Keen to have impact with your research but getting lost in all the knowledge exchange frameworks and models that are out there? Based on ten years’ experience working in translational public health for Fuse – The Centre for Translational Research in Public Health, a UK Clinical Research Centre collaboration across five universities in North East England, we identified four practical steps to develop collaborative research and achieve meaningful change in policy and practice.
The challenges of using research to inform policy and practice are well documented, including in public health where the evidence base for interventions or programmes is patchy or contested. In response to these challenges, an abundance of models and frameworks have been developed in recent years that try to define the knowledge exchange process (how research evidence can be used, in combination with other types of knowledge, to change policy and practice). Practitioners and researchers venturing into the field of knowledge exchange are bewildered by the options available, which don’t go beyond the conceptual level and fail to describe in practical terms what research translation on the ground looks like.
One of the major trends within the contemporary policy scene is ‘the use of behavioural insights (BI)’ to improve policymaking. All around the world, from Qatar to England and Japan, ‘Behavioural Insights Teams’ (or ‘BITs’), ‘Nudge advisers’ and ‘Chief Behavioural Officers’ now inhabit government, seeking to infuse it with state-of-the-art knowledge and methods from the behavioural sciences. The more specific signature traits of this BI agenda appear to be its focus on new behavioural economics, nudge techniques and Randomized Controlled Trials (RCTs). The COVID-19 crisis hasn’t hampered the behavioural momentum – quite the contrary: in the absence of a distributed vaccine, halting the spread of the coronavirus has very much been a behaviour change challenge, with BI being in great demand. The recent launch of dedicated ‘COVID-19 Teams’ and ‘Corona Behavioural Units’ within the UK’s and Dutch policy scene didn’t come as a surprise, and only confirmed that behavioural government is here to stay.
Intriguingly enough, though, one question about the new institutional praxis of ‘using BI’ remains not yet convincingly answered: What is it, really?
Many of us place our hopes on innovative breakthroughs and groundbreaking discoveries, believing them to be our best bet to achieve a better world. And indeed, science has produced extraordinary breakthroughs. Vaccines radically reduced the risk of death from communicable diseases. Nitrogen-based fertilisers vastly increased the production of food. Computers completely transformed how modern humans learn, work and communicate. Surely, it would seem that investing in scientific breakthroughs is the key to progress. In this spirit, social scientists develop ‘evidence-based’ practices and policies and create hierarchies of evidence to determine ‘what works’. Many believe that if only science can produce enough evidence, discoveries will follow that can change the world – if only we can effectively compel others to accept them.
You know the story. A lone cowboy (unfortunately never a cowgirl) rides away into the sunset having saved the day. The same expectations are often placed on knowledge brokers who bring together different communities to share knowledge and catalyse change. The lone knowledge broker is supposed to be a hero. But speaking from decades of experience, you just can’t do it alone. A single person does not have all the necessary networks, knowledge, understanding, skills or credibility. To be effective, knowledge brokers need teams.
In a unique experiment from 2013–2016, we set up the Bristol Knowledge Mobilisation team. This was made up of four local healthcare policymakers (called ‘commissioners’) and three primary care academics; all of whom had part-time contracts with both the university and in healthcare commissioning. Our aim was for both communities to draw on each other’s knowledge to create ‘research-informed commissioning’ and ‘commissioning-informed research’ (i.e. research of genuine relevance).
In a recent article published in Evidence & Policy, we explored the use of Aristotle’s three knowledge types: empirical knowledge, technical knowledge and practical wisdom, in the everyday work and decision-making of frontline public service professionals.
Our qualitative case study of a Scottish local authority revealed the importance of integrating and recognising the different types of knowledge that are needed to respond to complex policy problems, often referred to as ‘wicked’ problems. Understanding the craft of integrating different types of knowledge, and valuing what can be learnt from frontline workers, is key in achieving impactful evidence-informed policy.
In the current context of a rapidly changing policy landscape resulting from COVID-19, making policy decisions informed by the most appropriate types of evidence is crucial. In this blog, we discuss how Aristotle’s knowledge types can help us understand the types of evidence that should be considered in this ever changing landscape.
The UK Parliament performs key democratic functions holding the government to account by scrutinising policy, debating legislation and providing a venue for the public to air their views through elected representatives. Despite the key role of the UK Parliament in shaping government policy, for example in recent times on Brexit and COVID-19 (though many argue Parliament should have a greater role on the latter), scholars of science-policy interfaces have rarely explored how evidence is sourced and used in legislatures.
An evidence synthesis programme commissioned by the UK’s National Institute for Health Research from two academic teams produced a diverse range of outputs and methodological insights in its first three years of operation. The programme was subsequently re-commissioned for two further cycles. Scoping the topic and involving stakeholders were key to its success.
Matthew Johnson, Elliott Johnson, Laura Webber and Kate Pickett
The COVID-19 pandemic has increased interest in Universal Basic Income (UBI) as a means of addressing a range of socio-economic insecurities. While previous trials of cash transfer schemes have often focused on low-level transfers inadequate to satisfy the needs for which the policy was originally developed, emerging pilots are moving toward a position of increasing generosity. Our multidisciplinary project, Examining the Health Case for UBI, has brought together colleagues in behavioural science, public health, epidemiology and economics to establish pathways to health impact outlined in Figure 1 below. Our work suggests the potential for significant health impact and attendant economic benefit via reduced healthcare costs and increased economic activity. The model suggests that elements of impact may only be felt if payment is set at a more generous level. This could create greater return on investment and, ironically, a more cost-effective system.
We have spent much of our academic and professional careers participating in and leading initiatives that are trying to change how organisations, institutions and systems function. The relentless demands of this work mean there is often little opportunity to reflect on the efficacy of our efforts. To address this gap, we conducted more than two years of ethnographic research to learn how community-university-policy partnerships use research and strategic communication to change how youth homelessness is addressed on a pan-Canadian scale. Our intention was to improve our own tactical efforts to ensure our research contributes to the types of changes we want to see (e.g. an end to youth poverty and homelessness).
We learned that networked knowledge exchange is central to ensuring research-to-policy impact.
In this blog post, we suggest three things researchers can do to produce research that addresses persistent social problems.
Sheena Asthana, Rod Sheaff, Ray Jones and Arunangsu Chatterjee
In an article published in Evidence & Policy last year, ‘eHealth technologies and the know-do gap: exploring the role of knowledge mobilisation’, we described the eHealth Productivity and Innovation in Cornwall and the Isles of Scilly (EPIC) project, which aims to support the development of a sustainable innovation ecosystem. We found that, in order to build practically useful links between user (and/or carer) groups and those developing new eHealth technologies, the EPIC team had to invest significant resources in knowledge sharing, one-to-one networking, building focused linkages and capacity building; that financial support can play a key role in supply-side dynamics; but that the contextual and organisational barriers to eHealth innovation in England should not be underestimated.