A scoping review of female athletes’ psychosocial experiences of menstruation and the menstrual cycle.
Bibliographic record
Abstract
Increasingly, researchers have attended to the experiences of female athletes and the specific biological, sociocultural, and environmental considerations that could impact their sport participation experiences (Moore et al., 2023). Recently, researchers have called for the need to understand how the menstrual cycle is perceived to impact training and competition (Brown et al., 2020). The aim of this study was to summarize the existing literature on female athletes’ psychosocial experiences of menstruation and the menstrual cycle. A scoping review was conducted across five databases (PsychInfo, Scopus, Medline, and ProQuest Theses and Dissertations), and hand-searching of journals produced 6,749 abstracts were screened for inclusion in the review (inclusion criteria: full text empirical articles, English language, research on perceptions or experiences related to menstruation among female athletes). Researchers have mainly investigated the physical impacts of the menstrual cycle on female athletes’ participation in sport. Existing research demonstrates a) the negative psychosocial effects associated with menstrual irregularities in female athletes, b) widespread miscommunication between athletes and coaches regarding menstrual symptoms and dysregulation, and c) a lack of necessary adjustment of training schedules based on menstrual cycles, further perpetuating negative impacts on female athletes. There was limited research examining stress appraisals and coping across different phases of the menstrual cycle. Areas for future research include the influence of menstruation-related symptoms on stress and coping throughout the phases of the menstrual cycle. There is a need to explore how communication in the sport environment can be improved to better support female athletes’ psychosocial well-being.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".