Whole Community – Whole Health: A Participatory Team Science Cohort Model

• In Event: 2-096 - Advances in Community Engagement and Measurement in Longitudinal Cohort Studies

Integrative Statement

More than one in ten (11%) of all US children are born in Texas (Martin et al. 2015). Sixty-seven percent of Texas children are part of a minority race or ethnic group, and over one-third live with one or more parents who immigrated to the U.S. (Center for Public Policy Priorities, 2017). Texas mirrors essential health and social challenges facing the nation: A quarter of Texas children live in poverty, and Texas ranks worst nationwide for socioeconomic disparities in child health and 41st for child well-being. Texas provides an ideal microcosm to study factors that impact health and well-being of vulnerable children, families, and communities.

Whole Communities – Whole Health is a new interdisciplinary grand challenge initiative at the University of Texas at Austin seeking to enhance the longitudinal cohort study model traditionally used in health and developmental studies by: 1) increasing participation of vulnerable populations; 2) employing real-time, ecologically valid measurement and integrating large amounts of biological, psychosocial, environmental, and contextual data; 3) returning data to participants in timely, actionable format; and 4) modernizing ethical guidelines emerging concerns. This presentation gives an overview of the study design, approach, challenges, and novel strategies employed within each element of our project.

Community engagement among vulnerable populations: Vulnerable populations (low SES, undocumented, and other marginalized groups) are underrepresented in the majority of current research, resulting in a lack of evidence-based strategies for promoting health and well-being while preventing poor developmental outcomes. Our aim is to develop a replicable model for engaging vulnerable populations in research using participatory team science (Tebes & Thai, 2018). The driving principle of participatory science is that solving complex health and social problems requires both a variety of interdisciplinary academic expertise and continual input and involvement of individuals and communities affected by those problems.

Real-time, ecologically valid measurement and big data processing and analysis: Developmental
processes are dynamic. Infrequent, survey-based measures often do not capture daily processes that make up development. Wearable and home sensors and mobile applications offer opportunities to passively collect real-time data on a wide range of social-behavioral and health variables with reduced participant burden and increased ecological validity. However, they also yield tremendous amounts of sensitive data that require IT, storage, and analytic solutions. Our team includes engineers and data scientists to collect, manage, analyze, and integrate these data.

Data feedback: Study participants and the communities in which they reside rarely receive timely or actionable data back from research teams. Our team will develop an online data dashboard to enable real time, broad dissemination of study results to empower participants through user-friendly access to objective data on their health and well-being.

Ethical considerations: New technologies that collect more—and more detailed—data than before, coupled with increasingly pressing social concerns (e.g. deportation) present a number of ethical challenges that must be solved in order to enable vital research on vulnerable children and families. Our team is exploring institutional, technological, and legal mechanisms for ethical conduct of research and protection of vulnerable populations.

Authors

• Julie Maslowsky, University of Texas at Austin
  Presenting Author

• Sarah Kate Bearman, The University of Texas at Austin
  Non-Presenting Author