People are increasingly turning to online communities for entertainment, information, and social support, among other uses and gratifications. Online communities include traditional online social networks (OSNs) such as Facebook but also specialized online health communities (OHCs) where people go specifically to seek social support for various health conditions. OHCs have obvious health ramifications but the use of OSNs can also influence people's mental health and health behaviors. The use of online communities has been widely studied but in the health context their exploration has been more limited. Not only are online communities being extensively used for health purposes, but there is also increasing concern that the use of online communities can itself affect health. Therefore, there is a need to better understand how such technologies influence people's health and health behaviors.
The research in this dissertation centers on examining how online community use influences health and health behaviors. There are three studies in this dissertation. The first study develops a conceptual model to explain the process whereby the characteristics of a request from an OHC user for social support is answered by a wounded healer, who is a person leveraging their own experiences with health challenges to help others. The second study investigates how algorithmic fairness, accountability, and transparency of an OSN newsfeed algorithm influence the users' attitudes and beliefs about childhood vaccines and ultimately their vaccine hesitancy. The third study examines how OSN social overload, through OSN use, can lead to psychological distress and received social support. The research contributes theoretical and practical insights to the literature on the use of online communities in the health context. / Doctor of Philosophy / People use online communities to socialize and to seek out information and help. Online social networks (OSNs) such as Facebook are large communities on which people segregate into smaller groups to discuss joint interests. Some online communities cater to specific needs, such as online health communities (OHCs), which provide platforms for people to talk about the health challenges they or their loved ones are facing. Online communities do not intentionally seek controversy, but because they welcome all perspectives, they have contributed to phenomena such as vaccine hesitancy. Moreover, social overload from the use of OSNs can have both positive and negative psychological effects on users. This dissertation examines the intersection of online communities and health. The first study explains how the interaction of the characteristics of a request for social support made by an OHC user and the characteristics of the wounded healer drive the provision of social support. The model that is developed shows the paths through which the empathy of the wounded healer and the characteristics of the request lead to motivation to provide help to those in need on an OHC. In the second study, the role of characteristics of a newsfeed algorithm, specifically fairness, accountability, and transparency (FAT), in the development of childhood vaccine hesitancy is examined. The findings show that people's perceptions of the newsfeed algorithm's FAT increase their negative attitudes toward vaccination and their perceived behavioral control over vaccination. The third study examines how different uses of OSNs can influence the relationships between social overload and psychological distress and received social support. The findings show how OSN use can be tailored to decrease negative and increase positive psychological consequences without discontinuing use.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/111647 |
| Date | 26 August 2022 |
| Creators | Villacis Calderon, Eduardo David |
| Contributors | Business, Business Information Technology, James, Tabitha L., Lowry, Paul Benjamin, Adjerid, Idris, Shen, Wenqi, Wang, Alan Gang |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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