Abstract
It is increasingly recognized that some patients self-manage in the context of social networks rather than alone. Consumer health information technology (IT) designed to support socially embedded self-management must be responsive to patients' everyday communication practices. There is an opportunity to improve consumer health IT design by explicating how patients currently leverage social media to support health information communication. The objective of this study was to determine types of health information communication patterns that typify Facebook users with chronic health conditions to guide consumer health IT design. Seven hundred participants with type 2 diabetes were recruited through a commercial survey access panel. Cluster analysis was used to identify distinct approaches to health information communication both on and off Facebook. Analysis of variance (ANOVA) methods were used to identify demographic and behavioral differences among profiles. Secondary analysis of qualitative interviews ( n = 25) and analysis of open-ended survey questions were conducted to understand participant rationales for each profile. Our analysis yielded 7 distinct health information communication profiles. Five of 7 profiles had consistent patterns both on and off Facebook, while the remaining 2 demonstrated distinct practices, with no health information communication on Facebook but some off Facebook. One profile was distinct from all others in both health information communication practices and demographic composition. Rationales for following specific health information communication practices were categorized under 6 themes: altruism, instrumental support, social support, privacy and stigma, convenience, and Facebook knowledge. Facebook has been widely adopted for health information communication; This study demonstrates that Facebook has been widely adopted for health information communication. It also shows that the ways in which patients communicate health information on and off Facebook are diverse.
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More From: Journal of the American Medical Informatics Association : JAMIA
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