Helen: Welcome to Health Literacy Out Loud. I’m Helen Osborne, president of Health Literacy Consulting, founder of Health Literacy Month and your host of Health Literacy Out Loud.
In these podcasts, you get to listen in on my conversations with some truly remarkable people. You will hear what health literacy is, why it matters and ways we all can help improve health understanding.
Today I’m talking with Dr. David Nelson, a physician who directs the Cancer Prevention Fellowship Program at the National Cancer Institute, or NCI. Prior to this, he worked as an epidemiologist and health communication scientist at the Centers for Disease Control and Prevention, otherwise known as CDC. Dr. Nelson also is the author, lead author and co-author of numerous books and journal articles.
Fairly recently, somebody told me about an NCI workbook about numbers and numeracy called Making Data Talk. I got it and thought it was so good that I wanted to share it with you, the listeners of Health Literacy Out Loud. Happily, somebody at NCI introduced me to one of the workbook authors, Dr. David Nelson. Welcome.
Dr. Nelson: Hello.
Helen: I’m delighted that you’re with us on Health Literacy Out Loud. Let’s take it from the top–how I met you. The first sentence in the introduction to this workbook says, “Communicating scientific data to lay audiences is difficult.” My question to you is why is it so hard?
Dr. Nelson: I’ll start out by saying that communication in and of itself is difficult. Anybody who has ever been in a relationship or has had relationships with anybody might understand that. When you take a topic such as science and health, it’s more complex.
The principles are difficult for a lot of people. Let’s face it. Math and science were not necessarily everybody’s best subjects in school. In fact, there are many people who are quite averse to numbers and those kinds of things.
Helen: When you talk about data, science and health, are you talking only about number-based information or all kinds of science and health information?
Dr. Nelson: The two are interrelated. The book is primarily about data and numbers, but you can’t really talk about scientific numbers without connecting it into the scientific principles and things that go into making research. Surveillance data and the kinds of numbers that we report about are all based in things beyond the numbers themselves.
Helen: You’ve tackled a tremendous amount with this workbook. I’ve since had the pleasure of reading your textbook, Making Data Talk. The workbook is focused mainly on the how-to part.
The sub-title of the textbook is Communicating Public Health Data to the Public Policy Makers and the Press. That includes a lot of information about the whys and those overarching themes behind it. Why did you feel that this was something that needed to be shared?
Dr. Nelson: In watching and observing, and from some of my own experiences, many people who are scientists or involved in the health field think that it’s as simple as if you just tell people unlike scientists or health professionals the numbers, they’ll get it.
Without some understanding in the idea of data communication, it’s basically data with a small D and communication with a capital C.
Helen: What do you mean by data with a small D and communication with a capital C?
Dr. Nelson: When we started out working on this book, we thought it was mostly about how we can simplistically get the numbers across better to people. In reviewing a large volume of literature in various fields, we actually came to the conclusion that you have to understand the communication principles.
For example, it’s about knowing who the audience is, where they’re coming from and what their beliefs might be. You have to really understand what your purpose is for communication because that leads you to select and present data in certain ways. Of course, it’s always done based on what the research really shows and in an ethical fashion.
Helen: That’s really interesting. I just liked the way you framed it. It really resonated with me about communication with a capital C.
All along, I’ve been thinking that I need to understand numbers. A little truth here is that I’m really bad at understanding numbers. It’s not just about scientists giving me statistics that I need to understand. For me, representing a lay audience, is it about understanding how I learn and want to get information?
Dr. Nelson: Yes. It’s also being able to understand what data or numbers mean in the context of what we’ve known before, as well as integrating them into the broader understanding of what people need numbers for.
Generally speaking, people think about numbers for their own particular purposes and not just as a scientific argument of sorts. They look for some sort of practical application in their own lives or to people that they know.
