More pithy titles, still ignoring data

Tech Crunch has a great title in a post today:

Your Fitness App Is Making You Fat

Catchy isn’t it? The article goes on to explain the reasoning, drawing on the pseudo-science of journalist Gary Taubes, who has spent more than a decade slamming the research community. Here’s the thing, there is great research on what is missing from apps and wearables. The consistent conclusion, is that apps and wearables are self-monitoring tools. Self-monitoring is a cornerstone of successful behavior change – be it to increase activity (for its myriad health benefits beyond weight loss) or to lose weight. But self-monitoring is not sufficient. Apps and wearables don’t work because they don’t provide feedback. Feedback is what drives engagement and engagement drives long term success. None of that is new. Behavioral science has known it for sometime. It is just new to apps and wearables.

I’m glad to see the tech community paying attention to the outcomes from apps and wearables, but it would be great if it also paid attention to the science – the kind that comes from scientists.

What’s the MATTER?

It was recently announced that Coeus Health, the company I co-founded, was selected as one of the first members of MATTER.

We’re thrilled to be part of this amazing community of healthcare entrepreneurs working to push innovation forward. For the last few months, Coeus has been working out of 1871, another amazing resource Chicago offers to entrepreneurs. We’ve been fortunate to take advantage of the networking and mentoring opportunities at 1871 and are really excited by what we are hearing about the opportunities MATTER will provide.


If it is October, it must be time to raise awareness about breast cancer

Typically this time of year, I roll my eyes at all the posts about raising awareness about breast cancer. As if anyone isn’t aware. My push is always on taking action – because there is a lot we can do to PREVENT breast cancer. Current scientific estimates are that half of breast cancer could be prevented by lifestyle and chemoprevention strategies alone. (To read a great review on this:

A recent post from my colleague Graham Colditz, argues that breast cancer prevention efforts need to start much earlier, and that by doing so, we could prevent 70% of breast cancers!

For an (evidence-based) list of behavioral approaches, click here:

Evidence-based cancer risk assessment

Last week, I had the opportunity to share an evidence-based cancer risk assessment tool with Dr. Oz and his audience.

Your Disease Risk isn’t new, but it remains unique. The internet is increasingly populated by tools that are simply a means for someone to collect data from you and sell it. Your Disease Risk has never done this and I suspect never will. The internet is also full of data, lots of it bad. Just plain and simple, there is a lot of misinformation out there. Your Disease Risk was created by scientists – researchers and clinicians – based on decades of work to understand the causes of chronic disease, including cancer. The Your Disease Risk science has been published in a peer-reviewed journal. The Your Disease Risk team isn’t selling your data, but it also isn’t selling you something. Lots of so called “experts” out there are trying to sell their latest book. To do so, they need to say something different from what has been said before and that means they are going to say what they need to say to get your attention and sell books.

That doesn’t mean everyone online or everyone selling a book is full of bologna. But it does mean you should consider the source of information carefully.

The health behaviors we talked about on Dr. Oz are all evidence based. Salt, processed foods, obesity, diabetes and low vitamin D have all been consistently shown (in LOTS of studies) to increase cancer risk.

If you want a personalized cancer risk assessment (or that for several other chronic diseases including diabetes), head over to

How I do broccoli

When I was on Dr. Oz, we talked about how cooking vegetables can change the nutrient composition. We didn’t have time to go into all the changes – we focused on how microwaving broccoli can reduce the levels of some nutrients and suggested trying broccoli raw or sauteed instead (we didn’t get into on the show, but FWIW, cooking vegetables in the microwave can also INCREASE the levels of other nutrients).

For those of you who typically just eat broccoli microwaved or steamed, I wanted to share a few of my favorite recipes for broccoli other ways

For raw broccoli, Smitten Kitchen’s Broccoli Slaw is a winner. We also swap TJ’s broccoli slaw in for cabbage in this family favorite taco recipe also from Deb.

This broccoli cauliflower salad was a frequent summer side dish in my childhood.

If you haven’t tried roasted broccoli, give this salad from Cookie + Kate a whirl. Kate is also the source of my favorite grab and go to work breakfast. I prep and portion it out in freezer containers and heat up (in ceramic!) as I need it.

Information, knowledge and wisdom

@tedvickey posted this great quote today:

We’re already overwhelmed with data. What we need is information, knowledge and wisdom.
– Dr. John Halamka, CIO of Beth Israel


Halamka gets to the heart of what challenges so many of the health apps currently available to consumers. They collect a lot of data. Sometimes, they make pretty dashboards with that data. But what is consistently missing is the knowledge and wisdom of what that data means, what can be done with it and how.

