A Potential Screening Tool for Nutritional Preparedness in Collegiate Level Female Athletes: A Pilot study
Bibliographic record
Abstract
Background: Diet monitoring is part of an athlete’s health and performance assessment, and adequate nutrition is known to be a method that can positively influence the reduction in exercise-induced injury. However, the concept of nutritional preparedness as a screening tool to identify low energy availability for the competitive season is not mainstream practise. Objectives: Our pilot study investigated three aims: 1) changes to nutritional status from the pre-competition phase to the competition phase, 2) living status impact on athlete’s food accessibility, and 3) whether nutritional preparedness in the pre-competition phase influenced the potential for low energy availability during the competition phase. Methods: Female volleyball athletes (N=21, 19-22 yrs., 80% lived off campus) were recruited from 3 universities (Ambrose, Calgary, New Brunswick- Saint John) through social media sites, and word of mouth. Two cross-sectional questionnaires (questions derived from the Short Food Frequency-Q, LEAF-Q, and RED-S screening tool-Q) were administered prior to and during the competitive season. Results: The nutritional assessment score significantly decreased from the pre-competition to competition phase, respectively (n=20, 26.11 ± 4.25; n=12, 20.64 ± 4.74; p=0.022). Many athletes (6/12) reported an injury during the competitive season with an average time loss from sport of 8-14 days. Conclusions: These findings suggest that collegiate female volleyball athletes have a potential for low energy availability, regardless of living status. Future research should build on the nutritional preparedness concept as a method of screening for low energy availability and the influence on injuries sustained during the competition phase.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".