Measuring What Matters: Data Absenteeism, Science Communication, and the Perpetuation of Inequities

The ways in which we collect health and social data, particularly data on vulnerable and underprivileged populations, is enormously influential over the quality and content of science and health communication. Data absenteeism—the absence or limits of data on groups experiencing social vulnerability—is endemic; and as a result, inferences drawn from studies with absentee data are questionable. Reasons for data absenteeism include tendencies toward conventional recruitment of the subjects in research, the ways in which communities are engaged or not engaged in the research process, and a lack of understanding and appreciation of the lived reality of the socially vulnerable. The “hardly reached” are often labelled “hard to reach,” keeping this critical population out of view. One approach to mitigate data absenteeism is to engage key stakeholders of the community and its residents in the entire research process from design to dissemination, which influences how research questions are asked and answered and how research gets used. We argue for a more inclusive science of science communication to promote diversity and equity.