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Despite long-standing critiques, the rationalist model – which describes a simple, linear process by which evidence should inform policy decision-making – remains dominant in the minds of many researchers and policymakers. Why is this the case, and does it matter? I argue that in addition to its intuitive, simple appeal, the rationalist model has been bolstered by repeated appeals from the public health research community for policymakers to rely (often solely) on the 'best' evidence. The insistence on an evidence hierarchy creates the idea that some forms of evidence are of more value than others, and that research design can be used as a way to quickly identify 'best' evidence. I argue this enables misuse of evidence and reduces the scope for effective dialogue between those who make and those who use evidence. A more useful approach would be to explore how knowledge and policy interact at a more systemic level, to help us understand who is involved in evidence production, valuing, codification, and use. Conceptualising the political economy of knowledge in this way offers a new way to begin thinking about how to creatively shape a more helpful environment for both policy and evidence.

Background:
This paper provides insights into 'Policy to Research' (P2R) Fellowships and related programmes within the 'relationship' model of academic–policy engagement, which provide structured opportunities for policy officials to interact with academic researchers.

Aims and objectives:
Information is provided on P2R Fellowship and similar programmes in the UK, Europe and North America. The research questions concern the aims, features and intended outcomes of P2R Fellowship programmes; what can be learned from evaluations of these programmes; and whether value for money for these programmes can be deduced. The authors then aim to provide guidance for an evaluation framework.

Methods:
Programmes were identified through a subset of data gathered on research–policy engagement initiatives in a recent mapping exercise. This was supplemented via Google search. Published data on organisational websites is presented in a table, where data was checked by email with programme managers, who were also asked to provide additional evaluation documents.

Findings:
Twenty-four P2R Fellowship programmes were located. Eleven programme managers confirmed information provided in Table 1. Evaluation documents were provided for five programmes. An average cost of providing a P2R Fellowship was estimated at around £5,000 for each Fellow. Five common aims for P2R Fellowship programmes were identified.

Discussion and conclusion:
Quantitative and qualitative evaluations available from the 24 programmes are reviewed. The comparative lack of published evaluation data is discussed, and recommendations made for an evaluation framework for P2R Fellowships, to build understanding of how to intervene successfully to support a research-for-policy system which delivers for all.

Articulating the research priorities of government is one mechanism for promoting the production of relevant research to inform policy. This study focuses on the Areas of Research Interest (ARIs) produced and published by government departments in the UK. Through a qualitative study consisting of interviews with 25 researchers, civil servants, intermediaries and research funders, the authors explored the role of ARIs. Using the concept of boundary objects, the paper considers the ways in which ARIs are used and how they are supported by boundary practices and boundary workers, including through engagement opportunities. The paper addresses the following questions: What boundaries do ARIs cross, intended and otherwise? What characteristics of ARIs enable or hinder this boundary-crossing? and What resources, skills, work or conditions are required for this boundary-crossing to work well? We see the ARIs being used as a boundary object across multiple boundaries, with implications for the ways in which the ARIs are crafted and shared. In the application of ARIs in the UK policy context, we see a constant interplay between boundary objects, practices and people all operating within the confines of existing systems and processes. For example, understanding what was meant by a particular ARI sometimes involved 'decoding' work as part of the academic-policy engagement process. While ARIs have an important role to play they are no magic bullet. Nor do they tell the whole story of governmental research interests. Optimizing the use of research in policy making requires the galvanisation of a range of mechanisms, including ARIs.

This chapter examines the role of evidence in public service reform processes. We argue that the rhetoric of 'evidence-based policy-making' has served several political agendas, by legitimising various logics of public service management and innovation, and marginalising others. We explore three management cultures (public administration, new public management, and public value management) and three themes—evidence generation, evidence use, and organisational learning—across the policy domains of higher education, healthcare policy, and broader science policy. We conclude that we urgently need more empirical evidence about who gets to participate in knowledge production, the roles of power and different forms of knowledge, how credibility and legitimacy are framed and negotiated in different public and policy contexts, and how to best investigate these processes to deliver meaningful public value.

This article reviews the advice from the academic and 'grey' literatures to identify a list of dos and don'ts for academics seeking 'impact' from their research. From 'how to do it' sources, we identify consistent advice on how to engage effectively, largely because it is necessarily vague, safe, and focused primarily on individuals. We then consider the wider policymaking system in which actors make political choices and have unequal access to impact opportunities. We identify the effort it takes to have actual policy impact and how far academics should be expected to go to secure and take credit for it.

This article reviews the advice from the academic and 'grey' literatures to identify a list of dos and don'ts for academics seeking 'impact' from their research. From 'how to do it' sources, we identify consistent advice on how to engage effectively, largely because it is necessarily vague, safe, and focused primarily on individuals. We then consider the wider policymaking system in which actors make political choices and have unequal access to impact opportunities. We identify the effort it takes to have actual policy impact and how far academics should be expected to go to secure and take credit for it.

