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Personalized Prevention, Part II – The Psychology of Engagement

March 13, 2012

My colleague Meghan Searl collaborated with me on the psychology framework discussed herein.

 I don’t spend much time on Facebook.  Its not that I’m antisocial, but on a given day if I get through my email inbox by 10 PM, I feel good about myself.  That leaves little time for social networking.  I haven’t played Angry Birds or Farmville for the same reason.  I just have other priorities.  I grew up in a family of plain-spoken, simple Vermonters.   My dad was a kind and gentle man, but when he raised his voice we all took notice. And, because of his ‘kinder-gentler’ side and plain-spoken character, my brother and I took him quite seriously and felt it was wise to comply with his wishes.  Also, my folks both had a deep sense of the value of good health and strove to achieve a healthy lifestyle.

I believe this combination of circumstances and history is what is behind my individual connected health psychology.  I am responsive to authority – a compliant fellow who sometimes forgets, but when reminded complies.

In Personalized Prevention, Part I, I talked about the power of genetic data combined with the phenotypic mapping that connected health tools give us to micro-segment the population to a level where we have a completely unique, individual genotypic and phenotypic profile.  The example I used was obesity, suggesting that with these two technologies colliding, we’ll have the opportunity to identify individuals at risk for weight gain early in life and put them on connected health programs to keep them trim.  Many readers pushed back and the essence of the push back was, “micro-segmentation alone is not the answer.  Even providing individuals with data on their caloric expenditure in the context of their risk for weight gain will not solve this problem.”

Folks, I couldn’t agree more.  The medium of blogging is best suited to ‘bite-sized’ writing and the first bite in this series was about the micro-segmentation piece.  Today I want to spend time on the psychology of engagement, as I believe it is critical to the success of connected health and can also be highly individualized.

The first point to re-emphasize is that connected health data alone do not solve any problems, except perhaps for the very small group of highly motivated fitness buffs and quantified selfers (maybe 10% of the population).  There was a time when companies in this space boasted that they could ‘get biometric data into the PHR or EMR.’  Work done at the Center for Connected Health and by others has demonstrated that this is nearly meaningless.  We’ve relearned the old adage that data is not information.

Of course, it’s all about what you do with the connected health data.  Objective data inputs are a critical component of the solution – self-reported data is also nearly useless – but the success of connected health programs is all about the psychology of how we engage program participants in these data in order to motivate them to improve their health.

Most companies who have focused on engagement have not bothered to include the objective data stream because of the cost of sensors and the complexity of integration.  Most have also touted one engagement strategy or another as the key to success.  The options these days seem to be:  gamification, social networking, coaching, reminders, incentives and punishments.

Lets go back to me as an example.  If my employer rolled out a wellness program and the engagement tool was social networking, I am afraid I would not be successful in it.  Likewise for competitions/games.  But set me up with a reminder system and an automated coach with an authoritarian tone and I will improve my health behavior.

Purveyors of wellness programs tout their success, e.g., ‘40% engagement after 6 weeks.’    My question is what about the 60% who didn’t engage?  It seems to me we understand the tools and triggers to get closer to 100%, but we must admit that one size does not fit all and do some behavioral segmentation at the outset to tailor programs to what individual buttons need to be pushed.

Healthrageous comes the closest to offering this type of approach (I say this with as much objectivity as possible, as a co-founder and share holder).  Their vision is to know so much about you that they can anticipate the engagement experience that gets you involved in a way that you feel they know you intimately.  This will come about through a machine learning environment and as more and more participants take advantage of their programs, they’ll do better and better at this.  In the meantime, I think we can start with a simple set of questions designed to paint a profile of each individual that is akin to the one I wrote describing me at the beginning of this post.  We’re working on that at the Center. I am excited to share our learning as we go forward.

17 Comments leave one →
  1. Jay permalink
    March 14, 2012 12:28 am

    I’m not sure what to make of this post. You seem to admit at the outset that you are not typical (“I haven’t played Angry Birds or Farmville”), but then use yourself as the typical case (“Lets go back to me as an example”). So is this opinion?

    I would hope that most people would agree that it’s great to be able to design customizable solutions, but are you saying that social-network-based solutions are not a good idea, because you don’t think they work for everyone (i.e., you, with your “plain-spoken character” values you grew up with – which most of the country would also say they grew up with)?

    • March 14, 2012 8:06 am

      This is helpful feedback. My point was that there is no one size fits all solution, and that the next phase of development will be systems that sense one’s motivational make up and respond accordingly.

