Visuomotor deficits during locomotion in previously concussed athletes 30 or more days following return to play
Bibliographic record
Abstract
Current protocols for returning athletes to play (RTP) center around resolution of physical symptoms of concussion. However, recent research has identified that balance and cognitive deficits persist beyond physical symptom recovery. Protocols that involve testing dynamic balance and visuomotor integration have been recommended as potential tools for better understanding of length of impairment following concussion. A dynamic, visuomotor paradigm was undertaken in the current study to assess decision making in athletes who had sustained a concussion >30 days before study participation and had been cleared to RTP (N = 10). Two obstacles created a gap that varied between 0.6 and 1.8× participants' individual shoulder width in open space. Participants made decisions to navigate through or deviate around the gap created by the two obstacles. The results revealed that previously concussed athletes were highly variable in their decision making and demonstrated variable Medial-Lateral (ML) center of mass (COM) control when approaching the obstacles, when compared with nonconcussed, age-matched controls. As such, they showed poor visuomotor control and decision making, as well as poor dynamic stability compared to controls. Visuomotor deficits were persistent in the sample of previously concussed individuals, well beyond deficits identified by current RTP standards. This study suggests that dynamic, visuomotor integration tasks may be of benefit to increase rigor in RTP protocols and increase safety of athletes returning to sport.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".