| Reference : Comparative Evaluation of Models of Assistive Technologies’ Use |
| Scientific congresses, symposiums and conference proceedings : Unpublished conference | |||
| Social & behavioral sciences, psychology : Theoretical & cognitive psychology Social & behavioral sciences, psychology : Treatment & clinical psychology | |||
| Sustainable Development | |||
| http://hdl.handle.net/10993/36110 | |||
| Comparative Evaluation of Models of Assistive Technologies’ Use | |
| English | |
Abri, Diana  [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Integrative Research Unit: Social and Individual Development (INSIDE) >] | |
| Boll, Thomas [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Integrative Research Unit: Social and Individual Development (INSIDE) >] | |
| 6-Jul-2018 | |
| Yes | |
| International | |
| 47th Annual Conference of the British Society of Gerontology | |
| 4-6 July 2018 | |
| University of Manchester | |
| Manchester | |
| United Kingdom | |
| [en] assistive technologies ; models ; theories ; use ; older people ; literature review | |
| [en] Many older people have functional limitations and are at risk of losing their ability to live autonomously. Assistive Technology (AT) could help to reduce that risk. However, many older people don’t use ATs. Our presentation reviews existing models of ATs use, their applicability to specific types of AT, predictive value, fundamental elements, and critiques of such models.
In systematic literature searches in PsycINFO, MEDLINE, and Google Scholar 46 papers were identified that met our inclusion criteria. 32 papers covered models of ATs use, applicability to special types of ATs, components of models, and their predictive value. 14 papers cover criticisms of models of AT use. We classified the models into two groups: The first included 11 models focusing on individuals’ mental states (e.g., beliefs, desires) as factors explaining ATs use; the second included 22 models that also considered contextual factors (e.g., social influence, physical environment) in addition to individuals’ mental states. Across both groups the most frequently included explanatory components were subjective norm and personal attitudes towards AT use, followed by perceived usefulness, perceived ease of use and then intention to use. Models were most frequently applied to information technologies followed by application to socially assistive robots. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and an extended version of Technology Acceptance Model showed the highest amount of explained variance in intention to use (56-74%) and an extended model of UTAUT in actual use of ATs (64%). We conclude with recommendations for further improvement of AT use models. | |
| Integrative Research Unit: Social and Individual Development (INSIDE) > Institute for Research on Generations and Family: Research Group on Aging and Life Span Development | |
| Researchers ; Professionals ; Students | |
| http://hdl.handle.net/10993/36110 |
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