Clarke, H, Clark, S orcid.org/0000-0003-4090-6002, Birkin, M et al. (3 more authors) (2021) Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey. Journal of Medical Internet Research, 23 (5). e24236. ISSN 1438-8871
Abstract
Background:
Novel consumer and lifestyle data, such as those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers seeking to understand diet- and exercise-related risk factors for diseases. However, limited research has addressed public attitudes toward linking these data with individual health records for research purposes. Data linkage, combining data from multiple sources, provides the opportunity to enhance preexisting data sets to gain new insights.
Objective:
The aim of this study is to identify key barriers to data linkage and recommend safeguards and procedures that would encourage individuals to share such data for potential future research.
Methods:
The LifeInfo Survey consulted the public on their attitudes toward sharing consumer and lifestyle data for research purposes. Where barriers to data sharing existed, participants provided unstructured survey responses detailing what would make them more likely to share data for linkage with their health records in the future. The topic modeling technique latent Dirichlet allocation was used to analyze these textual responses to uncover common thematic topics within the texts.
Results:
Participants provided responses related to sharing their store loyalty card data (n=2338) and health and fitness app data (n=1531). Key barriers to data sharing identified through topic modeling included data safety and security, personal privacy, requirements of further information, fear of data being accessed by others, problems with data accuracy, not understanding the reason for data linkage, and not using services that produce these data. We provide recommendations for addressing these issues to establish the best practice for future researchers interested in using these data.
Conclusions:
This study formulates a large-scale consultation of public attitudes toward this kind of data linkage, which is an important first step in understanding and addressing barriers to participation in research using novel consumer and lifestyle data.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021, Holly Clarke, Stephen Clark, Mark Birkin, Heather Iles-Smith, Adam Glaser, Michelle A Morris. Originally published in the Journal of Medical Internet Research. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
Keywords: | topic modeling; text analysis; lifestyle data; consumer data; mHealth; loyalty card; fitness tracker; data linkage; data sharing; public attitudes; public opinion |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Funding Information: | Funder Grant number ESRC (Economic and Social Research Council) ES/S007164/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Apr 2021 08:56 |
Last Modified: | 25 Jun 2023 22:38 |
Status: | Published |
Publisher: | JMIR Publications |
Identification Number: | 10.2196/24236 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:173153 |
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Filename: Understanding Barriers to Novel Data Linkages.pdf
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