Sleep monitoring of a six-day microcycle in strength and high-intensity training

Exploring the impact of sleep on emotional and physical well-being in professional cricketers: a cohort study over an in-season training period

Background

Professional athletes navigate a multitude of unique challenges associated to sport-specific factors (e.g., training, travel and competition) and non-sport factors (e.g., performance pressure, stress and anxiety) that can interfere with healthy sleep behaviors. Sleep plays a key role in proper biopsychosocial development as well as short- and long-term biological, physical, psychological, and cognitive health. As poor sleep quality is known to impair proper brain function, this study aimed to investigate the effect of sleep quality on a professional athlete's ability to train, recover, and perform, as well as their overall emotional and physical well-being.

Methods

A cohort study was performed in 40 professional male cricket athletes from the Dutch national cricket team (mean age 26.5 ± 5.1 years). The athletes were monitored across a 22 weeks in-season training period. Sleep quality and overall emotional and physical well-being were assessed using daily sleep diaries and questionnaires which scored the readiness to train, stress levels, fatigue, muscle soreness and flu symptoms respectively. Quality of sleep and subsequent association with the consecutive elements of the well-being questionnaire were assessed through statistical using the student t-test and clinical differences with the methodology of Osoba and colleagues: <5% "no change", 5%-10% "little change"; 10%-20% "moderate change"; and >20% "very much change".

Results

The results demonstrated that the professional athletes assessed their sleep quality as average with a mean score of 3.4 out of 5. Lower perceived quality of sleep (<75th percentile) was correlated with a decreased readiness to train (mean score 3.2 [IQR: 3.0-4.0] vs. 3.5 [IQR: 3.0-5.0]; P < 0.001) and increased extent of muscle soreness (2.7 [IQR: 2.0-3.0] vs. 2.3 [IQR: 2-3]; P < 0.001), stress level (mean score 2.3 [IQR: 2.0-3.0] vs. 1.9 [IQR: 1.0-2.0]; P < 0.001) and perceived fatigue (mean score 2.9 [IQR: 2.0-3.0] vs. 2.3 [IQR: 2.0-3.0]; P < 0.001). Likewise, in patients with lower perceived quality of sleep, the proportion of players presenting with flu symptoms increased over 4-fold (4.1% vs. 17%; P < 0.001).

Conclusions

This study highlights that good sleep quality positively influences the overall emotional and physical well-being of professional athletes. Our results emphasize the importance of targeted sleep interventions to improve sleep quality and subsequently optimize psychological and physiological wellness.

Interval training has more negative effects on sleep in adolescent speed skaters: a randomized cross controlled trial

Objective

Sleep is an essential component of athletic performance and recovery. This study aimed to investigate the effects of different types of high-intensity exercise on sleep parameters in adolescent speed skaters.

Methods

Eighteen male adolescent speed skaters underwent aerobic capacity testing, Wingate testing, and interval training in a randomized crossover design to assess strength output, heart rate, and blood lactate levels during exercise. Sleep quality after each type of exercise was evaluated using the Firstbeat Bodyguard 3 monitor.

Results

The results showed that Wingate testing and interval training led to decreased sleep duration, increased duration of stress, decreased RMSSD, and increased LF/HF ratio (p < 0.01). Conversely, aerobic capacity testing did not significantly affect sleep (p > 0.05). The impact of interval training on sleep parameters was more significant compared to aerobic capacity testing (p < 0.01) and Wingate testing (p < 0.01).

Conclusion

High-intensity anaerobic exercise has a profound impact on athletes' sleep, primarily resulting in decreased sleep duration, increased stress duration, decreased RMSSD, and increased LF/HF ratio.

To Sleep Dreaming Medals: Sleep Characteristics, Napping Behavior, and Sleep-Hygiene Strategies in Elite Track-and-Field Athletes Facing the Olympic Games of Tokyo 2021

PURPOSE

Few data are available on sleep characteristics of elite track-and-field athletes. Our study aimed to assess (1) differences in sleep between sexes and among different track-and-field disciplines, (2) the effect of individualized sleep-hygiene strategies on athletes' sleep parameters, and (3) daytime nap characteristics in track-and-field athletes.

METHODS

Sleep characteristics of 16 elite Olympic-level track-and-field athletes (male: n = 8; female: n = 8) were assessed during the preseason period, at baseline (T0), and during the in-season period, after the adoption of individualized sleep-hygiene strategies (T1). Sleep parameters were objectively monitored by actigraphy for a minimum of 10 days, for each athlete, at both T0 and T1. A total of 702 nights were analyzed (T0 = 425; T1 = 277).

