Healthcare Virtual Support Communities: Pillars of Support and Companionship.

详细信息   

• 作者：Huang ; Kuang-Yuan.
• 学历：Ph.D.
• 年：2013
• 导师：Chengalur-Smith, InduShobha,eadvisorUzuner, Ozlemecommittee memberNambisan, Pryiaecommittee member
• 毕业院校：State University of New York
• Department：Information Science
• ISBN：9781303336249
• CBH：3592488
• Country：USA
• 语种：English
• FileSize：4072530
• Pages：125

文摘

The two studies in this dissertation identify and address two related research gaps in literature on healthcare virtual support communities. Study one suggested that the exclusive emphasis on social support behavior and its impacts on individual well-being in virtual support communities has led to the neglect of another type of social interaction that also promotes individual health&mdash；companionship activities. It is thus argued that in order to gain a deeper insight into the online support phenomenon, the consideration of companionship activities, in addition to social support exchange, is necessary. To bridge this gap in the literature, I contrasted individual engagement in support behavior and companionship activities that took place in two large online discussion forums&mdash；one for patients with breast cancer and the other for patients with prostate cancer. Based on the identification of the two types of social activities, the mutual-dependence between individuals participation in these activities, and gender differences in their activity engagement are also hypothesized and tested.. In the second study, I argued that in the literature of virtual support communities little attention has been paid to conceptualizing the determinants of social support provision. Drawing from social capital theory, the second study attempts to bridge this gap by presenting a model that applies the structural, relational, and cognitive dimensions of social capital to theorize the social determinants of the provision of informational and emotional support in virtual support communities. Through the use of qualitative content analysis and machine learning techniques, messages from a virtual support community for women with breast cancer are analyzed. The analysis results are used to test the proposed framework modeling support provision. The purpose of this dissertation is to advance the understanding of online socio-behavioral dynamics of virtual support communities. It also helps provide insights into the design of such communities and the delivery of patient-focused healthcare interventions..