Design (re)Thinking Health Systems

How might we design health systems to promote health and wellbeing and not just treat illness and disease and manage infirmary and chronic conditions? What if health systems were about health?

If we were to apply design thinking to health systems, what might be do?

In a previous post, I suggested that knowledge translation is too important to be trusted solely to health professionals, partly because they have largely failed to take up the charge. Taking a step back — a systems thinking perspective — one realizes that to design better knowledge translation, we need to design better health systems.

Julio Frenk, Dean of the School of Public Health at Harvard, believes this too. In a 2010 paper published in PLOS Medicine, Frenk comments on the state of health systems and examines how we might re-think them in light of global health challenges.

Health systems are the main instrumentality to close the knowledge–action gap. To realize this potential, it will be necessary to mobilize the power of evidence to promote change. Yet all too often reform efforts are not evaluated adequately. Each innovation in health systems constitutes a learning opportunity.

Frenk’s article is an invitation to engage in systems and design thinking about health. Both approaches invite pause to consider what the problem is in the first place. For design thinkers, problem scoping is the first step.

For systems thinkers this is akin to setting the boundaries around the problem.

Once we set the boundaries and find the appropriate problem, we then frame it appropriately for design. Problem definition is something often over-looked or under appreciated, but is the core of effective problem solving and design.

If I had an hour to solve a problem I’d spend 55 minutes thinking about the problem and 5 minutes thinking about solutions – Albert Einstein

Health systems are typically defined in light of professional services and policies aimed at making the sick well. They are essentially illness and disease (sick care) systems. This conceptualization, still dominant in the professional and policy discourse in many Western countries, places medicine at the centre of health services with the allied disciplines working alongside, but rarely ventures its gaze beyond the institutions of care or the conditions such institutions are designed to treat.

Frenk, writing in PLOS Medicine, suggests its time to expand our view of what makes a health system if we are to truly promote and sustain global health and see three key points as provoking such re-thinking:

First, health has been increasingly recognized as a key element of sustainable economic development [1], global security, effective governance, and human rights promotion [2]. Second, due to the growing perceived importance of health, unprecedented—albeit still insufficient—sums of funds are flowing into this sector [3]. Third, there is a burst of new initiatives coming forth to strengthen national health systems as the core of the global health system and a fundamental strategy to achieve the health-related Millennium Development Goals.

In order to realize the opportunities offered by the conjunction of these unique circumstances, it is essential to have a clear conception of national health systems that may guide further progress in global health.

Frenk offers some suggestions:

Part of the problem with the health systems debate is that too often it has adopted a reductionist perspective that ignores important aspects. Developing a more comprehensive view requires that we expand our thinking in four main directions.

First, we should think of the health system not only in terms of its component elements (like human resources, financing, hospitals, clinics, technologies, etc.) but most importantly in terms of their interrelations. Second, we should include not only the institutional or supply side of the health system, but also the population. In a dynamic view, the population is not an external beneficiary of the system; it is an essential part of it.

It’s important to note the mention of the role of the population and its dynamical impact on the system. As populations change dramatically in their composition and form of residency within countries, including a greater movement to urbanization, so too will the myriad factors that influence health systems. The people are the system and thus it will change as populations change. While Frenk lists this as one point of many, it is a radical departure for reductionists or those who see health systems as being about care, not people.

A third expansion of our understanding of systems refers to their goals. Typically, we have limited the discussion to the goal of improving health. This is, indeed, the defining goal of a health system. However, we must look not only at the level of health, but also at its distribution, which gives equity a central place in assessing a health system. In addition, we must also include other goals that are intrinsically valued beyond the improvement of health. One of those goals is to enhance the responsiveness of the health system to the legitimate expectations of the population for care that respects the dignity of persons and promotes their satisfaction. The other goal is fair financing, so that the burden of supporting the system is distributed in an equitable manner and families are protected from the financial consequences of disease.

Frenk’s third challenge is to affirm the very point of health systems at all.

While not explicitly speaking of systems thinking or design thinking, there is much that both fields have in common with Frenk’s argument. Design thinkers might ask: What have we hired our health system to do?

Frenk argues that our health systems must go well beyond just making gains in measured health outcomes towards dignity, respect and social justice.

Finally, we should expand our view with respect to the functions that a health system must perform. Most global initiatives have been concerned mainly with one of those functions, namely, the direct provision of services, whether they are medical or public health services. This is, of course, an essential function, but for it to happen at all, health systems must perform other enabling functions, such as stewardship, financing, and resource generation, including what is probably the most complex of all challenges, the health workforce.

Frenk did not identify specific solutions, but did pose some key questions for health systems design.

If we were to take this challenge up as designers and systems thinkers, what might we do? Here are some suggestions for inquiry:

Consider new definitions of health like the one posed in the British Medical Journal that emphasizes looking at the social and environmental influences on health beyond just the absence of physical symptoms. Further inclusion of a psychology of human flourishing might add to this definition.
Map out a new system visually with people at the centre, not professionals or institutions. What does that look like? Tools like a Gigamap might provide the kind of multi-media, multi-sensory visual way to conceive of the interrelationships that make up health system. System dynamic models can help this out as well.
Engage people across this system to validate this map and co-create possible future models that could serve to shape discussion at multiple levels and mobilize civil society to support healthy environments.
Create small scale, safe-fail / fail-forward, prototypes of small-scale innovations that can be tested, developmentally designed, and rapidly re-developed as needed to start shifting the system as a whole.

Designing health requires designing health systems. Applying new thinking and envisioning a system that is dynamic, comprised of people and just institutions is a start.

Photo: Bartolomeo Eustachi: Peripheral Nervous System, c. 1722 shared by brain_blogger used under Creative Commons Licence

Is Knowledge Translation In Health Too Important to Leave to Health Professionals?

Posted: April 24, 2013 | Author: Cameron D. Norman | Filed under: education & learning, innovation, journalism, knowledge translation | Tags: communication, health communication, health systems, journalism, knowledge exchange, knowledge integration, knowledge translation, librarians, social media, storytelling, teachers | 7 Comments »

Knowledge translation — and its affiliated terms knowledge exchange, knowledge integration and knowledge mobilization — was coined to describe a process of taking what is known into what is done in health across the spectrum of science, practice, policy and the public’s health. As health issues become more complex due to the intertwining of demographics, technology, science, and cultural transformations the need to better understand evidence and its impact on health has never been higher. Questions remain: has demand met supply? How are the health professions dealing with this equation?

Translating knowledge

The Canadian Institutes of Health Research (CIHR), one of the earliest champions of the concept of knowledge translation in research, define it as:

a dynamic and iterative process that includes synthesis, dissemination, exchange and ethically-sound application of knowledge to improve the health of Canadians (sic), provide more effective health services and products and strengthen the health care system.

These ideas are expanded below:

Synthesis – Synthesis, in this context, means the contextualization and integration of research findings of individual research studies within the larger body of knowledge on the topic. A synthesis must be reproducible and transparent in its methods, using quantitative and/or qualitative methods. It could take the form of a systematic review, follow the methods developed by the Cochrane Collaboration, result from a consensus conference or expert panel or synthesize qualitative or quantitative results. Realist syntheses, narrative syntheses, meta-analyses, meta-syntheses and practice guidelines are all forms of synthesis. Resources related to synthesis are available.

Dissemination – Dissemination involves identifying the appropriate audience and tailoring the message and medium to the audience. Dissemination activities can include such things as summaries for / briefings to stakeholders, educational sessions with patients, practitioners and/or policy makers, engaging knowledge users in developing and executing dissemination/implementation plan, tools creation, and media engagement.

