Data integration for causal inference in behavioral health

行为健康，广义上包括心理健康和物质使用，包括许多最重要的 我们这个时代最紧迫的公共卫生问题。向数据丰富、网络互联的社会过渡， 产生了一个产生解决方案的机会，但它需要在劳动力培训方面进行范式转变， 数据分析这个培训计划的目标是培养学者成为领导者在使用先进的 计算方法和设计，以估计行为健康的因果影响。为了实现这一目标， 我们将提供严格的培训和高质量的指导：1）行为健康科学; 2） 用于管理、分析和整合复杂数据源的计算和分析工具;以及3）因果关系 充分利用这些数据的推理方法。学员将获得跨学科的团队为基础的 培训，并将获得对所有三个领域的深刻理解。该培训计划将利用 丰富的资源，行为健康，分析和计算方法，以及生物统计学在约翰 霍普金斯布隆伯格公共卫生学院（JHSPH）和更广泛的大学。该计划将被安置在 但每年5名受训人员将来自四个社会科学部门中的任何一个。 在JHSPH面向部门：1）心理健康; 2）健康行为与社会; 3）健康政策和 （4）人口、家庭和生殖健康。此外，培训补助金将利用 与来自整个大学的数据科学家，统计学家和计算机科学家的联系。学员将 获得领导多学科合作研究团队所需的技能和经验。学员将 在公共卫生和行为健康的核心领域进行严格的课程计划 包括行为和社会科学、流行病学、生物统计学、数据科学、人口健康 信息学、因果推理和研究伦理。此外，每名受训人员还将选修其他课程 在心理健康和物质使用的社会和行为观点，信息学和计算技能， 以及因果和统计推断。学员将参加为期一年的行为分析研讨会， 保健，每两周一次的研讨会，讨论正在进行的研究和专业发展，持续辅导 研究项目和综合活动，以补充他们的教学课程。的重点领域 计划建立在JHSPH的优势之上;这些领域也被OBSSR，NIMH， 和NIDA。学员将得到一个由21名核心教师组成的经验丰富的小组的支持，每个学员将 由9个具有方法论专业知识的附属学院之一共同提供建议。培训计划主任，博士。 伊丽莎白·斯图尔特是行为健康分析工具的全国领导者，她将得到一个4- 一个内部执行委员会和一个5人外部咨询委员会。首要目标 该计划的目的是确定和培养学者谁将成为领导者在使用先进的多样性 分析工具和数据，以回答行为健康的关键问题。

Behavioral health, broadly defined to include mental health and substance use, includes many of the most pressing public health problems of our time. The transition to a data-rich, web-interconnected society has generated an opportunity to generate solutions, but it necessitates a paradigm shift in workforce training in data analytics. The goal of this training program is to train scholars to become leaders in the use of advanced computational methods and designs to estimate causal effects in behavioral health. To accomplish this goal, we will provide rigorous training and high-quality mentorship in: 1) the science of behavioral health; 2) computational and analytic tools to manage, analyze, and integrate complex data sources; and 3) causal inference methods to take full advantage of these data. Trainees will receive interdisciplinary team-based training and will acquire a deep understanding of all three areas. This training program will capitalize on the rich resources for behavioral health, analytic and computational methods, and biostatistics at the Johns Hopkins Bloomberg School of Public Health (JHSPH) and the broader University. The program will be housed in the Department of Mental Health but the 5 trainees per year will come from any of the four social science oriented departments at JHSPH: 1) Mental Health; 2) Health Behavior & Society; 3) Health Policy & Management; and 4) Population Family & Reproductive Health. Further, the training grant will leverage close connections with data scientists, statisticians, and computer scientists from across the University. Trainees will obtain the skills and experiences needed to lead multi-disciplinary, collaborative research teams. Trainees will undertake a rigorous program of coursework in the core domains of public health and behavioral health including behavioral and social science, epidemiology, biostatistics, data science, population health informatics, causal inference, and research ethics. In addition, each trainee will take additional elective courses in social and behavioral perspectives on mental health and substance use, informatics and computational skills, and causal and statistical inference. Trainees will participate in a year-long seminar on analytics for behavioral health, a bi-weekly seminar to discuss research in progress and professional development, ongoing mentored research projects, and integrative activities to complement their didactic curriculum. The focus area of the program builds on strengths within JHSPH; these areas also are highlighted as priorities by OBSSR, NIMH, and NIDA. The trainees will be supported by an experienced group of 21 core faculty and each trainee will be co-advised by one of 9 affiliated faculty with methodological expertise. The training program director, Dr. Elizabeth Stuart, is a national leader in analytic tools for behavioral health, and will be supported by a 4- member internal Executive Committee and a 5-member external Advisory Committee. The overarching aim of the program is to identify and train scholars who will become leaders in using a diversity of advanced analytic tools and data to answer key questions in behavioral health.