This article reports a study evaluating the implementation of Collaborative Learning in Practice models at a university School of Nursing and Midwifery with practice partners across the South West of England. We conducted four focus group interviews with 40 students with experience of Collaborative Learning in Practice placements, and two focus groups with eight clinical practice staff with responsibility for implementing and supporting such models in their areas. Data were transcribed and analysed using the Framework Method. Key themes were 'Real time' Practice of Collaborative Learning Implementation, Collaborative Learning as Preparation for Registrant Practice, and the Student/Mentor Relationship. We conclude that Collaborative Learning in Practice utilising models of coaching and peer support, offers benefits to students who are exposed to the reality of nursing practice from the beginning of their placement experiences, enabling them greater responsibility and peer support than under normal mentoring arrangements. Furthermore, there are benefits to the registrants because the burdens of supervising students are spread more widely. This is timely given the review of Nursing and Midwifery Council standards for programmes and student support and the need to increase placement capacity as a response to global nursing shortages.
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http://dx.doi.org/10.1016/j.nepr.2020.102742 | DOI Listing |
JMIR Med Educ
March 2025
Division of Pulmonary, Critical Care, & Sleep Medicine, Department of Medicine, NYU Grossman School of Medicine, 550 First Avenue, 15th Floor, Medical ICU, New York, NY, 10016, United States, 1 2122635800.
Background: Although technology is rapidly advancing in immersive virtual reality (VR) simulation, there is a paucity of literature to guide its implementation into health professions education, and there are no described best practices for the development of this evolving technology.
Objective: We conducted a qualitative study using semistructured interviews with early adopters of immersive VR simulation technology to investigate use and motivations behind using this technology in educational practice, and to identify the educational needs that this technology can address.
Methods: We conducted 16 interviews with VR early adopters.
Ecol Appl
March 2025
Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA.
There is substantial interest in restoring tidal wetlands because of their high rates of long-term soil carbon sequestration and other valued ecosystem services. However, these wetlands are sometimes net sources of greenhouse gases (GHG) that may offset their climate cooling potential. GHG fluxes vary widely within and across tidal wetlands, so it is essential to better understand how key environmental drivers, and importantly, land management, affect GHG dynamics.
View Article and Find Full Text PDFInt J Nurs Educ Scholarsh
January 2025
National Taipei University of Nursing and Health Sciences, Taipei City, Taiwan R.O.C.
Aim: This study evaluated the effect of cooperative learning on the attitude, satisfaction, and performance of undergraduate nursing students enrolled in community nursing courses.
Design: A one-group pretest-posttest quasi-experimental design.
Methods: This study was conducted at a university in northern Taiwan.
HCA Healthc J Med
February 2025
Staten Island University Hospital, Staten Island, New York.
Background: Creutzfeldt-Jakob disease (CJD) is a rapidly progressive neurodegenerative condition that is not easily diagnosed and has no curative treatments available, essentially requiring palliative measures, including tube feeding. Nonetheless, data shows that the endoscope used for percutaneous endoscopic gastrostomy (PEG) tube insertion can be a vector for CJD transmission.
Case Presentation: We discuss the case of an elderly patient diagnosed with CJD, requiring tube feeding.
Food Chem X
February 2025
Food Science College, Xizang Agriculture & Animal Husbandry University, R&D Center of Agricultural Products with Xizang Plateau Characteristics, The Provincial and Ministerial Co-founded Collaborative Innovation Center for R&D in Xizang Characteristic Agricultural and Animal Husbandry Resources, Nyingchi 860000, China.
Commercial jerky counterfeiting is widespread in the market. This study combined visible-near-infrared and short-wave-near-infrared hyperspectral imaging along with multiple machine learning algorithms for non-destructive identification of five types of commercial jerky products, and explored the impact of different spectral bands, algorithm selection, and optimization methods on identification performance. After data preprocessing, all models' accuracies and stability improved.
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