Intensive care nurse perspectives on family-centred rounds in adult critical care units
Bibliographic record
Abstract
Background: Family-centred rounds (FCR) are a component of family involvement in critical care settings. Nurses’ active participation is vital in implementing FCR. However, there is currently a lack of rigorous literature exploring nursing perspectives of FCR in adult critical care areas. Purpose: This study explored nursing perspectives of FCR in six adult critical care units across four Southwestern Ontario hospitals. Methods: A 56-question survey was distributed to critical care nurses working at six adult critical care units through an online Qualtrics® link. Nurses did not need to have experience participating in FCR to participate in this study. Results: Seventy percent of nurses (n = 135) were overall supportive of FCR. Nurses reported that processes, such as unit culture toward FCR, may impact how well nurses are able to incorporate families into FCR. The most significant advantage of FCR noted was the healthcare team could update family on the patient’s condition. However, they reported time was a major structural barrier to FCR, and the overall greatest barrier noted was the inconsistent or unknown timing of rounds. Tests of association revealed that nurses’ overall supportiveness of FCR was statistically significantly related to their ethnicity (p = .01) and hospital site (p = <.001). Conclusion: Most nurses are supportive of FCR overall. This research highlights their perceptions of the structures and processes that support them while implementing FCR and factors that may affect their support. It may contribute to developing evidence-based best practices for a higher-quality, standardized, family-centred rounding process. Keywords: family-centred nursing, clinical rounds, critical care nursing, 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".