The Ethics Ecosystem: Personal Ethics, Network Governance and Regulating Actors Governing the Use of Social Media Research Data

Governance of research and product improvement studies in consumer mental health apps. Interviews with researchers and app developers

Consumer mental health apps (MHAs) collect and generate mental health-related data on their users, which can be leveraged for research and product improvement studies. Such studies are associated with ethical issues that may be difficult for researchers and app developers to assess. To improve ethical study conduct, governance through rules, agreements and customs could be relied upon, but their translation into practice is subject to barriers. This qualitative interview study with 17 researchers and app developers looked into the role and impact of governance standards on consumer MHA studies. Interviewees experienced a significant number of rules, agreements and customs, although not all of the governance standards that can potentially be applicable. Standards did have an impact on the interests of researchers and app developers, app users and society, but this impact was mediated by several barriers related to their conceptualization and implementation. Conceptualization barriers impacted the development of a standard, the inclusion of relevant concepts and the coordination between standards. Implementation barriers concerned the resource cost of understanding a standard, as well as suboptimal enforcement. The framework developed in this study can support more effective efforts to improve the governance of future consumer MHA studies.

UK health researchers' considerations of the environmental impacts of their data-intensive practices and its relevance to health inequities

BACKGROUND

The health sector aims to improve health outcomes and access to healthcare. At the same time, the sector relies on unsustainable environmental practices that are increasingly recognised to be catastrophic threats to human health and health inequities. As such, a moral imperative exists for the sector to address these practices. While strides are currently underway to mitigate the environmental impacts of healthcare, less is known about how health researchers are addressing these issues, if at all.

METHODS

This paper uses an interview methodology to explore the attitudes of UK health researchers using data-intensive methodologies about the adverse environmental impacts of their practices, and how they view the importance of these considerations within wider health goals.

RESULTS

Interviews with 26 researchers showed that participants wanted to address the environmental and related health harms associated with their research and they reflected on how they could do so in alignment with their own research goals. However, when tensions emerged, their own research was prioritised. This was related to their own desires as researchers and driven by the broader socio-political context of their research endeavours.

CONCLUSION

To help mitigate the environmental and health harms associated with data-intensive health research, the socio-political context of research culture must be addressed.

Ethical and legal considerations in social media research for health technology assessment: conclusions from a scoping review

OBJECTIVES

The objective was to identify and describe the published guidance and current academic discourse of ethical issues and standards related to the use of Social Media Research for generating patient insights for the use by health technology assessment (HTA) or health policy decisions.

METHODS

A scoping review of the literature was conducted in PubMed and Embase and identified 935 potential references published between January 2017 and June 2021. After title and abstract screening by three reviewers, 40 publications were included, the relevant information was extracted and data were collected in a mind map, which was then used to structure the output of the review.

RESULTS

Social Media Research may reveal new insights of relevance to HTA or health policies into patient needs, patient experiences, or patient behaviors. However, the research approaches, methods, data use, interpretation, and communication may expose those who post the data in social media channels to risks and potential harms relating to privacy, anonymity/confidentiality, authenticity, context, and rapidly changing technologies.

CONCLUSIONS

An actively engaged approach to ensuring ethical innocuousness is recommended that carefully follows best practices throughout planning, conduct, and communication of the research. Throughout the process and as a follow-up, there should be a discourse with the ethical experts to maximally protect the current and future users of social media, to support their trust in the research, and to advance the knowledge in parallel to the advancement of the media themselves, the technologies, and the research tools.

Access to Biobanks: Responsibilities Within a Research Ecosystem

The past few decades have seen rapid increases in the size and scope of biobanks, with large-scale publicly funded ventures supporting health-related research becoming the norm. As these biobanks are increasingly asked to share their data, including for example, genome-wide analyses, questions arise about how such decisions are made, including whether applicants' research aligns with the aims of the biobank. To better understand how biobanks make decisions relating to their data use, we sought the views and experiences of those involved in decision-making relating to data access at 11 large-scale publicly funded health biobanks. We were particularly interested in how potentially contentious applications were approached. Interviewees had some concerns about decisions on applications they felt their governance structures could not reach. We ask broader questions about the responsibility of those involved in biobank access decisions-those working early in the research process-when considering such issues.

Bio-Ethics and One Health: A Case Study Approach to Building Reflexive Governance

