Communicating personal health information in virtual health communities: An integration of privacy calculus model and affective commitment

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Abstract

Health consumers such as patients and caregivers often join virtual health communities (VHCs) to seek and provide health-related information and emotional support. To do so, they converse with other individuals in platforms such as public discussion boards and blogs. During these online conversations, people may communicate their personal health information (PHI) to others. A potential driver for this form of revealing PHI is the immediate positive outcomes that it can provide for contributors and the community. PHI disclosure, however, can entail privacy risks and concerns for community members, which may ultimately hamper their participation in those communities. Moreover, one’s emotional attachment to a VHC (namely, affective commitment) may influence one’s PHI sharing behaviors in that community. Thus, to understand how various factors impact communicating PHI in public VHC discussions, we drew on the privacy calculus model and the notion of affective commitment, developed a theoretical model, and empirically tested the model. To do so, we administered a survey to individuals from three different populations including students, faculty, and staff at a large university and visitors to clinics. We performed a set of hierarchical moderated multiple regressions on the dataset. The results revealed that privacy concerns along with expected personal and community-related outcomes of communicating PHI affected willingness to communicate PHI in public VHC discussions. The results, however, refuted the hypothesized direct and moderating effects of affective commitment on willingness to share PHI in these virtual platforms. The findings of this study provide contributions to research and practice.

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APA

Kordzadeh, N., & Warren, J. (2017). Communicating personal health information in virtual health communities: An integration of privacy calculus model and affective commitment. Journal of the Association for Information Systems, 18(1), 45–81. https://doi.org/10.17705/1jais.00446

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