Introduction to pictograms, pictographs and icon arrays

Pictograms (also known as pictographs and icon arrays) are used to communicate frequencies of an event and to compare the frequencies among multiple alternatives (see Ancker 2006, Kurz-Milcke 2008 and Lipkus 2007). They are usually intended for communicating risks to the general public and patients through various media. They could also be useful to the regulators, as supplementary visual displays, to help them place benefits and risks in context.

A growing body of research has conclusively shown that when communicating individual statistics, pictograms are more quickly and better comprehended than other graphical formats and can help to prevent patients from being biased by other factors (see Fagerlin 2011, Galesic 2011 and Hawley 2008). One study concluded that pictograms were better than tables and numerical text in providing adequate understanding (see Tail 2010). The use of pictograms (icons) is also found to be a more attractive way to present frequency information to the older and younger generations when compared to verbal presentation e.g. compared to presenting proportions as ¡°1 in 5¡± (see Burkell 2004).

Although simple, information in pictograms can still be perceived incorrectly (see Kasper 2011). Pictograms become ineffective when conveying very small risks (<1%), most probably due to the effect of larger size of the arrays on people¡¯s perception (see Schapira 2001 and Dolan 2012). Presenting the same information using different numerators and denominators, for example 1 in 5 versus 20 in 100 can influence the perceived likelihood of an event. The former representation may be seen as less likely to occur than the latter although they are mathematically the same value (see Burkell 2004). The use of partially-represented icons (e.g. half of a face) may introduce quantitative error in perception and judgement because they tend to be rounded up in the interpretation (see Schapira 2001 and Burkell 2004). The issues surrounding denominator neglect in pictograms have been discussed in more detail elsewhere with some examples on the techniques to reduce it (see Okan 2001). Previous studies have also suggested that pictograms are associated with low clarity and are disliked by patients for medical decision-making, and therefore additional research is required to learn how best to use them in this context (see Elting 1999 and Dolan 2012).

Pictograms can be created in Microsoft Excel quite easily using the bar graph function with symbols to represent the values. There are also several online resources to create pictograms, including the Visual Fraction plotter, the Visual RX calculator and plotter and the Paling Palettes from the Risk Communication Institute).