title: A knowledge-driven approach to predicting technology adoption among Persons with Dementia.
abstract: As the demographics of many countries shift towards an ageing population it is predicted that the prevalence of diseases affecting cognitive capabilities will continually increase. One approach to enabling individuals with cognitive decline to remain in their own homes is through the use of cognitive prosthetics such as reminding technology. However, the benefit of such technologies is intuitively predicated upon their successful adoption and subsequent use. Within this paper we present a knowledge-based feature set which may be utilized to predict technology adoption amongst Persons with Dementia (PwD). The chosen feature set is readily obtainable during a clinical visit, is based upon real data and grounded in established research. We present results demonstrating 86% accuracy in successfully predicting adopters/non-adopters amongst PwD.
authors.forename: Timothy
authors.initials: T
authors.lastname: Patterson
authors.forename: Sally
authors.initials: S
authors.lastname: McClean
authors.forename: Patrick M
authors.initials: PM
authors.lastname: Langdon
authors.lastname: Shuai Zhang
authors.forename: Chris
authors.initials: C
authors.lastname: Nugent
authors.forename: Ian
authors.initials: I
authors.lastname: Cleland
mesh_terms: D040561:Assisted Living Facilities; D003704:Dementia / Q000628:therapy*; D006801:Humans; D005791:Patient Care / Q000295:instrumentation; D013672:Technology / Q000706:statistics & numerical data*