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Social network analysis model for research on organizational structure of the pyramid scheme communication network.

ABSTRACT: In this article, we introduce a structural analysis model to analyze the characteristics of the communication network structure of pyramid scheme organizations. This model is a combination of SNA (Social Network Analysis) model, motifs analysis model, and exponential random graph model. It can analyze the network from three aspects: global structure analysis, microstructure analysis, and construction feature analysis. We use this model to analyze the characteristics of multiple aspects of a typical pyramid scheme organization's communication network, and the analysis results effectively expand the understanding of the characteristics of the pyramid scheme organization.•SNA model can be used to analyze the global structure of the pyramid scheme communication network.•Motifs analysis model can be used to analyze the microstructure characteristics of the pyramid scheme organization communication network.•Exponential Random Graph Model can be used to analyze the construction characteristics of the pyramid scheme communication network.

SUBMITTER: Feng P

PROVIDER: S-EPMC8374287 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Social network analysis model for research on organizational structure of the pyramid scheme communication network.

Feng Pihu P Lu Xin X Gong Zaiwu Z Li Bo B Sun Duoyong D

MethodsX 20210203

In this article, we introduce a structural analysis model to analyze the characteristics of the communication network structure of pyramid scheme organizations. This model is a combination of SNA (Social Network Analysis) model, motifs analysis model, and exponential random graph model. It can analyze the network from three aspects: global structure analysis, microstructure analysis, and construction feature analysis. We use this model to analyze the characteristics of multiple aspects of a typi ...[more]

PMID: 34434781

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Project description:BackgroundOptimal care delivery requires timely, efficient, and accurate communication among numerous providers and their patients, especially during hospital discharge. Little is known about communication patterns during this process.ObjectiveOur aim was to assess the frequency and patterns of communication between patients and providers during patient discharges from a hospital-based medicine unit.Design and approachOn the day of the patient's discharge, the patient and all healthcare providers involved in the discharge were interviewed using structured questions related to information exchange during the discharge process. Each interview identified the frequency and method of communication between participants, including synchronous (e.g., face-to-face) and asynchronous (e.g., through electronic medical record) routes. Communication patterns were visually diagramed using social network analysis.ParticipantsForty-six patients were screened for inclusion in the network analysis. Of those, seven patients who were fully oriented and able to complete an interview and all providers who participated in their care during the discharge were selected for inclusion in the analysis. In all, 72 healthcare professionals contributing to the discharge process were interviewed, including physicians, nurses, therapists, pharmacists, care coordinators, social workers, and nutritionists.Key resultsPatients' mean age was 63, length-of-stay was 7.8 days, and most (86 %) were discharged to home. On average, 11 roles were involved with each discharge. The majority of communication was synchronous (562 events vs. 469 asynchronous events, p = 0.004). Most communication events occurred between the primary nurse and patient and the care coordinator and primary nurse (mean 3.9 and 2.3 events/discharge, respectively). Participants identified intern physicians as most important in the discharge process, followed by primary nurses and care coordinators.ConclusionsIn patients being discharged from the medicine service, communication was more frequently synchronous, and occurred between intern physicians, primary nurses, and patients. Potential improvements in coordinating patients' discharges are possible by reorganizing systems to optimize efficient communication.

Project description:Background and objectiveResearch collaborations in biomedical research have evolved over time. No studies have addressed research collaboration in network meta-analysis (NMA). In this study, we used social network analysis methods to characterize global collaboration patterns of published NMAs over the past decades.MethodsPubMed, EMBASE, Web of Science and the Cochrane Library were searched (at 9th July, 2015) to include systematic reviews incorporating NMA. Two reviewers independently selected studies and cross-checked the standardized data. Data was analyzed using Ucinet 6.0 and SPSS 17.0. NetDraw software was used to draw social networks.Results771 NMAs published in 336 journals from 3459 authors and 1258 institutions in 49 countries through the period 1997-2015 were included. More than three-quarters (n = 625; 81.06%) of the NMAs were published in the last 5-years. The BMJ (4.93%), Current Medical Research and Opinion (4.67%) and PLOS One (4.02%) were the journals that published the greatest number of NMAs. The UK and the USA (followed by Canada, China, the Netherlands, Italy and Germany) headed the absolute global productivity ranking in number of NMAs. The top 20 authors and institutions with the highest publication rates were identified. Overall, 43 clusters of authors (four major groups: one with 37 members, one with 12 members, one with 11 members and one with 10 members) and 21 clusters of institutions (two major groups: one with 62 members and one with 20 members) were identified. The most prolific authors were affiliated with academic institutions and private consulting firms. 181 consulting firms and pharmaceutical industries (14.39% of institutions) were involved in 199 NMAs (25.81% of total publications). Although there were increases in international and inter-institution collaborations, the research collaboration by authors, institutions and countries were still weak and most collaboration groups were small sizes.ConclusionScientific production on NMA is increasing worldwide with research leadership of Western countries (most notably, the UK, the USA and Canada). More authors, institutions and nations are becoming involved in research collaborations, but frequently with limited international collaborations.

Project description:BackgroundIn 2012 and 2013, we conducted a social network survey of a new translational research network (TRN) designed to deliver better care to cancer patients. Results of these two surveys showed that silos of researchers and clinicians existed before the TRN was established but that the network had mediated collaborative relationships. This paper reports on a third social network survey of the TRN and focusses on the structure of the collaborative arrangements among members.MethodsMembers of the TRN were invited to complete an on-line, whole network survey in May 2015. The survey asked respondents to identify personal impacts, outputs and wider outcomes attributable to their TRN membership. The final question asked respondents to select the name of TRN members with whom they had collaborated either formally or informally. For each member nominated, they were asked to say whether they had known this person before joining the TRN.ResultsResponse rate was 70 %. Over 4 years, the TRN has grown in size from 68 to 244 members. Relationships within and across the TRN have become more collaborative and interactive, with 1658 collaborative ties between members and over 40 % of ties with people unknown to participants before they joined the TRN. This points to a well-functioning network which has retained its focus on the original goals of the TRN and has fostered collaboration between researchers, clinicians, managers, consumers and TRN operational staff. This survey shows that the TRN's impact goes beyond outcomes from formal TRN-funded projects. About one third of respondents could list projects not directly funded by the TRN but which are attributed to TRN membership. Examples of practice change brought about through the TRN were given by 77 % of respondents. A substantial risk factor for the future is the high levels of dependency on key or central TRN participants.ConclusionsThe structure of the TRN with its active central actors and brokers has been able to foster collaboration on implementation initiatives that result in practice change. The role of a social professional network in driving this collaboration is shown.

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Social network analysis model for research on organizational structure of the pyramid scheme communication network.

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Social network analysis model for research on organizational structure of the pyramid scheme communication network.

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