| 000 | 02432 am a22002413u 4500 | ||
|---|---|---|---|
| 042 | _adc | ||
| 100 | 1 | 0 |
_aMilne, Richard _eauthor _92988 |
| 700 | 1 | 0 |
_aCosta, Alessia _eauthor _92989 |
| 700 | 1 | 0 |
_aBrenman, Natassia _eauthor _92990 |
| 245 | 0 | 0 | _aDigital phenotyping and the (data) shadow of Alzheimer's disease |
| 260 | _c2022-01. | ||
| 500 | _a/pmc/articles/PMC7614175/ | ||
| 500 | _a/pubmed/36793447 | ||
| 520 | _aIn this paper, we examine the practice and promises of digital phenotyping. We build on work on the 'data self' to focus on a medical domain in which the value and nature of knowledge and relations with data have been played out with particular persistence, that of Alzheimer's disease research. Drawing on research with researchers and developers, we consider the intersection of hopes and concerns related to both digital tools and Alzheimer's disease using the metaphor of the 'data shadow'. We suggest that as a tool for engaging with the nature of the data self, the shadow is usefully able to capture both the dynamic and distorted nature of data representations, and the unease and concern associated with encounters between individuals or groups and data about them. We then consider what the data shadow 'is' in relation to ageing data subjects, and the nature of the representation of the individual's cognitive state and dementia risk that is produced by digital tools. Second, we consider what the data shadow 'does', through researchers and practitioners' discussions of digital phenotyping practices in the dementia field as alternately empowering, enabling and threatening. | ||
| 540 | _a | ||
| 540 | _ahttps://creativecommons.org/licenses/by/4.0/This work is licensed under a CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) International license. | ||
| 540 | _ahttps://creativecommons.org/licenses/by/4.0/Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). | ||
| 546 | _aen | ||
| 690 | _aArticle | ||
| 655 | 7 |
_aText _2local |
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| 786 | 0 | _nBig Data Soc | |
| 856 | 4 | 1 |
_uhttp://dx.doi.org/10.1177/20539517211070748 _zConnect to this object online. |
| 999 |
_c495 _d495 |
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