RESULTS

Female athletes displayed better sleep efficiency (88.69 [87.69-89.68] vs 91.72 [90.99-92.45]; P = .003, effect size [ES]: 0.44), lower sleep latency (18.99 [15.97-22.00] vs 6.99 [5.65-8.32]; P < .001, ES: 0.65), higher total sleep time (07:03 [06:56-07:11] vs 07:18 [07:10-07:26]; P = .030, ES: 0.26), earlier bedtime (00:24 [00:16-00:32] vs 00:13 [00:04-00:22]; P = .027, ES: 0.18), and lower nap frequency (P < .001) than male athletes. Long-distance runners had earlier bedtime (00:10 [00:03-00:38] vs 00:36 [00:26-00:46]; P < .001, ES: 0.41) and wake-up time (07:41 [07:36-07:46] vs 08:18 [08:07-08:30]; P < .001, ES: 0.61), higher nap frequency, but lower sleep efficiency (88.79 [87.80-89.77] vs 91.67 [90.95-92.38]; P = .013, ES: 0.44), and longer sleep latency (18.89 [15.94-21.84] vs 6.69 [5.33-8.06]; P < .001, ES: 0.67) than athletes of short-term disciplines. Furthermore, sleep-hygiene strategies had a positive impact on athletes' total sleep time (429.2 [423.5-434.8] vs 451.4 [444.2-458.6]; P < .001, ES: 0.37) and sleep latency (14.33 [12.34-16.32] vs 10.67 [8.66-12.68]; P = .017, ES: 0.19).

CONCLUSIONS

Sleep quality and quantity were suboptimal at baseline in Olympic-level track-and-field athletes. Large differences were observed in sleep characteristics between sexes and among different track-and-field disciplines. Given the positive effect of individualized sleep-hygiene strategies on athlete's sleep, coaches should implement sleep education sessions in the daily routine of top-level athletes.

Blood and Salivary Cortisol Variations in Athletes in Relation to Cardiopulmonary Exercise Testing

Background and Objectives: Cortisol is a valuable marker for assessing the body's response to any form of stress. We conducted this study in order to evaluate the variations of salivary and serum cortisol levels in professional football players in relation to cardiopulmonary exercise testing (CPET) and their significance in potentially evaluating overtraining in athletes. Also, the question of whether salivary cortisol determination could fully substitute serum sampling was addressed. Materials and Methods: A total of 19 male professional football players were evaluated by measuring serum cortisol levels at rest (T0) and immediately after a CPET (T1) and salivary cortisol levels at rest (T0), 10 min after a CPET (T2), and 30 min after a CPET (T3). Results: T0 serum cortisol showed a statistically significant correlation with the oxygen uptake at the anaerobic threshold divided by the body weight (VO2-AT/weight), as did the T2 salivary cortisol with the maximum oxygen uptake at the anaerobic threshold (VO2-AT) and VO2-AT/weight. T0 salivary cortisol was significantly correlated with the subjects' height and the predicted O2 pulse. Conclusions: While some correlations were discovered, they are insufficient to recommend cortisol as a routine biomarker in athletes' evaluation. However, significant correlations were established between salivary and serum determinations, meaning that the non-invasive procedure could substitute venous blood sampling.

Which Dark Personality Traits Could Predict Insomnia? The Mediated Effects of Perceived Stress and Ethical Judgments

This study aimed to investigate the relationship between dark personality traits and insomnia by considering the mediated effects of perceived stress and ethical judgments. This descriptive and correlational study was conducted with 464 university athlete students from individual and team sports. Dark Triad Scale (DTS), Insomnia Severity Index (ISI), Perceived Stress Scale (PSS), and Moral Content Judgment in Sport Questionnaire (MCJSQ) were used. Significant correlation coefficients were observed between the dark personality traits and other variables. Regression analysis showed that psychopathy (about 19%) and ethical judgments (about 16%) could predict insomnia. It was shown that among dark personality traits, psychopathy along with ethical judgments could predict insomnia.

