Online Health Communities Users Research Articles

Paths of knowledge sharing of core and periphery users in online health communities: social support perspective

Paths of knowledge sharing of core and periphery users in online health communities: social support perspective

Information Seeking and Receiving of Older Adults with Diabetes in the Online Health Community: An Information Need Contextualization Perspective

ABSTRACT Online health communities (OHCs) are important online health communication channels for older adults with diabetes to access health information. When seeking health information, they often disclose a variety of contextual information (e.g., socio-economic situations) in their questions. Selective contextual information disclosure is a type of communication strategy for users in OHCs to elicit replies from others. In this study, we adopted text analysis to investigate what contextual information older adults with diabetes disclose to articulate their information needs and used the fixed-effect Poisson model to examine the relationships between different types of contextual information disclosure and informational support receipt. Our analyses were based on a dataset of 4,505 questions and corresponding replies from an online diabetes community. The results showed that cognitive information is the most frequently disclosed contextual information, while older adults tend to disclose demographic information in their questions less. Providing demographic and situational details in questions can enhance informational support receiving, resulting in an increased number of informational supports. However, disclosing cognitive, affective, informational channels, or support information does not significantly affect the informational support receiving. These findings can contribute to extending our existing understanding of information seekers’ communication strategies in OHCs.

The impact of doctors' facial attractiveness on users' choices in online health communities: A stereotype content and social role perspective

This study examines the impact of doctors' facial attractiveness on users' choices in online health communities (OHCs). We conducted a field study using a sample of 14,897 doctors registered on a Chinese OHC. The results indicate a significant negative relationship between the facial attractiveness of doctors and the number of visits to their homepage by users. However, this relationship only holds true for male surgeons and female internal medicine doctors, not for female surgeons or male internal medicine doctors. These findings suggest the possible presence of gender-specialty bias in the influence of facial attractiveness on patients' decision-making. To further investigate how facial attractiveness influences users' inclination to choose a particular doctor, we develop our research model drawing upon the stereotype content and social role perspective. Through a laboratory experiment, we found that OHC users' perceptions of doctors' warmth and competence act as mediating factors in the relationship between facial attractiveness and user choice. Additionally, this relationship is influenced by stereotypical gender-specialty fit.

Patient influencer: the impact of homophily on value co-creation behaviour in online health communities

ABSTRACT The world has witnessed a rapid rise of online health communities (OHCs) where patients can create a powerful network of support and resources to make a meaningful difference in people’s health lives. Despite this rapid rise, healthcare authorities and organisations are under enormous pressure to create a sustainable environment for OHCs. Prior studies revealed that encouraging patient value co-creation behaviour (VCB) is substantially beneficial for successful OHCs; however, what factors influence these patient behaviours to co-create value is still unknown. To fill this gap, this study uses the service-dominant logic perspective of value co-creation theory and discloses how homophily between patient influencers and patients in OHCs effect VCB. The data was collected through a self-administered survey from 422 patients who are users of OHC in China and was analysed via partial least squares structural equation modelling and fuzzy set qualitative comparative analysis (fsQCA). The results revealed that homophily positively influences VCBs, i.e. participation behaviour (PB) and citizenship behaviour (CB). A parasocial relationship only moderates the relations between homophily and (PB), whereas the influencer ethical interaction capability significantly moderates the relationship of both homophily with patient PB and CB. Furthermore, the fsQCA findings signify the robustness of the study model.

Getting better? Examining the effects of social support in OHCs on users’ emotional improvement

Online health communities (OHCs) have emerged as dynamic platforms facilitating patient communication and knowledge exchange on health matters. While extant research underscores the emotional benefits accrued from engagement in OHCs, the precise quantification of how social support within these communities influences users’ emotional states remains an intricate challenge. In light of this, the primary objective of this study is to explore the influential mechanisms underlying the received social support on the emotional improvement of users in OHCs, while concurrently investigating the potential moderating effects posed by individuals’ health conditions and levels of community involvement. Leveraging authentic user interaction data harvested from an online diabetes community, this study employed deep learning models and natural language processing methods to gauge the magnitude of received social support and the variation of users’ emotional states. Subsequently, a multiple linear regression model was formulated to evaluate the effects of both informational and emotional support on users' emotional improvement. Empirical results reaffirm the pivotal role of both informational and emotional support in enhancing users’ emotional states, with emotional support emerging as particularly influential. Notably, prolonged disease duration amplifies the beneficent impact of social support on emotional enhancement. The research outcomes bear implications for ameliorating negative emotional experiences and effectively managing chronic diseases.

