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Commentary Clarifies The Different Ways Of Working Together With Other Scientists

Report From An SER Symposium

Special report by Robert A Hiatt

My colleagues, Qing Li, Noel Weiss and Muin Khoury and I put on a symposium on the last morning of the recent 50th Anniversary SER Meeting just completed in Seattle entitled “The Central Role of Epidemiology in Transdisciplinary and Translational Team Science”. It was surprisingly well attended for being at the end of a long program and discussion was lively.

The editor of The Epidemiology Monitor thought that readers might be interested in hearing about the topic of Transdisciplinary Science and that it would be instructive to make some comparisons to the points made by George Kaplan in his interview in the May issue about his popular new book ““Growing Inequality—Bridging Complex Systems, Population Health, and Health Disparities” which he co-edited with Ana Diez-Roux, Carl Simon, and Sandro Galea.

There are in fact some interesting similarities and differences.


Transdisciplinary science, for those who are not familiar with it, is an approach to complex research topics that brings together scientists from multiple, and frequently diverse, disciplines to address common problem, using a common framework of possible causation. The participants in this approach are encouraged to hold their own knowledge lightly, listen to the the perspectives of others and seek, through open and trusting interactions, ways to come up with new knowledge, hypotheses and ideas that they may not have considered working alone or in their own disciplinary field.

It was described by Patricia Rosenfield in the mid 1990’s as distinguished from multidisciplinary science where scientists from multiple disciplines attacked a common problem, but stuck to their own skills and knowledge base and from interdisciplinary science where there was more interaction between team members, but still the contributions were coming primarily from their own disciplinary perspectives. Transdisciplinary science looks for a blending of ideas, novel approaches and unexpected new knowledge.

Transdisciplnary science has itself been a topic of study for some decades and the reader is referred to the work of Dan Stokols and Kara Hall who have both written extensively on the topic from their positions in the School of Social Ecology at University of California Irvine and the Nation Cancer Institute’s Division of Cancer Control and Population Sciences, respectively.  The NCI has supported a number of large transdisciplinary initiatives starting in the early 2000’s on topics such as tobacco control, cancer communication, cancer population health and health disparities, energy balance and breast cancer and the environment. The approach invariably draws on the need for team science and the literature frequently uses team science and transdisciplinary science interchangeably. 

Further, as we tried to emphasize in our symposium these approaches are oriented to applications in the service of translational science beyond “the bedside”, a point that Muin Khoury has written about extensively. I like to make the distinction between these processes for epidemiologists by saying that translational science is often best achieved by teams using a transdisciplinary approach. I also think that epidemiologists are highly suited to being key participants if not leaders in transdisciplinary science.


The similarities to the points that George Kaplan made in his interview last month include the interaction of scientists from multiple disciplines and the challenge of getting them to work together. Patience, time and the right settings are needed to get scientists to trust and understand each other’s language and ways of thinking. Sometimes the same word (e.g., race) can mean different things to different disciplines; sometimes the same concept has different words to express it. Having worked with George on a complex systems project, I know what he means when he says that the process of tackling the complexity of disease causation in an interdisciplinary group is “iterative” and “time consuming” but essential.


The difference between complex systems thinking and transdisciplinary science is, I believe, in that the first seeks primarily to understand complex systems of causation as they occur in the real world…not by exploring a “series of independent causes”.

Transdisicplinary science is more of an approach to solving problems, which may or may not be complex. This approach may be in the service of understanding causal relationships or it may be to develop a policy solution facing population health where the causal relationships have not yet been worked out. One doesn’t need to invoke the descriptor “transdisciplinary” to do what George and his colleagues have done in the Network on Inequality, Complexity and Health. However, I believe it is a useful concept for epidemiologists to consider as they seek new knowledge for the benefit of population health. 

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