Volunteer contributions in the emergency department: A scoping review
Bibliographic record
Abstract
The objective of this scoping review was to identify published and unpublished reports that described volunteer programs in the emergency department (ED) and determine how these programs impacted patient experiences or outcomes. Electronic searches of Medline, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and CINAHL were conducted and reference lists were hand-searched. A grey literature search was also conducted. Two reviewers independently screened titles and abstracts, reviewed full text articles, and extracted data. The search strategy yielded 4,589 potentially relevant citations; 87 reports were included in the review. Volunteer activities were categorized as non-clinical tasks (e.g., provision of meals/snacks, comfort items and mobility assistance), navigation, emotional support/communication, and administrative duties. 52 (59.8%) programs had general volunteers in the ED and 35 (40.2%) had volunteers targeting a specific patient population, including pediatrics, geriatrics, patients with mental health and addiction issues and other vulnerable populations. 18 (20.6%) programs included an evaluative component describing how ED volunteers affected patient experiences and outcomes. Patient satisfaction, follow-up and referral rates, ED hospital costs and length of stay, subsequent ED visits, medical complications, and malnutrition in the hospital were all reported to be positively affected by volunteers in the ED. These findings demonstrate the important role volunteers play in enhancing patient and caregiver experience in the ED. Future volunteer engagement programs should be formally described and evaluated to share their success and experience with others interested in implementing similar programs in the ED. Experience Framework This article is associated with the Infrastructure & Governance lens of The Beryl Institute Experience Framework. (http://bit.ly/ExperienceFramework) Access other PXJ articles related to this lens. Access other resources related to this lens.
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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 | 0.028 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".