According to Ben Goldacre, the author of Bad Science:

"The Telegraph reported that red wine prevents breast cancer - with the 
flimsiest of nutritionist-style evidence - just two months after writing that 
alcohol causes breast cancer (the latter is more correct)."

http://www.guardian.co.uk/commentisfree/2008/dec/27/bad-science-2008-media-roundup

Thus we come full-circle back to the discussion of alcohol and cancer.

Rick

Dr. Rick Froman, Chair
Division of Humanities and Social Sciences Box 3055
x7295
[email protected]
http://tinyurl.com/DrFroman

Proverbs 14:15 "A simple man believes anything, but a prudent man gives thought 
to his steps."


-----Original Message-----
From: Paul Brandon [mailto:[email protected]]
Sent: Thursday, February 26, 2009 9:42 AM
To: Teaching in the Psychological Sciences (TIPS)
Subject: Re: [tips] BBC NEWS | Antidote

Fortunately, the BBC has an antidote: see

http://www.guardian.co.uk/science/series/badscience

On Feb 26, 2009, at 7:53 AM, Gerald Peterson wrote:

> 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.

Paul Brandon
Emeritus Professor of Psychology
Minnesota State University, Mankato
[email protected]


---
To make changes to your subscription contact:

Bill Southerly ([email protected])

---
To make changes to your subscription contact:

Bill Southerly ([email protected])

Reply via email to