Tag: eHealth

eHealthinnovationpublic healthsocial innovationsocial media

Seeing the lights in research with our heads in the clouds

Lights in the clouds

Lights in the clouds

Some fields stagnate because they fail to take the bold steps into the unknown by taking chances and proposing new ideas because the research isn’t there to guide it while social innovation has a different twist on the problem: it has plenty of ideas, but little research to support those ideas. Unless the ideas and research match up it is unlikely that either area will develop.

 

Social innovation is a space that doesn’t lack for dreamers and big ideas. That is a refreshing change of pace from the world of public policy and public health that are well-populated by those who feel chained down to what’s been done as the entry to doing something new (which is oxymoronic when you think about it).

Fields like public health and medicine are well-served by looking to the evidence for guidance on many issues, but an over-reliance on using past-practice and known facts as the means to guide present action seriously limits the capacity to innovate in spaces where evidence doesn’t exist and may not be forthcoming.

The example of eHealth, social media and healthcare

A good example of this is in the area of eHealth. While social media has been part of the online communication landscape for nearly a decade (or longer, depending on your definition of the term), there has been sparse use of these tools and approaches within the health domain by professionals until recently. Even today, the presence of professional voices on health matters is small within the larger discourse on health and wellbeing online.

One big reason for this — and there are many — is that health systems are not prepared for the complexity that social media introduces.  Julia Belluz’s series on social media and healthcare at Macleans provides among the best examples of the gaps that social media exposes and widens within the overlapping domains of health, medicine, media and the public good. Yet, such problems with social media do not change the fact that it is here, used by billions worldwide, and increasingly becoming a vehicle for discussing health matters from heart disease to weight management to smoking cessation.

Social innovation and research

Social innovation has the opposite problem. Vision, ideas, excitement and energy for new ideas abound within this world, yet the evidence generation to support it, improve upon it and foster further design innovations is notably absent (or invisible). Evaluation is not a word that is used much within this sphere nor is the term research applied — at least with the rigour we see in the health field.

In late May I participated in a one-day event in Vancouver on social innovation research in Vancouver organized by the folks at Simon Fraser University’s Public Square program and Nesta as part of the Social Innovation Week Canada events.Part of the rationale for the event can be explained by Nesta on its website promoting an earlier Social Frontiers event in the UK:

Despite thriving practitioner networks and a real commitment from policymakers and foundations to support social innovation, empirical and theoretical knowledge of social innovation remains uneven.

Not only is this research base uneven, it’s largely invisible. I choose to use the word invisible because it’s unclear how much research there is as it simply isn’t made visible. Part of the problem, clearly evident at the Vancouver event, is that social innovation appears to be still at a place where it’s busy showing people it exists. This is certainly an important first step, but as this was an event devoted to social innovation research it struck me that most attendees ought to have already been convinced of that.

Missing was language around t-scores, inter-relater reliability, theoretical saturation, cost-benefit analysis, systematic reviews and confidence intervals – the kind of terms you’d expect to hear at a research conference. Instead, words like “impact” and “scale” were thrown out with little data to back them up.

Bring us down to earth to better appreciate the stars

It seems that social innovation is a field that is still in the clouds with possibility and hasn’t turned the lights on bright enough to bring it back down to earth. That’s the unfortunate part of research: it can be a real buzz-kill. Research and evaluation can confirm what it means for something to ‘work’ and forces us to be clear on terms like ‘scale’ and ‘impact’ and this very often will mean that many of the high-profile, well-intentioned initiatives will prove to be less impactful than we hope for.

Yet, this attention to detail and increase in the quality and scope of research will also raise the overall profile of the field and the quality and scope of the social innovations themselves. That is real impact.

By bringing us down to earth with better quality and more sophisticated research presented and discussed in public and with each other we offer the best opportunity for social innovation to truly innovate and, in doing so, reach beyond the clouds and into the stars.

Photo credit: Lightbulb Clouds by MyCatkins used under Creative Commons License. Thanks Mike for sharing!

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Returning Home

New ideas are blossoming

New ideas are blossoming

 

After more than four weeks of travel, conferences and events it is good to return home. CENSEMaking’s sabbatical is over and over the next few weeks I’ll be sharing the insights gained from a brief, but deep immersion into of the biggest design cultures in the world (Italy and Finland) and spending time exploring the latest in evaluation research and practice from around the world at the Canadian Evaluation Society‘s annual conference as well as time spent at PAHO in Washington DC working with the eSAC team looking at how to develop engaged communities of practitioners, innovators and policy makers in public eHealth and equity.

Stay tuned and enjoy the start of summer wherever you are.

Cameron

behaviour changeeHealthhealth promotioninnovationpublic health

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.

complexityemergencepublic healthsocial mediasystems science

Systems Thinking, eHealth and Changing Public Health

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

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

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

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

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

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

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

This makes me quite pleased.

behaviour changecomplexityeHealthinnovationknowledge translation

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

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

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

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

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

Technology Spectrum of Social Collaboration by Christopher Wilson

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

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

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

As complexity increases, the need for offline engagement increases.

