Engaging Communities, Modeling Systems: Lessons from System Dynamics Modeling on Maternal Health in Texas

Kyrah K Brown^1*Michael K Lemke²Deneen Robinson³Saeideh Fallah-Fini⁴David W. Lounsbury⁵Thanayi Lambert¹Mercy J Obasanya¹Tiffany Kindratt¹

• ¹University of Texas at Arlington, Arlington, United States
• ²University of Texas Health Science Center at Houston School of Public Health, San Antonio, United States
• ³Truth pregnancy resource center, Dallas, United States
• ⁴California State Polytechnic University, Pomona, Pomona, California, United States
• ⁵Albert Einstein College of Medicine, New York City, New York, United States

Introduction: Disparate maternal health outcomes among non-Hispanic Black women stem from intricate, interrelated factors shaped by clinical, social, and structural determinants.Traditional approaches often fall short in addressing these complexities, necessitating a shift toward systems thinking and community-driven solutions.This paper describes lessons learned from the implementation of system dynamics group model building (SD GMB) workshops grounded in community-based participatory research (CBPR) principles in two separate projects focusing on maternal health among Black women. We recruited 31 diverse stakeholders, including individuals with lived experience, and applied trauma-informed facilitation, wraparound supports, and structured systems modeling activities. We performed descriptive analysis of workshop data to accompany the identified lessons learned.Results: Evaluation data from surveys and open-ended responses indicated high stakeholder satisfaction, increased capacity to apply systems thinking, and a shift from skepticism to agency.Stakeholders valued the inclusive design, reported meaningful learning, and expressed interest in future engagement. The workshops fostered transformative learning and generated actionable systems insights rooted in community experience.Discussion: This work illustrates how SD GMB, when integrated with CBPR, can build trust, elevate marginalized voices, and produce models that reflect structural realities. Future directions include quantifying the models, hosting learning labs to test interventions, and developing an open-access dashboard to simulate policy scenarios. These findings contribute to ongoing efforts to design more equitable, community-informed approaches to maternal health research and practice.