Background: This paper has two objectives. Firstly, it provides an overview of the social network module, data collection procedures, and measurement of ego-centric and complete-network properties in the Korean Social Life, Health, and Aging Project (KSHAP). Secondly, it directly compares the KSHAP structure and results to the ego-centric network structure and results of the National Social Life, Health, and Aging Project (NSHAP), which conducted in-home interviews with 3,005 persons 57 to 85 years of age in the United States.
Methods: The structure of the complete social network of 814 KSHAP respondents living in Township K was measured and examined at two levels of networks. Ego-centric network properties include network size, composition, volume of contact with network members, density, and bridging potential. Complete-network properties are degree centrality, closeness centrality, betweenness centrality, and brokerage role.
Results: We found that KSHAP respondents with a smaller number of social network members were more likely to be older and tended to have poorer self-rated health. Compared to the NSHAP, the KSHAP respondents maintained a smaller network size with a greater network density among their members and lower bridging potential. Further analysis of the complete network properties of KSHAP respondents revealed that more brokerage roles inside the same neighborhood (Ri) were significantly associated with better self-rated health. Socially isolated respondents identified by network components had the worst self-rated health.
Conclusions: The findings demonstrate the importance of social network analysis for the study of older adults' health status in Korea. The study also highlights the importance of complete-network data and its ability to reveal mechanisms beyond ego-centric network data.
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http://dx.doi.org/10.1186/1471-2318-14-102 | DOI Listing |
JMIR Form Res
December 2024
Faculty of Behavioural, Management and Social Sciences, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, Netherlands, 31 053 489 9111.
Background: With the growing need of support for informal caregivers (ICs) and care recipients (CRs) during COVID-19, the uptake of digital care collaboration platforms such as Caren increased. Caren is a platform designed to (1) improve communication and coordination between ICs and health care professionals, (2) provide a better overview of the care process, and (3) enhance safe information sharing within the care network. Insights on the impact of COVID-19 on the implementation and use of informal care platforms such as Caren are still lacking.
View Article and Find Full Text PDFBiom J
February 2025
Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA.
Despite the extensive use of network autocorrelation models in social network analysis, network autocorrelation models for binary dependent variables have received surprisingly scant attention. In this paper, we develop four network autocorrelation models for a binary random variable defined by whether the peer effect (also termed social influence or contagion) acts on latent continuous outcomes leading to an indirect effect under a normal or a logistic distribution or on the probability of the observed outcome itself under a probit or a logit link function defining a direct effect to account for interdependence between outcomes. For all models, we use a Bayesian approach for model estimation under a uniform prior on a transformed peer effect parameter ( ) designed to enhance model computation and compare results to those under the uniform prior for .
View Article and Find Full Text PDFPLoS One
December 2024
Institute of Industrial Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
To prevent widespread epidemics such as influenza or measles, it is crucial to reach a broad acceptance of vaccinations while addressing vaccine hesitancy and refusal. To gain a deeper understanding of Japan's sharp increase in COVID-19 vaccination coverage, we performed an analysis on the posts of Twitter users to investigate the formation of users' stances toward COVID-19 vaccines and information-sharing actions through the formation. We constructed a dataset of all Japanese posts mentioning vaccines for five months since the beginning of the vaccination campaign in Japan and carried out a stance detection task for all the users who wrote the posts by training an original deep neural network.
View Article and Find Full Text PDFMymensingh Med J
January 2025
Dr Maisha Farjana, Research Assistant, Bangladesh Center for Communication Programs, Dhaka, Bangladesh; E-mail:
World population is experiencing huge death toll due to Covid-19 pandemic with panic and uncertainty. Students used the electronic media called e-learning, became the budging word in these days. This study was aimed to determine the experiences of the medical students regarding e-learning during Covid-19 pandemic.
View Article and Find Full Text PDFAIDS Behav
December 2024
University of Washington Addictions, Drug & Alcohol Institute, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA.
In Southern U.S. states with high HIV incidence and low HIV Pre-Exposure Prophylaxis (PrEP) uptake, enhanced efforts to increase interest in and willingness to use PrEP are needed.
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