Diabetes Risk Education and Communication Trial (DiRECT) for Primary Care Patients with Prediabetes

项目摘要 大型随机试验发现，强化生活方式干预（ILI）和二甲双胍是安全的， 预防糖尿病前期成人糖尿病的有效治疗选择。然而，这些治疗 很少使用，并且现有的研究很少关注以患者为中心的方法来促进其使用。 大量的证据表明，风险沟通干预是一种很有前途的激励方法。 患者采取多种预防性健康行为。但这种方法尚未得到明确的研究， 预防糖尿病的背景。因此，沟通糖尿病风险的内容、结构和过程 对糖尿病前期的成年人的影响尚不清楚。我们计划通过开发和试点来解决这一关键的知识差距 在初级保健中测试糖尿病风险教育和沟通试验（DiRECT）干预措施 糖尿病前期患者。这种新的干预措施，由医疗助理在患者例行检查之前提供， 计划的门诊访视包括以下3个部分，旨在促进ILI和二甲双胍的启动： 1)糖尿病前期决策辅助工具，重点关注糖尿病风险和预防糖尿病的治疗方案; 2）“思考” 3）制定初步治疗方案。先前的研究报告称， 可以提高初级保健中一些预防性卫生服务的利用率，这对ILI也可能是如此， 二甲双胍。我们将通过完成以下具体目标来检验这一假设。在目标1中，我们将开发 直接干预使用的材料，我们的小组已经创建和试点测试的目标人群。我们将 聘请专家咨询小组的利益相关者在糖尿病预防，谁将帮助制定干预措施 以便在发现有效时广为传播。目标2将评估DireCT的效果 干预患者对患糖尿病风险的感知和他们接受治疗的意愿，此外， 其他可能影响治疗决策的因素。目的3是一项比较DiRECT与常规治疗的初步随机试验 在80例糖尿病前期初级保健患者中（每组40例）。这一务实的试点试验将估计 DiRECT对以下3个月结局的初步影响：开始ILI和/或二甲双胍（主要）; 坚持这些治疗;和体重减轻。我们还将研究干预的可接受性、影响 临床工作流程和成本。我们假设，经验开发的DIRECT干预将改善 参与者风险认知的准确性，并增加他们开始治疗以预防糖尿病。这 研究将在一个大型社区卫生中心进行，其中90%的糖尿病前期患者是 少数民族和83%的人生活在贫困中。我们的建议是响应PAR-15-158：1）包括低- 收入，不同的人口; 2）使用医疗助理，这是一个无处不在的劳动力，因此可以扩展到 大多数初级保健环境;以及3）利用现有的数据基础设施来务实地评估参与者的 并收集其临床数据。

Project Summary Large randomized trials have found that intensive lifestyle interventions (ILI) and metformin are safe and effective treatment options for preventing diabetes among adults with prediabetes. However, these treatments are rarely used, and little existing research has focused on patient-centered approaches for promoting their use. A large body of evidence suggests that risk communication interventions are a promising method for motivating patients to adopt diverse preventive health behaviors. But this approach has not been definitively studied in the context of diabetes prevention. Therefore, the content, structure, and process for communicating diabetes risk to adults with prediabetes is not known. We plan to address this critical knowledge gap by developing and pilot testing the Diabetes Risk Education and Communication Trial (DiRECT) intervention among primary care patients with prediabetes. This novel intervention, delivered by medical assistants before patients’ routinely scheduled office visits, consists of the following 3 components intended to promote initiation of ILI and metformin: 1) a prediabetes decision aid focused on diabetes risk and treatment options for preventing diabetes; 2) a “think aloud” exercise; and 3) formulating a preliminary treatment plan. Previous studies report that medical assistants can improve uptake of some preventive health services in primary care, which may also be true for ILI and metformin. We will test this hypothesis by completing the following specific aims. In Aim 1, we will develop the DiRECT intervention using materials that our group has created and pilot tested in the target population. We will engage an Expert Advisory Panel of stakeholders in diabetes prevention, who will help develop the intervention so that can be widely disseminated if found to be effective. Aim 2 will evaluate the effects of the DiRECT intervention on patients’ perceived risk of developing diabetes and their intention to adopt treatment, in addition to other factors that may impact treatment decisions. Aim 3 is a pilot randomized trial of DiRECT vs. usual care in 80 primary care patients with prediabetes (40 in each arm). This pilot pragmatic trial will estimate the preliminary effects of DiRECT on the following 3-month outcomes: initiation of ILI and/or metformin (primary); adherence to these treatment(s); and weight loss. We will also examine the intervention’s acceptability, impact on clinical workflows, and costs. We hypothesize that the empirically developed DiRECT intervention will improve the accuracy of participants’ risk perceptions and increase their initiation of treatments to prevent diabetes. This study will be conducted in a large community health center, in which 90% of patients with prediabetes are racial/ethnic minorities and 83% live in poverty. Our proposal is responsive to PAR-15-158 by: 1) including a low- income, diverse population; 2) using medical assistants, a workforce that is ubiquitous and therefore scalable to most primary care settings; and 3) leveraging an existing data infrastructure to pragmatically assess participants’ eligibility and collect their clinical data.