Dietary Supplementation of High-performance Canadian Athletes by Age and Gender
Bibliographic record
Abstract
OBJECTIVE: To determine dietary supplementation practices and opinions, preferred means for dietary supplement (DS) education, and antidoping opinions among elite Canadian athletes varying in age and gender. DESIGN: A descriptive, cross-sectional survey. SETTING: Elite athlete training centers in Calgary, Canada and surrounding area. PARTICIPANTS: A total of 582 high-performance athletes (314 male, 268 female). MAIN OUTCOME MEASURES: High-performance athletes representing 27 sports with a mean age of 19.96+/-3.91 years completed a validated questionnaire assessing DS practices and opinions by recall. Sport categories included varsity, Canadian Sport Centre Calgary (CSCC), and National Sport School (NSS). RESULTS: There was extensive DS use, with 88.4% of participants taking>or=1 DS (mean of 3.08+/-1.87 DS per user) during the previous 6 months. Overall, sport drinks (22.4%), sport bars (14.0%), multivitamins and minerals (13.5%), protein supplements (9.0%), and vitamin C (6.4%) were most frequently reported. Older athletes were significantly more likely to report greater DS usage; to be advised by teammates, health food store retailers, and magazines; to prefer supplementation education via individual interviews; to claim awareness of anti-doping rules; and to perceive anti-doping compliance. Relative to gender, significant differences were observed for the types of DS reported; supplementation advisors; justifications for DS use; and awareness of anti-doping regulations. CONCLUSIONS: Utilization of this validated and reliable questionnaire has the potential for broad use and provides insight into the factors that influence DS use in elite 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".