In spite of my several competing interests, and its relatively low impact factor compared to its supposed peer general medical journals, the club of the big five including The Lancet, JAMA, New England Journal of Medicine and Annals of Internal Medicine, I still think the BMJ is perhaps the best medical journal for a young clinical/medical/health scientist. While other journals go out of their way to be interractive, it seems to me to be in the nature of the BMJ to be engaging and interractive. It is not unusual, in fact it is rather the rule than an exception, to learn more from the BMJ’s rapid responses to an article on bmj.com than from the main article itself.
Reading through BMJ’s triumphal announcement of their decision to go all the way with publishing only untraedited versions of research articles (BMJ pico) in print, about two months ago, I chanced upon a 2003 BMJ article by Gerd Gigerenzer and Adrian Edwards working at the Centre for Adaptive Behaviour and Cognition, Max Planck Institute for Human Development, which they started out by saying:
“The science fiction writer H G Wells predicted that in modern technological societies statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write. How far have we got, a hundred or so years later? A glance at the literature shows a shocking lack of statistical understanding of the outcomes of modern technologies, from standard screening tests for HIV infection to DNA evidence.”
They dispel the notion that this is due to some inherent innumeracy of mankind, and place the charge at the feet of scientists for not representing data clearly enough. In an example, they explore the difference between expressing information as conditional probabilities and as natural frequency:
Conditional probabilities
The probability that a woman has breast cancer is 0.8%. If she has breast cancer, the probability that a mammogram will show a positive result is 90%. If a woman does not have breast cancer the probability of a positive result is 7%. Take, for example, a woman who has a positive result. What is the probability that she actually has breast cancer?
Natural frequencies
Eight out of every 1000 women have breast cancer. Of these eight women with breast cancer seven will have a positive result on mammography. Of the 992 women who do not have breast cancer some 70 will still have a positive mammogram. Take, for example, a sample of women who have positive mammograms. How many of these women actually have breast cancer?
They found that most doctors could not answer the question correctly when framed in conditional probabilities , but could when presented as natural frequencies.
The BMJ version of the article is here, and if you don’t have access to the BMJ, then there is a free pdf version of the same article here.
There is a also a more recent and comprehensive discussion by Gigerenzer and four others about framing statistical information, which is targetted at a much wider readership here and it is free. Although much longer than the BMJ article, reading it is well worth the time and effort.
You may then want to try out this question from this week’s BMJ quiz.
