Citizen science approaches to crowdsourcing food environment data: A scoping review of the literature

Abstract

Globally, the adoption and implementation of policies to improve the healthiness of food environments and prevent population weight gain have been inadequate. This is partly because of the complexity associated with monitoring dynamic food environments. Crowdsourcing is a citizen science approach that can increase the extent and nature of food environment data collection by engaging citizens as sensors or volunteered computing experts. There has been no literature synthesis to guide the application of crowdsourcing to food environment monitoring. We systematically conducted a scoping review to address this gap. Forty-two articles met our eligibility criteria. Photovoice techniques were the most employed methodological approaches (n = 25 studies), commonly used to understand overall access to healthy food. A small number of studies made purpose-built apps to collect price or nutritional composition data and were scaled to receive large amounts of data points. Twenty-nine studies crowdsourced food environment data by engaging priority populations (e.g., households receiving low incomes). There is growing potential to develop scalable crowdsourcing platforms to understand food environments through the eyes of everyday people. Such crowdsourced data may improve public and policy engagement with equitable food policy actions.

Keywords: citizen science; crowdsourcing; food environments; public participation.