Analysis of the reliability and validity of the Turkish version of the intermittent and constant osteoarthritis pain questionnaire
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to analyze the validity and reliability of the Turkish version (ICOAP-TR) of the intermittent and constant osteoarthritis pain (ICOAP) questionnaire in patients with knee osteoarthritis (OA). METHODS: Thirty-eight volunteer patients diagnosed with knee OA answered the questionnaire twice with an interval of 2-4 days. The reliability of the measurement was assessed using Cronbach's alpha coefficient and intraclass correlation (ICC) for test-retest reliability. Criterion validity was tested against the Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain score and visual analog scale (VAS) designed to assess the perceived discomfort rated by the patient. RESULTS: Test-retest reliability was found to be ICC=0.942 for total score, 0.902 for constant pain subscale, and 0.945 for intermittent pain subscale. Internal consistency was tested using Cronbach's alpha and was found to be 0.970 for total score, 0.948 for constant pain subscale, and 0.972 for intermittent pain subscale. For criterion validity, the correlation between the total score of ICOAP-TR and WOMAC pain subscale was r=0.779 (p<0.05), and correlation between total score of ICOAP-TR and VAS was r=0.570 (p<0.05). CONCLUSION: The ICOAP-TR is a reliable and valid instrument to be used with patients with knee OA.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".