Pain Questionnaire Development Focusing on Cross-Cultural Equivalence to the Original Questionnaire: The Japanese Version of the Short-Form McGill Pain Questionnaire
Bibliographic record
Abstract
OBJECTIVES: The present study aimed to develop a Japanese version of the Short-Form McGill Pain Questionnaire (SF-MPQ-J) that focuses on cross-culturally equivalence to the original English version and to test its reliability and validity. DESIGN: Cross-sectional design. METHOD: In study 1, SF-MPQ was translated and adapted into Japanese. It included construction of response scales equivalent to the original using a variation of the Thurstone method of equal-appearing intervals. A total of 147 undergraduate students and 44 pain patients participated in the development of the Japanese response scales. To measure the equivalence of pain descriptors, 62 pain patients in four diagnostic groups were asked to choose pain descriptors that described their pain. In study 2, chronic pain patients (N=126) completed the SF-MPQ-J, the Long-Form McGill Pain Questionnaire Japanese version (LF-MPQ-J), and the 11-point numerical rating scale of pain intensity. Correlation analysis examined the construct validity of the SF-MPQ-J. RESULTS: The results from study 1 were used to develop SF-MPQ-J, which is linguistically equivalent to the original questionnaire. Response scales from SF-MPQ-J represented the original scale values. All pain descriptors, except one, were used by >33% in at least one of the four diagnostic groups. Study 2 exhibited adequate internal consistency and test-retest reliability, with the construct validity of SF-MPQ-J comparable to the original. CONCLUSION: These findings suggested that SF-MPQ-J is reliable, valid, and cross-culturally equivalent to the original questionnaire. Researchers might consider using this scale in multicenter, multi-ethnical trials or cross-cultural studies that include Japanese-speaking patients.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".