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Digital phenotyping and the (data) shadow of Alzheimer's disease.

Published version
Peer-reviewed

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Abstract

In 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.

Description

Funder: Economic and Social Research Council; FundRef: https://doi.org/10.13039/501100000269

Keywords

Alzheimer’s disease, Data shadow, ageing, data double, digital health, digital phenotype

Journal Title

Big Data Soc

Conference Name

Journal ISSN

2053-9517
2053-9517

Volume Title

9

Publisher

SAGE Publications
Sponsorship
Medical Research Council (MR/N029941/1)
Wellcome Trust (206194, 213579)