Is it wiser to train in the afternoon or the early evening to sleep better? The role of chronotype in young adolescent athletes
Bibliographic record
Abstract
STUDY OBJECTIVES: To examine the effect of the timing of high-intensity exercise (afternoon vs. evening) on adolescent athletes' bedtime psychological state, sleep quality, sleep staging, and next-day wellness/sleepiness according to chronotype. METHODS: Forty-two young athletes (morning type: n = 12, intermediate type: n = 14; evening type: n = 16) completed a randomized crossover study under free-living conditions. The counterbalanced sessions include: (AEX) afternoon (1:00-3:00 p.m.) and (EEX) evening (5:30-7:30 p.m.) high-intensity exercise. Sessions were conducted over three days each and were separated by a 1-week washout period. The time in bed was fixed (10:30 p.m.-7:30 a.m.). Sleep was assessed through ambulatory polysomnography. RESULTS: The effect of high-intensity exercise on sleep differs significantly depending on the time of exercise with lower sleep efficiency: SE (-1.50%, p < .01), and higher SOL (+4.60 min, p ≤=< .01), during EEX vs. AEX. Contrary to the previous view, we discovered differences in the mediated response based on the chronotype of young athletes. These differences were observable in the psychological state at bedtime, objective sleep, and the next day's self-reported wellness. Whereas the sleep of participants with a late chronotype remains stable regardless of the time of exercise, those with an early chronotype experience higher mood disturbances and clinically significant sleep disruptions following evening high-intensity exercise. CONCLUSIONS: Exercise timing and chronotype affect the psychological state at bedtime and objective sleep in adolescent athletes. This also alters next morning signs of pre-fatigue and wellness which suggest that the consideration of both features is important to adolescent athletes' recovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".