Cross-cultural adaptation and validation of the Persian version of the Intermittent and Constant Osteoarthritis Pain Measure for the knee
Bibliographic record
Abstract
OBJECTIVE: The present study aimed to translate and evaluate the reliability and validity of the Persian version of the 11-item Intermittent and Constant Osteoarthritis Pain (ICOAP) measure in Iranian subjects with Knee Osteoarthritis (KOA). MATERIALS AND METHODS: The ICOAP questionnaire was translated according to the Manufacturers Alliance for Productivity and Innovation (MAPI) protocol. The procedure consisted of forward and backward translation, as well as the assessment of the psychometric properties of the Persian version of the questionnaire. A sample of 230 subjects with KOA was asked to complete the Persian versions of ICOAP and Knee injury and Osteoarthritis Outcome Score (KOOS). The ICOAP was readministered to forty subjects five days after the first visit. Test-retest reliability was assessed using Intraclass Correlation Coefficient (ICC), and internal consistency was assessed by Cronbach's alpha and item-total correlation. The correlation between ICOAP and KOOS was determined using Spearman's correlation coefficient. RESULT: Subjects found the Persian-version of the ICOAP to be clear, simple, and unambiguous, confirming its face validity. Spearman correlations between ICOAP total and subscale scores with KOOS scores were between 0.5 and 0.7, confirming construct validity. Cronbach's alpha, used to assess internal consistency, was 0.89, 0.93, and 0.92 for constant pain, intermittent pain, and total pain scores, respectively. The ICC was 0.90 for constant pain and 0.91 for the intermittent pain and total pain score. CONCLUSION: The Persian version of the ICOAP is a reliable and valid outcome measure that can be used in Iranian subjects with KOA.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".