Abstract
High-fidelity human patient simulation has emerged as a valuable medium to reinforce educational content within programs of nursing. As simulation learning experiences have been identified as augmenting both didactic lecture content and clinical learning, these experiences have expanded to incorporate interprofessional education. Review of literature demonstrates research is necessary to support how interprofessional education can impact learning and how high-fidelity human patient simulation can be utilized as a mechanism to promote learning in an interprofessional manner. The purpose of this mixed methods study was to explore pre-licensure health professions students' perceptions of high-fidelity human patient simulation as a teaching modality for the promotion of interprofessional collaboration. A mixed methods convergent parallel design was utilized. Quantitative data focused on the readiness for interprofessional learning and collaboration among study participants after an interprofessional education focused high-fidelity learning experience. Qualitative data focused on perceptions of the student participants of an interprofessional learning experience.
Sigma Membership
Eta Gamma
Lead Author Affiliation
Baylor University, Dallas, Texas, USA
Type
Dissertation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Mixed/Multi Method Research
Keywords:
High-Fidelity Simulation, Human Patient Simulation, Interprofessional Education
Advisor
Tanya Sudia
Second Advisor
Laura P. Kimble
Third Advisor
Lisa Broussard
Degree
PhD
Degree Grantor
Mercer University
Degree Year
2013
Recommended Citation
Rossler, Kelly L., "Exploring interprofessional education through a high-fidelity human patient simulation scenario: A mixed methods study" (2024). Dissertations. 1941.
https://www.sigmarepository.org/dissertations/1941
Rights Holder
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Review Type
None: Degree-based Submission
Acquisition
Proxy-submission
Full Text of Presentation
wf_yes
Description
This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 3569841; ProQuest document ID: 1356858072. The author still retains copyright.