A questionnaire examining attitudes of collegiate athletes toward doping and pharmacists as information providers
Bibliographic record
Abstract
BACKGROUND: Doping in sport has become an increasingly prominent topic. The decision to take part in doping practices is multifactorial and often based on many different information sources of varying reliability. This study sought to determine the attitudes of athletes at a Canadian Interuniversity Sport (CIS) university toward doping and to discover if pharmacists are perceived to be a valid information source on medication usage for these athletes. METHODS: CIS athletes competing in at least 1 of 8 sports were asked to complete a questionnaire. Participants were asked various questions regarding their perceptions of doping, medication use, information available to them regarding doping and the role of pharmacists in providing advice on medication usage. RESULTS: In total, 92.7% (307/331) of questionnaires were at least partially completed. Generally, these athletes did not feel pressured to dope or that it was prevalent or necessary. The fear of doping violations largely did not alter the use of medications and supplements. The online doping education program administered by the Canadian Centre for Ethics in Sport was the most used information source (74.5%); pharmacists were used 37.7% of the time. Pharmacists were perceived to be a good source of information about banned substances by 75.6% (223/295) of participants, although only 35% (104/297) consulted a pharmacist each time they purchased a nonprescription medication. CONCLUSIONS: It appears that doping is neither prevalent nor worth the risk for these CIS athletes. There also appears to be an opportunity for pharmacists to play a more prominent role in providing advice on medication use to high-performance 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".