Addressing Rural Health Disparities by Optimizing "High Touch" Intervention Components in Digital Obesity Treatment

通过优化数字肥胖治疗中的“高接触”干预措施来解决农村健康差异

• 批准号: 10601655
• 负责人: Rebecca A. Krukowski
• 金额: $ 68.69万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10601655
• 关键词: Accountability; Address; Adult; Aftercare; Age; Area; Behavior Therapy; Behavioral; Body Weight decreased; Chronic Disease; Clinical; Communities; Congresses; County; Diabetes Mellitus; Dietary intake; Effectiveness; Electronic Mail; Elements; Enrollment; Ethnic Origin; Feedback; Gender; Geography; Human; Human Resources; Individual; Informal Social Control; Internet; Intervention; Life Style; Mediator; Minority; Monitor; Morbidity - disease rate; Motivation; Needles; Obesity; Outcome; Overweight; Participant; Persons; Physical activity; Pilot Projects; Policies; Population; Problem Solving; Process; Professional counselor; Public Health; Race; Randomized; Research; Resources; Risk; Rural; Rural Community; Rural Population; Site; Social support; Subgroup; Testing; Time; Touch sensation; United States; United States Centers for Medicare and Medicaid Services; Weight; Weight Gain; Weight maintenance regimen; comorbidity; cost; diabetes prevention program; digital; digital delivery; digital intervention; digital treatment; ethnic minority; evidence base; experience; experimental study; health disparity; implementation cost; lifestyle intervention; male; multiphase optimization strategy; obesity treatment; online intervention; prevent; programs; racial minority; recruit; remote delivery; rural area; rural counties; rural dwellers; rural health disparities; rural setting; sex; telephone coaching; treatment optimization; treatment program; underserved community; video session; weight loss intervention

Over 130 million individuals in the US have overweight and obesity, and rural communities experience significantly higher rates of obesity and related chronic diseases. Fortunately, weight losses of as little as 5-7% can ameliorate obesity-associated co-morbidities. Although lifestyle interventions successfully produce weight loss of this magnitude, the reach and availability of weight management programs is limited in rural areas. Digital interventions offer an attractive alternative for delivering lifestyle programs to rural populations. However, in-person behavioral obesity treatment programs achieve better weight losses than digital programs, likely because in-person programs typically include personnel-intensive “high touch” treatment components. Some studies indicate that having a human “behind the curtain” of a digital program, through emailed feedback or with the addition of online group sessions, can significantly increase weight loss. Thus, to reduce obesity- associated health disparities experienced by rural populations, it is time to move the field forward by identifying the specific constellation of human-delivered digital treatment components that produce the strongest weight loss outcomes. Therefore, the aims of this study are to increase the public health impact of digital obesity treatment for rural populations by simultaneously investigating 3 “high touch” intervention components. We will conduct a highly efficient 2 x 2 x 2 factorial experiment using the MOST framework with participants residing in non-urban areas recruited online from across the United States. Participants (N=616; 22% racial/ethnic minority; 40% male) will be randomized to: (1) weekly facilitated synchronous group video sessions (yes vs. no); (2) type of self-monitoring feedback received (counselor-crafted vs. pre-scripted); and (3) individual coaching calls (yes vs. no). Based on the results of the experiment, we will identify an optimized program in which each component (or combination of components) contributes meaningfully (≥1.5 kg at 6- months) to enhanced weight loss. We will investigate potential mediators (e.g., accountability, social support, self-regulation, motivation, and problem solving), as well as possible mediators (e.g., sex/gender, race/ethnicity, age), to explore their impact on weight loss outcomes. We will also examine treatment delivery costs for each component and conduct exploratory analyses of weight trajectories 6-months post-treatment (i.e., at 12 months) to elucidate the extended impact of the specific components on weight control. Ultimately, this research will set the stage for confirming the most promising digital behavioral weight loss intervention for dissemination without geographic borders to reduce obesity rates among rural residents and provide essential evidence to inform policy decisions on optimal dissemination.

美国有超过 1.3 亿人超重和肥胖，农村社区也存在这种情况 肥胖和相关慢性疾病的发生率显着升高，幸运的是，体重减轻幅度仅为 5-7%。 尽管生活方式干预成功地产生了体重，但可以改善与肥胖相关的并发症。 由于体重下降幅度如此之大，农村地区体重管理计划的覆盖范围和可用性都受到限制。 数字干预措施为向农村人口提供生活方式计划提供了一种有吸引力的替代方案。 然而，面对面的行为肥胖治疗计划比数字计划能实现更好的减肥效果， 可能是因为面对面的项目通常包括人员密集的“高接触”治疗部分。 一些研究表明，有一个人通过电子邮件反馈来“幕后”数字化项目 或者加上在线小组课程，可以显着增加减肥效果，从而减少肥胖。 鉴于农村人口所经历的相关健康差异，现在是通过确定以下方面来推动这一领域向前发展的时候了： 人类提供的数字治疗组件的特定组合，可产生最强的重量 因此，本研究的目的是增加数字对公共卫生的影响。 通过同时调查3“高接触”干预措施对农村人口进行肥胖治疗 我们将使用 MOST 框架进行高效的 2 x 2 x 2 阶乘实验。 居住在非城市地区的参与者是从美国各地在线招募的参与者（N=616； 22% 少数族裔；40% 男性）将被随机分配到：(1) 每周主持的同步小组视频 会议（是与否）；（2）收到的自我监控反馈的类型（辅导员精心设计与预先编写的）； (3) 单独辅导电话（是与否）根据实验结果，我们将确定优化方案。 计划中每个组成部分（或组成部分的组合）都做出有意义的贡献（≥1.5 kg at 6- 月）以增强减肥效果。我们将调查潜在的调节因素（例如责任、社会支持、 自我调节、动机和解决问题），以及可能的调解因素（例如，性/性别、 种族/民族、年龄），探讨它们对减肥结果的影响。我们还将检查治疗的实施情况。 每个组成部分的成本并对治疗后 6 个月的体重轨迹进行探索性分析 （即 12 个月时）以阐明特定成分对体重控制的长期影响。 这项研究将为确认最有前途的数字行为减肥干预措施奠定基础 无地域限制的传播，以降低农村居民的肥胖率，并提供必需的 为最佳传播政策决策提供信息的证据。