Digital orphans: Data closure and openness in patient-powered networks

Epistemology of the side effect: anecdote and evidence in the digital age

Through the history of rxisk.org, this article explores some of the Web’s effects on the production and circulation of pharmaceutical knowledge. RxISK is an independent website that solicits reports from patients in order to uncover drug-induced harms which clinical trials and national pharmacovigilance schemes fail to identify. The first part of the article locates the origins of the project in the nearly 15-year struggle to obtain recognition and redress for one particular side effect of selective serotonin reuptake inhibitor (SSRI) antidepressants—their ability to trigger violent or suicidal behavior. That struggle, I show, brought to light the ways in which modern evidence-making practices obscure the harms of pharmacological treatment. The second part, based on interviews with the site’s creators, examines how RxISK’s data collection practices seek to convert the Web from a site for the circulation of misinformation into a usable source of new knowledge about drugs. The project’s originality, I argue, lies in its effort to reframe the relation between anecdote and evidence so as to liberate the patient’s voice from the burden of representativeness. Within this reframed epistemology, the project is also freed from the imperative of large-scale data extraction that increasingly dominates the economy of digital health.

The construction of rare disease discourse on YouTube: highlighting a disparity between policy rhetoric and patient practices around public engagement

Background: Policy rhetoric around the 6,000-8,000 rare diseases affecting 300 million people worldwide often focuses on public engagement. Meanwhile, medical authorities tend either to treat patients with rare diseases as pre-categorised data sources, proffer to them notions of technological self-care as empowerment, or recruit them as advocacy allies. Conversely, people living with rare diseases often mobilise and engage with one another in self-organised communities via social media to share discussion, information, and resources. How rare disease discourse forms on specific social media platforms, the role of different actors (including medical authorities and algorithms), and its relation to public engagement policy are poorly understood. Methods: This paper examines data on YouTube video watching/sharing (gathered from YouTube’s API via DMI’s ‘Data Tools for YouTube’) through social network analysis (read through a controversy analysis lens). Results: The paper identifies eight patterns – each revolving around different levels of: focus on rare disease content; engagement between content and viewers, i.e. through likes, dislikes, and surrounding particular videos; permeability of videos between categories; and repetition in viewers watching the same video. Across six of the patterns, the paper finds a rare disease issue-network forming, where discourse is constructed through three distinct communication strategies, each garnering a different form of engagement. Conclusions: Overall, the paper highlights a disconnect between how rare disease discourse is enacted on YouTube and policy promises of public engagement, with potential spaces for dialogue often closed off by medical authorities. To close, the paper provides recommendations for how policymakers might engage with and facilitate more inclusive forms of social media interaction between specific rare disease related communities and clinicians to develop more meaningful forms of knowledge exchange.

The construction of rare disease discourse on YouTube: highlighting a disparity between policy rhetoric and patient practices around public engagement

Background: Policy rhetoric around the 6,000-8,000 rare diseases affecting 300 million people worldwide often focuses on public engagement. Meanwhile, medical authorities tend either to treat patients with rare diseases as pre-categorised data sources, proffer to them notions of technological self-care as empowerment, or recruit them as advocacy allies. Conversely, people living with rare diseases often mobilise and engage with one another in self-organised communities via social media to share discussion, information, and resources. How rare disease discourse forms on specific social media platforms, the role of different actors (including medical authorities and algorithms), and its relation to public engagement policy are poorly understood. Methods: This paper examines data on YouTube video watching/sharing (gathered from YouTube’s API via DMI’s ‘Data Tools for YouTube’) through social network analysis (read through a controversy analysis lens). Results: The paper identifies eight patterns – each revolving around different levels of: focus on rare disease content; engagement between content and viewers, i.e. through likes, dislikes, and surrounding particular videos; permeability of videos between categories; and repetition in viewers watching the same video. Across six of the patterns, the paper finds a rare disease issue-network forming, where discourse is constructed through three distinct communication strategies, each garnering a different form of engagement. Conclusions: Overall, the paper highlights a disconnect between how rare disease discourse is enacted on YouTube and policy promises of public engagement, with potential spaces for dialogue often closed off by medical authorities. To close, the paper provides recommendations for how policymakers might engage with and facilitate more inclusive forms of social media interaction between specific rare disease related communities and clinicians to develop more meaningful forms of knowledge exchange.

