Background: Stop the Bleed is a free 1-hour class that teaches laypersons to identify and treat life-threatening bleeding. The training requires a 1:10 instructor-to-participant ratio, which creates a resource drain on volunteer instructors. Nursing students are eligible to assist instructors.
Problem: Our State Legislature mandated that public schools equip themselves with bleeding control kits resulting in thousands of school staff needing training.
Approach: Our nursing school used a service learning model to aid schools. Nursing students coordinated the program, and student learning occurred through a learning-by-teaching strategy.
Outcomes: We trained 656 community members, taught in 5 counties, and students received 320 clinical hours. If not for COVID-19 (coronavirus disease 2019), numbers would have been doubled. We developed a sustainable relationship with school nurses. Students rated the program highly with respect to meeting course objectives and preparation for professional practice.
Conclusions: The program met its goals and will continue.
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http://dx.doi.org/10.1097/NNE.0000000000001038 | DOI Listing |
Sci Rep
December 2024
Department of Biology, University of South Dakota, 414 East Clark Street, Vermillion, SD, 57069-2390, USA.
Psychological distress, including anxiety or mood disorders, emanates from the onset of chronic/unpredictable stressful events. Symptoms in the form of maladaptive behaviors are learned and difficult to treat. While the origin of stress-induced disorders seems to be where learning and stress intersect, this relationship and molecular pathways involved remain largely unresolved.
View Article and Find Full Text PDFSci Rep
December 2024
Cereal Disease Laboratory, Agricultural Research Service, US Department of Agriculture, St. Paul, MN, 55108, USA.
Fusarium graminearum is a primary cause of Fusarium head blight (FHB) on wheat and barley. The fungus produces trichothecene mycotoxins that render grain unsuitable for food, feed, or malt. Isolates of F.
View Article and Find Full Text PDFSci Rep
December 2024
Institute of Informatics, HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland, Sierre, Switzerland.
Manual segmentation of lesions, required for radiotherapy planning and follow-up, is time-consuming and error-prone. Automatic detection and segmentation can assist radiologists in these tasks. This work explores the automated detection and segmentation of brain metastases (BMs) in longitudinal MRIs.
View Article and Find Full Text PDFBrief Bioinform
November 2024
In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, 250 Wuxing Street, 110, Taipei, Taiwan.
Accurate prediction of RNA modifications holds profound implications for elucidating RNA function and mechanism, with potential applications in drug development. Here, the RNA-ModX presents a highly precise predictive model designed to forecast post-transcriptional RNA modifications, complemented by a user-friendly web application tailored for seamless utilization by future researchers. To achieve exceptional accuracy, the RNA-ModX systematically explored a range of machine learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit, and Transformer-based architectures.
View Article and Find Full Text PDFFront Public Health
December 2024
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Objective: To characterize the public conversations around long COVID, as expressed through X (formerly Twitter) posts from May 2020 to April 2023.
Methods: Using X as the data source, we extracted tweets containing #long-covid, #long_covid, or "long covid," posted from May 2020 to April 2023. We then conducted an unsupervised deep learning analysis using Bidirectional Encoder Representations from Transformers (BERT).
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