Validity of measures of reactive balance training intensity
Bibliographic record
Abstract
ABSTRACT Intensity is a key component of exercise prescription. However, balance training intensity is not well defined. Consequently, balance training studies often do not report exercise intensity, which hinders implementing these interventions and developing exercise guidelines. This study aimed to validate measures of reactive balance training intensity. Healthy young (n=16) and older (n=15) adults experienced moving platform balance perturbations of varying magnitudes. Candidate intensity measures were: number of reactive steps; centre of mass displacement, velocity, and acceleration, and margin of stability 100 ms post-perturbation; peak electrodermal response; and OMNI Perceived Exertion Scale and Balance Intensity Scale scores. Correlations were examined between perturbation magnitude and candidate intensity measures. We also compared candidate intensity measures between backward- and forward-fall perturbations and between age groups using generalized linear mixed models. Peak centre of mass acceleration 100 ms after the perturbation was significant positively correlated with perturbation magnitude, with no significant age-group or direction effects, suggesting that this is a valid measure of absolute perturbation intensity. Number of reactive steps, peak electrodermal response, and OMNI Perceived Exertion Scale were significantly positively correlated with perturbation magnitude, and were significantly higher for backward-fall compared with forward fall perturbations and for older adults compared to younger adults at the same magnitude, suggesting that these are valid measures of relative perturbation intensity. These measures could be used to prescribe and report intensity of reactive balance training in future studies.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".