Exploring the role of shift work in the self-reported health and wellbeing of long-term and assisted-living professional caregivers in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Numerous studies have found negative outcomes between shift work and physical, emotional, and mental health. Many professional caregivers are required to work shifts outside of the typical 9 am to 5 pm workday. Here, we explore whether shift work affects the health and wellbeing of long-term care (LTC) and assisted-living (AL) professional caregivers. METHOD: The Caring for Professional Caregivers research study was conducted across 39 LTC and AL facilities in Alberta, Canada. Of the 1385 questionnaires distributed, 933 surveys (67.4%) were returned completed. After identifying 49 questions that significantly explained variances in the reported health status of caregivers, we examined whether there was a relationship between these questions and reported health status of caregivers working night shifts. RESULTS: We found significant differences between responses from those working different shifts across six of seven domains, including physical health, health conditions, mental/emotional health, quality of life, and health behaviors. In particular, we found that night shift caregivers were more likely to report incidents of poor heath (i.e., they lacked energy, had regular presences of neck and back pain, regular or infrequent incidents of fatigue or low energy, had difficulty falling asleep, and that they never do exercise) and less likely to report incidents of good health (i.e., did not expect their health to improve, were not satisfied with their health, do not have high self-esteem/were happy, were unhappy with their physical appearance, and do not get a good night's sleep), compared to caregivers working other shifts. CONCLUSIONS: Our study shows that professional caregivers working the night shift experience poor health status, providing further evidence that night shift workers' health is at risk. In particular, caregivers reported negative evaluations of their physical, mental/emotional health, lower ratings of their quality of life, and negative responses to questions concerning whether they engage in healthy behaviors. Our findings can support healthcare stakeholders outline future policies that ensure caregivers are adequately supported so that they provide quality care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".