Participation in online health communities and perceived social support : elaborating participation types, identification, and interpersonal bonds

dc.contributor.advisorStephens, Keri K.
dc.contributor.committeeMemberBernhardt, Jay
dc.contributor.committeeMemberBarbour, Joshua
dc.contributor.committeeMemberDonovan, Erin
dc.contributor.committeeMemberScott, Craig
dc.creatorZhu, Yaguang
dc.creator.orcid0000-0002-8025-3889
dc.date.accessioned2020-10-02T20:00:28Z
dc.date.available2020-10-02T20:00:28Z
dc.date.created2018-05
dc.date.issued2018-05
dc.date.submittedMay 2018
dc.date.updated2020-10-02T20:00:29Z
dc.description.abstractPresently, an increasing number of people with chronic diseases exchange social support using online health communities (OHCs). They often gain knowledge from interacting with like-others and improve self-management of their disease. Analyzing people’s online participatory behaviors boosts our understanding of the impact of OHCs. This dissertation project describes two interrelated studies that examine the relationship between participation types, group communication mechanisms, and social support. Together, they reveal how people participate in OHCs and provide understanding of the nuanced communicative mechanisms found in online communities that might help people cope and heal when they have a chronic disease. Study One critiques previous methodological approaches as limited by a static conceptualization of participation that (1) dichotomized people’s online interaction (e.g., low participation vs. high participation) and (2) did not allow for variability of OHC participation. To fill the gap, this study advances the conceptualization of OHC participation by defining participation in two equally important dimensions: level of participation (ranging from complete lurking to active posting) and mode of participation (task mode and/or relational mode). This conceptualization is further validated through an empirically-based user typology. Results of cluster analyses identify a fourfold typology of user participation: hybrid-mode posting, task-mode posting, relational-mode posting, and task-mode lurking. Drawing on Prentice et al.’s (1994) common-identity and common-bond framework, Study Two proposes and examines the group communication mechanisms through which members’ OHC participation influences their perceived social support. Results of the SEM model suggest that two group communication mechanisms—identification with the community and interpersonal bonds with other members—mediate the relationship between OHC participation and perceived social support. Specifically, identification has a stronger mediating effect than interpersonal bonds. Furthermore, one-way ANOVAs reveal that identification, interpersonal bonds, and perceived social support vary across different user participation types (as identified in Study One). A discussion of results is offered in addition to study limitations and future directions. Notably, this dissertation makes theoretical progress on the impact of different participation types and group communication mechanisms for benefiting members in OHCs. From an applied perspective, this research contributes to OHC design insights that can potentially (1) enhance users’ participation in OHCs and (2) improve online intervention programs by targeting specific functions of OHCs.
dc.description.departmentCommunication Studies
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2152/83062
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/10063
dc.language.isoen
dc.subjectOnline health communities
dc.subjectParticipation types
dc.subjectPerceived social support
dc.titleParticipation in online health communities and perceived social support : elaborating participation types, identification, and interpersonal bonds
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentCommunication Studies
thesis.degree.disciplineCommunication Studies
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

Access full-text files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
ZHU-DISSERTATION-2018.pdf
Size:
990.49 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
4.45 KB
Format:
Plain Text
Description:
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.84 KB
Format:
Plain Text
Description: