Why model?

By Steven Lade

Steven Lade
Steven Lade (biography)

What do you think about mathematical modelling of ‘wicked’ or complex problems? Formal modelling, such as mathematical modelling or computational modelling, is sometimes seen as reductionist, prescriptive and misleading. Whether it actually is depends on why and how modelling is used.

Here I explore four main reasons for modelling, drawing on the work of Brugnach et al. (2008):

  • Prediction
  • Understanding
  • Exploration
  • Communication.

I start with mental models – the informal representations of the world that we all use as we go about both our personal and professional lives – and then move on to formal models.

Mental models

We are all modellers! We all use mental models every day for a variety of different purposes:

  • To make quantitative predictions about the future. For example, if I throw the ball this fast, where will it land? How much money would my house sell for?
  • To understand things that happened. For example, why did the cake I baked not turn out like expected? Why was Donald Trump elected as president in the USA, against many expectations?
  • To explore alternative versions of our worlds. For example, what if I added a room to my house? What is life like for someone living in another country?
  • To communicate. Communication is nothing more than the construction and sharing of mental models via language, and we use it every day. For example, when we talk about love, the weather, justice, our garden, or tax, we use representations of these concepts that are at least partially shared among those involved in the conversation.

Formal models

All these purposes can also be fulfilled by formal models.

Prediction is the model purpose most commonly associated with formal modelling, though in wicked problems prediction should be treated cautiously and with full understanding of the model’s assumptions.

Understanding is the model purpose most commonly used in traditional science, to test hypotheses against observations.

The remaining two purposes, exploration and communication, are of the most relevance for wicked problems, yet are arguably the most underappreciated.

Exploration using formal models is nothing more than a reasoning tool to support our own mental modelling capacity for exploration. The effects of complex system dynamics features such as multiple interacting feedbacks can be difficult to anticipate and may even be counter-intuitive: that’s why they’re considered ‘complex’.

An example can be seen in research on how different poverty-environment relationships affect which poverty alleviation strategies are likely to be effective (Lade et al., 2017). We showed that in situations where poor people degrade their environment—usually because they have no choice—asset inputs may help break that cycle of poverty. But in situations where poor people maintain their environment, and agricultural intensification leads to increased environmental degradation, asset inputs may be counterproductive and even reinforce poverty, requiring other strategies.

Finally, sometimes the process of constructing the formal model can be just as valuable as the model itself. Participatory model construction encourages communication of each participant’s mental models, thereby developing awareness of others’ perspectives and possibly challenging one’s own mental model. In an earlier blog post, Jen Badham and Gabriele Bammer described how jointly designing formal models can help stakeholders draw out differences in their mental models of a complex system. For example, a modelling process could help draw out the different understandings that farmers and government policy-makers have of an agricultural system and the different challenges that they face when interacting with this complex system.

In summary, mathematical models have a valuable place even in complex systems with wicked problems, especially when used for exploration and communication. As with any tool, the key is to be aware of why you’re using them.

Why do you model? Do you have other modelling purposes to share? Or additional examples of the reasons for modelling described above?

References:
Brugnach, M., Pahl-Wostl, C., Lindenschmidt, K. E., Janssen, J. A. E. B., Filatova, T., Mouton, A., Holtz, G., van der Keur, P. and Gaber N. (2008). Complexity and Uncertainty: Rethinking The Modelling Activity. U.S. Environmental Protection Agency Papers, 72. (Online): http://digitalcommons.unl.edu/usepapapers/72

Lade, S. J., Haider, L. J.,  Engström, G. and Schlüter, M. (2017). Resilience offers escape from trapped thinking on poverty alleviation. Science Advances, 3, 5: e1603043. (Online) (DOI): https://doi.org/10.1126/sciadv.1603043

Biography: Steve Lade is a researcher at the Stockholm Resilience Centre, Stockholm University, Sweden and an Honorary Senior Lecturer at the Fenner School of Environment and Society, Australian National University in Canberra, Australia. He uses complex systems tools to study the resilience and sustainability of human and natural systems including fisheries, poverty traps and the Earth system. He is currently funded by a young researcher mobility grant from the Swedish Research Council Formas.

