Predicting comprehensibility of healthcare signs using drawings from participants: A pilot study of sign evaluation

Abstract

This paper advocates using visual data to evaluate signs, specifically by examining the similarities between signs and drawings produced by end-users based on a sign referent given to them. A similarity score is used to measure the extent to which a sign conforms to users' mental images triggered by the associated referent and to determine whether the sign should be redesigned. Based on the concept underlying the population stereotype production technique, it is argued that a higher similarity score implies higher comprehensibility of the sign. When redesigning is needed, the drawings can also serve as informative feedback for sign modification. This explorative approach is illustrated by a pilot study involving the evaluation of healthcare signs using visual data.