Social Networks and Health-Related Quality of Life Among Chinese Older Adults With Vision Impairment

2008 ◽  
Vol 20 (7) ◽  
pp. 804-823 ◽  
Author(s):  
Chong-Wen Wang ◽  
Cecilia L. W. Chan ◽  
Andy H. Y. Ho ◽  
Zhifan Xiong
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Social Networks ◽  
Vision Impairment ◽  
Health Related Quality ◽  
Chinese Older Adults ◽  
Related Quality ◽  
Health Related

Association between eHealth Literacy and Health-Related Quality of Life among Chinese Older Adults: A Cross-Sectional Study (Preprint)

2020 ◽  
Author(s):  
Shaojie Li ◽  
Yongtian Yin ◽  
Lijun Chen ◽  
Guanghui Cui ◽  
Jiaqin Li ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Mental Component Summary ◽  
Health Related Quality ◽  
Cross Sectional ◽  
Chinese Older Adults ◽  
Ehealth Literacy ◽  
Related Quality ◽  
Health Related

BACKGROUND Older adults’ health literacy levels are crucial to improving health outcomes and health-related quality of life (HRQoL). However, the impact of eHealth literacy on HRQoL in older adults is unclear. OBJECTIVE The aim of this study was to examine the association between eHealth literacy and HRQoL of older adults and provide reference for the development of network intervention measures related to the health quality of life of the older adults. METHODS An anonymous cross-sectional survey was conducted among 1,201 adults aged 60 or older from Jinan, China. The eHealth Literacy Scale and Short-Form Health Survey (SF-12) were used to measure eHealth literacy and HRQoL. We used linear regression to test the adjusted association between eHealth literacy and HRQoL. RESULTS Most participants (88.9%) had inadequate eHealth literacy. Lower eHealth literacy was related to older age ( F=12.618, P<.001), female gender( t=3.303, P<.01), living in rural areas( F=11.356, P<.001), having less education( F=59.084, P<.001), being unmarried, divorced or widowed( t=4.416, P<.001), having a lower family income( F=38.017, P<.001), living with others(χ2=4.319, P<.05), and not having health insurance( F=12.713, P<.001). There were significant differences across physical functioning( t=-4.862, P<.001), role- physical( t=-2.485, P<.05), bodily pain( t=-3.470, P<.01), general health( t=-4.449, P<.001), vitality( t=-3.498, P<.001), role-emotional( t=-2.654, P<.01), mental health( t=-4.150, P<.001), physical component summary( t=-6.350, P<.001) and mental component summary( t=-4.483, P<.001) between adequate eHealth literacy and inadequate eHealth literacy. After controlling for age, gender, and other covariates, adequate eHealth literacy was positively related to physical component summary ( beta=7.6, P<.001) and mental component summary(beta=4.6, P=.001). CONCLUSIONS This study showed that Chinese older adults with higher eHealth literacy were more likely to contribute to higher HRQoL. Thus, Older adults’ eHealth literacy levels need to be taken into account when formulating health education and promotion programs for older adults, especially when the expected outcome is to improve HRQoL.

scholarly journals Social networks and health-related quality of life: a population based study among older adults

2009 ◽  
Vol 51 (1) ◽  
pp. 06-13 ◽  
Author(s):  
Katia Gallegos-Carrillo ◽  
Jyoti Mudgal ◽  
Sergio Sánchez-García ◽  
Fernando A Wagner ◽  
Joseph J Gallo ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Social Networks ◽  
Population Based ◽  
Health Related Quality ◽  
Population Based Study ◽  
Related Quality ◽  
Health Related

scholarly journals Observational cohort study investigating cognitive outcomes, social networks and well-being in older adults: a study protocol

BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e029495 ◽  
Author(s):  
Joyce Siette ◽  
Andrew Georgiou ◽  
Johanna Westbrook
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Social Networks ◽  
Cognitive Function ◽  
Health Related Quality ◽  
Care Services ◽  
Related Quality ◽  
Health Related ◽  
Observational Cohort

IntroductionSocial networks play a role in slowing the development of dementia. However, there is a need for further investigation of the effects of improving social networks on health-related quality of life and cognitive performance. Targeted community aged care services are a central strategy for supporting older adults to initiate and maintain their social engagement with other individuals at all stages of later life. This protocol describes a prospective observational cohort study aimed at (1) characterising interpersonal relationships in older adults receiving community care services, (2) assessing the relationship social networks and health-related quality of life and cognition and (3) identifying the association between community care use, social networks and cognition. The findings will contribute to our understanding of how specific social network structures and social support services can maintain cognitive function in community-dwelling older adults.Methods and analysisThis is a prospective, observational cohort study of 201 older Australians residing in the community and receiving care services from one of three aged care organisations. Clients with a history of neurological injury will be excluded. Participants will undergo baseline measures of social networks, health-related quality of life and cognitive function, and a follow-up at 6 months. Service use and sociodemographic variables will also be collected. The primary outcome is cognitive function, and secondary outcomes include social networks and health-related quality of life. Multivariable linear regression will test the hypothesis that increased social networks are associated with an increase in cognitive function.Ethics and disseminationApproval of the study by Macquarie University Research Ethics Committee (reference number 5201831394062) has been obtained. This work will be disseminated by publication of peer-reviewed manuscripts, presentations in abstract form at scientific meetings and results will be made available to home and community-based care older adults and care staff of the involved organisations.Trial registration numberACTRN12618001723279; Pre-results.

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