Title | ||
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Context-Based User Stereotype Model For Mobile User Interfaces In Health Care Applications |
Abstract | ||
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Mobile technology has been piloted in a range of health-related areas, allowing doctors to receive critically important patient information in an automated way. It is vital that the technology be adaptable, so that the right information is available to the right doctors. We investigate the use of smartphones and various user stereotypes functioning in a hospital environment, as these stereotypes can play an important role in designing and adapting the mobile user interface (MUI) for health care applications. This paper discusses how a user stereotype can be modeled and used for adapting MUI for health care applications in a hospital setting. An empirical study using questionnaires and interviews among 30 doctors is conducted in order to extract the characteristics of each user stereotype, in terms of age group, domain experience, and mobile technology use. The study confirms that there are three groups of doctors in hospitals: junior, intermediate, and experienced, corresponding to the hierarchical structure in place in the hospital setting. A set of context descriptor sentences is extracted from each group during the interview, in order to consider the context of use of smartphones in adapting the MUI for these applications. (c) 2013 The Authors. Published by Elsevier B.V. |
Year | DOI | Venue |
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2013 | 10.1016/j.procs.2013.06.142 | 4TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2013), THE 3RD INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2013) |
Keywords | Field | DocType |
Mobile User Interface, User Stereotype, Context Descriptor, Health Care Applications | Mobile technology,Health care,World Wide Web,Computer science,Context based,Stereotype,User interface,Multimedia,Empirical research | Conference |
Volume | ISSN | Citations |
19 | 1877-0509 | 5 |
PageRank | References | Authors |
0.48 | 4 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Reem Al-Nanih | 1 | 25 | 3.19 |
Olga Ormandjieva | 2 | 317 | 37.11 |
Thiruvengadam Radhakrishnan | 3 | 117 | 32.44 |