Dietary Supplementation Practices among Varsity Athletes at a Canadian University
Bibliographic record
Abstract
BACKGROUND: Given the risks of inadvertent doping associated with dietary supplement (DS) use, it is critical to explore the extent of dependence of varsity athletes on DS to improve performance and support recovery. The purpose of this study was to gain insight into dietary supplementation practices among varsity athletes in a university setting in Ontario, Canada. METHODS: An online DS use questionnaire was completed by 302 varsity athletes (30.5% male, 69.5% female; 20.5 ± 1.8-year old) who were competing in intermittent, power and endurance-based sports at the University of Guelph. The data from supplement users were analyzed using a Chi-square analysis to investigate type of DS consumption, frequency of use and reasons for use. RESULTS: Overall, 58.3% of athletes reported having used at least one type of DS in the past six months. Gender and age had significant associations with prevalence of DS use, with male athletes and athletes over 20-year old being more likely to be DS users. The most frequently reported reasons for consuming DS were to maintain good health, increase energy, promote recovery, correct or prevent micronutrient deficiencies and supply convenient forms of energy and/or macronutrients. Although, most athletes were using reliable sources of information, health care professionals, 58.6% still mentioned wanting to become more knowledgeable about DS. CONCLUSIONS: Findings from this study may guide the development of educational materials needed to address knowledge gaps on DS among varsity 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".