Abstract
Online health communities (OHCs) represent a popular and valuable resource for those seeking health information, support, or advice. They have the potential to reduce dependency on traditional health information channels, increase health literacy and empower a broader range of individuals in relation to their health management decisions. Successful communities are characterized by high levels of trust in user-generated contributions, which is reflected in increased engagement and expressed through knowledge adoption and knowledge contribution. However, research shows that the majority of OHCs are composed of passive participants who do not contribute via posts, thereby threatening the sustainability of many communities and their potential for empowerment. Despite this fact, the relationship between trust and engagement, specifically the trust antecedents that influence engagement in the OHC community context has not been adequately explained in past research. In this study, we leverage social capital behavior and social exchange theory frameworks in order to provide a more granular trust-based elucidation of the factors that influence individuals’ engagement in OHCs. We collected data from 410 Brazilian participants of Facebook OHCs and tested the research model using partial least squares. The results confirm two new constructs—online community responsiveness and community support—as trust antecedents that influence engagement in OHCs, resulting in knowledge adoption and knowledge contribution responses. These findings contribute to the trust and engagement literatures and to social media research knowledge. From a practitioner perspective, the study findings can serve as an important guide for moderators and managers seeking to develop trusted and impactful OHCs.
Recommended Citation
Connolly, Regina; Sanchez, Otavio P.; Compeau, Deborah; and Tacco, Fabiana Martins de Souza
(2023)
"Understanding Engagement in Online Health Communities: A Trust-Based Perspective,"
Journal of the Association for Information Systems, 24(2), 345-378.
DOI: 10.17705/1jais.00785
Available at:
https://aisel.aisnet.org/jais/vol24/iss2/8
DOI
10.17705/1jais.00785
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