    • Sygriffin permalink
      March 27, 2012 8:33 pm

      Dr. K., In your post, you wrote that you respond to authority and comply when reminded. Throughout our lives, we encounter authority figures beginning with our parents, then teachers, and later employers. We are rewarded when we comply with these authority figures or at least avoid punishment for not doing so. In the healthcare field, the clinician is that authority figure, yet patients struggle to comply with the instructions they are given to improve their health, even when they have access to care and health insurance. My dissertation research informed me that people are willing to change their behavior, if their behavior resulted in a great deal of distress. In other words, we have to experience a great deal of grief before we are willing to consider changing our behavior. So, a visit to the emergency department (a source of financial and emotional grief) should be enough to encourage a person to change his/her health related behavior-yet this is not always the case. As a result, I am starting to believe that our health decisions are sitting on a balance scale. On one end of the scale are the benefits we receive from keeping the status quo, which may be numerous. Only if we are overwhelmed with the negative consequences of maintaining our behavior that the opposite end of the scale drops and we can no longer justify our behavior. At this point, it is not that someone has told us that we have to change; we are confronted with the reality that our situation will only worsen if we do not change. Of course, this is not the case for everyone, but change is truly difficult, and we resist it as much as we can. I believe the programs we develop to engage people in new health behaviors may consider this metaphorical scale and approach people based on how the scale is tipping. If the scale is tipping in favor of maintaining the status quo, it may be harder for people to succeed in changing their health behavior, even when provided with the best supportive technology. With these individuals, our strategies may focus on helping them identify the factors that will tip the scale in the opposite direction, allowing them to see the need for change; thus enhancing their ability to benefit from these technologies. On the other hand, if the scale has dropped heavily on the grief side, we may focus more on providing access to low cost, tailored health related tools that are easy to use and adjust to the person’s changing needs over time.

      • March 27, 2012 9:17 pm

        Thank you, Shanta, for your thoughtful comments. It’s a pleasure to have you reading and responding to the blog

  2. March 14, 2012 2:20 am

    I agree with the assessment that this is (in many ways) the beginning of a journey – where the only objective is better health (not a fixed desitnation).

    Ernst & Young released a pretty compelling report on this just this week. In effect, they say that everyone in the healthcare industry (payer, provider, pharma etc…) is now in the behavior change business. I couldn’t agree more – and I wrote as much on my blog too:

  3. March 14, 2012 8:06 am

    Thanks for the link and reference to the E & Y report, which I had not seen

  4. Cheryl permalink
    March 15, 2012 10:31 am

    I completely agree that engagement mechanisms need to be tailored to the individual –> each person is unique, is motivated by different things, and has different obstacles to overcome. One additional point – The measurement of success of such wellness/connected health programs should include, not just the % of people engaged, but also the length of time engagement is maintained. Many of us start exercise programs, diets, etc., and achieve positive outcomes in the short term (i.e. 6 wks, 6 mos., 1 year). However, many of these gains are lost over time (i.e. 2-5 years). Sustainable behavior change over the long term is the ultimate goal.

  5. March 15, 2012 12:06 pm

    Indeed, decay is a well recognized challenge with all behavior change methods. The feedback loops that are embedded in the connected health design tend to help combat this.

  6. March 16, 2012 5:49 pm

    I just read part 1 and was responding when I thought I should post in part 2 to keep up with the dialogue…

    The 40% predisposed towards diabetes/obesity who can follow the connected program protocol are successful doing what they should to change their behavior because they receive the educational information prescribed by their doc or other authority.

    However, while some predisposed to the disease might buy into interventions that may be generalized so they never become chronic conditions, others require more personalized help to reconnect mind-body with context.

    And the longer one becomes habituated, further silo’d and sick, the harder and more personalized intervention may need to be to change as the disconnect between mind and body becomes more ingrained.

    If you are genetically predisposed, you are compromised and the methodology provided to everyone else is only a band-aide prevention to a systemic issue. You are completely vulnerable to following your genetic predisposition at any given contextual trigger point and once you are mired in that quicksand, how do you get out?

    Studies like these –
    reveal as young children, we are able to take information in through our senses and act on it appropriately. Connections help to us to derive meaning and extrapolate our thoughts further from there.

    However, as we become educated, many of us fall through the cracks, losing our connection within ourselves and the ability to change our behavior meaningfully. In an effort to be efficient, education focuses from the neck up, while health seems to focus on the symptoms from the neck down. There are many reasons why that is…we have more information with the same amount of hours to learn, our model stems from industrialization & efficiently run factories, etc…but what it’s creating are silos of specialty and the loss of our individual natural capacity to self-regulate and adapt our behavior given all the contextual information.

    This is where your genetic screening comes in but another study I found fascinating is from Professors Marcel Just & Tom Mitchell at Carnegie Mellon who have done fMRI studies showing the link between read/spoken words in brain activated areas, then putting others through the fMRI, & putting the areas of the brain activation scanned into their machine algorithm, the computer can determine which word was spoken/read to that other individual. This was also done with people in different languages.

