Validation of the Chinese version of the Brief Pain Inventory in patients with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) primarily presents with symptoms of pain and compromised functionality. Pain is a subjective manifestation that necessitates the employment of reliable evaluation tools for practical assessment, thereby enabling the formulation of appropriate interventional strategies. The Brief Pain Inventory (BPI) is a widely utilized questionnaire for evaluating the status of chronic pain. The purpose of the present study is to translate the short form of BPI into Chinese version (BPI-CV) and conduct cross-cultural adaptation to evaluate the psychometric characteristics of BPI-CV in KOA patients. METHODS: BPI-CV was translated and cross-culturally adapted according to internationally recognized guidelines. A cohort comprising 150 patients diagnosed with KOA successfully completed the demographic questionnaire, BPI-CV, Western Ontario and McMaster University Osteoarthritis Index (WOMAC), and the EuroQoL Group's five-dimension questionnaire (EQ-5D). Internal consistency and test-retest analysis were used to evaluate the reliability. The internal consistency of the scale items was evaluated by calculating the Cronbach's α value (> 0.7). We chose to employ two scales commonly used in the evaluation of KOA patients: the disease-specific WOMAC scale and the universal EQ-5D scale. Construct validity was determined through Pearson correlation analysis, comparing BPI scores with those obtained from the WOMAC and EQ-5D scales. Exploratory factor analysis was used to structural validity. RESULTS: The BPI-CV was well accepted with no ceiling or floor effect. Cronbach's α for assessing internal consistency was 0.894. Test-retest reliability was excellent with an ICC of 0.852 (95%CI 0.785-0.905). The BPI-CV showed moderate to strong correlations with the pain dimension (r = 0.496-0.860) and the functional interference dimension (r = 0.517-0.712) of the WOMAC and the EQ-5D (r = 0.527-0.743). Three factors resulted using exploratory factor analysis: pain severity, activity interference, and emotional interference, accounting for 79.0% of the total variance. Standard error of measurement was 0.539. CONCLUSION: BPI-CV has good feasibility, reliability, and validity. It can be recommended for KOA patients in mainland China.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".