CVA-revalidatie in het verpleeghuis: therapie-intensiteit van en motivatie voor fysiotherapie
Bibliographic record
Abstract
INTRODUCTION: Stroke is a frequent and potential invalidating disease, of which recovery can be improved by rehabilitation. In The Netherlands old and frail stroke patients are rehabilitated in nursing homes. Probably, the intensity of and motivation for physiotherapy are important for successful discharge. The aim was to determine (1) therapy intensity of and motivation for physical therapy of geriatric stroke patients (2) its correlates and (3) the effect on discharge destination. METHODS: Data were obtained from the 'GRAMPS'-study, a longitudinal observational study of stroke rehabilitation in 15 Dutch nursing homes. Direct time spent on physiotherapy was registered during admission. Motivation was measured by the Pittsburgh Rehabilitation Participation Scale (PRPS). Data of 84 patients were analysed using uni- and multivariate regression analysis. RESULTS: Patients received an average 109 min of physiotherapy per week. 69 patients (82%) were good motivated for physiotherapy (had all PRPS scores 4 or higher). Therapy intensity was positively associated with the presence of a partner and good motivation. No significant independent variables of motivation were found. Therapy-intensity was positively related to discharge to prior living situation. CONCLUSION: Intensity of physiotherapy of stroke rehabilitation is an independent variable of successful discharge and is higher when the patient has a partner or is better motivated. These findings stress the importance of high motivation and therapy intensity in geriatric stroke rehabilitation.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".