Medical students must gain proficiency with the complex skill of case presentations, yet current approaches to instruction are fragmented and often informal, resulting in suboptimal transfer of this skill into clinical practice. Whole task approaches to learning have been proposed to teach complex skill development. The authors describe a longitudinal case presentation curriculum developed using a whole task approach known as four-component instructional design (4-C/ID). 4‑C/ID is based on cognitive psychology theory, and carefully attends to titrating a learner's cognitive load, aiming to always keep students in their zone of proximal development. A multi-institutional group of medical educators convened to develop expert consensus regarding case presentation instruction using the 4‑C/ID model. A curriculum consisting of 1) learning tasks, 2) supportive information, 3) just-in-time information, and 4) part-task practice was developed. Domains were identified that make the task of delivering a case presentation complex. A simplifying conditions approach was applied to each domain to develop sequential task class descriptions. Examples of the four components are given to facilitate understanding of the 4‑C/ID model, making it more accessible to medical educators. Applying 4‑C/ID to curriculum development for the complex skill of case presentation delivery may optimize instruction. The provision of the complete curricular outline may facilitate transfer and implementation of this case presentation curriculum, as well as foster the application of 4‑C/ID to other complex skill development in medical education.
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http://dx.doi.org/10.1007/s40037-018-0443-8 | DOI Listing |
Mil Med
January 2025
Department of Orthopaedic Surgery, Walter Reed National Military Medical Center, Bethesda, MD 20889, USA.
Introduction: As illustrated by the "Walker Dip," there is growing concern regarding the lack of combat casualty care during peacetime. Surgical volume and case complexity are paramount for training and skill sustainment. We sought to quantify the recent orthopedic trauma surgical case load of all military orthopedic surgeons across the Military Health System (MHS).
View Article and Find Full Text PDFJ Wound Care
January 2025
Center of Innovation for Complex Chronic Healthcare, Edward Hines Jr. VA Hospital, Hines, IL, US.
Objective: The Veterans Health Administration (VHA) recently piloted the implementation of the TeleWound Practice Program (TWP), which provides interprofessional wound care to Veterans remotely. We assessed the perceptions of Veterans and healthcare team members (HCTMs), and their experiences with the TWP.
Method: We surveyed Veterans from four VHA medical centres who had received at least one TWP visit between 1 May 2020 and 31 May 2021, and HCTMs associated with any TWP encounter between 1 September 2019 and 31 March 2021.
Eur J Dent Educ
January 2025
Grup de Recerca Educativa en Ciències de la Salut (GRECS), Universitat Pompeu Fabra, Barcelona, Spain.
Introduction: Generic competencies are transferable skills, knowledge and attitudes essential for personal and professional development and not restricted to any particular field. Evidence shows the relevance of incorporating them into the dentistry curriculum. However, defining which competencies to prioritise is complex and requires input from the academic community.
View Article and Find Full Text PDFJ Clin Med
December 2024
Regional Centre for Habilitation, Department of Mental Health, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway.
Cerebral palsy is a complex lifespan disability caused by a lesion to the immature brain. Evaluation of interventions for children with cerebral palsy requires valid and reliable outcome measures. Motor development curves and reference percentiles for The Gross Motor Function Measure (GMFM-66) are valuable tools for following, predicting, comparing, and evaluating changes in gross motor skills.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
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