Behavior patterns and influencing factors: Health information acquisition behavior of Chinese senior adults on WeChat

Wei, Wang; Zhang, H

doi:10.1016/j.heliyon.2023.e16431

Cited by 5 publications

(5 citation statements)

References 36 publications

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“…According to our analysis, Generation Z in China is predicted to share the views and aspirations of prior generations [22]. It is not surprising that, in line with earlier research [55,56], internet sources constitute Generation Z's primary source of information on health and well-being, surpassing traditional media and physician visits.…”

Section: Comparison With Prior Worksupporting

confidence: 59%

“…With their interest in health information and the gradual adoption of social media by older people, older Chinese adults have started using WeChat to access health information. For example, a cross-sectional survey was conducted in China to examine the specific patterns and motivating factors that influence how older adults obtain health information [22]. According to their 336 self-reported findings, there are 3 types of behavior (actively seeking, passively browsing, and long-term collecting) when it comes to learning how older adults access health information.…”

Section: Hisb Overallmentioning

confidence: 99%

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Predicting and Empowering Health for Generation Z by Comparing Health Information Seeking and Digital Health Literacy: Cross-Sectional Questionnaire Study

Jiao,

Chang,

et al. 2023

J Med Internet Res

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Background Generation Z (born 1995-2010) members are digital residents who use technology and the internet more frequently than any previous generation to learn about their health. They are increasingly moving away from conventional methods of seeking health information as technology advances quickly and becomes more widely available, resulting in a more digitalized health care system. Similar to all groups, Generation Z has specific health care requirements and preferences, and their use of technology influences how they look for health information. However, they have often been overlooked in scholarly research. Objective First, we aimed to identify the information-seeking preferences of older individuals and Generation Z (those between the ages of 18 and 26 years); second, we aimed to predict the effects of digital health literacy and health empowerment in both groups. We also aimed to identify factors that impact how both groups engage in digital health and remain in control of their own health. Methods The Health Information National Trends Survey was adopted for further use in 2022. We analyzed 1862 valid data points by conducting a survey among Chinese respondents to address the research gap. A descriptive analysis, 2-tailed t test, and multiple linear regression were applied to the results. Results When compared with previous generations, Generation Z respondents (995/1862, 53.44%) were more likely to use the internet to find out about health-related topics, whereas earlier generations relied more on traditional media and interpersonal contact. Web-based information-seeking behavior is predicted by digital health literacy (Generation Z: β=.192, P<.001; older population: β=.337, P<.001). While this was happening, only seeking health information from physicians positively predicted health empowerment (Generation Z: β=.070, P=.002; older population: β=.089, P<.001). Despite more frequent use of the internet to learn about their health, Generation Z showed lower levels of health empowerment and less desire to look for health information, overall. Conclusions This study examined and compared the health information–seeking behaviors of Generation Z and older individuals to improve their digital health literacy and health empowerment. The 2 groups demonstrated distinct preferences regarding their choice of information sources. Health empowerment and digital health literacy were both significantly related to information-seeking behaviors.

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Section: Comparison With Prior Worksupporting

confidence: 59%

Section: Hisb Overallmentioning

confidence: 99%

Predicting and Empowering Health for Generation Z by Comparing Health Information Seeking and Digital Health Literacy: Cross-Sectional Questionnaire Study

Jiao,

Chang,

et al. 2023

J Med Internet Res

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“…However, although previous studies have explored some information problems faced by MFWs, such as information acquisition [34,35], information literacy [36], information inclusion [37] and so on, few of them have specially examined the decision-making in their ISS. To make up for this gap, this study will focus on revealing MFWs’ decision-making in ISS through a cross-context research.…”

Section: Introductionmentioning

confidence: 99%

Social capital or non-human sources? A cross-context study on information source selection of migrant farmer workers

Fang

2021

Journal of Information Science

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Insufficient examination of social factors obscures the reason why non-human information sources are under-utilised by social groups with lower information literacy. This study explores the mechanism of information source selection (ISS) of Chinese migrant farmer workers (MFWs) in different industries by conducting a cross-context analysis. After iterative analyses of multiple cases, a theoretical model of information source selection within an individual’s information world is constructed. It explains why MFWs make more use of social capitals than non-human information sources in information seeking. Besides, the information needs are examined form both the needed information and the need itself. A classification of social capital as human information source is created and the roles that social capitals and non-human information sources play in ISS are identified. This study provides novel theoretical insights into the ‘old’ issue of ISS, and thus has practical implications for public information service providers and MFW-related policy makers.

