Development of a Japanese version of the Pain Disability Index: translation and linguistic validation
Bibliographic record
Abstract
The Pain Disability Index (PDI) is a self–reported outcome measure initially developed in English to assess disability caused by pain in seven dimensions of daily life activity, including family ⁄ home responsibilities, recreation, social activity, occupation, sexual behavior, self–care, and life–support activity. This study aimed to develop a linguistically valid Japanese version of the PDI (PDI–J) according to the guidelines for the translation and cultural adaptation of patient–reported outcome measures established by the task force of the International Society for Pharmacoeconomics and Outcomes Research. A draft of the PDI–J was developed through a forward translation of the original PDI from English to Japanese, reconciliation of the translation, back–translation from Japanese to English, and harmonization. We subsequently conducted a cognitive debriefing in five patients using the PDI–J draft and reviewed it before finalizing a linguistically valid PDI–J. We also considered a five–item version of the PDI (PDI–5–J), which excluded two items (sexual behavior and life–support activity) from the original version. This consideration was made for brevity and because sexual behavior is a considerably personal parameter that some patients may be reluctant to answer and life–support activity because it was considered ambiguous in Japanese. Therefore, we were able to develop a linguistically valid PDI–J and PDI–5–J through this process. Further study is warranted to confirm the psychometric validity and reliability of the two indices (PDI–J and PDI–5–J).
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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 | 0.022 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".