Efficacy of High-Fidelity Patient Simulation in Nursing Education: Research Protocol of ‘S4NP’ Randomized Controlled Trial View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Angelo Dante , Carmen La Cerra , Valeria Caponnetto , Ilaria Franconi , Elona Gaxhja , Cristina Petrucci , Loreto Lancia

ABSTRACT

High-Fidelity Patient Simulation is defined as a replicated clinical experience in a controlled learning environment that closely represents reality. This learning method creates the opportunity for students to gain specific and fundamental clinical skills in a controlled, safe, and forgiving environment. Even though the available evidence shows the impact of High-Fidelity Patient Simulation in improving nursing students’ learning objectives, several reasons do not allow confirming its effectiveness. Many studies show weakness in validity and reliability due to the low quality of study design, inadequate sample size and/or convenience sample recruitment. Furthermore, most studies appear uneven in research methods and unstable in outcome measurements. Finally, little is known about learning outcome retention. Therefore, high-level studies are required to strongly confirm the impact of High-Fidelity Patient Simulation on students’ learning outcomes, especially on long-term retention, and on patients’ advantages. This trial project, called S4NP (Simulation for Nursing Practice), was designed to confirm if the nursing students’ exposure to complementary training based on High-Fidelity Patient Simulation could produce long-term beneficial effects on learning outcomes compared to the traditional training program. More... »

PAGES

261-268

References to SciGraph publications

Book

TITLE

Methodologies and Intelligent Systems for Technology Enhanced Learning, 8th International Conference

ISBN

978-3-319-98871-9
978-3-319-98872-6

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-98872-6_31

DOI

http://dx.doi.org/10.1007/978-3-319-98872-6_31

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107186845


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