Emerging health data platforms: From individual control to collective data governance

Health data have enormous potential to transform healthcare, health service design, research, and individual health management. However, health data collected by institutions tend to remain siloed within those institutions limiting access by other services, individuals or researchers. Further, health data generated outside health services (e.g., from wearable devices) may not be easily accessible or useable by individuals or connected to other parts of the health system. There are ongoing tensions between data protection and the use of data for the public good (e.g., research). Concurrently, there are a number of data platforms that provide ways to disrupt these traditional health data siloes, giving greater control to individuals and communities. Through four case studies, this paper explores platforms providing new ways for health data to be used for personal data sharing, self-health management, research, and clinical care. The case-studies include data platforms: PatientsLikeMe, Open Humans, Health Record Banks, and unforgettable.me. These are explored with regard to what they mean for data access, data control, and data governance. The case studies provide insight into a shift from institutional to individual data stewardship. Looking at emerging data governance models, such as data trusts and data commons, points to collective control over health data as an emerging approach to issues of data control. These shifts pose challenges as to how “traditional” health services make use of data collected on these platforms. Further, it raises broader policy questions regarding how to decide what public good data should be put towards.

Research data management in health and biomedical citizen science: practices and prospects

Background

Public engagement in health and biomedical research is being influenced by the paradigm of citizen science. However, conventional health and biomedical research relies on sophisticated research data management tools and methods. Considering these, what contribution can citizen science make in this field of research? How can it follow research protocols and produce reliable results?

Objective

The aim of this article is to analyze research data management practices in existing biomedical citizen science studies, so as to provide insights for members of the public and of the research community considering this approach to research.

Methods

A scoping review was conducted on this topic to determine data management characteristics of health and bio medical citizen science research. From this review and related web searching, we chose five online platforms and a specific research project associated with each, to understand their research data management approaches and enablers.

Results

Health and biomedical citizen science platforms and projects are diverse in terms of types of work with data and data management activities that in themselves may have scientific merit. However, consistent approaches in the use of research data management models or practices seem lacking, or at least are not prevalent in the review.

Conclusions

There is potential for important data collection and analysis activities to be opaque or irreproducible in health and biomedical citizen science initiatives without the implementation of a research data management model that is transparent and accessible to team members and to external audiences. This situation might be improved with participatory development of standards that can be applied to diverse projects and platforms, across the research data life cycle.

Can digital health save democracy? Meeting the cosmopolitical challenge of digital worlds

This article explores the challenges and opportunities of social media health activisms to shape public participation in the digital future of healthcare. As health becomes ever more entangled with digital technologies, a growing ecology of digital health services promise greater individual autonomy to learn about and managing medical conditions, as well as accessing health services and engaging in forms of self-care. Cautioning against optimist visions of digital health and their promise of empowerment and autonomy, the article explores how health activisms on social media are reclaiming visions of healthcare that move beyond individual and depoliticised models of health technologies. The notion of cosmopolitics is employed to conceptualise relations between technology and health that implicate human and non-human interests in entanglements between health, morality and technology.

Concealment and discovery: The role of information security in biomedical data re-use

This paper analyses the role of information security (IS) in shaping the dissemination and re-use of biomedical data, as well as the embedding of such data in material, social and regulatory landscapes of research. We consider data management practices adopted by two UK-based data linkage infrastructures: the Secure Anonymised Information Linkage, a Welsh databank that facilitates appropriate re-use of health data derived from research and routine medical practice in the region, and the Medical and Environmental Data Mash-up Infrastructure, a project bringing together researchers to link and analyse complex meteorological, environmental and epidemiological data. Through an in-depth analysis of how data are sourced, processed and analysed in these two cases, we show that IS takes two distinct forms: epistemic IS, focused on protecting the reliability and reusability of data as they move across platforms and research contexts, and infrastructural IS, concerned with protecting data from external attacks, mishandling and use disruption. These two dimensions are intertwined and mutually constitutive, and yet are often perceived by researchers as being in tension with each other. We discuss how such tensions emerge when the two dimensions of IS are operationalized in ways that put them at cross purpose with each other, thus exemplifying the vulnerability of data management strategies to broader governance and technological regimes. We also show that whenever biomedical researchers manage to overcome the conflict, the interplay between epistemic and infrastructural IS prompts critical questions concerning data sources, formats, metadata and potential uses, resulting in an improved understanding of the wider context of research and the development of relevant resources. This informs and significantly improves the reusability of biomedical data, while encouraging exploratory analyses of secondary data sources.