Communication that changes lives: an exploratory research on a Chinese online hypertension community

Zhao, Dongxiang; Zhang, Qiping; Ma, Feicheng

doi:10.1108/lht-08-2019-0172

Cited by 13 publications

(18 citation statements)

References 35 publications

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“…In addition to social support from families, communities, social organizations and governments, online communities also offer new possibilities and supplementary options for the elderly to exchange social support (Goswami et al, 2010). This phenomenon is similar to the social support exchange in online health communities (Kazmer et al, 2014;Zhao et al, 2020). These members have similar experiences and circumstances, making it easier to provide and request social support within online communities.…”

Section: The Roles Of Online Communities For Older Adultsmentioning

confidence: 73%

“…At present, LaoYouBang has gradually formed a relatively mature social technology mechanism; that is, a small number of core users with close connection generate most of the online communication and they offer information and social support for a large number of non-core and inactive users such as lurkers (Pfeil and Zaphiris, 2009; Pfeil et al , 2011). Information and social support mechanisms in OCOA such as LaoYouBang were also validated in the OHC (Kazmer et al , 2014; Zhao et al , 2020).…”

Section: Discussionmentioning

confidence: 99%

“…LaoYouBang was deemed appropriate to be selected as the research site. Observational netnography was used by most of the studies (Berdychevsky and Nimrod, 2015; Nimrod, 2011; Zhao et al , 2020). According to the guide of observational netnography, before collecting online discussions, one of the authors first registered an account and then conducted a two-month-long online observation of LaoYouBang.…”

Section: Methodsmentioning

confidence: 99%

“…Similar to the situation of older adults, people with chronic conditions are increasingly using an online health community (OHC) to exchange health information and social support (Chen et al , 2019; Kazmer et al , 2014). It was found that the hypertension community and online communication indeed changed the lives and health conditions of people with hypertension (Zhao et al , 2020).…”

Section: Related Workmentioning

confidence: 99%

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What is discussed about eldercare?

Zhao

Zhang

2020

Self Cite

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Purpose The purpose of this paper is to investigate eldercare issues in China through exploring what was discussed about eldercare in a Chinese online community for older adults (OCOA). Design/methodology/approach Netnography was used to explore eldercare-related online discussion in a Chinese OCOA – LaoYouBang. After a two-month-long online observation, 275 microblogs and 594 comments were collected and analysed qualitatively and quantitatively. Findings The main findings include as follows: the users involved in an online discussion about eldercare were consist of four categories, namely, elderly user, non-elderly user, advertiser and community administrator. Non-elderly user include the elderly’s caregivers and families, young and middle-aged people concerning about eldercare. From 2012 to 2017, eldercare issues gradually became refined and differentiated in China and elderly users’ contribution proportion and activeness increased yearly. According to the results of thematic analysis, users’ information needs for eldercare included opinion, news, practice, emotion, knowledge and others. In China, some changes have taken place in the public’s conceptions of eldercare, embodied in the changes in the public’s attention, attitudes and cognition. Changes in user structure and communication patterns in OCOA have also been noted. OCOA plays an important role in eldercare information dissemination and social support exchange and helps to meet the eldercare challenges. Originality/value This study explored an online community for older adults. This is the first netnography study in the information field on Chinese OCOA. This paper provides new perspectives to explore eldercare issues and OCOA in other regions and cultures and it also provides some suggestions to improve OCOA.

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Section: The Roles Of Online Communities For Older Adultsmentioning

confidence: 73%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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What is discussed about eldercare?

Zhao

Zhang

2020

Self Cite

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“…Therefore, it is important to process missing and specific values before making a prediction. Hypertension is a serious disease which can result in a lot of negative situation [4]. According to the World Health Organization (WHO), high blood pressure causes one in every eight deaths and therefore Hypertension is considered the third leading killer in the world.…”

Section: Introductionmentioning

confidence: 99%

Hypertension Prediction using Machine Learning Technique

Choi¹

2020

IJATCSE

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Machine learning technology is used in advanced data analysis and optimization approaches for different kinds of medical problems. Hypertension is complicated, and every year it causes a lot of many severe illnesses such as stroke and heart disease. This study essentially had two primary goals. Firstly, this paper intends to understand the role of variables in hypertension modeling better. Secondly, the study seeks to evaluate the predictive performance of the decision trees. Based on these results, first, age, bmi, and average glucose level influence hypertension significantly, while other variables have on influence. Second, for the full model, the accuracy rate is 0.905, which implies that the error rate is 0.095. Among the patients who were predicted not to have hypertension, the accuracy that would not have hypertension was 90.51%, and the accuracy that had strike was 30.77% among the patients who were predicted to have hypertension.

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Utilizing health-related text on social media for depression research: themes and methods

Yao,

Wang,

Chen

et al. 2023

LHT

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PurposeSocial media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods.Design/methodology/approachThe authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles.Findings(1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife.Practical implicationsThe authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression.Originality/valueThis article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.

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Communication that changes lives: an exploratory research on a Chinese online hypertension community

Cited by 13 publications

References 35 publications

What is discussed about eldercare?

What is discussed about eldercare?

Hypertension Prediction using Machine Learning Technique

Utilizing health-related text on social media for depression research: themes and methods

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