Translation, cross-cultural adaptation, and evaluation of psychometric properties of the cystic fibrosis stigma scale
Bibliographic record
Abstract
To translate, cross-culturally adapt, and evaluate the psychometric properties of the Cystic Fibrosis (CF) Stigma Scale. This exploratory methodological study involved the translation and cross-cultural adaptation using the translation, back-translation, review by experts committee, and pre-test steps. The psychometric properties were analyzed by applying the adapted instrument to a sample of 52 Brazilian individuals with CF over 18 years old. Moreover, the participants responded to the Short-Form 12-Item Survey - version 2 (SF-12v2), General Anxiety Disorder 7-item scale (GAD-7) and Cystic Fibrosis Quality of Life Questionnaire - Revised (CFQ-R). The content validity, test-retest reliability, and convergent validity were also assessed. The translation and cross-cultural adaptation obtained Cohen's kappa coefficients > 0.61 in the experts committee step and ranged between 0.48 and 0.72 in the pre-test. The Brazilian version of the CF Stigma Scale showed excellent psychometric properties, observed by the internal consistency (α = 0.836), mean correlation between items (0.3) and test-retest reliability (r = 0.886; p < 0.0001), and convergent validity (positive correlation with the anxiety scale and negative correlation with scores of overall and specific quality of life for CF). The Brazilian version of the CF Stigma Scale was accurately translated and cross-culturally adapted, with favorable psychometric properties for future studies involving the stigma experience in Brazilian individuals with CF over 18 years.
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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 | 0.030 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".