Thursday, January 22, 2015

On Being an Early-Career Researcher in Digital Health: Part 1

We're back! A late Happy New Year, with wishes that 2015 has started off well. If you're an academic, it's likely that your Spring semester has started. Scranton has the luxury of a long intersession, so we still have 10 days to go. (If I'm being honest, I'll acknowledge that I've been back to work every day in January. Who can resist the call of flexible time to write papers?) You can rub it in when I'm still teaching in May.

I have had a productive intersession so far, and both papers and a fellowship application have given me plenty of opportunity to consider where I want my work to go next. Most signs point to digital tools for health behavior change, though as an early-career researcher (ECR), I hesitate to throw all of my energy in this direction. For a few reasons.

Full disclosure. Digital Health is not my area of specialization, but it is one of my interests, and my work moves more and more in this direction. In fact, this theme has come to unify a few of the disparate threads of my research. This post is a reflection on the opportunities and challenges for an ECR with interest in digital health who does not already have ample funding.

Digital health is a term that encompasses the use of technology in health promotion and healthcare, including mobile health (mHealth, or mobile applications), eHealth (electronic health, or web platforms/email), and wearable technology (Fitbits and the like). As such, it brings together computer programmers and software designers, engineers, medical specialists, big data analysts, entrepreneurs looking to design "the next big thing." And - arguably the most important - behavioral scientists. I'm biased, of course, but hear me out.

For example, I can hardly count the number of recent scientific papers and news articles that point to the simultaneous potential of wearable technology and/or mHealth apps and their failure to promote lasting health behavior change. Nearly all of these articles explicitly name behavioral science as missing or underappreciated in these domains. Indeed, what interests me in this area is identifying the missing link; my recent and forthcoming work has shown preliminary support for improvements to our use of technology-connected online social networks to facilitate and sustain behavior change. 

Each of these publications, including mine, involves a call to arms for larger, more rigorous, more cost-effective tests of improvements to digital health interventions. The time is now to strike in a hot area, which few ECRs ever get to to. Perfect! Except.... damn, this work is expensive and time-consuming. Today, I'll focus on expense; part two will cover the time commitment.

Expense. With wearables, it's the device ($90-$150) for each participant; with new apps or web platforms, it's their development (which I would have to pay someone to do); for either one, the convention is to offer some sort of monetary compensation for participants' time. I did get away with offering only the device and treatment in a recent study; I had 100% retention of 12 participants over four weeks. But this sample size and time frame aren't that impressive.

An obvious source of funding for these needs is a new faculty member's startup package. If you're a new faculty member at a research-oriented institution, and your institution understands the resources required for digital health, and you did your homework before negotiating, skip this section. But let's examine whether this is a common situation. Startup packages seem to be the privilege of only those hired to the tenure track. (A good friend of mine just accepted a non-tenure track, teaching/research faculty hybrid at an R1, and got only enough to cover her statistical software needs.) If you're at a non-R1, you might have to play hardball to get an administrator who is not familiar with digital health to pony up more startup money than s/he believes you deserve.

On, and you may have heard that, in the US and elsewhere, the tenure track is disappearing. So if you're hired into a short-term teaching faculty position, you'll need to write a grant proposal. Are you eligible for internal grants? Pray that the answer is yes; at many institutions, your status excludes you from both internal funds and government grants. Unless you can get a longer-term commitment based on your grant award. Meaning you have to get the grant. 

The same goes for many postdoctoral fellowships in the US. If you're in a formal training program that provides individual funding, great! Again, skip. But a good number of fellowships do not come with project funding, and same goes for internal and external grants. For example, at my postdoc institution, available funds went to graduate students and faculty, not postdocs. (I have heard that this is changing, which is great for the new class.) In health psychology, many organizations that offer small grants for which students are eligible, not postdocs. 

What are your remaining options? Again, without a longer-term commitment from your institution, you won't be eligible for many internal or government grants. The NIH K-series* is one exception (see Part 2). Aside from the K, I took advantage of every possible opportunity for funding on postdoc; most required that I be listed as a co-investigator, as I was not eligible to be the PI, though the project would have been mine. I also applied for ECR grants and fellowships through professional organizations. No luck for me, but I do recommend this route. It can't hurt to try, and your vita will show that you're knowledgeable about the process.

Your other option is collaboration. On postdoc, I was fortunate to be able to collect some pilot data by adding components to existing or new studies that were initiated by my mentors. And, as noted, I ran a pilot with no funding, using devices leftover from a previous study. This worked for me, but it's not the same as having control over study design and fund allocation. For behavioral scientists, sometimes partnering with those in basic science or computer programming will make your applications or final products look stronger to those evaluating them.

Whatever you do, think beyond your first study. If funds are limited, your devices or program will need to last you a while. Can you design a second study, perhaps even in a topic area that isn't quite digital health, so that will benefit from the money you spent on project one? For example, after my upcoming pilot intervention study, my devices will be used as assessment tools in a larger longitudinal project. It was a huge relief to realize that the devices could work for a distinct purpose and interest.

The bottom line. If you're a graduate student or postdoc with interests in digital health, think strategically. Use whatever funding you have or startup you get to purchase materials that will serve multiple purposes. Same goes for any early-career faculty member thinking of getting into the area. Apply for grants as early as possible, and use the money to build toward bigger and better projects. Collaborate. And try to keep up with the newest developments; unfortunately, your ideas and technology will be obsolete in a few months. More on this next time.

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