Fourteen knowledge translation competencies and how to improve yours

By Genevieve Creighton and Gayle Scarrow

Genevieve Creighton
Genevieve Creighton (biography)

Knowledge translation encompasses all of the activities that aim to close the gap between research and implementation.

What knowledge, skills and attitudes (ie., competencies) are required to do knowledge translation? What do researchers need to know? How about those who are using evidence in their practice?

As the knowledge translation team at the Michael Smith Foundation for Health Research, we conducted a scoping review of the skills, knowledge and attitudes required for effective knowledge translation (Mallidou et al., 2018). We also gathered tools and resources to support knowledge translation learning.

Gayle Scarrow
Gayle Scarrow (biography)

What should you know to effectively engage in knowledge translation? Here are the top 14 competencies identified:

  1. Understand the context: Develop an understanding of what goes on in organizational settings and/or local health care systems, day-to-day practices and “how things really work”.
  2. Understand the research process: Know the process of how to conduct research including how to develop a research question, use search strategies and how to identify appropriate databases to gather evidence on a specific topic.
  3. Know how knowledge is disseminated: Understand the range of meaningful ways to share knowledge/evidence to ensure that it is available and accessible to different audiences.
  4. Be aware of evidence resources: Know a variety of ways to find evidence including library databases and information contained in listservs, blogs, social media and newsletters. Understand the importance of oral tradition, practice and tacit knowledge as sources of evidence.
  5. Know theories, frameworks and models for doing knowledge translation and evidence-based practice: Understand the definitions of evidence-based practice and knowledge translation, and understand models and theories of knowledge translation.
  6. Understand knowledge translation and dissemination activities: Be able to interpret research findings for various audiences and uses. Understand the processes and uses of knowledge synthesis, knowledge translation planning templates, dissemination and implementation strategies and integrated knowledge translation.
  7. Know how to engage in collaboration and teamwork: Be able to develop effective, authentic and respectful working relationships with peers and others in order to collaborate, network, share information and engage in research.
  8. Engage leadership: Have an ability to scan the context, facilitate stakeholder involvement in evidence-based decision-making, influence skill development and act upon stakeholders’ views and needs.
  9. Know how to share knowledge: Be able to share information and data with diverse stakeholders. You should also have the skills to conduct research that is relevant to the intended users so that it is more likely to inform practice and policy.
  10. Be able to synthesize knowledge: Have the skills to use robust practices to combine research findings and grey literature, synthesize the evidence and appropriately use/apply the findings.
  11. Disseminate research findings: Know how to share research findings with various stakeholders. This competency includes the ability to summarize research findings, communicate and highlight key findings in a way that may influence decision-making.
  12. Make use of research findings: Know some strategies to apply research findings to clinical or policy decisions or to inform further research.
  13. Know how to foster innovation: Be able to use novel tools and strategies to improve practice or policy, address issues, assess and build service improvement approaches, and evaluate the impact of an innovation.
  14. Be a knowledge broker: Have the ability to act as a bridge between evidence and implementation; applying knowledge translation strategies to facilitate the flow of knowledge, improve practice and policy and increase research findings’ uptake.

Assess Yourself

It’s great to know what the knowledge translation competencies are, but how can you measure your own knowledge translation skills and knowledge? Knowledge Translation Pathways (https://ktpathways.ca/) is an online tool designed to enable researchers, knowledge brokers and those who use research evidence in their practice to rate themselves on the range of knowledge translation competencies and get the tools and resources to support further learning.

So how does it work? First, you…

Pick a pathway

There are three knowledge translation pathways, one each for those who produce, apply, and broker knowledge, as shown in the screenshot below. Because many of us play multiple roles (eg., we may both collect and use research), you are encouraged to reflect on what you do most in your work, and choose that pathway.

Three knowledge translation pathways
Screenshot from the Knowledge Translation Pathways website (https://ktpathways.ca/about/how-use-kt-pathways)

Next, you…

Choose a bucket

Knowledge translation competencies are grouped into ‘buckets’ such as: “Research Skills”, “Implementation Skills”, “Bringing People Together” and “Dissemination”. You can choose to do just the buckets that are most relevant to your work right now or you may choose to complete the entire tool to get a full assessment of your knowledge translation competence.

