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Well, the model was a long time coming for me. I'm gonna tell you a story. So I came
to CDC in 2003, and I had been doing health messaging work for about two or almost three
decades. I was all excited about representing my work and other people who had done work
in this area to encourage CDC to use some of our findings. I got my little tool kit,
walked in, and did a one-hour presentation and thought everybody was going to get all
excited and say "Yes, yes, we want it." I was really surprised by how silent that room
was. I looked around and I said "Well..?" Nobody said anything and then this kind man
he came to me after the presentation during the coffee break and said "We can't use most
of this stuff." I said "Well why not? I think it's great." And he said "We think it's great
too, we just can't use it." And I said "Well give me some reasons why we can't use it,
because I think it's terrific and you're telling me it's terrific." He said "Well it's population
health. We need much larger samples than you have and we need more messages than you are
showing us, and we need more disease states than you are showing us. These lab studies
only go so far, we really would like some field studies, because we're not sure whether
this is going to generalize in a more natural context. When people are making decisions
in real life, there are many things that are coming at them in addition to messages, and
even messages are coming from lots of different places and we just kind of rely on this data
to make our decisions." So needless to say I was totally devastated and I cut my meeting
short and went home and ate a whole pint of ice cream and thought I would just quit or
get another PHD in public health instead of marketing. So that took about three or four
weeks but then I picked myself up and said "I'm gonna fix this, I'm gonna do something
about it." That was actually the bulk of this tour, where I systematically thought about
different ways in which I could get a larger sample size, get more field work into the
data, make sure that we have many more different types of messages with many different types
of diseases and different types of audiences, and use that data then to create this tool
that we call Advisor for Risk Communication or ARC. And that was the book of ARC.
Well, I'm a health marketer. So as someone who's interested in health, I wanted to design
more effective health communication to make sure that people actually follow the recommendations
in these messages. As a marketer, I wanted to make sure that we could tailor these communications,
because that's what marketing is all about. Marketing 101 is about segmenting your audience,
designing customized programs for the audience and then systematically and rigorously making
sure that those programs work effectively, in other words, getting the best return on
investment for your money for that particular audience. So the ARC model had to have not
only different ideas and tactics for designing health communication, but it also had to have
some way of tailoring the messages as well as ensuring that we could measure the effectiveness
of that message. So that's what that model was designed to do.