behaviour changedesign thinkingeducation & learninginnovationpsychology

Design & Behavioural Science: It’s Time

Understanding the glass, whether its full or not, and why it matters (CC-Flickr SOCIALisBETTER)

What good is design and why should non-designers care? These are questions that designers ask a lot. As one who has developed his practice of design within public health (the behavioural sciences focus), I come from a world where the term “design” is viewed with disdain at worst or indifference or curiousity at best. The concept doesn’t resonate with that audience…yet.

As a designer of systems to promote the health and wellbeing of individuals through helping them solve complex problems individually and groups I find myself attracted to others who try to do the same, even if it is often from a perspective and focus other than health. That gets me into the world of graphic and industrial designers, interaction designers, and now those who use the term social designers or humanitarian designers.

Not surprisingly perhaps, this interaction brings with it much learning for me as it enables me to receive the gifts that diversity brings. The language, the culture and the context of design in design programs, studios and conversations is thrilling for me. As business has joined the conversation, that diversity has increased and programs like OCADU’s Masters in Strategic Foresight seem to capture this type of interaction between what might be called traditional and non-traditional design space.

From this vantage point I see a lot and being an ‘outsider’ provides a wider-angled lens on such phenomenon (while those inside have more telephoto lenses to enable them to see deeper, to extend the metaphor). There are a few things I see through this lens:

1. Designers care a lot about what others think they do and spend an inordinate amount of time coming up with definitions and terms used to describe their craft. On one hand, this is useful and encouraging to see such interest in communicating with the world the value of design, but what could be viewed as attention to education could also be seen as a sense of drifting priorities and a lack of focus or confidence within the field. This intense interest in using rhetoric to show the world designs value, exemplified in the videos, myriad books on design processes, thinking, types, and models is all useful to novices and getting the word out, but at some point the data need to speak.

2. Designers use the concept of “interdisciplinary” very differently than I do. I thought public health had a case of the interdisciplinary-itis, but clearly its endemic across different disciplines and fields and that the way it is used is very different. I already knew this from my own research that has looked at how interdisciplinary researchers collaborate on science problems, but it never ceases to amaze me how the terms get used in other fields and contexts. In design, interdisciplinary often means mixing graphics design folk with industrial designers and visual artists. Taken one step further and you get the IDEO model that expands this to include different fields like anthropology and engineering. This is much closer to what I think of when I consider interdisciplinary, but that is much more rare than I originally thought I’d find in the design world.

3. Designers have a strange relationship with psychology. The use of the word “empathy” is far more common in design than in public health. That excites me for design, but saddens me that it is so rare in public health, but I digress… Yet, while designers are great at getting to know their audience, the methods they use are rather small. Much of it relies on ethnographic study and (from what I can tell) fuzzy qualitative data collection. The methodology is not problematic, but the execution might be. In academia, particularly academic psychology (where I was trained), we are encouraged to explore two things in great depth when appraising others’ research: 1) the rigor of the application of method and analysis, and 2) the use of theory. In both cases I have found design research lacking. What is the theory of change or design used? How was the data analyzed? Why was [this] method used over [that] one? I rarely get good answers to this — at least the kind that my academic colleagues would appreciate.

Designers need behavioural scientists to help them step up their game as much as the world needs designers to help behavioural scientists step up theirs.

Many of the reasons I love design is that it goes to places where academia fails to look and where the public often lives. Many of the design methods and processes like sketching user experiences, empathic research and engaged interaction with clients are things that public health and other fields need to do. Many academics are so far removed from the real world that we’ve left little reason for the public to WANT to engage us. But the downside is that we’ve taken many of the theories, methods and tools that we’ve honed over thousands of trials and studies and produce some good data and synthesis with us. Designers need us to help them step up their game as much as we need designers to help behavioural scientists step up theirs.

behaviour changedesign thinkingevaluationresearchscience & technology

The Science of Design & the Design of Science

Glasgow Science Centre (by bruce89, used under Creative Commons Licence)

As the holidays approach I’ve been spending an increasing amount of time looking at a field that has become my passion: design. Design is relevant to my work in part because it frequently deals with the complex, requires excellent communication, and as Herbert Simon would suggest, is all about those interest in changing existing situations into preferred ones.

Yet for all the creativity, innovation and practicality that design has I find it lacking in a certain scientific rigour that it requires to gain the widespread acceptance it deserves.

