Who tweets what about personalised medicine? Promises and concerns from Twitter discussions in Denmark

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Abstract

Digital health data are seen as valuable resources for the development of better and more efficient treatments, for instance through personalised medicine. However, health data are information about individuals who hold opinions and can challenge how data about them are used. Therefore it is important to understand public discussions around reuse of digital health data. Social media have been heralded as enabling new forms of public engagement and as a place to study social issues. In this paper, we study a public debate on Twitter about personalised medicine. We explore who participates in discussions about personalised medicine on Twitter and what they tweet about. Based on user-generated biographies we categorise users as having a ‘Professional interest in personalised medicine’ or as ‘Private’ users. We describe how users within the field tweet about the promises of personalised medicine, while users unaffiliated with the field tweet about the concrete realisation of these ambitions in the form of a new infrastructure and express concerns about the conditions for the implementation. Our study serves to remind people interested in public opinion that Twitter is a platform used for multiple purposes by different actors and not simply a bottom-up democratic forum. This study contributes with insights relevant to policymakers wishing to expand infrastructures for reuse of health data. First, by providing insights into what is discussed about health data reuse. Second, by exploring how Twitter can be used as a platform to study public discussions about reuse of health data.

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Most cited references 51

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The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts.

Brent Mittelstadt, Luciano Floridi (2016)

The capacity to collect and analyse data is growing exponentially. Referred to as 'Big Data', this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: (1) informed consent, (2) privacy (including anonymisation and data protection), (3) ownership, (4) epistemology and objectivity, and (5) 'Big Data Divides' created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: (6) the dangers of ignoring group-level ethical harms; (7) the importance of epistemology in assessing the ethics of Big Data; (8) the changing nature of fiduciary relationships that become increasingly data saturated; (9) the need to distinguish between 'academic' and 'commercial' Big Data practices in terms of potential harm to data subjects; (10) future problems with ownership of intellectual property generated from analysis of aggregated datasets; and (11) the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices.

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Twitter and Facebook are not representative of the general population: Political attitudes and demographics of British social media users

Jonathan Mellon, Christopher Prosser (2017)

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The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review

Joana Barros, Jim Duggan, Dietrich Rebholz-Schuhmann (2020)

Background Public health surveillance is based on the continuous and systematic collection, analysis, and interpretation of data. This informs the development of early warning systems to monitor epidemics and documents the impact of intervention measures. The introduction of digital data sources, and specifically sources available on the internet, has impacted the field of public health surveillance. New opportunities enabled by the underlying availability and scale of internet-based sources (IBSs) have paved the way for novel approaches for disease surveillance, exploration of health communities, and the study of epidemic dynamics. This field and approach is also known as infodemiology or infoveillance. Objective This review aimed to assess research findings regarding the application of IBSs for public health surveillance (infodemiology or infoveillance). To achieve this, we have presented a comprehensive systematic literature review with a focus on these sources and their limitations, the diseases targeted, and commonly applied methods. Methods A systematic literature review was conducted targeting publications between 2012 and 2018 that leveraged IBSs for public health surveillance, outbreak forecasting, disease characterization, diagnosis prediction, content analysis, and health-topic identification. The search results were filtered according to previously defined inclusion and exclusion criteria. Results Spanning a total of 162 publications, we determined infectious diseases to be the preferred case study (108/162, 66.7%). Of the eight categories of IBSs (search queries, social media, news, discussion forums, websites, web encyclopedia, and online obituaries), search queries and social media were applied in 95.1% (154/162) of the reviewed publications. We also identified limitations in representativeness and biased user age groups, as well as high susceptibility to media events by search queries, social media, and web encyclopedias. Conclusions IBSs are a valuable proxy to study illnesses affecting the general population; however, it is important to characterize which diseases are best suited for the available sources; the literature shows that the level of engagement among online platforms can be a potential indicator. There is a necessity to understand the population’s online behavior; in addition, the exploration of health information dissemination and its content is significantly unexplored. With this information, we can understand how the population communicates about illnesses online and, in the process, benefit public health.

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Author and article information

Journal

Journal ID (nlm-ta): Digit Health

Journal ID (iso-abbrev): Digit Health

Journal ID (publisher-id): DHJ

Journal ID (hwp): spdhj

Title: Digital Health

Publisher: SAGE Publications (Sage UK: London, England )

ISSN (Electronic): 2055-2076

Publication date (Electronic): 20 April 2023

Publication date Collection: Jan-Dec 2023

Volume: 9

Electronic Location Identifier: 20552076231169832

Affiliations

[1-20552076231169832]Department of Public Health, Ringgold 4321, universityUniversity of Copenhagen; , Copenhagen K, Denmark

Author notes

[*]Lea Skovgaard, Department of Public Health, University of Copenhagen, Øster Farigmagsgade 5, Copenhagen K 1014, Denmark. Email: lsk@ 123456sund.ku.dk

Author information

Lea Skovgaard https://orcid.org/0000-0001-5491-6928

Article

Publisher ID: 10.1177_20552076231169832

DOI: 10.1177/20552076231169832

PMC ID: 10126701

PubMed ID: 37113257

SO-VID: b23013e0-c7ce-4a66-8a39-5358f82e3480

License:

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License ( https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, 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).

History

Date received : 26 September 2022

Date accepted : 29 March 2023

Funding

Funded by: Carlsbergfondet, FundRef https://doi.org/10.13039/501100002808;

Award ID: CF17-0016

Custom metadata

typesetter ts19

cover-date January-December 2023

Keywords: personalised medicine < personalised medicine,twitter < media,public debate,reuse of health data,denmark

Data availability:

Keywords: personalised medicine < personalised medicine, twitter < media, public debate, reuse of health data, denmark

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