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. 2021 Sep 3;18(17):9309.
doi: 10.3390/ijerph18179309.

Identifying the Knowledge Structure and Trends of Outreach in Public Health Care: A Text Network Analysis and Topic Modeling

Sooyeon Park  1 , Jinkyung Park  2
Affiliations

Identifying the Knowledge Structure and Trends of Outreach in Public Health Care: A Text Network Analysis and Topic Modeling

Sooyeon Park et al. Int J Environ Res Public Health. .

Abstract

Outreach programs are considered a key strategy for providing services to underserved populations and play a central role in delivering health-care services. To address this challenge, knowledge relevant to global health outreach programs has recently been expanded. The aims of this study were to analyze the knowledge structure and understand the trends in aspects over time and across regions using text network analysis with NetMiner 4.0. Data analysis by frequency, time and region showed that the central keywords such as patient, care, service and community were found to be highly related to the area, target population, purpose and type of services within the knowledge structure of outreach. As a result of performing topic modeling, knowledge structure in this area consisted of five topics: patient-centered care, HIV care continuum, services related to a specific disease, community-based health-care services and research and education on health programs. Our results newly identified that patient-centered care, specific disease and population have been growing more crucial for all times and countries by the examination of major trends in health-care related outreach research. These findings help health professionals, researchers and policymakers in nursing and public health fields in understanding and developing health-care-related outreach practices and suggest future research direction.

Keywords: outreach; public health care; semantics; text network analysis; topic modeling.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The flowchart of article inclusion process.
Figure 2
Figure 2
Overall knowledge structure for outreach research. The size of the node indicates the degree centrality of the keyword, and the width of the line indicates the strength of the link between keywords.
Figure 3
Figure 3
Knowledge structure of outreach research by each region. The size of the node indicates the degree centrality of the keyword, and the width of the line indicates the strength of the link between keywords; AFRO = African Region; AMR = Region of the Americas, SEARO = South-East Asia Region; EURO = European Region; EMRO = Eastern Mediterranean Region; WPRO = Western Pacific Region.
Figure 4
Figure 4
Topic modeling of outreach research by each region. The size of the node indicates the degree centrality of the keyword, and the width of the line indicates the strength of the link between keywords; AFRO = African Region; AMR = Region of the Americas, SEARO = South-East Asia Region; EURO = European Region; EMRO = Eastern Mediterranean Region; WPRO = Western Pacific Region.
Figure 4
Figure 4
Topic modeling of outreach research by each region. The size of the node indicates the degree centrality of the keyword, and the width of the line indicates the strength of the link between keywords; AFRO = African Region; AMR = Region of the Americas, SEARO = South-East Asia Region; EURO = European Region; EMRO = Eastern Mediterranean Region; WPRO = Western Pacific Region.
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