I agree with Chris about the value of the Gigerenzer article. It
also inspired me to think of how we might help our graduating
students teach health professionals about assessing medical
research and communicating risk assessments more clearly to their
patients. I think psych students--even undergrads, often have a
good research and stats background that might be of use in the
areas of consulting and training of health professionals. I wonder
if others have students trying to establish such a career track?
Gary
"Christopher D. Green" <[email protected]> 2/26/2009 8:41 am >>>
Yesterday in my "rant" about the BBC (and other media) coverage of the
recent correlational alcohol-cancer study (below), I mentioned Gerd
Gigerenzer's work on how commonly-used conventions about the reporting
of medical statistics misleads many people (including doctors)
about the
real risks involved. (Indeed, there is evidence that some
pharmaceutical
companies intentionally manipulate the format of statistics to
maximize
the appearance of benefit and minimize the appearance of risk.)
For anyone interested, I have a pdf of Gigerenzer's latest and most
detailed publication in this vein:
"Helping Doctors and Patients Make Sense of Health Statistics"
(/Psychological Science in the Public Interest/, 2008). I've attached
the abstract of the article below. It is longish (44 pp.) but it is so
good that I have been thinking about basing an entire course around
it.
The widespread misunderstanding of cancer and AIDS rates (and the
tests
that are supposed to detect them) are used as examples throughout.
Although I normally teach the standard statistics course in my
department (t, r, F, etc.), a course based on this information
would be
of much greater benefit to much wider range of students.
Because the file is 1.8Mb, I don't want to clog up the entire list
with
it, but I would be happy to forward a copy to anyone who asks me (off
list, please).
Regards,
Chris
--
Christopher D. Green
Department of Psychology
York University
Toronto, ON M3J 1P3
Canada
416-736-2100 ex. 66164
[email protected]
http://www.yorku.ca/christo/
==========================
SUMMARY Many doctors, patients, journalists, and politicians alike do
not understand what health statistics mean or draw wrong conclusions
without noticing. Collective statistical illiteracy refers to the
widespread inability to understand the meaning of numbers. For
instance,
many citizens are unaware that higher survival rates with cancer
screening do not imply longer life, or that the statement that
mammography screening reduces the risk of dying from breast cancer by
25% in fact means that 1 less woman out of 1,000 will die of the
disease. We provide evidence that statistical illiteracy (a) is common
to patients, journalists, and physicians; (b) is created by
nontransparent framing of information that is sometimes an
unintentional
result of lack of understanding but can also be a result of
intentional
efforts to manipulate or persuade people; and (c) can have serious
consequences for health.
The causes of statistical illiteracy should not be attributed to
cognitive biases alone, but to the emotional nature of the
doctor--patient relationship and conflicts of interest in the
healthcare
system. The classic doctor--patient relation is based on (the
physician's) paternalism and (the patient's) trust in authority, which
make statistical literacy seem unnecessary; so does the traditional
combination of determinism (physicians who seek causes, not
chances) and
the illusion of certainty (patients who seek certainty when there is
none). We show that information pamphlets, Web sites, leaflets
distributed to doctors by the pharmaceutical industry, and even
medical
journals often report evidence in nontransparent forms that suggest
big
benefits of featured interventions and small harms. Without
understanding the numbers involved, the public is susceptible to
political and commercial manipulation of their anxieties and hopes,
which undermines the goals of informed consent and shared decision
making. What can be done? We discuss the importance of teaching
statistical thinking and transparent representations in primary and
secondary education as well as in medical school. Yet this requires
familiarizing children early on with the concept of probability and
teaching statistical literacy as the art of solving real-world
problems
rather than applying formulas to toy problems about coins and dice. A
major precondition for statistical literacy is transparent risk
communication. We recommend using frequency statements instead of
single-event probabilities, absolute risks instead of relative risks,
mortality rates instead of survival rates, and natural frequencies
instead of conditional probabilities. Psychological research on
transparent visual and numerical forms of risk communication, as
well as
training of physicians in their use, is called for.
Statistical literacy is a necessary precondition for an educated
citizenship in a technological democracy. Understanding risks and
asking
critical questions can also shape the emotional climate in a
society so
that hopes and anxieties are no longer as easily manipulated from
outside and citizens can develop a better-informed and more relaxed
attitude toward their health.
-------- Original Message --------
On 2/25/2009 at 11:57 AM, Christopher Green <[email protected]>
wrote:
Amadio, Dean wrote:
How else is one to study this issue? Much of health research is
precisely
the same, due to obvious ethical concerns, including the research
on alcohol
and heart disease.
Which is precisely why medical research is, in general, so lousy
and its
(often overheated) conclusions keep changing from study to study,
resulting ultimately in lowered public respect for science at large.
What one should do is draw conclusions that are appropriate to the
evidence they are drawn from. If those conclusions are too bland
to be
interesting, that doesn't justify falsely strengthening them to make
them more interesting. And that seems to be what has happened here.
(Note that "causes" is feature[d] in the very first sentence of
the article.)
This is also old news (there are previous studies which find the
same
relationship among women). I've been advising my students for
several years,
especially females, to consider the cancer studies whenever they
hear the
research that alcohol is heart healthy.
If those cancer studies are like this one, then I would recommend
that
they ignore them, for they can tell [the students] nothing about
the effect on
their health of drinking moderate amounts of alcohol. They only
tell us
that the global genetics and lifestyles of people who choose to
abstain
from alcohol altogether do not result in cancer quite as much as
those
of people who do not adhere to such a prohibition.
Also, they use global percentages in their presentation of risk,
which
almost inevitably misleads people about the actual increase in
risk of
low base-rate conditions like cancer. (See, e.g., the recent
writings of
Gerd Gigerenzer). For instance, the article says that 5,000 of the
45,000 annual cases of breast cancer are due to alcohol -- an
increase
of 11% they say. The population of the UK is about 60 million.
Half of
the those are female -- 30 million. About 20% of those are
children --
leaving 24 million. (see
http://www.statistics.gov.uk/cci/nugget.asp?ID=6). 45,000 out of 24
million = .0019: 19 in ten thousand women are diagnosed with breast
cancer in any given year. Even if the alcohol-cancer causal link
were,
in fact true, the number of cancer cases would drop to 40,000 which,
against a vulnerable population of 24 million is .0017: 17 in ten
thousand. Now ask yourself the question: Would you change you
lifestyle
dramatically to reduce a risk by 2 in 10,000? And that's if the
causal
link had been established, which it hasn't been.
