Does Perturbation-Based Balance Training Prevent Falls? Systematic Review and Meta-Analysis of Preliminary Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Older adults and individuals with neurological conditions are at an increased risk for falls. Although physical exercise can prevent falls, certain types of exercise may be more effective. Perturbation-based balance training is a novel intervention involving repeated postural perturbations aiming to improve control of rapid balance reactions. PURPOSE: The purpose of this study was to estimate the effect of perturbation-based balance training on falls in daily life. DATA SOURCES: MEDLINE (1946-July 2014), EMBASE (1974-July 2014), PEDro (all dates), CENTRAL (1991-July 2014), and Google Scholar (all dates) were the data sources used in this study. STUDY SELECTION: Randomized controlled trials written in English were included if they focused on perturbation-based balance training among older adults or individuals with neurological conditions and collected falls data posttraining. DATA EXTRACTION: Two investigators extracted data independently. Study authors were contacted to obtain missing information. A PEDro score was obtained for each study. Primary outcomes were proportion of participants who reported one or more falls (ie, number of "fallers") and the total number of falls. The risk ratio (proportion of fallers) and rate ratio (number of falls) were entered into the analysis. DATA SYNTHESIS: Eight studies involving 404 participants were included. Participants who completed perturbation-based balance training were less likely to report a fall (overall risk ratio=0.71; 95% confidence interval=0.52, 0.96; P=.02) and reported fewer falls than those in the control groups (overall rate ratio=0.54; 95% confidence interval=0.34, 0.85; P=.007). LIMITATIONS: Study authors do not always identify that they have included perturbation training in their intervention; therefore, it is possible that some appropriate studies were not included. Study designs were heterogeneous, preventing subanalyses. CONCLUSIONS: Perturbation-based balance training appears to reduce fall risk among older adults and individuals with Parkinson disease.
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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 | 0.024 | 0.074 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".