116 Cross-cultural Translation, Adaptation and Validation of the Burnt Hand Outcome Tool (BHOT) from English to French Canadian
Bibliographic record
Abstract
Abstract Introduction The Burnt Hand Outcome Tool (BHOT) is a comprehensive patient-reported outcome measure to assess the multiple impacts of hand burn injuries. However, this tool is currently only available in English. The aim of this study was to create a French Canadian, cross-cultural translation and adaptation of the BHOT and to investigate its reliability and validity. Methods The BHOT was translated and culturally adapted following published good practice principles for patient-reported outcome measures. The steps included translation to French, backward translation, expert committee review, and cognitive debriefing with 5 adults having burn injuries excluding their hands. Then, 39 adults with hand burn injuries tested the pre-final French version of the questionnaire (BHOT-F) in order to determine its clinimetric properties. Reliability was investigated by determining the Cronbach’s alpha internal consistency coefficient. Construct convergent validity was assessed by comparing the BHOT-F to the shortened version of the Disabilities of the Arm, Shoulder and Hand questionnaire (QuickDASH). Content validity was evaluated based on comments extracted from interviews with the participants and a committee of burn care experts. Results The BHOT-F was modified during the adaption process to ensure its clarity. Cronbach’s alpha was 0.94 indicating excellent internal consistency and was > 0.75 for all sub-domains. The BHOT-F and the QuickDASH were strongly correlated (rs = .86; p < 0.01). Content validity was deemed satisfying. Conclusions The French-Canadian version of the BHOT is a reliable and valid tool that can confidently be used in clinical practice for adults with hand burn injuries and compared to data generated with Anglophone populations.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".