Characterizing Citizens’ Preferences for Engagement in Patient Care and Research in Adult and Pediatric Intensive Care Units
Bibliographic record
Abstract
Rationale: Engagement promotes and supports the active participation of patients and families in health care and research to strengthen their influence on decision-making. We sought to characterize how citizens wish to be engaged in care and research in the intensive care unit (ICU). Methods: Interviewers administered questionnaires to visitors in 3 adult ICUs and 1 pediatric ICU. Results: We surveyed 202 (adult [n = 130] and pediatric [n = 72]) visitors. Adults and pediatric visitors prioritized 3 patient care topics (family involvement in rounds, improving communication between family members and health-care providers, and information transmission between health-care practitioners during patient transfers) and 2 research topics (evaluating prevention and recovery from critical illness). Preferred engagement activities included sharing personal experiences, identifying important topics and outcomes, and finding ways to make changes that respected their needs. Both respondent groups preferred to participate by completing electronic surveys or comment cards and answering questions on a website. Few respondents (<5%) wanted to participate in committees that met regularly. Although adult and pediatric respondents identified common facilitators and barriers to participation, they ranked them differently. Although both groups perceived engagement to be highly important, adult respondents were significantly less confident that their participation would impact care (7.6 ± 2.2 vs 8.3 ± 1.8; P = .01) and research (7.3 ± 2.4 vs 8.2 ± 2.0; P = .01) and were significantly less willing to participate in care (5.6 ± 2.9 vs 6.7 ± 3.0; P = .007) and research (4.7 ± 3.0 vs ± 5.8 ± 3.0; P = .02). Conclusions: Adult and pediatric visitors expressed comparable engagement preferences, identified similar facilitators and barriers, and rated engagement highly. Adult visitors were significantly less confident that their participation would be impactful and were significantly less willing to engage in care and research.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".