Abstract
Purpose: Nursing research often relies on data obtained from individuals in an effort to understand human experiences of health and illness. These individual experiences do not occur in isolation; instead, they take place within larger contexts, such as families, social groups, and schools or communities. These organizations function as complex adaptive systems (CAS), which resist reduction into simple cause-and-effect relationships. Investigating such systems, including collection of data from multiple individuals, requires flexible and adaptable research methods. Social network analysis (SNA) facilitates data collection from multiple individuals in the same context (e.g., a family, an organization), examination of interactions among individuals, and analysis of the context within which they occur. This presentation will provide an overview of SNA and describe its utility for nursing research.
Methods: The authors have used social network analysis to study families at risk of inherited conditions, families in which an adolescent has a chronic condition, and social contexts of sexual relationships. Key aspects of SNA will be illustrated, including study preparation, sampling, and data collection, analysis, and presentation.
Results: Social networks are comprised of nodes and the relationships among them. The flexibility of SNA derives from the ability to define nodes and relationships, depending on the research question of interest. Networks may be defined by respondents or researchers. Statistically, SNA accounts for interdependence of linked data, and facilitates examination of change in groups over time. Analyses can describe network structure and relationships within the network, and examine the association of network data with outcomes of interest.
Conclusion: Social network analysis is applicable to a wide array of nursing research questions. Many research questions can be adapted to use network approaches, providing unique and integrated data from multiple individuals.
Sigma Membership
Unknown
Type
Presentation
Format Type
Text-based Document
Study Design/Type
N/A
Research Approach
N/A
Keywords:
Research Methods, Complex Adaptive Systems, Social Networks
Recommended Citation
Ersig, Anne L.; Paik, Anthony; and Ayres, Lioness, "Social network analysis as a method for nursing research" (2012). INRC (Congress). 216.
https://www.sigmarepository.org/inrc/2012/presentations_2012/216
Conference Name
23rd International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Brisbane, Australia
Conference Year
2012
Rights Holder
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Acquisition
Proxy-submission
Social network analysis as a method for nursing research
Brisbane, Australia
Purpose: Nursing research often relies on data obtained from individuals in an effort to understand human experiences of health and illness. These individual experiences do not occur in isolation; instead, they take place within larger contexts, such as families, social groups, and schools or communities. These organizations function as complex adaptive systems (CAS), which resist reduction into simple cause-and-effect relationships. Investigating such systems, including collection of data from multiple individuals, requires flexible and adaptable research methods. Social network analysis (SNA) facilitates data collection from multiple individuals in the same context (e.g., a family, an organization), examination of interactions among individuals, and analysis of the context within which they occur. This presentation will provide an overview of SNA and describe its utility for nursing research.
Methods: The authors have used social network analysis to study families at risk of inherited conditions, families in which an adolescent has a chronic condition, and social contexts of sexual relationships. Key aspects of SNA will be illustrated, including study preparation, sampling, and data collection, analysis, and presentation.
Results: Social networks are comprised of nodes and the relationships among them. The flexibility of SNA derives from the ability to define nodes and relationships, depending on the research question of interest. Networks may be defined by respondents or researchers. Statistically, SNA accounts for interdependence of linked data, and facilitates examination of change in groups over time. Analyses can describe network structure and relationships within the network, and examine the association of network data with outcomes of interest.
Conclusion: Social network analysis is applicable to a wide array of nursing research questions. Many research questions can be adapted to use network approaches, providing unique and integrated data from multiple individuals.