Abstract
In the current work, data gleaned from an assistive technology (reminding technology), which has been evaluated with people with Dementia over a period of several years was retrospectively studied to extract the factors that contributed to successful adoption. The aim was to develop a prediction model with the capability of prospectively assessing whether the assistive technology would be suitable for persons with Dementia (and their carer), based on user characteristics, needs and perceptions. Such a prediction tool has the ability to empower a formal carer to assess, through a very limited amount of questions, whether the technology will be adopted and used.
| Original language | English |
|---|---|
| Pages (from-to) | 169-176 |
| Journal | Interacting with Computers |
| Volume | 26 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published (in print/issue) - 2014 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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Dive into the research topics of 'Development of a Technology Adoption and Usage Prediction Tool for Assistive Technology for People with Dementia'. Together they form a unique fingerprint.Profiles
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Ian Cleland
- School of Computing - Reader
- Faculty Of Computing, Eng. & Built Env. - Research Director (Computing)
- Computer Science and Informatics Research
Person: Academic
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Mark Donnelly
- School of Computing - Senior Lecturer
- Faculty Of Computing, Eng. & Built Env. - Senior Lecturer
- Computer Science and Informatics Research
Person: Academic
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Sally McClean
- School of Computing - Professor of Mathematics
- Faculty Of Computing, Eng. & Built Env. - Full Professor
- Computer Science and Informatics Research
Person: Academic
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