Sport experience and age account for visuomotor performance more than multiple concussion history and sex
Bibliographic record
Abstract
Aims Previous studies have consistently shown a decline in cognitive-motor integration (CMI) performance in those either with a history of concussion, less sport experience or of older age. The present study sought to characterize CMI performance of individuals as a function of these factors combined. Hypothesis: relative to those with one concussion, those with multiple concussions would experience significantly greater neuropathological effects on the brain networks required for standard and rule-based visuomotor performance, resulting in impaired motor performance. Study design: Individual cross-sectional study. Level of evidence: Level 3. Materials & Methods Two hundred and twenty-three asymptomatic individuals with a concussion history participated in this study. They performed two touchscreen-based eye–hand coordination tasks, including a standard direct interaction task and one which involved CMI; target location and motor action were dissociated in the CMI task. Results A significant percentage of standard and CMI variance was explained only by age and sport experience in our sample of younger, mainly select-level athletes. Conclusion These findings may suggest that motor developmental stage, which corresponds to age, and sport experience provide brain network resilience that can compensate for concussion-related performance declines. Clinical relevance: These data provide evidence around the importance of accounting for sport experience and developmental age when evaluating return to play metrics in youth and young adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".