Evaluating Health Promotion Social Media Strategies for Public Health Impact

How is social media stacking up?

How is social media stacking up?

I recently spoke at an interactive workshop presentation at the 2013 Ontario Public Health Convention (TOPHC) looking at social media use in public health and the strategies available for evaluating those strategies in practice. The talk was focused on the tools, methods and approaches and the inherent challenges in dealing with a dynamic social communication environment.

Here are the slides from that presentation.

Evaluating Health Promotion Social Media Strategies for Public Health Impact

Image: Shutterstock (used under licence)

Evaluating Health Promotion Strategies for Public Health Impact from Cameron Norman

The Quality Metric in Education

Image

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

EducationHead

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 Job Market Metric In Education

UniversityDoors

Post-secondary and continuing education is continuing to be rationalized in ways that are transforming the very foundation of the enterprise. Funding is a major driver of change in this field: how much is available, when it flows, where it comes from, what is funded, and who gets the funding are questions on the minds of those running the academy.

At the centre of the focus of this funding issue is the job market. Training qualified professionals for the job market in various forms has been one of the roles a university has played for more than a century. Now that role has become central.

Let’s consider what that means and what it could do in shaping the various possible futures of the university. This second in a series looking at the post-secondary and continuing education focuses on the metrics of jobs.

“What are all these people going do?”

The employability of graduates is now the holy grail of education industry statistics. Earlier this year I was sitting on the stage at an academic convocation with a senior colleague staring out at a sea of soon-to-be-graduates when he leaned over and asked the question quoted above. Staring at a sea of masters and doctoral graduates numbered in the hundreds and knowing that this ceremony was held twice per year, the question stuck and remains without an answer.

Maybe there were enough jobs for that cohort, but this process gets repeated twice each year at universities around the world and each year that I’ve been a professor those numbers (of graduates) seem to go up. Some of our programs in the health sciences are admitting three times the number of students than they were just ten years ago. There is much demand for education (as judged by departmental applications), but are there jobs demanding this kind of education in its current form?

Yes, the Baby Boom is moving into an age of retirement and increasing needs for health services, but do we need to graduate 80+ Physical or Occupational Therapists to meet this need this year? Do we need a few dozen more epidemiologists or health promotion specialists to add to the pool? How about psychologists or social workers: how many of those do we need? The answer from my colleagues in these fields is: We don’t know.

Chasing the Wind

Jobs are a red herring. It’s one thing to have a job, but is it the job that you trained for? (And is having that job even a reasonable goal?) Being employed is not the same as building a career. What if you were trained perfectly for a job that no longer existed? Imagine a Blacksmith in the 20th century or a Bloodletter. These questions are not asked, nor is much asked about quality of education relative to the pressures of recruitment, cost-cutting and educational rationalization. Most of us don’t know what quality education is in real terms because we are measuring it (if we are measuring anything at all besides jobs) by standards set for the jobs of the past, not the future (or even the present?).

“Skate where the puck is going, not where it’s been.” – Wayne Gretzky

Jobs are living things and very few in 2013 will resemble what they did even 10 years ago. The citizens of the developing world are entering this rapidly changing job market ready for change (See also McKinsey Global Institute report on future of work in advanced economies) because they don’t have the old ways to rely on. They are primed for change and if professional education is to meet the needs of a changing world, it needs to change too. It means getting serious about learning.

If education is rationalizing itself to focus more on jobs, then it also needs to get serious about clarifying what jobs mean, defining what ‘success’ looks like for a graduate, and whether those jobs are designed for where the proverbial puck is now or for where it is going.

Disruptive Learning / Disturbed Education

“The Only Thing That Is Constant Is Change -” ― Heraclitus

I’ve pointed out that learners have an uneasy relationship with learning principally because it means disrupting things. This is a topic I’ll  be covering in greater depth in a future post, but if one considers how our social, economic, and environmental systems are changing it is not unreasonable to call this the age of disruption .