Relationships between Heart Rate Variability, Sleep Duration, Cortisol and Physical Training in Young Athletes

The aims of the current study were to examine the relationships between heart rate variability (HRV), salivary cortisol, sleep duration and training in young athletes. Eight athletes (16 ± 1 years) were monitored for 7 weeks during training and competition seasons. Subjects were training for endurance-based winter sports (cross-country skiing and biathlon). Training was divided into two zones (K1, easy training and K2, hard training). Heart rate and blood lactate during submaximal running tests (SRT), as well as cortisol, sleep duration and nocturnal HRV (RMSSD), were determined every other week. HRV and cortisol levels were correlated throughout the 7-week period (r = -0.552, P = 0.01), with the strongest correlation during week 7 (r = -0.879, P = 0.01). The relative changes in K1 and HRV showed a positive correlation from weeks 1-3 (r = 0.863, P = 0.006) and a negative correlation during weeks 3-5 (r = -0.760, P = 0.029). The relative change in sleep during weeks 1-3 were negatively correlated with cortisol (r = -0.762, P = 0.028) and K2 (r = -0.762, P = 0.028). In conclusion, HRV appears to reflect the recovery of young athletes during high loads of physical and/or physiological stress. Cortisol levels also reflected this recovery, but significant change required a longer period than HRV, suggesting that cortisol may be less sensitive to stress than HRV. Moreover, our results indicated that during the competition season, recovery for young endurance athletes increased in duration and additional sleep may be beneficial.

Effects of High-Intensity Interval Training on Sleep: A Systematic Review and Meta-Analysis

Objectives: To use a quantitative approach to examine the effects of high-intensity interval training (HIIT) interventions on sleep for adults. Methods: PubMed, Ebsco, Web of Science, Cochrane Central Register of Controlled Trials, the China National Knowledge Infrastructure, and Wanfang Data were searched from their inception to December 2020. Intervention studies with a control group that examined the effects of HIIT interventions on sleep were included in this meta-analysis. The risk of bias was assessed using the tool provided by the Cochrane Handbook for Systematic Reviews of Interventions. Effect sizes (ESs), calculated as weighted mean difference (WMD) and standardized mean difference (SMD), were used to examine the effects of objective outcomes and subjective outcomes separately. Results: A large increase in sleep quality (SQ) reflected by the Pittsburgh Sleep Quality Index global scores [WMD = −0.90, 95%CI (−1.72, −0.07), p = 0.03, n = 8] and a small-to-medium favorable effect on sleep efficiency (SE) [SMD = 0.43, 95%CI (0.20, 0.65), p = 0.0002, n = 10] were found after HIIT intervention. In addition, sub-analyses results suggest that ESs were moderated by the type, duration and frequency, as well as the length of the HIIT intervention. Conclusions: HIIT may be a promising way to improve overall subjective SQ and objective SE. PROSPERO, protocol registration number: CRD42021241734.

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.

Psychometric Properties of the RESTQ-Sport-36 in a Collegiate Student-Athlete Population

The purpose of the current study was to examine the reliability and validity of the RESTQ-Sport-36 for use in the collegiate student-athlete population. A total of 494 collegiate student-athletes competing in National Collegiate Athletic Association Division I, II, or III sanctioned sport completed the RESTQ-Sport-36 and Brief Profile of Mood States (POMS). Structural equation modeling (SEM) procedures were used to compare first order to hierarchical model structures. Results of a confirmatory factor analysis (χ²[528] = 1129.941, p < 0.001; SRMR = 0.050; CFI = 0.929) and exploratory structural equation modeling analysis (χ²[264] = 575.424, p < 0.001; SRMR = 0.013; CFI = 0.963) indicated that the first order 12-factor structure demonstrated the best fit of all models tested. Support was not observed for the fit of any hierarchical model. Moderate to strong correlations were observed between stress and recovery subscales and mood states, thus supporting the construct validity of the abbreviated RESTQ measurement model. The current findings provide support for the measure's use in this population and give pause as it relates to the scoring and interpretation of hierarchical factors such as Total Stress and Total Recovery. Overall, the current results indicate that the RESTQ-Sport-36 may be a useful tool for collegiate student-athlete training load and competition monitoring.

Prevalence of poor sleep quality in athletes before competition

OBJECTIVES

The purpose of this study was to investigate athletes sleep quality before competition and its relationship with age, gender, sport modality, competitive level, competition result, and practice time.

METHODS

The sample was 1010 Brazilian athletes (656 men and 354 women; 511 young and 499 adults), with an age of 20 ± 7 years old. Participants answered the question 'How would you evaluate the quality of your sleep in the past few days?' Participants rated their sleep quality on a Likert-type scale as follows: 1 = very poor, 2 = poor, 3 = regular, 4 = good, 5 = excellent.

RESULTS

Young athletes were 2.30 times more likely to experience poor sleep than adult athletes (p < 0.01; 95% Confidence Interval [CI] = 1.47-3.61). Individual athletes were 3.45 times more likely to present poor sleep compared to athletes of team sports (p = 0.00; 95% CI = 2.18-5.48). International athletes were 1.71 times more likely to present regular sleep compared to regional athletes (p = 0.01; 95% CI = 1.16-2.51). Conclusions: Thus, our study indicates that young, individual sports, and international athletes may be at higher risk of poor sleep quality before competitions.

