Introduction: The restrictions of the COVID-19 pandemic resulted in the broad and abrupt incorporation of virtual/online learning into medical school curricula. While current literature explores the effectiveness and economic advantages of virtual curricula, robust literature surrounding the effect of virtual learning on medical student well-being is needed. This study aims to explore the effects of a predominantly virtual curriculum on pre-clerkship medical student well-being.
Methods: This study followed a constructivist grounded theory approach. During the 2020-2021 and 2021-2022 academic years, students in pre-clerkship medical studies at Western University in Canada were interviewed by medical student researchers over Zoom. Data was analyzed iteratively using constant comparison.
Results: We found that students experiencing virtual learning faced two key challenges: 1) virtual learning may be associated with an increased sense of social isolation, negatively affecting wellbeing, 2) virtual learning may impede or delay the development of trainees' professional identity. With time, however, we found that many students were able to adapt by using protective coping strategies that enabled them to appreciate positive elements of online learning, such as its flexibility.
Discussion: When incorporating virtual learning into medical education, curriculum developers should prioritize optimizing existing and creating new ways for students to interact with both peers and faculty to strengthen medical student identity and combat feelings of social isolation.
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http://dx.doi.org/10.5334/pme.1184 | DOI Listing |
BMC Med Educ
December 2024
Department of Orthopedics, Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, 151203, India.
Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning to create diverse content, enabling personalized learning, enhancing resource accessibility, and facilitating interactive case studies. This narrative review explores the integration of generative artificial intelligence (AI) into orthopedic education and training, highlighting its potential, current challenges, and future trajectory.
View Article and Find Full Text PDFAcad Radiol
December 2024
Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.); Division of Medical Physics, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Neurology, Division of Movement Disorders, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Otolaryngology - Head and Neck Surgery, McGill University, Montreal, Quebec, Canada (R.F.); Department of Radiology, AdventHealth Medical Group, Maitland, FL (R.F.). Electronic address:
Rationale And Objectives: To evaluate and compare image quality of different energy levels of virtual monochromatic images (VMIs) using standard versus strong deep learning spectral reconstruction (DLSR) on dual-energy CT pulmonary angiogram (DECT-PA).
Materials And Methods: A retrospective study was performed on 70 patients who underwent DECT-PA (15 PE present; 55 PE absent) scans. VMIs were reconstructed at different energy levels ranging from 35 to 200 keV using standard and strong levels with deep learning spectral reconstruction.
Neuroimage
December 2024
Institute of Population Health, University of Liverpool, United Kingdom; Hanse Wissenschaftskolleg, Delmenhorst, Germany. Electronic address:
Recent work has shown rapid microstructural brain changes in response to learning new tasks. These cognitive tasks tend to draw on multiple brain regions connected by white matter (WM) tracts. Therefore, behavioural performance change is likely to be the result of microstructural, functional activation, and connectivity changes in extended neural networks.
View Article and Find Full Text PDFBone Health ECHO (Extension for Community Healthcare Outcomes) is a virtual community of practice, where healthcare professionals have met via videoconferencing weekly since 2015. This model of learning is focused on short didactics and the presentation of real but de-identified patient cases followed by highly interactive discussions. These are often clinical situations with diagnostic and therapeutic dilemmas that are not readily addressed by randomized placebo-controlled clinical trials and clinical practice guidelines.
View Article and Find Full Text PDFEBioMedicine
December 2024
Department of Anaesthesiology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands.
Background: Clinical decision-making is increasingly shifting towards data-driven approaches and requires large databases to develop state-of-the-art algorithms for diagnosing, detecting and predicting diseases. The intensive care unit (ICU), a data-rich setting, faces challenges with high-frequency, unstructured monitor data. Here, we showcase a successful example of a data pipeline to efficiently move patient data to the cloud environment for structured storage.
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