This is not to say that designers do not employ rigorous methods or that there is no science informing design. For example, architecture, a field where design is embedded and entwined, employs high levels of both rigour and science in its practice. The issue isn’t that these two concepts aren’t applied, they just aren’t applied to each other. I was heartened this week to see Dexigner profile a new pamphlet on the science of design. Although true in spirit, it wasn’t what I expected to see as it largely profiled ways to assess the quality of design projects from the perspective of design.

What if we could assess the impact of design on a larger scale, a social and human scale?

Interaction designers speak of this need to connect to the human in design work. The emergent field of social design exemplified by groups like Design 21 who aim to produce better products for social good. All of this is important, but it’s important largely because we say it is so. Rhetorical arguments are fine, but at some point design needs to confront the problem of evidence.

Does “good” design lead to better products than “bad” design?

What components of design thinking are best suited to addressing certain kinds of problems? Or are there simply problems that design thinking is just better at addressing than other ways of approaching them?

What methods of learning produce effective design thinkers? And what is effective design thinking anyway? Does it exist?

What is the comparative advantage of a design-forward approach to addressing complex problems than one where design is less articulated or not at all?

These are just some of the many questions that there seems to be little evidence in support of. A scientific approach to design might be one of the first ways of addressing this. In doing so, a scientifically-grounded design field is far more likely to garner support of decision makers who are the ones who will approve and fund the kind of projects that can have wide-scale impact. Design is making serious in-roads to fields such as business, education, and health, but it represents a niche market when it has the potential to be much larger.

Roger Martin has argued that the reliance on scientific approaches to problem solving runs counter to much of design thinking. This assumes that science is applied in a very detached, prescriptive manner, which is common, but not the only way. Micheal Gibbons and colleagues have described two forms of science, which they call Mode I and Mode II science. The first Mode is the one that most people think of when they hear the term “scientist”. It is of the (usually) lone researcher working in a lab on problems that are driven by curiosity with the aim of generating discoveries. For this reason, it is often referred to as discovery-oriented research.

Mode 2 research is designed to be problem-centred and aimed at answering questions posed by practical issues and has a strong emphasis on knowledge translation. This is an area more accustomed to the designer.

Design presents the opportunity to transcend both of these Modes into something akin to Mode 3 research, which I surmise is a blend of the abductive reasoning inherent in Roger Martin’s view of design thinking and the discovery-oriented approach that goes beyond just the problem to create value beyond the contracted issue. A design-oriented approach to the science of design would involve leveraging the creative processes of designers with some of the tools and methods accustomed to researchers in Mode 1 and 2 science. Can we not do detailed ethnographic studies looking at the process of design itself? Is there any reason why we cannot, with limits acknowledged and in appropriate contexts, attempt to do randomized controlled trials looking at certain design thinking activities and situations?

If design is to make a leap beyond niche market situations, a new field must dawn within design + science and that is the science of design and the design of science.

complexityeducation & learningemergencepublic healthsystems science

Spectrum Thinking and Complex Systems

Among the most frustrating aspects of being a systems thinker/actor/researcher is the “one thing” question: What is the one thing that we can do to solve this problem?

The answer is almost always: there isn’t one thing you can do, the problem requires a complex response*

*That isn’t always the case, but in my line of work, it pretty much is true that the problem and its solution fall within the realm of complexity.

When you work in complex systems, the problems are nearly always multifaceted, convoluted and multi-dimensional in their scope and impact. Yet the “one thing” request comes up all the time.

Dave Snowden, from Cognitive Edge,  in his work with the Cynefin Framework nicely points to the difference between best, good, and emergent practice. In public health and medicine, the term “best practice” has been so dominant that it is hard for people to lose the terminology, even if they acknowledge that it sometimes doesn’t fit (the concept of “better” practice is often snuck in as a way to placate those who subscribe a model of thinking that challenges “best” practice thinking). While this is very useful, the problem that even useful frameworks like Cynefin produce is a tendency for people to put whatever they are doing into boxes.

Looking at Cynefin, you can see the world compartmentalized into four nifty quadrants, making the world simple — or at least complicated, but certainly not complex. Dave Snowden himself has been critical of this tendency in his writings on Cognitive Edge’s blog, yet time and again I see this type of thinking come alive. I currently am teaching a course for graduate students on systems science perspectives in public health and this is one of the pitfalls that I hope the learners in my class can avoid.

