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.
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Cleland, I. et al. (2014). Predicting Technology Adoption in People with Dementia; Initial Results from the TAUT Project. In: Pecchia, L., Chen, L.L., Nugent, C., Bravo, J. (eds) Ambient Assisted Living and Daily Activities. IWAAL 2014. Lecture Notes in Computer Science, vol 8868. Springer, Cham. https://doi.org/10.1007/978-3-319-13105-4_39
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DOI: https://doi.org/10.1007/978-3-319-13105-4_39
Publisher Name: Springer, Cham
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