Abstract
The COVID-19 pandemic impacted the education of nursing students across the world. Nursing students were unable to care for patients with COVID-19 at the beginning and potentially throughout nursing school depending on the facility and nursing school restrictions. It was not known how the participation in a high-fidelity simulation will impact the confidence level of nursing students in the care of patients with COVID-19. A mixed methods phenomenological qualitative and survey design was utilized to determine the confidence level of nursing students after participation in a high-fidelity simulation of a patient diagnosed with COVID-19.
Sigma Membership
Non-member
Type
Dissertation
Format Type
Text-based Document
Study Design/Type
Phenomenology
Research Approach
Mixed/Multi Method Research
Keywords:
Simulation Education, Nursing Students, COVID-19 Pandemic, Patient Care
Advisor
Donald J. Dunn
Second Advisor
Larry Gay Reagan
Third Advisor
Nina Beaman
Degree
Doctoral-Other
Degree Grantor
Aspen University
Degree Year
2022
Recommended Citation
Paine, Faith A., "Impact of high-fidelity simulation on confidence level of nursing students in the care of COVID-19 patients" (2023). Dissertations. 708.
https://www.sigmarepository.org/dissertations/708
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
All permission requests should be directed accordingly and not to the Sigma Repository.
All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
None: Degree-based Submission
Acquisition
Proxy-submission
Date of Issue
2023-01-23
Full Text of Presentation
wf_yes
Description
This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 28971058; ProQuest document ID: 2642334262. The author still retains copyright.