The world is in the grip of a crisis that stands unprecedented in living memory. The COVID-19 pandemic is urgent, global in scale, and massive in impacts. Following Harold D. Lasswell's goal for the policy sciences to offer insights into unfolding phenomena, this commentary draws on the lessons of the policy sciences literature to understand the dynamics related to COVID-19. We explore the ways in which scientific and technical expertise, emotions, and narratives influence policy decisions and shape relationships among citizens, organizations, and governments. We discuss varied processes of adaptation and change, including learning, surges in policy responses, alterations in networks (locally and globally), implementing policies across transboundary issues, and assessing policy success and failure. We conclude by identifying understudied aspects of the policy sciences that deserve attention in the pandemic's aftermath.

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There is extensive health and public health literature on the ‘evidence-policy gap’, exploring the frustrating experiences of scientists trying to secure a response to the problems and solutions they raise and identifying the need for better evidence to reduce policymaker uncertainty. We offer a new perspective by using policy theory to propose research with greater impact, identifying the need to use persuasion to reduce ambiguity, and to adapt to multi-level policymaking systems.We identify insights from secondary data, namely systematic reviews, critical analysis and policy theories relevant to evidence-based policymaking. The studies are drawn primarily from countries such as the United States, United Kingdom, Canada, Australia and New Zealand. We combine empirical and normative elements to identify the ways in which scientists can, do and could influence policy.We identify two important dilemmas, for scientists and researchers, that arise from our initial advice. First, effective actors combine evidence with manipulative emotional appeals to influence the policy agenda – should scientists do the same, or would the reputational costs outweigh the policy benefits? Second, when adapting to multi-level policymaking, should scientists prioritise ‘evidence-based’ policymaking above other factors? The latter includes governance principles such the ‘co-production’ of policy between local public bodies, interest groups and service users. This process may be based primarily on values and involve actors with no commitment to a hierarchy of evidence.We conclude that successful engagement in ‘evidence-based policymaking’ requires pragmatism, combining scientific evidence with governance principles, and persuasion to translate complex evidence into simple stories. To maximise the use of scientific evidence in health and public health policy, researchers should recognise the tendency of policymakers to base judgements on their beliefs, and shortcuts based on their emotions and familiarity with information; learn ‘where the action is’, and be prepared to engage in long-term strategies to be able to influence policy; and, in both cases, decide how far you are willing to go to persuade policymakers to act and secure a hierarchy of evidence underpinning policy. These are value-driven and political, not just ‘evidence-based’, choices.

BackgroundMany of society’s health problems require research-based knowledge acted on by healthcare practitioners together with implementation of political measures from governmental agencies. However, there has been limited knowledge exchange between implementation science and policy implementation research, which has been conducted since the early 1970s. Based on a narrative review of selective literature on implementation science and policy implementation research, the aim of this paper is to describe the characteristics of policy implementation research, analyze key similarities and differences between this field and implementation science, and discuss how knowledge assembled in policy implementation research could inform implementation science.DiscussionFollowing a brief overview of policy implementation research, several aspects of the two fields were described and compared: the purpose and origins of the research; the characteristics of the research; the development and use of theory; determinants of change (independent variables); and the impact of implementation (dependent variables). The comparative analysis showed that there are many similarities between the two fields, yet there are also profound differences. Still, important learning may be derived from several aspects of policy implementation research, including issues related to the influence of the context of implementation and the values and norms of the implementers (the healthcare practitioners) on implementation processes. Relevant research on various associated policy topics, including The Advocacy Coalition Framework, Governance Theory, and Institutional Theory, may also contribute to improved understanding of the difficulties of implementing evidence in healthcare. Implementation science is at a relatively early stage of development, and advancement of the field would benefit from accounting for knowledge beyond the parameters of the immediate implementation science literature.SummaryThere are many common issues in policy implementation research and implementation science. Research in both fields deals with the challenges of translating intentions into desired changes. Important learning may be derived from several aspects of policy implementation research.

Abstract. While John Kingdon's Multiple Streams Approach (MSA) remains a key reference point in the public policy literature, few have attempted to assess MSA holistically. To assess its broader impact and trends in usage, we combine in-depth analysis of representative studies, with comprehensive coverage of MSA-inspired articles, to categorize its impact. We find that Kingdon's work makes two separate contributions. First, it has contributed to the development of 'evolutionary' policy theories such as punctuated equilibrium. Second, it has prompted a large, dedicated, and often empirical, literature. However, most MSA empirical applications only engage with broader policy theory superficially. The two contributions are oddly independent of each other. We argue that these trends in application are due largely to its intuitive appeal and low 'barrier to entry'. Drawing on other policy approaches, we offer suggestions to improve the MSA-inspired literature.

Many academics have strong incentives to influence policymaking, but may not know where to start. We searched systematically for, and synthesised, the 'how to' advice in the academic peer-reviewed and grey literatures. We condense this advice into eight main recommendations: (1) Do high quality research; (2) make your research relevant and readable; (3) understand policy processes; (4) be accessible to policymakers: engage routinely, flexible, and humbly; (5) decide if you want to be an issue advocate or honest broker; (6) build relationships (and ground rules) with policymakers; (7) be 'entrepreneurial' or find someone who is; and (8) reflect continuously: should you engage, do you want to, and is it working? This advice seems like common sense. However, it masks major inconsistencies, regarding different beliefs about the nature of the problem to be solved when using this advice. Furthermore, if not accompanied by critical analysis and insights from the peer-reviewed literature, it could provide misleading guidance for people new to this field.

Policy makers cannot consider all evidence relevant to policy. They use two shortcuts—emotions and beliefsto understand problems and “rational” ways of establishing the best evidence on solutions—to act quickly in complex,multilevel policy-making environments. Many studies only address one part of this problem. Improving the supply ofevidence helps reduce scientific and policy maker uncertainty. However, policy makers also combine their beliefs withlimited evidence to reduce ambiguity in order to choose one of several possible ways to understand and solve a problem.We use this insight to consider solutions designed to “close the evidence–policy gap

Advocates of complexity theory describe it as a new scientific paradigm. Complexity theory identifies instability and disorder in politics and policymaking, and links it to the behaviour of complex systems. It suggests that we shift our analysis from individual parts of a political system to the system as a whole; as a network of elements that interact and combine to produce systemic behaviour. This article explores the use of complexity theory in public policy, highlighting a small literature using the language of complexity directly to describe complex policymaking systems, and a larger literature identifying complexity themes. It then highlights the main problems to be overcome before complexity theory can become truly valuable in politics and policymaking.