Needs of family members of critically ill patients: A comparison of nurses and family perceptions
Bibliographic record
Abstract
Background and objective: Having a family member admitted to Intensive Care Unit (ICU) is stressful and confusing for family members. The aim of this study was to assess the perception of family members and nurses of their needs and whether those needs are met in four ICUs in Lebanon.Methods: A descriptive cross-sectional design using the Arabic version of Critical Care Family Need Inventory (CCFNI) and the Needs Met Inventory (NMI) were utilized to investigate the needs of 50 family members of patients and 50 nurses.Results: Seventeen of 30 need items on the CCFNI were significantly different between family members and nurses mostly related to ‘Information’ and ‘Assurance’. Family members also varied significantly on 5 out of 30 items on the NMI mostly related to ‘Support’. There were significant differences in needs between family members in terms of gender, age, and education, and significant differences in perceived needs based on the gender, years of experience, and age of nurses.Conclusions: The findings provide insight for nurses to consider the different needs of families, the effect of socio-demographic variations when providing care, and to be attuned to the needs of family members for understandable information and assurance of the wellbeing of patients in ICUs.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".