Translation, cross-cultural adaptation and validation of the traditional Chinese intermittent and constant osteoarthritis pain (ICOAP) questionnaire for knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: To translate and culturally adapt the Intermittent and Constant Osteoarthritis and Pain (ICOAP) measure to a traditional Chinese version, and to study its psychometric properties in patients with knee osteoarthritis (KOA). METHOD: The ICOAP was translated and cross-culturally adapted into traditional Chinese according to the recommended international guidelines. A total of 110 participants with KOA in Hong Kong were invited to complete the traditional Chinese ICOAP (tChICOAP), the Chinese Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale and the Chinese Short form of Health Survey (SF-12v2). Psychometric evaluations included content validity, construct validity, internal consistency and test and retest reliability. RESULTS: All participants completed the tChICOAP questionnaire without missing items. The content validity index of all items ranged from 80% to 100%. The tChICOAP total pain and subscale scores had excellent internal consistency with Cronbach's alpha value (0.902-0.948) and good corrected item-total subscale correlations. It had high test and retest reliability (intra-class correlations 0.924-0.960). The tChICOAP constant, intermittent and total pain scores correlate strongly with the WOMAC pain subscale (r=0.671, 0.678 and 0.707, respectively, p<0.001). The tChICOAP intermittent and total scores correlate strongly with SF-12v2 physical component score (r=-0.590 and -0.558, respectively, p<0.001). CONCLUSIONS: The tChICOAP is a reliable and valid instrument to measure the pain experience of Chinese patients with KOA.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".