Who is Apple ResearchKit for? Well – who is a researcher?
The name “Research Kit,” those first five set of pilot studies and apps, and the associated marketing material would all indicate that the primary target users for Apple’s new open-source software framework are the folks whom we first think of when we think of the word “Researchers”: scientists in university and industry settings. But it seems to me that thinking about the ResearchKit in this way seriously undershoots its potential application and value, both in the short and the long run. Research – exploration, sense-making, hypothesis, testing, and discovery – is not just for Researchers with a capital R.
When it comes to health and wellness, we’re all “researchers”.
Over 50 years ago, the psychologist George Kelly pointed out that all human beings operate as “scientists.” We don’t sit contentedly with our models of how things work; instead, we strive constantly to make sense of the world, conducting daily informal “experiments” to test our ideas, to revise and replace our models, and to adapt. A half-decade later, the emergence of the “quantified self,” the explosion of wearable health, wellness, and fitness monitoring and tracking technologies and applications, and the emergence of self-directed and consumer driven health care, all prove Kelly’s point: every day, ordinary people are driven to conduct personal health and wellness experiments on themselves. “If I cut back on processed sugar,” we ask ourselves, “will I have more energy?” “If I do hatha yoga three times a week, will my numbness from peripheral neuropathy improve?”
Unfortunately, our personal health and wellness “research” are often limited by our understanding of how to run a good experiment. As Kelly himself noted, while we may all explore the utility of our hypotheses, we are very often “naïve scientists.” Not only do we not all know how to run sophisticated experiments, we don’t all have access to simple, easy-to-use research and discovery tools to collect and analyze meaningful personal data and to gain actionable insights and learn over time.
“Research” in Clinical Care: Doctors, Care Teams, and Patients utilized as Applied Researchers
Have you ever found yourself in a physician’s office hearing something like: “Well, the most likely thing is an inflammatory condition – so, first, let’s try a steroid treatment for two weeks and see how you respond”? Even as we conduct experiments on ourselves, our doctors and care teams are doing something very similar, conducting informal diagnostic and treatment experiments as part of the fundamental every-day work of figuring out what’s happening with their patients, testing out treatments, and fine-tuning their practices’ own regular care pathways. Even with the advent of EHRs, these experiments are today almost always conducted very loosely, with minimal to no digital support; in fact, right now, it’s usually on the individual patient (“Schedule a follow up in 3 weeks and then we’ll see how you are doing”) to keep track of his or her own relevant outcomes.
ResearchKit for Everyone
This is where ResearchKit comes in. If we think of the ubiquity of the informal health and wellness experimentation conducted every day by ordinary people, as well as that conducted in clinical practice, it should be possible to build on the ResearchKit and HealthKit platforms to provide tools to empower non-professional researchers to become smarter and more effective health and wellness researchers in their own lives. It should be possible to enable healthcare providers, patients, and care teams to conduct more impactful and insightful applied experiments in clinical practice. And it should be possible to find ways to integrate and combine the data and insights of these masses of informal “researchers” with the data and insights generated by specialized Researchers.
I’m eager to see how we might build on ResearchKit to harness the research and discovery potential of all researchers – which is to say, of all of us.
For more reading on Researchkit, see Ryan Rossier’s comments on its evolution in mHealth Intelligence here.