Nurses as information providers: facilitating understanding and communication of statistical information.
Nurses are increasingly being called upon to be the conveyers of important statistical information to patients. This trend is particularly evident in the domains of genetics and cancer screening. These new roles, however, demand new competencies, such as the ability to solve statistical problems, and the skill to communicate the answers effectively, as effective communication is an important ingredient in shared decision making. Genetic testing, perhaps more than other medical domains, relies heavily on the use of statistics. Being able to convey statistical information effectively is vital. In this paper, we illustrate the problems health care professionals have had in tackling and communicating statistical information. We introduce the natural frequencies method of solving Bayesian inference problems and review empirical evidence that shows the superiority of this format. Being able to transform probabilities into natural frequencies facilitates correct Bayesian inferences. It is argued that the conventional approach to educating nurses in Bayesian problem solving should be reconsidered and their statistical curriculum should be supplemented with instruction in using the natural frequency format.
Hanoch
Yaniv
Y
Max Planck Institute for Human Development, Center for Adaptive Behavior and Cognition, Lentzeallee 94, Berlin 14195, Germany. yhanoch@mpib-berlin.mpg.de
Pachur
Thorsten
T
D001499:Bayes Theorem; D003657:Decision Making; D005817:Genetic Counseling / Q000706:statistics & numerical data*; D006801:Humans; D008403:Mass Screening / Q000706:statistics & numerical data*; D010353:Patient Education as Topic; D012106:Research / Q000706:statistics & numerical data*