Influence of Performance Level on Dietary Supplementation in Elite Canadian Athletes
Bibliographic record
Abstract
INTRODUCTION: It is well documented that athletes report greater dietary supplement (DS) usage than nonathletes; however, limited data exist for Canadian athletes, especially relative to competitive performance levels. PURPOSE: This descriptive and analytical, cross-sectional research investigated DS practices and opinions, preferred means for DS education, and antidoping opinions among elite Canadian athletes competing at various performance levels. METHODS: Subjects completed a validated questionnaire by recall. Combined, 582 high-performance athletes (314 M, 268 F) between the ages of 11 and 42 yr (mean 19.96 +/- 3.91 yr) and representing 27 sports activities participated. Respondents were categorized into five competitive performance levels: provincial (68), national (101), North America (61), international or professional (89), and varsity (263). RESULTS: Overall, most (88.4%) reported taking one or more DS during the previous 6 months (mean 3.08 +/- 1.87 DS per user). From a total of 1555 DS declared, 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. Athletes at the highest performance level were significantly more likely to use protein supplements, to be advised by strength trainers regarding DS usage, to have a higher self-rating of their diet, to prefer individual interviews for DS educational purposes, to perceive greater awareness of antidoping legislation, and train more h.wk(-1). Furthermore, differences were observed for the types of DS reported and justifications for use. CONCLUSION: This dataset, the first of its kind in Canada, was generated with a validated and reliable questionnaire and has the potential to be extended nationally and internationally to provide greater insight into the patterns and opinions of elite athletes regarding supplementation and antidoping.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".