
High Fidelity Simulation and the Development of Clinical Judgment in Senior Nursing Students: A Mixed Method Approach
Author(s) -
Warongrong Nilphet
Publication year - 2021
Publication title -
global journal of health science
Language(s) - English
Resource type - Journals
eISSN - 1916-9744
pISSN - 1916-9736
DOI - 10.5539/gjhs.v13n10p19
Subject(s) - psychology , medical education , inclusion (mineral) , fidelity , perception , nursing , multimethodology , qualitative property , medicine , pedagogy , social psychology , computer science , telecommunications , neuroscience , machine learning
Clinical judgment is defined as an understanding and interpretation regarding patient’s needs, health problems or concerns (Tanner, 2006). There are four interrelated processes in Tanner’s model that consist of noticing, interpreting, responding, and reflecting (Tanner, 2006). Because clinical judgment is extremely complex and encompasses many ways of thinking and types of knowledge, it requires a flexible capability to identify significant features of indeterminate clinical circumstances. Mixed methods study was conducted to describe senior nursing students’ experience in using high-fidelity simulation to evaluate the development of clinical judgment skills. A convenience sampling of 30 senior nursing students who signed the consent, met the inclusion criteria, and attend the selected school of nursing in the fall of 2020 were used for this study. All participants answered questionnaires regarding the quantitative survey. Participants interviewed face-to-face and video call using Zoom meeting program and recorded using an audio recorder. Both the quantitative and qualitative findings identified that learning through high-fidelity simulation supports the improvement in the participants’ clinical judgment skills. All participants reported their perceptions and experiences from using high-fidelity simulation develop and support their clinical judgment skills from the beginning through the end of the simulation, especially improving prioritizing data and working as a team with providing effective communication.