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Lancet. 2014 Jan 11;383(9912):166-75. doi: 10.1016/S0140-6736(13)62227-8. Epub 2014 Jan 8.

Increasing value and reducing waste in research design, conduct, and analysis.

Author information

1
Stanford Prevention Research Center, Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA; Division of Epidemiology, School of Medicine, Stanford University, Stanford, CA, USA; Department of Statistics, School of Humanities and Sciences, Stanford University, Stanford, CA, USA; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA. Electronic address: jioannid@stanford.edu.
2
Department of Epidemiology and Department of Statistics, UCLA School of Public Health, Los Angeles, CA, USA.
3
Division of Cardiovascular Medicine, Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA; Division of Health Services Research, Stanford University, Stanford, CA, USA.
4
Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemiology and Genomics Research Program, National Cancer Institute, Rockville, MD, USA.
5
Department of Clinical Neurosciences, University of Edinburgh School of Medicine, Edinburgh, UK.
6
Clinical Epidemiology Program, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada; Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
7
FHI 360, Durham, NC, USA; Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
8
Department of Health Research and Policy, Stanford University, Stanford, CA, USA; Department of Statistics, School of Humanities and Sciences, Stanford University, Stanford, CA, USA.

Abstract

Correctable weaknesses in the design, conduct, and analysis of biomedical and public health research studies can produce misleading results and waste valuable resources. Small effects can be difficult to distinguish from bias introduced by study design and analyses. An absence of detailed written protocols and poor documentation of research is common. Information obtained might not be useful or important, and statistical precision or power is often too low or used in a misleading way. Insufficient consideration might be given to both previous and continuing studies. Arbitrary choice of analyses and an overemphasis on random extremes might affect the reported findings. Several problems relate to the research workforce, including failure to involve experienced statisticians and methodologists, failure to train clinical researchers and laboratory scientists in research methods and design, and the involvement of stakeholders with conflicts of interest. Inadequate emphasis is placed on recording of research decisions and on reproducibility of research. Finally, reward systems incentivise quantity more than quality, and novelty more than reliability. We propose potential solutions for these problems, including improvements in protocols and documentation, consideration of evidence from studies in progress, standardisation of research efforts, optimisation and training of an experienced and non-conflicted scientific workforce, and reconsideration of scientific reward systems.

PMID:
24411645
PMCID:
PMC4697939
DOI:
10.1016/S0140-6736(13)62227-8
[Indexed for MEDLINE]
Free PMC Article

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