The association of sleep with subjective wellbeing and performance in female athletes: A systematic review
Bibliographic record
Abstract
Sleep and athletic performance have been investigated in previous research, showing sleep to be important for cognitive function, mood, and recovery.Inferior sleep has been reported in female athletes compared to male athletes; however, no systematic reviews have examined the association of sleep with performance and subjective wellbeing in female athletes.Three electronic databases (SPORTDiscus, PubMed, and Web of Science) were searched with no date restrictions in June 2024.Studies contained primary data and examined any association between sleep and performance in female athletes over the age of 18 years, with their level of competition described.Performance and subjective wellbeing were categorised as sportspecific performance; cognitive performance; physical performance, readiness, and availability; and mood and subjective wellbeing.From 2565 records, 38 studies remained for review.Most studies examined physical performance, readiness, and availability, whereas cognitive performance was the least studied aspect of performance.The majority of studies included in this review supported the general conclusion that positive sleep outcomes were associated with positive performance and subjective wellbeing outcomes (89% of sportspecific performance; 50% of cognitive performance; 38% of physical performance, readiness, and availability; and 21% of mood and subjective wellbeing studies), while negative sleep outcomes were associated with negative performance and subjective wellbeing outcomes (50% of cognitive; 33% of physical, readiness, and availability; and 50% of mood and subjective wellbeing studies) in female athletes.Only 2 studies were of high-quality according to a modified version of the Newcastle-Ottawa Scale, indicating a lack of highquality evidence in the reviewed literature.Lack of control for sleep, athletic population, and menstrual characteristics were particularly apparent.This review highlights lower sleep duration and/or quality being detrimental to sport-specific performance; cognitive performance; physical performance, readiness, and availability; and mood and subjective wellbeing of female athletes.However, more high-quality research is needed to describe sufficiently the relationship between sleep and performance in female athletes.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".