Background: Fidelity in simulation is an important design feature. Although it is typically seen as bipolar (i.e., "high"or "low"), fidelity is actually multidimensional. There are concerns that "low fidelity"might impede the immersion of learners during simulation training. "Locally built models"are characterized by decreased cost and reduced "structural"fidelity (how the simulator looks) while satisfying "functional"fidelity (what the simulator does). Objective: To 1) describe the use of a locally built chest tube model in building a mastery-based simulation curriculum and 2) describe evaluation of the model from learners in different stages and contexts. Methods: The model was built on the basis of key functional features of the assigned training task. A curriculumthat combined progressive difficulty and opportunities for deliberate practice andmastery was developed. An analysis of the learner's survey responses was performed using SAS studio (SAS Software). Results: We describe the process of creating the chest tube model and a curriculum in which the model is used for increasing levels of difficulty to reach skill mastery. Learners at different stages and in different contexts, such as practicing physicians and trainees fromdeveloped and developing countries, evaluated the model similarly. We provide validity evidence for the content, response process, and relationship with other variables when using the model in the assessment of chest tube insertion skills. Conclusion: As demonstrated in our chest tube critical care medicine curriculum, the locally built models are simple to build and feasible to use. Contrary to current thinking that low-fidelity models might impede immersion in simulation training for experienced learners, the survey results show that different learners provide very similar evaluations after practicing with the model.
CITATION STYLE
Pedro, T. S., Mtaweh, H., & Mema, B. (2021). More Is Not Always Better in Simulation Learners’ Evaluation of a “chest Model.” ATS Scholar, 2(1), 124–133. https://doi.org/10.34197/ats-scholar.2020-0040IN
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