Comparison of the two methods of defining high-stress on the Japanese Stress Check Program
Bibliographic record
Abstract
OBJECTIVES: In Japan, companies are required to implement a "stress check program" to prevent mental health problems in workers. To identify "high-stress" workers, the Brief Job Stress Questionnaire (BJSQ) is recommended. According to the stress check program manual issued by the government, high-stress can be defined using two criteria, either the "sum method" (simply summing the scores for each scales) or the "score converted method" (using converted scores according to the conversion table for each scales). In this study, we examined the differences in results found using these two criteria on "stress check program" data. METHODS: We used data of 71,422 workers in 117 companies and organizations who conducted stress checks in 2016. The prevalence of high-stress was calculated by applying the two criteria simultaneously, and the chi-square test was used to compare the proportion of workers with high-stress. We subsequently divided participants into the four following groups and calculated the proportion of each group: group A was defined as having high-stress by both criteria; group B, only by the sum method; group C, only by the score converted method; and group D, not defined as high-stress by either criterion. We compared the average values of stress response among four groups using the Kruskal-Wallis test, and further compared the average values between group B and group C using the Bonferroni method. RESULTS: The average age of participants was 43.7 ± 11.1, and 66.8% were males. The proportion of those defined as having high-stress were 11.7% using the sum method and 13.2% using the score converted method; the proportion of high-stress workers was thus significantly higher when using the score converted method (p <.001). Physical stress response was higher in group B; however, lack of vigor, irritation, fatigue, and depression were higher in group C (p <.01). CONCLUSIONS: Compared to the sum method, 1.5% more high-stress workers were observed using the converted method, and this result was similar for individual and employment-related factors. Furthermore, workers were more likely to be judged as having "high-stress" when the score of the physical stress response was higher in the sum method. Hereafter, it is important to consider which criteria are applied when discussing proportions of high-stress. Further research is needed to examine which criteria will predict health disorders.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".