Sharing health information across online platforms: A systematic review

Peer-to-peer sharing in public health interventions: strategies when people share health-related personal information on social media

PURPOSE

As sharing on social media has become an integrated part of everyday life, health and public health actors have started to show interest in the potential of people's peer-to-peer sharing of health-related personal information (HRI) for health interventions. In this article we focus on how people make sense of sharing HRI on social media.

METHODS

Twenty-two people between the ages 40 and 60 who had taken part in a regional health intervention were interviewed. Using theories about social media sharing, we explore their understandings and negotiations about whether, how much, and how to share HRI and discuss the results in relation to peer-to-peer sharing as a strategy in interventions.

RESULTS

We identified three aspects that were perceived as particularly risky: loss of control, effects on identity, and affecting others negatively, along with strategies that were used to manage risks in practice: avoiding sharing, allocating, and embedding HRI.

CONCLUSIONS

By allocating and embedding HRI, people can unlock motivating affordances for health work. However, strategies to manage risks can also be counterproductive. For actors to provide equality in health promotion, initiatives that include social media sharing need to be mindful of the sometimes counterproductive effects this may have on people's engagement.

Continuous adoption of online healthcare platforms: an extension to the expectation confirmation model and network externalities

BACKGROUND

Online healthcare platforms (OHPs) promote the accessibility of health services while integrating online and offline service delivery. Continuous adoption of these platforms can reduce the information asymmetry between patients and healthcare providers. However, existing study has rarely focused on how the network externalities of these platforms influence patients' continuous adoption. Expectation Confirmation Model (ECM) explains the continuous behavior after initial adoption and reveal the factors influencing satisfaction and continuous adoption intention. Few studies have integrated network externalities with the ECM to understand patients' continuous adoption of OHPs.

OBJECTIVE

This study aims to explore what factors affect the continuous adoption of OHPs based on an extension to the ECM and network externalities. We propose a comprehensive model for the continuous adoption of OHPs by patients with chronic diseases. We extend the conceptual framework by incorporating constructs related to perceived value, habits, and switching costs.

METHODS

This study utilized a web-based survey to collect data from participants in China. We selected a sample of individuals who had experience with OHPs using a random sampling method. This method ensured that participants was randomly chosen from a pool of patients without any regional bias. A total of 568 questionnaires were collected and 518 valid questionnaires were obtained. Structural equation modeling was applied to assess the relationships among the constructs. Hierarchical regression analysis was utilized to examine the moderating effects, while the mediating effects were investigated using the bootstrapping approach.

RESULTS

Direct network externality had significant positive impacts on the confirmation (β = 0.232, p < 0.001) and perceived value (β = 0.167, p < 0.010). Cross network externality had significant positive impacts on confirmation (β = 0.307, p < 0.001) and perceived value (β = 0.120, p < 0.05). Indirect network externality had significant positive impacts on confirmation (β = 0.169, p < 0.010) and perceived value (β = 0.270, p < 0.001). Confirmation had a significant positive impact on perceived value (β = 0.205, p < 0.001) and satisfaction (β = 0.508, p < 0.001). In addition, satisfaction had a significant positive impact on continuous adoption intention (β = 0.579, p < 0.001). Continuous adoption intention had a significant positive impact on continuous adoption behavior (β = 0.547, p < 0.001). Confirmation and perceived value significantly mediate the relationship between network externalities and satisfaction. Moreover, both confirmation and perceived value enhance continuous adoption intention by positively influencing satisfaction, which serves as a mediator. Additionally, confirmation directly influences satisfaction through the mediating role of perceived value. Habits and switching costs positively moderate the relationship between continuous adoption intention and behavior.

CONCLUSIONS

This study contributes by expanding the incorporation of network externalities into the ECM. Results enrich the existing literature on the continuous adoption of professional online platforms.

