Examining evidence based resistance plus balance training in community-dwelling older adults with complex health care needs: Trial protocol for the Muscling Up Against Disability project
Bibliographic record
Abstract
Progressive resistance plus balance training (PRBT) has been demonstrated as effective in reducing later life physical disability, falls risk and poor health, even among those with complex health care needs. However, few studies have examined the influence of PRBT on health service utilisation, cognitive wellbeing and training modality acceptance or undertaken a cost benefit analysis. This project will investigate the broad scope benefits of PRBT participation among community-dwelling older Australians receiving Government supported aged care packages for their complex health care needs. Using a modified stepped-wedge design, 248 community-dwelling adults 65 years and older with some level of government support aged care have been randomised into the study. Those randomised to exercise undertake six months of twice weekly machine-based, moderate to high intensity, supervised PRBT, followed by a six month unsupervised, unsupported follow-up. Controls spend six months undertaking usual activities, before entering the PRBT and follow-up phases. Data are collected at baseline and after each of the six month phases. Measures include level of and change in health and care needs, body composition, muscle capacity, falls, sleep, quality of life, nutritional and mental health status. In addition, acceptance and engagement is determined through telephone and focus group interviews complementing a multi-model health cost benefit evaluation. It is hypothesised this study will demonstrate the feasibility and efficacy of PRBT in improving primary and secondary health outcomes for older adults with aged care needs, and will support the value of this modality of exercise as an integral evidence-based service model of care.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
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".