Between-session reliability and minimal detectable difference of peak tibial acceleration during running on an indoor track
Bibliographic record
Abstract
Peak tibial acceleration (PTA) is commonly used to assess impact loading during running, but the number of strides required for reliable between-session measurement in overground conditions, as well as the minimal detectable difference (MDD), remains unclear. This study evaluated the one-week and three-week reliability of axial and resultant PTA during overground running and determined the minimum number of strides needed for good and excellent reliability. Eleven recreational runners completed three sessions on a 200-m indoor oval track while wearing a tibial-mounted accelerometer. PTA was analysed across different stride intervals, and test-retest reliability was assessed using intraclass correlation coefficients (ICC). Results showed moderate-to-good reliability for axial PTA (ICC = 0.71-0.80 at 1 week, 0.67-0.84 at 3 weeks) and moderate-to-excellent reliability for resultant PTA (ICC = 0.81-0.94 at 1 week, 0.78-0.91 at 3 weeks). Based on our results, we recommend averaging at least 40 strides to achieve good reliability for axial PTA (MDD = 2.93 g), and at least 100 strides to achieve excellent reliability of resultant PTA (MDD = 2.72 g). These findings support the reliability of PTA when evaluating longer-term interventions, such as gait retraining, but researchers should consider stride variability and track curvature when interpreting results.
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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 | 0.000 | 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".