Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Advertisement

Currently submitted to: Journal of Medical Internet Research

Date Submitted: Sep 18, 2020
Open Peer Review Period: Sep 11, 2020 - Nov 6, 2020
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Understanding barriers to linking novel consumer and lifestyle data for health research, results from the LifeInfo Survey: a topic modelling approach

ABSTRACT

Background:

Novel consumer and lifestyle data, for example those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers wishing to understand diet and exercise related risk factors for diseases. Yet, limited research has addressed public attitudes towards linking these data with individual health records for research purposes.

Objective:

The aim of this research was to identify key barriers for data linkage and recommend safeguards and procedures that would encourage individuals to share these data for potential future research.

Methods:

The LifeInfo Survey consulted the public on their attitudes towards 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 record in the future. The topic modelling technique Latent Dirichlet Allocation (LDA) was used to analyse these textual responses to uncover common thematic topics within the texts.

Results:

Participants provided responses related to sharing their store loyalty card data (n = 2,338) and health/fitness app data (n = 1,531). Key barriers to data sharing identified through topic modelling 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 data production services. We provide recommendations for addressing these issues to establish best practice for future researchers wishing to utilise these data.

Conclusions:

This study formulates large-scale consultation of public attitudes towards data linkage of this kind, as such, it is an important first step in understanding and addressing barriers to participation for research utilising novel consumer and lifestyle data.


 Citation

Please cite as:

Understanding barriers to linking novel consumer and lifestyle data for health research, results from the LifeInfo Survey: a topic modelling approach

JMIR Preprints. 18/09/2020:24236

DOI: 10.2196/preprints.24236

URL: https://preprints.jmir.org/preprint/24236

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.