ICU nurses’ perceptions on family involvement in delirium care for postoperative cardiac surgery patients: A qualitative study
Bibliographic record
Abstract
AIMS: Delirium is common among adults recovering from cardiac surgery in the intensive care unit (ICU), prompting increased family involvement in their care. This study aimed to describe ICU nurses' perceptions of factors that support or impede family involvement in preventing, assessing, and managing delirium in the postoperative period following cardiac surgery. METHODS: A convenience sample of 18 nurses with a mean age 36 years (24-49), 89 % female) was recruited from two university-affiliated ICUs in Canada. After providing written informed consent, participants engaged in a semi-structured individual interview. Descriptive thematic analysis was performed using an established method. FINDINGS: The analysis identified six key themes: 1) Choosing the right time to involve the family, 2) The importance of sharing information, 3) Influence of family characteristics, 4) Influence of organizational characteristics, 5) Family input helps detect delirium, and 6) Families can take concrete actions when delirium occurs. Notably, while information sharing during delirium episodes was highly valued, discussions on delirium prevention were absent among all nurse participants. CONCLUSIONS: Overall, ICU nurses perceive family involvement in delirium care as beneficial, depending on factors such as patient condition, nurse attitudes and preferences, family characteristics, and organizational support. This qualitative study provides valuable insights on nurses' perceptions regarding family involvement in ICU settings. IMPLICATIONS FOR CLINICAL PRACTICE: ICU nurses, healthcare administrators and educators can use these findings to support family involvement in ICU delirium care after cardiac surgery. Overcoming barriers, particularly around delirium prevention, requires further investigation into nurses' education, resource allocation, and organizational support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".