Re-conceptualizing postural control assessment in sport-related concussion: Transitioning from the reflex/hierarchical model to the systems model
Bibliographic record
Abstract
Background: While postural control impairment is common following sport-related concussion, few investigations have studied the physiological basis for this impairment. Both the Reflex/Hierarchical Model and the Systems Model are commonly used to characterize the physiological basis of postural control.Purpose: To discuss the physiological basis of postural control impairment resulting from sport-related concussion based on these models and suggest directions for future research.Methods: Narrative literature review.Findings: Postural control impairment seen with sport-related concussion is a multifaceted construct that can result from deficits in numerous systems that underlie postural control as described by the Systems Model, rather than a unidimensional construct that stems from the central nervous systems’ inability to integrate sensory input to control posture as per the Reflex/Hierarchical Model.Conclusion: We recommend a transition away from the Hierarchical/Reflex Model of postural control towards the Systems Model in the conceptualization of sport-related concussion. Future research on postural control following sport-related concussion should account for the multifaceted nature of the resulting postural control impairment based on the Systems Model. Clinically, there is a need for a clinical postural control test that allows examination across the affected systems under single-task, dual-task, and sport-specific paradigms.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".