Mediating pathways and gender differences between shift work and subjective cognitive function
Bibliographic record
Abstract
OBJECTIVES: Increased injury risk among shift workers is often attributed to cognitive function deficits that come about as a result of sleep disruptions. However, little is known about the intermediate influences of other factors (eg, work stress, health) which may affect this relationship. In addition, gender differences in these the complex relationships have not been fully explored. The purpose of this study is to (1) identify the extent to which work and non-work factors mediate the relationship between shift work, sleep and subsequent subjective cognitive function; and (2) determine if the mediating pathways differ for men and women. METHODS: Data from the 2010 National Population Health Survey was used to create a cross-sectional sample of 4255 employed Canadians. Using path modelling, we examined the direct and indirect relationships between shift work, sleep duration, sleep quality and subjective cognitive function. Multigroup analyses tested for significantly different pathways between men and women. Potential confounding effects of age and self-reported health and potential mediating effects of work stress were simultaneously examined. RESULTS: Work stress and sleep quality significantly mediated the effects of shift work on cognition. Age and health confounded the relationship between sleep quality and subjective cognition. No differences were found between men and women. CONCLUSIONS: Occupational health and safety programmes are needed to address stress and health factors, in addition to sleep hygiene, to effectively address cognitive function among shift workers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".