Exchange – The exchange of knowledge refers to the interaction between the knowledge user and the researcher, resulting in mutual learning. According to the Canadian Health Services Research Foundation (CHSRF), the definition of knowledge exchange is “collaborative problem-solving between researchers and decision makers that happens through linkage and exchange. Effective knowledge exchange involves interaction between knowledge users and researchers and results in mutual learning through the process of planning, producing, disseminating, and applying existing or new research in decision-making.”

Ethically-sound application of knowledge – Ethically-sound KT activities for improved health are those that are consistent with ethical principles and norms, social values, as well as legal and other regulatory frameworks – while keeping in mind that principles, values and laws can compete among and between each other at any given point in time. The term application is used to refer to the iterative process by which knowledge is put into practice.

In short, knowledge translation is about taking what we learn and know from evidence, sharing that knowledge with others and assisting them to make useful health choices in practice and policy through KT.

This often involves communicating across contexts, disciplines, and roles between and from scientists, clinicians, policy makers and to the public alike. In a health environment that is increasingly becoming complex, the ability to communicate across boundaries is no longer an advantage, it’s an essential skill. While we may not always have the right language, we can translate meaning through stories.

But if stories are to be effective they need to be valued.

The value of storytelling

I’ve seen health professionals — scientists and clinicians — roll their eyes when you mention storytelling in a work context. It is as if the only legitimate role for stories is to communicate with children (which University of Alberta researchers are exploring as a tool for sharing health knowledge with parents). Yet, it is through stories that most people share what they know in every other context; why would it be different in health?

Perhaps it is the connotation that stories are ‘made up’ like children’s bedtime tales, but one need only look to journalism to find that we’ve been making ‘stories’ a central part of our life every day. We listen to drive-time radio for stories about the traffic conditions, we watch, download and listen to news stories filed by professional journalists and citizen bloggers alike on mainstream media, Twitter, YouTube, Facebook along with myriad sources across the web. Last week we were glued to various sources to learn stories — some of them false — and create stories about the events of the Boston Marathon bombings.

Stories are what conveys multiple information threads and puts it in a coherent context.

Stories are coherence engines.

Valuing knowledge translation

If knowledge translation is important then it should be reflected in research priorities and evidence for its impact on the system across different disciplines. Dr Shannon Scott and her U of A team recently conducted a systematic review of knowledge translation strategies in the allied health professions and found that the field was full of low quality studies that made it impossible to make firm statements on which methods were best among them . That team has recently proposed a systematic review looking at how the arts and visual methods can further contribute to KT in practice, although it likely the same issue with methodological quality might come into play here, too.

What she and her team are doing is looking at the process of sharing stories and, from a research perspective, sharing stories appears to not have been worth investing in scientifically. At least, not enough to generate a lot of studies and good evidence.

One could argue that knowledge translation is still new and that it takes time to generate such evidence. That is partly true, but it is also an easy prop for those who want to avoid the messiness that comes with communication (and its problematic research context), learning from others, and creating more equitable information spaces, which is what knowledge translation ultimately does. Knowledge translation has also been in use for almost 20 years so in that time — even with the most dismal assessment of the length of time it takes to put knowledge into practice — we should be seeing some decent research published.

KT is fundamentally about sharing. Journalists’ are rewarded for sharing — the more they share and the more people who they share with (as measured by readers, listeners, viewers etc..) the more successful they are in their work. Teachers are rewarded for sharing because that means that they are teaching people. Librarians are rewarded for sharing because that means people are checking out books and using the resources in their library.

We don’t apply the same standard to academic research, even though we have some crude metrics to measure reach and impact, and there is roughly no metric for the degree to which clinicians share among themselves. Maybe this needs to change.

I have scientific colleagues who are fierce in the face of their most strident academic critics and have delivered keynotes to auditoriums filled with researchers that are nearly paralyzed in the face of speaking to the public. This is not fear of public speaking, its fear of speaking to the public.

Should they be? I don’t think speaking to the public should be expected to be enjoyable for everyone, but neither are doing statistical calculations, completing ethics applications, or presenting posters at conferences, but we still expect scientists to do that. We still expect nurses, doctors, psychologists, medical technicians and social workers to traverse complex social problems to talk to their patients in an open and honest way.

Why is it when scientists are speaking to policy makers, clinicians to scientists, policy makers to the public, or any professional to another from another discipline, speciality or division we decide its not critical for them to make the effort?

Why don’t we do the research to support it?

Why is it OK not to do KT because its uncomfortable, awkward, difficult or confusing?

Declining interest, rising demand

It is perhaps for reasons like this that knowledge translation is so poorly understood and taken up as a focus for research. Looking at Google NGram data (which tracks mention of specific topics in books and publications) we see a steady rise in citations until about 2003 followed by a levelling off. Keep in mind that the leveling begins before social media became known. In the years after Twitter, Facebook and YouTube — arguably the most powerful communications media we have for doing knowledge translation widely (but perhaps not deeply) — there is roughly no sharp increase.

Below are the citations for the terms knowledge translation, knowledge exchange, and knowledge integration from 1996 (when the Web first started gaining wide use beyond academia and the military) and 2008, the latest year for which there is available data. Note that the numbers reflect general mentions as a percentage of overall terms, so they are relative, not absolute values.

Figure 1: Google NGram Data for KT, KE & KI: 1996-2008

Is there so much other stuff to talk about in 2013 that the relative importance of knowledge translation is diminished?

A look at Google Trend data using the same terms finds that not only are these concepts not growing, their mention is actually shrinking.

Looking at the three terms we see that all three concepts have declined over time. During these years — 2004-2013 — we saw not only the birth of social media, but the rise of Internet-enabled handheld devices to allow knowledge to be shared anywhere there is a data signal. We now have apps and nearly all of the Internets resources in our pockets and we are seeing a decline in the use of these terms.

Figure 2: Google Trend Data for KT, KE & KI: 1996-2013

Where to?

So to review: We have a body of evidence in KT that is problematic and incomplete at the same time we have a decrease in use of the terms, while at the very same time we have a sharp rise in available tools and technologies to share information quickly and a continued, steady demand for more information to make decisions for health providers, patients, policy makers and insurers.

Yes, the data presented here are not perfect. But does it not make sense that there should at least be some trend upward if knowledge translation is valued? Should we not see some shift to more research, better research evidence, and greater interest given the tools and scope of communications we have through social media?

This begs the question: is knowledge translation in health too important to leave to health professionals?

In future posts this question will be looked at in greater depth. Stay tuned.

* Blog has been updated since original post

The Quality Metric in Education

Posted: January 15, 2013 | Author: Cameron D. Norman | Filed under: education & learning | Tags: cognition, complex adaptive systems, complexity, education, educational design, evaluation, graduate education, innovation, knowledge translation, learning, metrics, psychology, Sir Ken Robinson, systems thinking, teaching, university | 1 Comment »

What goes on the pedestal of learning?

What is quality when we speak of learning? In this third post in series on education and evaluation metrics the issue of quality is within graduate and professional education is explored with more questions than answers about the very nature of learning itself.

But what does learning really mean and do we set the system up to adequately assess whether people do it or not and whether that has any positive impact on what they do in their practice.

What do you mean when you say learning?

The late psychologist Seymour Sarason asked the above question with the aim of provoking discussion and reflection on the nature and possible outcomes of educational reform. Far from being glib, Sarason felt this question exposed the slippery nature of the concept of learning as used in the context of educational programming and policy. It’s a worthwhile question when considering the value of university and professional education programming. What do we mean when we say learners are learning?

The answer to this question exposes the assumptions behind the efforts to provide quality educational experiences to those we call learners. To be a learner one must learn…something.

The Oxford English Dictionary defines learning this way:

learning |ˈlərniNG|

noun

the acquisition of knowledge or skills through experience, practice, or study, or by being taught: these children experienced difficulties in learning | [ as modifier ] : an important learning process.

• knowledge acquired in this way: I liked to parade my learning in front of my sisters.

ORIGIN Old English leornung (see learn,-ing¹) .

