Psychometric evaluation of the Arabic version of the Quebec user evaluation of satisfaction with assistive technology (A-QUEST 2.0) in prosthesis users
Bibliographic record
Abstract
BACKGROUND: The evaluation of patient satisfaction and perceptions plays a vital role in determining the quality of prosthesis users' devices and the competency of healthcare services. AIM: To evaluate the psychometric properties of the Arabic Quebec User Evaluation of Satisfaction with Assistive Technology (A-QUEST 2.0) with prosthetics users. DESIGN: A methodological study. SETTING: Saudi Arabia, Turkey. POPULATION: A convenience sample of outpatient prosthesis users (N.=183). METHODS: The A-QUEST 2.0 includes two subscales respectively evaluating the user's satisfaction with the device and the services provided. The data for each subscale were investigated using Rasch analysis to evaluate the item fit, reliability indices, item difficulty, local item dependency, and differential item functioning (DIF). RESULTS: Both subscales met the Rasch criteria for the functioning of rating scale categories. All items showed an acceptable fit to the Rasch model. The person separation indices for the Device and Services subscales were 2.21 (Cronbach's α=0.90) and 1.72 (Cronbach's α=0.85), respectively. Therefore, the two subscales are sensitive enough to distinguish between at least three different levels of satisfaction. The unidimensionality of each subscale was confirmed, and none of the items displayed differential item functioning across age, gender, location of amputation, country, and duration of use. CONCLUSIONS: Overall, the findings indicate the psychometric evaluation of A-QUEST 2.0 is effective with prosthesis users across different clinical contexts and cultures. Thus, the A-QUEST 2.0 allows for a comprehensive understanding of users' perceptions of prosthesis characteristics, particularly among subjects with lower limb amputations caused by traumatic injuries. CLINICAL REHABILITATION IMPACT: Our paper provides clinicians dealing with Arabic patients a validated outcome measure for satisfaction with prosthesis. Besides providing information in the development of new products and service delivery. Further studies are necessary to improve the measure's metric quality in different contexts and for different prosthesis devices.
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How this classification was reachedexpand
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 | 0.006 | 0.007 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".