Literature DB >> 35064895

NIH Primary and Secondary Prevention Research in Humans: a Portfolio Analysis of Study Designs Used in 2012-2019.

Natasha K Oyedele1, Luis F Ganoza2, Sheri D Schully3, Charlene A Liggins2, David M Murray2.   

Abstract

We can learn a great deal about the research questions being addressed in a field by examining the study designs used in that field. This manuscript examines the research questions being addressed in prevention research by characterizing the distribution and trends of study designs included in primary and secondary prevention research supported by the National Institutes of Health through grants and cooperative agreements, together with the types of prevention research, populations, rationales, exposures, and outcomes associated with each type of design. The Office of Disease Prevention developed a taxonomy to classify new extramural NIH-funded research projects and created a database with a representative sample of 14,523 research projects for fiscal years 2012-2019. The data were weighted to represent the entirety of the extramural research portfolio. Leveraging this dataset, the Office of Disease Prevention characterized the study designs proposed in NIH-funded primary and secondary prevention research applications. The most common study designs proposed in new NIH-supported prevention research applications during FY12-19 were observational designs (63.3%, 95% CI 61.5%-65.0%), analysis of existing data (44.5%, 95% CI: 42.7-46.3), methods research (23.9%, 95% CI: 22.3-25.6), and randomized interventions (17.2%, 95% CI: 16.1%-18.4%). Observational study designs dominated primary prevention research, while intervention designs were more common in secondary prevention research. Observational designs were more common for exposures that would be difficult to manipulate (e.g., genetics, chemical toxin, and infectious disease (not pneumonia/influenza or HIV/AIDS)), while intervention designs were more common for exposures that would be easier to manipulate (e.g., education/counseling, medication/device, diet/nutrition, and healthcare delivery). Intervention designs were not common for outcomes that are rare or have a long latency (e.g., cancer, neurological disease, Alzheimer's disease) and more common for outcomes that are more common or where effects would be expected earlier (e.g., healthcare delivery, health related quality of life, substance use, and medication/device). Observational designs and analyses of existing data dominated, suggesting that much of the prevention research funded by NIH continues to focus on questions of association and on questions of identification of risk and protective factors. Randomized and non-randomized intervention designs were included far less often, suggesting that a much smaller fraction of the NIH prevention research portfolio is focused on questions of whether interventions can be used to modify risk or protective factors or to change some other health-related biomedical or behavioral outcome. The much heavier focus on observational studies is surprising given how much we know already about the leading risk factors for death and disability in the USA, because those risk factors account for 74% of the county-level mortality in the USA, and because they play such a vital role in the development of clinical and public health guidelines, whose developers often weigh results from randomized trials much more heavily than results from observational studies. Improvements in death and disability nationwide are more likely to derive from guidelines based on intervention research to address the leading risk factors than from additional observational studies.
© 2022. Society for Prevention Research.

Entities:  

Keywords:  Prevention research; Study design

Mesh:

Year:  2022        PMID: 35064895     DOI: 10.1007/s11121-022-01337-9

Source DB:  PubMed          Journal:  Prev Sci        ISSN: 1389-4986


  4 in total

Review 1.  Essential Ingredients and Innovations in the Design and Analysis of Group-Randomized Trials.

Authors:  David M Murray; Monica Taljaard; Elizabeth L Turner; Stephanie M George
Journal:  Annu Rev Public Health       Date:  2019-12-23       Impact factor: 21.981

Review 2.  Prevention trials: their place in how we understand the value of prevention strategies.

Authors:  Graham A Colditz; Philip R Taylor
Journal:  Annu Rev Public Health       Date:  2010       Impact factor: 21.981

Review 3.  Regression discontinuity designs in healthcare research.

Authors:  Atheendar S Venkataramani; Jacob Bor; Anupam B Jena
Journal:  BMJ       Date:  2016-03-14

Review 4.  Use of the Medicare database in epidemiologic and health services research: a valuable source of real-world evidence on the older and disabled populations in the US.

Authors:  Katherine E Mues; Alexander Liede; Jiannong Liu; James B Wetmore; Rebecca Zaha; Brian D Bradbury; Allan J Collins; David T Gilbertson
Journal:  Clin Epidemiol       Date:  2017-05-09       Impact factor: 4.790

  4 in total

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