Surveillance programs supporting the management of One Health issues such as antibiotic resistance are complex systems in themselves. Designing ethical surveillance systems is thus a complex task (retroactive and iterative), yet one that is also complicated to implement and evaluate (e.g., sharing, collaboration, and governance). The governance of health surveillance requires attention to ethical concerns about data and knowledge (e.g., performance, trust, accountability, and transparency) and empowerment ethics, also referred to as a form of responsible self-governance. Ethics in reflexive governance operates as a systematic critical-thinking procedure that aims to define its value: What are the “right” criteria to justify how to govern “good” actions for a “better” future? The objective is to lay the foundations for a methodological framework in empirical bioethics, the rudiments of which have been applied to a case study to building reflexive governance in One Health. This ongoing critical thinking process involves “mapping, framing, and shaping” the dynamics of interests and perspectives that could jeopardize a “better” future. This paper proposes to hybridize methods to combine insights from collective deliberation and expert evaluation through a reflexive governance functioning as a community-based action-ethics methodology. The intention is to empower individuals and associations in a dialogue with society, which operation is carried out using a case study approach on data sharing systems. We based our reasoning on a feasibility study conducted in Québec, Canada (2018–2021), envisioning an antibiotic use surveillance program in animal health for 2023. Using the adaptive cycle and governance techniques and perspectives, we synthesize an alternative governance model rooted in the value of empowerment. The framework, depicted as a new “research and design (R&D)” practice, is linking operation and innovation by bridging the gap between Reflexive, Evaluative, and Deliberative reasonings and by intellectualizing the management of democratizing critical thinking locally (collective ethics) by recognizing its context (social ethics). Drawing on the literature in One Health and sustainable development studies, this article describes how a communitarian and pragmatic approach can broaden the vision of feasibility studies to ease collaboration through public-private-academic partnerships. The result is a process that “reassembles” the One Health paradigm under the perspective of global bioethics to create bridges between the person and the ecosystem through pragmatic ethics.

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

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.

Research Ethical Norms, Guidance and the Internet

The internet, either as a tool or as an area of research, adds moral worries to an already complicated research ethical backdrop. Agencies, professional associations and philosophers have formulated research ethical norms designed to help scientists to arrive at responsible solutions to the problems. Yet, many criticize this reliance on norms. Somewhat more precisely, many claim that research ethical norms do not offer guidance. In the literature at least three arguments to that effect can be found. First, the research ethical norms fail to guide since they are inconsistent. Second, they fail to guide since they are too opaque. Third, they fail to guide since they cannot handle the moral complexity of issues scientists doing e-research face. In this paper I argue that these arguments are weak. The arguments are, in their original formulations, rather unclear. I try to improve the situation by spelling out the arguments with reference to a certain set of research ethical norms, to a certain account of action-guidance and with reference to certain important distinctions. It then turns out that the arguments' premises are either untenable or suffers from lack of relevance. The arguments do not force us to conclude that research ethical norms fail to guide.

Comparative analysis of regulatory framework on biobanking to inform policymakers in Central America and the Dominican Republic

Background.  The clinical and scientific importance of biobanks has been highlighted.  Ethical governance and regulatory oversight for biobanks should be in place to preserve and promote ethical and responsible conduct of research. Methods. This is an analytical documentary study of the regulatory scope concerning biobanks in Central America and the Dominican Republic. From the International Compilation of Human Research Standards 2020 edition of the Office of Human Research Protection Department of Health and Human Services of the United States of America identified the existing guidelines applicable to human research in each of the eight SICA member countries. Regulatory aspects searched for and the analysis was based on the recommendations set forth in Guideline 11 on the collection, storage, and use of biological materials and related data in the International Ethical Guidelines for Research Related to Human Health. Results. There is a lack of specific guidelines for the collection, use, and storage of human biological materials for research purposes, and the creation of biobanks in the countries been studied. No country in Central America and the Dominican Republic region has specific regulations for the creation of biobanks for research purposes. The term "biobank" was not found in the revised regulations. However, there are good examples of ethical governance of research in general in the region been Costa Rica, Panamá, and Guatemala examples of advances towards this direction. Conclusions. There is a need to move forward the governance and regulatory framework of biobanks in Central America and the Dominican which can be seen as an opportunity for international cooperation and regulatory collaborative agenda within this region.

Ethics review of big data research: What should stay and what should be reformed?

BACKGROUND

Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts.

MAIN TEXT

In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science.

CONCLUSIONS

We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.

Governing AI-Driven Health Research: Are IRBs Up to the Task?

Many are calling for concrete mechanisms of oversight for health research involving artificial intelligence (AI). In response, institutional review boards (IRBs) are being turned to as a familiar model of governance. Here, we examine the IRB model as a form of ethics oversight for health research that uses AI. We consider the model's origins, analyze the challenges IRBs are facing in the contexts of both industry and academia, and offer concrete recommendations for how these committees might be adapted in order to provide an effective mechanism of oversight for health-related AI research.

Population health AI researchers' perceptions of the public portrayal of AI: A pilot study

This article reports how 18 UK and Canadian population health artificial intelligence researchers in Higher Education Institutions perceive the use of artificial intelligence systems in their research, and how this compares with their perceptions about the media portrayal of artificial intelligence systems. This is triangulated with a small scoping analysis of how UK and Canadian news articles portray artificial intelligence systems associated with health research and care. Interviewees had concerns about what they perceived as sensationalist reporting of artificial intelligence systems - a finding reflected in the media analysis. In line with Pickersgill's concept of 'epistemic modesty', they considered artificial intelligence systems better perceived as non-exceptionalist methodological tools that were uncertain and unexciting. Adopting 'epistemic modesty' was sometimes hindered by stakeholders to whom the research is disseminated, who may be less interested in hearing about the uncertainties of scientific practice, having implications on both research and policy.

