Reliability and Validity of a Mobile Device Application for Use in Sports-Related Concussion Balance Assessment
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Bibliographic record
Abstract
Background Balance assessment is necessary when evaluating athletes after a concussion. We investigated a mobile device application (app) for providing valid, reliable, and objective measures of static balance. Objectives The mobile device app would demonstrate similar test–retest reliability to force platform center of pressure (COP) sway variables and that SWAY scores and force platform COP sway variables would demonstrate good correlation coefficients. Methods Twenty-six healthy adults performed balance stances on a force platform while holding a mobile device equipped with SWAY (Sway Medical LLC) to measure postural sway based on acceleration changes detected by the mobile device's accelerometer. Participants completed four series of three 10-second stances (feet together, tandem, and single leg), twice with eyes open and twice with eyes closed. Test–retest reliability was assessed using intraclass correlation coefficients (ICC). Concurrent validity of SWAY scores and COP sway variables were determined with Pearson correlation coefficients. Results Reliability of SWAY scores was comparable to force platform results for the same test condition (ICC = 0.21–0.57). Validity showed moderate associations between SWAY scores and COP sway variables during tandem stance (r = –0.430 to –0.493). Lower SWAY scores, indicating instability, were associated with greater COP sway. Discussion The SWAY app is a valid and reliable tool when measuring balance of healthy individuals in tandem stance. Further study of clinical populations is needed prior to assessment use. Conclusion The SWAY app has potential for objective clinical and sideline evaluations of concussed athletes, although continued evaluation is needed.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it