Resistance exercise training at different loads in frail and healthy older adults: A randomised feasibility trial
Bibliographic record
Abstract
OBJECTIVES: This trial aimed to determine the feasibility of recruitment, retention, adherence, and safety of a resistance training (RT) intervention to skeletal muscle failure in both frail and non-frail older adults. DESIGN: An 8-week randomised feasibility trial. SETTING AND PARTICIPANTS: Older adults, with and without frailty, recruited from both clinics and community. METHODS: Recruitment was based on the number of participants enrolled from those provided with a Patient Information Sheet (PIS). Retention was based on the number of participants who completed the trial. Adherence was based on the number of RT sessions attended out of 16. Outcomes included frailty (Fried criteria), muscle strength (maximal voluntary contraction), functional abilities (Short Physical Performance battery), quality of life (EQ-5D-5L), activities of daily living (LIADL) and safety (diary). RESULTS: Recruitment target (n = 60) was achieved within 15 months, 58 were randomised to high (n = 30) or low repetition-load (n = 28) groups. Mean age of participants was 72 years (range 65-93). Adherence and retention rate for the RT intervention was ≥70%. There was one serious adverse experience due to the RT intervention. There were no differences (P > 0.05) in effects of RT on outcome variables between low and high repetition-load groups. CONCLUSIONS AND IMPLICATIONS: Recruitment of frail people was challenging. Older adults performing supervised RT to skeletal muscle failure was feasible and safe, with appropriate caution, and the repetition-load did not appear to influence its efficacy. Future research into the effectiveness of this simplified model of RT is warranted.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".