Teaching Science* at the College Level

This is a revised post from my second blog, Healthy Science, which is now the official site of the Clinical Health Psychology Research Team at the University of Scranton.

It's Spring Break time at my institution, and I have that strange sense that the semester is both flying by and crawling along. This semester is much busier than the last, though I've managed to stay (mostly) afloat as I progress toward the end of my first year. One topic that's been on my mind for a while now (i.e., from before I started here) is how to teach and mentor in the scientific method, in a way that students find engaging?

By "science*," I mean scientific thinking in any discipline. In the physical sciences (biology, chemistry, etc.), it's reasonable to expect that students come to college with at least a rudimentary understanding of what it means to "do science" - run an experiment, write up the results, etc. And those who are majors should be moderately interested in doing this regularly. We wouldn't necessarily have the same expectation of an English or history major, but the methods for these disciplines are more similar than people think. But it seems that psychology is in a unique gap between the perceptions of hard sciences and the perceptions of liberal arts. But unless they had fantastic high school teachers, few students come to psychology with an understanding of what it really MEANS that "psychology is the scientific study of human behavior." And the vast majority haven't a clue that psychology involves biology, chemistry, physics, math, and other subjects they think they want to avoid.

One experience in particular brought this to mind before I started my current job. In my effort to start thinking and acting like a professor, I attended an interesting seminar on the subject of involving more students in research experiences at the undergraduate level. Dr. Jennifer Stanford, a biology professor at Drexel University who researches STEM educational practices, presented evidence that supports the positive relationship between research experiences and graduation rates. (Both student-selected experiences and university outreach programs.) She also noted that these experiences are time- and resource-intensive on the part of faculty, so few are willing to extend their expertise.

More recently, I've spent a lot of time talking with psychology students about what it means to "think like a scientist." I was surprised to realize that even bright students who sign up for research assistantships - who have taken several history, methods, and statistics courses (and some of whom have worked in other research labs) - have a difficult time answering this question. It's clear to me that they recognize the importance of the topic. So why the lack of confidence in their answers? Does this essential, fundamental issue fail to meet the long-term retention threshold? On the contrary, it seems that the answers that make sense to them never are encoded in the first place. My discussions with students continued through Socratic questioning, thought experiments, and examples using topics of individual interest. I'm pleased that these discussions seemed to be productive, and engaging to the students. But why was this the first time they had participated in such a conversation? They're not new to this!

And of course, this brings us back to Dr. Stanford's seminar. One reason that intensive research experiences can be so beneficial is that they allow time for the kind of discussions I had with students, which not all students have access to. Moreover, even students who have access to research positions don't always get the kind of attention they need to facilitate independent thinking. Problem: Being a good teacher and mentor takes time and effort, which many professors don't have. Not putting in the time and effort means we're not doing justice to the mission of higher education. Putting in the time and effort means that something else has to give. Or does it?

For my money, the most helpful aspect of Dr. Stanford's seminar were her suggestions for creative ways to involve large numbers of students in "research" by giving them opportunities to think like scientists. For example, rather than writing a typical research paper at the end of the semester, students at any level write a hypothetical research proposal: an interesting question, a bit about what we know and don't know, and how we would test a hypothesis. This isn't exactly a novel idea, but we tend to reserve it for advanced seminars. Opening it up to introductory courses and allowing students to write about what they find most interesting could have multiple benefits. I planned to use this in my Intro Psych class in the fall, though I switched as the semester approached. In the future, gearing the semester toward this assignment could help to connect the disparate sub-disciplines in psychology, which introductory textbooks (and classes) often fail to do. I did recently use it in my new Health Psychology course, where students did an excellent job of generating original research ideas.

What other ideas are out there? Save me some time by linking to journal articles and other blogs that offer similarly creative suggestions - I know they're out there :)

On Research and Running

Running? If you've been in academia for any length of time, you may have noticed that a considerable number of faculty are runners (or triathletes, etc.). I doubt that academia has THE highest concentration of runners in any field, but I suspect that we'd be high up on the list.* And not casual weekend warriors; serious 5 or 10K runners, half-marathoners, and marathoners. Maybe even an ultrarunner or two. 

Although training and racing are becoming more and more popular, the general public still seems to think that voluntarily forcing your body to move quickly along a stretch of road, track, trail, or treadmill belt would be torture. Some even go as far as to claim that running is "dangerous" - a claim that has not held up well under scrutiny. Though it's true that running is tough on your body and there's risk for injury; if you want to be healthy, why not do something less effortful, like biking? Especially given that academics work long and hard hours outside the classroom? WHY? As a runner, I find this noticeable overlap compelling.

