Cross‐cultural validation of the CHO‐KLAT and HAEMO‐QoL‐A in Canadian French
Bibliographic record
Abstract
Multi-site studies are necessary in the field of haemophilia to ensure adequate sample sizes. Quality of life (QoL) instruments need to be harmonized across languages and cultures to facilitate their inclusion. The purpose of this study was to adapt the Canadian Haemophilia Outcomes - Kids Life Assessment Tool (CHO-KLAT(©)) and HAEMO-QoL-A(©) to French for Canada. The CHO-KLAT and the HAEMO-QoL-A are haemophilia-specific measures of QoL for boys and men respectively. Both measures originated in English, were translated into Canadian French by clinicians with expertise in haemophilia care, back-translated by expert translators and harmonized by a multi-disciplinary team. The harmonized versions were evaluated through a cognitive debriefing process with 6 boys with haemophilia, their parents and 10 men with haemophilia. The final versions were validated in a sample of 19 boys with haemophilia, 19 parents, and 22 men with haemophilia along with a generic QoL scale: the PedsQL for children; and the SF-36 for adults. The translation and cognitive debriefing processes resulted in a preliminary version that maintained the intent of the original questions. The validation study estimated the mean score for the child-reported CHO-KLAT at 71.9 (SD 10.4), and the adult-reported HAEMO-QoL-A at 79.1 (SD 21.3). The CHO-KLAT correlated 0.64 with the PedsQL and the HAEMO-QoL-A correlated 0.78 with the SF-36 physical component summary score. The French-Canadian version of the CHO-KLAT and HAEMO-QoL-A are valid. These measures are available for use in multi-site haemophilia trials and clinical practices to capture QoL data from French Canadians.
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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 | 0.026 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".