Family satisfaction with critical care: measurements and messages
Bibliographic record
Abstract
PURPOSE OF REVIEW: Family satisfaction in the ICU reflects the extent to which perceived needs and expectations of family members of critically ill patients are met by healthcare professionals. Here, we present recently developed tools to assess family satisfaction, with a special focus on their psychometric properties. Assessing family satisfaction, however, is not of much use if it is not followed by interpretation of the results and, if needed, consecutive measures to improve care of the patients and their families, or improvement in communication and decision-making. Accordingly, this review will outline recent findings in this field. Finally, possible areas of future research are addressed. RECENT FINDINGS: To assess family satisfaction in the ICU, several domains deserve attention. They include, among others, care of the patient, counseling and emotional support of family members, information and decision-making. Overall, communication between physicians or nurses and members of the family remains a key topic, and there are many opportunities to improve. They include not only communication style, timing and appropriate wording but also, for example, assessments to see if information was adequately received and also understood. Whether unfulfilled needs of individual members of the family or of the family as a social system result in negative long-term sequels remains an open question. SUMMARY: Assessing and analyzing family satisfaction in the ICU ultimately will support healthcare professionals in their continuing effort to improve care of critically ill patients and their families.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".