The First-Night Effect in Elite Sports: An Initial Glance on Polysomnography in Home-Based Settings

Self-applied portable polysomnography is considered a promising tool to assess sleep architecture in field studies. However, no findings have been published regarding the appearance of a first-night effect within a sport-specific setting. Its absence, however, would allow for a single night sleep monitoring and hence minimize the burden on athletes while still obtaining the most important variables. For this reason, the aim of the study was to assess whether the effect appears in home-based sleep monitoring of elite athletes. The study sample included eight male and 12 female German elite athletes from five different sports. Participants slept with a portable polysomnography for two nights, which they self-applied at night before going to bed. Time in bed and wake-up time in the morning were freely chosen by each individual athlete without any restrictions regarding time or sleeping environment. Participants were asked to keep the same location and time frame during the two days of monitoring and stick to their usual sleeping schedules. Sleep stages were manually scored using 30-s epochs. Sleep parameters and stages were later compared with the help of linear mixed models to investigate the factor time. Significant differences between the two nights were found for percentage of Non-REM sleep [T(19) = -2,10, p < 0.05, d = -0.47, 95%-CI (-7.23, -0.01)] with small effect size, Total Wake Time [T(19) = 2.30, p = 0.03, d = 0.51, 95%-CI (1.66, 35.17)], Sleep Efficiency [T(19) = -2.48, p = 0.02, d = -0.55, 95%-CI (-7.43, -0.63)], and Wake percentage [T(19) = 2.47, p = 0.02, d = 0.55, 95%-CI (0.61, 7.43)] with moderate effect sizes, and N3 Sleep Onset Latency [T(19) = 3.37, p < 0.01, d = 0.75, 95%-CI (7.15, 30.54)] with large effect size. Confidence Intervals for all other indices range from negative to positive values and hence specify, that parameters were not systematically negatively affected in the first night. Findings suggest that some individuals are more affected by the first-night effect than others. Yet, in order to keep the measurement uncertainties to a minimum, a more conservative approach with at least two monitoring nights should be used whenever possible, if no other supporting information on the athletes says otherwise.

To Nap or Not to Nap? A Systematic Review Evaluating Napping Behavior in Athletes and the Impact on Various Measures of Athletic Performance

PURPOSE

The objective of this systematic review was to 1) determine how studies evaluated napping behavior in athletes (frequency, duration, timing and measurement); 2) explore how napping impacted physical performance, cognitive performance, perceptual measures (eg, fatigue, muscle soreness, sleepiness and alertness), psychological state and night-time sleep in athletes.

METHODS

Five bibliographic databases were searched from database inception to 11 August 2020. Observational and experimental studies comprising able-bodied athletes (mean age ≥12 years), published in English, in peer-reviewed journal papers were included. The Downs and Black Quality Assessment Checklist was used for quality appraisal.

RESULTS

Thirty-seven studies were identified of moderate quality. Most studies did not include consistent information regarding nap frequency, duration, and timing. Napping may be beneficial for a range of outcomes that benefit athletes (eg, physical and cognitive performance, perceptual measures, psychological state and night-time sleep). In addition, napping presents athletes with the opportunity to supplement their night-time sleep without compromising sleep quality.

CONCLUSION

Athletes may consider napping between 20 to 90 min in duration and between 13:00 and 16:00 hours. Finally, athletes should allow 30 min to reduce sleep inertia prior to training or competition to obtain better performance outcomes. Future studies should include comprehensive recordings of nap duration and quality, and consider using sleep over a 24 hour period (daytime naps and night-time sleep period), specifically using objective methods of sleep assessment (eg, polysomnography/actigraphy).

Sleep quality monitoring in individual sports athletes: parameters and definitions by systematic review

In the present review, we identify which instruments and parameters are used for sleep quality monitoring in individual sport athletes and which definitions were used for sleep quality parameters in this literature field. Systematic searches for articles reporting the qualitative markers related to sleep in team sport athletes were conducted in PubMed, Scopus and Web of Science online databases. The systematic review followed the Preferred Reporting Items for Systematic Reviews. The initial search returned 3316 articles. After the removal of duplicate articles, eligibility assessment, 75 studies were included in this systematic review. Our main findings were that the most widely used measurement instruments were Actigraphy (25%), Rating Likert Scales (16%) and Sleep Diary (13%). On sleep quality parameters (Sleep duration = 14%; Wake after sleep onset = 14%; Sleep Quality = 12%; Sleep Effciency = 11% and Sleep Latency = 9%), the main point is that there are different definitions for the same parameters in many cases reported in the literature. We conclude that the most widely used instruments for monitoring sleep quality were Actigraphy, Likert scales and Sleep diary. Moreover, the definitions of sleep parameters are inconsistent in the literature, hindering the understanding of the sleep-sport performance relationship.

