Introduction: Group learning has become important to professional students in the healing sciences. Groups share factual and procedural resources to enhance their performances.
Methodology: We investigated the extent to which students analyzing case-based evaluations as teams acquired an immediate performance advantage relative to those analyzing them as individuals and the extent to which group work on one problem led to better performance by individual students on related problems. We blinded written evaluations by randomly assigning numbers to groups of students and using removable tracers. Differences between groups and individuals were evaluated using Student's t statistic. Similar comparisons were evaluated by meta-analysis to determine overall trends.
Results: Students who analyzed evaluations as a group had an 8.5% performance advantage over those who analyzed them as individuals. When evaluations were divided into those asking questions related to treatment, differential diagnosis, and prognosis, specific performance advantages for groups relative to individuals were 8.9%, 5.9%, and 6.1% respectively. Students who had previously been trained by group evaluations had a 1.5% advantage relative to those who received their training as individuals.
Conclusions: Answers by students analyzing evaluations as groups suggested a deeper understanding, in large part because of their improved ability to explain treatment and to conduct differential diagnosis. These improvements suggested limited abilities to use previous experience to improve present performance.
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http://dx.doi.org/10.3138/jvme.29.1.43 | DOI Listing |
HGG Adv
January 2025
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196).
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran.
Genetics plays a significant role in Multiple Sclerosis (MS), with approximately 12.6% of cases occurring in familial form. While previous studies have demonstrated differences in disease progression and MRI findings between familial and sporadic MS, there has been no comparison of cognitive impairment between them.
View Article and Find Full Text PDFSci Rep
January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Department of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Introduction: Ultrasound is important in heart diagnostics, yet implementing effective cardiac ultrasound requires training. While current strategies incorporate digital learning and ultrasound simulators, the effectiveness of these simulators for learning remains uncertain. This study evaluates the effectiveness of simulator-based versus human-based training in Focused Assessed with Transthoracic Echocardiography (FATE).
View Article and Find Full Text PDFBMC Med Educ
January 2025
University of Birmingham, Birmingham, United Kingdom.
Purpose: Free Open Access Medical Education (FOAMed) is an emergent phenomenon within medical education. The rise of FOAMed resources has meant that medical education needs no longer be confined to the lecture theatre or the hospital setting, but rather, can be produced and shared amongst any individual or group with access to internet and a suitable device. This study presents a review of the use of FOAMed resources by students as part of their university medical education.
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