Attitudes and Dietary Behaviours among Athletes Engaged in Weight-Sensitive Performance Sports: A Mixed-Methods Study
Bibliographic record
Abstract
Purpose: This mixed-methods study investigated disordered eating attitudes and behaviours (DEAB) and the risk of eating disorders (ED) in adult athletes engaged in weight-sensitive sports, while also exploring their dietary concerns and body image perception. Methods: Fifty athletes (mean age 25.9 years) recruited across New Brunswick completed two validated self-administered questionnaires (the Eating Disorders Screen for Athletes (EDSA) and the Eating Disorder Examination Questionnaire (EDE-Q)) focusing on dietary concerns and body image perception. Ten individuals also participated in an individual interview. Results: DEAB and concerns about body image were widespread among participants. The mean EDSA score approached the high-risk threshold for ED, while the EDE-Q score remained below the diagnostic cutoff value. Both scores were significantly higher in females than males. EDE-Q scores in aesthetic sports were twofold greater than in gravitational sports. Two main themes convey the athletes’ perspectives: perception of an ideal body image in sports and perceived strong association between athletic performance level and weight or body shape, with sub-themes depicting the influence of various stakeholders and the sports environment, the experience of DEAB, and the athlete’s journey. Conclusions: Identifying ED among athletes participating in weight-sensitive sports requires a broad approach not limited to ED diagnostic criteria and should encompass those displaying DEAB, thus emphasizing prevention. Sociocultural factors such as the sport culture should also be addressed.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".