Acute Effects of Sleep Extension on Fatigue, Inhibitory Control, Short‐Term Vigilance and Neuromuscular Function in Youth Elite Ice Hockey Players: A Randomised Crossover Trial
Bibliographic record
Abstract
ABSTRACT Sleep extension has previously been shown to acutely benefit athletic performance. However, studies investigating the effects of sleep extension on fatigue and cognitive performance are lacking. In this randomised crossover trial, 22 elite youth hockey players (17 ± 1 years; 1.83 ± 0.07 m; 82 ± 7 kg) took part in a 3‐week protocol during the pre‐season. The first week included two familiarisation sessions. During the second and third week of the protocol, athletes underwent a testing session before and after a night of normal sleep vs. sleep extension (10 h of time in bed). For each athlete, these conditions were randomised across weeks. Each testing session consisted of 2 h of hockey training followed by a 30‐min colour Multi‐Source Interference Task (cMSIT). Three countermovement‐jumps (CMJs), three handgrip contractions and 3‐min psychomotor‐vigilance tasks (PVTs) were performed pre‐training, post‐training, and post‐cMSIT. Sleep was objectively monitored using actigraphy and sleep logs. Athletes slept normally 7:04 ± 0:39 h:mm. In the sleep extension condition, athletes increased their sleep by 16% ± 11% ( p < 0.001; η p 2 = 0.72). Sleep onset latency, WASO, and sleep efficiency were similar across conditions (all p > 0.016; η p 2 ≤ 0.11). cMSIT performance and fatigue improved by 8% ( p < 0.001; η p 2 = 0.21) and 23% ( p = 0.022; η p 2 = 0.02), respectively, following sleep extension. Performance on the PVTs, CMJs and handgrip contractions, while changing between pre‐training, post‐training and post‐cMSIT, remained similar across conditions ( p > 0.13; η p 2 ≤ 0.01). These results suggest that acute sleep extension is beneficial for improving perceived fatigue and performance on a long and demanding cognitive task (cMSIT), with no changes in less demanding cognitive tasks (PVT) or short physical tests.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".