Chinese adaptation and validation of the patellofemoral pain severity scale
Bibliographic record
Abstract
OBJECTIVE: This study validated the Patellofemoral Pain Severity Scale translated into Chinese. DESIGN AND SETTING: The Chinese Patellofemoral Pain Severity Scale was translated from the original English version following standard forward and backward translation procedures recommended by the International Society for Pharmacoeconomics and Outcomes Research. The survey was then conducted in clinical settings by a questionnaire comprising the Chinese Patellofemoral Pain Severity Scale, Kujala Scale and Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index. SUBJECTS: Eighty-four Chinese reading patients with patellofemoral pain were recruited from physical therapy clinics. MAIN MEASURES: Internal consistency of the translated instrument was measured by Cronbach alpha. Convergent validity was examined by Spearman rank correlation coefficient (rho) tests by comparing its score with the validated Chinese version of the Kujala Scale and the WOMAC Osteoarthritis Index while the test-retest reliability was evaluated by administering the questionnaires twice. RESULTS: Cronbach alpha values of individual questions and their overall value were above 0.85. Strong association was found between the Chinese Patellofemoral Pain Severity Scale and the Kujala Scale (rho = -0.72, p < 0.001). Moderate correlation was also found between Chinese Patellofemoral Pain Severity Scale with the WOMAC Osteoarthritis Index (rho = 0.63, p < 0.001). Excellent test-retest reliability (Intraclass correlation coefficient = 0.98) was demonstrated. CONCLUSIONS: The Chinese translated version of the Patellofemoral Pain Severity Scale is a reliable and valid instrument for patients with patellofemoral pain.
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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 | 0.010 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".