Use of Supplements by Japanese Elite Athletes for the 2012 Olympic Games in London
Bibliographic record
Abstract
OBJECTIVE: To investigate supplement use among Japanese elite athletes. DESIGN: We conducted a cross-sectional survey study using individual interviews during athletes' medical evaluations. SETTING: One to 5 months before the Olympic Games in 2012, London, United Kingdom. PARTICIPANTS: Five hundred fifty-two Japanese athletes for the London Games, including candidates. INDEPENDENT VARIABLES: Sex, sports, supplement category, and participation. MAIN OUTCOME MEASURES: Whether athletes used supplements, what products were used, the frequency and purposes of use, and from what sources athletes received information on supplements. RESULTS: All 552 athletes were interviewed by pharmacists regarding supplement use and agreed to the survey. Of them, 452 (81.9%) used 1 or more supplement products in the year before the study; a total of 952 different products (mean = 1.7, SD = 1.4) were used. The most commonly used supplement was amino acids (310 athletes; 56.2%), and 358 (38.7%) of the total products were amino acids. Of the athletes, 241 (43.7%) took at least 1 supplement daily, and of the supplements, 457 (49.4%) were taken daily. The most common purpose for supplement use was recovery from fatigue-327 (59.2%) athletes chose this answer, and 486 (52.5%) products were used for this purpose. Finally, regarding athletes' information sources on supplements, coaches, managers, and trainers were the most frequent advisors (275 athletes, 49.8%; 466 products, 50.4%). CONCLUSIONS: The results revealed widespread supplement use among Japanese elite athletes for the London Olympic Games. Education system was required not only for athletes but also for athletes' entourage, such as coaches, managers, trainers, and supplement companies. CLINICAL RELEVANCE: This study will provide basic data for establishing an education system that would better guide athletes' use of supplements.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".