Responsible Open Science: Moving towards an Ethics of Environmental Sustainability

The integration of open science as a key pillar of responsible research and innovation has led it to become a hallmark of responsible research. However, ethical, social and regulatory challenges still remain about the implementation of an internationally- and multi-sector-recognised open science framework. In this Commentary, we discuss one important specific challenge that has received little ethical and sociological attention in the open science literature: the environmental impact of the digital infrastructure that enables open science. We start from the premise that a move towards an environmentally sustainable open science is a shared and valuable goal, and discuss two challenges that we foresee with relation to this. The first relates to questions about how to define what environmentally sustainable open science means and how to change current practices accordingly. The second relates to the infrastructure needed to enact environmentally sustainable open science ethical and social responsibilities through the open science ethics ecosystem. We argue that there are various ethical obstacles regarding how to responsibly balance any environmental impacts against the social value of open science, and how much one should be prioritised over the other. We call for all actors of the open science ethics ecosystem to engage in discussions about how to move towards open data and science initiatives that take into account the environmental impact of data and digital infrastructures. Furthermore, we call for ethics governance frameworks or policy-inscribed standards of practice to assist with this decision-making.

Points of contention: Qualitative research identifying where researchers and research ethics committees disagree about consent waivers for secondary research with tissue and data

Background

This is a multi-method, in-depth, three part qualitative study exploring the regulation and practice of secondary research with tissue and data in a high-income country. We explore and compare the perspectives of researchers, research ethics committees (RECs) and other relevant professionals (e.g. pathologists and clinicians). We focus on points of contention because they demonstrate misalignment between the expectations, values and assumptions of these stakeholders.

Methods

This is a multi-method study using observational research, focus groups and interviews with 42 participants (conducted 2016–2017) and analyzed using thematic analysis.

Results

Results are arranged under the following themes: consent; balancing the social value of the research with consent requirements; and harm. Our findings demonstrate different perspectives on the review process, styles of ethical reasoning and issues of concern. First, researchers and RECs disagreed about whether the cost of re-consenting patients satisfied the criterion of impracticability for consent waivers. Second, most researchers were skeptical that secondary research with already collected tissue and data could harm patients. Researchers often pointed to the harm arising from a failure to use existing material for research. RECs were concerned about the potential for secondary research to stigmatize communities. Third, researchers adopted a more consequentialist approach to decision-making, including some willingness to trade off the benefit of the research against the cost of getting consent; whereas RECs were more deontological and typically considered research benefit only after it had been established that re-consent was impractical.

Conclusion

This research highlights ways in which RECs and researchers may be talking past each other, resulting in confusion and frustration. These finding provide a platform for realignment of the expectations of RECs and researchers, which could contribute to making research ethics review more effective.

Reasoning "Uncharted Territory": Notions of Expertise Within Ethics Review Panels Assessing Research Use of Social Media

The fast changing field of social media (SM) research presents unique challenges for research ethics committees (RECs). This article examines notions of experience and expertise in the context of REC members reviewing proposals for SM research and considers the role of the RECs in this area of review. We analyze 19 interviews with REC members to highlight that a lack of personal and professional experience of SM, compounded by a lack of institutional and professional guidelines, mean many REC members feel they do not possess sufficient expertise to review SM research. This view was supported by 14 interviews with SM researchers. REC members drew on strategies to overcome their lack of experience, although most SM researchers still found this problematic, to varying degrees. We recommend several steps to ensure REC expertise in SM research keeps pace of this fast-developing field, taking a pro-active, dialogic approach.

Automating Dynamic Consent Decisions for the Processing of Social Media Data in Health Research

Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even obtained, are typically broad and inflexible, or place a significant burden on the participant. Machine learning algorithms show much promise for facilitating a "middle-ground" approach: using trained models to predict and automate granular consent decisions. Such techniques, however, raise a myriad of follow-on ethical and technical considerations. In this article, we present an exploratory user study (n = 67) in which we find that we can predict the appropriate flow of health-related social media data with reasonable accuracy, while minimizing undesired data leaks. We then attempt to deconstruct the findings of this study, identifying and discussing a number of real-world implications if such a technique were put into practice.

Defining ethical standards for the application of digital tools to population health research

There is growing interest in population health research, which uses methods based on artificial intelligence. Such research draws on a range of clinical and non-clinical data to make predictions about health risks, such as identifying epidemics and monitoring disease spread. Much of this research uses data from social media in the public domain or anonymous secondary health data and is therefore exempt from ethics committee scrutiny. While the ethical use and regulation of digital-based research has been discussed, little attention has been given to the ethics governance of such research in higher education institutions in the field of population health. Such governance is essential to how scholars make ethical decisions and provides assurance to the public that researchers are acting ethically. We propose a process of ethics governance for population health research in higher education institutions. The approach takes the form of review after the research has been completed, with particular focus on the role artificial intelligence algorithms play in augmenting decision-making. The first layer of review could be national, open-science repositories for open-source algorithms and affiliated data or information which are developed during research. The second layer would be a sector-specific validation of the research processes and algorithms by a committee of academics and stakeholders with a wide range of expertise across disciplines. The committee could be created as an off-shoot of an already functioning national oversight body or health technology assessment organization. We use case studies of good practice to explore how this process might operate.