The Relationship Between Performance Enhancing Drug Use With Psychological Characteristics And Social Support In Iran
Bibliographic record
Abstract
PURPOSE: One of the problems among athletes, especially among bodybuilders, is the negative health effects of Performance Enhancing Drugs (PEDs), so it is important to identify factors that are related to the behavior of using PEDs. The aim of this study was to investigate the prevalence of PED use among bodybuilders in Iran and the relationship with the psychological characteristics and social support of this group. METHODS: In a descriptive-correlational study, 274 participants aged 18-40 years old from 20 randomly selected bodybuilding clubs in Semnan province voluntarily participated in the study. Participants filled out a questionnaire which included items about psychological characteristics (The Ottawa mental skills assessment tool: OMSAT-3), social support (The Social Support Appraisals Scale: SS-A) and levels of PED use measured using a scale developed by the World Anti-Doping Agency (2013) (including supplements and anabolic agents). The data obtained from the questionnaires were cleaned and screened for normality using Kolmogorov-Smirnov tests. RESULTS: More than a quarter (25.2%) of respondents reported using PEDs. Due to the non-normality of data distribution (P ≤ 0.001), the results of Spearman correlation tests were used and showed that there is a significant negative relationship between the prevalence of PEDs with psychological characteristics (r = -0.64, P = 0.001), and social support (r = -0.58, P = 0.001), of bodybuilders. CONCLUSIONS: The results show that exercise psychologists and educators may be able to address levels of psychological skills and enhance the positive social support of people who are using PEDs. Strengthening these characteristics and offering improved social support may minimize behaviors and therefore the risks of using PEDs in bodybuilders.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".