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Understanding complex interactions using social network analysis

Author

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  • Janette Pow
  • Kaberi Gayen
  • Lawrie Elliott
  • Robert Raeside

Abstract

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.

Suggested Citation

  • Janette Pow & Kaberi Gayen & Lawrie Elliott & Robert Raeside, 2012. "Understanding complex interactions using social network analysis," Journal of Clinical Nursing, John Wiley & Sons, vol. 21(19pt20), pages 2772-2779, October.
  • Handle: RePEc:wly:jocnur:v:21:y:2012:i:19pt20:p:2772-2779
    DOI: 10.1111/j.1365-2702.2011.04036.x
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    Cited by:

    1. Jin Zhang & Shanshan Zhai & Hongxia Liu & Jennifer Ann Stevenson, 2016. "Social network analysis on a topic‐based navigation guidance system in a public health portal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1068-1088, May.
    2. Alfonso Chaves-Montero & Fernando Relinque-Medina & Manuela Á. Fernández-Borrero & Octavio Vázquez-Aguado, 2021. "Twitter, Social Services and Covid-19: Analysis of Interactions between Political Parties and Citizens," Sustainability, MDPI, vol. 13(4), pages 1-15, February.
    3. Guancen Wu & Jing Li & Dan Chong & Xing Niu, 2021. "Analysis on the Housing Price Relationship Network of Large and Medium-Sized Cities in China Based on Gravity Model," Sustainability, MDPI, vol. 13(7), pages 1-20, April.

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