The Attitude of Iranian Critical Care Nurses Toward Euthanasia
Bibliographic record
Abstract
Today, one of the major ethical challenges facing the world's health care system, and in particular nurses in the intensive care unit, is euthanasia or death out of pity. The aim of this study was to investigate the attitude of Iranian nurses in the intensive care unit toward euthanasia. This was an analytical cross-sectional study using census sampling. The data collection tool was the Euthanasia Attitude Scale. A total of 206 nurses working in the intensive care unit in 4 hospitals in the Mazandaran province of Iran were included in this study. The mean of total Euthanasia Attitude Scale score in intensive care unit nurses was 2.96. The mean euthanasia dimensions were ethical consideration, practical considerations, treasuring life, and naturalistic beliefs, 3.03, 2.92, 2.98, and 2.99, respectively. There was significant but low negative correlation between age and total Euthanasia Attitude Scale score, ethical considerations, and practical considerations. Male nurses exhibited significantly higher Euthanasia Attitude Scale scores, specifically in regard to ethical and practical considerations compared with female nurses. The most Iranian nurses in the intensive care unit had a negative attitude toward euthanasia for patients in the later stages of the disease. However, this opposition was less than similar studies in Iran in the past.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".