Assessment of sleep quality and daytime sleepiness in German national ice hockey players preparing for the world championship

Abstract

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.

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

“…To further translate data from lab to practice, the implementation of a sleep diary or log on a regular basis may help to put measured data into perspective without objectively measuring every single night of sleep (Reed and Sacco, 2016;Kölling and Hof zum Berge, 2020). Accordingly, an athlete's sleep habits, architecture, and patterns must always be examined on an individual basis before implementing any interventions or structural changes (Driller et al, 2019;Hof zum Berge et al, 2021). Thus, different monitoring tools should not be considered as mutually exclusive.…”

“…However, available research only scratches the surface on how sleep influences athlete health (Walsh et al, 2020). As sleep quality may vary highly, even within a single team, there is an urgent need for highly individual sleep intervention programs (Hof zum Berge et al, 2021). Consequently, a onesize-fits-all approach for elite athletes is unlikely ideal for health and performance (Walsh et al, 2020).…”

Recovery management in sport: Overview and outcomes of a nine-year multicenter research program

“…The objective of the initial phase of the research program was to explore the usefulness and accuracy of various monitoring measures in capturing fluctuations in short-term fatigue and recovery stemming from training and competitive workloads (Project Module: Measures for Training and Competition Monitoring). 6,7,[10][11][12][13][14][15][16][17][18][19][20][21][22][23][25][26][27][28][29][30][31][32][33][34][35][36] This phase was complemented by the development and validation of two concise self-report tools for assessing recovery and stress in sports, namely the Acute Recovery and Stress Scale (ARSS) and the Short Recovery and Stress Scale (SRSS), 8,9,24,[70][71][72] which have been used in most of the studies. As a preliminary step and as part of preparatory trials, we devised and assessed training protocols that induce temporary fatigue in athletes while maintaining an acceptable level of tolerability (Project Module: Fatigue-Inducing Exercise Protocols).…”