An Exploration of the Relationship Between Disordered Eating, Exercise Dependence, and Athletic Injury
Bibliographic record
Abstract
Athletes can be at elevated risk for developing eating disorders, the effects of which can be devastating. Few researchers have examined the influence of a predisposition toward an eating disorder on athletic injury. Exercise dependence might bridge the gap toward understanding this relationship. This study sought to examine the relationship between predisposition toward an eating disorder and exercise dependence and looked at both as predictors of athletic injury. College students ( n = 132) completed the Eating Disorders Inventory and the Exercise Dependence Questionnaire, as well as provided demographic, activity, and injury information. Subscales of the Eating Disorders Inventory and Exercise Dependence Questionnaire were significant predictors of having at least one athletic injury in the preceding year. These findings suggest that both predisposition toward an eating disorder and exercise dependence may be contributing factors to injury.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".