Working Through Ethics Review of Big Data Research Projects: An Investigation into the Experiences of Swiss and American Researchers

Favaretto, Maddalena; Clercq, Eva De; Briel, Matthias; Elger, Bernice Simone

doi:10.1177/1556264620935223

Cited by 12 publications

(8 citation statements)

References 50 publications

(60 reference statements)

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“…While a recent study looked at the experience of Swiss researchers when submitting big data research for ethical review ( Favaretto et al, 2020a ), no study to date has investigated the opinions and perspectives of Cantonal RECs. Therefore, this study aims to fill this gap, complement existing research, and expand knowledge on the topic by engaging with members of Cantonal RECs.…”

Section: Introductionmentioning

confidence: 99%

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ferretti

Ienca

Velarde

et al. 2021

Journal of Empirical Research on Human Research Ethics

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Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.

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Section: Introductionmentioning

confidence: 99%

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ferretti

Ienca

Velarde

et al. 2021

Journal of Empirical Research on Human Research Ethics

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“…These risks can be accentuated when dealing with genomic data, which can be used to identify individuals even more precisely [ 50 ]. Likewise, with big data and machine learning techniques proliferating in social sciences research, it can be difficult to determine whether research protocols fall within the scope of ethics committee purview [ 51 ]. Accordingly, data encrypted using advanced privacy technologies such as HE will not be anonymised where the entity holding that data possesses a method to decrypt it.…”

Section: Discussionmentioning

confidence: 99%

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

2022

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Background Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and processing of patient data, allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland’s geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations. Methods To conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform. Results For our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation. Conclusion Our findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies.

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“…Digital research has in fact changed the traditional research subject/investigator dynamic [18] by introducing other factors/actors in the process (social media platforms, private firms etc.) and therefore raises ethical challenges for which researchers do not always have the necessary skills to either anticipate or face [25,43]. To the best of our knowledge, it seems that this aspect of responsibility has not yet entered the ethics debate.…”

Section: Discussionmentioning

confidence: 99%

“…We believe that academic investigators should not bear all the responsibility of the ethical design of research projects alone, or singularly confront themselves with the ethical implications of digital research [57]. At the moment, models of consultancy between ethics committees and researchers are advocated to assist investigators foresee ethical issues [25,43]. These models, together with the implementation of sustainable and transparent collaboration/partnership with data holders and owners [58], could assist the creation of appropriate paradigms of shared responsibility that could definitely play a significant role in the development of ethically sound research projects.…”

Section: Discussionmentioning

confidence: 99%

“…We decided to focus on behavioral sciences, specifically phycology and sociology, for two main reasons. First, the larger research project aimed at investigating the challenges introduced by Big Data methods for regulatory bodies such as Research Ethics Committees (RECs) and Institutional Review Boards (IRBs) [25]. Both in Switzerland and the United States, Big Data research methods in these two fields are questioning the concept of human research subject-due to the increased distance and detachment between research subjects and investigators brought by digitalized means for data collection (e.g.…”

Section: Methodsmentioning

confidence: 99%

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First do no harm: An exploration of researchers’ ethics of conduct in Big Data behavioral studies

et al. 2020

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Research ethics has traditionally been guided by well-established documents such as the Belmont Report and the Declaration of Helsinki. At the same time, the introduction of Big Data methods, that is having a great impact in behavioral research, is raising complex ethical issues that make protection of research participants an increasingly difficult challenge. By conducting 39 semi-structured interviews with academic scholars in both Switzerland and United States, our research aims at exploring the code of ethics and research practices of academic scholars involved in Big Data studies in the fields of psychology and sociology to understand if the principles set by the Belmont Report are still considered relevant in Big Data research. Our study shows how scholars generally find traditional principles to be a suitable guide to perform ethical data research but, at the same time, they recognized and elaborated on the challenges embedded in their practical application. In addition, due to the growing introduction of new actors in scholarly research, such as data holders and owners, it was also questioned whether responsibility to protect research participants should fall solely on investigators. In order to appropriately address ethics issues in Big Data research projects, education in ethics, exchange and dialogue between research teams and scholars from different disciplines should be enhanced. In addition, models of consultancy and shared responsibility between investigators, data owners and review boards should be implemented in order to ensure better protection of research participants.

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Working Through Ethics Review of Big Data Research Projects: An Investigation into the Experiences of Swiss and American Researchers

Cited by 12 publications

References 50 publications

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

First do no harm: An exploration of researchers’ ethics of conduct in Big Data behavioral studies

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