Research on the extent and nature of commonly misunderstood fundamental biomedical concepts across a medical curriculum is scarce. These misunderstandings could point toward robust misconceptions. We examined first whether common misunderstandings persist throughout a medical curriculum, followed by a fine-grained analysis to identify their nature. We designed and administered a 2-tier test to 987 medical students across our curriculum, with 8 questions covering the respiratory and cardiovascular systems, cell division, and homeostatic processes. Proportions of incorrect responses were computed. Four questions where misunderstandings persisted were further qualitatively analyzed. A one-way ANOVA showed the proportion of incorrect responses decreased significantly by students' academic year [(6, 986) = 96.05, < 0.001]. While novices and end-of -first-year students showed similar proportion of incorrect responses ( > 0.05), incorrect responses decreased significantly between first years and second years ( < 0.001). Thereafter, the proportion of incorrect responses remained stable from second to final year ( > 0.05), with ∼35% of incorrect responses. Five questions showed no decrease of incorrect responses between second and final years, with two questions where final year students performed marginally better than novices. A Chi-square analysis, with Bonferroni post hoc test, showed certain misunderstandings appeared frequently across the curriculum. The qualitative analysis of the open-ended questions yielded 15 categories of common misunderstandings of fundamental biomedical concepts in all years of training. If educators become aware of commonly misunderstood biomedical concepts, preventative measures could be taken to prevent robust misconceptions.
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http://dx.doi.org/10.1152/advan.00203.2020 | DOI Listing |
AJOG Glob Rep
February 2025
University of Texas Southwestern, Dallas, TX (Cohen, Ho, McIntire, Smith, and Kho).
Introduction: The use of generative artificial intelligence (AI) has begun to permeate most industries, including medicine, and patients will inevitably start using these large language model (LLM) chatbots as a modality for education. As healthcare information technology evolves, it is imperative to evaluate chatbots and the accuracy of the information they provide to patients and to determine if there is variability between them.
Objective: This study aimed to evaluate the accuracy and comprehensiveness of three chatbots in addressing questions related to endometriosis and determine the level of variability between them.
Ann N Y Acad Sci
January 2025
School of Psychology, Shenzhen University, Shenzhen, China.
Individuals with high math anxiety (HMA) demonstrate a tendency to avoid math-related tasks, a behavior that perpetuates a detrimental cycle of limited practice, poor performance, increased anxiety, and further avoidance. This study delves into the cognitive and neural bases of math avoidance behavior in HMA through the lens of reward processing. In Experiment 1, participants reported their satisfaction level in response to the reward provided after solving an arithmetic problem.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Department of Endodontics, Faculty of Dentistry, Marmara University, Başıbüyük, Başıbüyük Yolu Marmara Üniversitesi Başıbüyük Sağlık Yerleşkesi 9/3, Başıbüyük - Maltepe, PO Box: 34854, İstanbul, Turkey.
Introduction: The integration of artificial intelligence (AI) technologies in healthcare is revolutionizing the workflows of healthcare professionals, enabling faster and more accurate patient treatment. This study aims to evaluate the accuracy of responses provided by different AI chatbots to questions that dentists might ask regarding regenerative endodontic treatment (RET), a procedure that shows promising biological healing potential.
Methods: A total of 23 questions related to RET procedures were developed based on the American Association of Endodontists (AAE) 2022 guidelines.
Behav Brain Res
January 2025
Department of Neurosurgery, Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany; Cluster of Excellence Hearing4all, German Research Foundation, Hannover, Germany; Center for Systems Neuroscience (ZSN) Hannover, 30559 Hannover, Germany.
Background: The three-class oddball paradigm allows to investigate the processing of behaviorally relevant and irrelevant auditory stimuli. In humans, event-related potentials (ERPs) are used as neural correlate of behavior. We recorded local field potentials (LFPs) within the medial prefrontal cortex (mPFC) in rats during three-class and passive two-class oddball paradigms and analyzed the ERPs focusing on similarities to human recordings.
View Article and Find Full Text PDFNoncanonical sentence structures pose comprehension challenges because they require increased cognitive demand. Prosody may partially alleviate this cognitive load. These findings largely stem from behavioral studies, yet physiological measures may reveal additional insights into how cognition is deployed to parse sentences.
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