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Visualizing the conversation pathways of telephone linked care in a directed graph

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dc.contributor.advisor Robert Friedman and Peter Szolovits. en_US
dc.contributor.author Cuevas, Penelope H. (Penelope Huggins) en_US
dc.contributor.other Harvard University--MIT Division of Health Sciences and Technology. en_US
dc.date.accessioned 2010-04-28T15:35:32Z
dc.date.available 2010-04-28T15:35:32Z
dc.date.copyright 2009 en_US
dc.date.issued 2009 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/54458
dc.description Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2009. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 12). en_US
dc.description.abstract Telephone linked care (TLC) is a telehealth intervention that has been shown to be effective in a variety of clinical settings. TLC is an interactive computerized telephone system. The system 'speaks' to patients, asking them questions and understanding their responses. There is logic built into the calls, so that a patient's response to a question will dictate the next question that is asked. This serves to personalize the call for each patient, and makes the conversation more realistic. All of the patients' responses are stored in a database. This database provides much opportunity for analysis because a single phone call contains many responses. Visualization is an important way of gaining insight into data. Visualization can make data easier to understand and process. Different aspects of data can be encoded in a visualization. The TLC data lends itself to visualization. By viewing each of the questions that the system asks as nodes, and connecting the nodes by the chronological order in which these questions are asked, a tree structure will reveal the conversational paths that are taken in the calls. By combining data from multiple calls and encoding them in this tree structure, new insights can be gained into the TLC data. For example, the frequency with which questions are answered in a particular way can be encoded to reveal the most common pathways through the tree. This paper describes a visualization application of TLC data which will allow researchers to gain new insights into the TLC conversations and into medical interviews in general. en_US
dc.description.statementofresponsibility by Penelope H. Cuevas. en_US
dc.format.extent 24 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Harvard University--MIT Division of Health Sciences and Technology. en_US
dc.title Visualizing the conversation pathways of telephone linked care in a directed graph en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Harvard University--MIT Division of Health Sciences and Technology. en_US
dc.identifier.oclc 551181402 en_US


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