Change in complex systems is often logarithmic, not linear. It may be massively punctuated like a Lévy Flight or it could be closer to a random walk. In environments with a change coefficient that is large the level of attention must be more fine-grained than 5-year reviews. It requires developmental evaluation methods and learning organizations, not just conventional approaches to generating and assessing feedback. It requires mindful attention and contemplative inquiry to guide a regular reflective practice if one is to pay attention to the subtleties in change that could have enormous impact.

For example, if journalists and news media waited every five years to assess the state of their profession, they would have missed out on Twitter and come late to blogging, two of their (now) powerful sources of competition and tools of the trade. Some have waited, which is why they are no longer around. Metrics for journalism education today might consider the amount of exposure and proficiency in social media use, digital photography, use of handheld tools for communication, and real-time reporting skills. Metrics of the past might focus on newspapers and radio broadcasting. Which mindset, skillset and toolset would you rather be trained in today?

Questions for educators, learners (and evaluators):

Whether health sciences, journalism, human services or any field, what might some questions be that can help determine the role of job training in professional education? Here are five starters:

1. What is the state of your profession right now and are you training people for existing in this state? Are you preparing people for the next evolution?

2. Where is your field of practice going? What are the possible futures for your profession in the next 5, 10, and 20 years? Will it still exist? Are you a blacksmith looking for more horses in the automobile age or Steve Jobs waiting to attract people to a new graphical user interface?

3. Is your mindset, skillset or toolset in need of re-consideration? Does it still do the job you’ve hired it to do?

4. What do people need that your skills can help with? What unfilled needs and expectations are there in the world that your mindset, skillset and toolset could solve?

5. What would happen if your field of practice disappeared? How else could you apply what you know to making the contribution you wish to make and earn a living? What other skills, tools and ways of thinking would you need to adapt?

Design thinking can greatly help shape the way that one conceives of a problem, works through possible options, and develops prototypes to address the needs of the present and the future. Foresight methods help lay additional context for design and systems thinking by providing ways to anticipate possible futures for any given field. Lastly, knowing what the state of things are now and how they got to where they are now can help determine the path dependencies that education may have fallen into.

We can’t change what we don’t see and better foresight, hindsight and present sight is critical to better ensuring that education outcomes are not imagined, but based on something that can actually improve learning.


Rationalized Education and The Futures of the University

Hallowed Halls, Empty Promises?

Hallowed Halls, Empty Promises?

Next to the church, the university may be the most enduring formal institution in our society. And like nearly every institution from banking to manufacturing to healthcare and even the church, the university is facing a major disruption from social and technological change.

The church’s (simplified)  purpose is to provide a place of worship, communion and education on matters of faith and spiritual guidance.

The university is a place for preparing people to be better citizens, scientists or scholars, and professionals and to advance understanding of our world and universe.

Just as many question how well the church is realizing its purpose, so too are many questioning the university and how it is faring in its mission and purpose.

CENSEmaking returns to a discussion started last year with a requiem for the dream of a university no longer experienced by someone who aspired to serve within it. Following my advice to new scholars and attempts to peel back the curtain to show more about what university looks like for those outside it, it seems appropriate to revisit that discussion to explore the state of post-secondary education as another year passes.

This is the first in a series of upcoming posts looking at the future(s) of learning and professional education.

Rationalizing Education

Universities are rethinking things in a big way led by changes to the way they are funded. Quoting from a recent article in the Globe and Mail on the state of funding for Canadian universities:

Midsize Canadian universities are starting a new kind of cost-cutting exercise as they face the prospect of prolonged austerity and sustained pressure to show their graduates are succeeding.

Administrators have tended to slash budgets equally across the board, leaving it up to each dean and department to set targets inside their faculties. Now, Canadian schools are importing a movement from the United States in which economic hardship is viewed as an opportunity to refocus scarce dollars on faculties that deliver.

If we are to parse through this language, one will see it that points to a new way of evaluating the impact of the university and how it makes decisions about what to invest in:

“Instead of making decisions based on internal political factors or you-scratch-my-back-I’ll-scratch-yours, or whatever else has gone on in the past, it’s time for us to shift to a culture of evidence,” said Robert C. Dickeson, the U.S. consultant at the heart of the crusade against across-the-board cuts.

Ah, evidence. This powerful concept is the bedrock of science , has transformed the way medicine is practiced and is now being applied to the ‘business’ of education. In Canada, universities are now seeking data about its product to inform its strategic decisions. Some universities are doing more of this than others in applying some form of evidence to their policy and strategy to deal with current funding challenges:

The University of Guelph has gone furthest. Facing a $32-million shortfall over the next four years, Guelph’s leaders hired Dr. Dickeson for help after an invitation to a workshop he runs landed in provost Maureen Mancuso’s inbox. He was on hand at a Guelph University town-hall meeting in late November where president Alastair Summerlee laid out the challenge: rising costs, flat government funding and capped tuition, combined with a shortage of space to keep boosting enrolment.

“People outside of our institutions are full of a rhetoric around ‘do we produce quality, a quality product?’” Dr. Summerlee told a crowd of about 300. “These things make a case for actually trying to prioritize what we’re doing. … We need to act now.”

The plan is Darwinian. Each of the university’s nearly 600 programs and services, from undergraduate biology to the parking office, has to complete a “program information report” answering 10 criteria, to be reviewed and ranked by a task force of faculty, staff and students.

Embedded in the middle of this quote is the line: ‘do we produce quality, a quality product?

I have been involved in academic governance and policy making for 20 years first as a student representative at the undergraduate and graduate level and later as a full-time faculty member. The timing of my post-secondary life coincided with the last major shift in educational funding and rationalization that began in the early 1990′s with the first introduction of student fees and the start of philanthropic named sponsorship in Canadian universities. Prior to this time, students tuition was all they paid to access services and get an eduction and buildings, faculties and facilities were named based on criteria that was not tied to specific donations.

Despite all of this, quality was rarely a term used explicitly to shape strategy.

Money Matters and Defining Quality

I have never — not once — witnessed a major decision made on the basis of educational quality when juxtaposed against financial concerns. I’ve been a student, trainee or faculty member at five different universities and a visiting or guest lecturer or examiner at many more institutions worldwide and never have I seen quality of education trump fiscal or logistical issues on matters of great significance. Sure, there are small decisions to include particular content into a course or program or invite/disinvite a particular speaker based on perceptions of quality , but no program I’ve known chose, for example, to limit recruitment or enrolment because there were not enough resources to give a quality experience to students.

So if universities are now being judged on quality, what does this mean in practice?

Is quality about jobs? If so, then are they the jobs that students want, the ones they get (which may not be the same thing), the ones that students are trained for, or the ones that the market produces?

Is quality about what gets taught, what gets learned, or what gets applied? If it is some combination, then in what measure?

Is quality about what the market asks for or what the world’s citizens and its ecosystem (including plants, animals and oceans) demand?

Is quality about training people for jobs and roles that have traditionally existed, exist now, or may emerge in the future?

Is quality about the canon, questioning the canon, or re-discovering or creating new canons? Or all of them?

These are some of the questions worth asking if we wish to understand what the futures of the university might be and whether any of those possible futures mean not existing at all. Stay tuned.

Photo University by martybell from Deviant Art.


Evaluating Social Innovation For Social Impact

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.

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.


Design Thinking: Thinkers, Science and Practice

The Thinker, Auguste Rodin If to think and be aware of those thoughts (to think about thinking) is a defining feature of what it means to be human, why is it such a challenge to think about types of thinking? An answer to that question might help explain why design thinking is so difficult to translate into action and scholarship and why it continues to be the recipient of intense criticism and boosterism.

The other day a colleague reminded me of an essay on the demise of design thinking that I commented on in an earlier post . The post by William Storage adds further to the growing list of critiques of design thinking and ends this way:

In short, Design Thinking is hopelessly contaminated. There’s too much sleaze in the field. Let’s bury it and get back to basics like good design. Everyone already knows that solution-focus is as essential as problem-focus. Stop arguing the point. If good design doesn’t convince the world that design should be fully integrated into business and society, another over-caffeinated Design Thinking book isn’t likely to do so either.

