TY - JOUR
T1 - Nurses as information providers
T2 - Facilitating understanding and communication of statistical information
AU - Hanoch, Yaniv
AU - Pachur, Thorsten
N1 - Funding Information:
Financial support for this paper was provided by a Minerva fellowship to the first author, and by a Max Planck Society fellowship to the second author. We would like to thank Ulrich Hoffrage, Konstantinos V. Katsikopoulos, Stephanie Kurzenhäuser, Anita Todd and two anonymous reviewers for help with an earlier version. The authors contributed equally to the research and are listed alphabetically. Correspondence concerning this article should be addressed to either author via e-mail: [email protected] or [email protected] .
PY - 2004/4
Y1 - 2004/4
N2 - 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.
AB - 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.
KW - (In) numeracy
KW - Decision making
KW - Genetic counselling
KW - Information providers
KW - Natural frequencies
KW - Probabilities
KW - Screening
UR - http://www.scopus.com/inward/record.url?scp=1842503995&partnerID=8YFLogxK
U2 - 10.1016/j.nedt.2004.01.004
DO - 10.1016/j.nedt.2004.01.004
M3 - Article
C2 - 15046859
AN - SCOPUS:1842503995
SN - 0260-6917
VL - 24
SP - 236
EP - 243
JO - Nurse Education Today
JF - Nurse Education Today
IS - 3
ER -