    To me, what this shows is that undamaged brains have the same functional abilities but context and experience can vary, so it’s the collective context derived through various connection points and experience engagement enables.

    When it comes to teaching that leverages rote memorization, you can have increased self-control based on the correct response (teach to the test) for that special 10% & a more generalized program for the other 30% that need a little help but to have true self-control through engagement (critical/lateral thinking) required by that 60% to get over their challenge will require real data driven metrics and patient-centered engagement in my opinion. Connection between the mind-body and context needs to occur in an internal feedback loop of joint attention, perspectives, so higher-ordered thinking enabling self-control through engagement with others can be leveraged.

    Play, language, and engagement within ourselves and externally with others in intersecting feedback loops enables us to understand the meaning, context and experience of others and extrapolate our own thoughts and learning from there but unless we connect to it ourselves, we might feel we can’t change our behavior.

    Then I think data metrics for these individuals isn’t only about the quantity and duration of exercise, it must include monitoring engagement data through various connection points as well.

  7. March 16, 2012 6:04 pm

    It would be wonderful to find a cost effective solution to genetic screening.

    Genetic testing appeals but its costs are worrisome | Healthcare Finance News

  8. March 19, 2012 12:21 am

    the price continues to come down and by many estimates will be in the $200 range in a few years there is hope

  9. March 27, 2012 10:54 pm

    I and a few other colleagues in the US have been pioneering the field of persuasive technology, a set of computing tools that can alter human behavior and we have designed and implemented several technologies for healthy lifestyle and wellbeing. I am glad to see your group as well as E&Y finally saying that the time has come to focus on prevention through behavior change. But for those of us who have been engaged on this for a while, I agree that no one solution will work. Moreover we have recently published models in which we are changing our framing from persuasion to empowerment. When can users feel empowered? When the message is experientially rewarding, cognitively convincing but above all is aligned with his/her the long-term goals. To know that one has to enter into motivational interviewing techniques through which one can guage the goals and then design custom-tailored interventions. Also since the next generation is IT-savvy, it is important that we develop these solutions and bring them to where they are: SMS texting for younger folks, blogs and facebook for working adults and perhaps newsletter or websites for the senior older population. The key is to provide actionable message that they can act on.
    1. Samir. Chatterjee, Mike Csikszentmihalyi, J. Nakamura, David Drew, Kevin Patrick, From “Persuasion to Empowerment: A Layered Model, Metrics and Measurement” in Proc. Int’l Conf. on Persuasive Technology (Persuasive 2010), Copenhagen, Denmark, June 7-9, 2010.

    2. Samir Chatterjee, and Alan Price, “”Healthy Living with Persuasive Technologies: Framework, Issues, and Challenges”, Journal of the American Medical Informatics Association (JAMIA), 2009; 16: 171-178. PrePrint published December 11 2008.

  10. April 1, 2012 3:35 pm

    Thanks for the comments, and especially for the references.

  11. Jay Srinivasan permalink
    April 3, 2012 6:04 am

    My response is delayed since I just got to read your blog post, but this topic about engagement in healthcare is fascinating and complex and one I am wrestling with myself at my startup.

    I agree fully with Sygriffin’s post that people have to experience “a great deal of grief before…willing to consider changing behaviors” and the idea of a metaphorical scale says it quite simply and clearly. This brings to mind a notion in management (actually, marketing) that is a very useful construct in healthcare – though I’ve never actually seen it being discussed anywhere (I had a post elsewhere on the subject some time ago). That is one of “high involvement” vs “low-involvement”. High involvement goods are those that people care about deeply and spend much time and effort studying, understanding, and internalizing. These products or services, oftentimes, are not terribly important to our lives in the larger scheme of things – such as following the performance of the RedSox or evaluating the New iPad or the iPhone 4S (even as one has the earlier versions) or the latest LCD television or the merits of the latest Toyota Prius.

    In contrast, healthcare is low-involvement: even as we may be told, quite bluntly that we are susceptible to something that could cause future problems, we ignore it at our peril. People only become “highly involved” in their health when, to quote Sygriffin, “they experience a great deal of grief” or are “overwhelmed with the negative consequences of maintaining our behavior”. By that time, it is usually too late in terms of the overall toll it has taken on the person and their loved ones.

    What connected health, in association with pathbreaking psychology research, has to discover is how to make health endemically high involvement – rather like an iPhone, a Nintendo Wii, playing the daytime trader, or spending time in Las Vegas. In fact, all of these could inform our thinking on what makes people highly involved in certain areas – may be there is some genetic disposition or brain mapping that predisposes us to highly involved behavior in some and not in others.

    • April 3, 2012 9:35 am

      This is a nice way to simplify a complex topic. I like that. Always looking for ways to simplify the communication.


  1. Personalized Prevention, Part III: Applying the Model to Obesity « The cHealth Blog

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