Recruitment strategies for family members in intensive care unit studies: A retrospective observational study
Bibliographic record
Abstract
BACKGROUND: Family engagement in patient care has emerged as an important aspect of critical care delivery. There is a need for clinical trials to obtain robust evidence on family engagement interventions. However, limited evidence exists on effective strategies for recruiting family members of intensive care unit (ICU) patients in clinical trials. OBJECTIVE: The aim of this study was to describe and explore various recruitment approaches for enrolling family members of ICU patients as participants in clinical trials. METHODS: We reviewed recruitment approaches for three clinical studies (one prospective observational study; two randomised interventional trials) conducted in six Canadian ICUs involving family members of ICU patients. Variables collected included time of day approached, mode of initial contact, number of research personnel approaching a family member, method of consent, whether a white lab coat was worn by research personnel, and whether compensation was offered. RESULTS: A total of 392 family members participated in a study out of 845 family members approached (overall recruitment rate of 46.4%). Recruitment rate was numerically higher for morning than for afternoon approach (81.3% vs. 62.4%), two recruiters than one (86.4% vs. 61.2%), initial contact by phone than in-person (57.6% vs. 44.9%), and in case of compensation offered than in case of none (44.1% vs. 38.0%). Recruitment percentages were numerically similar regardless of white lab coat use (62.5% vs. 67.8%) or consent method (paper or electronic; 65.3% vs. 63.9%). Recruitment rates were numerically higher for observational than for interventional studies (71.0% vs. 35.7%, respectively) and in medical-surgical ICUs than in cardiac ICUs (63.1% vs. 41.6%, respectively). CONCLUSION: Several approaches had numerically higher recruitment percentage of family members as research participants in ICU studies. These findings can inform how we can optimise recruitment into family engagement interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".