A HOME-BASED PHYSICAL ACTIVITY AT DISCHARGE FROM A GERIATRIC UNIT: FEASIBILITY, ACCEPTABILITY AND HEALTH BENEFITS
Bibliographic record
Abstract
Mobility decline leads to increased risk of falls, fractures and loss of autonomy. Around 21% of Canadians aged 65 and over report mobility limitations and 30–60% experience functional decline after hospitalisation. Even if improving mobility is a healthcare priority, there is no current recommendation for implementing physical activity(PA) prescription at hospital discharge. Objectives: To evaluate the feasibility, acceptability and potential health benefits of a systematic approach of a home-based adapted PA at discharge from a Geriatric Short-term Unit(UCDG). Methods: Inclusion: MMSE score>18; discharge to home; length of stay>7days. A decisional tool based on 3 components (balance/cardio-strength/cognitive) was developed to prescribe PA according to an individualized profile(18-subtypes). The 12-week PA prescription included a session/day(4 exercises;15-20min/session). Telephone-monitoring took place once a week. Quantitative and qualitative evaluations were performed. Results: Among the 100 admitted patients, 56 were eligible, 33 accepted to participate and 17 completed the protocol(48%-dropout). There were no baseline clinical/physical differences between patients who participated(n=17) or not(n=16), except for lower disability score (SMAF-ADL) for the later; 82% of the participants reported to be satisfied and 76% to have enjoyed the program; 71 % of health professionals reported no-overwork associated to the implementation of the decisional tool and 88% considered it relevant. Adherence was 53.4[CI:39.2–67.6] sessions out of 36 expected (3-times/week). After 12 weeks, walking speed(TUG) and sit-to-stand performance were better than at discharge. Conclusion: This pilot study suggests that this PA approach is feasible, acceptable and seems promising as it induces beneficial health effects to prevent mobility decline in older adults.
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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 | 0.009 |
| 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 | 0.001 | 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".