The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.
Health information privacy concerns, antecedents, and information disclosure intention in online health communities
Abstract
Abstract This study explores the antecedents and consequences of health information privacy concerns in online health communities by integrating the dual calculus and protection motivation theories. On the basis of survey data from 337 users, health information privacy concerns, together with informational and emotional support, significantly influence personal health information (PHI) disclosure intention. Privacy concerns are negatively influenced by two coping appraisals (i.e., response efficacy and self-efficacy) and positively affected by two threat appraisals (i.e., perceived vulnerability and perceived severity). The perceived health status differentially moderates the effects of privacy concerns and informational support on the PHI disclosure intention.
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“They also ofer an anonymous and private space to participate in self-disclosure [54].”
BackgroundLiu, W., Jiang, M., Li, W., & Mou, J. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123407 · Cited by 98
Metadata
- Authors
- Zhang, X., Liu, S., Chen, X., Wang, L., Gao, B., & Zhu, Q.
- Venue
- Information & Management
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 55
- Issue
- 4
- Pages
- 482-493
- ISSN
- 0378-7206 (ISSN-L)
- OpenAlex
- W2768249236
- Cited by
- 437
- References
- 92
- FWCI
- 65.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, X., Liu, S., Chen, X., Wang, L., Gao, B., & Zhu, Q. (2018). Health information privacy concerns, antecedents, and information disclosure intention in online health communities. Information & Management. https://doi.org/10.1016/j.im.2017.11.003
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.