Study on health education methods based on rural residents' infectious disease-specific health literacy in Shandong, China

Adequate infectious disease-specific health literacy (IDSHL) is of benefit to residents in dealing with infectious diseases. This study aimed to investigate the methods by which residents acquire knowledge about infectious disease prevention and control (IDPC knowledge) so as to find effective health education methods used to improve residents' IDSHL level. In 2022, a cross-sectional study was conducted in Shandong Province, China. Participants were recruited from rural areas by multistage sampling. The IDPC knowledge cognitive questionnaire, as a reliable and valid tool, was applied to data collection and to investigate the participants' IDPC knowledge. Chi-square analysis was utilized to analyze the differences in possession level of IDSHL between different subgroups. The relationship between demographic factors and methods to acquire IDPC knowledge was also examined by chi-square analysis. The possession rate of adequate IDSHL among the total 2283 participants was 31.80%. There was a significant association between IDSHL level and socio-demographic factors, including age (P < .001), sex (P = .02), education (P < .001), occupation (P < .001), annual family income (P < .001), whether to use smartphones (P < .001), whether to browse WeChat on smartphones (P < .001), and whether to browse apps on smartphones except WeChat (P < .001). Univariate analysis showed that whether to adopt specific methods, including television (P = .02), WeChat on smartphones (P < .001), propaganda of infectious disease prevention and control (P < .001), and doctor's advice (P < .001) to acquire IDPC knowledge had significant associations with IDSHL level. Age (P < .001), education (P < .05), occupation (P < .05), and annual family income (P < .01) were associated with methods to acquire IDPC knowledge. The rural residents' adequate IDSHL in Shandong Province, China, was not optimistic. The combination of traditional methods and Internet publicity platforms should take greater responsibility for IDSHL health education among rural populations.

The association between social support and prosocial behavior: A three-level meta-analysis

Numerous studies have examined the relationship between social support and prosocial behavior and have concluded that social support is an important factor in generating prosocial behavior. However, different studies have produced different conclusions, and the moderating effect on the relationship is not entirely clear. The current study uses a three-level meta-analysis method to clarify the relationship between social support and prosocial behavior, and explores the moderating variables that affect the relationship between the two variables. Through a systematic literature search, a total of 92 studies, 418 effect sizes, and 74,378 participants were obtained. The main effects test found a significant positive correlation between social support and prosocial behavior. Tests of the moderating effects indicated that the relationship between social support and prosocial behavior was moderated by year of publication, source of social support, measurement of social support and measurement of prosocial behavior. In summary, social support plays an important role in prosocial behavior, and exploring their relationship is beneficial to families, schools and society in guiding individuals' prosocial behavior.

Communication Strategies to Promote COVID-19 Vaccination Intention: How Effective are Source, Appeal, Framing, and Evidence Type Approaches?

This systematic review analyzed the effectiveness of key persuasive strategies - source, appeal, framing, and evidence (SAFE) - on COVID-19 vaccination intention. Quantitative studies were searched in Web of Science, Scopus, and PubMed following the PRISMA guidelines. From the 61 studies that met inclusion criteria, source and framing are the most commonly applied SAFE strategies. However, source characteristics are a more consistent influence on vaccine intentions than message framing strategies, with expert sources and general practitioners emerging as the key sources contributing to greater vaccine intentions. In addition, a range of mediators and moderators influence the process through which SAFE message strategies impact vaccine intentions. Framing effects, in particular, are moderated by political identity, source characteristics, and vaccine perceptions. Tests of mediating processes highlight how health behavior judgments (e.g. perceived vaccine benefits, risks, trust in vaccination, perceived severity) and message response/perceptions (e.g. counterarguing, perceived similarity/empathy) operate as key intervening factors between SAFE message strategies and vaccine intentions. Overall, when practitioners apply various structural approaches (narrative elements, fear appeals, framing cues) to vaccine promotion campaigns, they should be cognizant of who is providing that appeal. Targeted populations may benefit most from different structural elements if they are integrated with sources that resonate with the audience.

Associations between digital literacy, health literacy, and digital health behaviors among rural residents: evidence from Zhejiang, China

OBJECTIVE

Within the digital society, the limited proficiency in digital health behaviors among rural residents has emerged as a significant factor intensifying health disparities between urban and rural areas. Addressing this issue, enhancing the digital literacy and health literacy of rural residents stands out as a crucial strategy. This study aims to investigate the relationship between digital literacy, health literacy, and the digital health behaviors of rural residents.

