with the SMP (Cohen’s kappa = 0.84) which yielded a diagnostic sensitivity of 81%, specificity of 93%, positive predictive value of 87%, and negative predictive value of 90%. There were 25.1% of athletes identified to have clinically relevant sleep disturbances that required further clinical sleep assessment. Sleep improved from time 1 at baseline to after the recommendations at time 3.

Conclusions

Sleep screening athletes with the ASSQ provides a method of accurately determining which athletes would benefit from preventative measures and which athletes suffer from clinically significant sleep problems. The process of sleep screening athletes and providing recommendations improves sleep and offers a clinical intervention output that is simple and efficient for teams and athletes to implement.

Electronic supplementary material

The online version of this article (10.1186/s40798-018-0140-5) contains supplementary material, which is available to authorized users.

The Effects of Sleep Extension on Sleep, Performance, Immunity and Physical Stress in Rugby Players

(1) Background: The purpose of the present study was to examine the efficacy of sleep extension in professional rugby players. The aims were to: (i) characterise sleep quantity in elite rugby players and determine changes in immune function and stress hormone secretion during a pre-season training programme; (ii) evaluate the efficacy of a sleep extension intervention in improving sleep, markers of physical stress, immune function and performance. (2) Methods: Twenty five highly trained athletes from a professional rugby team (age (mean ± SD) 25 ± 2.7 years; height 1.87 ± 0.07 m; weight 105 ± 12.1 kg) participated in a six week pre-post control-trial intervention study. Variables of sleep, immune function, sympathetic nervous activity, physiological stress and reaction times were measured. (3) Results: Sleep extension resulted in a moderate improvement in sleep quality scores ([mean; ± 90% confidence limits] −24.8%; ± 54.1%) and small to moderate increases in total sleep time (6.3%; ± 6.3%) and time in bed (7.3%; ± 3.6%). In addition, a small decrease in cortisol (−18.7%; ± 26.4%) and mean reaction times (−4.3%; ± 3.1%) was observed following the intervention, compared to the control. (4) Conclusions: Professional rugby players are at risk of poor sleep during pre-season training, with concomitant rises in physical stress. Implementing a sleep extension programme among professional athletes is recommended to improve sleep, with beneficial changes in stress hormone expression and reaction time performance.

A Subjective Assessment of the Prevalence and Factors Associated with Poor Sleep Quality Amongst Elite Japanese Athletes

Background

The amount, quality, and timing of sleep are considered important for athletes’ ability to train, maximize training responses, and recover. However, some research has shown that elite athletes do not obtain sufficient sleep. Based on this background, researchers recently started to assess and manage sleep in elite athletes.

The purpose of this study was to clarify the prevalence of poor sleep quality and its associated factors amongst elite Japanese athletes.

Methods

Eight hundred and ninety-one candidates for the 17th Asian Games Incheon 2014, who were over 20 years old, participated in this study. They completed a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, two-question case-finding instruments, and a checklist for sleep hygiene. Data from 817 of the 891 athletes (91.7%) with no missing values were analyzed.

Results

The mean time in bed was 7 h and 29 min. Two hundred and twenty-nine (28.0%) athletes showed a PSQI global score above the clinical criteria. A multiple logistic analysis revealed that sleep quality was significantly associated with five factors: “time in bed,” “eating breakfast every morning,” “avoiding the use of electronic devices (PC, smartphone, etc.) just before bedtime,” “depressive mood”, and “not thinking about troubles while in bed.” Forty percent of athletes reported they had been informed by someone about “snoring loudly” and/or “leg twitching or jerking during sleep.”

Conclusions

The results of this study demonstrate that 28% of the athletes showed the PSQI score above the cutoff for poor sleep quality (> 5.5), which suggests that there may be a high prevalence of poor sleep quality in this population of athletes. To improve athletes’ sleep, the five factors associated with sleep quality should be emphasized in athletes’ sleep education. Furthermore, in medical evaluations of athletes, it may be desirable to include screening for sleep disorders.

Self-Reported Perceptions of Sleep Quality and Resilience Among Dance Students

This study examined relationships between self-perceived sleep quality and resilience among 116 dance students (Mean age = 21.6 years; SD = 4.348). who self-reported sleep quality with the Pittsburgh Sleep Quality Index (PSQI) and personal resilience with the Resilience Scale (RS). Most participants (59.5%) reported poor sleep quality on the PSQI, with 62.9% of the women and 42.1% of the men ( p = .092) scoring higher than five points on this instrument. On the RS, a large majority of the participants (75%) obtained scores less than 147, indicating low resilience, with no significant gender differences observed. Those reporting poor sleep quality (PSQI scores > 5) obtained lower resilience scores (RS < 147) than those reporting good sleep quality (PSQI scores ≤ 5; p = .025), and participants with poorer sleep quality were at higher risk of low resilience (Odds Ratio = 3.273) relative to those with good sleep quality ( p = .006). Those with shorter duration sleep (claiming they slept <7 hours/night) were also at higher risk for low resilience (Odds Ratio = 3.266), relative to those with longer duration sleep (>7 hours/night). These findings can help students and dance professionals improve their performance and face pressures inherent in dance practice. Follow-up research should verify these findings in varied populations with objective sleep measures and observational data from multiple respondents.

