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A metacognitive confidence calibration (MCC) tool to help medical students scaffold diagnostic reasoning in decision-making during high-fidelity patient simulations

Year: 2022

Type: article

Abstract: This study demonstrates the feasibility of a metacognitive confidence calibration tool (MCC) to assess and promote novices in the learning of diagnostic reasoning and treatment decisions on patient care in real time during high-fidelity patient simulations while comparing confidence and accuracy data and identifying students' scientific misconceptions. Results revealed the presence of overconfidence bias, overtreatment, and the misconception of metabolic acidosis as the cause of the patient's problems rather than a consequence of untreated diabetes mellitus.

Source: AJP Advances in Physiology Education

DOI: 10.1152/advan.00156.2021

Authors: Luciana S. Garbayo, David M. Harris, Stephen M. Fiore, Matthew Robinson, Jonathan D. Kibble

Institution: University of Central Florida

Language: English

Topic: Clinical Reasoning and Diagnostic Skills

Subfield: Family Practice

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Quality education

Open Access status: diamond

Funder: College of Medicine, University of Central Florida