Storage is right to argue that another book will not convince people of the merits of design or design thinking (which is different), but I can’t imagine it is just because of its merits. There appears to be something that troubles people with picking up metacognitive concepts.

Thinking about (Design) Thinking

Metacogntion is thinking about thinking and concepts like design thinking and systems thinking are, at their most basic, about the thought processes involved in contemplating systems or design. What commentators like Storage and Bruce Nussbaum are railing against is how this more sophisticated concept of design thinking (design metacognition if you will) has over time become synonymous at best, but a wholesale replacement at worst with a set of tools and creativity exercises.

Here we see the gap between the methods and their methodology.

Systems thinking, having had a few decades jump on design thinking seems to be faring better in that its common use is treated more as a metacognitive exercise than just a method, but only slightly. Why does adding thinking to something make it so difficult to communicate?

There is a reductionist push towards making thinking — design thinking, systems thinking, critical thinkingvisual thinking — into a discussion of methods and tools. The concern, not unfounded, is that concepts like design thinking is pitched as a set of very simple techniques to provoke innovation while being stripped of its genuine innovation potential and reflective capacity, ironically removing the “thinking” part of the approach.  These tools are manifest expressions of thinking and facilitators of it, but they are not thinking on its own.

The business and evidence of thinking

Maybe this is our fault for not putting thinking into the development of these concepts from the start. For example, the field of design suffers greatly from a lack of scholarship and theory around its methods and approaches. Designers are a practical bunch and seek to create and build things over theorizing and submitting their own processes to research. There are notable exceptions to this of course, but overall it is safe to say given design’s pervasiveness in our world that we know relatively little about it.

Systems thinking (as it applies to human systems) is in a different position, almost an opposite position. Whereas design thinking has come from a long history of practice with little formal research supporting it, systems thinking has emerged largely from academia and has far less empirical support for its applications to social affairs.

Another issue is economic. The drive for innovation-led market advantages in many fields is pushing anything to support such activity — something design thinking can do — into high demand. Markets abhor vacuums so they get filled and early markets favour the swift and bold, not necessarily quality. As my doctoral advisor once told me when I was hesitating on publishing my research: “people remember the first, not necessarily the best“.

Thus, we have entire business enterprises founded on teaching people design thinking without much depth in their process or intellectual foundations to support their work. They are out there in spades and contributing to the reasoned distrust, frustration and dislike of design thinking by many who could be its biggest advocates.  Whether that’s hopeless or not remains to be seen.

Where to?

So what is to be done? One option, that taken by Bruce Nussbaum, is to consider design thinking a failed experiment and seek alternative terms and concepts that capture the essence of what it does to improve innovative thinking, but in a manner that is less distorted. The challenge here is that, even if a new term does supplant design thinking, what is to prevent that concept from being co-opted and distorted as well with the same innovation-related market drivers in place?

Some argue that by formalizing design thinking into accredited programs, designations, certificates or degrees can assure quality just as we’ve started to see creep into the field of evaluation,. This presumes that have an empirically supported or widely agreed definition of what design thinking is and what are its core competencies. It also presumes we have the faculty with these skills and in positions to train people using methods tested to produce specific outcomes. Neither of these is true at present. This is the equivalent of suggesting that artists must have art degrees. Some artists do, but many do not and there is little to distinguish the difference in quality of the work between them.

A third option, the more complicated one and the most flexible, is to consciously build a community of practice around design thinking aimed at improving the scholarship, research and communications about design thinking to enable the wider world to learn about it, debate it, and apply it. This is already starting to form through such venues as the Design Thinking LinkedIn group and the Design Thinking Network. To that end, we could see a tremendous opportunity for professional organizations such as DMI and AIGA to contribute to this by opening themselves up to the wider community in the focus of their events and training options. By increasing commitment from those doing design and design thinking to education and contemplative inquiry into their craft we are naturally developing a field of practice that forms an attractor basin for better thinking and action.

