The Effect of Shift Rotation on Employee Cortisol Profile, Sleep Quality, Fatigue, and Attention Level
Bibliographic record
Abstract
BACKGROUND: Disrupted circadian rhythm, especially working night duty together with irregular sleep patterns, sleep deprivation, and fatigue, creates an occupational health risk associated with diminished vigilance and work performance. PURPOSE: This study reviewed the effect of shift rotations on employee cortisol profile, sleep quality, fatigue, and attention level. METHODS: Researchers conducted a systematic review of relevant articles published between 1996 and 2008 that were listed on the following databases: SCOPUS, OVID, Blackwell Science, EBSCO Host, PsycINFO, Cochrane Controlled Trials Register, and CEPS. A total of 28 articles were included in the review. RESULTS: Previous research into the effects of shift work on cortisol profiles, sleep quality, fatigue, and attention used data assessed at evidence Levels II to IV. Our systematic review confirmed a conflict between sleep-wake cycle and light-dark cycle in night work. Consequences of circadian rhythm disturbance include disruption of sleep, decreased vigilance, general feeling of malaise, and decreased mental efficiency. Shift workers who sleep during the day (day sleepers) experience cortisol secretion increases, which diminish the healing power of sleep and enjoy 1 to 4 hours less sleep on average than night sleepers. Sleep debt accumulation results in chronic fatigue. Prolonged fatigue and inadequate recovery result in decreased work performance and more incidents. Rotation from day shift to night shift and its effect on shift workers was a special focus of the articles retained for review. CONCLUSIONS: Disturbed circadian rhythm in humans has been associated with a variety of mental and physical disorders and may negatively impact on work safety, performance, and productivity.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".