Project Details

Organized Screening Programs allow for a comprehensive approach towards the early detection of diseases with high incidence among the risk population. Despite the extensive implementation of these programmes in numerous European countries, inequalities in access to screening remain. Attendance is not distributed uniformly among the target population.

A substantial body of research has examined these dimensions of inequality as independent predictors of non-attendance. However, as no individual can be defined by a single social dimension alone, it is unlikely that examining the independent effect of each social dimension will provide a comprehensive understanding of the inequalities in accessing cancer screenings. It is crucial to consider the interplay between these social dimensions to fully comprehend the multifaceted ways in which individuals experience their circumstances and how these experiences shape their access to healthcare. This can be effectively captured using the intersectionality framework. This framework is based on the theory of intersectionality, which was developed in 1991 by Kimberlé Crenshaw. It posits that discrimination and oppression suffered by this collective result from the intersection of multiple aspects of identity (e.g. gender, ethnicity) and their related experiences.

Over the past two decades, several quantitative intersectionality methods have been developed. These range from relatively simple regression analyses with interaction terms or intersection variables to more complex and less frequently used approaches, such as decision trees. This project is positioned within this exciting methodological development momentum, as it aims to explore the use of decision trees for intersectional subgroup identification within the context of participation in organised cancer screening programmes.