For example, let’s say I said there were 50 cases of influenza in the county of Smith last year. You don’t know if that’s a lot of cases or a small number of cases. If I were to tell you there were 50 cases in Smith County last year and there were zero cases in Smith County the year before, that would mean one thing to you.
If I said that in the year before there were 150 cases of influenza or flu in Smith County, you would have a different understanding of what 50 cases means. You really have to fill that information in so that people understand what you’re talking about.
Helen: If your purpose is that you want me to go get a flu shot, do I even need to know how many flu cases were in my country last year?
Dr. Nelson: Probably not. We scientists sometimes get caught up in our own lingo and talk to people who are not scientists as if they have training in statistics and other kinds of mathematical studies when they don’t necessarily need it. Before I select data, I think about whether I even need to use data.
For example, if I look at areas like prevention of hurricane or tornado-related injuries, I don’t think it’s necessary to quote some studies that say it’s a good idea to go to the basement and to get away from a window. I know there are studies that would show if you do that, you lower your chance of risk.
If what I’m trying to do is convince you that the best way to prevent injury from these kinds of natural disasters is to do that, I would just tell you to take shelter without having to cite the scientific evidence and the numbers to prove that to you. I think about data as whether or not you even need to use it first.
It’s much the same way when you’re having a conversation with somebody. Do you or don’t you need to use a particular word or sometimes even speak at all? Sometimes nodding yes or shaking your head no is all that’s needed.
Helen: Is that a very different mindset? One thing of many that has impressed me so much about you is that you’re a physician and an epidemiologist, and you’re saying that we don’t always need numbers. I always thought it was me saying, “I don’t want those numbers.” You’re saying that it’s really okay not to.
Dr. Nelson: It’s really okay not to, assuming that I as a communicator have thought through who you are as an audience, what my purpose for communication is and whether or not I think data are even helpful for you.
We in science often start from a study, a report or some kind of numbers that are published in official documents, and we want to get that across to you. I don’t think that’s necessarily always a bad idea, but I think that we have to be very specific about what we’re trying to accomplish.
Are we trying to just instruct you about what you should be doing? Are we trying to increase your knowledge about a topic? Are we trying to help you choose between one of two perfectly acceptable options? Are we trying to persuade you to do something?
Scientists often start from a study and a number without starting from an audience and a purpose and thinking about what’s best to communicate.
Helen: We start from the audience and the purpose. What do we as people concerned about health literacy and health communicators do next?
Dr. Nelson: One of the things to do is to just ask people very simply whether they even prefer to hear numbers. We do know there are some people who are not numbers people, in which case I don’t think we should go down that track.
I also don’t want your audience of the podcast to think that we never use numbers. If you think about it, if a scientists only tells you stories or says “do this” or “don’t do that,” at some point you have to know why they think that.
I do think that once you have some understanding of an audience and what your purpose is, then that’s the time to think about what information you need to share with people and with numbers being part of that conversation, but not necessarily the focal point.
I almost always focus in on the story line. What is the one key thing that I’m trying to convey to people? You used an example earlier about a vaccination. I would want to start from that point.
If my purpose was trying to convince more people to get vaccinated, I’d start from that point and then decide whether or not there are any data that might be really helpful for that.
For example, I could say that people who got that vaccine are 10 times less likely to experience influenza compared to those that don’t. That number is actually quite helpful.
Helen: I have long heard that numbers give those of us doing this kind of work an air of authority. If not, it’s just mushy information. Can you see the positive side of using those numbers?
Dr. Nelson: Absolutely. Science is based on numbers, so I don’t want to convey that numbers don’t matter. I just think they need to be used judiciously.
I certainly think that there’s a role. They are a way in which we distinguish ourselves in science by saying that this is actually based on some sort of research that we know about so it’s not just an opinion or my belief about things.
I do think that they have their role and are very important. My goal is for your audience to think about it in a much broader sense. I also think that when we use numbers, we should think about using as few as we absolutely need.