Differences Between Sleep Logs and Actigraphy Combined With Electroencephalography in Adults With Sleep Disturbances

BACKGROUND

Actigraphy plus single-channel electroencephalography (EEG) has a high agreement with polysomnography and is considered a simple method for monitoring sleep at home. No studies, however, have evaluated its agreement with sleep logs.

PURPOSE

A sleep log was compared to a single-channel EEG in adults with sleep disturbances. The determinants of the agreement between the two recording methods were explored.

METHOD

This prospective comparison substudy included 71 participants aged 22-67 years sampled from a previous study of nonpharmacological therapy for sleep disturbances. The participants concurrently used a sleep log and a single-channel EEG machine for 6 days to measure their sleep at home. Total sleep time (TST) and sleep onset latency (SOL) were compared.

RESULTS

Correlations between measurements were .43 for TST ( p < .001) and .30 ( p < .01) for SOL. Bland-Altman analysis revealed that the mean bias between methods was 81.54 min (standard deviation [ SD] = 66.72 min) for TST and 5.58 min ( SD = 25.38 min) for SOL. SDs for both TST and SOL were higher for the sleep log than for EEG. A multivariate linear regression model demonstrated that age (standardized coefficient β = .42, p = .001) was a significant predictor of the mean difference in SOL measurements, accounting for 13.7% of the total variance in the mean difference.

CONCLUSION

Sleep log and single-channel EEG sleep measures are distinct from one another, and age predicts the mean level of disagreement between the two measures in adults with sleep disturbances.

Does Elite Sport Degrade Sleep Quality? A Systematic Review

BACKGROUND

Information on sleep quality and insomnia symptomatology among elite athletes remains poorly systematised in the sports science and medicine literature. The extent to which performance in elite sport represents a risk for chronic insomnia is unknown.

OBJECTIVES

The purpose of this systematic review was to profile the objective and experienced characteristics of sleep among elite athletes, and to consider relationships between elite sport and insomnia symptomatology.

METHODS

Studies relating to sleep involving participants described on a pre-defined continuum of 'eliteness' were located through a systematic search of four research databases: SPORTDiscus, PubMed, Science Direct and Google Scholar, up to April 2016. Once extracted, studies were categorised as (1) those mainly describing sleep structure/patterns, (2) those mainly describing sleep quality and insomnia symptomatology and (3) those exploring associations between aspects of elite sport and sleep outcomes.

RESULTS

The search returned 1676 records. Following screening against set criteria, a total of 37 studies were identified. The quality of evidence reviewed was generally low. Pooled sleep quality data revealed high levels of sleep complaints in elite athletes. Three risk factors for sleep disturbance were broadly identified: (1) training, (2) travel and (3) competition.

CONCLUSION

While acknowledging the limited number of high-quality evidence reviewed, athletes show a high overall prevalence of insomnia symptoms characterised by longer sleep latencies, greater sleep fragmentation, non-restorative sleep, and excessive daytime fatigue. These symptoms show marked inter-sport differences. Two underlying mechanisms are implicated in the mediation of sport-related insomnia symptoms: pre-sleep cognitive arousal and sleep restriction.

Self-reported sleep quantity, quality and sleep hygiene in elite athletes

Sleep is essential for recovery and performance in elite athletes. While actigraphy-based studies revealed suboptimal sleep in athletes, information on their subjective experience of sleep is scarce. Relatively unexplored is also the extent to which athletes' sleep is adversely affected by environmental conditions and daytime behaviours, that is sleep hygiene. This study aimed to provide insight in sleep quantity, quality and its putative association with sleep hygiene. Participants were 98 elite (youth) athletes competing at the highest (inter-)national level. Sleep quantity, quality and sleep hygiene were assessed once covering a 1-month period by using established (sub)clinical questionnaires, and repeatedly during 7 consecutive days. Sleep quality was generally healthy, although 41% of all athletes could be classified as 'poor sleeper', and 12% were identified as having a sleep disorder. Daily self-monitoring revealed sleep durations of 8:11 ± 0:45 h, but elevated wake after sleep onset of 13 ± 19 min. Sleep quality, feeling refreshed, and morning vigor were moderate at best. Regarding sleep hygiene, general measures revealed irregular sleep-wake patterns, psychological strain and activating pre-sleep behaviours. At the daily level, blue-light exposure and late-evening consumption of heavy meals were frequently reported. General sleep hygiene revealed significant associations with sleep quality (0.45 < r > 0.50; P < 0.001). Results indicate that there is ample room for optimization, specifically in onset latency and in wake after sleep onset. Subtle improvements in sleep seem possible, and optimizing sleep hygiene, such as regular sleep-wake patterns and reducing psychological strain, may facilitate this sleep upgrading process.

Sleep Applications to Assess Sleep Quality

This article highlights the potential uses that smartphone applications may have for helping those with sleep problems. Applications in smartphones offer the promised possibility of detection of sleep. From the author's own experience, one can also conclude that sleep applications are approximately as good as polysomnography in detection of sleep time, similar to the conventional wearable actimeters. In the future, sleep applications will help to further enhance awareness of sleep health and to distinguish those who actually poorly and only briefly sleep from those who suffer more likely from paradox insomnia.