Should implementation science make more room for consultation, collaboration and co-creation with stakeholders? Would finding more active roles for stakeholders in implementation science be a promising approach to increasing the use of research evidence for improvements in policy and services?
The goal of implementation science is to promote the sustainable implementation of research evidence at scale to improve population outcomes, especially in health and human services. Nevertheless, the mobilization of research evidence on the frontlines of health and human services has been quite limited, especially in public agencies serving the vast majority of consumers.
When we talk about co-creation, co-production, and co-design as exciting and productive alternative ways of approaching collaboration, it often doesn’t take too long for the conversation to turn to the challenges. Barriers, roadblocks, and disincentives appear and are lamented, or perhaps we celebrate that they have been overcome in a research-practice equivalent of the triumph of good over evil.
For every project the triumph may look a bit different – from the support an innovative funding agency, to a policy-maker or practitioner who understood the value of research, to the dedication, energy and sheer persistence of people who enjoy working together – the solutions are many and multi-faceted. These achievements should indeed be celebrated, and the lessons from them should be harvested.
Prediction under uncertainty is typically seen as a daunting task. It conjures up images of clouded crystal balls and mysterious oracles in shadowy temples. In a modelling context, it might raise concerns about conclusions built on doubtful assumptions about the future, or about the difficulty in making sense of the many sources of uncertainty affecting highly complex models.
However, prediction under uncertainty can be made tractable depending on the type of prediction. Here I describe ways of making predictions under uncertainty for testing which conclusion is correct. Suppose, for example, that you want to predict whether objectives will be met. There are two possible conclusions – Yes and No, so prediction in this case involves testing which of these competing conclusions is plausible.
Twenty years ago, at one of the first research workshops I held for stakeholders, a participant from the local community put up his hand and asked when we were going to start making something. I obviously looked confused so he picked up the workshop flyer and pointed to the word ‘workshop.’ “You make things in workshops don’t you?” he asked.
At the time, I took this as a lesson in choosing your terminology with care when working with diverse groups of stakeholders. However, on looking back I wonder if I missed something else.
Co-creation, and related terms like co-design, co-production, co-construction and co-innovation, are becoming increasingly popular. Upon closer scrutiny they share many characteristics with participatory processes. Is there a difference between the two – co-creation and participation – and if yes, what is it?
Let us first look at participation. Not all participatory processes are the same. They differ with regard to who is involved, who initiated the process and for what reason, the anticipated outcomes, the duration, the context in which it takes place, and who has control over the process and outcomes.
What can art contribute to participatory modelling? Over the past decade, participatory visual and narrative arts have been more frequently and effectively incorporated into scenario planning and visioning workshops.
We use arts-based techniques in three ways:
incorporating arts language into the process of visioning
delineating eco-aesthetic values of the visual and aural landscape in communities
engaging art to articulate challenges and solutions within local communities.
The arts based approaches we use include collage, drawing, visual note taking, map making, storyboarding, photo documentation through shared cameras, mobile story telling, performance in the landscape, drawing as a recording device, and collective mural creation.
They allow us to expand and deepen engagement strategies beyond the scope of traditional dialog tools such as opinion surveys, workshops, and meetings. And, they allow for both individual and collective work, from spending reflective time independently, to rejoining as a group to discuss process and products. They are also particularly effective in bicultural and multicultural settings.
Visual techniques can help foster a different type of discussion than one that is primarily verbal or quantitative because they involve participants in different patterns of thinking, questioning, and interacting.
La mayoría de los recientes enfoques para abordar problemas complejos no incluyen la dimensión política. Por otra parte, la ciencia política, así como los estudios de política pública y de gobierno contemporáneo han realizado escasas contribuciones al tratamiento de los procesos de toma de decisiones desde dinámicas complejas.
¿Cómo podemos desarrollar marcos innovadores que incorporen la dimensión política?
Why does the theory and practice of co-creation need to be informed by systems thinking? Co-creation without a thorough understanding of systems thinking can be deeply problematic. Essentially, we need a theory and practice of systemic co-creation.
Three key things happen in any co-creation:
It is necessary for a diversity of perspectives to engage.
There is the synergistic innovation that results from this engagement.
The innovation is meaningful in a context of use.
This is already a systemic definition, up to a point: parts (perspectives) are engaged in a whole (a dialogue or other form of collective engagement) that generates an emergent property (synergistic innovation), which is meaningful in context (it is useful).
However there are three problems with this, and they point to the need for a deeper form of systems thinking.
Relationships are the underpinnings of the co-production process. The quality of knowledge gained and the solutions produced are a function of the quality of relationships among the participants.
In a recent paper, Lorrae van Kerkhoff and Louis Lebel (2015) also made strong claims about the relevance, salience, and potential impacts of relationships in the co-production of science and governance needed for sustainable improvements responding to global environmental change.
One important clarification raised by van Kerkhoff and Lebel (2015) is that relationships exist not only among individuals, but also among institutions. These relationships among individuals and institutions exist in historical contexts that are interpreted differently by diverse members. Individual and institutional interpretations affect action and meaning-making in co-production settings.
Ask most 21st century citizens whether they like technology and they will respond with a resounding, “Yes!” Ask them why and you’ll get answers like, “Because it’s cool and technology is fun!” or “Technology systems help us learn and understand things.” Or “Technology helps us communicate with one another, keep up with current events, or share what we are doing.” Look at the day-to-day activities of most people on the planet and you’ll find that they use some form of technology to complete almost every activity that they undertake.
When you think about it, technologies are really just tools. And we humans are tool users of old.
I don’t see the world in pictures. I mean, I see the world in all its beautiful shapes and colors and shadings, but I don’t interpret the world that way. I interpret the world through the stories I create. My interpretations of these stories are my own mental models of how I view the world. What I can do then, to share this mental model, is create a more formalized model, whether it is a simple picture (in my case a very badly drawn one), or a system dynamics model, or an agent-based model. People think of models as images, as representations, as visualizations, as simulations. As tools to represent, to simplify, to teach, and to share. And they are all these things, and we need them to function as these things, but they are also stories, and can be interpreted and shared as such.
Citizens are increasingly coming together to solve problems that affect their communities. Participatory modeling is a method that helps them to share their implicit and explicit knowledge of these problems with each other and to plan and implement mutually acceptable and sustainable solutions.
While using this method, stakeholders need to understand large amounts of information relating to these problems. Various interactive visualization tools are being developed for this purpose. One such tool is ‘serious gaming’ which combines technologies from the video game industry – mystery, appealing graphics, etc., – with a purpose other than pure entertainment, a serious, problem driven, educational purpose.
Such gamification is an opportunity for participatory modeling approaches to embed models and simulations of complex processes into games and to attract the stakeholders.