Allison De Marco

Dissemination of research findings needs to not only reach and speak to other scientists; it also must reach and speak to those who can make sense of it and those who can make change with it. In essence, research and action are necessarily interdependent to drive meaningful impacts. Importantly, action often flows from authentic community engagement, which is one of the key tenets of anti-racism research and supported by the core tenets of Critical Race Theory and Participatory Action Research. Data walks are one method of engagement that involves discussing research findings with participants to gain insights and spark action to practical challenges within a community. In this article, we center data walks through three case studies that demonstrate how to plan and implement this method of equitable data dissemination. Two of the case studies present how the method is used in a variety of early childhood education sites in the Educare Network, which is working to implement a research agenda advancing racial equity. The third case study builds on the learning gleaned by working with colleagues who conducted the first two sets and extends the data walk method to a much different field, structural racism in affordable housing and homelessness. This addition serves to illustrate that data walks are discipline agnostic and can be used with a wide variety of data and audiences. We conclude by discussing actions that flowed from the data walks, methods for authentic engagement, and how to respond to power dynamics.

Neighborhood deprivation plays an important role in childhood health and development, but defining the appropriate neighborhood definition presents theoretical as well as practical challenges. Few studies have compared neighborhood definitions outside of highly urbanized settings. The purpose of the current study was to evaluate how various administrative and ego-centric neighborhood definitions may impact measured exposure to deprivation across the urban-rural continuum. We do so using the Family Life Project, a prospective longitudinal population-based sample of families living in North Carolina and Pennsylvania (USA), which also sets the stage for future investigations of neighborhood impacts on childhood health and development. To measure neighborhood deprivation, a standardized index of socioeconomic deprivation was calculated using data from the 2007-2011 American Community Survey. Families' residential addresses when children were 2 months of age (n=1036) were geocoded and overlaid onto a deprivation index layer created at the census block group level to construct multiple administrative and ego-centric neighborhood definitions. Friedman tests were used to compare distributions of neighborhood deprivation across these neighborhood definitions within urbanized areas, urban clusters, and rural areas. Results indicated differences in urbanized areas (Chisquare= 897.75, P<0.001) and urban clusters (Chi-square=687.83, P<0.001), but not in rural areas (Chi-square=13.52, P=0.332). Findings imply that in urban areas, choice of neighborhood definition impacts measured exposure to neighborhood deprivation. Although exposure to neighborhood deprivation appears to be less sensitive to neighborhood definition in rural areas, researchers should apply theoretical reasoning to choose appropriate definitions of children's neighborhood.