The goal of this article is to present a first list of ethical concerns that may arise from research and personal use of virtual reality (VR) and related technology, and to offer concrete recommendations for minimizing those risks. Many of the recommendations call for focused research initiatives. In the first part of the article, we discuss the relevant evidence from psychology that motivates our concerns. In Section “Plasticity in the Human Mind,” we cover some of the main results suggesting that (...) one’s environment can influence one’s psychological states, as well as recent work on inducing illusions of embodiment. Then, in Section “Illusions of Embodiment and Their Lasting Effect,” we go on to discuss recent evidence indicating that immersion in VR can have psychological effects that last after leaving the virtual environment. In the second part of the article, we turn to the risks and recommendations. We begin, in Section “The Research Ethics of VR,” with the research ethics of VR, covering six main topics: the limits of experimental environments, informed consent, clinical risks, dual-use, online research, and a general point about the limitations of a code of conduct for research. Then, in Section “Risks for Individuals and Society,” we turn to the risks of VR for the general public, covering four main topics: long-term immersion, neglect of the social and physical environment, risky content, and privacy. We offer concrete recommendations for each of these 10 topics, summarized in Table 1. (shrink)

Health research increasingly relies on organized collections of health data and biological samples. There are many types of sample and data collections that are used for health research, though these are collected for many purposes, not all of which are health-related. These collections exist under different jurisdictional and regulatory arrangements and include: 1) Population biobanks, cohort studies, and genome databases 2) Clinical and public health data 3) Direct-to-consumer genetic testing 4) Social media 5) Fitness trackers, health apps, and biometric data (...) sensors Population biobanks, cohort studies, and genome databases Clinical and public health data Direct-to-consumer genetic testing Social media Fitness trackers, health apps, and biometric data sensors Ethical, legal, and social challenges of such collections are well recognized, but there has been limited attention to the broader societal implications of the existence of these collections. Although health research conducted using these collections is broadly recognized as beneficent, secondary uses of these data and samples may be controversial. We examine both documented and hypothetical scenarios of secondary uses of health data and samples. In particular, we focus on the use of health data for purposes of: Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes Current safeguards relating to the use of health data and samples include research ethics oversight and privacy laws. These safeguards have a strong focus on informed consent and anonymization, which are aimed at the protection of the individual research subject. They are not intended to address broader societal implications of health data and sample collections. As such, existing arrangements are insufficient to protect against subversion of health databases for non-sanctioned secondary uses, or to provide guidance for reasonable but controversial secondary uses. We are concerned that existing debate in the scholarly literature and beyond has not sufficiently recognized the secondary data uses we outline in this paper. Our main purpose, therefore, is to raise awareness of the potential for unforeseen and unintended consequences, in particular negative consequences, of the increased availability and development of health data collections for research, by providing a comprehensive review of documented and hypothetical non-health research uses of such data. (shrink)

Together with large biobanks of human samples, medical registries with aggregated data from many clinical centers are vital parts of an infrastructure for maintaining high standards of quality with regard to medical diagnosis and treatment. The rapid development in personalized medicine and pharmaco-genomics only underscores the future need for these infrastructures. However, registries and biobanks have been criticized as constituting great risks to individual privacy. In this article, I suggest that quality with regard to diagnosis and treatment is an inherent, (...) morally normative requirement of health care, and argue that quality concerns in this sense may be balanced with privacy concerns. (shrink)

Background The ownership status of individual-level health data affects the manner in which it is used. In this paper we analyze two competing models of the ownership status of the data discussed in the literature recently: private ownership and public ownership. Main body In this paper we describe the limitations of these two models of data ownership with respect to individual-level health data, in particular in terms of ethical principles of justice and autonomy, risk mitigation, as well as technological, economic, (...) and conceptual issues. We argue that undifferentiated application of neither private ownership nor public ownership will allow us to resolve all the problems associated with effective, equitable, and ethical use of data. We suggest that, instead of focusing on data ownership, we should focus on the institutional and procedural aspects of data governance, such as using Data Access Committees (DACs) or equivalent managed access processes, which can balance the elements of these two ownership frameworks. Conclusion Undifferentiated application of the ownership concept (private or public) is not helpful in resolving problems associated with sharing individual-level health data. DACs or equivalent managed access processes should be an integral part of data governance. They can approve or disapprove data access requests after considering the potential benefits and harms to data subjects, their communities, primary researchers, and the wider society. (shrink)

