Using Structure Holes for Determining Key Factors: An Illustration of Reporting Eradication of Amoebiasis
Applied and Computational Mathematics
Volume 6, Issue 4-1, July 2017, Pages: 55-63
Received: Dec. 20, 2016; Accepted: Jan. 9, 2017; Published: Jan. 24, 2017
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Authors
Tsair-Wei Chien, Research Departments, Chi-Mei Medical Center, Tainan, Taiwan; Department of Hospital and Health Care Administration, Chia-Nan University of Pharmacy and Science, Tainan, Taiwan
Shih-Bin Su, Department of Occupation Medicine, Chi-Mei Medical Center, Tainan, Taiwan
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Abstract
Background: Many researches aim to determine key factors affecting their concerns of interest using traditional statistical techniques, such as logistical or linear regressions. Social network analysis (SNA) is a newly novel way determining key roles through the use of network and graph theories recently. An example of commonly visualized through SNA is the disease transmission path of Middle East respiratory syndrome (MERS). Purpose: To determine key roles using structure holes of SNA for further improvement, and to show the SNA advantage over traditional classic test theory. Methods: Data were records regarding 443 adult mentally retarded residents who were infected with amoebiasis and distributed in 10 houses in past 10 years. A series of intensive mass screenings and treatment interventions were conducted. Structure holes were applied to verify the efficacy of determining key roles and strong associations for the domains of interest in a network and compared with the result obtained from the traditional Chi-square statistics. Results: The classification of key roles in a network (e.g., with which year the residency room with amoebiasis cases has strongly association) can be effectively discriminated through the structure holes of SNA. Though the result is similar to the traditional Chi-square statistics, the structure holes can release much more useful and valuable information for further investigation. Conclusions: Because of advances in computer technology, the number of healthcare studies for the group classification and association assertion continues to increase and benefit comparisons of data if structure holes of SNA are applied.
Keywords
Social Network Analysis, Structure Holes, Chi-Square Statistics, Middle East Respiratory Syndrome, Amoebiasis
To cite this article
Tsair-Wei Chien, Shih-Bin Su, Using Structure Holes for Determining Key Factors: An Illustration of Reporting Eradication of Amoebiasis, Applied and Computational Mathematics. Special Issue: Some Novel Algorithms for Global Optimization and Relevant Subjects. Vol. 6, No. 4-1, 2017, pp. 55-63. doi: 10.11648/j.acm.s.2017060401.15
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Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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