Encouraging older adults with pre-frailty and frailty to “MoveStrong”: an analysis of secondary outcomes for a pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: This 8-week pilot stepped-wedge randomized controlled trial evaluated the MoveStrong program for teaching adults who have frailty/pre-frailty about balance and functional strength training and sufficient protein intake to prevent falls and improve mobility. METHODS: We recruited individuals aged 60 years and over, with a FRAIL scale score of 1 or higher and at least one chronic condition, who were not currently strength training. The program included 16 exercise physiologist-led hour-long group sessions and two dietitian-led hour-long nutrition sessions. We analyzed secondary outcomes-weight, gait speed, grip strength, physical capacity (fatigue levels), sit-to-stand functioning, dynamic balance, health-related quality of life (HRQoL), physical activity levels and protein intake-using a paired t test and a generalized estimating equation (GEE). RESULTS: Of 44 participants (mean [SD] age 79 [9.82] years), 35 were pre-frail and 9 were frail. At follow-up, participants had significantly improved grip strength (1.63 kg, 95% CI: 0.62 to 2.63); sit-to-stand functioning (2 sit-to-stands, 95% CI: 1 to 3); and dynamic balance (1.68 s, 95% CI: 0.47 to 2.89). There were no significant improvements in gait speed, HRQoL index scores, self-rated health, physical activity levels (aerobic activity and strength training) or protein intake. GEE analysis revealed an interaction between exposure to MoveStrong and gait speed, sit-to-stand functioning, dynamic balance and HRQoL index scores. The total cost to administer the program and purchase equipment was CAD 14 700, equivalent to CAD 377 per participant. CONCLUSION: Exploratory analyses suggest MoveStrong exercises may improve gait speed, sit-to-stand functioning, dynamic balance and HRQoL index scores in older individuals who are frail and pre-frail.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".