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

制定个性化健康食品激励措施以改善饮食和心血管风险

基本信息

批准号：
10663538
负责人：
MAYA VADIVELOO
金额：
$ 17.23万
依托单位：
UNIVERSITY OF RHODE ISLAND
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-05-15 至 2028-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10663538
关键词：
Address Adopted Adoption Adult Affect Award Behavior Behavior Therapy Behavioral Big Data Blood Pressure Body mass index Cardiovascular Diseases Categories Chronic Disease Collaborations Complex Consumption Data Data Science Decision Theory Decision Trees Development Diet Dietary Intervention Dietary Practices Dietary intake Dissemination and Implementation Eating Education Effectiveness Ensure Environment Focus Groups Food Future Goals Gorilla gorilla Health Health Food Healthy Eating Human Hypertension Incentives Intake Interdisciplinary Study Intervention Intervention Trial Knowledge Logic Machine Learning Mentors Mentorship Methodology Methods Modeling Morbidity - disease rate Nutritional Study Obesity Participant Policies Population Population Intervention Positioning Attribute Public Health Qualitative Research Randomized Randomized, Controlled Trials Recipe Recommendation Research Research Personnel Rhode Island Risk Factors Sales Strategic Planning Surveys Technology Testing Time Training Unhealthy Diet United States National Institutes of Health acceptability and feasibility arm behavioral economics behavioral health cardiovascular health cardiovascular risk factor career clinically significant cohort cost design dietary fruits and vegetables good diet group intervention health goals high risk implementation framework implementation research improved insight intervention participants literacy mortality novel nutrition personalized intervention personalized strategies pilot test preference programs tool training opportunity translational research program willingness

项目摘要

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.

标题：制定个性化健康食品激励措施以改善饮食和心血管风险抽象的必须解决推动食物决策和促进不健康饮食的复杂因素模式。这个指导性职业奖将支持严格的培训和研究计划，该计划将应用混合促进更健康的杂货购买并改善饮食摄入和心血管（CV）健康的方法。通过强有力的指导和培训机会，我将适应和测试新型自动化机器- 基于学习的 Smart Cart 2.0 平台，为健康提供个性化建议和激励罗德岛州成年人有心血管风险因素（即体重指数 (BMI) > 30 kg/m2）的杂货购买情况和/或高血压）。迄今为止，我的大数据和饮食决策实验室的跨学科研究已经重点研究大量人群中食物选择和饮食质量的决定因素，并使用这些见解可用于制定饮食干预措施。我之前开发并试点测试了一个半自动化的使用决策树逻辑的个性化健康食品激励平台，发现其显着提高在为期 9 个月的随机对照智能购物车研究中，健康成年人的杂货购买质量。这拟议的项目通过使用杂货销售数据的新颖应用来适应和评估来扩展这项研究自动化的“智能购物车2.0”平台鼓励更健康的食品购买和饮食质量。适应并将该平台扩展到具有高心血管风险的成年人，有必要了解其可行性、可接受性和促进具有心血管危险因素的成年人采用更健康饮食的初步效果。本项目还改进了利用技术和机器学习自动评估销售数据的方法并实时提供个性化饮食建议。拟议的研究将使用肥胖- 相关行为干预试验（ORBIT）框架确定Smart Cart 2.0平台是否适用根据具有心血管危险因素的成年人的意见进行调整和测试，促进饮食的临床显着改变质量和CV风险因素。在目标 1 中，我将评估 Smart Cart 2.0 的内容和功能如何满足通过焦点小组和调查来了解有心血管风险的成年人的需求。在目标 2 中，我将进行为期 1 周的 3 臂模拟在模拟的网上杂货店进行购物试验，看看平台对购买意愿的影响有多大（WTP）使用离散选择任务相对于对照推荐的食物比较a）个性化建议 b) 个性化建议和激励措施 c) 通用教育和激励措施（控制）。在目标 3 中，我将进行一项为期 6 个月的随机对照试验，以测试可接受性、可行性、 Smart Cart 2.0平台在改善现实世界饮食行为、饮食方面的初步效果质量、BMI 和血压。该项目的结果将提供关键的试点数据，以支持更大的随机对照试验。通过该奖项建立的培训计划和合作将使我定位开创一个与政策相关的转化研究计划，重点是促进更健康的饮食模式和简历健康。