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Predicting Technology Adoption in People with Dementia; Initial Results from the TAUT Project

Cleland, Ian, Nugent, Chris D., McClean, Sally I, Hartin, Phillip J., Sanders, Chelsea, Donnelly, Mark, Zhang, Shuai, Scotney, Bryan, Smith, Ken, Noron, Maria C. and Tschanz, JoAnn C. (2014) Predicting Technology Adoption in People with Dementia; Initial Results from the TAUT Project. In: International Work-Conference on Ambient Assisted Living (IWAAL), Belfast, UK. Springer International Publishing. Vol 8868 8 pp. [Conference contribution]

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URL: http://link.springer.com/chapter/10.1007%2F978-3-319-13105-4_39

DOI: 10.1007/978-3-319-13105-4_39

Abstract

The acceptance of technology is a crucial factor in successfully deploying technology solutions in healthcare. Our previous research has highlighted the potential of modelling user adoption from a range of environmental, social and physical parameters. This current work aims to build on the notion of predicting technology adoption through a study investigating the usage of a reminding application deployed through a mobile phone. The TAUT project is currently recruiting participants from the Cache County Study on Memory in Aging (CCSMA) and will monitor participants over a period of 12 months. Information relating to participants’ compliance with usage of the reminding application, details of cognitive assessments from the CCSMA and medical and genealogical related details from the Utah Population Database (UPDB) will be used as inputs to the development of a new adoption model. Initial results show, that with an unscreened dataset, it is possible to predict refusers and adopters with an F-measure of 0.79.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:30850
Deposited By: Dr Ian Cleland
Deposited On:21 Jan 2015 11:26
Last Modified:21 Jan 2015 11:26

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