Knowledge of pharmacy students about doping, and the need for doping education: a questionnaire survey
Bibliographic record
Abstract
BACKGROUND: Anti-doping activities are carried out on a global scale. Based on these activities, the specialty of "sports pharmacist," which entails a deeper comprehension of doping, use of supplements, and appropriate drug use for athletes, was established in 2009 in Japan. It is difficult to say whether the education on doping is adequate for pharmacy students who will be eligible to become sports pharmacists. It is also unclear how well these students understand doping. Therefore, the aim of this study was to investigate pharmacy students' current knowledge of appropriate drug use, doping and use of supplements, and to explore the need for further education on these topics. METHODS: A questionnaire survey was conducted from July 3rd to August 2nd in 2014 at Showa University in Japan. A total of 406 respondents (2nd- to 6th-year students) were assessed as eligible. Group comparison was used to compare those who had attended a lecture about doping and those who had not. RESULTS: Most of the students only knew the word doping and had not attended a lecture on the subject, but 72% of them expressed a desire to attend one. Over half did not know that the most common doping violation in Japan is unintentional doping, and were unfamiliar with certain past cases of doping. In addition, 41% did not know that over-the-counter medicines and dietary supplements might contain prohibited substances, and 87% were unaware that names of prohibited substances might not appear on the ingredient labels of dietary supplements. In contrast, attending a lecture on doping was effective in facilitating the acquisition of all these types of knowledge. CONCLUSIONS: It is important to provide more opportunities for appropriate education of pharmacy students on the topic of doping, given that interest exists and attending a lecture on the topic appears to be useful. More education about doping for pharmacy students would be as effective for anti-doping activities as is education of 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".