SCH: EAGER: Improving Nutritional Literacy and Decision Making with Learner-Centered Crowdsourcing

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This EAGER project is funded from the Smart and Connected Health portfolio which aims to support a varied set of health and healthcare related research projects focusing on fundamental work in these multi-disciplinary fields. This project carries out basic research in the nutritional habits of certain segments of the population. There exist robust empirical evidence suggesting the benefits of healthy diet for prevention and management of a variety of health conditions. At the same time, adopting a healthy diet and making daily healthy nutritional choices is an uphill battle for many individuals, particularly those residing in economically disadvantaged communities and among ethnic minorities. Many factors contribute to the poor eating habits of adult Americans; among them are poor nutritional literacy, limited ability to critically appraise nutritional value of meals, and limited ability to apply these skills to personal dietary choices. While there exist computing technologies for facilitating healthy nutrition, no solution developed to date addresses all of these challenges. The goal of this research is to investigate a new breed of social computing mechanism that blend together the benefits of online health communities, crowdsourcing, and online learning environments. Specifically it develops new learner-centered nutrition crowdsourcing tools that are grounded in the theory of self-regulated learning and that 1) help individuals to develop better nutritional judgment by assessing nutritional value of each otherÕs meals and receiving tailored feedback; 2) provide in-the-moment nutritional decision support through community-generated feedback on prospective meals; 3) encourage long-term engagement using reciprocity principle and simple award structure. The proposed technologies are evaluated in a pilot study with individuals with diabetes recruited from an online diabetes community TuDiabetes.