My "running in academia" story. Like many health-conscious undergrads, I went to the gym, and sometimes even jogged outside. (I use the now-pejorative term "jogged," because I had no idea what I was doing then. I just made my way from University City to the Philadelphia Museum of Art, over the Spring Garden Bridge, and back.) I did very little exercise during the transition to graduate school. Like many students, I loved my work but found the daily grind somewhat lacking. I wanted something to focus on, for me, that had nothing to do with work accomplishments or relationships.

I started running for real in 2008, during my third year in graduate school. Two factors contributed to the change: (1) I happened across an inexpensive copy of Hal Higdon's Marathon, the Bible of first-time training advice, and (2) a good friend (and experienced runner) was training for a marathon. I picked up the book thinking that it would be handy for "someday." And as my friend enjoyed company on her training runs, I benefited from observing her motivation and discipline. 

So it started. I ran two miles without stopping to walk. I ran a 5K race. I had something for me, that I could look forward to. No expensive equipment, no special facility needed. I had a crazy idea that turned into a commitment: I signed up for the 2008 Philadelphia Marathon. I spent long hours training between classes, research, clinical work, and a part-time job. My family and friends came to watch the event. I finished the race, and I was hooked.

Six marathons and an ultramarathon in, I transitioned to a faculty position. Because of the upheaval, I decided not to run a marathon during that season. I missed it terribly. I ran a half marathon and somehow injured my hip, which hasn't been the same since. I run on my treadmill most days, but I'm nervous about getting back out on the road, where the injury tends to flare up. Have my research or teaching suffered? Probably not, but my stress level and general well-being have. Something is missing without running.

So, what's the connection? I don't suggest that academics who run do so for the same reasons I do, but perhaps there is some overlap. We tend to be overachievers who are used to (and like?) pushing ourselves to excel. We test our limits. We like time to think - and there's actually precious little of that in a regular day. We're disciplined, and many of us like practicing our discipline in various ways. Running is a great way to say healthy and sane amidst all of the deadlines and meetings. And there's the obvious, and true, "grad school/pre-tenure is a marathon, not a sprint" comparison. I suspect there are many more reasons why academia and running mesh well. Share your ideas in the comments!

*A quick Google search reveals no such list, but perhaps Runner's World can take up the charge!

On Being an Early-Career Researcher in Digital Health: Part 2

Recap. Research in digital health (eHealth, mHealth, big data in healthcare) is a hot area with considerable room for growth. But working in this field has some potential pitfalls that early-career researchers (ECRs) need to consider before jumping in. Last time, I described some of the expenses associated with this work and some ways that ECRs can plan for these. I also noted that this work is time-consuming, which is today's topic.

Time is a commodity in academia, and the stress of effectively managing one's time is especially high for ECRs - we're just getting the hang of what works and what doesn't, after all. Of course, any research project* can be time- and effort-consuming, and perhaps more so for ECRs. We're less likely to have large collaborative networks, and in our networks, we have less clout than more established researchers. We're also just establishing our labs and identifying responsible RAs. So projects aren't always completed on our intended schedules, and we end up doing much of the work ourselves. This stalls our progress and creates undue worry about achieving tenure. 

In digital health, it's possible that you're actually unable to do all of the work yourself. For example, if I wanted to design a web program to deliver a new intervention, I would need a computer programmer's assistance. Same goes for collecting data in real time via smartphone app. As with reducing costs and/or accessing technology, maximizing the benefits of collaborations is essential for time management. If you're collaborating with non-academics, there is a good chance that your ideas about "complete" and "timely" work will not align with theirs. This could lead to a great deal of time and effort spent chasing down the products you need. See here for some signs that your collaborations are toxic.

Two other considerations about time management in digital health research. It's intuitive to expect that technology will decrease the time and effort that you need to spend managing data collection. Indeed, something like switching from in-person to internet survey administration frees up many hours that would have been devoted to participant supervision. But this exchange is not equal across all devices, platforms, and methods.

Take the aforementioned real-time data collection as an example. Once the app is set up, you just let it run and the data come rolling in, right? Anyone who has ever worked with this type of ecological momentary assessment procedure is laughing right now. Bugs in your app, device problems, and most of all, participant error will take more time to address than you can imagine. And managing the resulting data is a job I would never, ever want.

Similarly, take a web-based behavior change program. Once the platform is set up, even if it's been plot-tested, monitoring use, responding to problems, and managing any participant interaction takes more time than you expect. Students are fantastic and helpful in some respects, but they have myriad other responsibilities and will never treat the project with the same care you will. One more reason to pursue funding as early and often as possible: if you have professional staff, you don't have to bear this burden yourself. (It is my goal in life to get a grant that allows me to hire a professional research coordinator.) 