This might sufficiently answer Dr Sarason except there is no sense of what the content is or whether that content is appropriate, sufficient, timely or well-supported with evidence (research or practice-based); the quality of learning.

Knowledge translation professionals know that learning through evidence is not achieved through a one-size-fits-all approach and that the match between what professionals need and what is available is rarely clean and simple (if it was, there would be little need for KT). The very premise of knowledge translation is that content itself is not enough and that sometimes it requires another process to help people learn from it. This content is also about what Larry Green argues: practice-based evidence is needed to get better evidence-based practice.

How do we know when learning is the answer (and what are the questions)?

If our metric of success in education is that those who engage in educational programming learn, how do we know whether what they have learned is of good quality? How do we know what is learned is sufficient or appropriately timed? Who determines what is appropriate and how is that tested? These are all questions pertaining to learning and the answers to them depend greatly on context. Yet, if context matters then the next question might be: what is the scope of this context and how are its parameters set?

Some might choose academic discipline as the boundary condition. To take learning itself as an example, how might we know if learning is a psychology problem or a sociology problem (or something else)? If it is a problem for the field of psychology, when does it become educational psychology, cognitive psychology, community psychology or one of the other subdisciplines looking at the brain, behaviour, or social organization? Successful learning through all of these lenses means something very different across conditions.

Yet, consider the last time you completed some form of assessment on your learning. Did you get asked about the context in which that learning took place? When you were asked questions about what you learned on your post-learning assessment:

Did it take into account the learning context of delivery, reception, use, and possible ways to scaffold knowledge to other things?
Did your learner evaluation form ask how you intended to use the material taught? Did you have an answer for that and might that answer change over time?
Did it ask if your experience of the learning event matched what the teachers and organized expected you to gain and did you know what that really was?
Did you know at the time of completing the evaluation whether what you were exposed to was relevant to the problems you needed to solve or would need to solve in the future?
Did you get asked if you were interested in the material presented and did that even matter?
Was there an assumption that the material you were exposed to could only be thought of in one way and did you know what that way was prior to the experience? If you didn’t think of the material in the way that the instructors intended did you just prove that the first of these two questions is problematic?

Years of work in post-secondary teaching and continuing professional education suggests to me that your answer to these questions was most likely “no”, except the very last one.

These many questions are not posed to antagonize educators (or “learners”, too) for there are no single or right answers to any of them. Rather, these are intended to extend Seymour Sarason’s question to the present day and put in the context of graduate and professional education at a time when both areas are being rethought and rationalized.

Learning to innovate (and being wrong)

A problem with the way much of our graduate and professional education is set up is that it presumes to have the answers to what learning is and seeks to deliver the content that fills a gap in knowledge within a very narrow interpretation. This is based on an assumption that what was relevant in the past is both still appropriate now and will be in the future unless we are speaking of a history lesson. However, innovation and discovery — and indeed learning itself — is based on failure, discomfort and not knowing the answers as much as building on what has come before us. There is no doubt that a certain base level of knowledge is required to do most professional and scientific work and that building a core is important, but it is far from sufficient.

The learning systems we’ve created for ourselves are based on a factory model of education, not for addressing complexity or dynamic systems like we find in most social worlds. We do not have a complex adaptive learning system in place, one that supports innovation (and the failures that produce new learning) because:

If you’re not prepared to be wrong, you’ll never come up with anything original. – Sir Ken Robinson, TED Talk 2006

The above quote comes from education advocate Sir Ken Robinson in a humorous and poignant TED talk delivered in 2006 and then built on further in a second talk in 2010. Robinson lays bare the assumptions behind much of our educational system and how it is structured. He also exposes the problem we face in advancing innovation (my choice of term) because we have designed a system that actively seeks to discourage wide swaths of learning that could support it, particularly with the arts.

Robinson points to the conditions of interdisciplinary learning and creativity that emerge when we free ourselves of the factory model of learning that much of our education is set up, “producing” educated people. If we are assessing learning and we go outside of our traditional disciplines how can we assess whether what we teach is “learned” if we have no standard to compare it to? Therein lies the rub with the current models and metrics.

If we are to innovate and create the evidence to support it we need to be wrong. That means creating educational experiences that allow students to be wrong and have that be right. If that is the case, then it means building an education system that draws on the past, but also creates possibilities for new knowledge and learning anchored in experimentation and transcends disciplines when necessary. It also means asking questions about what it means to learn and what quality means in the context of this experimental learning process.

If education is to transform itself and base that transformation on any form of evidence then getting the right metrics to evaluate these changes is imperative and quality of education might just need to be one of them.

Image: Shutterstock

The Knowledge Metric in Education

Posted: January 9, 2013 | Author: Cameron D. Norman | Filed under: education & learning, evaluation, innovation, science & technology, systems thinking | Tags: design, education, educational design, evaluation, higher education, journalism, knowledge integration, knowledge translation, learning, professional education, social innovation, teaching, universities, university | 5 Comments »

Higher education is asking itself some big questions and making substantive changes to the way it sees itself and produces value for society. Education is increasingly being rationalized, which calls into question the metrics that are being used to judge how resources should be allocated. In a previous post, I looked at the jobs metric. Now, it’s time to look at the knowledge metric.

Just the facts

Education writer and teacher Will Richardson‘s TED Book Why School is a provocative read for those connected to teaching or just interested in schooling. While it focuses largely on grade school, the issues are the same for universities and colleges particularly as the primary and secondary students of today are tomorrow’s graduate and professional learners. Richardson questions the role of the school as institution in its current form suggesting that if the status quo — one characterized an information delivery warehouse — is maintained there is little need for schools to exist at all. Yet, if the education within schools is focused on asking better questions and learning when to apply knowledge, not just what knowledge to apply, there is hope.

The current trend in school reform is towards Common Core Standards, which emphasizes specific forms of knowledge, ‘facts’ and asks that students be able to recall such content when required. Under this model, the role of the teacher is one of content manager and facilitator rather than guide or mentor and students are prepped for the tests of their knowledge (memory) rather than be asked to demonstrate its application to anything outside of the test. It is this model that many proponents of online education embrace, because the Internet is a fabulous content delivery system and education can be literally programmed and delivered to students directly without the ‘noise’ that teachers introduce to the signal. Under this model, educational content can be delivered cheaply and widely to support uniform intended effects among learners.

Richardson argues for reforming schools to something closer to the alternative model that was advanced by educational reformer and philosopher John Dewey. Richardson writes:

“In this version of reform, schools and classrooms are seen as nodes in a much larger learning network that expands far beyond local walls. Students are encouraged to connect with others, and to collaborate and create with them on a global scale. It’s not “do your own work,” so much as “do work with others, and make it work that matters.” To paraphrase Tony Wagner, assessments focus less on what students know, and more on what they can do with what they know. And, as Dewey espoused, school is “real life,” not simply a place to take courses, earn grades, amass credits, and compete against others for recognition. There lies the tension.

This second path is simply not as easy to quantify as the first. Developing creativity, persistence, and the skills for patient problem solving, B.S.-detecting, and collaborating may now be more important than knowing the key dates and battles of the Civil War (after all, those answers are just a few taps on our phones away), but they’re all much more difficult to assign a score to. I’m not saying that a foundation of content knowledge isn’t still important. To communicate, function, and reason in the world, students need effective reading and writing skills, as well as a solid foundation in math, science, history, and more. But I’m convinced we must revise the overreaching coursework requirements we place on students — requirements created at a time of scarcity, by the way. And we desperately need to revisit the thinking we’ve developed around assessment that, as Harvard researcher Justin Reich says, “optimizes the measurable at the risk of neglecting the immeasurable.””

Facts vs Problems

The knowledge metric is flawed because it assumes that content solves problems. It also presumes that the curriculum teaches the right knowledge for the right problems and that those problems can be known in advance. Let’s look at these.

