MoveStrong at home: a feasibility study of a model for remote delivery of functional strength and balance training combined with nutrition education for older pre-frail and frail adults
Bibliographic record
Abstract
Exercise and nutrition interventions are often recommended for frailty; however, effective strategies are required for real-world implementation. Our primary aim was to assess the feasibility and acceptability of telephone and virtual delivery of MoveStrong, an 8-week exercise and nutrition program with a 4-week follow-up for older pre-frail and frail adults. A priori criteria for success included: recruitment (≥25/12 weeks), retention at follow-up (≥80%), and adherence to exercise and nutrition sessions (≥70%). We recruited community-dwelling Ontario residents; ≥60 years, ≥1 chronic condition, ≥1 FRAIL scale score. Participants received mailed materials, a personalized exercise program, 11 remote one-on-one training sessions with an exercise physiologist and 3 online dietitian-led nutrition education sessions. We completed exploratory analyses of secondary outcomes including physical function and dietary protein intake. Semi-structured interviews supported program evaluation. In total, 30 participants were enrolled. 28 (93%) participants completed program and follow-up assessments. Adherence to exercise and nutrition sessions (CI) was 84% (77%-91%) and 82% (70%-93%) respectively. At program end and follow-up [mean change (CI)], significant improvements were measured in 30-second chair stand test [3.50 (1.12-5.86), 4.54 (1.94-7.13) chair stands] and dietary protein intake [12.9 (5.7-20.0), 9.2 (0.4-18.1) g]. Overall, participants were satisfied with program delivery. Trial registration number: NCT04663685.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".