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The theme of
this blog is “all things evidence and policy”, that is, what works
and doesn’t work to get evidence translated into public health
action. This theme is being highlighted at a symposium I am
chairing at the Epidemiology Congress in Montreal this month
entitled “Epidemiology, Science Policy, and Society--Making More
Effective Use of Data When The Facts Don't Speak For Themselves”.
We will ask leaders in the field to address three questions
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What conceptual
framework works best to help epidemiologists understand and
navigate the process of data translation?
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What have we
learned from our study and practice about what works to
successfully translate data into action?
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What promising
approaches are being used today that can serve as models to make
more effective use of data
Stay tuned for the answers.
Although
facts will sometimes appear to speak for themselves by leading to
a clear cut conclusion, more often than scientists would like, the
facts are not the whole story in persuading people to take a
course of action. This conclusion is the topic of a very
interesting article in Mother Jones magazine recently by Chris
Mooney entitled “The Science of Why We Don’t Believe Science” or
“Rapture Ready-- The Science of Self-Delusion”
http://motherjones.com/print/106166
Examples of failure to navigate this gap between science and
policy are all around us on issues such as vaccines and autism,
climate change, mammography screening guidelines, and other
topics.
Mooney quotes Yale University’s Dan Kahan that “We’ve come to a
misadventure , a bad situation, where diverse citizens, who rely
on diverse systems of cultural certification, are in conflict”.
In looking for a framework from which to approach this challenge,
Mooney’s conclusion is helpful. According to Mooney, “…you don’t
lead with the facts in order to convince. You lead with values—so
as to give the facts a fighting chance.”
How this might be applied in translating epidemiologic findings
into policy? One example I have heard about is one in Kansas
where leaders were reportedly getting no traction in discussing
climate change and getting agreement on actions that could be
taken to mitigate the effects. However, when this issue was
presented as one of environmental stewardship as a part of
Christian stewardship, progress was achieved. Recommended actions,
such as reducing carbon footprints, by those pursuing Christian
stewardship are of the type that would be fully acceptable to
climate change activists coming at the issue from a different
frame of reference. Bottom line: Facts are not stand alone
entities. They take on meaning only in reference to some context,
and epidemiologists and public health professionals need to factor
this in when doing data translation.
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