One need only look to cigarette smoking as an example of how knowledge alone doesn’t always solve or prevent problems. One would be hard pressed to find anyone over the age of five who doesn’t know that sticking a lit tube of anything in their mouth and sucking on it isn’t at least somewhat unhealthy (and most know it is very unhealthy). An individual’s knowledge of smoking’s effects on physical health may not be complete, but it is often sufficient to inform the decision to quit or not start the unhealthy habit. And yet, citizens in highly educated countries like the United States, Canada and the U.K. smoke more than 1000 cigarettes per year per capita (and over 2700 per capita in places like Russia). These are not countries lacking in information on tobacco and health.

Using students’ ability to recall content makes the presumption that what is contained in a curriculum is what they need to know when they leave their program of study (at least as a start). While it may be somewhat true for students in the humanities and languages, it becomes highly problematic for those in dynamic fields or emergent areas of practice, which is becoming more normal than rare. There is no doubt that a corpus of key concepts, skills and ‘facts’ is useful, but the manner in which this knowledge can and may be applied is changing dramatically. For example, social media has upended communications in ways that very few health professionals are trained for. Journalists are particularly aware of the role that Twitter and related tools have had on their profession.

It also presumes that the content itself is relatively static. Certainly, curriculum renewal is something that most learning institutions engage in, but the primacy of content itself as the driver of education also assumes that the foundation for that knowledge is solid and can be applied today in the manner it was applied yesterday. In dynamic conditions, that isn’t often true. Further, the relevance of knowledge is framed by the problems to which that knowledge is applied. Genetic information, for example, can be incredibly useful when framed against tests that have high confidence, predictability and value to people, yet without such a context it is largely useless to those non-scientists who have it.

Areas of social innovation — which are expanding dramatically in number and scope — illustrate the problem of changing context well. This is a field characterized by problems, problem solving and novelty (which is what innovation is all about). Standard approaches don’t apply easily or at all when we are faced with high levels of novelty. Thinking and re-thinking the problem frame, knowing what to find, where to find it, and the skills to integrate relevant knowledge together is something that is not captured in the knowledge metric. Yet, it is those skills that will lead innovation. Knowledge translation professionals know this and so do knowledge brokers.

Are we designing our educational programming to advance on the kind of design issues of problem framing, finding and solving that our world is facing? Or are we simply taking content that can be obtained through books, the Internet and other materials, repackaging it and creating expensive warehouses of information that take learners out of the world and out of context in the process?

I don’t suggest that universities and continuing education programs stop delivering content, but if knowledge is the metric by which they are judging their success then it behooves educational administrators and funders to justify why they can do it better than other tools. What made sense when content was a rare commodity makes little today when it is overflowing in abundance for little or no cost. Universities and post-graduate training programs have an opportunity to re-imagine education and have the tools to do it in a way that makes learning more powerful and relevant for the 21st century should they choose to change their metrics of success.

Designing education

How might we take the enormous talent trust that exists among university faculty (and their students) who co-locate (physically, virtually or in some combination) in a school and develop the skills to not only address problems of today, but prepare everyone for possible challenges in the future?

How might we integrate what we know, identify the knowledge we need, and create systems to take advantage of the talent and creativity of individuals to make universities, colleges, and post-professional training venues for innovation and inspiration rather than just content delivery vehicles?

What kind of metrics do we need to evaluate this kind of education should we choose to develop it?

These are questions whose answers might yield more learning than those focused on what knowledge students have when they graduate.

___

Image source: Shutterstock.

The Fourth Estate of Health and Medicine

Posted: December 11, 2012 | Author: Cameron D. Norman | Filed under: knowledge translation, public health, science & technology, social media | Tags: Andre Picard, blogging, Darwin the monkey, evidence, health evidence, health reporting, journalism, Julia Belluz, knowledge translation, Malcolm Gladwell, media, Mitch Waldrop, news, newspapers, public health, science, social media, Stan Glantz, Steven Johnson, the fourth estate, tobacco control | 2 Comments »

Journalists occupy an important, yet often unacknowledged, role in the health system by providing a dispassionate account of the system’s strengths, weaknesses, and opportunities to the public. It is through journalists that much of the research we scientists and practitioners produce gets communicated to the audiences likely to use them. This fourth estate is also a place where hard questions can be asked and answered, holding governments, business and the health system itself to account because journalists operate apart from this space, unlike scientists and clinicians. We are at risk of losing this and it’s time to consider what that means for our collective health and wellbeing.

Disrupted Media

The news business is going through a massive upheaval, part of a larger overall disruption in media. Many newspapers are reducing the size of their print offerings, publishing less frequently or ceasing operations altogether.

This reduction in the capacity and size of the fourth estate begs two simple questions: Who will hold health scientists, clinicians, pharmaceutical companies, health product manufacturers, and policy makers to account? and who will tell the stories of science, health and medicine in public?

While we have some activist academics doing great work on influencing broader audiences like policy makers, they are exceptions not the norm. Stanton Glantz, a major tobacco control champion from UCSF who taken to blogging as a means of communicating to professionals and the public directly, is one of these such people. But Stan is atypical and holds a tenured position at a major university, something he’s acknowledged protected him when pursuing issues of evidence withholding from the tobacco companies in the 1990′s and beyond. Many faculty (particularly younger ones) are not this secure and even fewer independently funded scientists are. Academia is changing and not in ways that favour security and stability, which has implications for the kind of stories that get told.

Journalists have traditionally relied on protection from their publisher or producer under the name of journalistic freedom (the fourth estate) as a key pillar of their profession. It’s hard to imagine the Watergate scandal coming to light had Bob Woodward, Carl Bernstein and the other reporters working for the Washington Post, Time Magazine and New York Times not had the resources, stability and support provided by their newspapers . But what happens when these resources are no longer available or there are no institutions to support journalists in serving as watchdogs to hold people or institutions to account for what they do and don’t do?

Are ‘Monkeys in Coats’ A Healthy Story?

It’s been suggested that the Internet will take care of this. Citizen journalists, armed with camera-laden handsets connected to social media will fill the news gap. For example, it was citizens, not journalists, who first captured the story of Darwin the monkey, dressed in a shearling coat, walking around an Ikea parking lot in Toronto that went viral on a global scale on December 10, 2012. This is great for those interested in simian fashions and retail adventures, but the reason it was captured was because the story was obvious and in the face (or at the ankles) of those who told it. (For those of you not familiar with Toronto, coat-wearing monkeys are not typically seen at shopping centres or anywhere around town for that matter.)

Health and medicine is not the same as monkeys wearing coats (no matter what kind of joke you want to make). There is nuance, debate and reason that requires sustained attention and focus that someone with an iPhone and Twitter account is less likely to convey. Reasoned arguments for citizen journalism’s potential suggest it can complement the work of traditional journalism, not replace it. Yet, is this belief in one form (citizen journalism) undermining support for the other (traditional journalism) and serving as a fix that ultimately fails? If free-and-easy content is available, how likely are publishers willing to pay for professional work? Particularly if the choice of stories of one group (e.g., monkeys in coats) are more likely to garner the kind of attention that drives advertising than that of another (e.g., health care financing). Only one of these stories will impact our collective health.

Why does this matter? Trained journalists are required to be good communicators to a broad audience, scientists are not. Clinicians are slightly better, but decades of research has shown it is still highly problematic across areas of practice. This will not be solved overnight, if at all. Scientists and clinicians have told me they are already burdened with enough job expectations and adding knowledge translation skills to that list is asking too much.