Forecasting User Interests Through Topic Tag Predictions in Online Health Communities.

The increasing reliance on online communities for healthcare information by patients and caregivers has led to the increase in the spread of misinformation, or subjective, anecdotal and inaccurate or non-specific recommendations, which, if acted on, could cause serious harm to the patients. Hence, there is an urgent need to connect users with accurate and tailored health information in a timely manner to prevent such harm. This article proposes an innovative approach to suggesting reliable information to participants in online communities as they move through different stages in their disease or treatment. We hypothesize that patients with similar histories of disease progression or course of treatment would have similar information needs at comparable stages. Specifically, we pose the problem of predicting topic tags or keywords that describe the future information needs of users based on their profiles, traces of their online interactions within the community (past posts, replies) and the profiles and traces of online interactions of other users with similar profiles and similar traces of past interaction with the target users. The result is a variant of the collaborative information filtering or recommendation system tailored to the needs of users of online health communities. We report results of our experiments on two unique datasets from two different social media platforms which demonstrates the superiority of the proposed approach over the state of the art baselines with respect to accurate and timely prediction of topic tags (and hence information sources of interest).

Configuration Path Study of Influencing Factors on Health Information-Sharing Behavior among Users of Online Health Communities: Based on SEM and fsQCA Methods.

This study examines the determinants that drive the behavior of sharing health information within online health communities. Leveraging the Theory of Planned Behavior, the Technology Acceptance Model, and the "Knowledge-Attitude-Practice" theory, a comprehensive model elucidating the key elements that sway the health information-sharing behavior among users of online health communities is designed. This model is validated through Structural Equation Modeling (SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). Findings derived from the SEM suggest that perceived ease of use, perceived usefulness, perceived trust, and perceived behavioral control exert a significant positive impact on attitudes towards health information sharing, the intention to share health information, and the actual health information-sharing behavior. The fsQCA unfolds two unique configuration path models that lead to the emergence of health information-sharing behavior: one predicated on perceived trust and sharing intention, and the other on perceived usefulness, behavioral control, and sharing attitude. This research provides invaluable insights, fostering a deeper comprehension of the dynamics involved in health information sharing within online communities, thereby directing the design of more effective health platforms to augment user engagement and enable informed health decisions.

Fear appeals and coping appeals for health product promotion: Impulsive purchasing or psychological distancing?

The prevalence of online health communities (OHCs) motivates health product companies to manipulate persuasion-based marketing strategies, including fear appeals and coping appeals, to promote health products. However, whether such a practice is effective remains unclear. Respondents may either impulsively purchase the recommended health products or simply distance themselves psychologically from the information. Building on protection motivation theory (PMT), this study uncovers the mechanisms behind these two coping responses to persuasive messages, namely, the impulsive purchasing and psychological distancing of OHC users. Correspondingly, we evaluated 366 valid questionnaires, and the results reveal that (1) when encountering fear appeals, perceived health threat can evoke cyberchondria, leading to psychological distancing; and (2) when encountering coping appeals, perceived response efficacy leads to product affection, fostering impulsive purchasing. This study provides new insights into the effects of persuasive messages for health product promotion in social commerce. Marketers should design appropriate persuasive messages to foster impulsive purchasing by generating individuals’ product affection and avoiding cyberchondria.

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

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). 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. 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. 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.

The quality of informational social support in online health communities: A content analysis of cancer-related discussions.

Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this study is to conceptualize the Quality of Informational Social Support (QISS) and develop and test a measure of QISS for content analysis. A further aim is to investigate the level of QISS in cancer-related messages in the largest OHC in Slovenia and examine the differences among various types of discussion forums, namely, online consultation forums, online support group forums, and socializing forums. A multidimensional measurement instrument was developed, which included 20 items in a coding scheme for a content analysis of cancer-related messages. On a set of almost three million posts published between 2015 and 2019, a machine-learning algorithm was used to detect cancer-related discussions in the OHC. We then identified the messages providing informational social support, and through quantitative content analysis, three experts coded a random sample of 403 cancer-related messages for the QISS. The results demonstrate a good level of interrater reliability and agreement for a QISS scale with six dimensions, each demonstrating good internal consistency. The results reveal large differences among the social support, socializing, and consultation forums, with the latter recording significantly higher quality in terms of accuracy (M = 4.48, P < .001), trustworthiness (M = 4.65, P < .001), relevance (M = 3.59, P < .001), and justification (M = 3.81, P = .05) in messages providing informational social support regarding cancer-related issues. This study provides the research field with a valid tool to further investigate the factors and consequences of varying quality of information exchanged in supportive communication. From a practical perspective, OHCs should dedicate more resources and develop mechanisms for the professional moderation of health-related topics in socializing forums and thereby suppress the publication and dissemination of low-quality information among OHC users and visitors.

