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Record W2117637389 · doi:10.1123/ijsnem.2013-0087

Dietary Supplement Usage, Motivation, and Education in Young Canadian Athletes

2014· article· en· W2117637389 on OpenAlexafffundabout
Kristin Wiens, Kelly Anne Erdman, Megan Stadnyk, Jill A. Parnell

Bibliographic record

VenueInternational Journal of Sport Nutrition and Exercise Metabolism · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMount Royal University
FundersCanadian Foundation for Dietetic Research
KeywordsAthletesMedicineDietary supplementDemographicsPhysical therapyGerontologyFood scienceDemography

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate dietary supplement use in young Canadian athletes, their motivation for consuming supplements, and their sources of information. METHODS: A questionnaire tested for content validity and reliability was administered to 567 athletes between the ages of 11 and 25 years from the Canadian athletic community in face-to-face meetings. Demographics and sport variables were analyzed using descriptive statistics. Fisher's exact tests were used to examine dietary supplementation patterns and sources of information regarding dietary supplement use between categories of gender, age, sport type, and competition level. RESULTS: Ninety-eight percent of athletes were taking at least one dietary supplement. Males were more likely to consume protein powder, energy drinks, recovery drinks, branched chain amino acids, beta-alanine, and glutamine (p < .01); supplements typically associated with increased muscle mass. Athletes 11-17 years old focused on vitamin and mineral supplements; whereas, athletes 18-25 years old focused on purported ergogenic supplements. Strength training athletes were more likely to consume creatine, glutamine, and protein powders (p < .02). Reasons for supplement use included to stay healthy, increase energy, immune system, recovery, and overall performance. Primary sources of information were family and friends, coaches, and athletic trainers; with 48% of athletes having met with a dietitian. Preferred means of education included individual consultations, presentations, and the internet. CONCLUSIONS: The majority of young athletes are using dietary supplements with the belief they will improve performance and health; however, may not always have reliable information. Educational programs using individual consultations and electronic media are recommended for this demographic.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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

Citations119
Published2014
Admission routes3
Has abstractyes

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