Five principles of holistic science communication

Community member post by Suzi Spitzer

Suzi Spitzer (biography)

How can we effectively engage in the practice and art of science communication to increase both public understanding and public impact of our science? Here I present five principles based on what I learned at the Science of Science Communication III Sackler Colloquium at the National Academy of Sciences in Washington, DC in November 2017.

1. Assemble a diverse and interdisciplinary team

  1. Scientists should recognize that while they may be an expert on a particular facet of a complex problem, they may not be qualified to serve as an expert on all aspects of the problem. Therefore, scientists and communicators should collaborate to form interdisciplinary scientific teams to best address complex issues.
  2. Science is like any other good or service—it must be strategically communicated if we want members of the public to accept, use, or support it in their daily lives. Thus, research scientists need to partner with content creators and practitioners in order to effectively share and “sell” scientific results.
  3. Collaboration often improves decision making and problem solving processes. People have diverse cognitive models that affect the way each of us sees the world and how we understand or resolve problems. Adequate “thought world diversity” can help teams create and communicate science that is more creative, representative of a wider population, and more broadly applicable.

2. Tell a story

  1. Great science and great stories have something in common—as Frank Sesno explained at the colloquium, both involve “Compelling characters overcoming obstacles to achieve a worthy outcome.” Holistic science communication should therefore integrate diverse facts into a comprehensive message, and tell the story of the research process and results in a way that is engaging and relevant to an audience.
  2. There is a move towards attention-grabbing, tweet-sized science. Be careful to avoid sensationalism and do not shy away from studying complex issues in favor of addressing “tweet-sized problems.”
  3. In order to help our science tell a more complete story that includes more voices and resonates with more diverse audiences, scientists should be less numbers-driven and more willing and eager to incorporate qualitative data and experiential knowledge into their research.

3. Make the message personal

  1. Clearly articulate why people should care about your science. This involves thinking about what matters to the audience and then framing your message in a way that makes it more localized. For example, talk about cause and effect relationships that impact people’s daily lives.
  2. The identity and public perception of the messenger matters. As communicators, we must consider how our own identities might impact the way our message is received.
  3. Be mindful of the “information climate,” or socio-political landscape in which your science will be received. Science communicators need to consider the mental models of their audience members and think about how to best connect with audiences that may be culturally different or resistant to the new information.

4. Communicate with people, rather than to them

  1. It is mutually beneficial for scientists and the public to establish a two-way dialogue. Engaging the public and listening to their input helps scientists make their research more socially valuable and comprehensive, while scientists’ research helps the public make informed, evidence-based decisions. Excluding other voices from what should be an inclusive conversation causes scientists to lose public respect, rapport, and support.
  2. Face-to-face interactions and shared experiences are important for developing relationships and creating learning outcomes. Effective science communicators should aim to create moments that enthuse people to keep learning about our science and asking questions, even after we are gone.
  3. Science communicators need to abandon the information deficit model. The deficit model posits that skepticism or disuse of science stems from the public’s lack of knowledge, and if scientists take time to educate the masses and communicate information, then science-based decision making and public support of science will prevail throughout society. This model does not work! The missing link is not communication, but effective communication.

5. Remember to be a human first!

  1. If we want people to understand and use our science in their lives, we must earn their trust. We should not only communicate our science, but also communicate who we are and where we come from in order to give our expertise context and gain trust as humans.
  2. Scientists are often concerned with maintaining objectivity and eliminating bias. While these goals are understandable in a lab setting with respect to experimental design and execution, they are not attainable, or even desirable, in a real-world setting with respect to complex, transdisciplinary, and controversial societal issues. Scientists should realize that they are not objective actors, and that science is not only biased, but often inherently and unavoidably political. When communicating science, we must acknowledge our own biases and maintain honest and transparent communication with our audience.
  3. Scientists should work with other members of society to create socially-accepted and socially-useful science. First and foremost, the responsibility of science is to deliver to society, and in order to fulfill this social contract, scientists need to collaborate with experts in other disciplines, and establish a natural two-way dialogue with members of wider society in order to ensure that science is meeting the needs of the public.

What other suggestions do you have for thinking critically about your role as a science communicator? How do you remind yourself to always be mindful of your responsibility to society as a scientific researcher and as a citizen?

This blog post is based on a longer version published on the website of the University of Maryland Center for Environmental Science Integration and Application Network (

Biography: Suzi Spitzer is a PhD student in the Marine Estuarine Environmental Sciences Graduate Program at the University of Maryland Center for Environmental Science, USA. She works as a Graduate Research Assistant at the Integration & Application Network (IAN) studying science communication and citizen science. She is researching how effective community engagement and science communication can facilitate collaborative learning between scientists and the public within the context of citizen science.

Sharing mental models is critical for interdisciplinary collaboration

Community member post by Jen Badham and Gabriele Bammer

Jen Badham (biography)

What is a mental model? How do mental models influence interdisciplinary collaboration? What processes can help tease out differences in mental models?

Mental models

Let’s start with mental models. What does the word ‘chair’ mean to you? Do you have an image of a chair, perhaps a wooden chair with four legs and a back, an office chair with wheels, or possibly a comfortable lounge chair from which you watch television? Continue reading

ICTAM: Bringing mental models to numerical models

Community member post by Sondoss Elsawah

Sondoss Elsawah (biography)

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey. Continue reading

Models as narratives

Community member post by Alison Singer

Alison Singer (biography)

I don’t see the world in pictures. I mean, I see the world in all its beautiful shapes and colors and shadings, but I don’t interpret the world that way. I interpret the world through the stories I create. My interpretations of these stories are my own mental models of how I view the world. What I can do then, to share this mental model, is create a more formalized model, whether it is a simple picture (in my case a very badly drawn one), or a system dynamics model, or an agent-based model. People think of models as images, as representations, as visualizations, as simulations. As tools to represent, to simplify, to teach, and to share. And they are all these things, and we need them to function as these things, but they are also stories, and can be interpreted and shared as such. Continue reading

Knowledge synthesis and external representations

Community member post by Deana Pennington

Deana Pennington (biography)

Over a decade ago I became interested in the role of external artifacts in enabling knowledge synthesis across disciplinary perspectives, where external artifacts are any simplified physical representation of real phenomena that enable human manipulation of complex concepts. A simulation model is one example of an external artifact. In general every simplified representation of reality is a model, whether that representation occurs in our heads (mental models), on paper (conceptual models) or in a sophisticated computer-based simulation model. And so I embarked on a research agenda to understand the role of data, models, and other forms of external representations in enabling integration and synthesis across perspectives. Continue reading

Why participatory models need to include cultural models

Community member post by Michael Paolisso

Michael Paolisso (biography)

Participatory modeling has at its heart the goal of engaging and involving community stakeholders. It aims to connect academic environments and the communities we want to understand and/or help. Participatory modelling approaches include: use facilitators, provide hands-on experiences, allow open conversation, open up the modeling “black box,” look for areas of consensus, and “engage stakeholders” for their input.

One approach that has not been used to help translate and disseminate participatory models to non-modelers and non-scientists is something psychologists and anthropologists call “cultural models.” Cultural models are presupposed, taken-for-granted understandings of the world that are shared by a group of people. Continue reading