The effect of reactive balance training on responses to novel unexpected balance perturbations: a feasibility study
Bibliographic record
Abstract
ABSTRACT Trial design Pilot study embedded within an assessor-blinded parallel randomized controlled trial. Objective To determine the feasibility of using unexpected and novel balance perturbations to assess the efficacy of reactive balance training. Methods Participants : Community-dwelling adults with chronic stroke who could walk independently without a gait aid for at least 10 m. Interventions : Reactive balance training, using manual and internal perturbations, or ‘traditional’ balance training (control group). Training took place for one hour per session, twice per week for six weeks. Outcome : Proportion of unexpected slips triggered as intended; s tate anxiety, perceptions of situations, and participants’ subjective responses to the unexpected slip perturbation; and spatiotemporal and kinematic features of unperturbed and perturbed walking (step length, width, and time, and mechanical stability) pre- and post-training. Randomisation : Blocked stratified randomization. Blinding : Assessors were blinded to group allocation. Results Numbers randomised : 28 participants were randomized (15 to reactive balance training, 13 to control). Of these, nine reactive balance training group participants and seven control participants were eligible and consented to additional data collection for the pilot study. Numbers analysed : 12 participants (six per group) completed the post-training unexpected slip data collection and were included in analysis of the pilot objective. Outcome : All unexpected slips triggered as intended. Overall, participants did not report increased state anxiety or any concerns about the unexpected slip. Analysis of spatiotemporal and kinematic data suggested better stability following the unexpected slip for reactive balance trained participants than control participants; however, there were also between-group differences in spatiotemporal and kinematic features of walking pre- and post-training. Conclusions Unexpected slips are feasible in research. However, their value as outcomes in clinical trials may depend on ensuring the groups are balanced on prognostic factors. Trial registration ISRCTN05434601 Funding Canadian Institutes of Health Research.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".