Evidence-appraisal glossary
Specificity
Specificity is how well a test correctly clears people who do not have the condition. It is the proportion of disease-free people who correctly test negative. A test that is 90 percent specific wrongly flags 10 percent of healthy people (false positives). High specificity means a positive result is fairly convincing.
Also called: true negative rate.
Specificity is a diagnostic test property: among everyone who truly does not have the condition (per a reference standard), it is the fraction who test negative. It equals true negatives divided by all people without the disease. A highly specific test produces few false positives, so a positive result helps confirm the condition, captured by the mnemonic SpPin. When reading a study, look at how the disease-free group was defined and whether it resembles the people the test would actually be used on, since an easy comparison group can inflate specificity. Like sensitivity, specificity is a fixed characteristic and does not directly give the chance that a positive result is a true case; that also depends on disease prevalence. For example, a confirmatory test that is 99 percent specific rarely misfires on healthy people, so a positive result is hard to dismiss, but by itself it does not reveal how many true cases it misses, which is the job of sensitivity.
This is a plain-language methodology definition for reading research. It is general education, not medical advice.