- Title
- Deep assessment: a novel framework for improving the care of people with very advanced Alzheimer's disease
- Creator
- Lyons, Gordon; Arthur-Kelly, Michael; Eidels, Ami; Mavratzakis, Aimee
- Relation
- BioMed Research International Vol. 2015
- Publisher Link
- http://dx.doi.org/10.1155/2015/749451
- Publisher
- Hindawi Publishing Corporation
- Resource Type
- journal article
- Date
- 2015
- Description
- Best practice in understanding and caring for people with advanced Alzheimer's disease presents extraordinary challenges. Their severe and deteriorating cognitive impairments are such that carers find progressive difficulty in authentically ascertaining and responding to interests, preferences, and needs. Deep assessment, a novel multifaceted framework drawn from research into the experiences of others with severe cognitive impairments, has potential to empower carers and other support professionals to develop an enhanced understanding of people with advanced Alzheimer's disease and so deliver better calibrated care in attempts to maximize quality of life. Deep assessment uses a combination of techniques, namely, Behaviour State Observation, Triangulated Proxy Reporting, and Startle Reflex Modulation Measurement, to deliver a comprehensive and deep assessment of the inner states (awareness, preferences, likes, and dislikes) of people who cannot reliably self-report. This paper explains deep assessment and its current applications. It then suggests how it can be applied to people with advanced Alzheimer's disease to develop others' understanding of their inner states and to help improve their quality of life. An illustrative hypothetical vignette is used to amplify this framework. We discuss the potential utility and efficacy of this technique for this population and we also propose other human conditions that may benefit from research using a deep assessment approach.
- Subject
- carers; Alzheimer's disease; cognitive impairment; assessment; quality of life
- Identifier
- http://hdl.handle.net/1959.13/1328704
- Identifier
- uon:25973
- Identifier
- ISSN:2314-6133
- Rights
- Copyright © 2015 Gordon Lyons et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Language
- eng
- Full Text
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