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Cited by 437

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

Zhang, Xing, Liu, Shan, Chen, Xing, Wang, Lin, Gao, Baojun, Zhu, Qing·2018·Information & Management

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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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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CoChat. (2026). Citation check: Health information privacy concerns, antecedents, and information disclosure intention in online health communities. https://app.cochat.ai/papers/10.1016/j.im.2017.11.003
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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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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.