Characterization of Study Design Methodology and Targeted Populations in NIH Funded Primary and Secondary Prevention Research in Humans

Introduction: The choice of which study design to select to address a particular research question is guided by the nature of the health outcome under study and the hypothesized relationship to the exposure(s) being analyzed. The practicalities of research are also often major considerations (i.e. budget, time) in any study design choice, particularly in prevention research. In an effort to enhance rigor and reproducibility, recently the National Institutes of Health (NIH) has focused on improving the quality of experimental designs and the analysis methods used in biomedical, behavioral, and social science. The Office of Disease Prevention (ODP) within the NIH focuses on assessing, facilitating, and stimulating research in disease prevention and health promotion.

Methods: The ODP has recently developed a detailed, consensus-driven approach to systematically characterize the primary and secondary prevention research in humans supported by NIH grants. The application of this rigorous taxonomy has allowed us to develop a rich dataset to characterize the study designs used in NIH-supported prevention research, including studies that focus on analysis of existing data, methods research, non-randomized intervention studies, observational studies, pilot/feasibility/proof-of-concept/safety studies, and randomized intervention studies.

The ODP additionally captured information about the targeted study populations. The categories included those who were described in the grant abstract as being: incarcerated/institutionalized (e.g., in nursing homes, prisons, hospice); lesbian, gay, bisexual, transgender, and/or intersex (LGBTI); low income; military/veterans, older adults/elderly (aged 65+), people with disabilities, pregnant/postpartum women, rural, urban, youth, and other/unclear (e.g., general adult population or unspecified population). Gender and race/ethnicity were not coded as part of the taxonomy because data on those topics are available from existing NIH resources. Herein, we describe the pattern of funding of study designs and targeted populations in prevention research from FY 2012-2016.

Results: We will show preliminary results on the characterization of study designs and populations that are leveraged in prevention research from the NIH grant portfolio.

Conclusions: Ultimately, the identification of patterns and trends of study designs in NIH prevention research funding will inform NIH investments. Additionally, understanding which populations are being studied in prevention research may have policy and funding implications for research on health disparities in vulnerable populations.