Fisher’s 1918 paper accomplished two distinct goals: unifying discrete Mendelian genetics with continuous biometric phenotypes and quantifying the variance components of variation in complex human characteristics. The former contributed to the foundation of modern quantitative genetics; the latter was adopted by social scientists interested in the pursuit of Galtonian nature-nurture questions about the biological and social origins of human behavior, especially human intelligence. This historical divergence has produced competing notions of the estimation of variance ratios referred to as heritability. Jay (...) Lush showed that they could be applied to selective breeding on the farm, while the early twin geneticists used them as a descriptive statistic to describe the degree of genetic determination in complex human traits. Here we trace the early history of the heritability coefficient now used by social scientists. (shrink)

Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or (...) a rationale for particular decisions in individual cases, some commentators regard ceding medical decision‐making to black box systems as contravening the profound moral responsibilities of clinicians. I argue, however, that opaque decisions are more common in medicine than critics realize. Moreover, as Aristotle noted over two millennia ago, when our knowledge of causal systems is incomplete and precarious—as it often is in medicine—the ability to explain how results are produced can be less important than the ability to produce such results and empirically verify their accuracy. (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.

Engaging communities in community-based health research is increasingly being adopted in low- and middle-income countries. The use of community advisory boards is one method of practicing community involvement in health research. To date, few studies provide in-depth accounts of the strategies that CAB members use to practice community engagement. We assessed the perspectives, experiences and practices of the first local CAB in Eswatini, which was implemented as part of the MaxART Early Access to ART for All study. Trained Swazi research (...) assistants conducted two focus group discussions and 13 semi-structured interviews with CAB members who had been part of the MaxART study for at least 2.5 years. Interviews explored CAB composition and recruitment, the activities of CAB members, the mechanisms used to engage with communities and the challenges they faced in their role. The MaxART CAB played an active role in the implementation of the Early Access to Art for All study, and activities mainly focused on: promoting ethical conduct, in particular privacy, consent and confidentiality; communication and education, communicating about the study and educating the community on the benefits of HIV testing and early access to HIV treatment; and liaising between the community and the research team. Strategies for interacting with communities were varied and included attending general community meetings, visiting health facilities and visiting public places such as cattle dipping tanks, buses, bars and churches. Differences in the approach to community engagement between CAB members living in the study areas and those residing outside were identified. The experiences of the first CAB in Eswatini demonstrate that community engagement using CABs is a valuable mechanism for engaging communities in implementation studies. Considerations that could impact CAB functioning include clearly defining the scope of the CAB, addressing issues of CAB independence, the CAB budget, providing emotional support for CAB members, and providing continuous training and capacity building. These issues should be addressed during the early stages of CAB formation in order to optimize functioning. (shrink)

In the last third of the twentieth century, humanists and social scientists argued that attention to genetics would heighten already‐existing genetic determinism, which in turn would intensify negative social outcomes, especially sexism, racism, ableism, and harshness to criminals. They assumed that laypeople are at risk of becoming genetic essentialists. I will call this the “laypeople are genetic essentialists model.” This model has not accurately predicted psychosocial impacts of findings from genetics research. I will be arguing that the failure of the (...) model can be traced to its inability to recognize the complexity of laypeople’s attitudes; its incorrect theory of how beliefs, attitudes, and discourse function; and its blindness to how academics’ own interests can override the available evidence. More specifically, I suggest that the substantial data about laypeople’s deployment of genetics supports what I will call the “laypeople are strategic essentialists model” better than the “laypeople are genetic essentialists model.” The strategic essentialists model holds that people tend to store multiple categories, including multiple causal forces, that they deploy “strategically” to serve context‐dependent goals. It will be difficult for academics to reorient ourselves to model laypeople as sophisticated strategic essentialists rather than as naïve genetic essentialists. Perhaps a little shift, however, will be of value. (shrink)

Engaging communities in community-based health research is increasingly being adopted in low- and middle-income countries. The use of community advisory boards is one method of practicing community involvement in health research. To date, few studies provide in-depth accounts of the strategies that CAB members use to practice community engagement. We assessed the perspectives, experiences and practices of the first local CAB in Eswatini, which was implemented as part of the MaxART Early Access to ART for All study. Trained Swazi research (...) assistants conducted two focus group discussions and 13 semi-structured interviews with CAB members who had been part of the MaxART study for at least 2.5 years. Interviews explored CAB composition and recruitment, the activities of CAB members, the mechanisms used to engage with communities and the challenges they faced in their role. The MaxART CAB played an active role in the implementation of the Early Access to Art for All study, and activities mainly focused on: promoting ethical conduct, in particular privacy, consent and confidentiality; communication and education, communicating about the study and educating the community on the benefits of HIV testing and early access to HIV treatment; and liaising between the community and the research team. Strategies for interacting with communities were varied and included attending general community meetings, visiting health facilities and visiting public places such as cattle dipping tanks, buses, bars and churches. Differences in the approach to community engagement between CAB members living in the study areas and those residing outside were identified. The experiences of the first CAB in Eswatini demonstrate that community engagement using CABs is a valuable mechanism for engaging communities in implementation studies. Considerations that could impact CAB functioning include clearly defining the scope of the CAB, addressing issues of CAB independence, the CAB budget, providing emotional support for CAB members, and providing continuous training and capacity building. These issues should be addressed during the early stages of CAB formation in order to optimize functioning. (shrink)