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In biomedical research the use of discrete scales which describecharacteristics of individuals are widely applied for the evaluation ofclinical conditions. However, the number of classes (partitions) used in adiscrete scale has never been mathematically evaluated against the accuracy ofa scale to predict the true cases. This work, using as accuracy markers thesensitivity and specificity, revealed that the number of classes of a discretescale affects its estimating ability of correctly classifying the truediseased. In particular, it was proved that the sensitivity of scales is anon-decreasing function of the number of their classes. This result hasparticular interest in clinical research providing a methodology for developingmore accurate tools for disease diagnosis.

Sensitivity of health-related scales is a non-decreasing function of their classes