Background: Instant messaging via WhatsApp is used within hospital teams. Group messaging can lead to efficient and non-hierarchical communication. Despite being end-to-end encrypted, WhatsApp is owned by Facebook, raising concerns regarding data security. The aims of this study were: (1) to record the prevalence of WhatsApp group instant messaging amongst clinical teams; (2) to ascertain clinician attitudes towards use of instant messaging and (3) to gauge clinicians' awareness of best practice regarding mobile data protection.
Methods: Over a two-week period in May 2018, clinical nurse specialists in the Auckland District Health Board Orthopaedic department retrospectively collected data from all five team WhatsApp group message threads recording quantity of messages sent and the nature of the messages. Concurrently individuals in these WhatsApp groups completed an anonymous survey of their use of WhatsApp and their awareness of local data security policies and practice.
Results: One thousand three hundred and sixty messages were sent via WhatsApp in a two-week period. 384 (28%) of the messages contained patient identifiable data. Thirty-six photos were shared. Participants rated use of WhatsApp at 9.1/10 - extremely beneficial. Sixty-five percent of clinicians reported they had not read or were unaware of the ADHB policies regarding mobile devices and information privacy and security.
Conclusion: WhatsApp use is widespread within the Orthopaedic department and is the preferred platform of communication with many perceived benefits. Data security is a risk and implementation of appropriate guidelines to assist clinicians in achieving best practice is crucial to ensure patient data remains protected.
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http://dx.doi.org/10.1111/ans.17550 | DOI Listing |
Sci Rep
December 2024
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, 03680, Kyiv, Ukraine.
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December 2024
Department of Architecture, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran.
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resources efficiently, and enhance the overall well-being of residents. However, as cities become increasingly interconnected and data-dependent, concerns related to data privacy and security, as well as citizen participation and representation, have surfaced.
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December 2024
Key Laboratory of Computing Power Network and Information Security, Shandong Computer Science Center (National Supercomputing Center in Jinan), Ministry of Education, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250013, Shandong, P. R. China.
Crystal structure similarity is useful for the chemical analysis of nowadays big materials databases and data mining new materials. Here we propose to use two-dimensional Wasserstein distance (earth mover's distance) to measure the compositional similarity between different compounds, based on the periodic table representation of compositions. To demonstrate the effectiveness of our approach, 1586 Cu-S based compounds are taken from the inorganic crystal structure database (ICSD) to form a validation dataset.
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December 2024
Chair of Applied Electrodynamics and Plasma Technology, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany.
Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonlinear behavior observed in their current-voltage characteristics. To comprehend the nonlinear behavior, we have to understand the coexistence of resistive, capacitive, and inertia (virtual inductive) effects in these devices.
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November 2024
School of Science, China Pharmaceutical University, Nanjing 211198, China.
The supervision of novel psychoactive substances (NPSs) is a global problem, and the regulation of NPSs was heavily relied on identifying structural matches in established NPSs databases. However, violators could circumvent legal oversight by altering the side chain structure of recognized NPSs and the existing methods cannot overcome the inaccuracy and lag of supervision. In this study, we propose a scaffold and transformer-based NPS generation and Screening (STNGS) framework to systematically identify and evaluate potential NPSs.
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