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Not everyone appreciates the benefits of social support: the effects of relational self and attachment styles

Not everyone appreciates the benefits of social support: the effects of relational self and attachment styles
Not everyone appreciates the benefits of social support: the effects of relational self and attachment styles
Research on virtual communities and social support are well documented in psychology and marketing literature. There has been little research on how people react to the health-related information provided by other community members. Drawing from social support, attachment style, and relational self literatures, this research proposes a conceptual framework to examine these issues in the healthcare context, and seeking to understand how marketing messages can affect one’s attitude toward the healthcare community.
DHA2019
Wang, Weisha
3b06920a-f578-41b8-a356-7e2da53d3bf6
Wang, Weisha
3b06920a-f578-41b8-a356-7e2da53d3bf6

Wang, Weisha (2019) Not everyone appreciates the benefits of social support: the effects of relational self and attachment styles. In International Conference on Digital Health and Medical Analytics: Big data analytics and AI in digital health. DHA2019. 2 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

Research on virtual communities and social support are well documented in psychology and marketing literature. There has been little research on how people react to the health-related information provided by other community members. Drawing from social support, attachment style, and relational self literatures, this research proposes a conceptual framework to examine these issues in the healthcare context, and seeking to understand how marketing messages can affect one’s attitude toward the healthcare community.

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Published date: 25 August 2019

Identifiers

Local EPrints ID: 436048
URI: http://eprints.soton.ac.uk/id/eprint/436048
PURE UUID: 70bff83f-df49-4246-9dd8-ea98b9e00c78
ORCID for Weisha Wang: ORCID iD orcid.org/0000-0002-2985-3416

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Date deposited: 27 Nov 2019 17:30
Last modified: 16 Mar 2024 05:26

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Author: Weisha Wang ORCID iD

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