Discovery Tool Our Voice

Citizen science research that more fully engages the community can systematically involve people from under-resourced groups to create practical health-enhancing improvements across physical, social and food environments. Exemplary health equity-focused outcomes include key health behaviors (e.g., healthy eating or physical activity) and community-level changes (e.g., public transit to food shops) that are central to health promotion while being demonstrably impacted by local environmental contexts. Yet, few examples of this approach are readily available for application within complex, community-based settings. In this paper, we present the Our Voice (OV) four-step method to demonstrate an integrated participatory citizen science approach and its usability for action-focused researchers and community health practitioners. In addition, we present a summary of the major research, processes, and community outcomes, with examples drawn from nutrition and healthy food access areas, among others. Finally, we explore the hallmark features of the OV method that effectively engage citizen scientists, empowering action and fostering solution-building across social and environmental structures impacting community health. Expanding research that marries participatory research philosophies with innovative citizen science methods, supported by systematic data collection, visualization, and delivery technologies, in turn provides a powerful toolkit for tackling local to global health equity challenges.

Identifying elements of one's environment—observable and unobservable—that contribute to chronic stress including the perception of comfort and discomfort associated with different settings, presents many methodological and analytical challenges. However, it also presents an opportunity to engage the public in collecting and analyzing their own geospatial and biometric data to increase community member understanding of their local environments and activate potential environmental improvements. In this first-generation project, we developed a methodology to integrate geospatial technology with biometric sensing within a previously developed, evidence-based "citizen science" protocol, called "Our Voice." Participants used a smartphone/tablet-based application, called the Discovery Tool (DT), to collect photos and audio narratives about elements of the built environment that contributed to or detracted from their well-being. A wrist-worn sensor (Empatica E4) was used to collect time-stamped data, including 3-axis accelerometry, skin temperature, blood volume pressure, heart rate, heartbeat inter-beat interval, and electrodermal activity (EDA). Open-source R packages were employed to automatically organize, clean, geocode, and visualize the biometric data. In total, 14 adults (8 women, 6 men) were successfully recruited to participate in the investigation. Participants recorded 174 images and 124 audio files with the DT. Among captured images with a participant-determined positive or negative rating (n = 131), over half were positive (58.8%, n = 77). Within-participant positive/negative rating ratios were similar, with most participants rating 53.0% of their images as positive (SD 21.4%). Significant spatial clusters of positive and negative photos were identified using the Getis-Ord Gi* local statistic, and significant associations between participant EDA and distance to DT photos, and street and land use characteristics were also observed with linear mixed models. Interactive data maps allowed participants to (1) reflect on data collected during the neighborhood walk, (2) see how EDA levels changed over the course of the walk in relation to objective neighborhood features (using basemap and DT app photos), and (3) compare their data to other participants along the same route. Participants identified a variety of social and environmental features that contributed to or detracted from their well-being. This initial investigation sets the stage for further research combining qualitative and quantitative data capture and interpretation to identify objective and perceived elements of the built environment influence our embodied experience in different settings. It provides a systematic process for simultaneously collecting multiple kinds of data, and lays a foundation for future statistical and spatial analyses in addition to more in-depth interpretation of how these responses vary within and between individuals.