Changes in Perceived Exertion, Well-Being, and Recovery During Specific Judo Training: Impact of Training Period and Exercise Modality

The present study investigated the effect of intense and tapering training periods using different exercise modalities (i.e., Randori – grip dispute practice without throwing technique, Uchi-komi – technique repetition training, and sprinting) on rating of perceived exertion (RPE), well-being indices, recovery state, and physical enjoyment in judo athletes. Sixty-one adolescent male and female judo athletes (age: 15 ± 1 years) were randomly assigned to one of three experimental or one control groups. Experimental groups (Randori, Uchi-komi, and running) trained four times per week for 4 weeks of intense training (in addition to their usual technical-tactical judo training; control group underwent only such a training) followed by 12 days of tapering. RPE, well-being indices [i.e., sleep, stress, fatigue, and delayed onset muscle soreness (DOMS)], total quality of recovery (TQR), and physical enjoyment were measured every session. RPE, sleep, stress, fatigue, DOMS, Hooper index (HI; sum of wellbeing indices), and TQR were lower in the tapering compared with the intensified training period (P < 0.001). Moreover, the running group showed better values for sleep (P < 0.001), stress (P < 0.001), fatigue (P = 0.006), DOMS (P < 0.001), and HI (P < 0.001) in comparison with the other training groups, indicating a more negative state of wellbeing. The Randori and Uchi-komi groups showed higher values for TQR and physical enjoyment (both P < 0.001) than the running group, whereas RPE was lower in the control compared with all training groups (P < 0.001). Coaches should use more specific training modalities (i.e., Randori and Uchi-komi) during intensified training and should monitor well-being indices, RPE, and TQR during training periods. Moreover, for all variables, 12 days tapering period are beneficial for improving wellbeing and recovery after 4 weeks of intense training.

Integrating high-intensity interval training into the workplace: The Work-HIIT pilot RCT

The purpose of this study was to assess the feasibility and preliminary efficacy of a high-intensity interval training (HIIT) intervention integrated into the workplace on physical and mental health outcomes in a sample of adults. The Work-HIIT intervention was evaluated at the University of Newcastle (March-July 2019). University employees (18+ years) who self-identified as predominantly sedentary at work (n = 47, 43.0 ± 10.7 years; 41 female) were recruited, screened, and randomized after baseline assessments into Work-HIIT (n = 24) or wait-list control (n = 23) conditions. Participants were asked to attend 2-3 researcher-facilitated HIIT sessions/week (weeks 1-8). Sessions included a 2-minute gross-motor warm-up, followed by various combinations of aerobic and muscular fitness exercises lasting 8 minutes (using 30:30 second work: rest intervals). Program feasibility was assessed using measures of satisfaction, compliance, adherence, fidelity, and retention. Physiological and psychological outcomes were measured at baseline and 9 weeks. Feasibility data were investigated using descriptive statistics and efficacy outcomes determined using linear mixed models and Cohen's d effect sizes. Participant ratings showed high levels of satisfaction (4.6/5); 71% of participants attended ≥2 sessions/wk and averaged 85.9% HR_max across all sessions (including rest and work intervals). Small-to-medium positive effects resulted for cardiorespiratory fitness [+2.9 laps, 95% CI (-4.19-10.14); d = 0.34] and work productivity [+0.26, d = 0.47]. Large positive effects resulted for muscular fitness [push-ups +3.5, d = 0.95; standing jump +10.1 cm, d = 1.12]; HIIT self-efficacy [+16.53, d = 1.57]; sleep [weekday +0.76 hours, d = 1.05]; and autonomous motivation [+0.23, d = 0.76]. This study supports the feasibility and preliminary efficacy of facilitator-led Work-HIIT as a time-efficient, enjoyable, and convenient workplace exercise option for adults.

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.

Exercise Time and Intensity: How Much Is Too Much?

The growing prevalence and popularity of interval training necessitate additional guidelines in regard to maximal levels of time and intensity.

