Cross-cultural adaptation of the CHO-KLAT for boys with hemophilia in rural and urban china
Bibliographic record
Abstract
BACKGROUND: Quality of life (QoL) is increasingly recognized as an important outcome measure in clinical trials. The Canadian Hemophilia Outcomes-Kids Life Assessment Tool (CHO-KLAT) shows promise for use in China. OBJECTIVE: To adapt the CHO-KLAT version 2.0 for use in clinical trials in China. METHODS: Forward and back translations of the CHO-KLAT2.0 were completed in 2008. Between October 2009 and June 2010, a series of 3 focus groups were held with 20 boys and 31 parents in rural and urban China to elicit additional concepts, important to their QoL, for the Chinese CHO-KLAT2.0. All of the items identified by boys and parents were reviewed by a group of experts, resulting in a Chinese version of the CHO-KLAT2.0. This version underwent a detailed cognitive debriefing process between October 2010 and June 2011. Thirteen patient-parent pairs participated in this cognitive debriefing process until a stable and clearly understood Chinese version of the CHO-KLAT2.0 was obtained. RESULTS: The initial back translation of the Chinese CHO-KLAT2.0 was slightly discrepant from the original English version on 12 items. These were all successfully adjudicated. The focus groups identified 9 new items that formed an add-on Socio-Economic Context (SEC) module for China. Linguistic improvements were made after the 2nd, 5th, 7th and 13th cognitive debriefings pairs and affected a total of 18 items. The result was a 35 item CHO-KLAT2.0 and a SEC module in Simplified Chinese, both of which have good content validity. CONCLUSION: This detailed process proved to be extremely valuable in ensuring the items were accurately interpreted by Chinese boys with hemophilia ages ≤18 years. The need for the additional SEC module highlighted the different context that currently exists in China with regard to hemophilia care as compared to many Western countries, and will be important in tracking progress within both rural and urban China over time. Changes based on the cognitive debriefings suggest that expert verbatim translation alone is not sufficient. The Chinese version of the CHO-KLAT2.0 is well understood by boys with hemophilia in China. Next steps will be to test its construct validity and reliability in boys with hemophilia in China.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".