What the Quantified Self movement can learn from the trajectory model in engaging the unhealthiest patients
As our mhealth focus continues, Mavis Dixon discusses the Quantified Self movement and questions whether it is actually motivating change in patient adherence, or whether it is only motivating those who already have an adherent mindset.
Much has been made of the Quantified Self Movement, a health trend that capitalizes on the emergence of new technologies that permit self-tracking. Originally associated with the Quantified Self Labs founded by Gary Wolf and Kevin Kelly, it is now a term used to refer to a very large ecosystem of tools that provide a person with feedback on the minutiae of almost every conceivable interaction between the physiological self, the environment and time. In an age of inexpensive mobile and sensor technologies the movement has exploded. But as a patient engagement approach, are these data-driven tools “preaching to the converted“?
At the heart of the Quantified Self (QS)’s appeal is the powerfully-rewarding engagement loop experienced when a user receives feedback on his or her progress. Many QS applications have a distinctly game-like flavor, as the elements of providing feedback and progression toward a goal are design requirements with a long history in video game design. Many of the QS designs are centered on assigning points, badges, times and visualizations, such as graphs often mapped to biometric measures, such as steps or heart rate, and environmental information such as geolocation.
But when we look at the subset of people with chronic illness using QS technologies, we more often than not find the users are those who we would expect to be the most adherent, with or without assistive technologies. As Karmel Allison, a very healthy person with Type 1 Diabetes and a blogger with A Sweet Life puts it: “I love devices that show me biometric data. Granted, I’m the kind of person that loves numbers, and if I didn’t have diabetes, I would probably be wearing a heart-rate or activity monitor. The more data I have, the better, even if I can’t always interpret it at the outset.” Marathon runner, Doug Kanter’s blog post on QuantifiedSelf.com reflects the enthusiasm of another very healthy person with T1D for QS tools. Clearly the “more the data the better” works wonders for a subset of the population. But what about the rest?
Quantifying yourself is not the same as improving yourself.
While game-like, most QS apps are lacking a narrative – the meaningful storytelling element that connects with players emotionally. What really matters to the patient is at the heart of most successful innovations in adherence therapy. We know that when a QS running-fan shows up an application like RunKeeper they’ll recognize themselves in it and think “Wow! A community of runners. I belong here.” But what if the person who needs the exercise does not have a pre-existing self concept as sporty? The narrative has to fit.
This insight of using narrative and self concept to get engage people is at the heart of The Trajectory Model. Drawing insights from personality research and behavioural psychology is where we see technology developers headed, in their efforts to create more “persuasive” health technology that reaches a wider audience than the QS aficionados.
Bruce Lambert, in his webinar for the NIH Adherence Network (slides available here) asserts that people who are experiencing chronic illness have suffered a break in the chain of “biography” (established patterns of behaviors), “biology” (or body) and “self-concept” (who I am). This is what the Trajectory Model refers to as one’s “BBC”. While the QS movement does a great job of providing feedback on the biology and to a certain extent, the biography, it fails at reflecting Self Concept. According to Lambert, we are motivated to keep true to our sense of self, and our narrative.
Our self-concept means we will work hard to restore it if illness challenges us, but it also means we may not adhere to treatments that don’t fit with our self-concept. For example, a person whose self-concept is as a “thin person” will give up a medication whose side effect is weight gain, even if it causes them suffering. Lambert asserts: “If the illness is asymptomatic and the treatment forces them to depart from his or her established behaviors and self-identity, the patient will experience suffering and they will be non-compliant to treatment.“
“Drawing insights from personality research and behavioural psychology is where we see technology developers headed…”
The next generation of health applications can learn from these insights. The goal should not only be to quantify but to reflect and restore the self. Understanding the narrative of the self – who am I? what’s my story? – this should be a new design criteria for the QS movement.
In the next generation of Quantified Self applications will we see narrative content that reaches the disengaged and unhealthy? Better yet will we see narrative that helps the unhealthiest of users recognize themselves not in a shameful way but one that honours their sense of self and that uses Self Concept to motivate change? If we do, then we can expect to see the Quantified Self Movement get beyond preaching to the converted.
About the author:
Mavis Dixon is the Manager of Engagement and Projects at Ayogo Health. Named “Canada’s Hottest Digital Media Company”, Ayogo applies the psychology of games and play to the challenge of adherence, with a focus on chronic health challenges. Mavis loves the process of discovering how to benefit patients’ health by delivering engaging applications that also deliver value to pharma partners. Her thinking has shaped The Ayogo Model of patient engagement. For more information contact email@example.com or visit ayogo.com or join the linked in group, Patient Engagement: http://lnkd.in/j56UnM
Does the Quantified Self movement only “preach to the converted”?