Some further suggests to this point:

  • Follow what psychology did after the American Psychological Association President George Miller suggested they “give away psychology” to the world. Psychology was once an elitist, opaque field of therapy and science and now is widely taught, incorporated into nearly every human-centred discipline, and is founded on a strong scientific and practice base. Democratize design thinking.
  • Enlist creative professionals from fields like environmental studies, public health, social work, and education into the design thinking fold beyond traditional design disciplines. Get those living the spirit of Herb Simon who are out there trying to actively change current conditions into preferred ones — the social innovators, the public servants, the entrepreneurs of every stripe — to contribute their stories and insights on design thinking and get those into the public sphere for debate and dialogue.
  • Fund and support more research programs beyond examples of my own modestly-supported Design Foundations project , which has sought to study design thinking by interviewing those experts that do it and the literature on its practice across disciplines. And rather than proclaim design thinking’s success and power, prove it and document it.
  • Evaluate the programs that teach it, the processes used and determine what works, under what context, and document what happened along the way so we can learn more and be better at advocating for the power of design than simply proclaiming its worth.

Let’s contemplate more, study more, and reflect more about design thinking and maybe we’ll become better design thinkers.

What are your thoughts? Comment below.


The Ideology of Scaling Social Innovations

Box scaling

Does it scale? That question is central to the discussion of social innovation, yet the answer to it might lead us to questions about why it is so important to us in the first place and answers that could surprise us. 

Does it scale?” or “how to we take [idea, product, service] to scale?” are commonly heard questions in social innovation circles; so much so that they are left unquestioned. The thinking behind these questions is that if something works well at one level (or scale) then taking it another scale larger and achieving a wider reach must be better. Who wouldn’t want to see the benefits of something that serves the needs of one population, community or user extended outward and upward?

This is a laudable utilitarian goal, but it is a deceptively problematic one when we look a little closer at what scaling something actually means in practice.

Conceptualizing Scale

Jamer Hunt, the Director of the MFA program in Transdisciplinary Design at the New School in New York, speaking at last year’s DMI Fall Conference (which is available to view for DMI members), looked at the issue of design scaling through the lens of complexity and pointed to some of the problems with ‘scaling design’ in varied contexts. One of the examples he suggested is that of an ant compared with a human being taking a shower. For humans, the shower’s droplets of water are fine bodies of liquid that perform a particular task of facilitating cleaning, but for an ant those same droplets are enormous orbs of potential death. Water doesn’t scale the same for a human and an ant even though it is the same substance at both levels and the shower is identical in its structure.

In physics this is called scalar variance. What works ideally for humans is terrible for ants even though we are speaking of the same substance, same planet, same context. Water (most notably, a shower of it) doesn’t scale well in this case.

Yet, there is this insatiable desire among those working in social innovation to “scale things up” and “bring our innovations to scale” (even if we have little concept of how that would look or — as I will discuss — what that really means). The adherence to scaling as an ideology in social innovation (and applied social science in general) is bordering on “four legs good, two legs better” territory.

The Cult of Efficiency

International affairs scholar Janice Gross Stein attributes some of this fascination with scaling to a cult of efficiency, a political ideology that assumes that we can always rationalize human services optimally. What she found is that efficiency is used falsely as a stand-in for accountability, particularly in fields like education. Far from being against striving for optimal use of scarce resources, Stein nonetheless concludes that efficiency in human systems doesn’t always scale (my phrase, not hers) and that bigger and faster is often not better. Anyone who has taken a lecture with hundreds of others knows the difference of scale in learning between that and a seminar of five to ten people.

Taking Jamer Hunt’s argument: Bigger is just bigger…and whether its better or not is dependent on whether you’re an ant, a human and need to come into contact with water.

Designing for Systems and Scale: The Powers of 10

Designers and systems thinkers probably know the movie “The Powers of 10” by legendary designers Charles and Ray Eames. It’s a fascinating short film that looks at the universe moving out from a human being into the cosmos and inward towards what would now be quarks and everything in between. It is perhaps the best example of scaling ever produced. Beyond its educational and entertainment value, the Powers of 10 provide an illustrative example of where striving for scaling social innovations could be foolish and where it could have potential.

