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, selfapplied 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.

Both daily demands as well as training and competition characteristics in sports can result in a psychobiological state of mental fatigue leading to feelings of tiredness, lack of energy, an increased perception of effort, and performance decrements. Moreover, optimal performance will only be achievable if the balance between recovery and stress states is re-established. Consequently, recovery strategies are needed aiming at mental aspects of recovery. The aim of the study was to examine acute effects of potential mental recovery strategies (MR) on subjective-psychological and on cognitive performance outcomes after a mentally fatiguing task. A laboratory-based randomized cross-over study with twenty-four students (22.8 ± 3.6 years) was applied. Participants were run through a powernap intervention (PN), a systematic breathing intervention (SB), a systematic breathing plus mental imagery intervention (SB+), and a control condition (CC) with one trial a week over four consecutive weeks. Mental fatigue was induced by completion of the 60-min version of the AX-continuous performance test (AX-CPT). The Short Recovery and Stress Scale (SRSS) and Visual Analog Scales (VAS) were assessed to measure effects on perceptual outcomes. Cognitive performance was measured with a reaction time test of the Vienna Test System (VTS). During all three recovery interventions and CC portable polysomnography was applied. Results showed a significant increase from pre-AX-CPT to pre-MR on fatigue states and recovery-stress states indicating that the induction of mental fatigue was effective. Moreover, results underlined that analysis yielded no significant differences between recovery interventions and the control condition but they revealed significant time effects for VAS, SRSS items, and cognitive performance. However, it could be derived that the application of a rest break with 20 min of mental recovery strategies appears to enhance recovery on a mainly mental and emotional level and to reduce perceived mental fatigue.

Self-reports and actigraphy are common methods of sleep monitoring. Portable polysomnography (p-PSG) may serve as a screening tool in natural environments. Common concerns with its use are that sleep and compliance might be affected. Further, dysfunctional beliefs of the subjects may contribute to sleep disturbances, which might manifest throughout sleep monitoring. This study examined the effect of monitoring sleep patterns and attitudes among healthy individuals. Sixty-eight physically active university students (26.6 ± 2.5 years) were assigned to the intervention (n = 35) or the control group (n = 33). Sleep monitoring consisted of 2-week online sleep logs and a 1-week actigraphy. Portable PSG was applied for the final two nights. Objective and subjective sleep parameters and ratings were compared between the baseline measurements and the first two nig hts of actigraphy and the two nights of p-PSG. The participants answered the Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS), pre-and post-monitoring. The groups did not display any interactiontime effect (p = 0.187) for DBAS. Also, there were no subjective insomnia complaints. Following the nights with p-PSG application, perceived restfulness of sleep was reduced between baseline measurement and the second p-PSG night (p = 0.045). In contrast, the objective parameters showed an increased sleep-efficiency (p < 0.001) and reduced wake after sleep-onset (p = 0.002) after both p-PSG nights. All other sleep parameters revealed no significant differences between actigraphy-only and p-PSG nights. Two-week sleep monitoring had no negative effect on the objective sleep patterns and attitudes about sleep. Yet, sleep with p-PSG led to reduced subjective sleep quality, which was not reflected in the objective sleep parameters. Contrarily, participants showed higher sleep efficiency and shorter waking phases, possibly due to changed bedtime routine. Hence, p-PSG may be applicable for field studies in sport science, provided the participants receive detailed information.

Sleep is identified as a reoccurring behavioral state of reduced movement and responsiveness, allowing rest from prior periods of wakefulness, and is considered a precious resource for both, psychological and physiological well-being. 1,2 It follows a specific architecture within a circadian and ultra-circadian rhythm, and is divided into five stages, with three sleep stages (N1-N3), rapid eye movement (REM) sleep, and the waking state. Sleep stages split into light (N1-N2) and slow-wave (N3) sleep. A healthy sleeper starts a sleep cycle with N1, followed by more robust sleep (N2) and deep sleep (N3). REM as the last stage completes one sleep cycle. Ideally, a sleep cycle repeats three to seven

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Objectives Objectives were to examine subjective sleep quality and daytime sleepiness of the German ice hockey junior national team prior to the world championship to identify athletes of concern and areas of optimization with the intention of equally preventing injury and enhancing performance. Methods Twenty-one athletes (Mage = 18.5 ± 0.6 years, Mheight = 181.7 ± 4.3 cm, Mweight = 81.4 ± 7.1 kg), playing for national (n = 13) and international (n = 8) home clubs, answered the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) before training camp (T1, day 1) and prior to tournament (T2, day 11). Results Overall, 9 players at T1 and 7 at T2 were identified as bad sleepers (PSQI > 5), while high sleepiness (ESS > 10) was found for 6 athletes at each measurement time. Group means and standard deviations reduced descriptively for PSQI (T1 = 5.38 ± 2.31, T2 = 4.57 ± 2.36) and ESS (T1 = 9.24 ± 3.74, T2 = 8.48 ± 3.28). Tendential differences were visible for PSQI in international-based players (Z = −1.7, p = 0.09) and ESS in first-national-league players (Z = −1.73, p = 0.08) over time. Higher PSQI values for international-based players (6.25 ± 2.6) were found compared to first-national-league (5.83 ± 1.60) and lower-league players (4.00 ± 2.08), with large effect sizes for lower-league compared to international (d = 0.95) and national players (d = 0.98) at T1 and small effect sizes compared to first-league players (d = 0.24) at T2. Conclusion Findings emphasize great vulnerability and individuality and underline the importance of intraindividual sleep monitoring to meet the requirements needed to equally obtain health and enhance overall performance.

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 &lt; 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 &lt; 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.

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