Peer Support in Critical Care: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Identifying solutions to improve recovery after critical illness is a pressing problem. We systematically evaluated studies of peer support as a potential intervention to improve recovery in critical care populations and synthesized elements important to peer support model design. DATA SOURCES: A systematic search of Medical Literature Analysis and Retrieval System Online, Cumulative Index to Nursing and Allied Health Literature, PsychINFO, and Excertpa Medica Database was undertaken May 2017. Prospective Register of Systematic Reviews identification number: CRD42017070174. STUDY SELECTION: Two independent reviewers assessed titles and abstracts against study eligibility criteria. Studies were included where 1) patients and families had experienced critical illness and 2) patients and families had participated in a peer support intervention. Discrepancies were resolved by consensus and a third independent reviewer adjudicated as necessary. DATA EXTRACTION: Two independent reviewers assessed study quality with the Newcastle-Ottawa Scale and the Cochrane Risk of Bias Tool, and data were synthesized according to the Preferred Reporting Items for Systematic Reviews guidelines and interventions summarized using the Template for Intervention Description and Replication Checklist. DATA SYNTHESIS: Two-thousand nine-hundred thirty-two studies were screened. Eight were included, comprising 192 family members and 92 patients including adults (with cardiac surgery, acute myocardial infarction, trauma), pediatrics, and neonates. The most common peer support model of the eight studies was an in-person, facilitated group for families that occurred during the patients' ICU admission. Peer support reduced psychologic morbidity and improved social support and self-efficacy in two studies; in both cases, peer support was via an individual peer-to-peer model. In the remaining studies, it was difficult to determine the outcomes of peer support as the reporting and quality of studies was low. CONCLUSIONS: Peer support appeared to reduce psychologic morbidity and increase social support. The evidence for peer support in critically ill populations is limited. There is a need for well-designed and rigorously reported research into this complex intervention.
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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 | 0.030 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".