Participant-driven research is a burgeoning domain of research innovation, often facilitated by mobile technologies. Return of results and data are common hallmarks, grounded in transparency and data democracy. PDR has much to teach traditional research about these practices and successful engagement. Recommendations calling for new state laws governing research with mHealth modalities common in PDR and federal creation of review mechanisms, threaten to stifle valuable participant-driven innovation, including in return of results.

Biomedical research using data from participants’ mobile devices borrows heavily from the ethos of the “citizen science” movement, by delegating data collection and transmission to its volunteer subjects. This engagement gives volunteers the opportunity to feel like partners in the research and retain a reassuring sense of control over their participation. These virtues, in turn, give both grass-roots citizen science initiatives and institutionally sponsored mHealth studies appealing features to flag in recruiting participants from the public. But while grass-roots citizen science (...) projects are often community-based, mHealth research ultimately depends on the individuals who own and use mobile devices. This inflects the ethos of mHealth research towards a celebration of individual autonomy and empowerment, at the expense of its implications for the communities or groups to which its individual participants belong. But the prospects of group harms — and benefits — from mHealth research are as vivid as they are in other forms of data-intensive “precision health” research, and will be important to consider in the design of any studies using this approach. (shrink)

To address the ethical challenges in big data health research we propose the concept of systemic oversight. This approach is based on six defining features and aims at creating a common ground across the oversight pipeline of biomedical big data research. Current trends towards enhancing granularity of informed consent and specifying legal provisions to address informational privacy and discrimination concerns in data-driven health research are laudable. However, these solutions alone cannot have the desired impact unless oversight activities by different stakeholders (...) acquire a common substantive orientation. (shrink)

Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within (...) a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research—among researchers and with data subjects—is grounded in trust, which should be more explicitly recognised in the governance of health data research. (shrink)

Precision medicine research involving human biological material is becoming an increasingly central component of healthcare, and its potential is quickly growing due to rapid technological progress...

Count Me In (CMI) was launched in 2015 as a patient-driven research initiative aimed at accelerating the study of cancer genomics through direct participant engagement, electronic consent and open-access data sharing. It is an example of a large-scale direct-to-patient (DTP) research project which has since enrolled thousands of individuals. Within the broad scope of ‘citizen science’, DTP genomics research is defined here as a specific form of ‘top-down’ research endeavour developed and overseen by institutions within the traditional human subjects research (...) context; in novel ways, it engages and recruits patients with defined diseases, consents them for medical information and biospecimens sharing, and stores and disseminates genomic information. Importantly, these projects simultaneously aim to empower participants in the research process while increasing sample size, particularly in rare disease states. Using CMI as a case study, this paper discusses how DTP genomics research raises new questions in the context of traditional human subjects research ethics, including issues surrounding participant selection, remote consent, privacy and return of results. It aims to demonstrate how current research ethics frameworks may be insufficient in this context, and that institutions, institutional review boards and investigators should be aware of these gaps and their role in ensuring the conduct of ethical, novel forms of research together with participants. Ultimately, a broader question is raised of whether the rhetoric of participatory genomics research advocates for an ethic of personal and social duty for contributing to the advancement of generalisable knowledge about health and disease. (shrink)

Gifts have served as a fundamental aspect of the human experience across time, even as their precise roles and functions have shifted. In the past, bioethicists and others have drawn upon anthropol...

Massive amounts of data are collected and stored on a routine basis in virtually all domains of human activities. Such data are potentially useful to biomedicine. Yet, access to data for research purposes is hindered by the fact that different kinds of individual-patient data reside in disparate, unlinked silos. We propose that data cooperatives can promote much needed data aggregation and consequently accelerate research and its clinical translation. Data cooperatives enable direct control over personal data, as well as more democratic (...) governance of data pools. This model can realize a specific kind of data economy whereby citizens and communities are empowered to steer data use according to their motivations, preferences, and concerns. Policy makers can promote this model by recognizing citizens’ rights to access and to obtain a copy of their own data, and by funding distributed data infrastructures piloting new data aggregation models. (shrink)

In this Symposium on the Ethics and Epistemology of Big Data, we present four perspectives on the ways in which the rapid growth in size of research databanks—i.e. their shift into the realm of “big data”—has changed their moral, socio-political, and epistemic status. While there is clearly something different about “big data” databanks, we encourage readers to place the arguments presented in this Symposium in the context of longstanding debates about the ethics, politics, and epistemology of biobank, database, genetic, and (...) epidemiological research. (shrink)

The research ethics framework put forward by McCradden et al. to support systematic inquiry in the development of artificial intelligence and machine learning technologies in healt...

As donor trust legitimises research, trust is vital for research in the fields of biomedicine, genetics, translational medicine and personalised medicine. For parts of the donor community, the consent signature is a sign of trust in research. Many consent processes in biomedical research ask donors to provide their data for an unspecified future use, which introduces uncertainty of the unknown. This uncertainty can jeopardise donor trust or demand blind trust. But which donor wants to trust blindly? To reduce this uncertainty, (...) we explore first, which future-proof actors donors could trust when signing a consent form. Second, we discuss the question Can we know if donor trust expires? and what prevents donor trust from expiring. Finally, we present possible measures that can help to nurture trust in the far future. In this article, we draw on our previous research on trust in biomedical research, on trust in the broader healthcare system and Niklas Luhmann’s and Anthony Giddens’ trust theories. Our findings suggest that, in the far future, researchers will need to consider donor autonomy, as well as societal norms and values of the time period in which the data were donated. They will need to find mechanisms where possible to publicly announce the use of old data sets. However, foremost researchers will need to treat the data respectfully. It remains vital that professionals and the society continue to elaborate on the norms and values that shape the common understanding of what is morally right and wrong when researching data. (shrink)

In this paper, we discuss how access to health-related data by private insurers, other than affecting the interests of prospective policy-holders, can also influence their propensity to make personal data available for research purposes. We take the case of national precision medicine initiatives as an illustrative example of this possible tendency. Precision medicine pools together unprecedented amounts of genetic as well as phenotypic data. The possibility that private insurers could claim access to such rapidly accumulating biomedical Big Data or to (...) health-related information derived from it would discourage people from enrolling in precision medicine studies. Should that be the case, the economic value of personal data for the insurance industry would end up affecting the public value of data as a scientific resource. In what follows we articulate three principles – trustworthiness, openness and evidence – to address this problem and tame its potentially harmful effects on the development of precision medicine and, more generally, on the advancement of medical science. (shrink)

New models of data governance for health data are a focus of growing interest in an era of challenge to the social licence. In this article, we reflect on what the data trust model, which is founded on principles of participatory governance, can learn from experiences of involving and engagement of members of the public and participants in the governance of large-scale biobanks. We distinguish between upstream and ongoing governance models, showing how they require careful design and operation if they (...) are to deliver on aspirations for deliberation and participation. Drawing on this learning, we identify a set of considerations important to future design for data trusts as they seek to ensure just, proportionate and fair governance. These considerations relate to the timing of involvement of participants, patterns of inclusion and exclusion, and responsiveness to stakeholder involvement and engagement. We emphasise that the evolution of governance models for data should be matched by a commitment to evaluation. (shrink)