It’s not easy. We humans love to compartmentalize things. Charles Darwin, one of the founders of modern science, famously began his career putting things in literal and metaphorical boxes. Classification is something we do from our earliest years and do all the way through school. Indeed, a brilliant and somewhat depressing look at how engrained this thinking is can be seen in Sir Ken Robinson’s animated TED Talk on the history and possible future of education.

Systems thinking requires spectrum thinking. People must be able to see things on a gradient, rather than in absolute compartments. Students can’t be faulted too much for having a hard time with this when they are graded based on letters where a B+ is a 79 and an A- is one percentage point higher, yet the mere presence of a B (anything) on a transcript can mean the difference between an award, admission, or a job and not.

This is in no way a criticism of Cynefin or other frameworks used to explain or assist in the understanding of complexity, but rather a statement of the problems inherent in our quest to teach others about complexity that is intellectually honest, reasonably accurate, yet also effective in helping people understand the gravity and scope of complexity in practice. I don’t have an answer for this, but do find using a spectrum useful.

And on a side note, the multi-coloured palette of the spectrum also allows for an introduction of the concept of diversity and human relations at the same time as it illustrates a way of thinking about complex systems.


design thinkingeducation & learninginnovationsocial systems

Coffee Culture and Ideas: A Need for A Break

A little departure this week. Think of it as a coffee break.

There is a theory that the Industrial Revolution and the intellectual flourishing that came from it in England was due to one thing: coffee. Up until then, people were mostly, well drunk. When water sanitation is poor and the options for getting water intake few, beer and wine were among the only options for people seeking means to hydrate. So for centuries there were entire generations of people who largely pickled from day to day (no wonder the lifespan was less than 40 for many).
Then along came coffee, allowing you do something with boiled water that tasted — well, better than boiled water. (Although as one who is a bit of a coffee connoisseur, I can only imagine that it tasted horrible back then, but I digress). Coffee had a bonus effect: it is a stimulant. So instead of swilling back a pint of ale at the pub, which leads to sleepiness, proclivity for getting into fights or having unwanted/unplanned sex, and general unwellness (not mention a big gut), we had people perky, with neurons firing wanting to chat and coming up with ideas — lots of them. And the recipe for coming up with a good idea, is to come up with lots and lots of ideas. The author Steven Johnson talks (and writes) about this in a very interesting and recent TED talk .

For me coffee has had a very special place in my heart (and tummy I suppose). I discovered coffee in the dog days of high school when coffee shops were one of the only places we could hang out. But it was in university that I really enhanced my love of the bean and used it various ways. It was an escape from studying: “I’m just going for a coffee”

Or work: “coffee break time”.

Sometimes it was to help me wake up, and sometimes it was used to help me stay up.

But what I loved most about it were those times when it was the catalyst for the kind of discussions that Steven Johnson talks about. I had three different places I frequented, but none were as enjoyable as Stone’s Throw, which was literally a stone’s throw from the university campus, where I lived for the last two years of my degree. During my time there I made friends, and grew friendships, but also found solace in books and my journals that I kept. It really was a time when my ideas lived large and ruled my life as I somehow managed to find a way to fit my friends, loved ones, work, academic pursuits, hobbies and down time.

We are our ideas and what we do with them and its that simple act of taking pause over a cup of coffee (or tea, or matcha latte, or ….) that can remind us of what those ideas are and, in the process, who we are as people. The idea of the “to go” cup is anathema in some cultures, because it takes the act of communion that coffee brings out of the equation and just leaves you with a pressed drink of beans, water, and maybe some milk. I agree to some extent, but even the act of going out for coffee — particularly with friends or people who love (who are often both) — is a way of creating possibilities by engaging people in dialogue, through a shared experience of a drink.

You cannot travel to any culture where food and drink is not part of a welcome or hosting arrangement. To offer someone something to drink is a sign of hospitality. I’ve been reminded of the importance of this a lot over the last few weeks and with it, what ideas have been nurtured along with it.

Our ideas and the sharing of those ideas are the utmost expression of who we are. It is creativity: to create something. By offering tools and technologies, knowledge and opportunities to connect people to helpful services, we are inspiring in them ideas about how to engage in the world.

With a Starbucks on nearly every corner, it should be easy to generate ideas and get good ones. But it seems that what is missing is the break. Sit in any Starbucks or related cafe and you’ll see that most orders are “to-go”, creating all kinds of waste and also potentially stifling the opportunity to sit and reflect. What we’ve done is taken all the caffeine benefits from coffee, added sugar to it, and upped the calories without adding the most essential ingredient: time.

