Abstract WP120: Real-world Canadian experiences from therapy staff implementing an intensive rehabilitation protocol in stroke inpatient rehabilitation settings: a survey study
Bibliographic record
Abstract
Objective: Despite guidelines recommending intensive rehabilitation for walking recovery after stroke, its implementation remains challenging. Our understanding of barriers and facilitators in real-world settings remains minimal. We aimed to understand the implementation factors for intensive rehabilitation within real-world inpatient rehabilitation settings. Methods: A cross-sectional online survey design was used. We invited 85 therapy staff (physiotherapists + therapy assistants) who delivered the structured, progressive intensive rehabilitation protocol (>2000 steps, 40-60% heart rate reserve, >30 minutes/session) as usual care from 12 sites (7 Canadian provinces) within the Walk ’n Watch implementation trial (NCT04238260). Fitbit step counters and Garmin heart rate monitors were provided. The survey was developed by a multidisciplinary team (clinicians, scientists, and a stroke patient), including close-ended (Likert agreement scale) and open-ended questions regarding protocol practicalities, workplace structure, and support. Close-ended responses were descriptively summarized. Open-ended responses were thematically analyzed using the Consolidated Framework for Implementation Research (CFIR). Results: Forty-seven therapy staff (85% female; mean 13 ± 10 years clinical experience) completed the survey. Most therapy staff agreed that they delivered the protocol safely and successfully (87%) and that the step and heart rate targets were helpful (72%). However, only about one-third agreed that they had enough time to deliver the protocol (36%); 26% and 47% agreed that they achieved the prescribed step count and heart rate targets, respectively. The major time-related factor was insufficient therapy time to accommodate the 30-minute protocol, besides other required therapy activities (CFIR Work Infrastructure). For example, discharge planning often took priority near the end of the stay. Most agreed to future use of the protocol (87%). However, only about half agreed to future use of the trial-assigned devices (49% step counters, 64% heart rate monitors), likely due to perceptions of device inaccuracies (CFIR Materials&Equipment). Conclusions: Therapy staff reported successfully delivering an intensive rehabilitation protocol as usual care under real-world conditions. Strategies identified to facilitate implementation included building in discharge planning considerations within the protocol and acquiring more accurate step counters and heart rate monitors.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".