How COVID-19 Affects the Willingness of the Elderly to Continue to Use the Online Health Community: A Longitudinal Survey

In response to the COVID-19 outbreak, the governments of different countries adopted restrictions, such as locking down cities and restricting travel and social contact. Online health communities (OHCs) with specialized physicians have become an important way for the elderly to access health information and social support, which has expanded their use since the outbreak. This paper examines the factors influencing elderly people's behavior in terms of the continuous use of OHCs from a social support perspective to understand the impact of public health emergencies. Research collected data from March to April 2019, February 2020, and August 2021 in China. A total of 189 samples were collected and analyzed by using SmartPLS. The results show that (1) social support to the elderly during different stages has different influences on their sense of community and (2) the influence of the sense of community on the intention to continuously use OHCs also seems to change over time. The results of this study provide important implications for research and practice related to both OHCs and COVID-19. © 2022 IGI Global. All rights reserved.

Factors Affecting Users' Continuous Usage in Online Health Communities: An Integrated Framework of SCT and TPB.

BACKGROUND: Online health communities (OHCs) provide a new channel for users to obtain more health-related information and support, playing an important role in alleviating hospital congestion and uneven medical resource distribution, especially during the COVID-19 pandemic in China. An in-depth study of users' continuous usage is of great value for the long-term development of OHCs. OBJECTIVE: The purpose of this study is to explore the factors that influence users' continuous usage in online health communities based on the theory of planned behavior (TPB) and social cognitive theory (SCT). METHODS: Data from 480 users with experience in online health communities were collected through a questionnaire survey, and structural equations were applied to verify the model hypotheses empirically. RESULTS: Self-efficacy and controllability have significant effects on users' continuous intention; attitude has a significant relationship with continuous intention; social norms have a positive effect on continuous intention. Moreover, the relationship between continuous intention and behavior is positive. Self-efficacy and outcome expectations have significant positive associations with continuous usage. Finally, system quality, information quality, and social interaction ties have significant and positive relationships to continuous usage. CONCLUSION: To improve the level of user's continuous usage, online health service providers can improve the quality of the community by organizing the website's page layout, navigation menus, and site elements to ensure users quickly search and find what they want meanwhile try to change people's cognition gradually, in addition, decision and policymakers should provide more favorable policies to stimulate and help provider in building and managing strategic plans for sustaining a thriving online community. A supportive climate in society through public service advertisements and others for the sake of OHCs is necessary. LIMITATIONS: (1) This study collected data through a cross-sectional survey. Thus, it lacked the process of capturing the changes in participants' attitudes toward all variables. (2) The environmental factors in SCT theory need to be more comprehensive, containing online factors without offline factors. (3) The dates were obtained from China, which neglects the different cultural content.

How COVID-19 Affects the Willingness of the Elderly to Continue to Use the Online Health Community: A Longitudinal Survey

In response to the COVID-19 outbreak, the governments of different countries adopted, such as locking down cities and restricting travel and social contact. Online health communities (OHCs) with specialized physicians have become an important way for the elderly to access health information and social support, which has expanded their use since the outbreak. This paper examines the factors influencing elderly people's behavior in terms of the continuous use of OHCs from a social support perspective, to understand the impact of public health emergencies. Research collected data from March to April 2019, February 2020, and August 2021, in China. A total of 189 samples were collected and analyzed by using SmartPLS. The results show that (1) social support to the elderly during different stages has different influences on their sense of community and (2) the influence of the sense of community on the intention to continuously use OHCs also seems to change over time. The results of this study provide important implications for research and practice related to both OHCs and COVID-19.

How information processing and risk/benefit perception affect COVID-19 vaccination intention of users in online health communities.

Objective: To investigate the relationship among information processing, risk/benefit perception and the COVID-19 vaccination intention of OHCs users with the heuristic-systematic model (HSM). Methods: This study conducted a cross-sectional questionnaire via an online survey among Chinese adults. A structural equation model (SEM) was used to examine the research hypotheses. Results: Systematic information processing positively influenced benefit perception, and heuristic information processing positively influenced risk perception. Benefit perception had a significant positive effect on users' vaccination intention. Risk perception had a negative impact on vaccination intention. Findings revealed that differences in information processing methods affect users' perceptions of risk and benefit, which decide their vaccination intention. Conclusion: Online health communities can provide more systematic cues and users should process information systematically to increase their perceived benefits, consequently increase their willingness to receive COVID-19 vaccine.

Development and implementation of an online community as a strategy for mixed methods research during a pandemic.

Conducting mixed methods research is critical for healthcare researchers to understand attitudes, behaviors, and experiences on health-related topics, such as vaccine acceptance. As the COVID-19 pandemic has made it difficult to employ traditional, face-to-face qualitative methodologies, this paper describes the use of a virtual platform to conduct person-centered research. To overcome these challenges and better understand the attitudes and behaviors of vaccine-eligible individuals in the United States, an online health community called the Virtual Engagement Research Community (VERC) was designed and implemented. Using the Health Belief Model as a framework, the VERC employed a mixed methods approach to elicit insights, which included discussion topics, rapid polls, and surveys. Throughout the initial enrollment period of April-October 2021, continuous improvement efforts were made to bolster recruitment and member engagement. This agile research strategy was successful in utilizing mixed methods to capture community sentiments regarding vaccines. While this community focused on vaccination, the methodology holds promise for other areas of health research such as obesity, HIV, mental health disorders, and diabetes.

