Network for Advancing Methodological Research in Longitudinal Studies of Aging

推进老龄化纵向研究方法论研究网络

• 批准号: 10435769
• 负责人: Sung-Hee Lee
• 金额: $ 39万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10435769
• 关键词: Aging; Appointment; Asian Americans; Behavioral; Biological Markers; Biosocial; COVID-19 pandemic; Collaborations; Complement; Complex; Consent; Consult; Cross-Sectional Studies; Data; Data Collection; Development; Devices; Educational workshop; Electronics; Ensure; Environment; Faculty; Funding; Future; Goals; Group Meetings; Health; Health and Retirement Study; Hispanic Americans; Hispanic Populations; Home; Influentials; Institutes; International; Interview; Investigation; Investments; Lead; Life Cycle Stages; Linguistics; Link; Longitudinal Studies; Measurement; Measures; Methodology; Methods; Michigan; Minority; Minority Groups; Modernization; Online Systems; Paper; Participant; Patient Self-Report; Pilot Projects; Play; Population; Population Study; Postdoctoral Fellow; Records; Research; Research Activity; Research Design; Research Methodology; Research Personnel; Research Project Grants; Retirement; Role; Running; Series; Shapes; Social Interaction; Subgroup; Survey Methodology; Surveys; Techniques; Technology; Time; Training; Training Activity; Training Programs; Universities; Work; aging demography; aging population; data collection methodology; design; evidence base; experience; improved; innovation; meetings; member; mid-career faculty; new technology; population based; programs; racial and ethnic; recruit; research and development; response; social; synergism; trend; virtual; web portal; web site; working group

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.

对退休前后人口的纵向研究，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中的数据 课程视角，允许研究人员做出总体水平的因果推理。因为这样的数据 收藏是研究人员和人群之间的一种社会互动，是用来收集的方法 这些研究中的数据需要适应社会变化。美国的老龄化人口是 经历着快速的变化。首先，它的种族、民族和语言构成正在被 不断增长的西班牙裔和亚裔美国人。第二，老龄化人口对新的 新冠肺炎疫情加速了移动和视频技术的发展。同时， 以人口为基础的数据收集的研究环境也发生了变化，可获得性增加 可以与调查数据集成的管理记录，以及现代设备的更多使用 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形成方法创新 未来的纵向研究。例如，由于人们已经习惯于通过 在新冠肺炎大流行期间，基于人群的研究已经从使用 一种采访模式，混合模式，包括基于网络的数据收集和虚拟采访。 不幸的是，针对老龄化人口的最佳数据收集方法的方法学研究 到目前为止，这种做法有几个严重的缺陷：明显缺乏关于 少数群体、获得行政记录联系同意的最佳办法和 生物标记物数据收集未知，需要对抗不断增加的磨损率的方法， 缺乏关于使用新技术收集数据的方法论研究。 我们建议形成一个由国际知名的方法和实质性专家组成的网络，这些专家 正在积极研究新的数据收集方法的好处，以应对这些社会 事态的发展。拟议的网络将定期举行会议，以具体确定方法创新 用于老龄化人口的测量和设计研究，将产生基于证据的最佳 这类纵向测量的实践。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的、严格的 从(和为)收集纵向测量的更有效方法的方法学研究 人口老龄化。通过一个协调的国际培训、咨询、专题工作组方案 会议和试点研究项目，我们的目标是制定纵向方法学研究的议程 老龄化研究和保护NIA在人口代表性纵向研究中的投资。