THE JAPANESE TRANSLATION AND CULTURAL ADAPTATION OF EXPANDED PROSTATE CANCER INDEX COMPOSITE (EPIC)
Bibliographic record
Abstract
PURPOSE: To develop a Japanese version of the Expanded Prostate Cancer Index Composite (EPIC): originally designed to measure the Quality of Life of localized prostate cancer patients, after careful assessments of cross-cultural equivalence, face validity and practically. METHODS: We translated the original version that consisted of 50 items into a preliminary Japanese version. This multi-stage procedure included a forward-translation, back-translation and discussion with the original developer. Additionally, we tested the preliminary Japanese version on 11 localized prostate cancer patients and identified problems with its cross-cultural equivalence, practicality. Based on the findings of this pretest, we revised the Japanese version. Consensus by discussion among all researchers was obtained through out this process. RESULTS: The original developer reviewed the back-translation of the preliminary Japanese version: some wording was revised. In the pretest, the average age of patients was 68.8 years old. Four of the sexual subscale showed over 10 percent missing data. In five items, all patients chose identical answers. We conducted an in-depth qualitative investigation of these items. The average response time was 11.7 minutes. We revised the Japanese to reflect patients' opinions as much as possible. Items which were showed problems in terms of cross-cultural adaptation included questions measuring 'bother' and two items of the sexual subscale. The wordings of these items were revised so that Japanese patients could easier understand them. We ensured that the original developer's intentions remained the same. The original developed approved all revisions. CONCLUSION: We translated and adapted the original EPIC to the Japanese culture. The Japanese version of EPIC was found to be functional in the pretest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".