Creating a Collaborative Research Vision for a New Research Team
Post 3 in the Six Team Science Best Practices series
In the previous two posts, we covered the importance of having a research vision and how to craft your own personal vision for your research, as well as how to share that vision with your team to ensure you are in alignment. Here, I share some thoughts on how to work with a new team to create a collaborative research vision. This post is specifically focused on interdisciplinary, team science projects, but it could work for any research team.
I often see groups of researchers get together to respond to a new funding opportunity or to create a research proposal in an area of common interest. Though well intentioned and initially enthusiastic, these groups often struggle to come to an agreement about what exactly they want to do together, without getting caught up in the details of dividing often limited resources or how to bring together their various strands of research into a cohesive research question. As researchers, we are accustomed to viewing the world and problem spaces through our own disciplinary lens and tend to see solutions in terms of what our own approaches and methods can contribute.
(Note: depending on the size of the group, it can be incredibly helpful to bring in or hire a facilitator to help guide these conversations. Many universities have research development professionals or team science facilitators, especially within cancer centers and CTSAs, that can help.)
What is the problem you are trying to solve?
The first step is to come to an agreement on the research problem you’re trying to address, at a very high level. This step may seem straightforward, but the reason team science is so powerful is that it brings together different perspectives. The reason team science can be so challenging is that it requires us to see past our own perspective and to integrate it with that of others! Very few researchers have had any training in doing this aspect of the work. Teams often skip this step, and it frequently comes back to haunt them. Several years ago, I worked with a group interested in submitting a proposal for a large research center, bringing together researchers and clinicians around the question of preventing falls in the elderly by monitoring their walking gait. This large team consisted of specialists in geriatric and hospital medicine, nursing, data science, biostatistics, development of sensors, and others. Each had a radically different view of what the problem space was and what needed to be “solved” based on their disciplinary perspective and past experience. But if the team couldn’t agree on what the actual problem was, how could they begin to solve it? After many facilitated conversations, the group eventually came to agreement on the high-level problem they were trying to solve, which was reducing hospital readmission for elderly patients who had previously fallen by easy-to-monitor sensors that measured the patient’s gait. Once they agreed on that problem space, the team could begin to think more clearly and precisely about how they could both carve up the research space into multiple chunks and integrate their perspectives to magnify their individual contributions.
A few questions that can help your group come to consensus around the problem include (and these will look familiar for those who have read the first post in this series!):
What is the overarching problem we are trying to solve?
How will the world be different if we solve this problem?
Who will be impacted by solving this problem?
What, in tangible terms, would success look like if we were to solve this problem?
By focusing on the problem space and the impact the team hopes to make by working together, the team can move beyond their disciplinary and personal perspectives to create a shared vision.
Or… not. Sometimes these discussions help the team see that they are so far out of alignment that there is really no point in collaborating, and that is an extremely valuable realization to have before investing time and energy in developing a project together. I have seen many teams who have tried to force synergy and alignment in their research projects in order to chase a certain funding mechanism or because they’ve already invested so much time and energy into the collaboration that it feels like a waste to give up. Please always remember that collaboration can be a lot of work, but it should not feel like suffering! (A future post on YANAH (You Are Not a Hamster), TSL’s sister site, will cover why scientists believe they need to suffer in order to do science…)
One other interesting and important aspect of this visioning work is the need for interdisciplinary conversations about approaches and methods, which I will cover in more depth in a future post (Best Practice #2). For now, it is important, again, to remember that we all come at our work from the disciplinary perspectives in which we have been trained and have previously approached problems. Different disciplines may use the same word to mean different things. For example, different disciplines use the word “model” in different ways. Statistical methods, standards for data collection, core data sets that can be leveraged all differ across fields. As above, this is a core strength of team science, but can create confusion and frustration if not kept front of mind during the visioning discussion.
A couple of ways to address this challenge include reminding team members to be explicit when they talk about the work they do, the methods they use (and why), or the ways in which their discipline operates. Invite everyone on the team to speak up early and often when they suspect others are using jargon or using familiar terms in ways that are different than they are used to. Unfortunately, there’s no magic bullet here, just leveraging the innate curiosity that drove us to become scientists and the capacity for asking questions that has been trained into us!
Once you have agreement around this high-level research vision, you can begin to have discussions about how to do the research, which then takes the team into specific aims or research questions. In fact, there may be a number of projects that emerge that could be tackled as part of making this research vision a reality, which could keep your team in business for years to come! (And if that is the case, please think about investing in developing strong team processes through Collaboration Planning as early as possible!!)
By the way, if you are interested in doing a more intensive exercise with a broader group of potential collaborators, I highly recommend reading this paper by Dr. Beth LaPensee and her team at the University of Michigan Institute for Clinical and Health Research (MICHR) on “Research Jams,” an evidence-based approach to focusing groups around research topics. Dr. LaPensee has also created a curriculum to train others in delivering Research Jams.