Abstract IA53: Challenges of implementing interventions in “small populations.”

The ability to harness the benefits of big data has had a revolutionary impact on science, with its focus on the volume and variety of data sources and application of both traditional and innovative analytic methods appropriate for large, aggregated datasets. We are concerned, however, about the opposite: small data for which the size, dispersion, or accessibility of the population of interest makes it difficult to obtain adequate sample sizes to test specific research questions. Data from these groups, however, are critical if we want to include health-related issues across all populations in cancer research.

An example of the potential negative ramifications of not including underrepresented groups in research or inappropriately aggregating them across groups-- comes from the study of racial and ethnic health disparities and issues of equity in the US. Intervention research often does not include a wide range of racial/ethnic subgroups; so it is not feasible to test whether an intervention created specifically for the majority group is also efficacious for the subgroups. Likewise, the ability to test whether an intervention can be altered for a particular subgroup is also often not possible. Epidemiologic and surveillance research usually involves the inclusion of “minority or underserved populations” in addition to white/non-Hispanic white (NHW) groups. While this has allowed for a better understanding of these smaller populations and provides some progress toward addressing health inequities, there remain pockets of communities that are severely underrepresented within the broader minority and underserved populations.

Citation Format: Shobha Srinivasan, Richard P. Moser, Gordon Willis, William Riley, Mark Alexander. Challenges of implementing interventions in “small populations.” [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr IA53.