Network for Advancing Methodological Research in Longitudinal Studies of Aging

对接近退休阶段、整个退休阶段和退休后的人口进行纵向研究，如健康 和退休研究（HRS），在老龄化研究中发挥着重要作用，因为它们提供了生活数据， 过程的角度来看，使研究人员作出人口水平的因果推理。因为这样的数据 收集是研究人员与人口之间的社会互动，收集的方法 这些研究中的数据需要适应社会变化。美国人口老龄化 经历着快速的变化。首先，它的种族，民族和语言组成正在改变， 西班牙裔和亚裔美国人的数量不断增加。其次，人口老龄化对新能源的依赖 新型冠状病毒疫情加速了移动的和视频技术的发展。同时对 基于人口的数据收集的研究环境也有所发展， 行政记录可与调查数据相结合，现代设备的使用增加 用于收集人体测量和生物标志物数据，以补充传统的自我报告调查数据。 研究人员可以利用这些自然发生的趋势，并塑造方法创新， 未来的纵向研究例如，随着人口习惯于通过 在COVID-19大流行期间，基于人群的研究已经从使用电子设备过渡到使用 从单一访谈模式到混合模式，包括基于网络的数据收集和虚拟访谈。 不幸的是，关于老龄化人口最佳数据收集方法的方法学研究 迄今为止进行的评估有几个严重的缺点： 少数群体，获得行政记录链接同意的最佳方法， 生物标志物数据收集是未知的，需要用于对抗增加的损耗率的方法， 也没有对使用新技术收集数据进行方法研究。 我们建议建立一个国际知名的方法和实务专家网络， 正在积极研究新的数据收集方法的好处，以应对这些社会问题。 发展理念拟议的网络将定期举行会议，以具体形成方法创新 用于衡量老龄化人口和设计研究， 这种纵向测量的方法。有大量有影响力的纵向 目前该领域的老龄化研究将受益于这种协调，严格的 方法学调查更有效的方法来收集纵向措施从（和） 人口老龄化。通过协调的国际培训、咨询、专题工作组方案， 会议和试点研究项目，我们的目标是制定议程的方法研究纵向 研究老龄化和保护NIA投资的人口代表性纵向研究。

Longitudinal studies of the population near, through and after the retirement stage, such as the Health and Retirement Study (HRS), play an important role in aging research because they provide data from a life course perspective, allowing researchers to make population-level causal inference. Because such data collection is a social interaction between researchers and the population, the methods employed to collect data in these studies need to accommodate societal changes. The aging population in the U.S. is experiencing rapid changes. First, its racial, ethnic, and linguistic composition is being shifted by the growing Hispanic and Asian American populations. Second, the reliance of this aging population on new mobile and video technologies has been accelerated by the COVID-19 pandemic. At the same time, the research environment for population-based data collection has also evolved, with an increased availability of administrative records that can be integrated with survey data and the increased use of modern devices for collecting anthropometric and biomarker data that can complement traditional, self-report survey data. Researchers can capitalize on these naturally occurring trends and shape methodological innovations for future longitudinal studies. For example, as the population has become accustomed to communicating via electronic devices during the COVID-19 pandemic, population-based studies have transitioned from using one interview mode to mixing modes, including web-based data collection and virtual interviewing. Unfortunately, the methodological research on optimal data collection approaches for aging populations that has been performed to date has several critical shortcomings: there is a notable lack of data on minority subgroups, optimal approaches to obtaining consent for administrative record linkage and biomarker data collection are unknown, methods for combatting increasing rates of attrition are needed, and there is an absence of methodological research on the use of new technologies for data collection. We propose to form a network of internationally-renowned methodological and substantive experts who are actively researching the benefits of new data collection methodologies in response to these societal developments. The proposed network will meet regularly to shape methodological innovations specifically for the measurement of aging populations and design studies that will produce evidence-based best practices for this type of longitudinal measurement. There are a large number of influential longitudinal studies of aging in the field at present that would stand to benefit from this type of coordinated, rigorous methodological investigation of more efficient approaches to collecting longitudinal measures from (and for) aging populations. Via a coordinated international program of training, consulting, thematic working group meetings, and pilot research projects, we aim to set the agenda for methodological research on longitudinal studies of aging and protect NIA investments in population-representative longitudinal studies.