Development and Validation of a Scale for Rating Motor Compensations Used for Reaching in Patients With Hemiparesis: The Reaching Performance Scale
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Recent movement analysis studies have described compensatory movement strategies used by people with hemiparesis secondary to stroke during reaching and grasping tasks. The purpose of this article is to describe the development of a new scale--the Reaching Performance Scale (RPS)--for assessing compensatory movements for upper-extremity reaching in people with hemiparesis secondary to stroke. SUBJECTS: Twenty-eight individuals with hemiparesis, with a mean age of 54.9 years (SD=18.6), participated. METHODS: The study design involved scale development with expert panels and criterion standards for validity. Participants were evaluated on the new scale as well as other clinical tests for validity. They were videotaped while performing reaching and grasping movements. RESULTS: The RPS scores correlated with measurements of grip force and Chedoke-McMaster Stroke Assessment and Upper Extremity Performance Test for the Elderly (TEMPA) scores. The RPS discriminated patients with different impairment levels according to the Chedoke-McMaster Stroke Assessment. Preliminary intrarater and interrater reliability coefficients were acceptable for the whole scale. Mean kappa values on individual scale components for 3 raters represented a mean of 67% (SD=13.5%) agreement. DISCUSSION AND CONCLUSION: Although the RPS shows some types of validity, more rigorous tests of reliability are needed for meaningful conclusions. This study is a first step in validating the scale to assess efficacy of intervention for motor recovery of the arm.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".