Adaptation and validation of the rheumatoid arthritis quality of life scale for use in Canada.
Bibliographic record
Abstract
OBJECTIVE: The Rheumatoid Arthritis Quality of Life questionnaire (RAQoL) was developed simultaneously in the UK and the Netherlands to measure quality of life in patients with RA. We adapted and validated the RAQoL for the English-Canadian and French-Canadian languages and culture. METHODS: The UK RAQoL was translated into French-Canadian by a bilingual translation panel. Separate lay panels were then used to ensure that this and the English-Canadian instruments were appropriate for use with Canadian patients. Interviews were conducted with 15 French-Canadian and 15 English-Canadian patients with RA to determine the content validity. Reliability and construct validity were established by means of test-retest mail surveys conducted with 92 French-Canadian and 87 English-Canadian RA patients. The survey consisted of the adapted RAQoL, the Health Assessment Questionnaire (HAQ), and a demographic questionnaire. RESULTS: The RAQoL was successfully adapted for both the French and English-Canadian cultures. Field testing showed both versions to be well received by respondents. Of the French-Canadian patients included in the postal survey, 52 responded at Time 1 and 50 at Time 2. For the English-Canadian sample, 54 responded at both time points. Missing data rates for the RAQoL were low and floor and ceiling effects were minimal. Test-retest reliability was good for both versions: 0.87 for the French-Canadian and 0.95 for the English-Canadian. Alpha coefficients (0.92 for the French-Canadian, 0.93 for the English-Canadian) showed the items to be adequately interrelated and scores on the measure showed moderate to high correlations with the HAQ, confirming construct validity. Both versions of the RAQoL were also able to distinguish patient groups that differed according to perceived health status and perceived severity of RA. In addition, the French-Canadian version was able to distinguish patients who rated today as bad or very bad from those who rated today as good or very good. CONCLUSION: The new versions of the RAQoL were well received by both French and English speaking Canadians. The psychometric quality of the adapted questionnaires means they are suitable for inclusion in clinical trials involving patients with RA.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".