Clinicians and administrators have a professional obligation to contribute (OTC) to improvement of healthcare quality. At the same time, participation in embedded research poses risks to healthcare institutions. Disclosure of an institution’s sensitive information could endanger relationships with patients and undermine its reputation. The existing ethical framework (EF) for learning healthcare systems (LHSs) does not address the conflict between the OTC and institutional interests. Ethical guidance and policy regulation are needed to create a safe environment for embedded research. In this (...) article we analyse the EF for LHSs and the concept of professionalism. We suggest that the EF should be supplemented with an obligation to protect provider’s legitimate interests. We define legitimate interests as those that enable providers to discharge their primary duties. We argue that both the OTC and the obligation to protect legitimate interests are grounded in the concept of medical professionalism and can be understood as a matter of contract between a democratic society and medical professionals. The proposed supplemented EF can be implemented into a regulatory system in three different ways: theself-regulating: where providers decide themselves how to balance the ethical claims, the centralised: where a governmental institution decides the right balance between providers’ interests and interests of a health system; and themediating: where medical professionals, the state and patients negotiate their interests. Our article contributes to the discussion on ethical relevance of providers’ interests and the regulatory model for weighing opposite interests in LHSs. (shrink)

Rothstein (2010) argues that groups may be harmed by research on deidentified data. He concludes that researchers are obligated to minimize group harms and demonstrate respect for a studied group t...

As part of a (bio)colonial project, the biological information of Indigenous Peoples has historically been under scientific scrutiny, with very limited benefits for communities and donors. Negative past experiences have contributed to further exclude Indigenous communities from novel developments in the field of omics research. Over the past decade, new guidelines, reflections, and projects of genetic research with Indigenous Peoples have flourished in Australia, providing opportunities to move the field into a place of respect and ethical relationships. This review explores (...) the ethical and cultural implications of the use of biological samples from Indigenous communities in biomedical research. A structured framework outlining emerging topics of interest for the development of respectful omics research partnerships with Indigenous Australians is presented. This paper highlights aspects related to Indigenous governance, community and individual consent, respectful handling of biological samples, data management, and communication in order to protect Indigenous interests and rights and to promote communities’ autonomy. (shrink)

Background: Recent changes to regulatory guidance in the US and Europe have complicated oversight of secondary research by rendering most uses of de-identified data exempt from human subjects oversight. To identify the implications of such guidelines for harms to participants and communities, this paper explores the secondary uses of one de-identified DNA sample collection with limited oversight: the Human Genome Diversity Project (HGDP)-Centre d'Etude du Polymorphisme Humain, Fondation Jean Dausset (CEPH) Human Genome Diversity Panel. Methods: Using a combination of keyword (...) and cited reference search, we identified English-language scientific articles published between 2002 and 2009 that reported analysis of HGDP Diversity Panel samples and/or data. We then reviewed each article to identify the specific research use to which the samples and/or data was applied. Secondary uses were categorized according to the type and kind of research supported by the collection. Results: A wide variety of secondary uses were identified from 148 peer-reviewed articles. While the vast majority of these uses were consistent with the original intent of the collection, a minority of published reports described research whose primary findings could be regarded as controversial, objectionable, or potentially stigmatizing in their interpretation. Conclusions: We conclude that potential risks to participants and communities cannot be wholly eliminated by anonymization of individual data and suggest that explicit review of proposed secondary uses, by a Data Access Committee or similar internal oversight body with suitable stakeholder representation, should be a required component of the trustworthy governance of any repository of data or specimens. (shrink)

Patient preference predictors (PPPs) promise to provide medical professionals with a new solution to the problem of making treatment decisions on behalf of incapacitated patients. I show that the use of PPPs faces a version of a normative problem familiar from legal scholarship: the problem of naked statistical evidence. I sketch two sorts of possible reply, vindicating and debunking, and suggest that our reply to the problem in the one domain ought to mirror our reply in the other. The conclusion (...) is thus conditional: if we think the problem of naked statistical evidence is a serious problem in the legal domain, then we should be concerned about the symmetrical problem for PPPs. (shrink)

BackgroundIt has been argued that ethics review committees—e.g., Research Ethics Committees, Institutional Review Boards, etc.— have weaknesses in reviewing big data and artificial intelligence research. For instance, they may, due to the novelty of the area, lack the relevant expertise for judging collective risks and benefits of such research, or they may exempt it from review in instances involving de-identified data.Main bodyFocusing on the example of medical research databases we highlight here ethical issues around de-identified data sharing which motivate the (...) need for review where oversight by ethics committees is weak. Though some argue for ethics committee reform to overcome these weaknesses, it is unclear whether or when that will happen. Hence, we argue that ethical review can be done by data access committees, since they have de facto purview of big data and artificial intelligence projects, relevant technical expertise and governance knowledge, and already take on some functions of ethical review. That said, like ethics committees, they may have functional weaknesses in their review capabilities. To strengthen that function, data access committees must think clearly about the kinds of ethical expertise, both professional and lay, that they draw upon to support their work.ConclusionData access committees can undertake ethical review of medical research databases provided they enhance that review function through professional and lay ethical expertise. (shrink)

