Female athlete triad screening in Canadian Interuniversity Sport universities: analysis of the pre-participation evaluation form.
Bibliographic record
Abstract
BACKGROUND: Our aim was to examine inclusion of screening questions related to female athlete triad in the Canadian Interuniversity Sport (CIS) pre-participation evaluation (PPE) forms. We hypothesized that the current CIS PPE forms are not comprehensive screening tools for identifying athletes at risk for the female athlete triad. METHODS: All 48 English-speaking CIS universities were invited to participate in the study. Via e-mail, a copy of the PPE form was requested from team physicians and certified athletic trainers. Two reviewers evaluated the PPE forms for inclusion of the 12 items recommended by the Female Athlete Triad Coalition for primary screening for the triad. RESULTS: Thirty-nine of 48 CIS universities responded (81%). The majority of the universities (97%), required a PPE for incoming athletes. Only 9 universities (24%) had 6 or more of the 12 recommended screening items included in their forms, whereas 26 universities (70%) included 4 or less items. Three universities (8%) did not address any of the recommended questions. Questions related to disordered eating were often absent in the collected PPEs. In 10 universities (27%), PPE forms were completed by the athlete alone. The remaining 27 (73%) universities required the form to be completed by the athlete in conjunction with a therapist, physician, or both. CONCLUSIONS: PPE forms used by CIS universities have limited ability to identify athletes at risk of the triad-based on the recommendations of the Coalition. Furthermore, there is a lack of uniformity of the PPE forms within the CIS.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".