Evidence map›Paper›PMID 35769844›Full record

ArticleJournal of the American College of Emergency Physicians open2022

An emergency medicine based model for community-engaged learning.

Barry J Knapp, Julie Stoner, Joseph Lang, Rebecca Johnson, Ronald Flenner, Maryanne Gathambo

Open access · goldAbstract read
In one paragraph

Article in Journal of the American College of Emergency Physicians open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. An emergency medicine based model for community-engaged learning.Journal of the American College of Emergency Physicians open · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Barry J KnappDepartment of Emergency Medicine Eastern Virginia Medical School Norfolk Virginia USA.ORCID https://orcid.org/0000-0002-9905-4417
Julie StonerAcademic Affairs Eastern Virginia Medical School Norfolk Virginia USA.
Joseph LangDepartment of Emergency Medicine Eastern Virginia Medical School Norfolk Virginia USA.
Rebecca JohnsonDepartment of Emergency Medicine Eastern Virginia Medical School Norfolk Virginia USA.
Ronald FlennerAcademic Affairs Eastern Virginia Medical School Norfolk Virginia USA.
Maryanne GathamboAcademic Affairs Eastern Virginia Medical School Norfolk Virginia USA.
Eastern Virginia Medical School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Community-engaged learning (CEL) integrates community service with structured learning to strengthen the knowledge and skills of future physicians while still in medical school. A national model forCEL during medical school does not currently exist. Emergency physicians have the opportunity to play a vital role in medical student education using CEL as a platform. This article elucidates the structure of a bystander cardiopulmonary resuscitation (B-CPR) CEL program developed by emergency physicians that could serve as a national model for community engagement. As B-CPR is a well-known evidence-based community intervention that can be taught by students and implemented by the community, it represents an ideal CEL that can also have a measurable impact on local B-CPR rates. The development and structure of a B-CPR CEL program, lessons learned, and impact on B-CPR in a local area are reported.

Indexed as

Bystander CPRcommunity‐engaged learningundergraduate medical education

Identifiers

PMID35769844
PMCPMC9208716
OpenAlexW4283156357

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.