Impact of Introversion-Extraversion Personality Traits on Knowledge-Sharing Intention in Online Health Communities: A Multi-Group Analysis

This paper investigates the influence of introversion-extraversion personality traits on the knowledge-sharing intention of online health communities (OHCs) using personality trait theory and social capital theory. This study investigates two types of users in OHCs—doctors and patients—and compares and analyses the knowledge-sharing paths of these two types of users. The results show that extraversion personality, interaction, and reciprocity positively influence the physicians’ and patients’ knowledge-sharing intention; for both types of users, interaction partially mediates between extraversion personality and knowledge-sharing intention, and reciprocity partially mediates between interaction and knowledge-sharing intention. Comparative analyses show that the physicians’ introversion-extraversion personality traits have stronger positive effects on interaction, and interaction has stronger positive effects on trust and reciprocity than patients, the physicians’ trust and reciprocity have stronger positive effects on knowledge-sharing intention than patients, and the physicians’ introversion personality traits have stronger positive effects on knowledge-sharing intentions than patients. This study enriches the theory of user knowledge-sharing in OHCs while advancing the managers’ understanding of what motivates users’ knowledge-sharing intention.

Understanding knowledge sharing in online health communities: A social cognitive theory perspective

With the growing conflict between increased health awareness and the relative shortage of offline medical resources, online health communities (OHCs) have become an important resource for people seeking help with health difficulties. However, patients joining OHCs prefer to learn about health knowledge rather than to share. As a result, the supply and demand of health information in OHC are out of balance. We collected data from users of four major Chinese OHCs using a questionnaire survey to examine the knowledge sharing intention of OHCs users. A total of 324 cases were included in the final sample. We use structural equation modeling approach to test the proposed hypotheses. The results show that user environmental factors including informational support and emotional support affect trust toward members. Platform environmental factors including information quality and service quality affect trust toward community. Both trust toward members and trust toward community positively influence community commitment. Community commitment and trust toward members positively influence users’ attitudes toward knowledge sharing. Both community commitment and attitude toward knowledge sharing have been proven to be strong predictors of knowledge sharing intentions.

The Impact of Data Vulnerability in Online Health Communities: An Institutional Assurance Perspective.

In the last few years, online health communities (OHCs) have experienced rapid development due to advances in technology and the COVID-19 pandemic. However, the sensitive nature of medical information has also raised concerns from users about their privacy and reduced their intention to use OHCs. Considering the critical role of data privacy, this study explored the effect of data vulnerability on OHC users. Using online survey data collected from 438 OHC users in China, we found that data vulnerability significantly reduced psychological comfort, while the latter enhanced continuance intention. We also found that psychological comfort negatively mediated the impact of data vulnerability on continuance intention. Institutional assurance approaches, namely privacy policy, privacy protection technology, industry self-regulation, and government legislation, were also found to mitigate the negative impact of data vulnerability on psychological comfort. This study not only contributes to the data privacy, psychological comfort, and institutional assurance literature but also offers suggestions for OHC stakeholders.

Understanding Online Health Community Users' Payment Intention

Users often lack the motivation to pay for health information and services in online health communities (OHC). This may undermine the sustainable development of OHC. Integrating both perspectives of perceived value and trust, this research identified the factors affecting OHC users’ payment intention. The results indicated that payment intention is influenced by both functional value and trust. Functional value includes price utility and information quality, whereas trust includes trust in doctors and trust in community. We did not find the effect of emotional value and social value on payment intention. The results imply that OHC need to create a trustworthy climate and offer utilitarian value to users in order to facilitate their payment intention.

Understand the Impact of Technology Feature in Online Health Communities: Why the Representation of Information Matters

With the increasing prevalence of chronic diseases and their negative socio-economic impact, online health communities (OHCs) where patients can seek informational and emotional support play an essential role in mitigating the impact. However, chronically ill patients encounter a big issue when using OHCs for self-management and health promotion—poor information quality. Grounded on the information quality framework and information-motivation-behavioral skills model, this article investigates how technology feature, specifically the information representation feature, impacts OHC users' health knowledge acquisition and self-efficacy. The findings show that structured health information can positively impact health knowledge acquisition via OHC users' perceptions of information completeness and ease of understanding. A positive impact of health knowledge acquisition on self-efficacy is also found. The findings provide insights into supporting OHCs users through effective utilization of different information representation features.

