A Review of Visiting Policies in Intensive Care Units
Bibliographic record
Abstract
Admission to intensive care units is potentially stressful and usually goes together with disruption in physiological and emotional function of the patient. The role of the families in improving ill patients' conditions is important. So this study investigates the strategies, potential challenges and also the different dimensions of visiting hours' policies with a narrative review. The search was carried out in scientific information databases using keywords "visiting policy", "visiting hours" and "intensive care unit" with no time limitation on accessing the published studies in English or Farsi. Of a total of 42 articles, 22 conformed to our study objectives from 1997 to 2013. The trajectory of current research shows that visiting in intensive care units has, since their inception in the 1960s, always considered the nurses' perspectives, patients' preferences and physiological responses, and the outlook for families. However, little research has been carried out and most of that originates from the United States, Europe and since 2010, a few from Iran. It seems that the need to use the research findings and emerging theories and practices is necessary to discover and challenge the beliefs and views of nurses about family-oriented care and visiting in intensive care units.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".