Assessing the acceptability and feasibility of a novel early mobilization program following transcatheter aortic valve replacement (Preprint)
Bibliographic record
Abstract
BACKGROUND Patients undergoing a transcatheter aortic valve replacement (TAVR) are typically discharged from hospital the next day, leaving little time to support mobilization needs. The JUMPSTART program was developed as a self-directed, tailored virtual exercise program to improve post-TAVR patients’ mobilization. OBJECTIVE This pilot evaluation assessed the acceptability and feasibility of the preliminary exercise module developed for the program. METHODS The evaluation was conducted at a regional cardiac centre in Southwestern Ontario. Patients meeting inclusion criteria were contacted via telephone post-discharge and provided with an electronic link to the JUMPSTART exercise module. A second call was made, 14 days post-discharge, to gather feedback regarding module acceptability and feasibility, and to discuss barriers to participation, via a structured survey. RESULTS Of the 216 patients who met inclusion criteria, 112 (52%) completed the survey. Sixty-eight respondents (61%) had done the recommended exercises; they were satisfied with the module (mean = 5.92; 1= very dissatisfied and 7= very satisfied) and most rated the exercises as being the ‘right level of difficulty’ (56%). For the 44/112 (39%) who did not try the exercises, key barriers were being busy (n=13), not feeling well (n = 10), and believing the module was unnecessary (n=8). CONCLUSIONS A major barrier to participating in the evaluation was the technological requirement. The preliminary module was determined to be acceptable and feasible by TAVR patients who attempted the exercises. Findings refined the implementation of the JUMPSTART program, which has been expanded to include additional modules, and is undergoing an assessment of its impact on quality of life.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".