Virtual family participation in adult intensive care unit rounds: A multicenter pilot feasibility cohort study
Bibliographic record
Abstract
INTRODUCTION: Family participation in intensive care unit (ICU) rounds is a recommended care practice by critical care professional societies. However, system and individual-level barriers may prevent families from attending rounds in person. This study aimed to assess the feasibility of virtual family participation in ICU rounds. METHODS: This multicenter prospective cohort study included family members of ICU patients who participated via videoconference in daily multidisciplinary team rounds in five adult ICUs in Montreal, Canada, between June 2023 and August 2024. Feasibility metrics included recruitment rate, intervention uptake, technical issues, and follow-up rate. Family-centered outcomes included care engagement (FAMily Engagement; FAME), satisfaction (Family Satisfaction in the ICU-24R), and mental health (Hospital Anxiety and Depression Scale). RESULTS: A total of 72 family members participated in at least one virtual round (out of 84 enrolled; 85.7 % uptake). No technical issues were experienced in 113/132 (85.7 %) virtual rounds. Follow-up data were available for 56/72 (77.7 %) participants. From baseline to post-intervention, overall family engagement scores (FAME) increased (64.5 ± 20.5 to 69.8 ± 15.2; p = 0.045) with improvements in the perception of engagement (63.0 ± 22.3 to 70.8 ± 16.5; p = 0.04) and family-centered care (75.7 ± 16.9 to 82.1 ± 14.0; p = 0.04) domains. Overall mean family satisfaction was high (75.8 ± 17.2). Anxiety and depression symptoms were reported by 42.8 % and 23.2 % of participants, respectively. CONCLUSION: Virtual participation by family members in ICU rounds was feasible and was associated with improved family engagement scores and high satisfaction scores. These results support the need for a multicenter trial to evaluate the effectiveness of virtual rounds in improving process and experience-related outcomes.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".