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Record W3045975739 · doi:10.3390/nu12082284

Dietary Supplement Use among Non-athlete Students at a Canadian University: A Pilot-Survey

2020· article· en· W3045975739 on OpenAlexaffabout
Dalia El Khoury, Joel Hansen, Madelyn Tabakos, Lawrence L. Spriet, Paula Brauer

Bibliographic record

VenueNutrients · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBachelorFamily medicineMedicineCross-sectional studyAdverse effectGuardianGerontologyComputer-assisted web interviewingPsychologyHealth professionalsEnvironmental healthHealth careGeography

Abstract

fetched live from OpenAlex

Despite the emerging evidence of adverse consequences and interaction with doping substances, dietary supplements (DS) are commonly used by many Canadians. The purpose of this study was to evaluate the patterns and determinants of current DS use among non-athlete students at a Canadian university using a cross-sectional approach. Of the 475 participants who completed the online survey, 43.4% declared using DS in the past six months. Participants who were male, aged ≥20 years old, and had a parent/guardian with a bachelor's degree were significantly more likely to use DS. The types of DS used and the sources of information regarding DS were significantly influenced by age and gender. The most commonly used DS were vitamin and mineral and protein supplements. Most participants referred to healthcare professionals for information on DS, but many continued to depend on unreliable sources including family and friends. Of DS users, 10.1% reported experiencing adverse events from using DS. Findings from this study indicate that supplementation is very common among Canadian non-athlete students and highlight the urgent need for the development of educational programs surrounding DS use.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.979

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 head0.030
GPT teacher head0.237
Teacher spread0.208 · 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

Citations28
Published2020
Admission routes2
Has abstractyes

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