Reliability and Validity of the English, Chinese, Korean, Indonesian, and Vietnamese Versions of the Public Health Research Foundation Stress Checklist Short Form
Bibliographic record
Abstract
Abstract Background: Foreign nationals residing in Japan account for approximately 2% of the total population (i.e., approximately 2.6 million people). Of these, 12% are not proficient in speaking Japanese, and 25% feel difficulty in reading Japanese. Therefore, a simple, convenient, and accurate scale in the native language of foreign nationals is required to support their mental health. In this study, the Public Health Research Foundation Stress Checklist Short Form (PHRF-SCL (SF)) was translated into five languages, and the reliability and validity of the translations were confirmed. These scales are expected to address the needs of over half of the foreign nationals residing in Japan Methods: The five translated versions of the PHRF-SCL (SF) have been reverse-translated into the original language, Japanese. The creator confirmed that there were no inconsistencies between the Japanese and reverse-translated version. A total of 777 adults aged 18–64 years participated in the study. They were asked to complete the native language version of the PHRF-SCL (SF) and DASS 21 online. Results: The internal consistency was confirmed by the alpha coefficients of the subscales in each language version. Participants were classified into two groups based on the severity classification obtained from each subscale of the DASS 21. Scores of PHRF-SCL(SF) are significantly higher in groups classified as severe by DASS 21, thereby confirming construct validity. Concomitant validity was confirmed based on correlations with the DASS 21. Conclusions: The results indicate that the English, Chinese, Korean, Indonesian, and Vietnamese versions of the PHRF-SCL (SF) can be applied as scales for evaluating the stress levels of foreign healthy adults.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".