Optimizing an mHealth Intervention to Change Food Purchasing Behaviors for Cancer Prevention

摘要 饮食摄入量是影响癌症风险的一个强大的、可改变的因素。不幸的是，美国的大多数成年人。 发现很难遵守预防癌症的饮食指南。一个有希望的途径， 饮食依从性是针对杂货店购物习惯，即，购买食品在家里消费。二-- 每日食物摄入量的三分之一来自家庭或在家中食用，因此提高家庭食物的质量 环境应改善整体饮食质量。当购买健康食品和不健康食品时， 不，最低限度的自我控制是需要在家里做出健康的饮食选择。在购买时， 很难抗拒美味食物的诱惑，但干预措施可能会促进健康的选择， 在杂货店购物时实时促进饮食目标显著性，B）增强制作的动机， 持续改变饮食，以及c）增加家庭对健康食品的支持和责任 purchasing.在这个研究阶段，有系统地测试可以改变食物的干预成分， 购买行为是必要的，为了制定一个可行的，可接受的， 并针对功效和可扩展性进行了优化。拟议的研究将招募患有低血糖的成年人（N = 64）。 坚持癌症预防饮食建议。所有参与者将参加3小时的营养 教育研讨会。在研讨会结束后的6个月内，所有与会者都将收到文本通知， 提供量身定制的食品购买提醒和建议。本研究将采用析因设计， 实验测试四个额外的干预措施组成部分，并检查其可行性，可接受性， 对3个月和6个月时食物购买和饮食摄入的影响。(Each组件被随机分配为 50%的参与者）。测试的四个成分是：1）位置触发文本 通知：提醒和食品购买的建议是交付“及时”，当到达 杂货店购物地点，以提高目标的突出性。2)关于变革益处的思考： 为了提高人们的积极性，在信息中增加了内容，鼓励人们反思健康饮食的预期好处。 3)教练监控：食品购买由教练自动监控（通过一个收集 商品级商店数据），发送个性化的购买后消息，以增强支持 责任感和动机。4)家庭文本：家庭中的其他成年人接收消息 旨在为购买健康食品寻求支持，并提供另一个支持性问责制的来源。 研究的初步目的是评估干预措施的可行性和可接受性。的 这项研究的主要目的是量化每个干预组成部分的影响，单独和 组合，对杂货店食品购买（通过商店数据进行客观评估）和饮食摄入量的影响 （24小时食品召回评估）。还将进行调解分析。这个项目的首要目标是 该项目旨在优化这种移动健康干预措施，未来可以在一项全面的临床试验中进行测试。

Abstract Dietary intake is a powerful, modifiable factor that influences cancer risk. Unfortunately, most adults in the U.S. find it difficult to adhere to dietary guidelines for cancer prevention. One promising pathway for improving dietary adherence is to target grocery shopping habits, i.e., foods purchased for consumption at home. Two- thirds of daily food intake is sourced from or eaten in the home, so improving the quality of the home food environment should improve overall diet quality. When healthy foods are purchased and unhealthy foods are not, minimal self-control is needed to make healthy eating choices in the home. At the point of purchase, it is difficult to resist the temptation of palatable foods, but interventions might facilitate healthy choices by a) promoting dietary goal salience in real-time while grocery shopping, b) enhancing motivation to make and sustain changes to the diet, and c) increasing household support and accountability for healthy food purchasing. At this stage of research, methodical testing of intervention components that can change food purchase behaviors is needed, in order to craft an mHealth intervention package that is feasible, acceptable, and optimized for efficacy and scalability. The proposed study will enroll adults (N = 64) who have low adherence to cancer prevention dietary recommendations. All participants will attend a 3-hour nutrition education workshop. For 6 months following the workshop, all participants will receive text notifications that provide tailored reminders and recommendations for food purchasing. The study will use a factorial design to experimentally test four additional intervention components and examine their feasibility, acceptability, and effect on food purchases and dietary intake at 3 and 6 months. (Each component is randomly assigned to be activated for 50% of participants.) The four components to be tested are: 1) Location-triggered text notifications: Reminders and recommendations for food purchases are delivered “just-in-time,” when arriving at grocery shopping locations, to enhance goal salience. 2) Reflections on the benefits of change: To enhance motivation, content is added to messages to encourage reflection on the anticipated benefits of healthy eating. 3) Coach monitoring: Food purchases are automatically monitored by a coach (through a system that collects item-level store data) who sends personalized post-purchase messages designed to enhance supportive accountability and thus motivation. 4) Household text: Other adults in the household receive messages designed to elicit support for healthy food purchasing and provide another source of supportive accountability. The preliminary aim of the study is to assess feasibility and acceptability of the intervention components. The primary aim of the study is to quantify the effect of each intervention component, individually and in combination, on grocery store food purchases (objectively assessed with store data), and dietary intake (assessed with 24-hour food recalls). Mediation analyses also will be conducted. The overarching goal of this project is to optimize this mHealth intervention, which can be tested in the future in a fully powered clinical trial.