Dr. Eric S. Kim is currently a Research Scientist in the Department of Social and Behavioral Sciences at the Harvard T.H. Chan School of Public Health. He is also a research affiliate at the Lee Kum Sheung Center for Health and Happiness (housed at the Harvard T.H. Chan School of Public Health), and a research affiliate at the Program on Integrative Knowledge and Human Flourishing (housed at Harvard University’s Institute for Quantitative Social Science). He received his Ph.D. in Clinical Psychology from the University of Michigan, where he also received advanced statistical training (2009-2015). He then completed a Postdoctoral Research Fellowship in the NHLBI Cardiovascular Disease Epidemiology Program in Behavior, Environment, and Global Health (2015-2017), which honed his ability to conduct biopsychosocial and population-health research. His program of research aims to identify, understand, and intervene upon the dimensions of psychological well-being that reduces risk of age-related conditions. It also aims to understand the influence that the social environment has on the connection between psychological well-being and physical health. His research integrates perspectives from psychology (health, developmental, clinical, social, personality), gerontology, social epidemiology, biology, biostatistics, and translational science.
Population aging is one of the most important social trends of the 21st century. In the U.S. the number of adults aged ≥65 is projected to increase by nearly 50% in the next 15 years. As societies grapple with the rising tide of chronic conditions, healthcare costs, and long-term care costs, it is imperative to develop a science that informs a more comprehensive approach to healthy aging. Dr. Kim’s overarching goal is to be part of a team that substantially helps improve the physical health and psychological well-being of our rapidly growing population. In pursuit of this goal, Dr. Kim’s program of basic and translational research revolves around five interwoven areas of inquiry.
Are different dimensions of psychological well-being (e.g., sense of purpose in life, optimism) associated with reduced risk of age-related chronic conditions (e.g., cardiovascular disease, cognitive impairment)?
What are the mechanistic biobehavioral pathways that explain how psychological well-being influences health: 1) health behaviors such as physical activity, sleep, and diet, 2) biological pathways such as DNA methylation and inflammation, 3) stress-buffering?
Our health is influenced by the social milieu in which we live, including stressful experiences at the individual (e.g., major disease diagnosis), household (e.g., death of a spouse), neighborhood (e.g., low neighborhood cohesion), and societal levels (e.g., social and racial disparities, economic shocks like the 2008 recession). Yet inadequate attention has been given to psychosocial assets that may buffer against these social adversities. Are dimensions of psychological well-being pathways through which social conditions shape people’s health, and do they foster resilience against these forces?
Large epidemiological studies cannot regularly capture a wide array of psychological and social factors because repeatedly administering self-assessments causes substantial response burden for study participants and is financially prohibitive for researchers. This limitation constrains progress in the field. With full participant consent, can machine learning algorithms leverage digital footprints in social media to automatically assess an array of psychosocial factors?
From a translational science perspective, how might we partner with large non-profits and healthcare insurers to rigorously test and disseminate meaningful, durable, self-sustaining, population-level interventions aimed at improving psychological well-being and its potential downstream effects (e.g., lower physical and psychological morbidity, lower healthcare expenditures, and enhance prognosis if illness does strike)?
In the investigation described above, he used a variety of study designs and analytic tools including: population-based cohort studies, biostatistical causal inference methods, systematic reviews and meta-analyses, focus groups, and randomized controlled trials.
Dr. Kim has had the honor of working with incredible colleagues in a range of disciplines and has thus been able to publish 1st authored papers in a variety of outlets including: Proceedings of the National Academy of Sciences, JAMA Psychiatry, Stroke, Circulation, Preventive Medicine, American Journal of Epidemiology, Psychosomatic Medicine, and Health Psychology. These studies have been featured in the New York Times, Los Angeles Times, The Atlantic, CBS News (Television Interview), BBC News (Radio Interview), NPR (Radio Interview), Time Magazine, and the Washington Post. His work has been supported by funding from the National Institute on Aging (NIA), National, Heart, Lung, Blood, Institute (NHLBI), the Robert Wood Johnson Foundation, and AARP.
Dr. Kim is the recipient of a K99/R00, the Horace H. Rackham Predoctoral Fellowship (awarded to Ph.D. candidates at the University of Michigan with the top dissertation proposals), and the Telluride Association Scholarship. He was recognized as one of Forbe's 30 Under 30 in Healthcare (Top 30 Innovators Under the Age of 30) and also one of the Top 30 Thinkers Under the Age of 30 by Pacific Standard.
Dr. Kim volunteers by providing pro bono statistical consulting to non-profit organizations in his community - please contact him if you are interested. He currently serves as a subject matter specialist for AARP/Age UK's Global Council on Brain Health.