When traveling through the universe it is easy to see scales that are self-similar, thus they share properties that make them optimally relatable. These forms are often fractal in nature (thus, they share the same properties at different scales like that of a snowflake). Imperfectly, certain scales in the Powers of 10 are close to self-similarity where one scale looks and shows behaviour similar to those adjacent to it. These are spaces where it may be possible to transport an innovation from one to the other to good effect. Others scales look radically different from one another, suggesting a mis-fit in the scalar variance.

This is an idea, not an empirical point as we have little research on scalar variance in social innovation. Scaling innovation makes greater sense when the social systems have similar structures and ‘shapes’ and less when they do not. It is why in organizational science, certain models of management and decision making transport well from setting to setting and others do not. It’s why we’ve seen quality improvement processes like Six Sigma achieve great success in certain industries and firms and spectacularly fail in others.

Rather than adhere to an ideology that imposes scaling as a goal, social innovators need to generate the kinds of intelligence about the systems they are operating in (or seeking to operate or expand into) before making plans for scaling a promising intervention or product. As funders and policymakers this means setting performance targets that are appropriate or, perhaps better yet, working developmentally with innovators to co-create the outcomes of interest and the measures and metrics used to determine scalability and appropriateness early in the design and implementation cycle.

Without best evidence (which is almost always lacking in social innovation by its very nature), setting performance targets related to scale a priori is foolish. For innovators themselves, equally foolish is not gathering the kind of information about the systems they are operating in to know if they are the human or the ant and whether a shower is on the way.

 


Evaluation and Design For Changing Conditions

Growth and Development

The days of creating programs, products and services and setting them loose on the world are coming to a close posing challenges to the models we use for designing and evaluation. Adding the term ‘developmental’ to both of these concepts with an accompanying shift in mindset can provide options moving forward in these times of great complexity.

We’re at the tail end of a revolution in product and service design that has generated some remarkable benefits for society (and its share of problems), creating the very objects that often define our work (e.g., computers). However, we are in an age of interconnectedness and ever-expanding complexity. Our disciplinary structures are modifying themselves, “wicked problems” are less rare

Developmental Thinking

At the root of the problem is the concept of developmental thought. A critical mistake made in comparative analysis — whether through data or rhetoric — is one that mistakenly views static things to moving things through the same lens. Take for example a tree and a table. Both are made of wood (maybe the same type of wood), yet their developmental trajectories are enormously different.

Wood > Tree

Wood > Table

Tables are relatively static. They may get scratched, painted, re-finished, or modified slightly, but their inherent form, structure and content is likely to remain constant over time. The tree is also made of wood, but will grow larger, may lose branches and gain others; it will interact with the environment providing homes for animals, hiding spaces or swings for small children; bear fruit (or pollen); change leaves; grow around things, yet also maintain some structural integrity that would allow a person to come back after 10 years and recognize that the tree looks similar.

It changes and it interacts with its environment. If it is a banyan tree or an oak, this interaction might take place very slowly, however if it is bamboo that same interaction might take place over a shorter time frame.

If you were to take the antique table shown above, take its measurements and record its qualities and  come back 20 years later, you will likely see an object that looks remarkably similar to the one you lefty. The time of initial observation was minimally relevant to the when the second observation was made. The manner by which the table was used will have some effect on these observations, but to a matter of degree the fundamental look and structure is likely to remain consistent.

However, if we were to do the same with the tree, things could look wildly different. If the tree was a sapling, coming back 20 years might find an object that is 2,3,4 times larger in size. If the tree was 120 years old, the differences might be minimal. It’s species, growing conditions and context matters a great deal.

Design for Development / Developmental Design

In social systems and particularly ones operating with great complexity, models of creating programs, policies and products that simply release into the world like a table are becoming anachronistic. Tables work for simple tasks and sometimes complicated ones, but not complex ones (at least, consistently). It is in those areas that we need to consider the tree as a more appropriate model. However, in human systems these “trees” are designed — we create the social world, the policies, the programs and the products, thus design thinking is relevant and appropriate for those seeking to influence our world.