PURPOSE

To correlate salivary hormones and time in varying heart-rate (HR) zones. The hypothesis was that chronic exercise durations >9% of total exercise time in the >90% maximum HR zone would lead to decreased variation in salivary cortisol concentration after exercise in a 2-bout high-intensity protocol compared with less or more time in this zone.

METHODS

A total of 35 healthy adults who regularly exercised for an average of 8 hours per week recorded their HR during every training session for 3 weeks. Later, they completed an experimental day composed of two 30-minute high-intensity interval sessions separated by 4 hours of nonactive recovery. The authors collected saliva samples before, immediately following, and 30 minutes after each exercise session to assess changes in cortisol concentrations.

RESULTS

There was a correlation between weekly time training at an intensity >90% maximum HR and the variables associated with overtraining. Salivary cortisol concentration fluctuated less in the participants who exercised in this extreme zone for >40 minutes per week (P < .001).

CONCLUSION

Based on the current study data, for individuals who regularly exercise, 4% to 9% total training time above 90% maximum HR is the ideal duration to maximize fitness and minimize symptoms related to overreaching.

Innovative Use of Wrist-Worn Wearable Devices in the Sports Domain: A Systematic Review

Wrist wearables are becoming more and more popular, and its use is widespread in sports, both professional and amateur. However, at present, they do not seem to exploit all their potential. The objective of this study is to explore innovative proposals for the use of wearable wrist technology in the field of sports, to understand its potential and identify new challenges and lines of future research related to this technology. A systematic review of the scientific literature, collected in 4 major repositories, was carried out to locate research initiatives where wrist wearables were introduced to address some sports-related challenges. Those works that were limited to evaluating sensor performance in sports activities and those in which wrist wearable devices did not play a significant role were excluded. 26 articles were eventually selected for full-text analysis that discuss the introduction of wrist-worn wearables to address some innovative use in the sports field. This study showcases relevant proposals in 10 different sports. The research initiatives identified are oriented to the use of wearable wrist technology (i) for the comprehensive monitoring of sportspeople’s behavior in activities not supported by the vendors, (ii) to identify specific types of movements or actions in specific sports, and (iii) to prevent injuries. There are, however, open issues that should be tackled in the future, such as the incorporation of these devices in sports activities not currently addressed, or the provision of specific recommendation services for sport practitioners.

Portable PSG for sleep stage monitoring in sports: Assessment of SOMNOwatch plus EEG

Current sport-scientific studies mostly neglect the assessment of sleep architecture, although the distribution of different sleep stages is considered an essential component influencing an athlete's recovery and performance capabilities. A mobile, self-applied tool like the SOMNOwatch plus EEG might serve as an economical and time-friendly alternative to activity-based devices. However, self-application of SOMNOwatch plus EEG has not been validated against conventional polysomnography (PSG) yet. For evaluation purposes, 25 participants (15 female, 10 male; M _age = 22.92 ± 2.03 years) slept in a sleep laboratory on two consecutive nights wearing both, conventional PSG and SOMNOwatch plus EEG electrodes. Sleep parameters and sleep stages were compared using paired t-tests and Bland-Altman plots. No significant differences were found between the recordings for Sleep Onset Latency, stages N1 to N3 as well as Rapid Eye Movement stage. Significant differences (Bias [95%-confidence interval]) were present between Total Sleep Time (9.95 min [-29.18, 49.08], d = 0.14), Total Wake Time (-13.12 min [-47.25, 23.85], d = -0.28), Wake after Sleep Onset (-11.70 min [-47.25, 23.85], d = -0.34) and Sleep Efficiency (2.18% [-7.98, 12.34], d = 0.02) with small effect sizes. Overall, SOMNOwatch plus EEG can be considered a valid and practical self-applied method for the examination of sleep. In sport-scientific research, it is a promising tool to assess sleep architecture in athletes; nonetheless, it cannot replace in-lab PSG for all clinical or scientific purposes.

Sleep quality associated with mood in elite athletes

Objectives: This study aimed to analyze the association between sleep quality and mood in elite athletes of different competitive levels. Methods: Participants were 1041 elite athletes (aged 20.82 ± 6.62 years), with 671 men (64.5%/21.52 ± 6.90 years) and 370 women (35.5%/19.55 ± 5.89 years) from 10 individual sports and 6 team sports. Participants self-reported sleep quality on a Likert-type scale and mood was measured with the Brunel Mood Scale (BRUMS). The data were analyzed using the Kruskal-Wallis test, and binary logistic regression. Results: Results revealed that athletes who compete internationally are 84% more likely to have poor sleep quality than athletes who compete at a regional level. International athletes with good sleep quality showed greater vigor. National athletes with poor sleep quality showed more confusion, depression, and fatigue. Thus, mood and competitive level are factors associated with sleep quality. Confusion, fatigue, and tension impair sleep, and vigor reduces the likelihood of poor sleep. Conclusions: Sleep should be monitored, especially in international level athletes, in order to prevent sleep disorders during competitions. Coaches and athletes should use techniques and strategies for appropriate management of sleep and mood, to maintain the athletes in optimal condition before important competitions.

