In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often‐ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science—including genomewide association studies and polygenic indexes—can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. (...) SBG research that compares individuals within a group according to a “sensitive” phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk‐benefit profile. (shrink)

Bioethicists frequently call for empirical researchers to engage participants and community members in their research, but don't themselves typically engage community members in their normative research. In this article, we describe an effort to include members of the public in normative discussions about the risks, potential benefits, and ethical responsibilities of social and behavioral genomics (SBG) research. We reflect on what might—and might not— be gained from engaging the public in normative scholarship and on lessons learned about public perspectives on (...) the risks and potential benefits of SBG research and the responsible conduct and communication of such research. We also provide procedural lessons for others in bioethics who are interested in engaging members of the public in their research. (shrink)

Researchers and practitioners are increasingly using machine‐generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accuracy and reliability issues, worries about fairness and bias, and new regulatory challenges. The virtue of synthetic data is often understood (...) to be its detachment from the data subjects whose measurement data is used to generate it. However, we argue that addressing the ethical issues synthetic data raises might require bringing data subjects back into the picture, finding ways that researchers and data subjects can be more meaningfully engaged in the construction and evaluation of datasets and in the creation of institutional safeguards that promote responsible use. (shrink)

Since 2011, the research community had waited with bated breath as regulators contemplated for the first time bringing secondary research with nonidentifiable biospecimens under the Common Rule and dramatically tightening the criteria for waiving consent to biospecimen research. After considerable pushback from both researchers and patients and amid rumors of intractable disagreement among Common Rule agencies, the Final Rule published on the last day of President Obama's administration left out these troubling changes, and there was a collective sigh of relief. (...) Relief is appropriate, but celebration premature: researchers have little reason to avail themselves of the new broad consent option offered in the Final Rule, and the question of whether biospecimens ought to be treated as inherently identifiable has merely been postponed. (shrink)

Using mobile health research as an extended example, this article provides an overview of when the Common Rule “applies” to a variety of activities, what might be meant when one says that the Common Rule does or does not “apply,” the extent to which these different meanings of “apply” matter, and, when the Common Rule does apply, how it applies.

Hastings Center Report, Volume 52, Issue 1, Page 51-58, January/February 2022.

Researchers and practitioners are increasingly using machine-generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accuracy and reliability issues, worries about fairness and bias, and new regulatory challenges. The virtue of synthetic data is often understood (...) to be its detachment from the data subjects whose measurement data is used to generate it. However, we argue that addressing the ethical issues synthetic data raises might require bringing data subjects back into the picture, finding ways that researchers and data subjects can be more meaningfully engaged in the construction and evaluation of datasets and in the creation of institutional safeguards that promote responsible use. (shrink)

As a recent special report in the Hastings Center Report demonstrates, many bioethicists are rethinking the way we regulate both biomedical research and clinical practice, as well as the sharp boundary that the field has assumed can and should exist between them. Such a rethinking is long overdue. There is surely a meaningful normative distinction between activities whose expected risk‐benefit profile is and is not “reasonable” for participants (to echo the language in the Common Rule—the core set of human research (...) guidelines found in many federal regulations). But neither the research‐practice distinction nor the criteria underlying it—the intention of the actor, whether the activity is “systematic,” and whether its results are “generalizable”—closely track good and bad outcomes for research participants and patients or justify either the bureaucratic, paternalistic licensing system that governs human subjects research or the comparatively lax governance of medical practice. The specious distinction between research and practice is especially ripe for dismantling in light of the embarrassing fact that evidence‐based medicine remains more aspiration than reality. (shrink)

Many assumed that the Obama administration would usher in a sea change from the previous administration by expanding NIH support for human embryonic stem cell (hESC) research and reducing the patchwork of state and federal regulations that currently governs it. This article examines the extent to which NIH’s new Guidelines are likely to accomplish these goals.