Empty Houses,Loose Dogs,and Engaged Citizens: Lessons Learned From Community Participatory Data Collection in Rural Areas

Abstract

Rural surveys tend to oversample easy to reach populations, which can misrepresent community health needs. To achieve baseline data reflective of the communities served by the high obesity program (HOP), an innovative evaluation plan was created to prioritize equity and reflect the whole community. Principles of Community-Based Participatory Research (CBPR) were used to guide instrument development, research protocols, and data collection. A random sample of addresses created with United States Postal Service records provided a representative list of addresses in three HOP counties in Louisiana. Local data collectors were recruited to go door to door at the selected addresses to collect in-person surveys (N = 682; response rate of 84%). Over a quarter of participants reported using the charitable food system and walking for transportation at least weekly. Collecting door to door data in rural communities presents unique challenges, including abandoned properties, inaccurate address records, loose dogs, and at times, racial tensions and houses far removed from public roads. Lessons learned include the importance of local knowledge, adapting protocols to fit local conditions, and community awareness of the survey. Health practitioners need confidence when they are making data-based decisions about interventions, and one way to provide this confidence is to collect data from a true cross-section of the community. With a plan and in partnership with community members, a probability sample is feasible to collect in rural communities.