As I have argued previously, there is a valued place for synthetics in research: those are who are good at taking ideas and weaving them together into an accessible narrative. Journalists are ideally suited to play or support this role. They do the job that many scientists can’t or won’t do and have better to tools, skills and strategies to do it. They write in a style that is suited to broad audiences in a way that suit those audiences’ needs, not what funders, disciplinary traditions, universities, or scientific peers demand (without evidence that those methods of communication are effective). There are reasons why journalists assess the reach of their work in the thousands and social scientists in the dozens (by citations in their field of practice).

Going Deeper to See Clearer

Although we have more information about health available to us than ever before, this may not be healthy for patients. The potential for those uninformed about medical diagnostics, evidence, and the nature of health itself to make poor choices based on incomplete, incorrect or overwhelming information is high. Further, without the kind of dispassionate examination of evidence in a synthetic manner that is tied to the way in which that evidence is expressed in the world through public opinion, policy making and healthcare practices, we lose a major accountability mechanism and means of informing public discourse.

In October I co-delivered a workshop on health evidence for students at the University of Toronto with the 2012 Hancock Lecturer and journalist Julia Belluz. Julia writes the Science-ish blog for Macleans Magazine and is an Associate Editor with the Medical Post. Julia`s lecture was on the role that social media plays in our health system and how its power to leverage the attention of the masses — for good and ill — is shaping the public understanding of health and medicine often in the absence of evidence for effects of conditions, processes, and practice. The lecture is summarized online on Science-ish beginning here.

Reading through the lecture notes one sees a depth of study that would be unlikely to be found anywhere within the formal health system. The reasons are that it blends evidence with commentary, observation with carefully selected sources, and takes a perspective that seeks to inform a wide, not narrow audience in both practical and intellectually stimulating ways. Taken together, this is a collection of activities that are not within the scope of practice for scientists and practitioners. There are reasons why the greatest contributors to public discourse on many scientific issues has come from journalists, not the scientists who generate the research. They tell the story better.

Malcolm Gladwell, Steven Johnson, Mitch Waldrop, Julia Belluz, Andre Picard and others are a big part of the reasons most of the those who vote to support funding of science, who donate to research-related causes, and fight for policies to keep us healthy know of the research that backs those ideas up.

Imperfect as journalism is, it serves the public when done with integrity. It’s worth spending some time considering what can be done to support the fourth estate so it supports us.

Photo credit: DBduo Photography on Flickr used under Creative Commons Licence.

Evaluating Social Innovation For Social Impact

Posted: November 15, 2012 | Author: Cameron D. Norman | Filed under: complexity, design thinking, education & learning, emergence, evaluation, knowledge translation, systems thinking | Tags: design, design thinking, developmental design, developmental evaluation, evaluation, evidence, Helsinki Design Lab, knowledge exchange, knowledge translation, research design, research methods, social impact, social innovation | 1 Comment »

How do the innovation letters line up?

Earlier this week I has the pleasure of attending talks from Bryan Boyer from the Helsinki Design Lab and learning about the remarkable work they are doing in applying design to government and community life in Finland. While the focus of the audience for the talks was on their application of design thinking, I found myself drawn to the issue of evaluation and the discussion around that when it came up.

One of the points raised was that design teams are often working with constraints that emphasize the designed product, rather than its extended outcome, making evaluation a challenge to adequately resource. Evaluation is not a term that frequents discussion on design, but as the moderator of one talk suggested, maybe it should.

I can’t agree more.

Design and Evaluation: A Natural Partnership

It has puzzled me to no end that we have these emergent fields of practice aimed at social good – social finance and social impact investing, social innovation, social benefit (PDF)– that have little built into their culture to assess what kind of influence they are having beyond the basics. Yet, social innovation is rarely about simple basics, it’s influence is likely far larger, for better or worse.

What is the impact being invested in? What is the new thing being created of value? and what is the benefit and for whom? What else happened because we intervened?

Evaluation is often the last thing to go into a program budget (along with knowledge translation and exchange activities) and the first thing to get cut (along with the aforementioned KTE work) when things go wrong or budgets get tightened. Regrettably, our desire to act supersedes our desire to understand the implication of those actions. It is based on a fundamental idea that we know what we are doing and can predict its outcomes.

Yet, with social innovation, we are often doing things for the first time, or combining known elements into an unknown corpus, or repurposing existing knowledge/skills/tools into new settings and situations. This is the innovation part. Novelty is pervasive and with that comes opportunities for learning as well as the potential for us to good as well as harm.

An Ethical Imperative?

There are reasons beyond product quality and accountability that one should take evaluation and strategic design for social innovation seriously.

Design thinking involves embracing failure (e.g, fail often to succeed sooner is the mantra espoused by product design firm IDEO) as a means of testing ideas and prototyping possible outcomes to generate an ideal fit. This is ideal for ideas and products that can be isolated from their environment safely to measure the variables associated with outcomes, if considered. This works well with benign issues, but can get more problematic when such interventions are aimed at the social sphere.

Unlike technological failures in the lab, innovations involving people do have costs. Clinical intervention trials go through a series of phases — preclinical through five stages to post-testing — to test their impact, gradually and cautiously scaling up with detailed data collection and analysis accompanying each step and its still not perfect. Medical reporter Julia Belluz and I recently discussed this issue with students at the University of Toronto as part of a workshop on evidence and noted that as complexity increases with the subject matter, the ability to rely on controlled studies decreases.

Complexity is typically the space where much of social innovation inhabits.

As the social realm — our communities, organizations and even global enterprises — is our lab, our interventions impact people ‘out of the gate’ and because this occurs in an inherently a complex environment, I argue that the imperative to evaluate and share what is known about what we produce is critical if we are to innovate safely as well as effectively. Alas, we are far from that in social innovation.

Barriers and Opportunities for Evaluation-powered Social Innovation

There are a series of issues that permeate through the social innovation sector in its current form that require addressing if we are to better understand our impact.

Becoming more than “the ideas people”: I heard this phrased used at Bryan Boyer’s talk hosted by the Social Innovation Generation group at MaRS. The moderator for the talk commented on how she had wished she’d taken more interest in statistics in university because they would have helped in assessing some of the impact fo the work done in social innovation. There is a strong push for ideas in social innovation, but perhaps we should also include those that know how to make sense and evaluate those ideas in our stable of talent and required skillsets for design teams.
Guiding Theories & Methods: Having good ideas is one thing, implementing them is another. But tying them both together is the role of theory and models. Theories are hypotheses about the way things happen based on evidence, experience, and imagination. Strategic designers and social innovators rarely refer to theory in their presentations or work. I have little doubt that there are some theories being used by these designers, but they are implicit, not explicit, thus remaining unevaluable and untestable or challenged by others. Some, like Frances Westley, have made theories guiding her work explicit, but this is a rarity. Social theory, behaviour change models and theories of discovery beyond just use of Rogers’ Diffusion of Innovation theory must be introduced to our work if we are to make better judgements about social innovation programs and assess their impact. Indeed, we need the kind of scholarship that applies theory and builds it as part of the culture of social innovation.
Problem scope and methodological challenges with it. Scoping social innovation is immensely wide and complicated task requiring methods and tools that go beyond simple regression models or observational techniques. Evaluators working social innovation require a high-level understanding of diverse methods and I would argue cannot be comfortable in only one tradition of methods unless they are part of a diverse team of evaluation professionals, something that is costly and resource intensive. Those working in social innovation need to live the very credo of constant innovation in methods, tools and mindsets if they are to be effective at managing the changing conditions in social innovation and strategic design. This is not a field for the methodologically disinterested.
Low attendance to rigor and documentation. When social innovators and strategic designers do assess impact, too often there is a low attention to methodological rigor. Ethnographies are presented with little attention to sampling and selection or data combination, statistics are used sparingly, and connections to theory or historical precedent are absent. Of course, there are exceptions, but this is hardly the rule. Building a culture of innovation within the field relies on the ability to take quality information from one context and apply it to another critically and if that information is absent, incomplete or of poor quality the possibility for effective communication between projects and settings diminishes.
Knowledge translation in social innovation. There are few fora to share what we know in the kind of depth that is necessary to advance deep understanding of social innovation, regularly. There are a lot of one-off events, but few regular conferences or societies where social innovation is discussed and shared systematically. Design conferences tend towards the ‘sage on the stage’ model that favours high profile speakers and agencies, while academic conferences favour research that is less applied or action-oriented. Couple that with the problem of client-consultant work that is common in social innovation areas and we get knowledge that is protected, privileged or often there is little incentive to add a KT component to the budget.
Poor cataloguing of research. To the last point, we have no formalized methods of determining the state-of-the-art in social innovation as research and practice is not catalogued. Groups like the Helsinki Design Lab and Social Innovation Generation with their vigorous attention to dissemination are the exception, not the rule. Complicating matters is the interdisciplinary nature of social innovation. Where does one search for social innovation knowledge? What are the keywords? Innovation is not a good one (too general), yet neither is the more specialized disciplinary terms like economics, psychology, geography, engineering, finance, enterprise, or health. Without a shared nomenclature and networks to develop such a project the knowledge that is made public is often left to the realm of unknown unknowns.

