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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Methodological Approaches to Understanding Causes of Health Disparities
Neal Jeffries1, Alan M Zaslavsky1, Ana V Diez Roux1
1Neal Jeffries is with the National Heart, Lung, and Blood Institute, National Institutes of Health (NIH), Bethesda, MD. Alan M. Zaslavsky is with the Department of Health Care Policy, Harvard Medical School, Boston, MA. Ana V. Diez Roux is with the Dornsife School of Public Health, Drexel University, Philadelphia, PA. John W. Creswell is with the Department of Family Medicine, University of Michigan, Ann Arbor. Richard C. Palmer, Kelvin Choi, Xinzhi Zhang, and Nancy Breen are with the National Institute on Minority Health and Health Disparities, NIH, Bethesda. Steven E. Gregorich is with the Department of Medicine, University of California, San Francisco. James D. Reschovsky is with Mathematica Policy Research, Washington, DC. Barry I. Graubard and Ruth M. Pfeiffer are with the National Cancer Institute, NIH, Bethesda. Richard C. Palmer and Nancy Breen are also Guest Editors for this supplement issue.
Abstract:
Understanding health disparity causes is an important first step toward developing policies or interventions to eliminate disparities, but their nature makes identifying and addressing their causes challenging. Potential causal factors are often correlated, making it difficult to distinguish their effects. These factors may exist at different organizational levels (e.g., individual, family, neighborhood), each of which needs to be appropriately conceptualized and measured. The processes that generate health disparities may include complex relationships with feedback loops and dynamic properties that traditional statistical models represent poorly. Because of this complexity, identifying disparities' causes and remedies requires integrating findings from multiple methodologies. We highlight analytic methods and designs, multilevel approaches, complex systems modeling techniques, and qualitative methods that should be more broadly employed and adapted to advance health disparities research and identify approaches to mitigate them.
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