The relationship between chronotype and sleep behavior during rotating shift work: a field study
Bibliographic record
Abstract
Shift work, an essential part of our 24/7 society, inevitably leads to displacement of the habitual sleep period and thereby to misalignment of the internal circadian timing system with the rest-activity cycle and the environment. How interindividual differences in circadian organization affect sleep duration and timing during rotating shift work is not fully understood. The objective of this study was to assess the effect of chronotype, shift type, and their interaction on actigraphy-based sleep behavior in 74 police officers (20 women and 54 men; age [mean ± SD]: 32.1 ± 5.4 years) involved in rotating shift work throughout a 28- to 35-day work cycle consisting of morning, evening, and night shifts. Using linear mixed modeling, we found that chronotype was associated with sleep duration depending on the shift type: increasing morningness was correlated with longer sleep duration during series of consecutive morning shifts, while increasing eveningness was correlated with longer sleep duration during series of evening shifts. During series of night shifts, increasing eveningness was associated with a longer duration of the main sleep episode, but this relationship was attenuated and no longer significant when naps were taken into account due to increased napping in morning chronotypes during series of night shifts. Providing a detailed within-subject characterization of sleep behavior across a complete work cycle consisting of morning, evening, and night shifts, this study advances the understanding of the relationship between chronotype and sleep in rotating shift workers and supports the implementation of work schedules that take into account chronobiological principles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".