Building Trust and Influence in Population Health Through Community‑Centered Data
Abstract
As public trust in science continues to decline, population health researchers need new ways to work with data that feels relevant, fair, and useful to communities. This presentation shares findings from an 18-month assessment of the Robert Wood Johnson Foundation’s Healthy Communities data work, led by the Michigan Public Health Institute. We used multiple methods, including document review, interviews with funders and grantees, focus groups with community data leaders, and a review of published and gray literature, to understand how data projects are designed, supported, and used at both national and community levels.
We identified a strong yet fragmented data landscape. Many projects generated high-quality data and tools, especially large dashboards and academic-led initiatives, but often lacked clear connections among themselves or to community priorities. In contrast, community-based projects were more effective at building trust by focusing on local issues, using participatory approaches, and valuing lived experience alongside data. Across all perspectives, trust grew when data work was transparent, relationships were built over time, communities shared decision-making power, and “data translators” made complex information understandable and meaningful.
Community data leaders highlighted that trust isn’t built only by sharing data. Instead, it grows through listening, sharing power, storytelling alongside statistics, and investing in people and relationships. They also noted that uncertain funding decisions, limited opportunities for shared learning, and a lack of support for community organizations to turn data into action challenge their efforts.
This presentation offers practical lessons for researchers, funders, and practitioners who want population health science to be more meaningful to the people it serves. We emphasize designing community-centered data efforts that balance technical quality with real-world relevance, support community leadership, and translate data into action that communities find credible, useful, and aligned with their efforts.
