Oxford Knee Score: crosscultural adaptation and validation of the Turkish version in patients with osteoarthritis of the knee
Bibliographic record
Abstract
OBJECTIVE: The Oxford Knee Score (OKS) is a valid, short, self-administered, and site- specific outcome measure specifically developed for patients with knee arthroplasty. This study aimed to cross-culturally adapt and validate the OKS to be used in Turkish-speaking patients with osteoarthritis of the knee. METHODS: The OKS was translated and culturally adapted according to the guidelines in the literature. Ninety-one patients (mean age: 55.89±7.85 years) with knee osteoarthritis participated in the study. Patients completed the Turkish version of the Oxford Knee Score (OKS-TR), Short-Form 36 Health Survey (SF-36), and Western Ontario and McMaster Universities Index (WOMAC) questionnaires. Internal consistency was tested using Cronbach's α coefficient. Patients completed the OKS-TR questionnaire twice in 7 days to determine the reproducibility. Correlation between the total results of both tests was determined by Spearman's correlation coefficient and intraclass correlation coefficients (ICC). Validity was assessed by calculating Spearman's correlation coefficient between the OKS, WOMAC, and SF-36 scores. Floor and ceiling effects were analyzed. RESULTS: Internal consistency was high (Cronbach's α: 0.90). The reproducibility tested by 2 different methods showed no significant difference (p>0.05). The construct validity analyses showed a significant correlation between the OKS and the other scores (p<0.05). There was no floor or ceiling effect in total OKS score. CONCLUSION: The OKS-TR is a reliable and valid measure for the self-assessment of pain and function in Turkish-speaking patients with osteoarthritis of the knee.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".