Practical approaches to user-adaptive visualization in the pharmaceutical industry: age-related differences in graph comprehension

Abstract In business settings, where graphs are often used for decision-making, it is advisable to use graphs that are selected or designed considering the reader’s graph comprehension, which refers to the ability to accurately interpret graphical data within a short, fixed viewing time (on the order of tens of seconds). However, there is little knowledge on how to achieve this in practice. In this study, we conducted an experiment involving 93 pharmaceutical industry employees in Japan to identify how graphs should be selected or designed to adapt to a reader’s level of graph comprehension. The data analysis examined the relationship between graph comprehension and individual characteristics (cognitive abilities, personality traits, and demographic attributes), finding a moderately negative correlation between graph comprehension and age. In addition, for some questions assessing graph comprehension, although the required interpretation was the same, appropriate graph selection more than doubled the number of correct respondents among the older group (aged 51–61; all were employed at the time of the experiment). Furthermore, specific questions that the older group tended to answer incorrectly shared common features such as the type of interpretation required, participants’ familiarity with the graph type shown, and the number of elements present in the graph. Based on these age-related findings, we derived practical approaches for graph selection or design that can be readily applied by graph creators in the pharmaceutical industry. Graphical abstract