Physiological Responses of a Jaw-Repositioning Custom-Made Mouthguard on Airway and Their Effects on Athletic Performance
Bibliographic record
Abstract
Martins, RS, Girouard, P, Elliott, E, and Mekary, S. Physiological responses of a jaw repositioning custom-made mouthguard on airway and their effects on athletic performance. J Strength Cond Res 34(2): 422-429, 2020-Advanced dental techniques such as jaw-repositioning have shown to increase lower body muscular power such as vertical jump, but its effects on acceleration and speed have not been studied. Similarly, jaw repositioning is commonly used to increase airways volume and ventilation in a special population (i.e., obstructive sleep apnea); however, its ergogenic effects on aerobic performance have yet not been studied. The purpose of the cross-over study was to investigate the effects of a jaw-repositioning custom-made mouthguard (JCM) on volumetric changes in airway and jaw position and determine the effects this may have on aerobic and anaerobic performance. Results indicated that jaw-repositioning custom-made mouthguard may have an ergogenic effect on performance. The JCM condition showed an increase of 13% in upper airway volume (p = 0.04), 10% in upper airway width (p = 0.004), 7% in ventilation (p = 0.006), 5% in maximal aerobic power (p = 0.003), 4% in time to exhaustion (p = 0.03), 3% in vertical jump (p = 0.03), 2% in broad jump (p = 0.009), and a decrease of 4% in 20-m (p = 0.04) and 2% in 40-m (p = 0.001) sprint times. This is the first study to demonstrate a significant link between jaw repositioning, airway volumetric change, and performance enhancement in both aerobic and anaerobic performances. The results of this study may lead to a change in culture for the use of mouthguards in different sports applications, from high orofacial injury risk sports to other sports, specifically for ergogenic enhancement.
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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 | 0.001 | 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".