As the holidays approach, the days get shorter, and the number of demands increase, I am reminded about the benefits of coffee beyond the warmth it brings and how, with time (and maybe a little sugar), it can do wonders to stoke innovation.

complexityemergencepublic healthsocial mediasystems science

Systems Thinking, eHealth and Changing Public Health

Tomorrow is my last class in CHL 5804: Health Behaviour Change for the 2010 year. Like every year, it was filled with the expected, unexpected and everything in between. I love teaching the course and interacting with about 30 graduate students from different disciplines, research backgrounds and educational levels. And while we often don’t admit it to our peers, one of the biggest reasons to teach is that we learn a lot, maybe more, than the students in our courses.

This year I was quite surprised by the interest in two areas: systems thinking and eHealth. Now these are my areas of interest so this is not a surprise on the surface, but then I’ve had these interests for a few years and are about equally passionate today than in past years. Another argument is that I am a better teacher today, which I suppose is possible, but as I look more into my own teaching practice I can’t imagine that the quality of teaching is significantly different than in past years.

I am taking this as a sign of maturity of both fields relative to public health. Both of these fields are relatively new. Depending on your definitions — of which there are many — eHealth has been around for about 15 years, evolving with the World Wide Web. Systems thinking and public health is a little younger, with its rise beginning less than 10 years ago. The publication of the US National Cancer Institute’s monograph on systems thinking and tobacco control, Greater than the Sum, published a couple years ago and the special issue of the American Journal of Preventive Medicine and the American Journal of Public Health, both signaled the rise of systems thinking and public health.

As we know from work in knowledge translation, it can take a long time to get knowledge into practice and this year I think the knowledge about the potential of tools like social media, mobile technologies and consumer-oriented databases has translated into action. My students do presentations each year pitching a hypothetical version of a Framework Convention similar to the one on tobacco control. This year, to my surprise (and with no coaching, particularly given that my eHealth “lectures” are all delivered electronically) most of the groups included some type of eHealth or mHealth intervention in their plans.

These were not just ideas aimed at impressing the professor, rather they represented some remarkably creative ideas on how to use technology to support health promotion, disease prevention, and public eHealth all around.

Attached to this idea of technology aiding the development of interventions for change was the idea that these eHealth tools exist within a larger system. When you speak of social networks or systems dynamics, you are in the realm of systems thinking. The idea that things are connected and intertwined is an idea that seems to hold a lot of appeal for many students and this is growing, particularly as more of my students have real world experience each year. This is important because once you’ve spent time dealing with problems at anything other than a theoretical level, you begin to see the breakdown in linear approaches to problem solving and the need for thinking in systems.

At the same time, as you spend time in that world you also see the problems and costs associated with relying solely on face-to-face methods of intervening. There simply isn’t enough funds, people or other resources to sustain a model that relies exclusively on physical, one-to-one care and prevention efforts. eHealth provides an avenue to consider ways of doing things at a distance and, for some conditions, this translates into interest in doing things that can reach more people for less money, hence the interest in eHealth.

This makes me quite pleased.

behaviour changecomplexityeHealthinnovationknowledge translation

The Face-to-Face Complexity of eHealth & Knowledge Exchange

The Public Health Agency of Canada‘s 2010 Knowledge Forum on Chronic Disease was held last night today in Ottawa with the focus on social media. The invitation-only affair was designed to bring together a diverse array of researchers, practitioners, policy developers, consultants and administrators who work with social media in some capacity. There were experts and non-experts alike gathered to learn about what the state of the art of social media is and how it can support public health. By state of the art, I refer not to the technological side of things, but rather the true art of public health, much like that discussed earlier this year at the University of Toronto.

Last night began with a presentation from Leanne Labelle that got us all thinking about how social media is radically different in the speed of its adoption and breadth of its social impact drawing inspiration from this video from Eric Qualman’s Socialnomics website.

Today we got down to business and started working through some of the issues that we face as a field when adopting social media. I would probably consider myself among the most experienced users in the audience, yet still gained so much from the day. Although I learned some things about how to use social media in new ways, what I learned most was how others use it and what struggles they have. This is always a useful reminder.

