Evidence map›Paper›PMID 40477650›Full record

ArticleSmart learning environments2022

Implementing a cost effective and configurable hybrid simulation platform in healthcare education, using wearable and web-based technologies.

Wayne J Brown, Cindy Reid

Abstract read
In one paragraph

Article in Smart learning environments, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Wayne J BrownUniversity of Eastern Finland, Joensuu, Finland.ORCID 0000-0003-1543-8913
Cindy ReidGeorgian College of Applied Arts and Technology, Barrie, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are many examples of hybrid simulation models in healthcare education which are designed to simulate specific scenarios. However, there appears to be a need for a cost effective and configurable hybrid simulation platform which can be used by educators of various healthcare disciplines to simulate different scenarios. The purpose of this paper is to develop a proof-of-concept platform that can be easily implemented at little cost and provide flexibility to healthcare instructors to develop a variety of simulation scenarios, and to determine the effectiveness of this platform. Using a standardized patient, a person acting as a patient in a scripted manner, along with wearable and web-based technologies, a congestive heart failure simulation was used as an evaluative exercise for a group of personal support worker students at a Canadian Community College. Personal support workers typically provide care to any person who may require personal assistance with activities of daily living such as feeding, lifting, bathing, skin care and oral hygiene to name a few. Standardized patients are typically used in healthcare education to educate and evaluate soft skills, such as caregiver to patient communication, professionalism, as well as hard skills, such as history taking, examination and diagnostic skills (Rosen in J Crit Care 23:157-166, 2008). Instructor feedback indicated that the platform was easy to use and capable of simulating a large variety of scenarios. Pre and post test results are evidence of initial findings of promise indicating that the platform seemed to be effective in enabling students to meet learning outcomes. Focus group results seem to indicate an increase in student confidence as it relates to their ability to handle a similar scenario in the workplace.

Indexed as

Healthcare educationHybrid simulationStandardized patientWearable technologiesWeb-based technology

Identifiers

PMID40477650
PMCPMC9122077

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.