Helen: I know throughout your book your talk about story. You’ve mentioned that already. How would you use data to tell that healthcare story or that influenza story? What would that sound like?
Dr. Nelson: The split between sciences and literature or people who study narrative for a living goes back many decades in this country. That’s unfortunate. I actually think that there’s an opportunity to use metaphors and things like that to help convey numbers in a way that can really help to drive home points.
In the book, we have a couple of examples that we cite. For example, think of the twin towers that were hit on 9/11. The people who were killed in those attacks is an example of how many people die from cancer in this country.
Helen: That’s really powerful. I had never thought of it that way.
Dr. Nelson: You get an idea of that. This is one from several years ago that I used in the book. There are 10 times as many gun dealers in California as there are McDonald’s restaurants. You can see that use of numbers into something that people can understand. That quotation actually comes from the 1990’s. That may not be the case today.
You can see that helping people put numbers in context makes a lot more sense than just saying there were X thousand gun dealers or there were X number of deaths. These are the kinds of comparisons or analogies that can be quite helpful in helping people understand something.
Helen: You talk a lot about the metaphor. I’m a true believer in metaphors and comparing something familiar to something unfamiliar in order to make that clear.
When I think of story, I think of something a little bit bigger that has a character, challenge, setting and some kind of resolution. Can you use data in that too?
Dr. Nelson: You can, but I think that’s actually unusual. Usually I think of metaphor as an easier way to get data across or the story line which is bottom-line message we’re trying to convey to people.
I also think of story as having a beginning, middle and an end. The reality is that in much of research, that’s not quite the case in science and medicine. The story continues on as more information comes out and more research is discovered.
It can be used in the sense of helping to drive home points, but I don’t know that’s the most common use. In fact, I think it’s very rare.
Helen: I was just thinking of that. I was working on a project this morning. I’m working as a plain language writer on a project. It’s a rather cumbersome, therapeutic intervention. It takes some twists and turns unlike those I’ve ever heard before. They also have patient testimonials.
I was thinking of actually framing the nuances of that treatment within the context of a story. Is that along the lines of what might work?
Dr. Nelson: That’s definitely an option to consider, assuming that the science is truly evidence based. If you were to read any major health story, you almost always have some kind of an interview with an individual who might have a particular disease or condition, as well as some statistics, numbers and research all integrated and woven together.
If you think about how people have learned over the past thousands of years, stories played an integral role. In fact, there are still many parts of the world where people don’t have written language and don’t really use numbers in the sense we think of in the Western sense.
Tying things in together is really important and helps those people who prefer to learn in different ways tackle different things.
Helen: I have a real appreciation that you frame it that way.
Stories can be powerful, metaphors can be powerful, and data used appropriately is powerful for the right audience. Is there anything to consider as writers and communicators to put these different pieces together?
I actually will frame this in terms of a concept I’ve been talking about for years. It’s a concept that I call the “ethics of simplicity.” Is there anything to weigh as we put all of these different parts of communication together?
Dr. Nelson: Yes. There’s a real danger of cherry picking. From the psychological world, the terms selective exposure and confirmation bias are pretty well known to people in that world. Generally what it means is that we hear what we want to hear and see what we want to see.
I will give you an example of that. Say a new study comes out that confirms something I already believe. I’m happy to share that information with you. This shows that this policy has a positive impact or this particular medication works. I pass that around to people.
Let’s say two weeks later a story comes out and shows just the opposite. I’m not likely to pass that around to everybody. I’m likely to be searching for all the problems in those studies that in my opinion must have been done poorly because they don’t confirm what I already believe. The ethics of simplicity is a good way to think about it.
We need to really make sure that when we do narrow it down to one or two numbers and a short metaphor that it is accurately conveying what scientific evidence shows, and not just simply showing what we want to pass on to people as being factual when it is opinion based. Perhaps it’s not as simple or as clear as we would be letting on to people.
