Interrater Reliability of Three Versions of the Chedoke Arm and Hand Activity Inventory
Bibliographic record
Abstract
Purpose: The purpose of this study was to estimate the interrater reliability of three shortened versions of the Chedoke Arm and Hand Activity Inventory (CAHAI-7, CAHAI-8, CAHAI-9) when used with persons with acquired brain injury (ABI). The CAHAI is an assessment of upper limb function with high reliability in the stroke and ABI populations. In the stroke population, three shortened versions of the measure have established reliability. Clinicians report time constraints as a barrier to using standardized assessments; thus, establishing the reliability of the shortened versions of the CAHAI in the ABI population may increase the use of this measure. Method: This was an observational, parameter estimation study. The participants were recruited from an in-patient ABI rehabilitation programme. The administration of the CAHAI to six persons with ABI was video recorded, and the video recordings were assessed by six clinicians to estimate interrater reliability. A Latin square design was used to balance the order in which the raters evaluated the videos. A repeated-measures analysis of variance was performed, and the variance components were used to calculate an intra-class correlation coefficient (ICC) and standard error of measurement (SEM) with 95% confidence limits (CLs) for each of the shortened versions. Results: Interrater reliability was high for all three versions: CAHAI-7, ICC=0.96 (95% CL: 0.89, 0.99; SEM 2.65); CAHAI-8, ICC=0.96 (95% CL: 0.90, 0.99; SEM 2.72); and CAHAI-9, ICC=0.95 (95% CL: 0.85, 0.99; SEM 3.49). Conclusions: These results suggest that the three shortened versions of the CAHAI demonstrate high reliability in the ABI population. These versions may be particularly useful when time constraints or patient tolerance are an issue.
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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 | 0.017 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".