Statistics training that works with our innate ability to assess the likelihood of events can help doctors and patients figure the odds of illness better

September 16, 2001

'Natural-frequency' approach may be superior for training people to interpret health tests, judge courtroom evidence and more

WASHINGTON -- Does a positive mammogram mean a woman has breast cancer? Does a positive HIV test mean someone is infected with the virus? As ordinary people confront the laws of probability, the odds of misinterpretation and false alarms rise. Two German psychologists have found a better way to teach basic statistical concepts, based on the way people naturally weigh the odds. This approach can help patients, and the doctors who advise them, more accurately assess the meaning of test results.

Peter Sedlmeier, Ph.D., of the Chemnitz University of Technology and Gerd Gigerenzer, Ph.D., of the Max Planck Institute for Human Development in Berlin, tested their approach using computer-based tutorials that cover basic binary statistical literacy (the outcome is either this or that), that took students up to two hours to complete. The psychologists' findings appear in the September issue of the Journal of Experimental Psychology: General, published by the American Psychological Association (APA).

In their article, Sedlmeier and Gigerenzer contrast two approaches to statistical training. Percentage-based rules would state, for example (using hypothetical numbers), "If a woman undergoing mammography has breast cancer, the probability that she will test positive is 80%." Natural-frequency rules would state, using the same example, "Eight of every 10 women with breast cancer who undergo mammography will test positive." Whereas Percentages view probabilities in light of a fixed number, 100, natural frequencies don't share a common norm.

Still, the authors predicted that the latter approach would be easier for people to learn because it taps a natural ability to count the observable, without having to use symbolic abstraction. Previous research has shown that people calculate the odds of any given event more easily and accurately using natural frequencies, which the authors say represents information in a way that is attuned to our "cognitive algorithms" for reasoning with certain kinds of data.

This may be one reason why typical percentage-based statistical training has been ineffective, say the authors, causing problems when health-care providers counsel patients -- often inconsistently and/or inaccurately -- about the chances of disease associated with (for example) positive HIV blood tests and positive mammograms.

In these cases, doctors and patients have to layer new information, such as an individual's positive mammogram, onto more general information, such as how many people in a given group have breast cancer and how many of those with positive mammograms have breast cancer, to arrive at the odds that the individual in question may actually have the disease.

Sedlmeier and Gigerenzer conducted a series of studies with students at the University of Chicago, the Free University of Berlin and the University of Munich; there was almost no difference in the groups' results. Up to four dozen students took part in each study.

The authors created several different computer-based tutorials that used percentage-based rules or natural-frequency rules, and predicted that the latter would work better. The results were consistent: Students who took the percentage-based rule tutorial showed a substantial short-term increase in performance with excellent transfer, but it decayed over several weeks. People who took the natural-frequency tutorial had a noticeably higher training effect (i.e. they got more cases "right"), equally good transfer to other problems, and, most significantly, no loss of performance after 15 weeks.

Sedlmeier summarizes the results: "Both groups learned, but the natural-frequency group learned better and it lasted longer, with no decay." In their article, the authors propose further research into multi-variable (not just binary) statistical training, training for "shortcuts" in making probability estimates, and the uses of such brief tutorial programs for mathematical and statistical literacy.

For example, they speculate about convenient, cost-effective computer-based tutorials that could teach high-school students how best to evaluate the results of pregnancy, HIV or drug tests. "The teaching of statistical literacy," the authors conclude, "can take advantage of human psychology."

Finally, they point out that statistical smarts increasingly matter outside the doctor's office. For example, jurors must evaluate a greater number of statistical averages and frequencies presented as evidence, and citizens in a growing number of democracies must intelligently evaluate the kinds of information that their governments make public.
-end-
Article: "Teaching Bayesian Reasoning in Less Than Two Hours," Peter Sedlmeier, Chemnitz University of Technology, and Gerd Gigerenzer, Max Planck Institute for Human Development, Berlin; Journal of Experimental Psychology - General, Vol. 130., No. 3.

Peter Sedlmeier can be reached by email at peter.sedlmeier@phil.tu-chemnitz
Full text of the article is available from the APA Public Affairs Office and at http://www.apa.org/journals/xge/press_releases/september_2001/xge1303380.html

The American Psychological Association (APA), in Washington, DC, is the largest scientific and professional organization representing psychology in the United States and is the world's largest association of psychologists. APA's membership includes more than 155,000 researchers, educators, clinicians,consultants and students. Through its divisions in 53 divisions of psychology and affiliations with 60 state, territorial and Canadian provincial associations, APA works to advance psychology as a science, as a profession and as a means of promoting human welfare.

American Psychological Association

Related Breast Cancer Articles from Brightsurf:

Oncotarget: IGF2 expression in breast cancer tumors and in breast cancer cells
The Oncotarget authors propose that methylation of DVDMR represents a novel epigenetic biomarker that determines the levels of IGF2 protein expression in breast cancer.

Breast cancer: AI predicts which pre-malignant breast lesions will progress to advanced cancer
New research at Case Western Reserve University in Cleveland, Ohio, could help better determine which patients diagnosed with the pre-malignant breast cancer commonly as stage 0 are likely to progress to invasive breast cancer and therefore might benefit from additional therapy over and above surgery alone.

Partial breast irradiation effective treatment option for low-risk breast cancer
Partial breast irradiation produces similar long-term survival rates and risk for recurrence compared with whole breast irradiation for many women with low-risk, early stage breast cancer, according to new clinical data from a national clinical trial involving researchers from The Ohio State University Comprehensive Cancer Center - Arthur G.

Breast screening linked to 60 per cent lower risk of breast cancer death in first 10 years
Women who take part in breast screening have a significantly greater benefit from treatments than those who are not screened, according to a study of more than 50,000 women.

More clues revealed in link between normal breast changes and invasive breast cancer
A research team, led by investigators from Georgetown Lombardi Comprehensive Cancer Center, details how a natural and dramatic process -- changes in mammary glands to accommodate breastfeeding -- uses a molecular process believed to contribute to survival of pre-malignant breast cells.

Breast tissue tumor suppressor PTEN: A potential Achilles heel for breast cancer cells
A highly collaborative team of researchers at the Medical University of South Carolina and Ohio State University report in Nature Communications that they have identified a novel pathway for connective tissue PTEN in breast cancer cell response to radiotherapy.

Computers equal radiologists in assessing breast density and associated breast cancer risk
Automated breast-density evaluation was just as accurate in predicting women's risk of breast cancer, found and not found by mammography, as subjective evaluation done by radiologists, in a study led by researchers at UC San Francisco and Mayo Clinic.

Blood test can effectively rule out breast cancer, regardless of breast density
A new study published in PLOS ONE demonstrates that Videssa® Breast, a multi-protein biomarker blood test for breast cancer, is unaffected by breast density and can reliably rule out breast cancer in women with both dense and non-dense breast tissue.

Study shows influence of surgeons on likelihood of removal of healthy breast after breast cancer dia
Attending surgeons can have a strong influence on whether a patient undergoes contralateral prophylactic mastectomy after a diagnosis of breast cancer, according to a study published by JAMA Surgery.

Young breast cancer patients undergoing breast conserving surgery see improved prognosis
A new analysis indicates that breast cancer prognoses have improved over time in young women treated with breast conserving surgery.

Read More: Breast Cancer News and Breast Cancer Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.