Promoting Inpatient Mobility in a Canadian Healthcare Setting: Impacts, Outcomes and Lessons Learned from the Implementation of a Multidisciplinary Early Mobility Program
Bibliographic record
Abstract
Introduction: Inpatient mobility has garnered increasing attention due to its significant impacts on patient outcomes, with immobility during hospitalization linked to various complications.This study explores the implementation and outcomes of a multidisciplinary early mobility program within the Vitalité Health Network, located in New Brunswick, Canada.Methods: The study was conducted in two phases.Phase 1 focused on the early implementation of the inpatient mobility program, involving patient and healthcare professional feedback, and assessing changes in patient mobility and satisfaction.Phase 2 expanded the evaluation to include a larger patient cohort and sought to assess the sustainability of exercise behaviors and mobility improvements over time (seven days and 30 days after patient discharge).Results: The program demonstrated high patient satisfaction and notable improvements in autonomy scores, with an average increase of 17.5% thorough phase 1 and 2 (AM-PAC Basic Mobility Inpatient Short Form, 6 Clicks).Analysis also revealed sustained enhancements in patients' exercise habits post-discharge (seven days and 30 days), indicating the program's potential in promoting medium to long-term health behavior changes.Conclusion: These findings highlight the value of early mobility programs in improving both inpatient autonomy and patient exercise habits post-discharge.Our study also underscores the necessity of using a strategic and multidisciplinary approach when implementing this kind of intervention within a healthcare setting.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".