Moving forward, the challenge for social innovation is to find ways to make what it does more accessible to those beyond its current field of practice. Evaluation is one way to do this, but in pursuing such a course, the field needs to create space for evaluation to take place. Interestingly, FSG and the Center for Evaluation Innovation in the U.S. recently delivered a webinar on evaluating social innovation with the principle focus being on developmental evaluation, something I’ve written about at length.

Developmental evaluation is one approach, but as noted in the webinar : an organization needs to be a learning organization for this approach to work.

The question that I am left with is: is social innovation serious about social impact? If it is, how will it know it achieved it without evaluation?

And to echo my previous post: if we believe learning is essential to strategic design we must ask: How serious are we about learning?

Tough questions, but the answers might illuminate the way forward to understanding social impact in social innovation.

* Photo credit from Deviant Art innovation_by_genlau.jpg used under Creative Commons Licence.

Jonah Lehrer and the Crisis of Knowledge Synthesis

Posted: August 22, 2012 | Author: Cameron D. Norman | Filed under: complexity, innovation, knowledge translation, psychology | Tags: complex adaptive systems, complexity, Jonah Lehrer, journalism, knowledge translation, Malcolm Gladwell, science, science writing, Steven Johnson, tipping point | Comments Off

Jonah Lehrer is/was as big as it gets in science writing and two weeks ago proved the adage that the higher one climbs the farther the fall after admitting to some false content in his stories. This is bad news for him, but may be much worse for all of us interested in making science and innovation knowledge accessible for reasons that have as much to do with the audience as it does the message and messenger.

Jonah Lehrer was one of our most prolific and widely read science writers until he admitted fudging some quotes about Bob Dylan in his new book, Imagine, which looks at the process of discovery, creativity and innovation. The discovery by fellow journalist (and fervent Bob Dylan fan) Michael Moynihan set off a wave of reflections and investigations of Lehrer’s work revealing passages in the book (and other pieces) that had been reused from his other writings without proper self-attribution and sparking questions about the integrity of the author’s entire body of work. The “fall of Jonah Lehrer” was big news at a time when the London Olympics were dominating most of the media’s attention.

This case is a testament to the wide appeal that Lehrer’s work had beyond the usual ‘science geeks’ while illustrating the power of the internet to enable the kind of curation and investigation to support on and offline fact checking. But what it spoke to most for me is the role

The Writer and his Craft

Much digital type has been spent on the Lehrer incident. Search Google and you’ll find dozens of commentaries looking at how things transpired and how Lehrer ironically succumbed to the cognitive biases he wrote about.

Roxane Gay, writing in Salon, took a gendered approach to the issue and questioned whether our fascination is less with the science and more about the ‘young male genius’. Lehrer’s youth was something she saw as critical to amplifying the fascination with his work. She writes:

When young people display remarkable intelligence or creativity, we are instantly enamored. We want or need geniuses to show us the power and potential of the human mind and we’re so eager to find new people to bestow this title upon that the term and the concept have become quite diluted.

I agree with her on the point about our desire to over-inflate the accomplishments of youth (as if we are *amazed* that any of them could possibly do anything brilliant, which is as offensive to them and it is to older people), although a careful look at Lehrer’s articles and much of the press around his work suggests that he was much less a focus of the attention than his ideas.

John McQuaid‘s take on the affair in Forbes speaks to a larger issue:

Call it “Gladwellization.” It’s not just lucrative, but powerful: your ideas (or rather, the ideas you’ve turned into compelling anecdotes for a popular audience) can influence everything from editorial choices across the publishing world to corporate management and branding strategies.

But with this comes mounting demands to produce, and to recycle. You have to be prolific, churning out longer pieces that give your insights some ballast, and brilliant, bite-sized items. And yet you can’t be too new either: people want to hear what you’re already famous for. In this cauldron of congratulation and pressure for more and more, it’s not hard to see how standards might erode, how the “ideas” might become more important than doing the necessary due diligence to make sure they sync with reality.

‘Snappy Science’ and Synthesis

Innovation is about ‘new’ and there are good reasons why its a challenge to get the message out that this ‘new’ can be adapted, small, and unsexy and still make a large difference in the long run instead of big, bold and transformative right away. We are in an age of selling “snappy science” and it says more about the media and audiences than the authors and scientists producing the original work.

This snappy, bite-sized science might sell books and make for great TED talks, but it is a misrepresentation of what we actually know and do as scientists. Rarely does a single finding lead to a solution, rather it is an amalgam of discoveries small and large brought together that gets us to closer to answers. Synthesis is the driver of change and synthesis is what journalists do particularly well. Malcolm Gladwell, Steven Johnson and Jonah Lehrer are among the best synthesizers out there and I would imagine (no pun intended) that they contribute to more to public and professional understanding of social innovation than all of the original-sourced scientific knowledge on the subject combined.

When I hear Malcolm Gladwell cited as an original source in serious discussions with colleagues on scientific matters, I realize we have a problem…and an opportunity. Gladwell’s writings popularized the concept of tipping points, but his work is based on a wealth of scientific data on complex systems. They are not his original ideas, but they are his syntheses and (sometimes) his interpretations. This is important work and I am not taking anything from anyone who makes science data digestible and accessible, but it is not the original science.

That Jonah Lehrer is as well known as he is tells me that there is an appetite for science and I’ll freely admit to using his work (and that of the other authors I’ve mentioned) to inform what I do in a general sense. It is good work, however I also acknowledge that I have the scientific training to know how to go beyond the initial articles to critically appraise the information, place it in context, and I have the resources to go to the original sources in academic journals. Most people (professionals and lay people) do not. This access is going to decrease as resources shrink.

It is for this reason that synthetic work is so important. My Twitter feed often is filled with references to such synthetic work, rather than original works of research because I aim to fill role that is somewhere between journalism and the science of design, systems and psychology. I am not a pure science blogger, nor am I speaking to the lay public, but rather other professionals seeking to enrich their knowledge base. That is a role I’ve created for myself, largely because there is a high demand and low supply.

We have a need for synthesis and a demand for it, but little acknowledgement of the value of this role in professional scientific circles. Yet, when we leave journalists to do the work for us, we allow a different system to take charge. John McQuaid ended his article with this caution:

Book publishers don’t do fact-checks, so there’s no fail-safe, just the conscience of the writer. Reach that point, and all is lost.

Filling the gap, meeting a need and shooting the messenger

Journalists like Johnson, Gladwell and Lehrer fill a gap, which is why I am saddened by the loss of one of them and angry at what has transpired. While there is no doubt that Lehrer made mistakes, they were of a rather minor nature in the grand scheme of things. Synthetic work is designed to provide a big picture overview, not guide microscopic decisions. I would like people to read Lehrer and learn about the creative process and the role of neuroscience in making our lives better, to appreciate systems thinking and decision making because of Malcolm Gladwell, and see innovation, emergence and discovery in new ways because of writers like Steven Johnson.

