Clinician perspectives on cross-education in stroke rehabilitation
Bibliographic record
Abstract
PURPOSE: Cross-education is a neural phenomenon where strength of an untrained muscle improves after unilateral training of the opposite homologous muscle. It has been extensively studied in healthy populations and shows promise for post-stroke rehabilitation. The purpose of this study is to understand current post-stroke upper extremity rehabilitation practice; clinician's perspectives on cross-education and; facilitators and barriers to implementation of a cross-education intervention. MATERIALS AND METHODS: This qualitative study used an interpretive description framework. Twenty-three occupational therapists and two physiotherapists who worked with individuals with stroke were interviewed. Digital audio files were transcribed and then line-by-line coding for units of information was conducted by two investigators. A third investigator, who was not present during the interviews, participated in category development. RESULTS AND CONCLUSIONS: Cross-education is paradoxical yet promising was the primary theme. This theme was elucidated by three descriptive categories: (1) therapists worked in a forced-use paradigm; (2) there was gap in current practice for those with more severe impairments in arm function; and (3) cross-education used as an adjunct could be useful within current practice for specific patients. Therapists suggested that educational materials for clinicians, patients, and patient families would be essential to the success of cross-education to explain training the less affected limb. This study provides important foundational information about clinician perspectives that will facilitate future translational research in this area. Implications for rehabilitation Cross education, or training the stronger arm to increase strength in the weaker arm, is an intervention particularly appropriate for people with stroke who have severe impairments in arm strength. This intervention should not replace the forced use paradigm, but may be a useful adjunct in rehabilitation. Therapists perceived that education of patients, families, therapists, and doctors would be critical for cross education to be implemented successfully - as it is opposite the forced use paradigm that characterizes most of stroke rehabilitation.
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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 | 0.033 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".