Understanding barriers to novel data linkages : topic modeling of the results of the LifeInfo survey

Clarke, H ORCID: https://orcid.org/0000-0002-1975-5679, Clark, S ORCID: https://orcid.org/0000-0003-4090-6002, Birkin, M ORCID: https://orcid.org/0000-0001-5991-098X, Iles-Smith, HM ORCID: https://orcid.org/0000-0002-0520-2694, Glaser, A ORCID: https://orcid.org/0000-0003-1814-5120 and Morris, MA ORCID: https://orcid.org/0000-0002-9325-619X 2021, 'Understanding barriers to novel data linkages : topic modeling of the results of the LifeInfo survey' , Journal of Medical Internet Research, 23 (5) , e24236.

Preview

PDF - Published Version Available under License Creative Commons Attribution 4.0. Download (252kB) | Preview

Abstract

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. 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. 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. 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. 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. [Abstract copyright: ©Holly Clarke, Stephen Clark, Mark Birkin, Heather Iles-Smith, Adam Glaser, Michelle A Morris. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.05.2021.]

Item Type:	Article
Contributors:	Eysenbach, G (Editor)
Additional Information:	** From PubMed via Jisc Publications Router **Journal IDs: eissn 1438-8871 **Article IDs: pubmed: 33998998; pii: v23i5e24236 **History: accepted 12-04-2021; revised 27-01-2021; submitted 18-09-2020
Schools:	Schools > School of Health and Society
Journal or Publication Title:	Journal of Medical Internet Research
Publisher:	JMIR Publications
ISSN:	1438-8871
Related URLs:	Publication
Funders:	National Institute for Health Research Clinical Research Network, Consumer Data Research Centre, Medical Bioinformatics Centre, School of Medicine, University of Leeds
SWORD Depositor:	Publications Router
Depositing User:	Publications Router
Date Deposited:	04 Jun 2021 11:10
Last Modified:	16 Feb 2022 07:16
URI:	https://usir.salford.ac.uk/id/eprint/60821

Actions (login required)

Edit record (repository staff only)