METHODS

Initially, we developed measurement instruments aimed at assessing the levels of digital literacy and health literacy among rural residents. Subsequently, leveraging micro survey data, we conducted assessments on the digital literacy and health literacy of 968 residents in five administrative villages in Zhejiang Province, China. Building upon this foundation, we employed Probit and Poisson models to empirically scrutinize the influence of digital literacy, health literacy, and their interaction on the manifestation of digital health behaviors within the rural population. This analysis was conducted from a dual perspective, evaluating the participation of digital health behaviors among rural residents and the diversity to which they participate in such behaviors.

RESULTS

Digital literacy exhibited a notably positive influence on both the participation and diversity of digital health behaviors among rural residents. While health literacy did not emerge as a predictor for the occurrence of digital health behavior, it exerted a substantial positive impact on the diversity of digital health behaviors in the rural population. There were significant interaction effects between digital literacy and health literacy concerning the participation and diversity of digital health behaviors among rural residents. These findings remained robust even after implementing the instrumental variable method to address endogeneity issues. Furthermore, the outcomes of robust analysis and heterogeneity analysis further fortify the steadfastness of the aforementioned conclusions.

CONCLUSION

The findings suggest that policymakers should implement targeted measures aimed at enhancing digital literacy and health literacy among rural residents. This approach is crucial for improving rural residents' access to digital health services, thereby mitigating urban-rural health inequality.

Factors Influencing the Answerability and Popularity of a Health-Related Post in the Question-and-Answer Community: Infodemiology Study of Metafilter

BACKGROUND

The web-based health question-and-answer (Q&A) community has become the primary and handy way for people to access health information and knowledge directly.

OBJECTIVE

The objective of our study is to investigate how content-related, context-related, and user-related variables influence the answerability and popularity of health-related posts based on a user-dynamic, social network, and topic-dynamic semantic network, respectively.

METHODS

Full-scale data on health consultations were acquired from the Metafilter Q&A community. These variables were designed in terms of context, content, and contributors. Negative binomial regression models were used to examine the influence of these variables on the favorite and comment counts of a health-related post.

RESULTS

A total of 18,099 post records were collected from a well-known Q&A community. The findings of this study include the following. Content-related variables have a strong impact on both the answerability and popularity of posts. Notably, sentiment values were positively related to favorite counts and negatively associated with comment counts. User-related variables significantly affected the answerability and popularity of posts. Specifically, participation intensity was positively related to comment count and negatively associated with favorite count. Sociability breadth only had a significant impact on comment count. Context-related variables have a more substantial influence on the popularity of posts than on their answerability. The topic diversity variable exhibits an inverse correlation with the comment count while manifesting a positive correlation with the favorite count. Nevertheless, topic intensity has a significant effect only on favorite count.

CONCLUSIONS

The research results not only reveal the factors influencing the answerability and popularity of health-related posts, which can help them obtain high-quality answers more efficiently, but also provide a theoretical basis for platform operators to enhance user engagement within health Q&A communities.

"In Flow"! Why Do Users Share Fake News about Environmentally Friendly Brands on Social Media?

Social media has triggered an increase in fake news spread about different aspects of modern lives, society, politics, societal changes, etc., and has also affected companies' reputation and brands' trust. Therefore, this paper is aimed at investigating why social media users share fake news about environmentally friendly brands. To examine social media users' behavior towards environmentally friendly brands, a theoretical research model proposed and analyzed using structural equations modeling in SmartPLS on a convenience sample consisting of 922 questionnaires. Data was collected by means of a quantitative-based approach via a survey conducted among social media users from an emerging market. The results show that social media flow has a mediated impact on sharing fake news about environmentally friendly brands on social media. Considering the critical consequences of fake news, the paper argues that understanding the dissemination process of this type of bogus content on social media platforms has important theoretical and managerial implications. Understanding the psychological mechanisms that influence people's behavior in sharing fake news about environmentally friendly brands on social networking sites (SNS) could help in better understanding the factors and the effects of this phenomenon. The originality of this research consists of proposing flow theory from positive psychology to be used as a theoretical framework to explain users' behavior of sharing fake news about environmentally friendly brands on social media.