Test–retest reliability and construct validity of the Aspects of Wheelchair Mobility Test as a measure of the mobility of wheelchair users
Bibliographic record
Abstract
BACKGROUND: The Aspects of Wheelchair Mobility Test (AWMT) was developed for use in a repeated measures format to provide comparative effectiveness data on mobility facilitated by different wheelchair types. It has been used in preliminary studies to compare the mobility of wheelchairs designed for low-resource areas and is intended to be simple and flexible enough so as to be used in low-technology settings. However, to reliably compare the impact of different types of wheelchairs on the mobility of users, a measure must first be a reliable and valid measure of mobility. METHODS: This study investigated the test-retest reliability and concurrent validity for the AWMT 2.0 as a measure of mobility. For reliability testing, participants in a low-resource setting completed the tests twice in their own wheelchairs at least one week apart. For concurrent validity, participants also completed the Wheelchair Skills Test Questionnaire (WST-Q), a related but not identical validated assessment tool. RESULTS: Concurrent validity was indicated by a significant positive correlation with an r value of 0.7 between the WST-Q capacity score and the AWMT 2.0 score. Test-retest reliability was confirmed by an intraclass correlation coefficient greater than 0.7 between the two trials. CONCLUSION: Results support the preliminary reliability and validity of the AWMT 2.0, supporting its effectiveness in comparing the mobility provided by different wheelchair types. This information can be used to enable effective use of limited funds for wheelchair selection at individual and organisational scales.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".