Developing a Diabetes Numeracy Intervention for American Indians/Alaska Natives

描述（由申请人提供）：为美国印第安人/阿拉斯加原住民开发糖尿病算术干预项目概述糖尿病患者必须参与各种自我保健行为，包括适当的饮食习惯，血糖自我监测和药物管理。理解和使用数字（例如，计算碳水化合物）的能力对这些行为都很重要。这种能力被称为“计算能力”，与各种糖尿病自我护理行为和结果（例如，血糖控制）有关。虽然糖尿病的患病率在全国范围内有所上升，但美国印第安人和阿拉斯加原住民（AI/ANs）被诊断患有糖尿病的比率是非西班牙裔白人的2-3倍。然而，土著人面临着数字技能限制的风险，而这对糖尿病管理至关重要。虽然计算能力方面的缺陷很普遍，但这种限制在种族/族裔少数群体和收入和教育有限的个人中尤为普遍。由于许多AI/AN社区的教育机会有限和贫困率高，土著糖尿病患者面临糖尿病相关计算能力受限的风险。尽管有证据表明计算能力与健康之间存在联系，但没有任何旨在改善与健康有关的计算能力的干预措施发表。拟议项目的目标是开发和试点测试一种干预措施，以提高患有糖尿病的人工智能/人工智能的糖尿病相关数字技能。该项目的目的如下：(1)发展一种文化上适当的干预措施，教授成功的糖尿病自我管理所需的数字技能；(2)评估干预后计算能力的变化；(3)探讨干预后糖尿病患者自我效能感、自我护理行为和临床结局的变化，并评估计算能力的变化是否能预测这些次要结局的变化。“提高糖尿病患者计算能力干预计划”（intent）将改编自现有的两门计算能力课程——“扩展数学能力”（EMPower）和“行动统计”（SfA）——这两门课程旨在教授成年人处理日常数字任务所需的数学技能。项目团队包括人工智能/网络健康和糖尿病计算方面的专家，以及EMPower和SfA的开发人员，他们将调整这些课程，以解决人工智能/网络中的糖尿病管理问题。intention将在一项随机对照试验中进行测试，该试验涉及来自华盛顿州Toppenish的Yakama Indian Health Center的130名AI/AN糖尿病患者。分析将评估参与intention的患者是否比对照组患者在计算能力、自我效能、自我护理行为和临床结果方面表现出更大的改善。由于文献中尚未报道旨在改善与健康相关的计算能力的干预措施，因此这一创新项目将推进与计算能力相关的科学，并强调干预人工智能/人工智能人群和其他有糖尿病及其并发症风险的人群的新途径。由于管理心血管疾病和高血压等其他严重健康问题也需要类似的数字技能，因此这项工作的结果也可能为制定针对其他疾病的有效干预措施提供信息。

DESCRIPTION (provided by applicant): Developing a Diabetes Numeracy Intervention for American Indians/Alaska Natives Project Summary Patients with diabetes must engage in a variety of self-care behaviors, including appropriate dietary practices, blood glucose self-monitoring, and medication management. Important to each of these behaviors is the capacity to understand and use numbers (e.g., counting carbohydrates). Referred to as "numeracy," such abilities are associated with a variety of diabetes self-care behaviors and outcomes (e.g., glycemic control). Although the prevalence of diabetes has raised nationwide, American Indians and Alaska Natives (AI/ANs) are diagnosed with diabetes at 2-3 times the rate of non-Hispanic Whites. And, yet, Native people are at risk for limitations in the numerical skills that are criticl for diabetes management. Although deficits in numeracy are widespread, such limitations are particularly common among racial/ethnic minorities and individuals with limited income and education. As a result of restricted educational opportunities and high rates of poverty in many AI/AN communities, Native people with diabetes are at risk for limitations in diabetes-related numeracy. Despite evidence of a link between numeracy and health, no interventions aimed at improving health- related numeracy have been published. The goal of the proposed project is to develop and pilot test an intervention to improve diabetes-related numerical skills among AI/ANs with diabetes. The aims of the project are the following: (1) To develop a culturally appropriate intervention to teach the numerical skills required for successful diabetes self-management; (2) To assess change in numeracy skills following intervention; and (3) To explore change in diabetes self-efficacy, self-care behavior, and clinical outcomes following intervention and to assess whether change in numeracy predicts change in these secondary outcomes. The INTervention to Enhance Numeracy in Diabetes (INTEND) will be adapted from two existing numeracy curricula - Extending Mathematical Power (EMPower) and Statistics for Action (SfA) - which were developed to teach adults the math skills needed to manage everyday numerical tasks. The project team, which includes experts in AI/AN health and diabetes numeracy as well as the developers of EMPower and SfA, will adapt these curricula to address diabetes management among AI/ANs. The INTEND will be tested in a randomized controlled trial involving 130 AI/AN patients with diabetes from Yakama Indian Health Center in Toppenish, WA. Analyses will assess whether patients who participate in the INTEND show significantly greater improvement in numeracy, self-efficacy, self-care behavior, and clinical outcomes than do control patients. As no interventions designed to improve health-related numeracy have been reported in the literature, this innovative project will advance science related to numeracy and highlight a new avenue for intervening with AI/ANs and other populations at risk for diabetes and its complications. As similar numerical skills are required in the management of other serious health problems, such as cardiovascular disease and hypertension, the results of this work may inform the development of effective interventions for other conditions as well.