The Importance of Recruitment of Low-Income Pregnant Persons in Interdisciplinary Research to Understand the Impact of Social and Environmental Determinants: Lessons Learned About Implementation and Recruitment.

Abstract

Background: Prior research indicates that enrolling underrepresented populations in clinical research is challenging. Although research has identified some barriers to participation and strategies to overcome them, studies have made little progress in being inclusive and representative. There remains a great need for including racial/ethnic minorities, low-income families, and pregnant women in research. The purpose of this article is to describe the implementation of enrollment strategies used in our study to understand the feasibility of building a maternal cohort and better understand the relationship between environmental and social impacts on maternal exposure and child outcomes.

Methods: Working across multiple academic units, our team implemented equity-focused team science strategies to recruit diverse populations into a research study. The phases included development, conceptualization, implementation, and translation.

Results: Our interdisciplinary team study used intentionality and commitment to deploy effective strategies including clearly defining the problem, selecting the correct team members to leverage expertise, clearly defining the study, establishing roles and responsibilities, representation, and clear and constant communication. A total of 100 pregnant women enrolled in our study using a team science interdisciplinary model.

Discussion: Building interdisciplinary teams can help us understand complex problems, increase innovation, and develop effective solutions in policy and practice. More specifically, interdisciplinary teams can advance our ability to recruit diverse populations into research. Future studies should consider how to harness the strengths of the different research team members to achieve more inclusive participation.

Health equity implications: This work has the potential to improve representation in research findings, enhance understanding of health disparities, and promote inclusive research practices.