Refinement, scoring, and validation of the Family Satisfaction in the Intensive Care Unit (FS-ICU) survey*
Bibliographic record
Abstract
OBJECTIVES: To refine the Family Satisfaction in the Intensive Care Unit (FS-ICU) survey and develop a validated method for scoring the instrument. DESIGN: Instrument development study, using data from two prospective cohort studies. SETTING: Intensive care units in seven university-affiliated hospitals (six Canadian, one United States). SUBJECTS: Family members of ICU patients. INTERVENTIONS: Based on a priori criteria, items were tagged for potential removal and discussed with the FS-ICU developers. Factor analysis was used to test the conceptual structure of the instrument and develop a scoring method based on scales and subscales. The new scoring method was validated in the U.S. cohort using the Quality of Dying and Death (QODD) instrument and nurse-assessed quality indicators. MEASUREMENTS AND MAIN RESULTS: A total of 1,038 family members completed the FS-ICU across seven sites. Fifteen items were initially tagged for possible removal. After consensus with the developers, ten items were dropped (and 24 were retained in the final instrument). Factor analysis explained 61.3% of the total variance using a two-factor model. The first factor pertained to satisfaction with care (14 items). The second factor encompassed satisfaction with decision making (10 items). A scoring method was developed based on this conceptual model. In validity testing, the FS-ICU was significantly correlated with the Family-QODD total score (Spearman's .56, p < .001) as well as individual QODD items such as quality of care by all providers (.64, p < .001). The FS-ICU also correlated significantly with multiple nurse-assessed quality indicators. CONCLUSIONS: The shortened FS-ICU measures two main conceptual domains-satisfaction with care and satisfaction with decision making. Scores on the FS-ICU show good validity against other indicators of ICU quality. The instrument holds promise as a useful outcome measure in studies that attempt to improve this component of ICU care.
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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 | 0.048 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".