That’s what scientific experts bring to the table. Our years of training and experience are exactly about how to take all that data (believe me, we collect insane amounts of it in every study) and use it to improve – to make weight loss programs better, to improve the feedback that program participants get, to IMPROVE OUTCOMES.

There are a lot of apps that have been created by some smart teams. Many of them have brilliant programmers. But most of them have never run a behavior change program. They haven’t piloted a new approach and had it deliver unprecedented results (or had it bomb terribly – an equally valuable learning experience).

Yes, those folks can go to PubMed and read all about the research that my colleagues and I have spent decades doing. If they’re lucky, they can find a stellar systematic review and meta-analysis that sums it all up in under 4,000 words. But doing isn’t reading. I can read every Berkshire Hathaway Annual Report, but that doesn’t make me the Oracle of Omaha and I can’t imagine someone suggesting to you that taking investment advice from me is a sound financial decision.  So why are we putting our health data and the opportunities it provides for information, knowledge and wisdom in the hands of amateurs?

Lean Academia

I’ve been taking time away from the lab each day for the past few weeks to learn web application development. I’ll post more about the what and why another time.  This week the connection between my program and my lab work came together in another way.

I’m enrolled in class at Starter School (formerly called The Starter League and Code Academy), which sits with-in 1871, Chicago’s premiere start-up incubator and co-work space. Starter School is a 9-month program that teaches the coding, design and entrepreneurship to build software and start companies. (If you want to learn more about what makes this program unique and awesome, check out this WSJ article and the interview with my classmate Chance).  I’m only enrolled in the first 3 months which focuses on coding and programming.  We do start diving into entrepreneurship and it has been an eye opening experience for me.

Our starting point in those classes was The Lean Start-up by Eric Ries and the How to Build a Startup series on Udacity with Steve Blank.  I wish everyone in academic research would watch Blank’s first lesson (which is done in three videos).  I see a number of parallels to academia worth that I’ve been noodling based only on my teaser introduction to the world of Lean Start-ups.

“Start-ups are not small version of big companies.”  The labs of our senior established faculty (the people with endowed chairs who have four R01s (or used to) at a time) seem like big companies.  They have well established systems for moving their research forward. Processes that they’ve built over years, staff that execute details. But the lab of a newly hired assistant professor can’t operate like a smaller version of that.  I don’t think it should.  In the current funding climate, I think allowing (and encouraging) junior faculty to act and think more like start-ups would increase their likelihood of success and increase their ability to innovate.

In recent years, people within and outside the research community have criticized our grant review process as not really promoting the kinds of innovations and leaps we need to truly tackle our goals (as a cancer researcher, these are often written and framed within our failure to “win the war on cancer”). These commentaries assert that we don’t make the kinds of leaps we hope to make, but instead make small incremental advances in our science.  I’ve heard time and again from my peers about the great novel idea they had that got a response of “No one will fund YOU to do that. You’re too unproven” in some form or another from mentors or peer reviewers. These faculty are like entrepreneurs – they have hypotheses about what will work and they need to test them (in academia, we call this getting pilot data). The problem is that we tend to be resistant to pivoting when the pilot data doesn’t play out.  Our resources are so limited that the pilot data is too often seen as a means of showing we can do “anything” rather than “this thing”. Hypothesis testing in the lean start-up is expected to lead to lots of hypothesis rejection or modification until the hypotheses left to test are so low risk (e.g., should the logo be Pantone 165 or 166?) that spending time and money to test them may not be necessary to launch.

Lean start up also aligns nicely with the calls from some of our best scientists to think about alternatives to the randomized clinical trial.  Randomized trials are expensive and time consuming and not conducive to early data that suggests the intervention/product won’t work in the “real world.”  When data to reject “real world applicability” comes to a lean start-up, it MUST re-evaluate the path.  But a junior faculty member trying to build a lab doesn’t have the ability to pivot a randomized trial or it might be the last one she’s funded to run.  She needs to deliver the study she was funded to.  A greater flexibility in the study designs we let drive our decision making would benefit our field.  We would also benefit from giving our faculty and their NIH program officers more flexibility to adapt and make changes mid-study.

Opening academia up to new approaches to building a research program/lab and new ways of thinking seems at least worth contemplating given our tight funding climate. I’d love to hear others’ thoughts on this!