The relationship between Rating of Everyday Arm‐use in the Community and Home (REACH) scale affected arm‐use assessment, activity and participation after stroke
Bibliographic record
Abstract
Abstract Background and Objectives While arm function has been traditionally used as a primary goal for upper extremity rehabilitation post‐stroke, we propose a simple measure of arm use, which may translate into better activities and participation. The aim was to determine the relationship between arm use and measures of activity and participation. Methods This was a cross‐sectional study with evaluative components involving community‐dwelling individuals with chronic stroke. The Rating of Everyday Arm‐Use in the Community and Home (REACH) Scale was used to assess affected arm use, Barthel Index and activity domain of the Stroke Impact Scale (SIS) for activities, and participation domain of the SIS for participation. The participants were also asked if they resumed driving after the stroke. Results Forty‐nine individuals (mean age = 70.3 ± 11.5 years, male sex = 51%) living with the effects of a stroke for at least 3 months participated in this study. There was a positive relationship between affected arm use and activities (Barthel Index score – rs = 0.464; SIS activities – rs = 0.686), participation (rs = 0.479), and driving (rs = 0.581). The Barthel Index scores were higher for individuals with dominant arm hemiparesis (p = 0.003) or left hemisphere lesions (p = 0.005). There was also greater arm use in left hemisphere lesions (p = 0.018). Conclusions Affected arm use in individuals with chronic stroke is related to activities and participation. Given the importance of arm use in activities and participation after stroke, rehabilitation therapists may consider utilizing the REACH Scale, a simple and quick outcome measure, as a means to assess arm use and implement effective interventions for improving arm use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".