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Diagnostic tests are regarded as providing definitive information about the presence or absence of a target disease or condition.

There are arguably two kinds of tests used for assessing people’s health: diagnostic tests and screening tests. Arguments are made that sensitivity and specificity should usually be applied only in the context of describing a screening test’s attributes relative to a reference standard that predictive values are more appropriate and informative in actual screening contexts, but that sensitivity and specificity can be used for screening decisions about individual people if they are extremely high that predictive values need not always be high and might be used to advantage by adjusting the sensitivity and specificity of screening tests that, in screening contexts, researchers should provide information about all four metrics and how they were derived and that, where necessary, consumers of health research should have the skills to interpret those metrics effectively for maximum benefit to clients and the healthcare system. Clarification is then provided about the definitions of sensitivity, specificity, and predictive values and why researchers and clinicians can misunderstand and misrepresent them. In this article, therefore, foundations are first established concerning these metrics along with the first of several aspects of pliability that should be recognized in relation to those metrics. Within the context of screening tests, it is important to avoid misconceptions about sensitivity, specificity, and predictive values. Independent academic researcher and author, Albury, NSW, Australia.