Powered by ‘big health data’ and enormous gains in computing power, artificial intelligence and related technologies are already changing the healthcare landscape. Harnessing the potential of these technologies will necessitate partnerships between health institutions and commercial companies, particularly as it relates to sharing health data. The need for commercial companies to be trustworthy users of data has been argued to be critical to the success of this endeavour. I argue that this approach is mistaken. Our interactions with commercial companies need (...) not, and should not, be based on trust. Rather, they should be based on confidence. I begin by elucidating the differences between trust, reliability, and confidence, and argue that trust is not the appropriate attitude to adopt when it comes to sharing data with commercial companies. I argue that what we really should want is confidence in a system of data sharing. I then provide an outline of what a confidence-worthy system of data sharing with commercial companies might look like, and conclude with some remarks about the role of trust within this system. (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)

The development and use of large and dynamic health data repositories designed to support research pose challenges to traditional informed consent models. We used semi-structured interviewing to elicit diverse research stakeholders' views of a model of consent appropriate to participation in initiatives that entail collection, long-term storage, and undetermined future research use of multiple types of health data. We demonstrate that, when considering health data repositories, research stakeholders replace a concept of consent as informed with one in which consent is (...) engaged. In engaged consent, a participant's ongoing relationship with a repository serves as a substitute or adjunct to information exchange at enrollment. We detail research stakeholders' views of the risks of engaged consent and suggest questions for further study about engagement and consent procedures in initiatives that aim to store data for future unspecified research purposes. (shrink)

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)

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call “demonstrated consent” that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its metadata (...) information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples. (shrink)

In clinical research – whether pharmaceutical, genetic or biomarker research – it is important to protect research participants’ autonomy and to ensure or strengthen their control over health-related decisions. Empirical–ethical studies have argued that both the ethical concept and the current legalistic practice of informed consent should be adapted to the complexity of the clinical environment. For this, a better understanding of recruitment, for which also the physician–patient relationship plays an important role, is needed.Our aim is to ethically reflect communication (...) processes by identifying patterns used by physicians to motivate patients’ participation in clinical research and to assess whether patients also use these patterns in formulating their own research motivation. We conducted a secondary analysis with empirical data from a research project involving physicians and patients in a clinical research setting of a biomarker study for rectal cancer treatment. Our empirical data included observations of physician–patient consultations ( n = 54) and semi-structured interviews with patients ( n = 40). Overall, we collected 93 interviews.We found two dominant communication patterns, which physicians applied for motivating patients to take part in this research study. Some forms of these patterns tend to mislead patients’ understanding, while others could justifiably be applied in this consultation setting without undermining patients’ autonomy. This insight that the physician–patient communication has a strong influence on patients increases the importance to strengthen physicians’ ethically acceptable communication patterns regarding research participation.We further suggest that there is a need for a critical reflection of the ethics committee’s requirements for information regarding research participation. (shrink)

BackgroundThe advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, particularly research activities. Current consent models in Quebec were not established with the context of LHSs in mind and do not support the agility and transparency required to obtain consent from all involved, especially the citizens. Therefore, a new approach to consent is needed. Previous work identified the meta-consent model as a promising (...) alternative to fulfill the requirements of LHSs, particularly large-scale deployments. We elicited the public’s attitude toward the meta-consent model to evaluate if the model could be understood by the citizens and would be deemed acceptable to prepare for its possible implementation in Quebec.MethodsEight focus groups, with a total of 63 members of the general public from various backgrounds were conducted in Quebec, Canada, in 2019. Explicit attention was given to literacy levels, language spoken at home and rural vs urban settings. We assessed attitudes, concerns and facilitators regarding key components of the meta-consent model: predefined categories to personalized consent requests, a dynamic web-based infrastructure to record meta-consent, and default settings. To analyse the discussions, a thematic content analysis was performed using a qualitative software.ResultsOur findings showed that participants were supportive of this new approach of consent as it promotes transparency and offers autonomy for the management of their health data. Key facilitators were identified to be considered in the implementation of a meta-consent model in the Quebec LHSs: information and transparency, awareness campaigns, development of educational tools, collaboration of front-line healthcare professionals, default settings deemed acceptable by the society as well as close partnerships with recognized and trusted institutions.ConclusionsThis qualitative study reveals the openness of a sample of the Quebec population regarding the meta-consent model for secondary use of health data for research. This first exploratory study conducted with the public is an important step in guiding decision-makers in the next phases of implementing the various strategies to support access and use of health data in Quebec. (shrink)

Recital 33 GDPR has often been interpreted as referring to ‘broad consent’. This version of informed consent was intended to allow data subjects to provide their consent for certain areas of research, or parts of research projects, conditional to the research being in line with ‘recognised ethical standards’. In this article, we argue that broad consent is applicable in the emerging field of Computational Social Science (CSS), which lies at the intersection of data science and social science. However, the lack (...) of recognised ethical standards specific to CSS poses a practical barrier to the use of broad consent in this field and other fields that lack recognised ethical standards. Upon examining existing research ethics standards in social science and data science, we argue that they are insufficient for CSS. We further contend that the fragmentation of European Union (EU) law and research ethics sources makes it challenging to establish universally recognised ethical standards for scientific research. As a result, CSS researchers and other researchers in emerging fields that lack recognised ethical standards are left without sufficient guidance on the use of broad consent as provided for in the GDPR. We conclude that responsible EU bodies should provide additional guidance to facilitate the use of broad consent in CSS research. (shrink)

BackgroundLimited research has been conducted on explanations and understandings of biobanking for future genomic research in African contexts with low literacy and limited healthcare access. We report on the findings of a sub-study on participant understanding embedded in a multi-disease community health screening and biobank platform study known as ‘Vukuzazi’ in rural KwaZulu-Natal, South Africa.MethodsSemi-structured interviews were conducted with research participants who had been invited to take part in the Vukuzazi study, including both participants and non-participants, and research staff that (...) worked on the study. The interviews were transcribed, and themes were identified from the interview transcripts, manually coded, and thematically analysed.ResultsThirty-nine individuals were interviewed. We found that the research team explained biobanking and future genomic research by describing how hereditary characteristics create similarities among individuals. However, recollection and understanding of this explanation seven months after participation was variable. The large volume of information about the Vukuzazi study objectives and procedures presented a challenge to participant recall. By the time of interviews, some participants recalled rudimentary facts about the genetic aspects of the study, but many expressed little to no interest in genetics and biobanking.ConclusionParticipant’s understanding of information related to genetics and biobanking provided during the consent process is affected by the volume of information as well as participant’s interest in the subject matter being discussed. We recommend that future studies undertaking biobanking and genomic research treat explanations of this kind of research to participants as an on-going process of communication between researchers, participants and the community and that explanatory imagery and video graphic storytelling should be incorporated into theses explanations as these have previously been found to facilitate understanding among those with low literacy levels. Studies should also avoid having broader research objectives as this can divert participant’s interest and therefore understanding of why their samples are being collected. (shrink)