How People Understand Risk Matrices, and How Matrix Design Can Improve their Use: Findings from Randomized Controlled Studies

How can we make risk matrices marginally more interpretable?

This study ran two experiments by changing the structure.

I’ve skipped heaps due to laziness.

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Extracts:

· They discuss the use of logarithmically increasing RM categories, which allows a comparison between risks that span several orders of magnitude

· But, even expert audiences struggle with log scales, with one survey study showing professional ecologists struggled with graphs using log-scales compared to linear, and among engineering students

· They discuss the value of geometric scales, where values increase in geometric values, e.g. 1, 5, 25, 125, 625 – noting it may aid interpretation

· Cell shape is also implicated in comprehension, where the spacing/tick marks help people understand plots with log axes

· E.g. cells to the top-right of the matrix are physically larger than those to the bottom-left, indicating a difference in scale

· They found that “there are changes to the standard format of qualitative and semiqualitative risk matrices (rectangular cells, linear scale labeling, use of a key) that may help them to communicate risk more effectively”

· Image 2 shows a combination of the potential recommendations

· “the primary recommendation for an improved risk presentation format is the use of ordinal, explicitly nonlinear scale labels for matrices with an exponential or otherwise nonlinear increase in likelihood and/or impact along the axes”

· “These types of scales represent the nonlinear change from one cell to another by increasing in a suitable geometric progression”

· “Evidence … also suggests a possible benefit of a “logarithmic” format with increasing spacing between lines, although it should be emphasized that this may not be true for people who are already familiar with risk matrices”

· “It may be worth considering integratingcany information currently in a key onto the matrix,cwhere this is graphically reasonable”

· “Some of these changes (logarithmic matrix; integrated information) may not be subjectively preferred by users on first experience despite their benefits, but opinions are likely to improve swiftly with familiarity”

· “In this pair of online experiments (total n = 2699), we show that risk matrices are not always superior to text for the presentation of risk information, and that a nonlinear/geometric labelling scheme helps matrix comprehension (when the likelihood/impact scales are nonlinear)”

Study: https://doi.org/10.1111/risa.13822

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