Cross-Cultural Adaptation of the CHAMPS Questionnaire in French Canadians with COPD
Bibliographic record
Abstract
Physical activity is difficult to measure in individuals with COPD. The Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire demonstrated strong clinometric properties when used with the elderly and with those affected by chronic disease. Study objectives were to translate, culturally adapt the CHAMPS into French, and reexamine its test-retest reliability and construct validity in French and English Canadians with COPD. This paper presents the cross-cultural adaptation of the CHAMPS; results of its clinometric testing will be described in another article. The CHAMPS examines the degree of physical activity performed in a typical week through two summary scales, caloric expenditure and activity frequency. The CHAMPS was only in English; thus, a cross-cultural adaptation was needed to translate the CHAMPS into French for use in French Canadians with COPD. Cross-cultural adaptation consisted of forward and back translation, with expert review at each stage of translation: minor inconsistencies were uncovered and rectified. Five French participants with COPD completed the finalized Canadian French CHAMPS and participated in cognitive debriefing; no problematic items were identified. A structured and stepwise, cross-cultural adaptation process produced the Canadian French CHAMPS, with items of equivalent meaning to the English version, for use in French Canadians with COPD.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".