Improving impact infrastructure: key predictors of researchers’ policy engagement based on behavioural science

Despite significant investments in “impact infrastructure”—the sum of interventions promoting researchers’ policy engagement—there is a notable lack of evaluations (Oliver et al. 2022) or systematic, theory-driven evidence to inform these efforts. Given the lack of evidence on “what works,” identifying predictors of researchers’ policy engagement based on behavioural science can fill the gap and generate much-needed evidence to inform practical investments in these interventions. This article presents the first behavioural science-based comprehensive diagnosis of key predictors of policy engagement using the COM-B model, which explains behaviour based on capability, opportunity, and motivation. We operationalised the model using the Theoretical Domains Framework, which structures more granular theoretical constructs related to these components. Our analysis is based on a theory-informed, psychometrically validated survey with 1115 publicly funded researchers in Germany. Communication skills and policy literacy (capability), tangible resources and role models (opportunity), as well as incentives and “mission” (i.e., identity, duty, and purpose)-driven motivation (motivation) emerge as key behavioural predictors of policy engagement. Our analysis of social norms reveals that science advisors experience peer disapproval—evidence of a “Carl Sagan effect” for policy engagement; a stigma around engagement named after the prominent science communicator. Additionally, the evidence on training opportunities suggests that they are insufficient in quantity, quality, or both. Our findings offer an interdisciplinary perspective, combining behavioural science and policy studies, to advance the literature on researchers’ policy engagement. They lay the groundwork for developing theory-informed and evidence-based “impact infrastructure” that effectively promotes policy engagement. Organisations can align their context-specific intervention strategies with the key predictors identified in this study to increase their effectiveness and return on investment.