Yet, when we seek more and more from these authors, we might get less and less. This is what happened to Jonah Lehrer. As more people found themselves drawn to his work, the pressure grew for doing more, faster and getting that ‘snappy science’ out the door. GOOD magazine in the ‘tyranny of the big idea‘ goes further:

The problem is that it’s unreasonable to expect that every new piece of media should upend conventional wisdom or deliver a profound new insight. To think that Jonah Lehrer could expose an amazing new facet of human psychology every week, in 1,000-odd words no less, is ludicrous. There are only so many compelling, counterintuitive, true ideas out there.

But the demand for them doesn’t abate. That’s why you see so many science writers talking about the same handful of studies (the Stanford prison experiment, the rubber hand illusion, Dunbar’s number, the marshmallow test) over and over. That’s why you see pop economists who should know better creating flimsy and irresponsible contrarian arguments about climate change for shock value. That’s why you get influential bloggers confessing they’re only 30 percent convinced of their own arguments but “you gotta write something.” That’s why the#slatepitches meme hits home.

Search Censemaking and you’ll find many of these topics not just because they are punchy, but because they are useful.

I hope we haven’t lost Jonah Lehrer as a voice just as I hope more people stop putting writers like him on a pedestal, where they don’t belong (nor do the scientists who produce the research). Synthesis is about bringing ideas together to produce innovative insights that often lead to bigger conversations about how to socially innovate. Synthesis is bigger than science, but dependent on it. It means paying attention to parts and wholes together and is the epitome of systems thinking in knowledge work.

It also means taking responsibility as knowledge producers and consumers and be wary of shooting the messengers while asking more from the messages they deliver.

Unless we are prepared to give people time to search, appraise and synthesize research on their own — and train them to make informed choices — the role of synthesizers – professional, journalistic, or otherwise – will become more important than ever.

Photo from Wikimedia Commons and is used under licence.

Too Much Social Media, Not Enough Social Message

Posted: July 30, 2012 | Author: Cameron D. Norman | Filed under: business, marketing, social media | Tags: Cluetrain manifesto, communication, complexity, Edmund Snow Carpenter, emergence, Facebook, idea markets, knowledge integration, knowledge translation, learning, markets, Marshall McLuhan, media ecology, social media, Twitter, Web 2.0, YouTube | 1 Comment »

Social media is any networked information technology, tool or platform that derives its content and principal value from user engagement and permits those users to interact with that content. But last time I checked (in), the content stream being produced through my media stream was becoming a lot less social (Web 2.0) and more of a throwback to the media of old (Web 1.0); the implications could be considerable for those wishing to reach new audiences or create them in the first place.

It’s been a rough ride for social media companies. On Friday Facebook’s shares were at a record low since their IPO a couple months ago. Last month, Twitter provoked much concern after dropping its partnership with LinkedIn as part of its desire to have greater control over its messaging, prompting concern that Twitter might end up closing itself off to 3rd party applications like EchoFon, HootSuite and Tweetbot to ensure quality. This desire for tailoring and control of messages and trends has prompted some to suggest that Twitter may be ruining itself in the process.

The issue is not just one of control, but of a disrespect for the complexity and conversation that makes social media attractive to its users. In short: it’s about the social, not the media.

Social media, non social content

Scanning through my Facebook page its easy to see why their stock is dropping and will continue to do so. In their quest to justify their valuation, Facebook needs to find ways to make money from what people post and pictures of people’s kids, quips about daily hassles and joys, sharing cat videos, and posting check-ins at a local restaurant aren’t enough to justify a $100bn valuation. To do this, they need advertising dollars and deals with game makers and app developers to drive revenue up. Aside from the possibility of games, there is little social about advertising, no matter what kind of spin is offered.

Within a year my Facebook page has gone from a loose collection of social miscellany from friends and family to a steady stream of non-social junk with advertisements in the form of page updates, news stories that require me to accept an app that sends me more ads, and a litany of non-essential information.

The signal to noise ratio has officially flipped from more noise and less signal.

Bit by bit, Facebook is choking its users to death with ephemera and it would not surprise me if in two years we refer to it as we do MySpace today. YouTube is also running perilously close to offering too much media with not enough message as users increasingly have to sit through advertisements or click on banner ads before accessing content. News sites like the Globe and Mail will run a 30 second advertisement before allowing you to see a 20 second news clip, a 150% advertisement to content ratio on some stories.

I remember a few years ago when my email took the same turn. Now, probably 75 per cent of my received (non-spam!) email goes unread and is immediately deleted on sight. This isn’t necessarily spam, much of it is bacn, the kind of updates that I might have subscribed to voluntarily or I receive as part of a professional membership or affiliation. However, it’s severely disabled email’s potential and is now a ‘necessary evil’ instead of a useful tool I welcomed having in my toolkit.

Speaking to colleagues, it is not unreasonable to hear of people receiving messages in the hundreds each day and spending more than 3 hours per day just managing that content alone. How is this helping us communicate better? To learn?

This is one gigantic distraction and is not proving useful to improving our communications or helping us integrate the knowledge we receive and already have. Some claim that the era of big data will allow advertisers to target their ads with such exceptional focus and appropriateness that they will be serving us as much as we are needed to service them. I somehow doubt that.

From Web 2.0 back to 1.0

Consider the definition of what social media is on Wikipedia (as Web 2.0):

Web 2.0 is a concept that takes the network as a platform for information sharing, interoperability, user-centered design,^[1] and collaboration on the World Wide Web. A Web 2.0 site allows users to interact and collaborate with each other in a social media dialogue as creators (prosumers) of user-generated content in a virtual community, in contrast to websites where users (consumers) are limited to the passive viewing of content that was created for them. Examples of Web 2.0 include social networking sites, blogs, wikis, video sharing sites, hosted services, web applications, mashups and folksonomies.

When my social media stream is filled with promoted tweets, sponsored posts, ‘like’ requests on advertisements or updates from projects, I lose the social and just end up with media.

Social media is at its best when it is a conversation. Sometimes the conversation involves a lot of talking on one side, but there is a genuine back-and-forth, an unpredictability to it, and a non-linear dynamic that makes it interesting. Straight-to-viewer messages that offer no ways to engage except to watch, click off or ‘like’ don’t make for a conversation.

Imposing Structure and Losing Complexity

In trying to turn a setting where complexity, emergence and non-linearity come alive and work to create conversation, social media property managers are stifling the very thing that makes their tools and platforms so attractive. Creativity is born from serendipity and diverse connections. In imposing structures that remove or highly limit this potential for discovery by adding unnecessary noise, we are a risk of losing some of the best tools for idea testing, discussion, and knowledge translation we have ever known by reducing the opportunities for serendipity.

It is the commercial drive that contributed to bringing these tools in the first place, however that drive can lead to blindness creating an Internet ivory tower rather than a true marketplace of ideas as advocated in the Cluetrain Manifesto, which looked at how markets operate as innovation hubs by promoting conversations.

From markets to artists, the messages that are created by media are related to the media itself. Marshall McLuhan knew that and so did his peer, Edmund Snow Carpenter. Mathematician-artist a Youtube video maker vihart knows this too and spoke to Carpenter’s thesis in a terrific short video below.

In critiquing the push for standard ‘best practices’ in social media, vihart (and Carpenter, by posthumous extension) point to the ways in which the traditional media formats that advertisers desperately wish to use to contain your attention (and limit your feedback) is exactly the opposite of the new media.

