Optimising cohort data in Europe

We outlined the contradictory interaction between the GDPR and the data-intensive cohort research related to digital data collection technologies. As preliminary measures we propose the following: y y The conditions and modalities of consent should be carefully considered and identified in relation to participants' social, cultural and material environments. In particular, researchers should ensure that participants' consent is based on their understanding of the research project rather than on societal and cultural constraints inherent to digital data collection technologies (i.e. some data collection technologies such as social media may incite participants to participate for social conformity reasons). y y Researchers, data controllers and research institutions should assess the integration potential of data from digital technologies with public health records and national health systems. This would facilitate the formulation of generalised health prevention and health surveillance strategies. y y Purely individualised, "consumer-based" conceptualisations of participants' contributions should be jettisoned in favour of a more relational approach where the iterative relationship between the participants, their immediate environment, the researchers and the structural characteristics of digital devices plays a central role. For instance, wearable technologies have structural characteristics that favour the commitment of informed, knowledgeable and interested participant communities in relation to specific alignments. The role of researchers and data controllers is thus to favour and support such agency through appropriate access arrangements. References Aiello AE, Renson A, Zivich PN. Social media- and Internet-based disease surveillance for public health. Annual Review of Public Health 2020;41:101-118. https://doi. org/10.1146/annurev-publhealth-040119-094402 Appelbaum PS, Parens E, Berger SM, Chung WK, Burke W. Is there a duty to reinterpret genetic data? The ethical dimensions. Genetics in Medicine 2020;22(3):633-639. https://doi.org/10.1038/s41436-019-0679-7 Beyan O, Choudhury A, van Soest J, Kohlbacher O, Zimmermann L, Stenzhorn H, ... & Dekker A. Distributed analytics on sensitive medical data: The Personal Health Train. Data Intelligence 2020; 2(1-2), 96-107. https://doi.org/10.1162/dint_a_00032 Bialke M, Bahls T, Geidel L, Rau H, Blumentritt A, Pasewald S, et al. MAGIC: once upon a time in consent management-a FHIR® tale. Journal of Translational Medicine 2018;16(1):256. https://doi.org/10.1186/s12967-018-1631-3