Applying novel technologies and methods to inform the ontology of self-regulation

应用新技术和方法来告知自我监管本体

• 批准号: 9139956
• 负责人: Lisa A. Marsch
• 金额: $ 73.67万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9139956
• 关键词: Adherence; Alcohol or Other Drugs use; Area; Atlases; Bayesian Modeling; Behavior; Behavior Therapy; Behavior assessment; Behavioral; Biological; Biological Assay; Cataloging; Catalogs; Cessation of life; Chronic Disease; Cognitive; Data; Data Set; Development; Diabetes Mellitus; Diet; Disease; Elderly; Emotional; Equation; Evaluation; Exercise; Factor Analysis; Food; Functional Magnetic Resonance Imaging; Funding; Goals; Health; Health behavior; Health behavior change; Healthcare; Image; Informal Social Control; Internet; Intervention; Laboratories; Literature; Measures; Mechanics; Medical; Medicine; Mental Health; Methods; Modeling; Monitor; Obesity; Ontology; Outcome; Overweight; Pain management; Patient-Centered Care; Patient-Focused Outcomes; Pattern; Persons; Play; Population; Process; Regimen; Research; Resources; Rewards; Risk Behaviors; Role; Sampling; Science; Scientific Inquiry; Self Efficacy; Smoker; Smoking; Stimulus; Substance abuse problem; Technology; Testing; Time; Tobacco; United States National Institutes of Health; Validation; Work; base; behavior change; behavioral health; burden of illness; chronic pain; cost; cost effective; design; diet and exercise; effective intervention; emotion regulation; experience; health care service utilization; improved; medication compliance; mobile computing; neural circuit; new technology; novel; physical inactivity; population health; precision medicine; psychologic; ranpirnase; relating to nervous system; response; scale up; technology validation; tool

 DESCRIPTION (provided by applicant): Health risk behavior, including poor diet, physical inactivity, tobacco and other substance use, causes as much as 40% of the illness, suffering, and early death related to chronic diseases. Non-adherence to medical regimens is an important exemplar of the challenges in changing health risk behavior -- and is common, costly (due to increased utilization of healthcare services), and associated with poor patient outcomes. Although an array of interventions have been shown to be effective in promoting health behavior change, much of this work has been siloed (focused on one disorder at a time). Additionally, interventions are typically intended to engage multiple mechanisms of behavior change, but the mechanisms by which they actually work are infrequently systematically examined. One promising domain of putative behavior change targets is that of self-regulation -- a person's ability to manage cognitive, motivational, and emotional resources to act in accordance with his/her long-term goals. The Center for Technology and Behavioral Health, a national NIH-funded P30 "Center of Excellence" uses science to inform the development, evaluation, and implementation of technology (web, mobile)-based self- regulation tools for behavior change targeting a wide array of populations and health behaviors. This work examines behavioral phenomena (and the mechanisms by which they work) ranging from substance abuse, mental health, chronic pain management, medication adherence, diet, exercise, diabetes, and smoking. Self- regulation tools offered on mobile platforms enable widespread reach and scalability of effective interventions. In this proposal, we plan to examine putative targets (processes) of behavior change within the self- regulation mechanism domain across contexts, populations, and assays - in 3 primary levels of analysis: (1) psychological (e.g., constructs such as self-efficacy; emotion regulation; response inhibition), (2) behavioral (e.g., tasks of reward responsiveness; temporal horizon), and (3) biological (structural and functional MRI of key neural circuitry). We will evaluate the extent to which we can engage and manipulate these putative targets both within and outside of laboratory settings (using a novel mobile self-regulation monitoring and intervention platform). We will conduct this work with two populations for which behavior plays a critical role in the course of medical regimen adherence, health, and health outcomes: (1) smokers and (2) obese/overweight persons. We will then examine cross-assay validity and cross-context and cross-sample reliability of assays to identify relations among self-regulatory targets. We will finally evaluate the degree to which engaging targets produces a desired change in medical regimen adherence (across 4 week self-regulation interventions) and health behavior among smokers and obese/overweight persons. This project will identify valid and replicable assays of mechanisms of self-regulation across populations to inform an ontology of self-regulation that can ultimately inform development of health behavior interventions of maximal efficacy and potency.

 描述（由申请人提供）：健康风险行为，包括不良饮食，缺乏运动，烟草和其他物质的使用，导致多达40%的疾病，痛苦和与慢性病有关的过早死亡。不遵守医疗方案是改变健康风险行为的挑战的一个重要例子-并且是常见的，昂贵的（由于医疗保健服务的利用率增加），并与不良的患者结局相关。虽然一系列干预措施已被证明在促进健康行为改变方面是有效的，但大部分工作都是孤立的（一次只关注一种疾病）。此外，干预措施通常旨在参与行为改变的多种机制，但它们实际工作的机制很少被系统地检查。一个有前途的领域的假定行为改变目标是自我调节-一个人的能力，管理认知，动机和情感资源，按照他/她的长期目标。技术和行为健康中心是一个由NIH资助的国家P30“卓越中心”，它利用科学为基于技术（网络、移动的）的自我调节工具的开发、评估和实施提供信息，这些工具用于针对广泛人群和健康行为的行为改变。这项工作研究了行为现象（及其工作机制），包括药物滥用，心理健康，慢性疼痛管理，药物依从性，饮食，运动，糖尿病和吸烟。在移动的平台上提供的自我调节工具使有效干预措施能够广泛覆盖和扩展。在这个提议中，我们计划在跨情境、人群和测定的自我调节机制域中检查行为改变的假定目标（过程）-在3个主要分析水平中：（1）心理（例如，结构如自我效能;情绪调节;反应抑制），（2）行为（例如，奖励反应任务;时间范围），以及（3）生物学（关键神经回路的结构和功能MRI）。我们将评估我们在实验室环境内外（使用一种新的移动的自我调节监测和干预平台）参与和操纵这些假定目标的程度。我们将在两个人群中开展这项工作，对于这两个人群，行为在医疗方案依从性、健康和健康结果的过程中起着关键作用：（1）吸烟者和（2）肥胖/超重者。然后，我们将检查跨检测的有效性和跨上下文和跨样本的可靠性检测，以确定自我调节目标之间的关系。我们将最终评估参与目标在吸烟者和肥胖/超重人群中产生医疗方案依从性（4周自我调节干预）和健康行为的预期变化的程度。该项目将确定跨人群自我调节机制的有效和可复制的测定，以告知自我调节的本体，最终可以告知最大功效和效力的健康行为干预措施的发展。