The COVID-19 pandemic has made it difficult to conduct research in person, but qualitative and quantitative data remain critical for developing research design. To gather and understand vaccine perceptions, opinions, and behaviors in a real time manner, The Virtual Engagement Research Community (VERC) was launched. As of October 2021, the VERC had 72 members who had the opportunity to participate in research events such as surveys, polls, discussion topics, and moderated chats in a private, invitation-only virtual community. The online format offered researchers the opportunity to adapt the types and frequency of engagements, fine-tune the research questions based on community responses and current events, and adjust the analysis and reporting methodology as needed to increase participation and maximize the value of the VERC. The success of the VERC and the lessons learned support the use of online communities to enhance mixed methods research as a valuable strategy for other health researchers.

How COVID-19 Affects the Willingness of the Elderly to Continue to Use the Online Health Community: A Longitudinal Survey

In response to the COVID-19 outbreak, the governments of different countries adopted, such as locking down cities and restricting travel and social contact. Online health communities (OHCs) with specialized physicians have become an important way for the elderly to access health information and social support, which has expanded their use since the outbreak. This paper examines the factors influencing elderly people’s behavior in terms of the continuous use of OHCs from a social support perspective, to understand the impact of public health emergencies. Research collected data from March to April 2019, February 2020, and August 2021, in China. A total of 189 samples were collected and analyzed by using SmartPLS. The results show that (1) social support to the elderly during different stages has different influences on their sense of community and (2) the influence of the sense of community on the intention to continuously use OHCs also seems to change over time. The results of this study provide important implications for research and practice related to both OHCs and COVID-19.

Examining the Impact of COVID-19 on People With Dementia From the Perspective of Family and Friends: Thematic Analysis of Tweets.

BACKGROUND: The COVID-19 pandemic is taking a serious toll on people with dementia. Given the rapidly evolving COVID-19 context, policymakers and practitioners require timely, evidence-informed research to address the changing needs and challenges of people with dementia and their family care partners. OBJECTIVE: Using Twitter data, the objective of this study was to examine the COVID-19 impact on people with dementia from the perspective of their family members and friends. METHODS: Using the Twint application in Python, we collected 6243 relevant tweets over a 15-month time frame. The tweets were divided among 11 coders and analyzed using a 6-step thematic analysis process. RESULTS: Based on our analysis, 3 main themes were identified: (1) frustration and structural inequities (eg, denied dignity and inadequate supports), (2) despair due to loss (eg, isolation, decline, and death), and (3) resiliency, survival, and hope for the future. CONCLUSIONS: As the COVID-19 pandemic persists and new variants emerge, people with dementia and their family care partners are facing complex challenges that require timely interventions. More specifically, tackling COVID-19 challenges requires revisiting pandemic policies and protocols to ensure equitable access to health and support services, recognizing the essential role of family care partners, and providing financial assistance and resources to help support people with dementia in the pandemic. Revaluating COVID-19 policies is critical to mitigating the pandemic's impact on people with dementia and their family care partners.

User Behaviors and User-Generated Content in Chinese Online Health Communities: Comparative Study.

BACKGROUND: Online health communities (OHCs) have increasingly gained traction with patients, caregivers, and supporters globally. Chinese OHCs are no exception. However, user-generated content (UGC) and the associated user behaviors in Chinese OHCs are largely underexplored and rarely analyzed systematically, forfeiting valuable opportunities for optimizing treatment design and care delivery with insights gained from OHCs. OBJECTIVE: This study aimed to reveal both the shared and distinct characteristics of 2 popular OHCs in China by systematically and comprehensively analyzing their UGC and the associated user behaviors. METHODS: We concentrated on studying the lung cancer forum (LCF) and breast cancer forum (BCF) on Mijian, and the diabetes consultation forum (DCF) on Sweet Home, because of the importance of the 3 diseases among Chinese patients and their prevalence on Chinese OHCs in general. Our analysis explored the key user activities, small-world effect, and scale-free characteristics of each social network. We examined the UGC of these forums comprehensively and adopted the weighted knowledge network technique to discover salient topics and latent relations among these topics on each forum. Finally, we discussed the public health implications of our analysis findings. RESULTS: Our analysis showed that the number of reads per thread on each forum followed gamma distribution (HL=0, HB=0, and HD=0); the number of replies on each forum followed exponential distribution (adjusted RL2=0.946, adjusted RB2=0.958, and adjusted RD2=0.971); and the number of threads a user is involved with (adjusted RL2=0.978, adjusted RB2=0.964, and adjusted RD2=0.970), the number of followers of a user (adjusted RL2=0.989, adjusted RB2=0.962, and adjusted RD2=0.990), and a user's degrees (adjusted RL2=0.997, adjusted RB2=0.994, and adjusted RD2=0.968) all followed power-law distribution. The study further revealed that users are generally more active during weekdays, as commonly witnessed in all 3 forums. In particular, the LCF and DCF exhibited high temporal similarity (ρ=0.927; P<.001) in terms of the relative thread posting frequencies during each hour of the day. Besides, the study showed that all 3 forums exhibited the small-world effect (mean σL=517.15, mean σB=275.23, and mean σD=525.18) and scale-free characteristics, while the global clustering coefficients were lower than those of counterpart international OHCs. The study also discovered several hot topics commonly shared among the 3 disease forums, such as disease treatment, disease examination, and diagnosis. In particular, the study found that after the outbreak of COVID-19, users on the LCF and BCF were much more likely to bring up COVID-19-related issues while discussing their medical issues. CONCLUSIONS: UGC and related online user behaviors in Chinese OHCs can be leveraged as important sources of information to gain insights regarding individual and population health conditions. Effective and timely mining and utilization of such content can continuously provide valuable firsthand clues for enhancing the situational awareness of health providers and policymakers.