Translation and Cross-cultural Validation of the English Young Adult Burn Outcome Questionnaire (YABOQ) in Spanish
Bibliographic record
Abstract
The Young Adult Burn Outcome Questionnaire (YABOQ) is a validated, English-language patient-reported outcome assessment of young adults' recovery from burn injury across 15 scale domains. We evaluated the cross-cultural validity of a newly developed Spanish version of the YABOQ. Secondary data from English- and Spanish-speaking burn survivors (17 to 30 years of age) were obtained from the Multicenter Benchmarking Study. We conducted classic psychometric analyses and evaluated the measurement equivalence of the English and Spanish YABOQs in logistic and ordinal logistic regression differential item functioning analyses. All multi-item scales in the Spanish YABOQ demonstrated adequate reliability except the Pain and Itch scales. One item in the Perceived Appearance scale showed differential item functioning across English- and Spanish-speaking burn survivors, but the observed differential item functioning had no clinically significant impact on scale-level Perceived Appearance scores. Our findings support the cross-cultural validity of the YABOQ Physical Function, Perceived Appearance, Sexual Function, Emotion, Family Function, Family Concern, Satisfaction with Symptom Relief, Satisfaction with Role, Work Reintegration and Religion scales among English- and Spanish-speaking young adult burn survivors. This work supports the use of these English and Spanish YABOQ scales to assess the effect of therapeutic interventions on young adults' burn outcomes in pooled analyses and to assess disparities in young adults' burn outcomes across language groups.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".