Knowledge Mobilization & Evidence-Based Statistical Communication Practices

With the rise of evidence-based decision-making movements (e.g., in medicine and social policymaking), there is an increased need to communicate statistical evidence from research studies to decision-makers who may not have robust statistical and data literacy. We argue that instead of assuming research evidence will be used by and useful to decision-makers, we as statisticians and researchers should directly study strategies for disseminating statistical evidence and mobilizing knowledge. We delineate three areas of interconnected research that should be pursued to effectively study knowledge mobilization: (1) examining norms embedded in the statistical evidence we communicate, (2) descriptively understanding the statistical cognition of how decision-makers reason about this evidence, and (3) prescriptively developing and evaluating communication strategies that facilitate better use and usefulness of evidence. We demonstrate how this three-faceted framework – normative, descriptive, prescriptive – considers the perspectives and priorities of both researchers and decision-makers. As a case study, we present results from our recent statistical cognition experiment that evaluates four data visualizations used to communicate meta-analytic data to education policymakers and decision-makers. We point to existing evidence in education, data visualization, cognitive psychology, and human-computer interaction that should inform our statistical communication practices, and we identify areas where further knowledge mobilization research is needed.

Statistical communication

Statistical cognition

Data visualization

Knowledge mobilization

Evidence-based decision-making 

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Women in Statistics and Data Science 2023