Implementing an evidence-based mHealth diet and activity intervention: Make Better Choices 2 for rural Appalachians

摘要 我们提出了一种类型1的混合有效性-实施研究来测试适应的基于证据的 干预和探索关键的实施问题，包括可行性、可接受性和成本 影响规模扩大和持续发展。我们将这项适应性、有效性和实施研究的重点放在 服务不足的农村居民，他们保持着极高的次优饮食和久坐不动的比率 行为，使他们患心血管疾病、肥胖、糖尿病、癌症和其他疾病的风险增加 慢性疾病。在阿巴拉契亚地区农村居民社会经济地位较低的弱势群体中 肯塔基州人的健康状况甚至更差，包括发病率最高和 全国的死亡率。这种逆境因社区资源不足而加剧，并与之相关。 然而，阿巴拉契亚居民和其他弱势群体正在越来越多地获得 可能有助于应对这些健康挑战的模式，包括互联网连接和近 无处不在的手机使用。尽管这种技术的使用正在加速，但基于个人的证据 在农村高需求人群中，与技术相关的干预措施(MHealth)仍然很少。我们建议 最终确定适应并测试基于证据的多组件mHealth干预，使之变得更好 选择2(MBC2)，这是一个由个性化健康指导、应用程序、加速计、 和财政奖励。在最近一项在城市成年人中进行的随机对照试验中，MBC2产生了大量 通过利用有效的行为改变技术持续改善饮食和体力活动， 包括目标设定、自我监控、责任追究和支持。为实施这一点做好准备 成功地干预了以极端健康不平等和资源稀缺为标志的新人口，我们的 该小组在动态适应进程框架的基础上开展了广泛的基础工作。 这些措施包括：(1)完成焦点小组和主要线人访谈，以评估可行性和 阿巴拉契亚农村居民使用MBC2计划的接受度；(2)开展全面的 社区清单，以显示现有和需要的资源；(3)让利益攸关方参与社区和 学术团队会议，包括社区论坛和CAB会议；以及(4)确定MBC2 需要调整的方案和结构要素。通过这次广泛的前期活动，我们现在 提出了一种类型1的混合有效性-实现试验，在该试验中：(1)通过线框和 与阿巴拉契亚当地居民一起测试MBC2的可用性；(2)进行RCT以测试 调整后的MBC2与主动控制ARM进行比较；以及(3)探索实施成果和背景 因素，重点是维持。这个项目渴望证明系统的适应和 实施循证干预可以带来有意义和持续的行为变化， 并为干预措施的可能扩大和持续做好准备，以最大限度地提高其对公共卫生的影响。

ABSTRACT We propose a type 1 hybrid effectiveness-implementation study to test an adapted evidence-based intervention and explore critical implementation issues, including feasibility, acceptability, and costs, that influence scale-up and sustainment. We focus this adaptation, effectiveness, and implementation study on underserved rural residents, a population that maintains extremely high rates of suboptimal diet and sedentary behaviors, placing them at elevated risk for cardiovascular disease, obesity, diabetes, cancer, and other chronic conditions. Within the vulnerable low socioeconomic status population of rural residents, Appalachian Kentuckians experience even worse health outcomes, including among the highest rates of morbidity and mortality in the nation. Such adversity is exacerbated by and associated with inadequate community resources. Increasingly, however, Appalachian residents and other vulnerable populations are gaining access to modalities that may be useful in addressing these health challenges, including internet connectivity and nearly ubiquitous cell phone use. Despite this accelerating technology use, the evidence base on personal technology-associated interventions (mHealth) in a rural, high need population remains sparse. We propose finalizing adaptation and testing an evidence-based multicomponent mHealth intervention, Make Better Choices 2 (MBC2), a behavioral program consisting of personalized health coaching, an app, accelerometer, and financial incentives. In a recent randomized controlled trial among urban adults, MBC2 produced large, sustained diet and physical activity improvements by leveraging effective behavior change techniques, including goal-setting, self-monitoring, accountability, and support. To prepare for the implementation of this successful intervention with a new population marked by extreme health inequities and sparse resources, our team has engaged in extensive foundational efforts based on the Dynamic Adaptation Process framework. These include: (1) completing focus groups and key informant interviews to assess the feasibility and acceptability for rural Appalachian residents to use the MBC2 program; (2) undertaking a comprehensive community inventory to reveal existing and needed resources; (3) engaging stakeholders in community and academic team meetings, including community forums and CAB meetings; and (4) identifying MBC2 programmatic and structural elements in need of adaptation. With this extensive preliminary activity, we now propose a type 1 hybrid effectiveness-implementation trial in which we: (1) finalize adaptation by wireframe and usability testing MBC2 with local Appalachian residents; (2) conduct a RCT to test the effectiveness of the adapted MBC2 compared to an active control arm; and (3) explore implementation outcomes and contextual factors, with a focus on sustainment. This project aspires to demonstrate that systematic adaptation and implementation of an evidence-based intervention can lead to meaningful and sustained behavioral changes, and to prepare for potential scale-up and sustainment of the intervention to maximize its public health impact.