The association between the risk of relative energy deficiency in sports and performance outcomes: A real-world examination of international elite volleyball male athletes
Bibliographic record
Abstract
Background Relative Energy Deficiency in Sports (REDs) has been reported in Olympic-level male athletes, but the impacts of REDs on performance is unclear. This study explored the association between international elite level volleyball male athletes at risk of REDs and countermovement jump (CMJ) and cognitive performance in real-world setting.Methods Using a cross-sectional design, 22 male athletes from a national indoor volleyball program were assessed for medical history, resting metabolic rate, dual energy x-ray absorptiometry assessment of body composition, hematological analysis, 4-day dietary intake, restrained eating behaviour via three-factor eating questionnaire – R18, Victorian Institute of Sport Assessment questionnaire – patellar tendon, CMJ and cognitive performance with the Stroop test. Being at risk of REDs was associated with poorer jump performance (mean power, velocity and jump height) and not Stroop test outcomes (p ≤ 0.05).Results Being at risk of REDs was associated with poorer jump performance (mean power, velocity and jump height) and not Stroop test outcomes (p ≤ 0.05).Conclusion Future work should characterize the effects of REDs on neuromuscular performance in international elite level team-based male 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".