Stress experiences in neighborhood and social environments (SENSE): a pilot study to integrate the quantified self with citizen science to improve the built environment and health

Abstract

BackgroundIdentifying 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.ResultsIn 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.ConclusionsParticipants 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.Electronic supplementary materialThe online version of this article (10.1186/s12942...

Crowdsourcing in health and medical research: a systematic review

“…Overall, 96 studies examined effectiveness, 127 examined feasibility, and 37 examined cost. Among those that examined effectiveness, all reported a behavioral outcome with the exception of two studies which reported a clinical outcome: measures of motor performance [27] and electrodermal activity [28].…”

Stressing the accuracy: Wrist‐worn wearable sensor validation over different conditions

“…It overcomes the limitations of most commercial devices, such as being restricted to one signal, reporting only proprietary metrics (i.e., rather than standard measurement units) or averaged values, and not providing access to raw data (Quintana, Alvares, & Heathers, 2016). The E4 is specifically designed for research purposes, and it has already been used, for instance, in a multimodal assessment of adult attachment (Parra, Miljkovitch, Persiaux, Morales, & Scherer, 2017) and in urban stress research (Chrisinger & King, 2018). Among the measured signals, heart rate (HR), heart rate variability (HRV), and skin conductance (SC) are of particular interest.…”

Smoke Sense Initiative Leverages Citizen Science to Address the Growing Wildfire‐Related Public Health Problem

“…With the gathered information, health authorities, working with "Culture Brokers" ((U.S. FEMA), 2019), can give risk and health promotion messages best suited for the structure of social and political dynamics in existing regional networks (Smell Pittsburgh, 2018; The University of Texas Medical Branch at Galveston, 2018). Chrisinger and King (2018) engaged citizen scientists to report objective and perceived elements of the built environment that contribute to chronic stress. In Tasmania, researchers developed an AirRater app that integrates symptom surveillance, environmental monitoring, and notifications of environmental conditions such as wildfire smoke and pollen (F. H. Johnston et al, 2018).…”

“…Katapally et al (2018) reported on a recent study using a mobile app to collect information on physical activity, physical and social context, and motivation and tested information interventions to increase active living behaviors. Chrisinger and King (2018) engaged citizen scientists to report objective and perceived elements of the built environment that contribute to chronic stress. Rosas et al (2016) engaged citizen scientists in Mexico to collect and gather data about barriers and facilitators of physical activity in participants' neighborhoods and facilitate the use of data to collectively advocate for local environmental-and policy-level changes to support active living.…”