Patricia G. Davidson

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In the recent years, the number of individuals engaged in self-care of chronic diseases has grown exponentially. Advances in computing technologies help individuals with chronic diseases collect unprecedented volumes of health-related data. However, engaging in reflective analysis of the collected data may be challenging for the untrained individuals. We(More)
Collaborative tagging mechanisms are integral to social computing applications in a variety of domains. Their expected benefits include simplified retrieval of digital content, as well as enhanced ability of a community to makes sense of the shared content. We examine the impact of collaborative tagging in context of nutrition management. In a controlled(More)
OBJECTIVE To investigate subjective experiences and patterns of engagement with a novel electronic tool for facilitating reflection and problem solving for individuals with type 2 diabetes, Mobile Diabetes Detective (MoDD). METHODS In this qualitative study, researchers conducted semi-structured interviews with individuals from economically disadvantaged(More)
OBJECTIVE To investigate how individuals with diabetes and diabetes educators reason about data collected through self-monitoring and to draw implications for the design of data-driven self-management technologies. MATERIALS AND METHODS Ten individuals with diabetes (six type 1 and four type 2) and 2 experienced diabetes educators were presented with a(More)
OBJECTIVE To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. MATERIALS AND METHODS The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge(More)
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