Background: Interprofessional teamwork improves patient care quality, safety, and health outcomes. Interprofessional education (IPE) is crucial in today's medical education to prepare students for the workforce as integral members of a collaborative team. The diversity of IPE learners indicates the importance of exploring the relationship between learning styles and attitudes toward IPE. The purpose of this study was to investigate the relationship between learning styles and attitudes toward IPE.
Methods: A cross-sectional study was conducted between August 2023 and September 2023 in 49 colleges located in the south-eastern region of China. A convenience sampling approach was employed, selecting 500 students majoring in Clinical Medicine and Nursing. The students completed an online questionnaire, which included sociodemographic characteristics, educational characteristics, interprofessional educational characteristics, learning styles, and the readiness for interprofessional learning scale, and Kolb's learning style inventory. Descriptive statistics, Spearman's correlation, and multiple linear regression analysis were used to analyze the data.
Results: The most learners are diverger (93.2%), followed by assimilator (3.4%), accommodator (2.6%), and Converger (0.8%). The total score on the RIPLS was 69.70 (7.42), ranging from 48 to 88. A statistical relationship could be established between learning styles and attitudes toward IPE.
Conclusion: Abstract conceptualization and active experimentation learning modes and convergers were closely linked with positive attitudes toward IPE. Gender, age, and study stress can affect attitudes toward IPE. This study highlights the need for medical education curricula to integrate innovative teaching methods such as PBL, role-playing, scenario simulation and clinical early exposure to strengthen professional identity, and improve abilities related to interprofessional learning.
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http://dx.doi.org/10.1186/s12909-024-05710-w | DOI Listing |
Phys Rev Lett
December 2024
CERN, Geneva, Switzerland.
Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins.
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January 2025
Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Introduction: Generating physician letters is a time-consuming task in daily clinical practice.
Methods: This study investigates local fine-tuning of large language models (LLMs), specifically LLaMA models, for physician letter generation in a privacy-preserving manner within the field of radiation oncology.
Results: Our findings demonstrate that base LLaMA models, without fine-tuning, are inadequate for effectively generating physician letters.
Sci Rep
January 2025
Division of Plastic, Craniofacial and Hand Surgery, Sidra Medicine, and Weill Cornell Medical College, C1-121, Al Gharrafa St, Ar Rayyan, Doha, Qatar.
Training a machine learning system to evaluate any type of facial deformity is impeded by the scarcity of large datasets of high-quality, ethics board-approved patient images. We have built a deep learning-based cleft lip generator called CleftGAN designed to produce an almost unlimited number of high-fidelity facsimiles of cleft lip facial images with wide variation. A transfer learning protocol testing different versions of StyleGAN as the base model was undertaken.
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January 2025
Preventive Dental Science Department, College of Dentistry, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Background: The National Commission for Academic Accreditation and Assessment (NCAAA) in Saudi Arabia underscores the importance of assessing student satisfaction to ensure program quality. No previous studies have explored the satisfaction levels of dental students enrolled in clinical Periodontics courses at King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS). This study aims to assess dental students' satisfaction with clinical Periodontics courses and to explore potential differences in satisfaction based on gender and academic level.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy.
In recent years, the growing number of vehicles on the road have exacerbated issues related to safety and traffic congestion. However, the advent of the Internet of Vehicles (IoV) holds the potential to transform mobility, enhance traffic management and safety, and create smarter, more interconnected road networks. This paper addresses key road safety concerns, focusing on driver condition detection, vehicle monitoring, and traffic and road management.
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