Personalized content recommendation in online health communities

PurposeRecommending suitable content for users of online health communities (OHCs) is critical for overcoming information overload problem and facilitate medical decision making, but remains not fully investigated. This study aims to provide a content recommendation approach to automatically match valuable health-related information for OHC members.Design/methodology/approachA framework of health-related content recommendation was proposed by leveraging rich social information in online communities. The authors constructed user influence relationship (UIR) utilizing users' interaction records, user profiles and user-generated content. The initial user rating matrix and the user post matching matrix were then created by analyzing text content of posts. Finally, the user rating matrix and the recommended content were generated for community members. Datasets were collected from an OHC to evaluate the effectiveness of the proposed approach.FindingsThe experimental results revealed that the proposed method statistically outperformed baseline models in content recommendation for users of OHCs.Research limitations/implicationsThe incorporation of social information can significantly enhance the performance of content recommendation in OHCs. The user post matching degree based on text analysis can improve the effectiveness of recommendation.Practical implicationsThis study potentially contributes to the social support exchange and medical decision making of community members and the sustainable prosperity of OHCs.Originality/valueThis study proposes a novel social content recommendation method for online health consumers based on UIRs by leveraging social information in OHCs. The results indicate the significance of social information in content recommendation of healthcare social media.

Understanding online health community users' information adoption intention: an elaboration likelihood model perspective

PurposeThe purpose of this research is to draw on the elaboration likelihood model (ELM) to examine users' information adoption intention in online health communities (OHC).Design/methodology/approachThe authors collected 350 valid responses using a survey and conducted the moderated regression analysis to examine the research model.FindingsThe results indicated that users' information adoption intention is influenced by both central cues (argument quality) and peripheral cues (source credibility and emotional support). In addition, self-efficacy moderates the effect of both central cues and peripheral cues on information adoption intention.Originality/valuePrevious research has focused on the effect of individual motivations such as reciprocity and benefits on user behavior, and has seldom disclosed the influencing process of external factors on OHC users' behavioral decision. This research tries to fill the gap by adopting ELM to uncover the mechanism underlying OHC users' information adoption.

Examining online health community users’ sharing behaviour: A social influence perspective

Online health communities (OHC) provide a platform for users to exchange health-related information and seek emotional support. However, users often lack the intention to share their knowledge, which may lead to the failure of OHC. Drawing on the social influence theory, this research examined OHC users’ sharing behaviour. The results indicated that users’ sharing intention is influenced by three social influence factors, which include subjective norm, social identity and group norm. In addition, social support and privacy concern have effects on these three social influence factors. The results imply that OHC need to leverage social influence in order to facilitate users’ sharing behaviour.

Exploring the Relationship Between Users' Psychological Contracts and Their Knowledge Contribution in Online Health Communities.

The knowledge contribution of members is essential and beneficial to both the business and users of online health communities (OHCs). This study explores and tests the effects of OHC users' psychological contracts on their community identification and knowledge-sharing behavior. A total of 362 valid responses from several well-known OHCs in China are used in the data analysis. The results of the path analysis with structural equation modeling show that users' transactional psychological contracts have a negative effect on their knowledge contribution both directly and indirectly by weakening their community identification. In contrast, users' relational psychological contracts can lead to increased active knowledge contributions both directly and indirectly by enhancing their community identification. Knowledge sharing self-efficacy can strengthen the relationship between relational psychological contracts and knowledge contributions, and the relationship between community identification and knowledge contributions. However, it has no significant impact on the path from transactional psychological contracts to knowledge contribution. The implications and direction of future works are presented on the basis of the results of the empirical analysis.

Engagement in online health communities: Channel expansion and social exchanges

This paper contributes to the discussion on patient engagement in online health communities (OHCs) by integrating channel expansion and social exchange theories. Using survey data from 348 users of OHC, we examine the impacts of perceived channel richness, social support, and willingness to exchange information on OHC engagement. Results show that the perceived channel richness positively influences OHC engagement. The effect of patients’ willingness to share and seek information on engagement is moderated by health status. Finally, engagement in OHCs enhances self-care efficacy and perceived health outcomes. We propose several theoretical implications for researchers and practical contributions for OHC administrators.