THERAPISTS' UNDERSTANDING OF THE CANADIAN BEST PRACTICE RECOMMENDATIONS FOR UPPER EXTREMITY REHABILITATION AFTER STROKE; AND BARRIERS AND FACILITATORS FOR THEIR IMPLEMENTATION
Bibliographic record
Abstract
Background: Stroke is one of the leading causes of disability. Physical rehabilitation must be evidence-based and address a range of clinical subtypes and severity of disabilities. Clinical practice guidelines provide a useful mechanism for implementing rehabilitation plans based on research evidence. To increase adherence to guideline use, there is a need to understand therapistsu2019 attitudes and intentions toward guideline implementation. Objectiveu2022tTo describe how physical and occupational therapists understand, interpret, intend to implement or currently employ the Canadian Stroke Best Practice Recommendations.u2022t To detect the potential barriers and facilitators for the implementation process.MethodsSample Size: Maximum 40 participants or till data saturated.Data Collection: This study proposes using the qualitative method of descriptive content analysis to collect and analyze data throughout two different stages. 1st stage: Semi-structured cognitive interviews will be conducted and recorded with physical and occupational therapists practicing within the arena of stroke rehabilitation. The interview questions will be informed by the components of the theory of planned behavior, including; attitudes, subjective norms andperceived behavioral control as a determinants for therapistsu2019 intention toward implementing a particular clinical guideline. 2nd stage: Determine implementation issues by compiling and analyzing answers to a standardized tool (GLIA: The Guideline Implementability Appraisal) that focuses on implementation of clinical practice guidelines, completed by the same cohort of therapists. Data Analysis:A descriptive approach will be used to summarize the facilitators/barriers for implementing a clinical guidelines described by participants in both the interviews and GLIA. Themes will be compiled reflecting the categories and constructs of GLIA.
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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 | 0.026 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".