Yet, we need to go even further. Designing tables means creating a product and setting it loose. Designing for trees means constantly adapting and changing along the way. It is what I call developmental design. Tim Brown, the CEO of IDEO and one of the leading proponents of design thinking, has started to consider the role of design and complexity as well. Writing in the current issue of Rotman Magazine, Brown argues that designers should consider adapting their practice towards complexity. He poses six challenges:

  1. We should give up on the idea of designing objects and think instead about designing behaviours;
  2. We need to think more about how information flows;
  3. We must recognize that faster evolution is based on faster iteration;
  4. We must embrace selective emergence;
  5. We need to focus on fitness;
  6. We must accept the fact that design is never done.
That last point is what I argue is the critical feature of developmental design. To draw on another analogy, it is about tending gardens rather than building tables.

Developmental Evaluation

Brown also mentions information flows and emergence. Complex adaptive systems are the way they are because of the diversity and interaction of information. They are dynamic and evolving and thrive on feedback. Feedback can be random or structured and it is the opportunity and challenge of evaluators to provide the means of collecting and organizing this feedback to channel it to support strategic learning about the benefits, challenges, and unexpected consequences of our designs. Developmental evaluation is a method by which we do this.
Developmental evaluators work with their program teams to advise, co-create, and sense-make around the data generated from program activities. Ideally, a developmental evaluator is engaged with program implementation teams throughout the process. This is a different form of evaluation that builds on Michael Quinn Patton’s Utilization Focused-Evaluation (PDF) methods and can incorporate much of the work of action research and participatory evaluation and research models as well depending on the circumstance.

Bringing Design and Evaluation Together

To design developmentally and with complexity in mind, we need feedback systems in place. This is where developmental design and evaluation come together. If you are working in social innovation, your attention to changing conditions, adaptation, building resilience and (most likely) the need to show impact is familiar to you. Developmental design + developmental evaluation, which I argue are two sides of the same coin, are ways to conceive of the creation, implementation, evaluation, adaptation and evolution of initiatives working in complex environments.
This is not without challenge. Designers are not trained much in evaluation. Few evaluators have experience in design. Both areas are familiarizing themselves with complexity, but the level and depth of the knowledge base is still shallow (but growing). Efforts like those put forth by Social Innovation Generation initiative and the Tamarack Institute for Community Engagement in Canada are good examples of places to start. Books like Getting to Maybe,  M.Q. Patton’s Developmental Evaluation, and Tim Brown’s Change by Design are also primers for moving along.
However, these are start points and if we are serious about addressing the social, political, health and environmental challenges posed to us in this age of global complexity we need to launch from these start points into something more sophisticated that brings these areas further together. The cross training of designers and evaluators and innovators of all stripes is a next step. So, too, is building the scholarship and research base for this emergent field of inquiry and practice. Better theories, evidence and examples will make it easier for all of us to lift the many boats needed to traverse these seas.
It is my hope to contribute to some of that further movement and welcome your thoughts on ways to build developmental thinking in social innovation and social and health service work

Image (Header) Growth by Rougeux

Image (Tree) Arbre en fleur by zigazou76

Image (Table) Table à ouvrage art nouveau (Musée des Beaux-Arts de Lyon) by dalbera

All used under licence.


Social Media and Health: Leaders(hip) and Followers(hip)

Social media is finally catching on with healthcare, public health, and  health promotion. With a few recent articles published in the academic literature to rest on, academic health sciences has finally (and I might argue, begrudgingly) conceded that 900+ million users and $100B valuations (Facebook), and thousands of messages exchanged every milisecond (microblogs like Twitter and Sina Wiebo) might have some value for the public beyond entertainment.

If you note how long it took the health sector to start using the telephone as a serious means of engaging their patients or the public, this is lightning-quick adoption. Still, the barriers to adoption are high and the approach to using the technology is scattered. Indeed, just like the start of Internet-delivered telehealth (or cybermedicine (PDF), which has now evolved into eHealth), there is a mad rush to get liked, followed or some other metrics that most health professionals barely understand.