Finally, keeping up with advancements in the field presents unique challenges in digital health. As noted, the field is exploding, with new papers and journals appearing every week. Moreover, technology evolves, especially in commercial industry, at an alarming rate. By the time you hear about a device or platform, design a study, learn how to use the technology, hire/train others, and collect the data, your technology is out of date. Then you have to write papers, wrangle any collaborators, deal with peer review and rejection.... by the time you actually publish your findings, the current technology is much more sophisticated than what you used. If behavioral science is your field, then the technology matters less than the way it's used. But if not, have a plan for how you'll deal with criticisms about living in the digital past.

What other challenges do you see for digital health ECRs, or ECRs more broadly? Post your comments below.

*I'm currently reading Joel Cooper's Cognitive Dissonance: Fifty Years of Classic Theory, which describes many of the key studies in this social psychology area. It's reconnected me with my incredible respect for social psychology research. You want time-consuming? They use rigorous experimental methods to test complex theories, using multiple moderators, confederates, and elaborate cover stories. Impressive.

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.

First-Year Faculty: Survival Skills

Evaluating advice. As a new faculty member, I've had a lot of people offer their advice on how to be successful. (I've also sought a lot of advice, as noted.) Much of what I've absorbed as been spot on and immensely helpful. Though I have raised my eyebrows in surprise and skepticism more than once, which also has been useful. As we come to the end of the first semester, here are my tips for surviving the first year.

(1) Read, read, read. You're not alone. Thousands have made this transition before, and hundreds have shared their advice in books and blogs. Make a habit of searching for their tips; download Kindle books, search Google and Twitter, follow links from blog to blog. No matter how busy you are in the few months before you start, you can set aside a few minutes per day to prepare yourself. My list included:

• From Student to Scholar: A Candid Guide to Becoming a Professor - Cahn & Stimpson
• The Academic Self: An Owner's Manual - Hall (particularly good for promoting self-awareness and reducing egotism)
• What They Didn't Teach You in Graduate School - Gray & Drew
• Preparing for Your First Year as a Faculty Member - compiled by Brown University
• Get a Life, Phd (blog) - Tanya Golash-Boza

(2) Trust your training. Much of what you'll read warns that an academic job is unlike training. It's true that you haven't done this job before, and that neither grad school nor postdoc fellowship prepared you for exactly the challenges you'll encounter in your first semester (e.g., politics, managing your own time, managing TAs, preparing lectures, choosing service "opportunities"). But if you made it through graduate and postdoc training successfully, then you know how to juggle classwork, academic writing, meetings, requests from supervisors, and student assistants. 

The difference is that no one tells you which of these to work on at any given time. This may require some adjustment, and might seem overwhelming at first. Rely on the techniques that got you through training - lists, designated work time, working (or not) from home, or whatever helped you be successful to this point. Those can keep working for you if you adapt them to your new situation.

(3) Work on long-term mind. You kept your eyes on the prize (an academic job) for years, and it helped get you through some tough moments. Well, it starts all over again, with the new prize of tenure several years away. As frustrating as this can be, you know how to do it. And what's different is that now you can work on the projects that are most meaningful to you. Write the papers that matter to you; choose your assistants based on your own values and goals. Chip away a little bit at a time and mix in some relaxation. Remember that you don't have to do everything at once. You have a few years to make your tenure case, so plan thoughtfully.

(4) Pick your battles, but stand up for yourself. As the new kid, well-intentioned colleagues will offer you their insights, and only some of these pearls of wisdom will be solicited. Some of it will inspire gratitude, and some of it will make your blood boil - particularly if it comes across as unnecessarily condescending. No matter what the culture of your institution or department, they hired YOU, and they hired you to be a colleague. As long as you're being reasonable, don't let seniority equal disrespect. When necessary, make your expectations known, and provide warm but firm feedback. (Because not everyone is willing to do this, unacceptable behaviors persist. Often, people are grateful when someone finally says something.) *If you don't preserve your self-respect, you may find yourself bitter and resentful right quick.

Of course, not every technique is optimal for everyone, so I refer back to #2 - do what works! Though do adapt it to your new environment.

I had a fantastic first semester, which included manuscript submissions/acceptances and earning a teaching grant to purchase materials for a new course. It can be done.

#AcWriMo - Academic Writing Month (Part 3)

Ambivalence. As #AcWriMo2014 winds down, I have mixed impressions of my success. I produced what I set out to (and then some), which is gratifying during such a busy time of year. As planned, I:

• Completed and submitted a teaching enhancement grant application
• Completed and submitted my first year self-report
• Finished and submitted two in-progress papers (including my first solo-authored!)
• Make significant progress on a (major) revise and resubmit invitation for my dissertation manuscript

I also submitted four conference abstracts (three with student co-authors), attended the Association of Behavioral and Cognitive Therapies conference to present two posters (one an Obesity & Eating Disorders SIG citation selection), and received word that my submission to the Society of Behavioral Medicine annual meeting was accepted as a paper presentation. All of this is fantastic, and I'm delighted to share the success with students.

