The validation and cross-cultural adaptation of the PainDETECT questionnaire in osteoarthritis-related pain
Bibliographic record
Abstract
BACKGROUND: Patients with knee osteoarthritis (KOA) often experience persistent pain and functional impairment after total knee arthroplasty (TKA), which presents challenges for pain management. Accurate preoperative assessment of pain characteristics is crucial for tailoring individualized treatment plans. The PainDETECT Questionnaire has been widely used to identify neuropathic components in chronic pain and has been validated for its reliability and validity across various cultural contexts. However, a culturally adapted version tailored to Chinese patients is currently lacking. This study aims to translate and culturally adapt PainDETECT for Chinese patients and evaluate its validity in TKA patients in China. METHODS: This study followed international guidelines to translate and adapt the PainDETECT Questionnaire (PDQ) into Chinese (PDQ-CV). A cohort of 241 knee osteoarthritis (KOA) patients completed the PDQ-CV, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), EuroQol-5 Dimensions-5 Levels (EQ-5D-5 L), and Central Sensitization Inventory Chinese Version (CSI-CV). We assessed internal consistency using Cronbach's alpha and test-retest reliability via intraclass correlation coefficient (ICC). Construct and structural validity were evaluated through Pearson correlations and factor analyses. RESULTS: The PDQ-CV demonstrated good acceptability among KOA patients, with no floor or ceiling effects observed. Internal consistency was high (Cronbach's α = 0.896), and test-retest reliability was excellent (ICC = 0.994; 95% CI: 0.943-1.045). The PDQ-CV total score showed significant positive correlations with WOMAC (r = 0.589, P < 0.01), EQ-5D-5 L (r = 0.533, P < 0.01), and CSI-CV (r = 0.776, P < 0.01). Exploratory factor analysis (EFA) extracted two primary factors, corresponding to the sensory dimension (52.1% variance) and the affective dimension (16.3% variance), explaining a total variance of 68.4%. CONCLUSION: The PDQ-CV demonstrated good feasibility, reliability, and validity in Chinese KOA patients, supporting its use in clinical practice and providing a foundation for future research.
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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 | 0.017 | 0.024 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".