Researchers increasingly rely on large data sets of health information, often linked with biological specimens. In recent years, the argument has been made that obtaining informed consent for conducting records-based research is unduly burdensome and results in ?consent bias.? As a type of selection bias, consent bias is said to exist when the group giving researchers access to their data differs from the group denying access. Therefore, to promote socially beneficial research, it is argued that consent should be unnecessary. After (...) analyzing the biostatistics evidence and bioethics arguments, the article concludes that (1) claims about the amount of consent bias are overstated; (2) commonly used statistical methods usually can account for consent bias; and (3) any residual effects of consent bias are below an acceptable level of imprecision and constitute a reasonable social cost for conducting ethically responsible research. (shrink)

In this article the authors reflect on regulations which have been developed to protect research subjects and data in research which uses human subjects. They suggest that regulations related to informed consent and privacy protection are burdensome in research which uses human subjects. They argue that a new category of research risk must be established which informs research subjects of the level of risk that they will be exposed to by participating in the research.

Spurred by a confluence of factors, most notably the decreasing cost of high-throughput technologies and advances in information technologies, a number of population research initiatives have emerged in recent years. These include large-scale, internationally collaborative genomic projects and biobanks, the latter of which can be defined as an organized collection of human biological material and associated data stored for one or more research purposes. Biobanks are a key emerging research infrastructure, and those established as prospective research resources comprising biospecimens and (...) data from many participants are viewed as particularly promising drivers of biomedical progress. Such biobanks, particularly those publicly funded and set up to promote the public interest, have expanded across the globe in recent years. (shrink)

Scientific research is indispensable inter alia in order to treat harmful diseases, address societal challenges and foster economic innovation. Such research is not the domain of a single type of organization but can be conducted by a range of different entities in both the public and private sectors. Given that the use of personal data may be indispensable for many forms of research, the data protection framework will play an important role in determining not only what types of research may (...) occur but also which types of actors may carry it out. This article looks at the role the EU’s General Data Regulation plays in determining which types of actors can conduct research with personal data. In doing so it focuses on the various legal bases that are available and attempts to discern whether the GDPR can be said to favour research in either the public or private domains. As this article explains, the picture is nuanced, with either type of research actor enjoying advantages and disadvantages in specific contexts. (shrink)

The HIPAA Privacy Rule is notoriously weak because of its incomplete coverage, numerous exclusions and exemptions, and limited rights for individuals. The three areas in which it provides the most protection are fundraising, marketing, and research. Provisions of the 21st Century Cures Act, pending in Congress, and the Notice of Proposed Rulemaking to amend the federal research regulations, awaiting final regulatory action, would weaken the privacy protections for research. If these measures are adopted, the HIPAA Privacy Rule would have so (...) little value that it might not be worth the aggravation and burden. (shrink)

BackgroundSharing de-identified individual-level health research data is widely promoted and has many potential benefits. However there are also some potential harms, such as misuse of data and breach of participant confidentiality. One way to promote the benefits of sharing while ameliorating its potential harms is through the adoption of a managed access approach where data requests are channeled through a Data Access Committee (DAC), rather than making data openly available without restrictions. A DAC, whether a formal or informal group of (...) individuals, has the responsibility of reviewing and assessing data access requests. Many individual groups, consortiums, institutional and independent DACs have been established but there is currently no widely accepted framework for their organization and function.Main textWe propose that DACs, should have the role of both promotion of data sharing and protection of data subjects, their communities, data producers, their institutions and the scientific enterprise. We suggest that data access should be granted by DACs as long as the data reuse has potential social value and provided there is low risk of foreseeable harms. To promote data sharing and to motivate data producers, DACs should encourage secondary uses that are consistent with the interests of data producers and their own institutions. Given the suggested roles of DACs, there should be transparent, simple and clear application procedures for data access. The approach to review of applications should be proportionate to the potential risks involved. DACs should be established within institutional and legal frameworks with clear lines of accountability, terms of reference and membership. We suggest that DACs should not be modelled after research ethics committees (RECs) because their functions and goals of review are different from those of RECs. DAC reviews should be guided by the principles of public health ethics instead of research ethics.ConclusionsIn this paper we have suggested a framework under which DACs should operate, how they should be organised, and how to constitute them. (shrink)

(2013). Can Informed Consent Go Too Far? Balancing Consent and Public Benefit in Research. The American Journal of Bioethics: Vol. 13, No. 4, pp. 1-2. doi: 10.1080/15265161.2013.778645.

The unsustainable growth in U.S. health care costs is in large part attributable to the rising costs of pharmaceuticals and medical devices and to unnecessary medical procedures. This fact has led health reform advocates and policymakers to place considerable hope in the idea that increased government support for research on the comparative effectiveness of medical treatments will eventually help to reduce health care expenses by informing patients, health care providers, and payers about which treatments for common conditions are effective and (...) which are not. Comparative effectiveness research has shown in some cases that expensive but commonly used treatments are significantly less effective than relatively inexpensive alternatives. Critics warn, however, that CER will homogenize patient care, limit patient choices, and lead to improper health care rationing and even to the denial of lifesaving treatments. (shrink)