In-Group Nutrition Interventions with Elite Weight-Sensitive Athletes Are Associated with an Increase in Nutrition Knowledge and Intake of Carbohydrate-Rich Foods, but Not a 400+ Increase in Daily Caloric Intake
Bibliographic record
Abstract
Background: Nutrition knowledge is positively associated with energy intake in athletes, and therefore, improving nutrition knowledge may offer a cost-effective approach to prevent negative performance and health outcomes associated with low energy availability (LEA) described in the Relative Energy Deficiency in Sports (REDs) syndrome model. The aim was to assess the short-term influence of a 60-min group-based nutrition education intervention on sports nutrition knowledge and dietary intake in elite athletes. Method: Twenty-five elite Canadian athletes were enrolled into a 3-week prospective single blinded randomized pragmatic trial. Participants were randomly assigned to 1 of 2 group-based nutrition education interventions. Education content was similar between both groups with 1 group assigned an additional 5-10 mins to review athlete testimonials on the negative impacts of REDs. Participants were assessed, before and about 10 days after the intervention, using anthropometry, Platform to Evaluate Athlete Knowledge of Sports Nutrition, Athlete Food Choice, Eating Disorder Examination 6.0, LEA/Triad, Athlete Diet Index questionnaires, and consecutive 5-day food record. Results: The education intervention that was supplemented with athlete testimonials performed similarly to the intervention without (p>0.05). Overall, nutrition knowledge (score from 69.8, to 72.8) and the intake of carbohydrate-rich foods (12.4 to 14.3) increased while disordered eating/eating symptoms decreased (0.788 to 0.642) after the education intervention (all p< 0.05). No changes in daily energy and carbohydrate intake were observed after the education intervention (p>0.05). Conclusion: The nutrition education sessions were associated with an in-crease in nutrition knowledge and other factors associated with food choice leading to increased consumption of carbohydrate-rich foods and reducing disordered eating/eating disorder symptoms. More research is required on methods to influence athlete eating behaviours to optimize energy intake to prevent associated negative health and performance outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".