Danish translation and linguistic validation of the BODY-Q Chest Module
Bibliographic record
Abstract
The aim of this study was to translate and linguistically validate the patient-reported outcome (PRO) instrument BODY-Q Chest Module, designed to measure outcomes following chest contouring surgery. The BODY-Q Chest Module includes two scales that measure appearance of chest and nipples. The translation and validation were performed according to the guidelines from the world health organization (WHO) and the international society for pharmacoeconomics and outcomes research (ISPOR). This approach involved two independent forward translations, a backwards translation, an expert panel meeting and cognitive debriefing interviews with patients. Each step was undertaken with the aim of achieving a conceptual and culturally equal instrument. This process led to a linguistically validated and conceptually equivalent danish version of the BODY-Q Chest Module. The forward translation resulted in several discrepant translations of items that were harmonized to form the backward translation. This translation included three items with conceptual differences that required further revision. The revised version presented at the expert panel meeting had six items that needed to be revised due to conceptual discrepancies. The cognitive debriefing interviews led to revision of one item. The practices from the who and ispor guidelines were essential to developing a translation that preserved the meaning of the content of the BODY-Q Chest Module from the original development study. The translation and linguistic validation methods used in our study could be used for further translations and validation of pro instruments. These new scales have since been field-tested as part of an international psychometric study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".