Longevity, Equity, and Aging Research Network (L.E.A.R.N.) Consortium Analysis Core

项目总结-分析核心

PROJECT SUMMARY—ANALYSIS CORE The overall goal of the Analyses Core (AnC) of the of the Longevity, Equity, and Aging Research Network (L.E.A.R.N) Consortium is to provide biostatistical, epidemiological, and methodological training, mentoring and assistance, and to guide junior investigators from diverse and underrepresented groups (collectively called RCMAR Scientists) in the conduct of transdisciplinary ethnogeriatrics health disparities research that integrates biological, social, behavioral, and cultural considerations. We will train them to use various innovative techniques, including emerging methodologies (i.e., biomedical data science, digital health methods, precision medicine techniques and virtual reality and simulation-based interventions), qualitative research, mixed methods research, and implementation science. The AnC will review, monitor, and provide guidance and continuing biostatistical, bioinformatics and database support for all our RCMAR Scientists. We will closely collaborate within our center with the Leadership and Administration Core and the Research Education Component to provide continuing individualized consulting, training, and education for RCMAR Scientists. We will also collaborate and share resources with the L.E.A.R.N Consortium faculty, the RCMAR Coordinating Center and our sister RCMAR centers across the nation. The strength of our core lies in our experienced core investigators with complementary expertise/experience and exceptional devotion to mentoring and education of early career researchers. Along with mentoring and consulting, the AnC will provide formal education through statistics and methods classes in the Stanford Psychiatry Department. The AnC and the Research Education Component will work closely to direct RCMAR Scientists to the appropriate courses based on the needs of their pilot projects and their personalized training plan. The AnC will also assist the RCMAR Scientists with safe and high-quality database management for the pilot projects. As the RCMAR Scientists are early career researchers, special care will be taken to ensure that, regardless of the nature of pilot projects, they will be mentored to exercise great caution in handling the human subject data, which will also provide a crucial opportunity for them to train with and learn from experts on proper management of human subject data. In addition to supporting RCMAR Scientists, the AnC will actively develop cutting edge statistical and research methods with the common goal of advancing care of and research on older adults from diverse backgrounds. Taking advantage of the interdisciplinary forum that will be naturally formed under the proposed RCMAR program, the AnC will lead and encourage project investigators to collaborate on various statistical and methodological research topics pertinent to ethnogeriatrics, such as biomedical data science approaches, bioinformatics, digital health, virtual reality and simulation study design, personalized (precision) medicine, qualitative and mixed methods, comparative effectiveness, behavioral interventions, effect heterogeneity, and joint utilization of multiple analytical traditions to effectively handle multitude of information.