Danish Linguistic Validation and Cultural Adaptation of the LIMB-Q Kids
Bibliographic record
Abstract
(1) Background: Lower Limb deformities include many conditions where pain and physical limitations negatively impact the health-related quality of life (HRQL) of children. The ideal way to assess this impact is by using a Patient Reported Outcome Measure (PROM). Such a condition-specific PROM is under development, called LIMB-Q Kids. This study aimed to perform a translation and cultural adaption (TCA) of the LIMB-Q Kids for use in Danish-speaking children. (2) Methods: TCA guidelines established by the World Health Organization (WHO) and the Professional Society for Health Economics and Outcomes Research (ISPOR) were followed. This process consisted of two independent forward translations, a reconciliation meeting, a backward translation with an assessment, an expert meeting, cognitive interviews with patients, editing based on the interviews, and proofreading. (3) Results: The TCA process contributed to the Danish version of LIMB-Q Kids. The reconciliation meeting resulted in a reconciled Danish version. The revision of the backward translation led to 16 corrections, and after the expert panel meeting, 26 changes were made. Twelve cognitive interviews led to nine changes, which were validated by two further interviews. Proofreading led to no further comments. (4) Conclusions: The TCA process led to a linguistically validated and culturally adapted Danish version of LIMB-Q Kids. This version is being used in the international field test 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 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 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".