Validation of the French-Canadian Version of FAME, a Family Engagement Measurement Tool for the Intensive Care Unit
Bibliographic record
Abstract
BackgroundA growing body of evidence supports the benefits of family engagement in patient care in intensive care units (ICUs). The English version of the FAMily Engagement (FAME) tool has been validated to measure ICU family engagement. This study aimed to validate the French-Canadian version of FAME.MethodsParticipant-level data from two prospective observational validation studies of the FAME tool, involving family members of patients from eight Canadian ICUs between May 2022 and July 2024, were included. Family members completed FAME in English or French-Canadian. Following discharge, family members completed questionnaires measuring care satisfaction and mental health (anxiety and depression). Reliability was assessed by internal consistency, and convergent and predictive validity by correlation between FAME and related outcome measures. A comparison of French and English scores was also conducted.ResultsA total of 104 family members completed the French-Canadian FAME questionnaire (age 57.0 ± 15.2 years; 62% women; 8% non-White; 53% spouse/partner). This version demonstrated internal consistency (Cronbach's alpha = 0.84) and convergent and predictive validity. FAME was associated with care satisfaction, but not anxiety or depression scores. There were no significant differences in overall FAME, care satisfaction, or anxiety and depression scores between the French and English cohorts (p > 0.05).ConclusionThe French-Canadian version of the FAME tool demonstrated reliability and convergent and predictive validity in French-Canadian speakers, supporting the inclusion of French-speaking family members in future studies utilizing the FAME tool to measure family involvement in ICU patient care.This study includes data from Measuring Family Engagement in Care (The FAME Study), ClinicalTrials.gov (NCT05659485): https://clinicaltrials.gov/study/NCT05659485.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".