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"Think about how you can get diverse input from multiple populations so that your research can benefit everybody."
This Women’s History Month, let’s talk about inclusion of women and gender minorities as participants in human subjects research. Most human subjects researchers know that a 50/50 split of men and women is desirable, but this still remains a lofty goal. In my own field of exoskeleton research, women remain underrepresented as research participants because “men handle the physical jobs.” As a result, many exoskeletons fit women poorly and do not provide the desired benefits such as back relief. When women are included, many studies simply aim for a 50/50 split and call it a day: they do not consider gender differences in analysis and simply hope that men and women will average out in the analysis. Furthermore, when women are included, they are usually white and under 65 years old, with women of color and older women still underrepresented.
That doesn’t even consider gender minorities. NIH enrollment reports include three categories: “Male”, “Female”, and “Unknown”. Where do we put our transgender and gender diverse participants? They are often simply excluded; in my own field of affective computing, which examines physiological responses to stress, transgender people are often excluded because hormone replacement therapy may result in “unpredictable” physiological responses. At the same time, they often do not self-report their gender identity, either because the research documentation does not allow it (“Check one: Male, Female”) or because they do not feel comfortable discussing it with researchers. Even if they do report it, researchers may not be motivated to report it in publications; I have been criticized by reviewers for reporting that transgender people were included in research that was not focused on gender issues, as if transgender people may only exist in gender research. As a research community, we must do better. At minimum, don’t just think about male/female quotas: think about how you can get diverse input from multiple populations so that your research can benefit everybody.
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