Psychophysical stress and strain of maritime pilots in Germany. A cross-sectional study

Introduction

Maritime pilots work in an irregular deployment system (rotation system) with unpredictable work assignments under high levels of physical and mental stress. Fatigue or chronic diseases, e.g. coronary heart disease, peptic ulcers or gastritis can occur as a consequence. This can lead to long-term limitations of pilots’ work ability. The aim of this study is to analyse current stress and strain in maritime pilots.

Methods

Initially, all German pilots were interviewed with an online questionnaire about their living and working situation (response rate 43%). Subsequently, a medical and psychological examination of a random sample was carried out with pilots working in a 4-month rotation system compared with those working in a 1-week system. Most of the measurements took place at the beginning and the end of continuous work assignments each lasting several weeks (pre vs post-rotation). The questionnaires RESTQ-work 27, Resilience Scale RS-13 and Berlin Questionnaire were used as well as a sleeping diary. Furthermore, cardiovascular parameters (during rest and under ergometric stress), activity and blood parameters, urine stress hormones, and the pupillary unrest index were surveyed.

Results

60 pilots were recorded with an average age of 48.7 years (SD 8.3 years). Among the parameters collected, there were no significant differences between pre and post-rotation examinations. Pilots with a 4-month rotation system experienced a much higher subjective strain level in RESTQ work-27 (OR 10.12 (95% CI 1.21–84.59)). According to the sleep diaries of the pilots working in a 4-month rotation system, reduced levels were found concerning the pre and post-rotation subjective performance level (p = 0.042 and 0.029), subjective sleep duration (p = 0.032) and current subjective feeling post-rotation (p = 0.036). Objectively measured arterial hypertension was significantly more frequent among pilots working 4 months at a time (OR 21.41 (95% CI 1.26–364.05)). In addition, elevated levels of total cholesterol, triglycerides and uric acid were more common among this group of pilots (p = 0.038, p = 0.033 and p = 0.038). In particular, the risk of hypertriglyceridemia was increased (OR 4.41 (95% CI 1.15–16.91)).

Discussion

Maritime pilotage represents a very straining profession that has been studied very little up to this point. The present results indicate that 4-month rotation systems lead to higher levels of subjective and objective strain than 1-week rotation systems. Interventions are therefore recommended; especially a change in the rotation system should be considered.

Sleepiness of day workers and watchkeepers on board at high seas: a cross-sectional study

OBJECTIVES

To estimate the prevalence of sleepiness on duty among day workers and watchkeepers on board.

DESIGN

Cross-sectional survey in a maritime field study.

SETTING

10 shipping companies with container vessels under German management.

PARTICIPANTS

The whole crew (75 day workers and 123 watchkeepers) during 18 voyages on 18 different container ships.

OUTCOME MEASURES

Sleepiness on duty and efficiency of sleep using pupillometry (in a cross-shift design) and the SenseWear armband activity monitor.

RESULTS

The watchkeepers showed significantly shorter sleep periods than day workers (5.5 hours vs 5.8 hours). The average efficiency of sleep was 69.6% and significantly lower among watchkeepers (OR 0.48; 95% CI 0.26 to 0.88). 396 pupillometric examinations were carried out and revealed 88 study members (22.2%) with a pupillary unrest index (rPUI) in a range characterised as 'unfit for duty' and 110 seafarers (27.8%) categorised as 'particular attention required'. The average rPUI was similar between day workers and watchkeepers. The Epworth Sleepiness Scale revealed recent daytime sleepiness in 70 seafarers, which was similarly often stated by day workers and watchkeepers. Based on the Stanford Sleepiness Scale (SSS), a measurable cross-shift increase in the SSS value during the examined shift was observed, especially among watchkeepers. The amount of time already spent on the vessel at the time of the present examination was significantly associated with the rPUI (p=0.009).

CONCLUSION

Sleep periods of both the day workers and the watchkeepers aboard vessels were alarmingly short and sleep efficiency was low. Sleepiness on duty is similarly prevalent among day workers and watchkeepers and seems to depend partly on the cumulative working period on the vessels. Preventive measures need to be taken by the shipping industry to counteract fatigue (eg, by enabling sufficient rest and sleep times).

