ANKLE SPRAIN RISK FACTORS: A 5-MONTH FOLLOW-UP STUDY IN VOLLEY AND BASKETBALL ATHLETES
Bibliographic record
Abstract
ABSTRACT Introduction Ankle sprain is a frequent sports injury among volley and basketball players, and identifying risk factors is necessary to prevent injuries and prolong their careers. Objective To identify intrinsic and extrinsic factors in basketball and volleyball players related to the risk of ankle sprain injury over a five-month follow-up period. Methods Ninety-four Brazilian young competitive athletes (15.8±1.7 years, 47 basketball and 47 volleyball players) participated in this study. They were evaluated for intrinsic risk factors (previous history of ankle sprain, dominant lower limb, ankle ligament laxity, range of motion of the ankle-foot complex, electromyographic response time of ankle evertors, postural control and muscular torque of ankle invertors and evertors) and extrinsic risk factors (type of shoes worn, use of orthosis, previous injuries while training or competing, and the players’ position). Results During the study period, 18 (19%) athletes suffered unilateral sprains. Multivariate logistic regression analysis gave a final regression with four factors: dominant leg (p=0.161), type of shoes worn (p=0.049), player’s position (p=0.153), and peroneus brevis muscle reaction time (p=0.045). There was an 86.1% probability of an ankle sprain if the athlete had a left dominant leg, wore shoes without vibration dampeners, or played in the small forward, wing/hitter spiker, middle blocker, or opposite spiker positions, and had a peroneus muscle reaction time longer than 80ms. However, only the player’s position was significantly (p=0.046) associated with lesion occurrence. Conclusion The player’s position appeared to be a risk factor in both sports, and this result may help professionals to prevent ankle sprains. Level of Evidence I; High quality randomized clinical trial with or without statistically significant difference but with narrow confidence intervals.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".