Cross-cultural adaptation and validation of the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0): the development of the Taiwanese version
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To develop and validate a cross-cultural version of the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) for users of assistive technology devices in Taiwan. DESIGN: A cross-sectional survey. PROCEDURES: The standard cultural adaptation procedure was used for questionnaire translation and cultural item design. A field test was then conducted for item selection and psychometric properties testing. SUBJECTS: One hundred and five volunteer assistive device users in community. MAIN OUTCOME MEASURES: A questionnaire comprising 12 items of the QUEST 2.0 and 16 culture-specific items. RESULTS: One culture-specific item, 'Cost', was selected based on eight criteria and added to the QUEST 2.0 (12 items) to formulate the Taiwanese version of QUEST 2.0 (T-QUEST). The T-QUEST consisted of 13 items which were classified into two domains: device (8 items) and service (5 items). The internal consistencies of the device, service and total T-QUEST scores were 0.87, 0.84 and 0.90, respectively. The device, services and total T-QUEST scores achieved good test-retest stability (intraclass correlation coefficient (ICC) 0.90, 0.97, 0.95). Exploratory factor analysis revealed that T-QUEST had a two-factor structure for device and service in the construct of user satisfaction (53.42% of the variance explained). CONCLUSIONS: Users of assistive device in different culture may have different concerns regarding satisfaction. T-QUEST is the first published version of QUEST with culture-specific items added to the original translated items of QUEST 2.0. T-QUEST was a valid and reliable tool for measuring user satisfaction among Mandarin-speaking individuals using various kinds of assistive devices.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it