MANAGING MOBILITY IN VULNERABLE SENIORS (MMOVES) WITH AN INDIVIDUALIZED, HOME-EXERCISE PROGRAM
Bibliographic record
Abstract
After hospitalization, further disability among seniors could be prevented through exercise. Nonetheless, a one-on-one rehabilitation is not realistic for the volume of seniors that are experiencing disability. Currently available educational material for improving disability is so vast and non-specific that passive dissemination may pose a barrier to behaviour change. The aim of this pilot study was to estimate the extent to which an individualized, exercise-focused, self-management program (MMOVES), in comparison to exercise information, is more effective in improving mobility after 6 months among seniors recently discharged from hospital. The physiotherapy-facilitated intervention consisted of 1) evaluation of mobility capacity; 2) setting short and long term goals; 3) delineation of an exercise treatment plan. In addition, MMOVES participants received an educational booklet to enhance mobility self-management skills and were followed-up with monthly telephone calls. Control group received a booklet with information on exercises targeting mobility limitations in seniors. Mobility, pain, and health status were assessed at baseline and at 6 months using multiple indicators drawn from DASH, LEFS, SF-36. After imputing missing data, generalised estimating equations (GEE) estimated the odds of response for people receiving the intervention in comparison to the odds of response in the control group. Each person was classified as having made a response, deterioration, or no change on each measure based on change of one level on the ordinal scale. 26 people were randomized to the intervention (mean age 81 ± 8; 39% women), 23 were randomized to the control (mean age 79 ± 7; 33% women). The OR for the mobility outcomes combined was 3.08 and the 95%CI excluded 1 (1.65 – 5.77). The ORs for pain and health perception favoured the MMOVeS group; but, the 95%CI included the null value. Our individualized, exercise-focused, self-management program was more effective than exercise information in improving mobility outcome for seniors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".