What stuck out was a presentation and related discussion from Christopher Wilson from the University of Ottawa’s Centre on Governance and a consultant on governance issues. In speaking about the challenges of doing collaboration, Christopher pointed to the problems of a ‘one-size fits all’ strategy using a diagram illustrating the fundamental differences between engagement at a small scale (under 25 people) and what is the mass collaboration that folks like Clay Shirky, Don Tapscott, and others write about. His diagram looks like this:

Technology Spectrum of Social Collaboration by Christopher Wilson

What Wilson stressed to the audience was the role that complexity plays in all of this. Specifically, he stated:

The more complex and interdependent things become, the more people need to be aware of the changing context and the changes in shared understanding.

As part of this, groups are required to engage in ways that enable them to deal with this complexity. In his experience, this can’t be done exclusively online. He further stated:

As complexity increases, the need for offline engagement increases.

I couldn’t agree more. In my work with community organizing and eHealth promotion, I’ve found the most effective means of fostering collaboration is to blend the two forms of knowledge generation and exchange together. The model that my research team and I developed is called the CoNEKTR (Complexity, Networks, EHealth, and Knowledge Translation Research Model).

This model combines both face-to-face methods of organizing and ideation, with a social media strategy that connects people together between events. The CoNEKTR model has been applied in many forms, but in each case the need to have ways to use the power of social media and rich media together with in-person dialogue has been front and centre. Using complexity science principles to guide the process and powered by social media and face-to-face engagement, the power to take what we know, contextualize it, and transform it into something we can act on seems to me the best way forward in dealing with problems of chronic disease that are so knotted and pervasive, yet demand rapid responses from public health.

complexityemergenceknowledge translationpublic healthsystems science

Evidence Democratization in Complex Systems

In the social media and marketing world there is a concept called “brand democratization”, which refers to the notion of having your customers contribute to and partly shape a brand’s identity. Marty Neumeier, who has written extensively on branding, asserts that a brand isn’t what the producers of the product say it is, but rather what the customers say it is.

The notion that the meaning and identity of a brand is outside of the control of those that develop a product is unsettling for many in business. Social media only amplifies this feeling. A social media consultant I work with once relayed a story about how a client (a big company) once asked how they could use social media to control their message more effectively and how unsettled they were to hear that “control” is not what social media is about and frustrated at the thought that they were no longer in the driver’s seat.

To some extent, we are seeing the same thing take place in the health sector, particularly in areas of great complexity. As complex chronic conditions become more prevalent and the number of people with multiple chronic conditions represent a larger proportion of the population (a near inevitability in societies with aging demographics and better health care), complexity will gain a greater place in our health care policy discourse.

Evidence-based medicine holds very clearly a sense of what is good and not-so-good quality content. Hierarchies abound and medical students are taught early on about what the best evidence is and how it is generated. The problem with the “best evidence” in health care is that it typically comes from studies focused within a rather narrow contextual band of activity using designs that aim for simplicity, not complexity. In standard research programs the aim is to reduce variation, not embrace it.

This is nearly the opposite of complex systems, where variation is, to a point, the key to learning and adaptation. Making sense within a complex system requires deep appreciation of context and an understanding of one’s position within the system. However, because such positions are relative, the ability to hold “expertise” in a system is limited. Indeed, there are many who occupy positions where they have great knowledge and the ability to re-interpret and generate evidence as opposed to only a few.

Does this create evidence democratization? When there is so much information from many sources, a need for contextualized feedback and many actors with useful experience and knowledge occupying different positions related to a problem, it seems that the answer is “yes”.

Social media operates within an environment of complexity due to the widescale involvement of diverse actors working in a coordinated, yet sell-organized manner, across many boundaries within multiple overlapping contexts. What is “true” within a social media sphere is only made so by the application of that knowledge within a particular context. A blog only has meaning to its creator and her or his audience, not the entire system. Yet, the actors engaged with that content may take it and rework it, retweet it, or post it in a new environment, where it is transformed into something else. If that “something else” has value, it lives onward.

In health contexts, that value might be very different depending on the condition and the manner in which that knowledge is applied. From a traditional evidence-based health approach, this is utterly terrifying. How can evidence be re-interpreted? What are the harms associated with taking something from one context and applying them to another for which it wasn’t designed? These are concerns, yet it is hard to imagine that there isn’t also some potential value in exploring ways in which this plays out in chronic and complex conditions given that the evidence is rarely that “hard” going in.

Are we on the cusp of a new wave of evidence democratization? And if so, are we going to be healthier as a result of it? More innovative? Or in deep trouble?