Abstract
The discovery of efficacious treatment options for neuropsychiatric conditions is a process that remains in jeopardy. Contributing to the failure of clinical trials, a strong positive bias exists in the reported results of preclinical studies, including in the field of neuroscience. However, despite clear recognition of major factors that lead to bias, efforts to address them have not made much meaningful change, receiving inadequate attention from the scientific community. In truth, little real-world value is currently attached to efforts made to oppose positive bias, and instead—partially driven by competitive conditions—the opposite has become true. Since pressures throughout our system of scientific discovery, particularly those tied to definitions of individual success, hold these damaging practices firmly in place, we urgently need to make changes to the system itself. Such a transformation should include a pivot away from explicit or tacit requirements for statistical significance and clean narratives, particularly in publishing, and should promote a priori power calculations as the determinant of final sample size. These systemic changes must be reinforced and upheld in responsible decisions made by individual scientists concerning the planning, analysis, and presentation of their own research.
Highlights
The discovery of efficacious treatment options for neuropsychiatric conditions is a process that remains in jeopardy
Contributing to the failure of clinical trials, a strong positive bias exists in the reported results of preclinical studies, including in the field of neuroscience
We rely on preclinical work conducted by basic scientists, to guide which costly clinical investigations are most beneficial for successful therapeutic development in humans
Summary
Rule #1: Make a solid plan to test your predictions before conducting the research. Rule #3: Run experiments following the plan and using responsible experimental practices. One can suggest that increased incidence of statistically significant findings is a natural result of asking well-founded, hypothesis-driven questions, but this premise cannot account for the estimated 6% increase in reported positive findings per year between 1990 and 2007 (Fanelli, 2012). The high value of significant findings gives luck an outsized role in determining a scientist’s success—a career that may require 10 or more years of post-baccalaureate training, during which time it is typical to earn limited wages. At worst, it encourages scientific fraud (Fanelli, 2009; Devine et al, 2021). Perhaps as the adage says, people living in glass houses should not throw stones—unless they need to remodel.)
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