A Network Analytic Model of Adherence and Abstinence

描述(申请人提供)：健康行为是健康的唯一最大决定因素。我们希望人们按处方服药，遵循健康饮食，获得充足的睡眠，避免有害物质和成瘾。这些行为可能被认为是二元行为--坚持和禁欲--个人可能会参与--也可能不参与--在日常生活中。然而，药物使用治疗或戒除的临床试验使用的效果衡量标准大相径庭。对于这些不同的测量，没有明显的生物学或行为学解释。此外，坚持和禁欲的衡量标准往往无法解释健康行为模式的丰富变化。这些坚持或禁欲的模式可能进一步有助于个人的预后。这一建议提供了一种新的方法来衡量坚持和禁欲，使用改编自网络分析的概念。伽马指数衡量的是服用剂量(或未服用物质)之间的关联性，在一个创新的代数模型中，它解释了个人坚持或禁欲的模式。这一指数可以用来模拟依从性和禁欲，以检查它们对临床相关生物学结果的影响。对于完全不遵守(或非禁欲)，Gamma的值为0，对于完全坚持(或完全禁欲)，Gamma的值为1。我们建议分析从四个领域完成的临床试验的一系列数据集：(1)艾滋病毒/艾滋病患者坚持高效抗逆转录病毒疗法(HAART)；(2)阿片依赖患者坚持丁丙诺啡治疗；(3)戒烟试验中戒烟；以及(4)酒精使用障碍患者试验中戒酒或减少饮酒。在抗病毒依从性的试验中，我们将检查两者之间的联系 指数和病毒载量的变化之间的关系。在烟草、酒精和药物治疗的试验中，我们将检查该指数与长期禁酒率之间的关系。该项目的具体目标是(1)评估伽玛指数在HIV感染者的抗病毒治疗试验中提高对病毒载量变化的坚持的解释力的能力，以及(2)评估伽玛指数解释在有药物使用障碍的受试者的试验中停药终点差异的能力，例如酗酒、吸毒和吸烟。这种建模需要每日依从性(或物质使用)记录，这使得使用生态瞬时评估(EMA)方法、时间线跟踪技术或电子药帽数据的这些研究变得理想。该项目的杰出跨学科团队包括在遵守、图论和网络分析、艾滋病毒的治疗以及合法和非法物质的使用方面的知名专家。伽马指数提供了对健康行为的潜在模式、它们与临床结果的关系、量化这些模式的手段以及促进健康行为的新的实时干预的可能性的新见解。

DESCRIPTION (provided by applicant): Health behavior is the single greatest determinant of health. We want people to take their medication as prescribed, follow healthful diets, get adequate sleep, and avoid harmful substances and addictions. These actions may be thought of as binary behaviors-adherence and abstinence-that individuals may engage in-or not-on a daily basis. Yet, clinical trials of substance use treatment or abstinence use widely disparate measures of effect. There is no obvious biological or behavioral explanation for these disparate measurements. Further, measures of adherence and abstinence often fail to account for the rich variation in the pattern of the health behavior. These patterns of adherence or abstinence may further contribute to the individual's prognosis. This proposal offers a novel method to measure adherence and abstinence, using concepts adapted from network analysis. The gamma index, which measures the connectedness of doses taken (or substances not taken), accounts for the pattern of an individual's adherence, or abstinence, in an innovative algebraic model. This index can be used to model adherence and abstinence to examine their effect on clinically relevant biologic outcomes. Gamma is bounded at a value of 0 for perfect non-adherence (or non-abstinence), and 1 for perfect adherence (or perfect abstinence). We propose to analyze a series of datasets from completed clinical trials in four domains (1) adherence to Highly Active Antiretroviral Therapy (HAART) in subjects with HIV/AIDS; (2) adherence to buprenorphine treatment in subjects with opioid dependence; (3) abstinence from tobacco in trials of smoking cessation; and (4) abstinence or reduction in drinking in trials of subjects with alcohol use disorders. In trials of antiviral adherence, we will examine associations between the index and changes in viral load. In trials of tobacco, alcohol and drug treatment, we will examine associations between the index and long-term abstinence rates. The Specific Aims of this project are to (1) Assess the ability of the gamma index to improve the explanatory power of adherence on changes in viral load in trials of antiviral therapy in individuals infected with HIV, and (2) Assess the ability of the gamma index to explain differences in cessation endpoints in trials of subjects with substance use disorders, such as alcohol abuse, drug use, and smoking. Daily records of adherence (or substance use) are needed for this modeling, which makes these studies, which employ ecological momentary assessment (EMA) methods, timeline follow-back techniques, or electronic pill cap data, ideal. The outstanding interdisciplinary team for this project includes renowned experts in adherence, graph theory and network analysis, the treatment of HIV, and use of licit and illicit substances. The gamma index offers to provide new insights into underlying patterns of health behavior, their relationship to clinical outcomes, a means of quantifying these patterns, and the possibility of novel real-time interventions to promote healthy behaviors.