NIMLAS Admin Supplement

NIMLAS 管理补充

基本信息

批准号：
10754344
负责人：
Sung-Hee Lee
金额：
$ 8.53万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
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/10754344
关键词：
Acceleration Address Aging Area Asian Americans Biological Markers COVID-19 pandemic Communication Communities Complement Consent Consult Country Data Data Collection Development Devices Disparity Education Educational Intervention Elderly Electronics English Language Enrollment Environment Ethnic Origin Ethnic Population Facebook Family Feedback Foundations Funding Future Gender Goals Grant Group Meetings Health Health Disparities Research Health and Retirement Study Hispanic Americans Home Influentials Institution International Intervention Interview Investigation Investments Knowledge Language Latino Latino Population Learning Learning Module Length Life Cycle Stages Linguistics Literature Longitudinal Studies Measurement Measures Mentors Methodology Methods Minority Minority Groups Minority Health Research Modernization Newsletter Online Systems Outcome Participant Patient Self-Report Play Population Population Study Positioning Attribute Process Race Records Religious Belief Research Research Design Research Methodology Research Personnel Research Project Grants Resources Retirement Review Literature Role Sampling Series Shapes Social Interaction Source Subgroup Surveys Target Populations Technology Testing Time Training Programs Translating Treatment Efficacy Trust Underrepresented Minority Underrepresented Populations Underserved Population Work aging population cognitive interview community partnership data collection methodology distrust eHealth effective intervention electronic health information ethnic minority evidence base experience follow up assessment improved innovation knowledge base literacy new technology novel poor health outcome population based post-COVID-19 racial minority racial population recruit remote delivery response socioeconomics tool trend underserved area underserved community virtual web-based intervention working group

项目摘要

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.

对接近退休阶段、退休阶段和退休后阶段人口的纵向研究，例如健康和退休研究（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，使研究人员能够做出人群层面的因果推断。因为这样的数据收集是研究人员与公众之间的社会互动，收集所采用的方法这些研究中的数据需要适应社会变化。美国的人口老龄化程度是经历快速的变化。首先，其种族、民族和语言构成正在因不断增长的西班牙裔和亚裔美国人人口。其次，人口老龄化对新能源的依赖 COVID-19 大流行加速了移动和视频技术的发展。与此同时，基于人口的数据收集的研究环境也发生了变化，可用性有所提高可以与调查数据集成的行政记录以及现代设备的增加使用用于收集人体测量和生物标记数据，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，随着人们已经习惯于通过在 COVID-19 大流行期间，基于人群的研究已经从使用电子设备转变为从一种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，针对老龄化人口的最佳数据收集方法的方法学研究迄今为止所进行的研究存在几个严重缺陷：明显缺乏关于少数群体、获得行政记录链接同意的最佳方法以及生物标志物数据收集未知，需要对抗不断增加的损耗率的方法，缺乏使用新技术进行数据收集的方法学研究。我们建议建立一个由国际知名的方法论和实质性专家组成的网络，他们正在积极研究新数据收集方法的好处，以应对这些社会问题事态发展。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人口老龄化和设计研究，以产生基于证据的最佳结果此类纵向测量的实践。有一大批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、严格的研究方法论调查更有效的方法来收集纵向测量（以及为）人口老龄化。通过协调一致的国际培训、咨询、专题工作组计划会议和试点研究项目，我们的目标是为纵向方法论研究制定议程老龄化研究并保护 NIA 在人口代表性纵向研究中的投资。