Strengthening Causal Inference in Behavioral Obesity Research

加强行为肥胖研究中的因果推断

• 批准号: 10442511
• 负责人: DAVID B ALLISON
• 金额: $ 20.59万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10442511
• 关键词: Address; Adult; Affect; Alabama; Behavior; Behavior Therapy; Behavioral; Behavioral Sciences; Biomedical Research; Body Composition; Clinical; Clinical Trials; Cluster randomized trial; Collaborations; Communities; Complex; Cookbook; Deception; Dietary Practices; Disadvantaged; Discipline; Economics; Educational process of instructing; Epidemiologic Methods; Epidemiology; Etiology; Experimental Designs; Exposure to; Faculty; Feedback; Foundations; Genetic; Health; Health Policy; Indiana; Individual; Instruction; Internet; Intervention; Lead; Learning; Location; Mathematics; Measures; Medicine; Meta-Analysis; Methodology; Methods; Modeling; Natural experiment; Nutritional Study; Obesity; Outcome; Pathway interactions; Philosophy; Physiological; Policies; Population; Population Distributions; Positioning Attribute; Prevalence; Prevention; Prize; Psychology; Public Health; Quasi-experiment; Randomized; Randomized Controlled Trials; Recommendation; Reporting; Research; Research Design; Research Misconduct; Research Personnel; Research Technics; Resources; Science; Scientist; Strategic Planning; Techniques; Testing; Training; United States National Institutes of Health; Universities; Variant; base; behavioral study; behavioral/social science; case control; design; energy balance; experience; experimental study; genetic approach; improved; interdisciplinary approach; novel; novel strategies; personalized approach; prospective; psychologic; social; sound; statistics; unethical

Project Summary/Abstract Identifying causal relations is fundamental to a science of intervention and prevention. Obesity is a major problem for which much progress in understanding, treatment, and prevention remains to be made. Behavior is a vital contributor to variations in energy balance and body composition, the final common pathways of obesity. Social, environmental and physiological factors are also key influences on behaviors which affect energy balance. Evidence for causation of these hypothesized factors exists on a continuum from weakest to strongest. Yet, most obesity research does not consider the evidence continuum between ordinary association tests (OATs) (observational, non-intervention studies among unrelated individuals), which do not offer strong evidence of causal effects, and randomized controlled trials (RCTs), which do offer strong evidence, but cannot be done in all circumstances. In contrast, there are techniques that lie intermediary between OATs and RCTs, including but not limited to quasi-experimental studies and natural experiments. Such designs are increasingly used, especially in the disciplines of economics and genetics, but are used by obesity researchers less often than seems warranted. Our ability to draw causal inferences in obesity research could be strengthened by using such approaches. In-depth understanding and appropriate use of the full continuum of these methods requires input from disciplines including statistics, economics, psychology, epidemiology, mathematics, philosophy, and behavioral or statistical genetics. Applying these techniques, however, does not involve routine ‘cookbook’ approaches but requires understanding of underlying principles, so the investigator can tailor approaches to specific and varying situations. Yet, other than our annual 5-day short course, no resource provides such training, particularly for behavioral and social science researchers. Our short course on methods for causal inference in obesity research, which features some of the world’s finest scientists, has been consistently evaluated by attendees as essential for their research and teaching. The course provides rigorous exposure to the key fundamental principles underlying a broad array of techniques and experience in application through guided discussion using real examples. The course is dynamic in that we refine and modify its content and delivery methods based on feedback from stakeholders. In this renewal application, we propose to continue to offer this course, alternating its location between Indiana University and the University of Alabama at Birmingham. Given the prevalence of obesity and its related health problems, training behavioral and social science researchers to better assess causal effects is more important than ever.

项目概要/摘要 识别因果关系是干预和预防科学的基础。肥胖是一个大问题 对此，在认识、治疗和预防方面仍有待取得很大进展。行为举止至关重要 导致能量平衡和身体成分变化，这是肥胖的最终常见途径。社会的， 环境和生理因素也是影响能量平衡行为的关键影响因素。 这些假设因素的因果关系证据存在于从最弱到最强的连续体中。然而，大多数 肥胖研究不考虑普通关联测试（OAT）之间的证据连续体 （在无关个体中进行的观察性、非干预性研究），没有提供强有力的证据 因果效应和随机对照试验（RCT）确实提供了强有力的证据，但不能在 所有情况。相比之下，有些技术介于 OAT 和 RCT 之间，包括但 不限于准实验研究和自然实验。此类设计被越来越多地使用， 特别是在经济学和遗传学学科中，但肥胖研究人员使用的频率低于 似乎有道理。通过使用这样的方法可以增强我们在肥胖研究中得出因果推论的能力 接近。深入理解和正确使用这些方法的完整连续体需要输入 来自统计学、经济学、心理学、流行病学、数学、哲学等学科 行为或统计遗传学。然而，应用这些技术并不涉及常规的“食谱” 方法，但需要了解基本原理，因此研究人员可以根据需要定制方法 具体和不同的情况。然而，除了我们每年为期 5 天的短期课程外，没有任何资源提供此类培训， 特别是对于行为和社会科学研究人员。我们关于因果推理方法的短期课程 由世界上一些最优秀的科学家参与的肥胖研究得到了一致的评估 与会者对于他们的研究和教学至关重要。该课程提供对关键知识的严格接触 通过指导，掌握广泛技术和应用经验的基本原理 使用真实例子进行讨论。该课程是动态的，我们会完善和修改其内容和授课方式 基于利益相关者反馈的方法。在此续订申请中，我们建议继续提供此服务 当然，其地点在印第安纳大学和阿拉巴马大学伯明翰分校之间交替。给定 肥胖及其相关健康问题的流行，培训行为和社会科学研究人员 更好地评估因果效应比以往任何时候都更加重要。