A discussion I had earlier today reminded me of an argument I’ve had with friends in the scientific community on multiple occasions. The argument revolves around the belief that conclusions of science, such as the effect of cholesterol on heart disease, suggests specific interventions, such as reducing the dietary fat that we believe causes high cholesterol. In essence, we debate the means by which new scientific evidence should be used to influence public policy and private behavior. Taking strong evidence of a specific causal link between a cause and an undesireable outcome as prescription for a population intervention to remove the causative factor is fraught with danger. There are many reasons for this, but the two most salient are confounding and the law of intendended consequences.
Over the past year, I have had the pleasure of advising the non-profit organization Lybba. Lybba’s vision is closely aligned with the work we’ve been doing at New Media Medicine. This month I accepted a one year Research Fellowship with Lybba; the objective is to complete and apply my PhD research in the context of Lybba’s ongoing projects. Chief among these projects is the Collaborative Clinical Care Network (C3N) which I wrote about a few weeks ago.
I’ve been extremely impressed with the scope of their ambition, the quality and breadth of their team and partners, and the concrete projects they’ve chosen to invest time in. Continue reading
Nearly one quarter of US adults read patient-generated health information found on blogs, forums and social media; many say they use this information to influence everyday health decisions. Topics of discussion in online forums are often poorly-addressed by existing, high-quality clinical research, so patient’s anecdotal experiences provide the only evidence. No method exists to help patients use this evidence to make decisions about their own care. My research aims to bridge the massive gap between clinical research and anecdotal evidence by putting the tools of science into the hands of patients.
Specifically, I am enabling patient communities to convert anecdotes into structured self-experiments that apply to their daily lives. The self-experiment, a type of single-subject (N-of-1) trial, can quantify the effectiveness of a lifestyle intervention for one patient. The patient’s challenge is deciding which of many possible experiments to try given the information available. A recommender system will aggregate experimental outcomes and background information from many patients to recommend experiments for each individual. Unusual interventions that succeed over many trials become evidence to motivate future clinical research.
I’m sharing the current status of my proposal to invite feedback and discussion.
What is Self Tracking??????????
Self-tracking is a process through which we attempt to uncover patterns in our daily lives or environment. Tracking can be used for a variety of purposes, including exploratory (what correlations do I see), explanatory (why does this happen) or experimental (If I change X, Y should happen). Regardless of the specific purpose, our ultimate goal is almost always to develop some model of cause and effect that we can use to inform our future decisions. The discovery of cause-effect relationships and the consequences of interventions is the essential aim of the scientific method. It takes years of education and practical training to understand how to apply methodology to gain valid insights into fundamental questions about cause and effect in some natural or artificial system. Methodology is crucial to avoid developing incorrect conclusions.
However, we must also acknowledge that tracking, modeling and intervening in system is a fundamental human exercise. Continue reading
I had a great time giving an unusual talk at the Quantified Self meetup in SF last week. Several people asked me to post slides online. There were also a few questions we didn’t have time to address to which this is a partial answer.
Self-Experimentation without a Written Record
Tracking my lifestyle changes and related symptoms on an ongoing basis has proved to be challenging. The severity of my symptoms have never been such that I’ve made detailed note-taking a priority. Instead, I slowly evolved a mental methodology for keeping track of my experiences by focusing on one hypothesis at a time and slowly accumulating what I consider to be informative observations and conclusions.
In practice, I mentally maintain two mental ‘records’:
A video link of my talk at the Mayo Clinic Transform Event.