PhD student: Paul Reichel
Title: Improving the measurement of EDI-relevant treatment effect modifiers in clinical trials
Supervisors: Viet-Thi Tran, Karolin Krause, Sanne Peters
Doctoral school: ED 393 -Pierre-Louis de Santé Publique
Promotion:2026
Funding: European commission, Horizon Europe Marie Skłodowska-Curie Actions
Thesis abstract
Randomized controlled trials (RCTs) underpin regulatory and clinical decision-making in healthcare, yet they are primarily designed to estimate average treatment effects within selected samples. This raises concerns about external validity and equity, as underserved groups are often underrepresented due to restrictive eligibility criteria and structural barriers to participation. Even when included, patient characteristics that are relevant to considerations of equity, diversity and inclusion (EDI), including demographic, psychosocial, contextual characteristics, are captured inconsistently across RCTs and sometimes with insufficient detail to determine whether findings apply across population groups. Recent guidance, including the 2024 revision of the Declaration of Helsinki and World Health Organization recommendations, calls for improved reporting of EDI-relevant patient characteristics. Frameworks such as PROGRESS-Plus identify key domains but provide limited direction on how these constructs should be measured in practice.
In addition to demographic factors, psychosocial and contextual characteristics such as health literacy, treatment preferences, financial constraints, and social support shape patients’ engagement with treatment but are rarely measured systematically in RCTs. As a result, little is known about whether underserved populations respond differently to treatments and which psychosocial or contextual factors may explain differences in treatment engagement and outcomes, particularly in chronic physical and mental health conditions that require sustained engagement and self-management.
This PhD project will examine how EDI-relevant characteristics are currently measured in late-phase clinical trials, identify and appraise candidate instruments, and evaluate selected measures within a large e-cohort of patients with chronic conditions
