Evidence map›Paper›PMID 36505119›Full record

ArticleCureus2022

Development of Content for a Virtual Reality Simulation to Understand and Mitigate Moral Distress in Healthcare Workers.

Mithusa Sivanathan, Caroline W Espinola, Alvaro Uribe Quevedo, Bill Kapralos, Sridhar Krishnan, Venkat Bhat, Adam Dubrowski

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Moral injury prevention and intervention.European journal of psychotraumatology · 2025
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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

7 authors at 5 institutions in 4 countries.

Mithusa SivanathanHealth Sciences, Ontario Tech University, Oshawa, CAN.
Caroline W EspinolaPsychiatry, St. Michael's Hospital, Toronto, CAN.
Alvaro Uribe QuevedoSoftware and Informatics Research Centre, Ontario Tech University, Oshawa, CAN.
Bill KapralosSoftware and Informatics Research Centre, Ontario Tech University, Oshawa, CAN.
Sridhar KrishnanElectrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, CAN.
Venkat BhatPsychiatry, St. Michael's Hospital, Toronto, CAN.
Adam DubrowskiHealth Sciences, Ontario Tech University, Oshawa, CAN.
St Michael’s Hospital · IESt. Michael's Hospital · CAMetropolitan University · RSSt Michael's Hospital · GBUniversity of Ontario Institute of Technology · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background In high-stakes situations, healthcare workers are prone to suffer moral injury, the psychological, social, and spiritual impact of events involving betrayal or transgression of one's own deeply held moral beliefs and values. As a result, this may negatively impact their capacity to provide adequate levels of care to patients. There is a lack of educational resources catered to help healthcare workers navigate ethical situations in clinical settings that may lead to or worsen moral distress. The aim of this report is to describe the methodology of development and resulting outcomes in the form of an educational resource that includes a virtual reality (VR) simulation to help healthcare workers understand and mitigate moral distress as a result of internal and external constraints at their workplaces. Methodology A study using a method outlining a set of constraint parameters, followed by ideation utilizing design thinking (DT), and concluding with a consensus-building exercise using Delphi methodology (DM) with a group of 13 experts in healthcare simulation, VR, psychiatry, psychology, and nursing. The constraints parameters included technology use (VR), use of experiential learning theory, and duration of the intervention (15 minutes). A DT process was performed to generate and expand on ideas on the scenario and intervention of a possible VR simulation which were funneled into a three-round DM to define the foundations of the VR simulation. Average, standard deviations, and free-text comments in the DM were used to assess the inclusion of the produced requirements. Finally, a focus group interview was conducted with the same experts to draft the VR simulation. Results Within the specified constraints, the DT process produced 33 ideas for the VR simulation scenario and intervention that served as a starting point to short-list the requirements in Round 1. In Rounds 1 to 2, 25 items were removed, needed revising, and/or were retained for the subsequent rounds, which resulted in eight items at the end of Round 2. Round 2 also required specialists to provide descriptions of potential scenarios and interventions, in which five were submitted. In Round 3, experts rated the descriptions as somewhat candidate to use in the final VR simulation, and the open feedback in this round proposed combining the elements from each of the descriptions. Using this data, a prototype of the VR simulation was developed by the project team together with VR designers. Conclusions This development demonstrated the feasibility of using the constraints-ideation-consensus approach to define the content of a possible VR simulation to serve as an educational resource for healthcare workers on how to understand and mitigate moral distress in the workplace. The methodology described in this development may be applied to the design of simulation training for other skills, thereby advancing healthcare training and the quality of care delivered to the greater society.

Indexed as

covid-19educational resourcehealthcare simulationmental healthmobile appmoral distressmoral injurypsychiatrypsychologyvirtual reality

Identifiers

PMID36505119
PMCPMC9731177
OpenAlexW4308507731

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.