To develop a mathematical model for determining faculty workload at a college of pharmacy with a team-based learning curriculum. Using faculty provided data, our model calculated activity and weighted means in teaching, scholarship and service. Subsequently, these data were used to develop departmental and institutional workload models. For the pharmaceutical and biomedical sciences department, percent faculty activity mean values were greatest for service followed by teaching and scholarship. These values in the clinical sciences department were greatest for teaching followed by service and scholarship. Overall, the institutional workload model had the largest maximum faculty activity value for teaching, followed by service and then scholarship. A novel faculty workload model proved to be effective in optimizing faculty workload within a college of pharmacy. Since the workload analysis, the faculty service commitment has been substantially changed, by reducing the number of committees at our institution. This type of workload analysis may particularly benefit colleges of pharmacy that employ a team based learning curriculum, with a large time commitment to teaching.
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http://dx.doi.org/10.5688/ajpe809152 | DOI Listing |
Appl Nurs Res
February 2025
Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands; School of Health Sciences, Faculty of Environmental and Life Sciences, University of Southampton, UK.
Objectives: The extent to which healthcare professionals apply Shared Decision Making (SDM) on hospital wards is still unknown. The aim was to explore the current knowledge of SDM among healthcare professionals and the experienced factors influencing SDM on the wards of Dutch hospitals, regarding both treatment and care decisions.
Setting: Twelve hospital wards in two university medical centres and one teaching hospital.
BMC Nurs
January 2025
Nursing Department, Hamad Medical Corporation, Doha, P.O. Box 3050, Qatar.
Background: Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.
View Article and Find Full Text PDFNutrients
January 2025
Physical and Sports Performance Research Centre, Faculty of Sports Sciences, Pablo de Olavide University, 41013 Seville, Spain.
Background And Objectives: In karate, particularly in the kata discipline, there is a notable lack of studies focused on specific physical preparation for competitions. This highlights an urgent need for more in-depth research into this crucial aspect of athletic training to optimize performance and athlete preparation. The objective of this study was to analyze the influence of a dietary plan combined with specific physical preparation on the performance and body composition of a professional kata athlete preparing for a Pan American championship.
View Article and Find Full Text PDFJ Clin Med
January 2025
Institute of Infectious Diseases and Infection Control, Jena University Hospital, Friedrich-Schiller-University Jena, 07747 Jena, Germany.
: Despite recent decades' rapid advances in the management of patients with sepsis and septic shock, global sepsis mortality and post-acute sepsis morbidity rates remain high. Our aim was, therefore, to provide a first overview of sepsis care pathways as well as barriers and supportive conditions for optimal pre-clinical, clinical, and post-acute sepsis care in Germany. : Between May and September 2023, we conducted semi-structured, video-based, one-to-one pilot expert interviews with healthcare professionals representing pre-hospital, clinical, and post-acute care settings.
View Article and Find Full Text PDFVet Parasitol
January 2025
Selcuk University, Faculty of Veterinary Medicine, Department of Veterinary Parasitology, Konya, Türkiye.
Eimeria is a protozoan parasite that causes coccidiosis in various animal species, especially in chickens, resulting in infections characterized by intestinal damage, hemorrhagic diarrhea, lethargy, and high mortality rates in the absence of effective control measures. The rapid spread of these parasites through ingestion of food and drinking water can seriously endanger animal health and productivity, leading to significant economic losses in the chicken industry. Chicken Eimeria species are difficult to identify by conventional microscopy due to similarities in oocyst morphologies.
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