“I just wasn’t expecting it”: lived experiences of early menstruators and the impact of parental support in competitive dance
Bibliographic record
Abstract
Introduction: Menarche is a significant milestone in adolescence, yet the implications of early menarche [menarche before 12.72 years (Canadian mean)], remain insufficiently understood. Early menarche is generally linked to increased mental health risks, which may be intensified by the appearance-based pressures of competitive dance. Existing literature emphasizes menstrual disorders and delayed menarche, leaving early menarche in dance largely underexplored. Methods: This study investigated how young women in competitive dance perceive and experience early menarche, and how parental support influences dancers' ability to express needs and navigate this transition. Five dancers (Mage = 14.62) who experienced their first menstruation at 11.58-12.54 years (M = 12.24), participated in one-on-one semi-structured interviews, and five parents joined a focus group. Guided by interpretive description, data were analyzed using reflective thematic and functional analysis. Results: Three themes were generated to reflect athletes' experiences: Alone in the Spotlight: What It Means to Menstruate Early, Behind the Curtain: Presence and Absence of Support, and Dancing Through Discomfort: Symptoms, Struggles, and Strength. Two shared dancer-parent themes were generated: Step by Step: Mastering the Art of Hiding Periods and Choreographing Comfort: Medication for Period Symptoms. Three additional themes were generated to reflect parent experiences: The Prep Step: Early Education and Preparation Before Onset, Backstage Support: Helping Young Dancers Manage Their Period, and Dad's Got the Moves: Stepping Up for Her Cycle. Discussion: Findings from this research highlight the unique, multi-faceted challenges of early menarche in competitive dance and underscore the need for tailored education, support, and resources for dancers and their families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".