Finally, you…

Do the assessment, get your results and receive knowledge translation learning resources

When you complete the assessment, you’re provided with a knowledge translation learning profile that details your current areas of knowledge translation strength and areas for professional development. You’ll then be directed to knowledge translation resources that will build your competence (eg., articles, videos, blogs, websites, templates and/or online reports).

You can also explore the Knowledge Translation Pathways’ resources database on topics such as arts-based knowledge translation, behaviour change, bringing people together, critical appraisal of research evidence, co-production of knowledge, knowledge translation evaluation, knowledge translation planning frameworks, implementation science and more, as shown in the screenshot below.

Learning resources on the Knowledge Translation Pathways website
Screenshot of some of the learning resources on the Knowledge Translation Pathways website (https://ktpathways.ca/resources)

Feedback and additional resources:

Do you have knowledge translation resources you’ve found helpful? Let us know!

Have you identified other knowledge translation competencies? What about in other disciplines that could inform how we practice knowledge translation?

Reference:
Mallidou, A. A., Atherton, P., Chan, L., Frisch, N., Glegg, S. and Scarrow, G. (2018). Core knowledge translation competencies: A scoping review. BMC Health Services Research, 18, 1: 502. (Online) (DOI): https://doi.org/10.1186/s12913-018-3314-4

Biography: Genevieve Creighton PhD is manager, knowledge translation at the Michael Smith Foundation for Health Research, a research funding agency in Vancouver, British Columbia, Canada. She is responsible for the implementation, monitoring and evaluation of the Foundation’s knowledge translation strategy.

Biography: Gayle Scarrow is director, knowledge translation at the Michael Smith Foundation for Health Research in Vancouver, British Columbia, Canada. She leads the development, implementation, and ongoing management of the Foundation’s knowledge translation plan for the purposes of fostering and accelerating the impact of health research in British Columbia and beyond.

Learning from interdisciplinary and transdisciplinary research ‘failures’

By Dena Fam and Michael O’Rourke

Dena Fam
Dena Fam (biography)

What makes interdisciplinary and transdisciplinary research challenging? What can go wrong and lead to failure? What has your experience been?

Modes of research that involve the integration of different perspectives, such as interdisciplinary and transdisciplinary research, are notoriously challenging for a host of reasons. Interdisciplinary research requires the combination of insights from different academic disciplines and it is common that these:

  • bear the stamp of different epistemologies; and,
  • involve different types of data collected using different methods in the service of different explanations.

Continue reading

Four patterns of thought for effective group decisions

Community member post by George P. Richardson and David F. Andersen

George Richardson
George P. Richardson (biography)

What can you do if you are in a group that is trying to deal with problems that are developing over time, where:

  • root causes of the dynamics aren’t clear;
  • different stakeholders have different perceptions;
  • past solutions haven’t worked;
  • solutions must take into account how the system will respond; and,
  • implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?

Continue reading

Five lessons for early career researchers in interacting with policymakers

Community member post by Aparna Lal

Aparna Lal
Aparna Lal (biography)

How, as an early career researcher, can you get started in developing a working relationship with government policy makers? What do you need to be prepared for? What benefits can you expect?

Here I present five lessons from my first self-initiated engagement with policymakers. I am a computer modeller exploring the links between water-quality, climate and health. As such, my research sits at the crossroads of environmental science and public health. At the end of 2018, I decided to present some of my work to the Australian Capital Territory Environment, Planning and Sustainable Development Directorate.

My anticipated outcomes from this presentation were to start a conversation around water and health in the Australian Capital Territory and to leave the meeting with new insights. I also learnt the following lessons: Continue reading

Five principles of co-innovation

Community member post by Helen Percy, James Turner and Wendy Boyce

Helen Percy (biography)

What is co-innovation and how can it be applied in practice in a research project?

Co-innovation is the process of jointly developing new or different solutions to a complex problem through multi-participant research processes – and keeping these processes alive throughout the research.

James Turner (biography)

Our experience has been applying co-innovation as a research approach to address complex problems in an agricultural context, however, the principles apply well beyond agriculture. Co-innovation is most suited to hard-to-solve technical, social, cultural and economic challenges. Such challenges have no obvious cause and effect relationships, as well as many different players with a stake in the research problem and solution. These include policy makers, industry, community members, first nations representatives and others who are involved in the research as partners and stakeholders. Continue reading