Up next, I'll find out whether my department votes to keep me (i.e., the result of my first year report) on Tuesday, December 2nd; I'll hear about the teaching grant sometime before the end of the semester (December 16th). Manuscript submissions? As always, it's anyone's guess. (Though very nice to have them on someone else's plate, so they can linger for a while without complaint from me.) I hope to send the R&R off to co-authors for feedback in the next few days.

So why the ambivalence, if I met my goals? The goal that I didn't meet had much less to to with outcome than with process: I committed to writing for one hour per day (or two half hours), and as noted, I did not meet this goal 2-3 days per week. Even after recommitting to blocking out time, the MWF teaching/office hours/seminar schedule got the best of me. I did meet my goal on two of four Mondays and one of four Wednesdays and Fridays, which is decent considering everything else going on. But every blog, book, and tweet about being a productive writer, from productive writers, recommends a daily writing habit, and there is something alluring about such consistency. 

Perhaps what #AcWriMo has taught me is that I don't need daily writing to be "productive" at my desired level. I can continue to strive for this goal or knuckle down when I need to finish something, but beating myself up isn't necessary. Maybe relief, or disbelief, is manifesting as ambivalence? Either way, maybe it's time to lighten up.

Credit where it is due. I'm immensely grateful to Charlotte Frost at PhD2Published, who started the initiative, and to the hundreds of academics who posted tweets of progress and support. Especially @ATRWibben, @JosephsonJyl, and @iladylayla (aka the Global #AcWri Team) for their company and encouragement during writing episodes. Being part of the community has made the frenzy of #AcWriMo enjoyable. Sign me up for next year!

#AcWriMo - Academic Writing Month (Part 2)

November. The first semester has hummed along at a steady clip for two months. I've had time to get to know colleagues, write and submit, run, and even relax a little. It seemed that I might achieve work-life balance after many years without it. 

Then, BAM - November! This is me on 11/14:

Now I know why November is #AcWRiMo - so easy to get caught up in other tasks! Tomorrow = reflection on the first two weeks, and planning.
— Dr. Danielle Arigo (@DaniArigo) November 14, 2014

Let's review. I knew that it would be a busy month. I had decided to apply for a teaching grant (due 11/3) to buy materials for a new course. I'm traveling for a conference the weekend before Thanksgiving, and then again for the holiday, plus I agreed to  do a guest lecture on eating disorders in a sports psychology course. And that first year self-report, due the 24th, which needs to be drafted early enough that generous colleagues can provide feedback. So I needed to get ahead of the game. 

My #AcWriMo goals included a mix of necessary tasks and additional objectives, which I thought were reasonable:

• Complete teaching enhancement grant
• Complete first year self-report
• Finish and submit two in-progress papers
• Revise and resubmit dissertation manuscript

It started with the teaching grant application. Syllabus for a new course I've never taught, timeline, budget, proposal, and letter of support (which I wrote myself). Despite my head start, there was a bit of cramming the night before to make the pieces cohere. Fortunately, the eating disorders lecture occurred in the same week span as the same topic in my own courses, so there was only a bit of extra work there. Though I learned that four straight hours of teaching with no break = fatigue and the 10,000-step buzz from my FitBit by 1:00 pm. Conference poster is nearly done, I've made steady progress on the revision and first year report. And I submitted one of those in-progress manuscripts.

So where am I? The concrete achievements sound pretty good, except that the workload is catching up to me. I set a goal of writing for at least one hour every day, as I would really like to get into a daily writing habit. The first week went well; I skipped one day, but exceeded the total for the week. I realized that finishing the revisions for an invited resubmission is NOT reasonable, considering the work involved. So I edited that one to "address revise and resubmit invitation," which I can make progress on for the next few weeks. 

But this week, I skipped three days of writing - my teaching days, which are exceptionally busy, and require either early mornings or late evenings to squeeze in writing. One hour isn't that much, so I could have done this. Though I realized that I really, really enjoy having nights off during the week. Right now, I don't think I'm willing to spend two or three nights per week working. I've done it for years and I'm tired. I could feel guilty about this, but I think it's reasonable. I think about Tanya Golash-Boza's commitment to a 40-hour week and wonder if it's possible to achieve it as a junior faculty member. So I have to think of another way.

Some options include:

• Spending less time on Twitter
• Breaking the hour into 20-minute blocks
• Closing the door after office hours, no matter who wants what
• Accepting that MWF are not writing days

I don't like the first or the last; I get a lot from the academic support and suggestion network on Twitter, and I learn about valuable research in my area. And I'm not a quitter. So this week, despite travel, I will schedule time to write each day and commit to sticking with it. Wish me luck.