English Translation and Cultural Adaptation of the Knee Numeric-Entity Evaluation Score (KNEES-ACL): A Condition-Specific Patient-Reported Outcome Measure for Anterior Cruciate Ligament Injuries
Bibliographic record
Abstract
BACKGROUND: The Knee Numeric-Entity Evaluation Score (KNEES-ACL) is a 41-item condition-specific patient-reported outcome measure (PROM) that was developed for patients with an anterior cruciate ligament (ACL) deficiency and patients after ACL reconstruction. This measure is intended to be used for longitudinal clinical studies. The KNEES-ACL has demonstrated face and content validity and superior responsiveness compared with other PROMs commonly used in patients with an ACL injury. However, this PROM was developed in Danish and has not been appropriately translated and culturally adapted into North American English. PURPOSE: To translate and culturally adapt the KNEES-ACL from Danish to North American English. STUDY DESIGN: Cross-sectional study. METHODS: Translation from Danish to English and cultural adaptation to a North American context were performed according to the dual panel method. First, the Danish KNEES-ACL was translated by a bilingual panel, which provided multiple English wording options for each item. Second, an English lay panel focus group was formed to determine the wording for each item that best reflected everyday spoken language. Finally, individual think-aloud cognitive interviews were conducted with patients after an ACL injury to evaluate the relevance, comprehensiveness, and comprehensibility of the PROM content and questions. Repeated modifications and testing were performed until a final English version of the KNEES-ACL was constructed. RESULTS: Participants in the lay panel focus group were able to reach unanimous decisions for each of the 41 items. Further changes to 17 items were made after 8 think-aloud interviews with patients with ACL injuries at various time points to ensure that items were relevant and being interpreted consistently among different types of patients. The final KNEES-ACL consisted of 6 domains: Problems with Daily Activities, Mental Impact, Stability, Strength and Control, Pain, and Sport and Physical Activity. CONCLUSION: The English KNEES-ACL for patients with ACL injuries has undergone appropriate translation and cultural adaptation using established dual panel and cognitive interviewing methods in the population of interest. The psychometric properties of the English KNEES-ACL will likely mirror those established with the Danish version. However, direct validation of the psychometric properties of the English version would be beneficial before widespread use.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".