Determination of the prevalence of anabolic steroids, stimulants, and selected drugs subject to doping controls among elite sport students using analytical chemistry
Bibliographic record
Abstract
Drug abuse by adolescents has been investigated in various surveys that reported correlations between age, gender, and activity. However, none of these studies included chemical analyses to help substantiate the statements of participants. In the present study, the urine specimens of 964 students (439 females, 525 males; mean age 22.1 years, s = 1.7), who applied to study sports sciences at university, were assessed for anabolic steroids, stimulants, and selected drugs prohibited in sports. In total, 11.2% of the urine specimens provided contained drugs covered by doping controls. The most frequently detected compound was the major metabolite of tetrahydrocannabinol (9.8%) followed by various stimulants related to amphetamine and cocaine (1.0%). Indications of anabolic steroid use were found in 0.4% of urine samples but originated from contraceptives containing norethisterone. The present study provided unambiguous data on the status quo of drug (ab)use by adolescents hoping for a career related to elite sport or sports sciences. No use of anabolic steroids was detected. However, evidence for stimulants and tetrahydrocannabinol administration was obtained, although not reported by any participant, which highlights the issue of under-reporting in surveys based solely on questionnaires.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".