The Rasch Analysis Shows Poor Construct Validity and Low Reliability of the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0) Questionnaire
Bibliographic record
Abstract
This study aims to test the construct validity and reliability of the Quebec User Evaluation of Satisfaction with assistive Technology 2.0 (QUEST)-device, an eight-item questionnaire for measuring satisfaction with assistive devices. We collected 250 questionnaires from 79 patients and 32 caregivers. One QUEST was completed for each assistive device. Five assistive device types were included. QUEST was tested with the Rasch analysis (Many-Facet Rating Scale Model: persons, items, and device type). Most patients were affected by neurological disabilities, and most questionnaires were about mobility devices. All items fitted the Rasch model (InfitMS range: 0.88-1.1; OutfitMS: 0.84-1.28). However, the ceiling effect of the questionnaire was large (15/111 participants totalled the maximum score), its targeting poor (respondents mean measure: 1.90 logits), and its reliability was 0.71. The device classes had different calibrations (range: -1.18 to 1.26 logits), and item 3 functioned differently in patients and caregivers. QUEST satisfaction measures have low reliability and weak construct validity. Lacking invariance, the QUEST total score is unsuitable for comparing the satisfaction levels of users of different device types. The differential item functioning suggests that the QUEST could also be problematic for comparing satisfaction in patients and caregivers.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".