Evidence map›Paper›PMID 37288220›Full record

ArticleCureus2023

Making Quality Improvements to Clinical Simulation Scenarios via Podcasting.

Beheshta Momand, Olivia Sacuevo, Masuoda Hamidi, Flávio Vaz Machado, Adam Dubrowski

Abstract readEditorial
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Beheshta MomandHealth Sciences, Ontario Tech University, Oshawa, CAN.
Olivia SacuevoHealth Sciences, Ontario Tech University, Oshawa, CAN.
Masuoda HamidiHealth Sciences, Ontario Tech University, Oshawa, CAN.
Flávio Vaz MachadoHealth Sciences, Ontario Tech University, Oshawa, CAN.
Adam DubrowskiHealth Sciences, Ontario Tech University, Oshawa, CAN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation is a common method for teaching and enhancing healthcare skills. Nevertheless, the construction of a simulation scenario is expensive and time-consuming and requires a great deal of effort. As a result, it is imperative that we make quality improvements to the process of scenario construction. When this is accomplished, we will be able to enhance the existing scenarios, develop new ones, and ultimately enhance these teaching tools. Currently, publishing simulation scenarios as peer-reviewed technical reports is one way to ensure quality and global sharing of scenarios. Yet, another undiscovered potential to further improve the quality of scenarios once the peer-review process is complete is to allow the original scenario designers to reflect on their creative processes using podcasting. This paper proposes that podcasting can be used as a supplement to the peer-review process to address this issue. Podcasting is one of the prevalent forms of media in the twenty-first century. There are currently numerous podcast channels in the healthcare simulation space. However, the majority are focused on introducing simulation experts or discussing issues in healthcare simulation, and none are focused on making quality improvements to clinical simulation scenarios with the authors. We propose to make quality improvements with scenario designers using podcasting in order to communicate information to the public and evaluate what went well and what might have been done better in order to inform future developers.

Indexed as

clinical scenariosdebriefingeducationimproving clinical scenariospodcastingsimulation medicine

Identifiers

PMID37288220
PMCPMC10243395

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.