The Wheelchair Use Confidence Scale (WheelCon): Arabic translation, adaptation, and validation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study translated and culturally adapted the Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M) and the Wheelchair Use Confidence Scale for Power Wheelchair Users (WheelCon-P) into Arabic and examined their reliability and validity. Internal consistency and test–retest reliability were examined, and concurrent validity was evaluated using Pearson correlation coefficients with the Arabic versions of the Functioning Everyday with a Wheelchair (FEW) and the Functional Mobility Assessment (FMA). The Arabic translated versions of the WheelCon-M (WheelCon-M-A) and the WheelCon-P (WheelCon-P-A) were administered to 33 adult wheelchair users. Cronbach’s α was 0.94 (p < 0.01) for the WheelCon-M-A and 0.95 (p < 0.01) for the WheelCon-P-A. The WheelCon-M-A and WheelCon-P-A were reliable with respect to test–retest with an ICC of 0.974 (p < 0.01) and 0.965 (p < 0.01), respectively. The Pearson correlation coefficient of the WheelCon-M-A scores was 0.776 with the FEW scores and 0.685 with the FMA scores (p < 0.01). The Pearson correlation coefficient of the WheelCon-P-A scores was 0.782 with the FEW scores and 0.654 with the FMA scores (p < 0.01). This study has provided preliminary evidence of new valid, reliable, and useful tools for healthcare professionals to help measure confidence with wheelchair use among Arab wheelchair users.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it