What is scaling science? How does it relate to integrated knowledge translation (IKT)? To answer these questions, we talked with Rob McLean, an IKTRN member, recent PhD graduate from Stellenbosch University (under the supervision of members Jimmy Volmink and Ian Graham), and co-author of the new book Scaling Impact: Innovation for the Public Good. In this book, McLean details the results of an integrated knowledge translation project that retrospectively reviewed over 200 research projects funded by the International Development Research Centre (IDRC). In this project, McLean worked with IDRC, a Canadian research funder, to co-produce a novel, evidence-based approach for generating more meaningful research impact – Scaling Science.
Can you explain scaling science in lay terms?
RM: Effectively, scaling science is a new framework that we’re developing for optimizing the impact of research. Our hope is that it will help researchers to design, manage and evaluate the impact of the work they’re doing. The title, “Scaling Science”, is a purposeful play on words with an intentional double-meaning. We’re talking about scaling the results of science, so creating better impact with science through people or health systems or whoever our intended users are, but also the scientific study of that process. So we really are trying to embody both needs.
How is scaling science different from what we would traditionally think of as knowledge translation (KT) or implementation science?
RM: My hope is that scaling science will enrich the way we think about implementation science or knowledge translation. If KT is about converting research into action, then scaling is about optimizing the impacts of those actions. And so what that implies conceptually, is that we’re going much deeper into the world of the knowledge user.
To judge implementation as successful we think, for example, did the hospital practitioner use our findings? Did they implement the proven good practice? And while that’s an important step in having research be impactful, when we reviewed projects we found that so often those results were implemented for a short period of time or were only relevant in a very tightly defined context. And so we wanted to think about building a way that researchers could think from the beginning of their project much further into the world of this knowledge user and all of the challenges they’ll face as they try to make use of the research.
It pushes us a bit further into the ‘application’ part of knowledge translation than our current models do. I think it’s up to KT experts to challenge that and to unpack that a little bit. And so this is a great way for me to present that argument and see how people respond to it.
What are the similarities between IKT and scaling science?
RM: When we looked at these past projects in our research we found so many of the principles of IKT as drivers of research impact. If you look at the book, each of the five cases contains some element of IKT. For example, writing relevant questions for knowledge users and working with the users to interpret the data and your findings. Our first guiding principle for scaling science for doing impactful research is ‘Justification’: scaling research impact is a choice, and that choice is shared. I think that’s a really clear indication of the importance of co-production and IKT. We found over and over again that if this decision was shared, you were more likely to have impact with your work.
In IKT we use the term “knowledge users” for people who collaborate with researchers on IKT projects. Is this term equivalent to the four groups of “initiators, enablers, competitors, and impacted” referred to in scaling science?
RM: The short answer is – these are the same things as knowledge users in many cases, but we have these four categories that might help us enrich the way we think about engaging people in research.
We wanted to further categorize the different types of “actors” that exist in the system you’re working in when you’re doing a research project. We talk about “initiators, enablers, competitors and the impacted” and each of these play critical roles in the success of a research project.
“Initiators” can be your funder because they’re paying you to implement. They can be your team that does this kind of work. These people play a critical role and without them, you’re probably not going to have any research impact. “Enablers” are people like your hospital administrator saying you can do this project here and we’ll let you collect this data, or your peers who give you ethics review or support in implementing this work and they also play a critical role.
Another player in the research system that’s quite novel is our “competitors.” This doesn’t necessarily mean another researcher who is somehow competitive with you. In the scaling science model, we’re not just talking about people; we’re also talking about things like norms, institutions, culture or laws. Often times, a certain proven good practice for health is not going to jive well with local culture, whether that’s hospital culture or religious culture, and so you may run into problems convincing people this is a good way to do things no matter how much evidence you have. So mapping those “competitors” out really helped projects achieve meaningful impact.
And then finally “the impacted” – those can be your users, but often times it’s more than just your users and it’s the full group of intended and unintended beneficiaries of the research project. So not just the nurses who you engaged in your behaviour change process because you want them to do something differently; it’s also the people the nurses are there to serve, so patients. A key finding of our research is how much “the impacted” really matter for success, not because you want to affect them but because of how much control they ultimately have over success. If they don’t like the thing that’s happening to them, they’re not going to engage with it. And so although we like to plan for how our work will benefit these people, bringing them into the process is a key driver of success because ultimately they control whether or not you are successful.
What is not talked a lot about in IKT is how these groups are what we call ‘evolving.’ And so you may have a knowledge user who is engaged from start to finish as your research partner. But then different players come and go through the process of doing the research, and you need to find ways to engage them appropriately dependent on where you are in the process. Being accepting and flexible about changing users is critical for the ultimate impact of the research.
What can IKT learn from scaling science?
RM: I would push IKT researchers to think beyond “implementation” or think beyond “translation” and think about research impact. When you start to design a project for impact, you think about it very differently. Imagine how your research matters to other potential users? In different jurisdictions? Or in five years from now? You won’t always find precise answers to these questions, and there likely aren’t precise answers. But, thinking it through will illuminate issues our knowledge users face downstream in their applications. In our research, we saw that those who did were more likely to produce research that led to meaningful and sustainable results.
Given that scaling science is an IDRC initiative, does scaling have applications outside of international development?
RM: I certainly believe so. Although the results are derived from a review of what IDRC calls “research for development” projects, looking at this from another angle, you might simply describe these as use-oriented projects implemented in, and by, the Majority World. Although Minority World researchers dominate the conventional scientific space like publications, conferences and academic platforms, those of us in high-income countries are not the majority of brilliant minds on this planet! There is much we can all learn by looking to the experience and ingenuity of the Majority World.
I’m also a part of a team based in Canada looking at writing reporting guidelines for scaling studies in health sciences. These reporting guidelines are long overdue. “Scaling” has become a buzz word but it’s really haphazardly defined, reported and evaluated. These reporting guidelines will be applicable for projects trying to scale something or evaluating the scaling of something or doing research on a scaling issue. Improving how scaling is reported in the literature will help continue building the science of scaling. And so that’s really exciting for me that we are creating international reporting guidelines for application in different countries and settings.
Want to learn more about scaling science?
- Open access book – Scaling Impact: Innovation for the Public Good
- Guide for researchers – The Scaling Playbook: A Practical Guide for Researchers
- Short brief – In Brief: Scaling Science
- 2-minute video – What is Scaling Science?
- IDRC’s Scaling Science website