Differences between Hair Cortisol Concentrations in Day Shift Workers and Rotating Night Shift Workers in Japan
Bibliographic record
Abstract
PURPOSE: The study aimed to determine the differences between stress levels in day shift workers and night shift workers by measurements of hair cortisol concentration (HCC) and by using self-administered questionnaires. METHODS: HCC was measured by using liquid chromatography-mass spectrometry. The subjective stress level was evaluated by a brief job stress questionnaire, stress response scale-18 (SRS-18), and visual analog scale (VAS). RESULTS: Mean (± standard deviation: SD) HCC in the 16 subjects was 17.28 ± 7.39 pg/mg. There was no significant difference between HCCs in day shift workers (17.98 ± 3.03 pg/mg) and rotating night shift workers (16.37 ± 1.86 pg/mg). There were also no significant differences in SRS-18 scores, job-related stress scale scores, and VAS scores between day shift workers and rotating night shift workers. There was a significant difference in HCC between the group in which the stress condition was weak or normal and the group in which the stress condition was slightly strong or definitely strong according to the SRS-18 level (p = 0.030). CONCLUSIONS: Day shift workers and rotating night shift workers have similar HCCs and similar degrees of job-related stress. In rotating shift workers who feel strong stress, acquirement of resilience due to stress coping for medium- to long-term stress may be involved in low HCC.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".