
Perceptions of Disease Risk: From Social Construction of Subjective Judgments to Rational Decision Making
Author(s) -
Neil McRoberts,
C. Hall,
L. V. Madden,
G. Hughes
Publication year - 2011
Publication title -
phytopathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.264
H-Index - 131
eISSN - 1943-7684
pISSN - 0031-949X
DOI - 10.1094/phyto-04-10-0126
Subject(s) - regret , risk perception , risk analysis (engineering) , perception , risk aversion (psychology) , actuarial science , affect (linguistics) , disease , management science , expected utility hypothesis , computer science , psychology , economics , business , mathematics , statistics , machine learning , medicine , communication , pathology , neuroscience
Many factors influence how people form risk perceptions. Farmers' perceptions of risk and levels of risk aversion impact on decision-making about such things as technology adoption and disease management practices. Irrespective of the underlying factors that affect risk perceptions, those perceptions can be summarized by variables capturing impact and uncertainty components of risk. We discuss a new framework that has the subjective probability of disease and the cost of decision errors as its central features, which might allow a better integration of social science and epidemiology, to the benefit of plant disease management. By focusing on the probability and cost (or impact) dimensions of risk, the framework integrates research from the social sciences, economics, decision theory, and epidemiology. In particular, we review some useful properties of expected regret and skill value, two measures of expected cost that are particularly useful in the evaluation of decision tools. We highlight decision-theoretic constraints on the usefulness of decision tools that may partly explain cases of failure of adoption. We extend this analysis by considering information-theoretic criteria that link model complexity and relative performance and which might explain why users reject forecasters that impose even moderate increases in the complexity of decision making despite improvements in performance or accept very simple decision tools that have relatively poor performance.