Without the willingness of people to voluntarily participate in studies, research on health and disease would not be possible. However, finding a sufficiently high number of study participants is not the only important dimension of scientific research. Study participants should also reflect the diversity of the society or the individuals about whom the study wishes to make statements. This is referred to as the representativeness of the study sample, with representativeness seen as a quality feature of quantitative studies. It is therefore important to know whether the study sample represents the target population in all relevant aspects. For example, people with a low socioeconomic status are often underrepresented in health research. Furthermore, study participation differs depending on differential categories such as sex/gender, socioeconomic status or ethnic origin. Therefore, an improved understanding of study participation is of great importance for research.
An intersectional perspective does not view the decision to participate or not to participate in a study as an exclusively individual one. Instead, social processes such as discrimination are taken into account as explanatory approaches. In the case of underrepresented groups, there is a lack of reliable statements about their health and therefore also of measures to reduce health inequities. Here is an example:
What are the reasons for people to not participate in studies? It is a challenge to obtain sufficient information about this. One possibility is to survey people who have declined the offer to participate in a study, through so-called non-responder surveys. However, these questionnaires are very short and, accordingly, contain only a small selection of questions. The reasons for a decision against participation can thus often only be understood to a limited extent. Here, qualitative studies are suitable as a way to gain a deeper understanding of study participation and non-participation.
Another challenge is to be clearly able to identify the characteristics that identify groups with a high or low probability of participation.From an intersectional perspective, the question arises of whether social categories such as sex/gender, ethnicity, age or income are suitable as predictors of study participation. Having information on these characteristics and their effects on participation and non-participation can support the development of appropriate recruitment strategies for future research projects.
Here you will find options for an intersectionality-informed description of representativeness in population-based health studies. An intersectional perspective can help identify over- or underrepresented social groups more precisely. When developing questions for a non-responder survey, the possibilities for describing study participation could be expanded by considering relevant social categories. Finally, quantitative methods are available that allow for an intersectionality-informed analysis of the representation of all intersections in a study population.