Modified Balance Error Scoring System (M-BESS) test scores in athletes wearing protective equipment and cleats
Bibliographic record
Abstract
BACKGROUND: Balance testing is an important part of the initial concussion assessment. There is no research on the differences in Modified Balance Error Scoring System (M-BESS) scores when tested in real world as compared to control conditions. OBJECTIVE: To assess the difference in M-BESS scores in athletes wearing their protective equipment and cleats on different surfaces as compared to control conditions. METHODS: This cross-sectional study examined university North American football and soccer athletes. Three observers independently rated athletes performing the M-BESS test in three different conditions: (1) wearing shorts and T-shirt in bare feet on firm surface (control); (2) wearing athletic equipment with cleats on FieldTurf; and (3) wearing athletic equipment with cleats on firm surface. Mean M-BESS scores were compared between conditions. RESULTS: 60 participants were recruited: 39 from football (all males) and 21 from soccer (11 males and 10 females). Average age was 21.1 years (SD=1.8). Mean M-BESS scores were significantly lower (p<0.001) for cleats on FieldTurf (mean=26.3; SD=2.0) and for cleats on firm surface (mean=26.6; SD=2.1) as compared to the control condition (mean=28.4; SD=1.5). Females had lower scores than males for cleats on FieldTurf condition (24.9 (SD=1.9) vs 27.3 (SD=1.6), p=0.005). Players who had taping or bracing on their ankles/feet had lower scores when tested with cleats on firm surface condition (24.6 (SD=1.7) vs 26.9 (SD=2.0), p=0.002). CONCLUSIONS: Total M-BESS scores for athletes wearing protective equipment and cleats standing on FieldTurf or a firm surface are around two points lower than M-BESS scores performed on the same athletes under control conditions.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".