Reliability of an observation-based scoring grid to assess bimanual performance during unstandardized tasks in adults living with cerebral palsy
Bibliographic record
Abstract
Purpose: Most activities of daily living (ADLs) require the use of both upper extremities.However, few assessments exist to assess bimanual performance, especially among adults living with cerebral palsy (CP).The aim of this preliminary study is to assess the interrater reliability and convergent validity of the Assisting Hand Assessment (AHA) scoring grid applied to unstandardized ADLs.Materials and methods: For this validation study, nineteen adults living with spastic unilateral CP were videotaped performing seven bimanual ADLs.Three raters assessed the videos independently using the 20-item grid of the AHA.Gwet's AC2 was used to assess interrater reliability.Kendall's Tau-b correlation was used between the observation-based scoring grid and Jebsen-Taylor Hand Function Test (JTHFT) scores to assess convergent validity.Results: Interrater reliability was good (0.84, SD = 0.02).The correlation with the JTHFT was high (τb = -0.74;p < 0.001). Conclusion:The results show the potential of using an observation-based scoring grid with unstandardized ADLs to assess bimanual performance in adults living with CP, but further research on psychometric properties is needed.This method allows for an assessment that is occupation-oriented, ecological, and meaningful. h IMPLICATIONS FOR REHABILITATION• An observation-based scoring grid (Assisting Hand Assessment) can be applied in unstandardized activities of daily living to assess bimanual performance in adults with cerebral palsy.• This method allows an occupation-oriented, ecological, and client-meaningful assessment.• Although this approach is a pilot measure, it can be used by clinicians and researchers until further psychometric analyses are undertaken.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".