A Pilot Study for Remote Evaluation of Upper Extremity Motor Function After Stroke: The Arm Capacity and Movement Test (ArmCAM)
Bibliographic record
Abstract
IMPORTANCE: A simple measure that can be administered remotely by means of videoconferencing is needed for telerehabilitation. OBJECTIVE: To develop a valid and reliable measure, the Arm Capacity and Movement Test (ArmCAM), that can be administered remotely by means of videoconferencing to evaluate upper extremity motor function poststroke. DESIGN: Cross-sectional. SETTING: Participants' homes. PARTICIPANTS: A sample of people with stroke (N = 31). OUTCOMES AND MEASURES: Test-retest and interrater reliabilities were assessed through intraclass correlation coefficients (ICCs), Cohen's κ, standard error of measurement (SEM), and minimal detectable change (MDC). Interrater reliability validity was examined with Pearson and Spearman rank correlation coefficients. RESULTS: The ArmCAM (range = 0-30) consists of 10 items and takes 15 min to administer with no special equipment except for a computer and internet access. The ICCs for test-retest reliability and interrater reliability were .997 and .993, respectively. The SEM and MDC95 were 0.74 and 2.05 points, respectively. Individual items' test-retest reliability and interrater levels of agreement ranged from .811 to .957 and from .475 to .842, respectively, as measured with Cohen's κ. Correlations between the ArmCAM and the Rating of Everyday Arm-use in the Community and Home scale; the Stroke Impact Scale, hand function domain; the Fugl-Meyer Assessment for upper extremity; and the Action Research Arm Test were good to excellent. CONCLUSIONS AND RELEVANCE: The ArmCAM has good reliability and validity. It is an easy-to-use assessment designed to be administered remotely by means of videoconferencing. What This Article Adds: The ArmCAM is a psychometrically sound instrument that can be easily administered remotely by means of videoconferencing to evaluate upper extremity motor function after stroke.
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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 | 0.002 | 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 | 0.000 |
| 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".