Physical therapists’ perceptions and use of standardized assessments of walking ability post-stroke
Bibliographic record
Abstract
OBJECTIVES: To determine physical therapists' perceptions and use of standardized assessments of walking ability post-stroke. DESIGN: Cross-sectional survey. METHODS: A questionnaire was posted to physical therapists in neurological practice registered in Ontario, Canada (n = 1155). Of the 705 responders, 270 treated adults with stroke and completed the questionnaire. RESULTS: Assessment tools most frequently used with > 6/10 patients were the Chedoke-McMaster Stroke Assessment (61.1%), Functional Independence Measure (45.2%), and gait speed test (32.2%). Only 11.1% consistently used the 6-minute walk test. The tools were used to evaluate (44.6%), monitor change over time (42.9%), form a prognosis (19.4%) or judge readiness for discharge (28.4%). Some therapists (40.1%) were unaware or unsure that valid and reliable measures of walking exist. As many as 80.5% of respondents agreed or strongly agreed that clinical practice guidelines should recommend specific measures of walking ability for use post-stroke. CONCLUSION: A moderate number of physical therapists consistently use standardized assessment tools to evaluate or monitor change in walking limitation post-stroke. Interventions to improve use must increase awareness, in addition to the perceived relevance and applicability, of recommended assessment tools.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".