Ben Goldacre's "Bad Science" column (which is typically great!) is actually with the /Guardian/, not the BBC. It will be interesting to see if Goldacre has something to say about the BBC coverage of the alcohol-cancer study.
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/ ========================== Paul Brandon wrote: > 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])
