A Mixed-Methods Evaluation of mHealth Weight Management for Racial/Ethnic Minorities

项目概要/摘要 在美国，肥胖是心脏代谢发病率和死亡率最普遍的可预防风险因素。 此外，肥胖症在少数种族/族裔中更为普遍，其发病率继续上升。 肥胖的种族/民族差异受到健康的社会决定因素的影响，这些决定因素有助于社会 在多个层面的影响力。在它们的影响中，健康的社会决定因素可以干扰 饮食和活动行为是肥胖的主要驱动力，也是体重的目标， 管理干预。干预措施需要考虑到社会不利地位的这些潜在影响。 移动的卫生干预措施特别有前途，因为它们具有覆盖面和效率 公平的人口传播。然而，社会不利因素干扰 mHealth治疗效果尚未得到很好的研究，因此目前还不清楚mHealth体重 管理干预在各种社会文化背景下产生公平的结果。的研究需要 探讨社会劣势是否限制了移动健康干预带来的好处，以便 通知潜在需要的优化。该项目将利用多种协同研究方法， 跨越干预证据谱来评估这个问题。系统性综述和荟萃分析将 提供关于mHealth肥胖治疗如何影响的研究文献的全面，严格的概述 可能会受到社会环境背景和不利因素的影响。二次定量分析 以前进行的mHealth减肥试验将评估多层次社会决定因素在多大程度上 健康行为的适度改善。最后，将采用定性访谈和分析 评估种族/少数民族参与者对参与移动健康的障碍和促进因素的看法 体重管理总之，这些协同方法要学习和应用在这个奖学金跨越 解析光谱它们的整合将建立一个连贯的基础，我们可以在此基础上推进移动健康 对少数种族/族裔的体重管理进行干预。

Project Summary/Abstract Obesity is the most prevalent preventable risk factor for cardiometabolic morbidity and mortality in the US. Additionally, obesity is more prevalent among racial/ethnic minorities whose rates continue to increase. Racial/ethnic disparities in obesity are influenced by social determinants of health that contribute to social disadvantage at multiple levels of influence. Among their influences, social determinants of health can interfere with the diet and activity behaviors that are the primary drivers of obesity and the targets of weight management interventions. Interventions need to account for these potential influences of social disadvantage. Mobile Health (mHealth) interventions are particularly promising because they have the reach and efficiency for equitable population-level dissemination. However, the degree to which social disadvantage interferes with mHealth treatment efficacy has not been well-studied, and so it is unclear whether mHealth weight management intervention produces equitable outcomes across sociocultural contexts. Research is needed to explore whether social disadvantage constrains the benefit derived from mHealth intervention, in order to inform potentially needed optimization. This project will leverage multiple synergistic research methods that span the intervention evidence spectrum to evaluate this question. A systematic review and meta-analysis will provide a comprehensive, rigorous overview of research literature on how mHealth obesity treatment effects may be moderated by socioenvironmental context and disadvantage. Secondary quantitative analyses of two previously conducted mHealth weight loss trials will evaluate the extent to which multilevel social determinants of health moderate improvements in health behaviors. Finally, qualitative interviews and analysis will be used to evaluate racial/ethnic minority participants’ perceptions of barriers and facilitators to engagement in mHealth weight management. Together, these synergistic methods to be learned and applied in this fellowship span the analytic spectrum. Their integration will build a coherent foundation upon which we can advance mHealth interventions for weight management among racial/ethnic minorities.