Development of a Family Engagement Measure for the Intensive Care Unit
Bibliographic record
Abstract
Introduction: Family engagement is a goal of care delivery in the intensive care unit (ICU). However, currently, no validated instrument for the ICU is designed specifically to measure family engagement. Our objective was to develop a novel family engagement measure. Methods: ngagement (FAME) tool was developed through an iterative process, with input from experts, family members, and end-users. The FAME questionnaire is composed of 12 items. Each item is scored using a 5-point Likert scale and transformed onto a 0-100-point range, with higher scores indicating greater engagement. We performed a single-site pilot study for family members of patients in a cardiovascular ICU. Results: The FAME tool had a high construct validity and required an average of 3.33 minutes to complete. A total of 32 family members completed the FAME questionnaire (mean age: 52.4 ± 14.2 years; 71.4% female; 47% adult child ; 31% spouse/partner). The overall mean FAME score was 84.0% ± 25.2%. Differences in engagement across various domains were identified. Conclusions: The FAME measure is a focused and pragmatic tool to measure the degree and type of family engagement in care of patients in the ICU. Further studies are needed to evaluate the FAME tool in a larger population.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".