And that is part of the problem.

Meaningful Social Media Metrics

What is a meaningful metric for social media and health? A recently published article in Health Promotion Practice suggested four metrics that are taken from social marketing and applied to social media. These Key Performance Indicators (KPI’s) are:

  • Insights (consumer feedback)
  • Exposure (media impressions, visits, views, etc..)
  • Reach (# people who connect to the social media application)
  • Engagement (level of interaction with the content)

These are reasonable, but to to the uninitiated I would suggest a few words of caution and commentary to this list.

Firstly, the insights suggested by Neiger and colleagues “can be derived from practices such as sentiment analysis or data mining that uses algorithms to extract consumer attitudes and other perspectives on a particular topic” (p.162). While not incorrect, this makes the job sound relatively simple and it is not. Qualitative analysis + quantitative metrics such as those derived from data mining are key. Context counts immeasurably in social media use. It’s only in situations where social media is used as a broadcasting tool that gross measures of likes and sentiment analysis work with little qualification.

Even that is problematic. Counts of ‘likes’, ‘visits’, ‘follows’ and such are highly problematic and can be easily gamed. I am ‘followed’ on Twitter by people who have tens of thousands of followers, yet virtually no presence online. Most often they are from marketing fields where the standard practice is to always follow back those who follow you. Do this enough and pretty quickly you, too can have 23,000 followers and follow 20,000 more. This is meaningless from the perspective of developing relationships.

Engagement is the most meaningful of these metrics and the hardest to fully apply. This category gets us to consider the difference between “OMG! AWESOME!” and “That last post made me think of this situation [described here] and I suggest you read [reference] here for more” as comments. Without understanding the context in which these are made within the post, between posts (temporally and sequentially), and in relation to a larger social and informational context, simple text analysis won’t do.

Social Media Evidence: Problems and More Problems

One of the objections to the use of social media by some is that it is not evidence-based. To that extent I would largely agree that this is the case, but then we’ve been jumping out of airplanes with parachutes despite any randomized controlled trial to prove their worth.

Another article in Health Promotion Practice in 2011 highlights potential applications for social media and behaviour change without drawing on specific examples from the literature, but rather on theoretical and rhetorical arguments. An article published in the latest issue of Perspectives on Psychological Science highlights the current state of research on Facebook, which is timely given that its IPO is set for today. That review by Wilson and colleagues illustrates the largely descriptive nature of the field and offers some insight on to the motivation of Facebook users and their online activities, but rather little in what Facebook does to promote active change in individuals and communities when they leave the platform.

The answer to whether social media like platforms such as Facebook ‘work’ as methods of promoting change is simply: we don’t know.

Does social media provide support to people? Yes. Does it inform them? Yes to that too. Does that information produce something other than passive activity on the topic? We don’t know.

In order to answer these questions, health sciences professionals, evaluators, and tech developers need to consider not just followership, but leadership. In this respect, it means creating changes to the way we gather evidence, the tools and methods we use to analyse data, and the organizational structures necessary to support the kind of real-time, rapid cycle evaluation and developmental design work necessary to make programs and evidence relevant to a changing context.

As Facebook launches into its new role as a public company it is almost assured to be introducing new innovations at a rapid pace to ensure that investor expectations (which are enormous) are met. This means that today’s Facebook will not be next month’s. Having funding mechanisms, review and approval mechanisms, a staff trained and oriented to rapid response research, and an overall organizational support system for innovation is the key.

Right now, we are a long way from that. Hospitals are very large, risk averse organizations; public health units are not much different. They both operate in a command-and-control environment suited for complicated, not complex informational and social environments. Social media is largely within the latter.

Systems thinking, design thinking, developmental evaluation, creativity, networks and innovation: these are the keywords for health in the coming years. They are as author Eric Topol calls the dawning of the creative destruction of medicine.

The public is already using social media for health and now the time has come for health (care, promotion and protection) systems to get on board and make the changes necessary to join them.


Follow

Get every new post delivered to your Inbox.

Join 2,468 other followers