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Influence of Performance Level on Dietary Supplementation in Elite Canadian Athletes

2006· article· en· W2083073292 on OpenAlexafffundabout
Kelly Anne Erdman, Tak Fung, Raylene A. Reimer

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsElite athletesEliteAthletesFood sciencePsychologyMedicinePhysical therapyBiologyPolitical science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.256
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations104
Published2006
Admission routes3
Has abstractyes

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