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“…eHealth literacy is defined as the ability to search, comprehend, and evaluate health information from electronic resources and apply this information to make health decisions ( 31 ). eHealth literacy can influence individuals’ health information-seeking behaviors in a new media environment ( 60 , 61 ) and is one of the core predictors of information technology adoption and continued use behavior ( 62 – 64 ). Previous research indicated that lower levels of eHealth literacy are associated with lower engagement in health information-seeking behaviors ( 61 , 65 ) and higher levels of technological anxiety ( 66 ).…”

Section: Discussionmentioning

confidence: 99%

“…eHealth literacy can influence individuals’ health information-seeking behaviors in a new media environment ( 60 , 61 ) and is one of the core predictors of information technology adoption and continued use behavior ( 62 – 64 ). Previous research indicated that lower levels of eHealth literacy are associated with lower engagement in health information-seeking behaviors ( 61 , 65 ) and higher levels of technological anxiety ( 66 ). On the contrary, individuals with higher eHealth literacy are more adept at obtaining the health information they need through WeChat public accounts, leading to a stronger intention to continue using these accounts.…”

Section: Discussionmentioning

confidence: 99%

Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM

Min,

Li,

et al. 2024

Front. Public Health

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BackgroundWomen’s health WeChat public accounts play a crucial role in enhancing health literacy and fostering the development of healthy behaviors among women by disseminating women’s health knowledge. Improving users’ continuous usage behavior and retention rates for the women’s health WeChat public account is vital for influencing the overall effectiveness of health communication on WeChat.ObjectiveThis study aimed to construct a comprehensive model, delving into the key factors influencing women’s continuance intention of the women’s health public accounts from the perspectives of perceived health threats, individual abilities, and technological perceptions. The goal is to provide valuable insights for enhancing user stickiness and the effectiveness of health communication on WeChat public accounts.MethodAn online survey was conducted among women receiving gynecological care at a certain hospital to gage their willingness for sustained use of the women’s health WeChat public accounts. Through structural equation modeling, the study investigated the influencing factors on women’s sustained intention to use the women’s health WeChat public accounts.ResultsThe study included a total of 853 adult women. Among them, 241 (28.3%) women had followed women’s health official accounts in the past but do not currently follow them, 240 (28.1%) women had followed women’s health official accounts in the past and are still following them, and 372 (43.6%) women had never followed women’s health official accounts. Currently, 240 women are still browsing women’s health public accounts, 52 of whom read women’s health public accounts every day, and most of them read women’s health public accounts for 10–20 min at a time (100, 11.7%). The results of the structural equation model revealed that performance expectancy, social influence, hedonic motivation, habit, and e-health literacy had significantly positive effects on women’s sustained intention to use public accounts (performance expectancy: β = 0.341, p < 0.001; social influence: β = 0.087, p = 0.047; hedonic motivation: β = 0.119, p = 0.048; habit: β = 0.102, p < 0.001; e-health literacy: β = 0.158, p < 0.001). E-health literacy and self-efficacy indirectly influence sustained intention by affecting performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit. The effect sizes of e-health literacy on performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit were 0.244 (p < 0.001), 0.316 (p < 0.001), 0.188 (p < 0.001), 0.226(p < 0.001), 0.154 (p < 0.001), and 0.073 (p = 0.046). The effect sizes of self-efficacy on performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit were 0.502 (p < 0.001), 0.559 (p < 0.001), 0.454 (p < 0.001), 0.662 (p < 0.001), 0.707 (p < 0.001), and 0.682 (p < 0.001). Additionally, perceived severity and perceived susceptibility indirectly affected sustained intention by influencing performance expectancy and social influence. The effect sizes of perceived severity on performance expectancy and social influence were 0.223 (p < 0.001) and 0.146 (p < 0.001). The effect size of perceived susceptibility to social influence was 0.069 (p = 0.042).ConclusionUsers’ e-health literacy, self-efficacy, perception of disease threat, and users’ technological perceptions of the WeChat public accounts are critical factors influencing women’s continuance intention of using the WeChat public accounts. Therefore, for female users, attention should be given to improving user experience and enhancing the professionalism and credibility of health information in public account design and promotion. Simultaneously, efforts should be made to strengthen users’ health awareness and cultivate e-health literacy, ultimately promoting sustained attention and usage behavior among women toward health-focused public accounts.

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Behavior patterns and influencing factors: Health information acquisition behavior of Chinese senior adults on WeChat

Cited by 5 publications

References 36 publications

Predicting and Empowering Health for Generation Z by Comparing Health Information Seeking and Digital Health Literacy: Cross-Sectional Questionnaire Study

Predicting and Empowering Health for Generation Z by Comparing Health Information Seeking and Digital Health Literacy: Cross-Sectional Questionnaire Study

Social capital or non-human sources? A cross-context study on information source selection of migrant farmer workers

Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM

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