Development of personalized healthy food incentives to improve diet and cardiovascular risk

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Title: Development of personalized healthy food incentives to improve diet and cardiovascular risk ABSTRACT It is imperative to address the complex factors that drive food decisions and promote unhealthy dietary patterns. This mentored career award will support a rigorous training and research plan that will apply mixed methods to promote healthier grocery purchases and improve dietary intake and cardiovascular (CV) health. Through strong mentorship and training opportunities, I will adapt and test the novel automated machine- learning based Smart Cart 2.0 platform to deliver personalized recommendations and incentives for healthier grocery purchases among Rhode Island adults with CV risk factors (i.e., Body Mass Index (BMI) > 30 kg/m2 and/or hypertension). To date, interdisciplinary research from my Big Data and Eating Decisions lab has focused on investigating determinants of food choice and diet quality in large population cohorts and using those insights to develop dietary interventions. I previously developed and pilot tested a semi-automated personalized healthy food incentive platform using decision tree logic and found that it significantly improved grocery purchase quality among healthy adults in the 9-month randomized controlled Smart Cart Study. The proposed project extends this research by using novel applications of grocery sales data to adapt and evaluate the automated `Smart Cart 2.0' platform to encourage healthier food purchases and dietary quality. To adapt and scale this platform to adults at high CV risk, it is essential to understand its's feasibility, acceptability, and preliminary effectiveness to facilitate adoption of a healthier diet among adults with CV risk factors. This project also advances methodology to leverage technology and machine learning to automatically evaluate sales data and deliver personalized dietary recommendations in real time. The proposed research will use the Obesity- Related Behavioral Intervention Trials (ORBIT) framework to determine whether the Smart Cart 2.0 platform adapted and tested with input from adults with CV risk factors promotes a clinically significant change in diet quality and CV risk factors. In Aim 1, I will evaluate how well the Smart Cart 2.0 content and function meet the needs of adults at CV risk using focus groups and surveys. In Aim 2, I will conduct a 1-week 3-arm mock shopping trial in a simulated online grocery store to see how much the platform affects willingness to purchase (WTP) recommended foods relative to control using a discrete choice task comparing a) personalized recommendations b) personalized recommendations plus incentives to c) generic education and incentives (control). In Aim 3, I will conduct a pilot 6-month randomized controlled trial to test the acceptability, feasibility, and preliminary effectiveness of the Smart Cart 2.0 platform for improving real-world dietary behaviors, diet quality, BMI, and blood pressure. Results of this project will provide critical pilot data to support a larger randomized controlled trial. The training plan and collaborations established through this award will position me to pioneer a policy-relevant translational research program focused on promoting healthier dietary patterns and CV health.