Helen: It almost gets back to your original point about knowing your audience and, even more, knowing the purpose. Is your purpose to inform or to persuade? You might give different data there.
Dr. Nelson: That’s the real risk. The reality is that much of public health and clinical medicine communication really is designed to persuade. I don’t mean that as a bad thing, I’m very value neutral about that.
If we are in persuasive mode, we had better make sure that the preponderance of the scientific evidence confirms what we’re trying to persuade people to do and that it’s not just our beliefs we’re trying to get across and there isn’t solid science behind it.
Helen: We really need to be looking at what impact all of this information might have on the other person’s life.
Dr. Nelson: Absolutely. What we say really does matter. When we are experts, scientists, health providers, health professionals or whatever other health realm we work in, we have a very strong ethical responsibility to make sure we are accurately conveying information to people.
If we don’t know, we can say we don’t know. If recommendations have changed, we have to explain that to people. We often want scientists to be definitive.
We want experts to be definitive in general and don’t always want things to change, but we also have to try to convey to people that that’s the nature of research. “We thought this for a long period of time. Now we think this, and here’s why.”
Helen: Thank you for validating that. Looking ahead, we’re in the era of technology. Will any of this get easier or harder?
Dr. Nelson: I think it’s not going to change. There’s a belief in this country and in many countries that technology is the solution. I don’t think it’s either a problem or the solution. It can actually help convey some things, particularly visually.
I’ve seen some really wonderful work by a man named Hans Rosling where he has shown, for example, average income across countries and years. He does this really wonderful demonstration where he shows balls moving over the course of time. It’s quite striking for a data person to see somebody be able to do this.
That’s an example that comes to mind where I can see how the technology helps, but you never get away from the core things. Who is the audience? What is the story line? What message are you trying to convey? What is your purpose for communication?
There is a tendency to sometimes be wooed into thinking that we can do this with technology. It’s also really easy with technology to add a lot of bells and whistles, do a bunch of different things, and put a bunch of three-dimensional bar charts in multiples colors. We’ve really lost sight of the key thing we’re trying to show people.
For example, and this is just from looking at charts, often one of the ways to really get the key point home is to actually write the key message on the chart, maybe in the title or with an arrow.
If you can see that things are going up, you can put an arrow to the line showing an upward trend and say, “Such and such cases doubled over a three-year period.” Not only can people see that things have gone up visually, but they can also get the words trying to emphasize that, “Here is the key point.”
Helen: Thank you for that example.
I do want to share with listeners who are probably as eager as I am to learn all of that how-to information. We will have links on the Health Literacy Out Loud website for the book, the workbook and other references you talked about, but I wonder if you could just share a few resources with us right now.
Dr. Nelson: Sure. At the risk of sounding like I’m promoting myself, I want to let listeners know that I don’t receive any royalties from this book because I am a federal employee. I’ve done some of the work on this book on government time, so there’s no promotion of that.
The name of the book is Making Data Talk, and it’s published by Oxford University Press. Also, the Making Data Talk workbook is published by the National Cancer Institute, or NCI.
Helen: Thank you. I have Making Data Talk. I have highlights all over it just filled with examples and dos and don’ts. It’s a wealth of information. The workbook I downloaded as a PDF, so we will have those links on the website.
I want to thank you so much for sharing this information and your views, and reminding us that it’s data with a small D and communication with a capital C. Thank you very much.
Dr. Nelson: Thank you.
Helen: I learned so much from Dr. David Nelson, and I hope that you did too, but Health literacy isn’t always easy. For help clearly communicating your health message, please visit my health literacy consulting website at www.HealthLiteracy.com. While you’re there, sign up for the free e-newsletter, What’s New in Health Literacy Consulting.
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Did you like this podcast? Did you learn something new? If so, tell your colleagues and friends. Together, let’s let the whole world know why health literacy matters. Until next time, I’m Helen Osborne.