We are in an era of team science. It’s hard to identify important problems that can be solved by applying the techniques of a single discipline. The translation of biologic insight into something that can actually help someone is a long road requiring more knowledge and skills than any single person can master.
I recently participated in a Workshop sponsored by the Research Centers Collaborative Network that convened researchers from many disciplines to discuss behavior change for older adults. The participants ranged from neuroimagers to economists. The slides and a recording of the proceedings will be available at RCCN-aging.org soon. The Workshop included a session for early-career scientists to help them understand the challenges of multidisciplinary investigation and provide team-building skills. Those slides will not be posted. I shared my observations on how to approach scientists from other disciplines. These are some of the points I made.
- Every scientific discipline has its own culture, and it pays to understand the differences between your culture and those of your collaborators. What constitutes success in another field is useful to know. In medical science, articles in well-cited high prestige journals are a measure of success, but what qualifies as a high prestige journal differs by discipline. Journal articles aren’t as important in informatics where the inclusion in the proceedings of important conferences may be more highly valued. Epidemiologists don’t really care that much about patents, but they are strongly regarded in engineering fields. Differences can come down to the order that authors are listed in published articles. My culture values first and last author placement. But that valuation is not universal, and in some fields publishing works as a sole author is most valued. It’s important to know what counts as a success for your teammates to ensure that team participation results in products that advance everyone in their discipline.
- Even the standards of what constitutes science can differ across disciplines. When I was a graduate student, I was invited to observe a multidisciplinary meeting where my Department Chair and noted cancer epidemiologist, Barbara Hulka, presented an overview of how epidemiologists link environmental exposures to health outcomes. In the Q&A that followed, a physicist stood up and said that epidemiology wasn’t a science and would lead to no useful knowledge. The standards of evidence and inference were so alien to him that he couldn’t accept their conclusions. This is a stark example, but scientists who manipulate animal models sometimes denigrate clinical science because human studies can’t prove mechanistic hypotheses with the certainty of animal studies. Similarly, clinical scientists can denigrate animal research because they feel that animals models don’t relate well to the human condition.
- Every discipline has a set of tacit / assumed knowledge. A sign that you’re maturing in a discipline is that you develop an understanding of the things your colleagues take as given and the things that require logic or evidence to be accepted. On a multidisciplinary team, your teammates will not share this understanding of your field. I’m often asked to provide the rationale behind epidemiologic concepts that other epidemiologists would accept without question. I never respond, “Oh, that’s Epidemiology 101, everyone knows . . . ” Condescension poisons the team. A well-functioning team is a safe place to share and learn. Similarly, a role I can play as a senior member of a team is to ask “stupid” questions to unpack the accepted knowledge in other fields. There is a good chance that other team members will benefit from an explanation, and as a senior scientist I’m not especially concerned about what others will think of me based on such questions.
- Every discipline uses some words that you think you know in precise and controlled ways. When you’re on a team, it’s useful to identify and ask about the meaning of these words to reduce the chances of misunderstanding. For example, many people I work with say the proportion of people with a disease in a population is the “risk” of that disease. Not to an epidemiologist: the risk of disease is the proportion of persons at risk for a disease who develop the disease over a defined period of time. Statisticians have claimed the words “significance” and “power” and given them technical meanings. Misusing words can mark you as a noob and get you dismissed out of hand. I participated in a grant review where the applicant stated that they were going to study post-menopausal mice. I think the applicant meant they were going to study female mice in the last third of their lifespan. The reviewer stated that mice didn’t experience menopause, and by virtue of that mistake the application received no further consideration. Ouch. You can develop a sense of assumed knowledge and how specific words are used by reading in other fields, by hanging around folks in other fields and attending their conferences. But you can’t do this for all fields, so it pays for team members to be aware of these issues to facilitate communication and engender mutual respect.
- It’s important to either elicit or be expressive of: a) What you see as the long-term pay off of a collaboration. Collaborations will drift into conflict if members of the teams are pulling in different directions. b) What your role on the team is going to be. Is it as a full collaborator, or is this a work-for-hire assignment? Lack of clarity on this point is a source of frustration, especially among early-career team participants who may be overlooked as collaborators due to their junior status. c) How credit will be shared. Early-career scientists can be asked to do the lion’s share of the work on a project only to receive minimal credit. It’s best to have this stated in advance to stave off frustration later on.
The Aging Report 