BACKGROUND: Understanding how policies lead to changes in health systems and in practice helps policymakers and researchers to intervene more successfully. Yet identifying all the possible changes that occur as a result of a new policy is challenging not only methodologically and logistically, as limited resources are available to conduct indefinite evaluations, but also theoretically, as a complete mapping and attribution of post-hoc changes requires a full understanding of the mechanisms underpinning all change. One option is to identify possible changes across a number of policy impact domains. METHODS: Using a Policy Impact Framework, we brought together data from media, documents and interviews to identify changes to midwifery policy, practice and provision, following the launch of a new global policy initiative, the State of the World's Midwifery (SoWMy 2014) report published in 2014. We used these identified impacts to develop a map of the mechanisms underpinning these changes. RESULTS: SoWMy 2014 contributed to a number of changes at national levels, including increased status of midwifery within national governments, improved curricula and training opportunities for midwives, and improved provision of and access to midwifery-led care. These contributions were attributed to SoWMy 2014 via mechanisms such as stakeholder interaction and acquisition of government support, holding national and international dissemination and training events, and a perceived global momentum around supporting midwifery provision. Policy initiatives of this kind can lead to changes in national and international policy dialogue and practice. We identify factors and mechanisms that are likely to increase the scope and scale of these changes, at contextual, national and global levels. CONCLUSIONS: Identifying changes following a policy using a policy impact framework can help researchers and policymakers understand why policies have the effect they do. This is important information for those wishing to increase the effectiveness of future policies and interventions.

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.

Background:Despite the known need for empirical research-to-policy studies, little is known about the factors and conditions needed to support meaningful evidence use or how to intervene to promote quality evidence use.
Aims and objectives:To study research-policy processes empirically and descriptively, we conducted an ethnography that focused on the impact of the Research-to-Policy Collaboration (RPC) on legislator and researcher evidence use or policy engagement, including whether and how researchers and policymakers created and sustained meaningful relationships.
Methods:The ethnography included participant observation as well as pre- and post- semi-structured interviews from policymakers (n=17), researchers (n=23), and RPC staff (n=5). The team attended relevant events as well as observed the formal and informal ways research is used in policymaking.
Findings:In the paper, we describe how 1) legislative priorities were identified; 2) networks were established and maintained; 3) trainings evolved over time; 4) relationships between RPC staff, congressional staff, and researchers were facilitated; and 5) RPC followed up with policymakers and researchers.
Discussion and conclusions:We 1) describe the experiences of participants and whether involvement in the intervention changed attitudes or behaviours about evidence use in policy; 2) describe the RPC process in practice, and how it was implemented and evolved over time; and 3) better understand the conditions supporting evidence use in policymaking. We conclude with the value of the RPC as a resource to fill a niche within the evidence and policy space, as well as suggestions for future research-to-policy programmes and practices.

Evaluating complex interventions and policies is challenging. This is particularly true for the identification of unintended consequences, whether negative or positive. This article uses data from a workshop with policymakers and evaluators to explore the evaluation of unintended consequences. We identify three main challenges for policymakers and evaluators: being able to identify and evaluate unintended effects, to avoid creating unintended effects and being able to explain these effects. We discuss practical, political and ethical issues for each of these challenges and identify recommendations for evaluators who want to consider unintended consequences. First, use a broader range of methods to explore how policies play out; second, use theory to plan evaluations; and third, discuss both methods and theory with relevant stakeholders to make these as useful as possible. We offer novel insights into recent debates about theory-led and co-produced interventions and policies.

Evaluating complex interventions and policies is challenging. This is particularly true for the identification of unintended consequences, whether negative or positive. This article uses data from a workshop with policymakers and evaluators to explore the evaluation of unintended consequences. We identify three main challenges for policymakers and evaluators: being able to identify and evaluate unintended effects, to avoid creating unintended effects and being able to explain these effects. We discuss practical, political and ethical issues for each of these challenges and identify recommendations for evaluators who want to consider unintended consequences. First, use a broader range of methods to explore how policies play out; second, use theory to plan evaluations; and third, discuss both methods and theory with relevant stakeholders to make these as useful as possible. We offer novel insights into recent debates about theory-led and co-produced interventions and policies.

Scientists often worry that their evidence is not used properly in the policy-making process. Their main response is to change the supply of evidence to reduce policymaker uncertainty. They should focus more on ambiguity, combining evidence and persuasion to help policymakers define the policy problem. To do so, they need to understand the policy process in which they engage. They cannot do so alone. Policy scholars can help, by articulating the practical value of policy theories. To help most effectively, they need to state clearly the "causal mechanisms" of the policy process. For example, what causes policymakers to pay attention to an issue informed partly by evidence, or what rules guide their behavior most strongly when weighing up evidence with other factors? In this paper, we show that policy theories have informed this debate, but often without making explicit statements of causality. We draw on the social science causal mechanisms field to improve such analysis and suggest use qualitative methods to clarify and measure causal mechanisms to benefit policy scholars and the wider policy analysis community. A focus on mechanisms can inform policy scholarship, science community engagement and on-the-ground policy work.

AbstractPolicy makers cannot consider all evidence relevant to policy. They use two shortcuts—emotions and beliefs to 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 of evidence helps reduce scientific and policy maker uncertainty. However, policy makers also combine their beliefs with limited evidence to reduce ambiguity by choosing 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."