Wheelchair use confidence scale for Arab pediatric manual wheelchair users: preliminary evaluation of its measurement properties
Bibliographic record
Abstract
Introduction This study translated the pediatric Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M-P) into Arabic (WheelCon-M-A-P) and evaluated whether the translation produced scores similar to the original English version. Methods The English version was first translated into Arabic and then verified by back translation method by expert committee in the field of rehabilitation and wheelchair service provision. The final versions were administered to assess confidence with manual wheelchair use among children. Each participant was asked to complete both the WheelCon-M-P English version and the WheelCon-M-A-P Arabic version in a random sequence. Kappa statistics were used to quantify the level of agreement between scores obtained from both versions. Results Participants (n = 48) had an average age of 14.2 years, were all bilingual, and 54% were male. Kappa agreement obtained was 0.54 (95% confidence interval, 0.49–0.62) indicating significant moderate agreement between the two versions (p < 0.000). Discussion This study provides preliminary evidence of a valid WheelCon-M-A-P to assess confidence with manual wheelchair use among Arabic-speaking children. Future studies to further test its psychometric properties are crucial.
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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 | 0.003 | 0.008 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".