Factors Influencing Physical Therapists' Use of Standardized Measures of Walking Capacity Poststroke Across the Care Continuum
Bibliographic record
Abstract
BACKGROUND: The use of standardized assessment tools is an element of evidence-informed rehabilitation, but physical therapists report administering these tools inconsistently poststroke. An in-depth understanding of physical therapists' approaches to walking assessment is needed to develop strategies to advance assessment practice. OBJECTIVES: The objective of this study was to explore the methods physical therapists use to evaluate walking poststroke, reasons for selecting these methods, and the use of assessment results in clinical practice. DESIGN: A qualitative descriptive study involving semistructured telephone interviews was conducted. METHODS: Registered physical therapists assessing a minimum of 10 people with stroke per year in Ontario, Canada, were purposively recruited from acute care, rehabilitation, and outpatient settings. Interviews were audiotaped and transcribed verbatim. Transcripts were coded line by line by the interviewer. Credibility was optimized through triangulation of analysts, audit trail, and collection of field notes. RESULTS: Study participants worked in acute care (n=8), rehabilitation (n=11), or outpatient (n=9) settings and reported using movement observation and standardized assessment tools to evaluate walking. When selecting methods to evaluate walking, physical therapists described being influenced by a hierarchy of factors. Factors included characteristics of the assessment tool, the therapist, the workplace, and patients, as well as influential individuals or organizations. Familiarity exerted the primary influence on adoption of a tool into a therapist's assessment repertoire, whereas patient factors commonly determined daily use. Participants reported using the results from walking assessments to communicate progress to the patient and health care professionals. CONCLUSIONS: Multilevel factors influence physical therapists' adoption and daily administration of standardized tools to assess walking. Findings will inform knowledge translation efforts aimed at increasing the standardized assessment of walking poststroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".