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

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

behaviour changepsychologysocial media

Social Media / Social Activism Redux: Can we Learn from Behaviour Change Theories?

What started as a simple column post a column on October 4th in the New Yorker has really turned into a firestorm of discussion over the last few days (reflecting a building crescendo of discontent and plaudits from those on each side of the debate). The latest volley in the debate has come from the founder of Twitter themselves in a piece in the Guardian. In that column, the chief Tweeters remark:

Williams said:

“It was a very well-constructed argument but it was kind of laughable.

“Anyone who’s claiming that sending a tweet by itself is activism, that’s ludicrous — but no one’s claiming that, at least no one that’s credible. If you can’t organise you can’t activate. I thought [the article] was entertaining but kind of pointless.”

They have a good point. But while Gladwell might be too dismissive of the power of tools like Twitter, it is easy to overstep and imply that information is power and having more of it networked leads to activation (something I discussed earlier this week).

Knowing and doing are very different and any analysis of major theories on behaviour change and the evidence, shows a relatively weak correlation between knowing more and doing more. It also shows an OK, but also not a strong correlation.

What does change people’s behaviour? Lots of things — and that’s the problem. The either/or thinking that permeates the discussion of social media is too often simplistic and driven by an interplay of ideas and values that are not always aligned with the evidence or personal experience.

People tend to change for the following reasons:

1. They have information that tells them there is a threat or a problem with the status quo;

2. Others believe that the behaviour should be changed;

3. The person changing actually cares what other people think;

4. That person has the skills and tools to be able to change;

5. The environment is supportive of change and facilitative (e.g. there are policies, procedures, access to resources — including time);

6. There are more pros to changing than cons (and there are more pros to the strategy of change than the cons);

7. A person actually wants to change (they are self-motivated and not doing things because everyone else thinks they should);

8. A person feels capable of making the change at all.

The more of these elements are present, the more likely the change is going to take place and stick. This is a big list and indicates that change isn’t always straightforward, and it certainly isn’t easy.

The revolution most likely will be Tweeted, but whether that is the cause or the consequence is why research on social media and social activism is needed. Otherwise, we will wind up with another chicken and egg problem.

 

Chicken, Eggs or Social Eggs?

 

innovationsystems science

Systems (Science): Sexy and Not So Much

Recently I was discussing what I do with someone relatively unfamiliar to my research, yet in the same field and I described my interest in systems thinking, knowledge translation, and eHealth and how they go together. Somehow in the conversation the term “sexy” was used to describe these fields along with “hot” and “upcoming”. It’s nice to be at the forefront of a field — or three — but it also has some downsides.

One of the downsides is that rigor often gets displaced by enthusiasm. Even fields like knowledge translation, which first emerged in the mid 1990’s (and far earlier than that if you’re willing to consider different terms), is just now evolved to the point where it is widely accepted and supported as a legitimate area of research. There is still much work that calls itself KT that is really just dissemination with a different name, but the concept of KT at least has some respect.

So too, does the idea of systems thinking. With recent special issues in respected journals like the American Journal of Preventive Medicine and American Journal of Public Health and full monographs from the National Cancer Institute, the idea of transmitting systems science from the backwaters of public health to the forefront is close to reality.

eHealth was sexy too, but too much investment matched with too little patience for good evidence quickly burned through much of the potential that consumer-directed eHealth had for making transformative differences on a broad scale. No worry, mHealth is here and that is quickly proving to be as “hot” as eHealth was ten years ago.

The problem is that “hot” and “sexy” terms often presage their demise in respected discourse before too long. I was once told by a senior official with a large health NGO that he’d given up on eHealth because he knew it didn’t work. This was 2002. Most of the best evidence hadn’t been generated yet and already people had thrown in the towel.

Knowledge translation is having its problems too, because the evidence of a shortening from “evidence to effect” is hard to generate. Often, KT requires systems level changes and systems thinking to create the conditions to generate effective KT practice. That suddenly transforms something that is “sexy” into something difficult and much less so in the eyes of those who are responsible for implementation of KT plans.

Systems science as it is applied to health is in greater danger because the scale and scope of change required to generate good evidence is often at a scale that is prohibitive. Take gambling as one potential public health problem. Governments are now deriving enormous revenue from gambling, while the social costs seem to rise with it. So important is gambling to provincial government revenues in most Canadian provinces that the only way to really change is to change the system as a whole. Diabetes care, mental health, and public nutrition and food security are other issues that are complex and of a scope that requires a true systems-level intervention to effectively address. Suddenly, when you speak of connecting the private sector to the public sector, changing regulations, building true KT systems within these areas, supporting public health education and practice, and tackling the social inequalities that are propped up by a current system of organization, systems don’t seem as sexy.

Furthermore, in the case of systems, KT, or eHealth, acknowledging complexity in the way we handle things, and considering problems from a systems perspective, means hard work, different time horizons, and truly working collaboratively across disciplines and settings. That is hard stuff and it sure isn’t sexy.

There are lots of areas within the health system that are not sexy, but few are seen less interesting than issues that were once viewed as sexy, but now not so much. That’s the danger with systems, knowledge translation and eHealth.