Sleep Patterns, Alertness, Dietary Intake, Muscle Soreness, Fatigue, and Mental Stress Recorded before, during and after Ramadan Observance

Ramadan is one of the pillars of the Islamic creed. Its observance commonly causes chrono-biological changes. The present study examined sleep and alertness during Ramadan observance relative to data collected before and after Ramadan in a sample of young, physically active men. Information was also collected on dietary intake, muscle soreness, fatigue, and mental stress over the three periods. Fourteen physically active men (age: 21.6 ± 3.3 years, height: 1.77 ± 0.06 m, body-mass: 73.1 ± 9.0 kg) completed the Hooper questionnaire and the Pittsburgh Sleep Quality Index (PSQI) and responded to the digit cancellation test (DCT) fifteen days before Ramadan, during the last ten days of Ramadan and 20 days after Ramadan. The PSQI results indicated that sleep duration was significantly longer before Ramadan (p = 0.003) and after Ramadan (p = 0.04) compared to during Ramadan and was longer before Ramadan than after Ramadan (p = 0.04). In addition, the sleep efficiency was lower during Ramadan in comparison to before Ramadan (p = 0.02) and after Ramadan (p = 0.04). The daytime dysfunction score increased during Ramadan in comparison with before Ramadan (p = 0.01) and after Ramadan (p = 0.04), and the sleep quality score was higher during (p = 0.003) and after Ramadan (p = 0.04) as compared to before Ramadan. The sleep disturbance score increased during Ramadan relative to before Ramadan (p = 0.04). However, Ramadan observance had no significant effect on sleep latency. Mental alertness also decreased at the end of Ramadan compared to before (p = 0.003) or after Ramadan (p = 0.01). Dietary intake, muscle soreness, fatigue, and mental stress as estimated by the Hooper questionnaire remained unchanged over the three periods of the investigation (p > 0.05). In conclusion, Ramadan observance had an adverse effect on sleep quantity and on mental alertness, but not on sleep quality. However, dietary intake, muscle soreness, fatigue, and mental stress remained unaffected.

Nocturnal Activity Is Not Affected by a Long-Duration, Low-Intensity Single Exercise Bout

The aim of the current study was to examine whether prolonged low-intensity aerobic exercise could affect nocturnal activity in healthy individuals. Twenty-one healthy adults (24 ± 3.7 years; 9 females) were enrolled in this study. All participants participated in a 3-h low-intensity walking exercise protocol. Standard biochemical indices were assessed before the exercise protocol and at 72 h. Nocturnal activity and various indices of health were recorded for five consecutive days. The score of muscle pain peaked the night after the exercise protocol (p < 0.05) and returned to baseline two days after. No statistical differences were found in any of the parameters examined, including nocturnal activity. Prolonged low-intensity exercise does not affect nocturnal activity. The anecdotal reports suggesting that exercise or/and physical activity could worsen symptoms of motor restlessness during sleep in sleep disorders, such as restless legs syndrome and periodic limb movements, are not supported by this study. However, these findings need to be verified in clinical populations, as well as by using protocols with different forms of exercise.

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.

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.

Monitoring Energy Expenditure Using a Multi-Sensor Device-Applications and Limitations of the SenseWear Armband in Athletic Populations

In order to monitor their energy requirements, athletes may desire to assess energy expenditure (EE) during training and competition. Recent technological advances and increased customer interest have created a market for wearable devices that measure physiological variables and bodily movement over prolonged time periods and convert this information into EE data. This mini-review provides an overview of the applicability of the SenseWear armband (SWA), which combines accelerometry with measurements of heat production and skin conductivity, to measure total daily energy expenditure (TDEE) and its components such as exercise energy expenditure (ExEE) in athletic populations. While the SWA has been shown to provide valid estimates of EE in the general population, validation studies in athletic populations indicate a tendency toward underestimation of ExEE particularly during high-intensity exercise (>10 METs) with an increasing underestimation as exercise intensity increases. Although limited information is available on the accuracy of the SWA during resistance exercise, high-intensity interval exercise, or mixed exercise forms, there seems to be a similar trend of underestimating high levels of ExEE. The SWA, however, is capable of detecting movement patterns and metabolic measurements even at high exercise intensities, suggesting that underestimation may result from limitations in the proprietary algorithms. In addition, the SWA has been used in the assessment of sleep quantity and quality as well as non-exercise activity thermogenesis. Overall, the SWA provides viable information and remains to be used in various clinical and athletic settings, despite the termination of its commercial sale.