Social Network Communications in Chilean Older Adults

Impact of smart device use on objective and subjective health of older adults: findings from four provinces in China

Background

The digital divide has grown because of the deepening digitalization of the Chinese society and the intersection between high-end technology and the age structure. Older adults show an increasing level of weakness in digital life integration. What digital development can bring to older adults is a pressing concern.

Objective

This study aims to investigate how smart device use affects older adults' health status and offers an empirical reference for improving their digital literacy and health.

Methods

The data in this study were collected from an offline survey conducted from December 2021 to April 2022, which obtained 1110 valid samples of older adults This study used a multivariate ordered logit model, mediating effect model, and heterogeneity test to analyze the impact of smart device use on the health status of older adults.

Results

Smart device use has a significant positive effect on the self-rated, physical, and psychological health of older adults, and this positive effect is more pronounced among older adults living in urban areas or with a higher age. The average net effect of smart devices on each health status of older adults is 0.161 for self-rated health, 0.155 for physical health, and 0.071 for psychological health. In-depth research found that older adults' attitudes toward smart devices played a mediating role in the influence of smart device use on self-rated and psychological health respectively.

Conclusions

The study found that smart device use had a positive effect on the health status of older adults and that the performance expectations and individualized needs of older adults exhibited an effective linkage between smart devices and health status. Smart device use could improve the overall health of older adults, especially the urban and low-age older adults. Promoting the understanding of the practicality of smart devices for older adults and the aging-oriented transformation of smart devices is an effective way to improve the health status of older adults. The findings provide theoretical support for the wide application of smart devices in older adults, and can effectively help eHealth practitioners implement accurate geriatric health support strategies.

Social network research hotspots and trends in public health: A bibliometric and visual analysis

Objectives

To understand the research landscape and identify the research hotspots and trends of the application of social network theory and analysis to public health.

Study design

A bibliometric study of publications regarding application of social network theory and analysis to public health.

Methods

Choosing 1607 articles about the application of social network theory and analysis to public health from the core collection database of Web of Science published from 1991 to 2020 as the research sample. A bibliometric and visual analysis of publication quantity and content was performed to analyze time trends, spatial distribution, cooperation networks, influential references, and keyword co-occurrence, clusters, and emergence.

Results

There is an increasing trend in the use of social network theory and analysis in the public health field, with the United States taking the lead. Research focuses include on transmission of diseases or behavior through social networks and the influence of social networks on population health at different ages. Current research frontiers primarily include the role of social networks in tracking of emerging infectious diseases like COVID-19, preventing and controlling chronic diseases, and carrying out healthy behavioral interventions.

Conclusions

This study provides a comprehensive quantitative overview of the historic development of and latest topics in the application of social network theory and analysis method to public health. More attention should be paid to the important role of social networks in tracing the emergence of serious infectious diseases like COVID-19, as well as preventing and controlling chronic diseases and intervening in health behaviors, considering the increasing challenges and opportunities presented by online social networking.

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The use of social network theory and analysis (SNT/A) in public health has grown sharply since 2007.

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The United States has taken the lead in this field of research, with some active institutions in the U.S. and the Europe.

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The transmission of diseases or behaviors within social networks is a major research focus in this interdisciplinary field.

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Research frontiers primarily include using SNT/A to track, prevent and control diseases, like COVID-19.

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

This study analyzes the most important predictors of acceptance of social network sites in a sample of Chilean elder people (over 60). We employ a novelty procedure to explore this phenomenon. This procedure performs apriori segmentation based on gender and generation. It then applies the deep learning technique to identify the predictors (performance expectancy, effort expectancy, altruism, telepresence, social identity, facilitating conditions, hedonic motivation, perceived physical condition, social norms, habit, and trust) by segments. The predictor variables were taken from the literature on the use of social network sites, and an empirical study was carried out by quota sampling with a sample size of 395 older people. The results show different predictors of social network sites considering all the samples, baby boomer (born between 1947 and 1966) males and females, silent (born between 1927 and 1946) males and females. The high heterogeneity among older people is confirmed; this means that dealing with older adults as a uniform set of users of social network sites is a mistake. This study demonstrates that the four segments behave differently, and many diverse variables influence the acceptance of social network sites.

Lonely in the City-Sociodemographic Status and Somatic Morbidities as Predictors of Loneliness and Depression among Seniors-Preliminary Results

Up to a third of the population of older adults has been estimated to suffer from feelings of loneliness, which is considered a risk factor of depression. The aim of this paper is to compare the perceived level of loneliness and depression in seniors living in the country and in the cities and assess somatic morbidity and sociodemographic status as predictors of loneliness and depressiveness. n = 92 older adults in primary care units filled out a set of questionnaires: authors' survey on sociodemographic data and morbidities, Beck Depression Inventory II (BDI, to measure depressiveness) and De Jong Gierveld Loneliness Scale (DJGLS, to assess loneliness). There was a strong, positive and statistically significant correlation between the BDI and DJGLS scores (R = 0.855, p < 0.001). City residents had on average higher BDI and DJGLS scores. Linear regression models were constructed to predict BDI and DJGLS scores. The set of statistically significant predictors were similar for BDI and DJGLS. Sociodemographic status and somatic morbidities accounted for around 90% of variance of depressiveness and loneliness scores in the studied group. Living alone was found to be the strongest relative predictor of both loneliness and depressiveness in the studied sample of the older adults. Our current results suggest that there might be a need to improve social support in the late adulthood as an intervention to diminish the sense of loneliness and depressiveness.