Shared Decision-Making With a Surrogate for Life-Sustaining Treatment of Critically Ill Patients: Protocol for a Scoping Review
Bibliographic record
Abstract
Background: Shared decision-making (SDM) is a collaborative process that integrates patients' values and preferences into health care decisions. In intensive care units, patients who are critically ill often lack the capacity to make decisions, necessitating surrogates to make complex choices regarding life-sustaining treatments (LSTs). Objective: This scoping review aims to assess the range of research conducted on surrogate SDM for LSTs among patients who are critically ill over the past decade and highlight areas where current research remains limited. Methods: This scoping review will follow the Joanna Briggs Institute methodology and adhere to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guidelines. Studies will be included if they examine SDM involving surrogates of adult patients who are critically ill in relation to LST decisions within intensive care unit settings. SDM is defined using 4 criteria: participation of both health care professionals and surrogates, mutual information sharing, consensus building, and agreement on treatment based on the patient's values and preferences. A comprehensive search will be performed across PubMed, CINAHL, PsycInfo, CENTRAL, and Ichushi-Web for English- and Japanese-language studies published between 2016 and 2025. Eligible study designs will include quantitative, qualitative, and mixed methods research. Title and abstract screening, as well as full-text selection, will be conducted independently by 2 reviewers using Rayyan. Data will be extracted on study characteristics, SDM definitions, participant roles, and key findings. Results will be synthesized descriptively and presented in tables and narrative summaries to identify research gaps and inform future investigations. Results: As of June 13, 2025, the literature search has been completed. A total of 2899 citations were identified through the specified database searches, and 527 (18.2%) duplicates were removed. Title and abstract screening are currently in progress, and full-text review is expected to be completed by September 2025. Conclusions: This scoping review will systematically map recent evidence on surrogate SDM in the context of LST decisions for patients who are critically ill. By synthesizing diverse studies, it will identify challenges faced by surrogates and summarize existing interventions that aim to improve SDM processes. The findings are expected to inform future interventions and policies and advance patient- and family-centered care in critical care settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.111 | 0.105 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.097 | 0.018 |
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".