Taken from the forward of Carpenter’s book, They Became What They Beheld, (and explicated beautifully by vihart) come some rules of communication commonly pursued by traditionalists and reasons why we shouldn’t pay attention. These rules as noted by Carpenter are:

1. Know your audience and address yourself directly to it

2. Know what you want to say and say it clearly and fully

3. Reach the maximum audience by using existing channels

Whatever sense this may have made in world of print, it makes no sense today. In fact, the reverse of each rule applies.

If you address yourself to an audience, you accept at the outset the basic premises that unite the audience. You put on the audience, repeating cliches familiar to it. But artists don’t address themselves to audiences; they create audiences. The artist talks to himself out lout. If what he has to say is significant, others hear & are affected.

The trouble with knowing what to say and saying it clearly and fully, is that clear speaking is generally obsolete thinking. Clear statement is like an art object: it is the afterlife of the process which called it into being. The process itself is the significant step and, especially at the beginning, is often incomplete and uncertain.

The problem with full statement is that it doesn’t involve: it leaves no room for participation; it’s address to consumer, not co-producer.

One is left watching this video with the question: what happens when social media has too much media, not enough message?

Have We Turned the Page on Social Science Research for Health?

Posted: May 15, 2012 | Author: Cameron D. Norman | Filed under: knowledge translation, science & technology, social systems, systems science | Tags: funding, health promotion, knowledge translation, public health, research, research funding, science policy, social science | 2 Comments »

Turning the Page on Social Science and Health Research

Over the last two weeks social science researchers across Canada began receiving the decisions from last autumn’s competition for a Social Science and Humanities Research Council (SSHRC) funding award. SSHRC is the principal funder of social science research in Canada, although notably is not in the business of funding heath-related research, which is supposed to be funded by the Canadian Institutes for Health Research (CIHR). [Full disclosure: I currently hold grants from both of these organizations]. The problem is that CIHR was born from a policy and programming body and the former Medical Research Council and has a rather awkward relationship with social science research given its medical focus. It has funded some social science programs, but not in a manner that has enabled social scientists to comfortably explore the range of issues that they might have under traditional SSHRC funding programs, particularly when social issues are not always obviously health issues (e.g., poverty, education) and can easily be dismissed as not being relevant in spite of the evidence that they are. Yet, SSHRC has decided to forgo any funding of health-related projects due in part to the absence of funding to support it when there are presumably options through CIHR or the disease-specific health charities like the Canadian Cancer Society, the Lung Association and others.

Yet, these options are not suitable. In a manifesto entitled “The end of medical anthropology in Canada” a group of leading social scientists painted the picture of the situation in grim terms in University Affairs. Although medical anthropology is the focus of the piece, the authors might as well be speaking for social sciences in general:

Health is inherently social and cultural. SSHRC has always understood this; CIHR, we fear, does not. We face the possible extermination of one of the most vibrant, high-demand and policy-relevant health disciplines, the only scholarly field that places culture at the centre of the analysis of health and that characteristically does so in both national and international contexts. In a multicultural, settler society with a substantial aboriginal population, and in a world where health is at the core of developmental, political and social issues in so many countries, where Canada otherwise wishes to have an impact, does this make any sense?

This brings me back to the beginning of this post and the announcement of the results of the last competition. Looking at the funding numbers released by SSHRC, a discouraging picture emerges. In 2011-12, 37 per cent of all applications in the open competition were deemed fundable, yet only 22.5 per cent were funded. These numbers are similar t0 2010-11, when 36 per cent were deemed fundable and 22 per cent were funded. What is not mentioned in these numbers was the level at which these grants were funded in the first place. I am a 2010-11 recipient of funding from SSHRC — meaning my grant proposal was within the top 22 per cent of all applications for that year — and the amount I received was approximately half of what I requested. That means that I had to take half of my budget and throw it away. So yes, I was successful providing I did either half of the research or found money elsewhere. I did the latter and my pocketbook is none the better for it.

Consider the implications of this change in funding. With one in five projects funded and many of those that are funded at levels well below what was requested the motivation for researchers is one of the first casualties. Researchers know that funding is tight and that it is highly competitive, but few alternative sources for research grants that lay outside of specific disease-focused areas, social scientists young and old are faced with little option. This creates another set of affected parties: students and trainees. Research funding not only supports the scientists themselves in many cases (see my previous posts on this), but those seeking to become scientists themselves or those who seek to get better acquainted with research. In health sciences and policy, this means just about everyone enrolled in such programs.

Now consider all of this in light of a trend towards increasing graduate education numbers. At the academic institution I am affiliated with (like many of its peers), the enrolment numbers are set to nearly double across many of the professional programs associated with health practice and policy in the coming years. Increased demand for training opportunities from the public has created a means for universities to cash in. Of course, what these students will do when they get there is unclear (let alone when they graduate), but it cannot be much in the way of research — at least as it pertains to social science and health. The funding is simply not there to support the kind of broad-based inquiry into the social factors that influence health, illness and well-being anymore. We have, as I call it, reached ‘the Turn’.

The Turn is that point where the system changes irrevocably towards a new direction. It is like a ‘tipping point‘. Dwindling numbers of social scientists working from funding from an institutional budget (e.g., tenure-stream faculty positions) + a doubling of the student cohort * half of the research dollars makes for rather toxic math. The Turn will fundamentally shape the way social science inquiry is done and the kind of questions that get asked. As question foci change, the quality of the research shifts, and the depth of inquiry is reduced, so too will the real impact that social science has on our health.

The gap between what we know, what we do, and what we can do to prevent illness, treat sickness, and promote well-being will grow.

Anecdotally speaking, this trend is not unique to the social sciences, but it is amplified in this domain. Social sciences in Canada and abroad are consistently funded at lower levels than that of basic research (see here for a starting point). But what is interesting is that many of the problems that we face within health require social science knowledge and research to address and social science — from knowledge translation, social network studies, technology adoption, innovation, management, to policy implementation and beyond .

Prevention of disease and chronic illness is often a social phenomenon (e.g., hand washing). Even the act of taking the best of basic science and translating it into practice or policy options (or other scientific research) is a social act that draws on social science research to execute. Social determinants of health are social in nature and require social science to understand their impact. Designing the policy and programmatic interventions that support creating a healthier society also falls to social science research and practice.

What will our health landscape look like without the ability to take what we know and translate it into action? Worse yet, what if we simply are unable to even know what to do because the research and evidence isn’t there in the first place to translate into anything? Without another turn towards something more positive in our research support, we are about to find out.

* Photo Turn the Page by Miaboas used under Creative Commons License from Deviant Art.

Censemaking

Contemplating complexity, design and innovation for health

Design (re)Thinking Health Systems

The Quality Metric in Education

What do you mean when you say learning?

How do we know when learning is the answer (and what are the questions)?

Learning to innovate (and being wrong)

Jonah Lehrer and the Crisis of Knowledge Synthesis

The Writer and his Craft

‘Snappy Science’ and Synthesis

Filling the gap, meeting a need and shooting the messenger

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Contemplating complexity, design and innovation for health

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Translating knowledge

The value of storytelling

Valuing knowledge translation

Declining interest, rising demand

Figure 1: Google NGram Data for KT, KE & KI: 1996-2008

Figure 2: Google Trend Data for KT, KE & KI: 1996-2013

Where to?

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What do you mean when you say learning?

How do we know when learning is the answer (and what are the questions)?

Learning to innovate (and being wrong)

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Just the facts

Facts vs Problems

Designing education

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Disrupted Media

Are ‘Monkeys in Coats’ A Healthy Story?

Going Deeper to See Clearer

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Design and Evaluation: A Natural Partnership

An Ethical Imperative?

Barriers and Opportunities for Evaluation-powered Social Innovation

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The Writer and his Craft

‘Snappy Science’ and Synthesis

Filling the gap, meeting a need and shooting the messenger

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Social media, non social content

From Web 2.0 back to 1.0

Imposing Structure and Losing Complexity

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