Death Anxiety and Related Factors Among Iranian Critical Care Nurses: A Multicenter Cross-Sectional Study
Bibliographic record
Abstract
The aim of this study is to investigate death anxiety (DA) and related factors among critical care nurses. Using a cross-sectional research design, 325 critical care nurses in eight hospitals in Iran enrolled in the study. Multiple logistic regression analysis showed that deputy head nurse (OR = 18.299; CI: 1.764–189.817; p = .015), shift morning fixed (OR = 8.061; CI: 1.503–43.243; p = .015), surviving parents (OR = 3.281; CI: 1.072–10.037; p = .037), number of children (OR = 1.866; CI: 1.157–3.010; p = .011), years of working experience (OR = 1.143; CI: 1.048–1.246; p = .003), number of end-of-life patient care in the last 3 months (OR = .900; CI: .828–0.977; p = .012), age (OR = .809; CI: .732–.893; p < .001), CCU nurses (OR = .250; CI: .100–.628; p = .003), and mild stressful life events (SLEs) (OR = .167; CI: .046–.611; p = .007) were significantly related to high DA. Therefore, nurse managers and policymakers should pay special attention to these related factors in developing programs to maintain and promote the health of critical care nurses to improve the quality of nursing care.
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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 | 0.001 |
| 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".