The impact of nurses working multiple jobs and drowsy driving accidents: A scoping literature review
Bibliographic record
Abstract
Background and objectives: Nurses driving while sleep-deprived is a global problem; however, few studies have examined sleep deprivation impacted by nurses working multiple jobs concurrently. Nurses work in high-pressure environments and endure long working hours, which can exacerbate nurses' fatigue. As a result, nurses are susceptible to sleep deficiency and disrupted circadian rhythms. Conceivably, sleep deficiency and disruption in circadian rhythms impact nurses' performance and well-being. The strain of long work hours and insufficient sleep worsens when nurses work multiple jobs. Nevertheless, the adverse effects are not restricted to the healthcare contexts in which nurses work; nurses must also commute back home—this scoping review canvasses existing evidence showing the implications of working multiple jobs for drowsy driving accidents.Methods: In-depth primary data analysis highlights the connection between the two measures (multiple job-holding and drowsy driving accidents). A total of ten studies were identified from CINAHL, PubMed, ScienceDirect, and MEDLINE. These databases contain recent research on nursing trends. The focus was on studies published from 1988 to 2022. This timeframe widens the pool of evidence that can be included in the research using Arksey and O'Malley's five-step process for conducting this scoping review.Results: The review finds ten studies spotlighting the relationship between intensified job demands associated with multiple job-holding and fatigue, which predisposes nurses to drowsy driving and accidents. In-depth primary data analysis highlights the connection between the two measures; multiple job-holding and drowsy driving accidents.Conclusions: Nurses must be optimal performers, yet they work under exceptionally stressful circumstances. The present study suggests that sleep deficiency and disruptions to circadian rhythms have profound negative implications for nurses' well-being beyond health facilities. Sleep interruption is challenging when nurses hold multiple jobs due to intensified job demands. In addition, exhausted nurses working several jobs are prone to drowsy driving, which can lead to accidents. Subsequent research needs to precisely document the implications of multiple job-holding among nurses concerning its impact on drowsy driving and accidents.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".