Aims And Objectives: The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research.
Background: The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention.
Design: Review of literature and illustration of the application of the method of social network analysis using research examples.
Methods: First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated.
Results: The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors.
Conclusion: Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network.
Relevance To Clinical Practice: Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider.
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http://dx.doi.org/10.1111/j.1365-2702.2011.04036.x | DOI Listing |
R Soc Open Sci
January 2025
Mathematics Application Consortium for Science and Industry (MACSI), University of Limerick, Limerick, Ireland.
The analysis of social networks enables the understanding of social interactions, polarization of ideas and the spread of information, and therefore plays an important role in society. We use Twitter data-as it is a popular venue for the expression of opinion and dissemination of information-to identify opposing sides of a debate and, importantly, to observe how information spreads between these groups in our current polarized climate. To achieve this, we collected over 688 000 tweets from the Irish Abortion Referendum of 2018 to build a conversation network from users' mentions with sentiment-based homophily.
View Article and Find Full Text PDFFront Child Adolesc Psychiatry
November 2024
Department of Psychology, Palo Alto University, Palo Alto, CA, United States.
Introduction: Autism Spectrum Disorder (ASD) is characterized by deficits in social cognition, self-referential processing, and restricted repetitive behaviors. Despite the established clinical symptoms and neurofunctional alterations in ASD, definitive biomarkers for ASD features during neurodevelopment remain unknown. In this study, we aimed to explore if activation in brain regions of the default mode network (DMN), specifically the medial prefrontal cortex (MPC), posterior cingulate cortex (PCC), superior temporal sulcus (STS), inferior frontal gyrus (IFG), angular gyrus (AG), and the temporoparietal junction (TPJ), during resting-state functional magnetic resonance imaging (rs-fMRI) is associated with possible phenotypic features of autism (PPFA) in a large, diverse youth cohort.
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October 2024
Department of Oncology, National Orthopaedic Hospital, Igbobi, Lagos 2008, Nigeria.
Introduction: Numerous challenges hinder the development of multidisciplinary medical education in a resource-constrained environment. Communal tumour boards built through networking could be a suitable model for the effective management of diseases and enhancement of medical education. This study evaluated the impact of an integrated care pathway for patients with musculoskeletal tumours via multi-institutional networking in a metropolis.
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December 2025
Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu India.
Autism spectrum disorder (ASD) is one of the complicated neurodevelopmental disorders that impacts the daily functioning and social interactions of individuals. It includes diverse symptoms and severity levels, making it challenging to diagnose and treat efficiently. Various deep learning (DL) based methods have been developed for diagnosing ASD, which rely heavily on behavioral assessment.
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