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

Ian Cleland; Chris D. Nugent; Sally I McClean; Phillip J. Hartin; Chelsea Sanders; Mark Donnelly; Shuai Zhang; Bryan Scotney; Ken Smith; Maria C. Noron; JoAnn C. Tschanz

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

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

Ian Cleland
, Chris D. Nugent
, Sally I McClean
, Phillip J. Hartin
, Chelsea Sanders
, Mark Donnelly
, Shuai Zhang
, Bryan Scotney
, Ken Smith
, Maria C. Noron
, JoAnn C. Tschanz

Alzheimer's Association

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Citations (Scopus)

214 Downloads (Pure)

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.

Original language	English
Title of host publication	Unknown Host Publication
Publisher	Springer
Pages	266-274
Number of pages	8
Volume	8868
ISBN (Print)	978-3-319-13105-4
DOIs	https://doi.org/10.1007/978-3-319-13105-4_39
Publication status	Published (in print/issue) - 2 Dec 2014
Event	International Work-Conference on Ambient Assisted Living (IWAAL) - Belfast, UK Duration: 2 Dec 2014 → …

Conference

Conference	International Work-Conference on Ambient Assisted Living (IWAAL)
Period	2/12/14 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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

TAUT IWALL paper Camera readyAuthor Accepted Manuscript, 457 KB

Cite this

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title = "Predicting Technology Adoption in People with Dementia; Initial Results from the TAUT Project",

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{\textquoteright} 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.",

author = "Ian Cleland and Nugent, \{Chris D.\} and McClean, \{Sally I\} and Hartin, \{Phillip J.\} and Chelsea Sanders and Mark Donnelly and Shuai Zhang and Bryan Scotney and Ken Smith and Noron, \{Maria C.\} and Tschanz, \{JoAnn C.\}",

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Cleland, I , Nugent, CD , McClean, SI, Hartin, PJ, Sanders, C, Donnelly, M , Zhang, S , Scotney, B, Smith, K, Noron, MC & Tschanz, JC 2014, Predicting Technology Adoption in People with Dementia; Initial Results from the TAUT Project. in Unknown Host Publication. vol. 8868, Springer, pp. 266-274, International Work-Conference on Ambient Assisted Living (IWAAL), 2/12/14. https://doi.org/10.1007/978-3-319-13105-4_39

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AU - Cleland, Ian

AU - Nugent, Chris D.

AU - McClean, Sally I

AU - Hartin, Phillip J.

AU - Sanders, Chelsea

AU - Donnelly, Mark

AU - Zhang, Shuai

AU - Scotney, Bryan

AU - Smith, Ken

AU - Noron, Maria C.

AU - Tschanz, JoAnn C.

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N2 - 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.

AB - 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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Y2 - 2 December 2014

ER -

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

Abstract

Conference

UN SDGs

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