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 – r s = 0.464; SIS activities – r s = 0.686), participation ( r s = 0.479), and driving ( r s = 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".