An individual s decision to place a close family member in a nursing home is both difficult and crucial. To assist consumers with such a decision, several initiatives have led to the creation of public websites designed to communicate quality indicators for nursing homes. However, a majority of consumers fail to fully utilize this information for various reasons, such as the multidimensionality, complexity, and uncertainty of the information. Some of the difficulties may be alleviated by information visualization (InfoVis) techniques. However, several unsuccessful attempts in applying InfoVis to decision making suggest that a thorough understanding of the user s perspective is necessary.
Accordingly, the author has developed an InfoVis tool for the decision domain of choice of a nursing home. First, a framework of overarching InfoVis and decision theories, called the visualized decision making (VDM) framework, has been developed and contextualized within the selection of a nursing home. Second, a decision-support tool using several InfoVis techniques such as the weighting slider bar and the distribution view have been designed for application within the framework, and the designed tool, called VDM, was implemented. Third, VDM was empirically tested through a web-based experiment and follow-up interviews.
The results of this study showed that individuals faced with the decision of selecting a nursing home could make fairly high quality decisions when they used VDM. Though the effects of proposed InfoVis techniques were not evident, this study provided the theoretical framework and empirical results which may help other designers of InfoVis techniques because this work addresses several issues consumers face when choosing a nursing home that can be generalized to other decision making contexts.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/24662 |
Date | 08 July 2008 |
Creators | Yi, Ji Soo |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Dissertation |
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