A Pilot Randomized Trial of an Interactive Web-based Tool to Support Surrogate Decision Makers in the Intensive Care Unit
Bibliographic record
Abstract
Abstract Rationale Breakdowns in clinician–family communication in intensive care units (ICUs) are common, yet there are no easily scaled interventions to prevent this problem. Objectives To assess the feasibility, usability, acceptability, and perceived effectiveness of a communication intervention that pairs proactive family meetings with an interactive, web-based tool to help surrogates prepare for clinician–family meetings. Methods We conducted a two-arm, single-blind, patient-level randomized trial comparing the Family Support Tool with enhanced usual care in two ICUs in a tertiary-care hospital. Eligible participants included surrogates of incapacitated patients judged by their physicians to have ≥40% risk of death or severe long-term functional impairment. The intervention group received unlimited tool access, with prompts to complete specific content upon enrollment and before two scheduled family meetings. Before family meetings, research staff shared with clinicians a one-page summary of surrogates’ main questions, prognostic expectations, beliefs about the patient’s values, and attitudes about goals of care. The comparator group received usual care enhanced with scheduled family meetings. Feasibility outcomes included the proportion of participants who accessed the tool before the first family meeting, mean number of logins, and average tool engagement time. We assessed tool usability with the System Usability Scale, assessed tool acceptability and perceived effectiveness with internally developed questionnaires, and assessed quality of communication and shared decision-making using the Quality of Communication questionnaire. Results Of 182 screened patients, 77 were eligible. We enrolled 52 (67.5%) patients and their primary surrogate. Ninety-six percent of intervention surrogates (24/25) accessed the tool before the first family meeting (mean engagement time, 62 min ± 27.7) and logged in 4.2 times (±2.1) on average throughout the hospitalization. Surrogates reported that the tool was highly usable (mean, 82.4/100), acceptable (mean, 4.5/5 ± 0.9), and effective (mean, 4.4/5 ± 0.2). Compared with the control group, surrogates who used the tool reported higher overall quality of communication (mean, 8.9/10 ± 1.6 vs. 8.0/10 ± 2.4) and higher quality in shared decision-making (mean, 8.7/10 ± 1.5 vs. 8.0/10 ± 2.4), but the difference did not reach statistical significance. Conclusions It is feasible to deploy an interactive web-based tool to support communication and shared decision-making for surrogates in ICUs. Surrogates and clinicians rated the tool as highly usable, acceptable, and effective.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | medium |
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".