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

摘要 我们提出了一个类型1混合有效性实施研究，以测试一个适应的循证医学 干预和探讨关键的实施问题，包括可行性，可接受性和成本， 影响扩大规模和维持。我们将这一适应性、有效性和实施研究的重点放在 服务不足的农村居民，这一人口保持着极高的次优饮食率和久坐不动 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。 慢性病在脆弱的低社会经济地位的农村居民，阿巴拉契亚 毛里塔尼亚人的健康状况更差，包括发病率最高， 死亡率在全国。这种困境因社区资源不足而加剧，并与之相关。 然而，越来越多的阿巴拉契亚居民和其他弱势群体正在获得 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加速技术的使用，证据基础上的个人 在农村，高需求人群中的技术相关干预措施（mHealth）仍然很少。我们提出 最后确定适应和测试基于证据的多成分移动健康干预措施，使更好 选择2（MBC 2），一个行为计划，包括个性化的健康教练，一个应用程序，加速度计， 和经济激励。在最近的一项针对城市成年人的随机对照试验中，MBC 2产生了大量， 通过利用有效的行为改变技术来持续改善饮食和身体活动， 包括目标设定、自我监督、责任和支持。为准备实施这一 成功的干预与新的人口特点是极端的健康不平等和稀缺的资源，我们的 团队在动态适应过程框架的基础上进行了广泛的基础工作。 这些措施包括：（1）完成焦点小组和关键线人访谈，以评估可行性， 阿巴拉契亚农村居民使用MBC 2计划的可接受性;（2）进行全面的 社区清单，以揭示现有的和所需的资源;（3）参与社区的利益相关者， 学术团队会议，包括社区论坛和CAB会议;以及（4）确定MBC 2 需要调整的方案和结构要素。通过这一广泛的初步活动，我们现在 提出了一种类型1混合有效性实施试验，其中我们：（1）通过线框完成适应， 可用性测试MBC 2与当地阿巴拉契亚居民;（2）进行随机对照试验，以测试的有效性， 适应MBC 2相比，主动控制臂;（3）探索实施结果和上下文 的因素，重点是可持续性。该项目旨在展示系统的适应和 实施循证干预可以导致有意义和持续的行为改变， 并为可能扩大和维持干预措施做好准备，以最大限度地扩大其公共卫生影响。

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.