Daily collaboration of senior doctors, residents and nurses involves a major potential for sharing knowledge between professionals. Therefore, more attention needs to be paid to informal learning to create strategies and appropriate conditions for enhancing and effectuating informal learning in the workplace. The aim of this study is to visualize and describe patterns of informal interprofessional learning relations among staff in complex care. Questionnaires with four network questions - recognized as indicators of informal learning in the clinical workplace - were handed out to intensive and medium care unit (ICU/MCU) staff members (N = 108), of which 77% were completed and returned. Data were analyzed using social network analysis and Mokken scale analysis. Densities, tie strength and reciprocity of the four networks created show MCU and ICU nurses as subgroups within the ward and reveal central but relatively one-sided relations of senior doctors with nurses and residents. Based on the analyses, we formulated a scale of intensity of informal learning relations that can be used to understand and stimulate informal interprofessional learning.
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http://dx.doi.org/10.3109/13561820.2012.656773 | DOI Listing |
Nanoscale
March 2025
Department of Physics, University of Gothenburg, Gothenburg, Sweden.
In order to relate nanoparticle properties to function, fast and detailed particle characterization is needed. The ability to characterize nanoparticle samples using optical microscopy techniques has drastically improved over the past few decades; consequently, there are now numerous microscopy methods available for detailed characterization of particles with nanometric size. However, there is currently no "one size fits all" solution to the problem of nanoparticle characterization.
View Article and Find Full Text PDFAm J Community Psychol
March 2025
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Intergenerational connectedness broadly encompasses relations among humans, lands, and all living and spiritual beings, and functions as an important part of Indigenous well-being. Many public health campaigns and interventions aim to promote connectedness to support holistic wellness and reduce health inequities. Currently, however, there are no measurement tools to assess intergenerational connectedness to support culturally grounded research and program evaluation.
View Article and Find Full Text PDFR Soc Open Sci
March 2025
School of Electronics and Computer Science, University of Southampton, Southampton, UK.
Medical image classification plays an important role in medical imaging. In this work, we present a novel approach to enhance deep learning models in medical image classification by incorporating clinical variables without overwhelming the information. Unlike most existing deep neural network models that only consider single-pixel information, our method captures a more comprehensive view.
View Article and Find Full Text PDFEURASIP J Audio Speech Music Process
March 2025
Centre for Digital Music, Queen Mary University of London, London, UK.
This paper introduces singing to speech conversion (S2S), a cross-domain voice conversion task, and presents the first deep learning-based S2S system. S2S aims to transform singing into speech while retaining the phonetic information, reducing variations in pitch, rhythm, and timbre. Inspired by the Glow-TTS architecture, the proposed model is built using generative flow, with an adjusted alignment module between the latent features.
View Article and Find Full Text PDFTob Use Insights
March 2025
Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
The novelty of e-cigarette regulatory policy poses difficulties for evidence-informed decision making because there is little evaluative evidence on the effects of specific policies. One way to provide evidence to inform Canadian policy in this situation is to learn from users how they would behave under different policy scenarios without actually implementing those policies in real-world settings. Discrete Choice Experiments provide an opportunity to undertake this research.
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