Dr. Hwanhee Hong is a post-doctoral fellow in the Department of Mental Health at the Johns Hopkins Bloomberg School of Public Health. Dr. Hong obtained statistical background for biomedical research from the University of Minnesota and Harvard School of Public Health, where she completed a PhD and a MS in biostatistics, respectively. This K99 training award will help her obtain critical knowledge in mental health research and focused statistical methods to accomplish the proposed project. The proposed project aims to (1) develop statistical methods for estimating population treatment effects in the context of mental health, integrating meta-analytic techniques with a number of existing survey data analysis methods and generalizability methods for a single randomized trial, (2) validate and assess performance of the proposed methods, and apply them to real investigative randomized trials for schizophrenia and bipolar disorder, and (3) extend the proposed methods to network meta-analysis, comparing multiple treatments at once, for finding the best treatment for the general population. This project will enhance the use of clinical trials and meta-analyses in mental health, yielding methods to make better decisions about intervention implementation in general populations, which fits the National Institute of Mental Health?s mission. The two-year mentored training program consists of organized mentorship with regular in-person individual meetings, team meetings, formal coursework in both mental health and biostatistics, seminars, working groups, academic conferences, and career development activities. These training activities will provide the groundwork for the following three-year independent stage. Short-term career goals include to establish a better understanding of mental health research, particularly complex features of mental disorders and outcomes from relevant clinical trials, advanced topics in causal inference, and additional statistical methods for generalizing results of meta-analyses including survey weighting and flexible machine learning methods. Long-term career goals include to build an independent research portfolio and become a leading methodologist in mental health and other multidisciplinary research. The Department of Mental Health of the Johns Hopkins Bloomberg School of Public Health provides an ideal setting for training a new independent methodologist in mental health with an extensive program of formal and informal education for post-doctoral researchers, opportunities for collaboration with researchers having expertise in diverse areas, and resources for career development. Dr. Hong will also use all available resources from other Departments including biostatistics, epidemiology, and psychiatry. This environment maximizes the potential for Dr. Hong to obtain the necessary training and perform the research to establish herself as a skilled investigator with an independent research program.
This project will help mental health researchers generalize, apply, and implement findings from meta-analyses of randomized clinical trials to target populations. Traditional meta-analyses enable us to borrow strength across multiple studies to gain more power, resulting in reliable and precise effect estimates; however they do not consider how well the trials represent target populations of interest. By developing methods to help generalize the results of meta-analyses, we will help translate results into appropriate decisions regarding broad implementation and clinical practice.
| Susukida, Ryoko; Crum, Rosa M; Hong, Hwanhee et al. (2018) Comparing pharmacological treatments for cocaine dependence: Incorporation of methods for enhancing generalizability in meta-analytic studies. Int J Methods Psychiatr Res 27:e1609 |
