Evidence-appraisal glossary
Sensitivity
Sensitivity is how well a test detects people who truly have the condition. It is the proportion of people with the disease who correctly test positive. A test that is 95 percent sensitive misses 5 percent of true cases (false negatives). When sensitivity is high, a negative result helps rule the condition out.
Also called: true positive rate, recall.
Sensitivity is a property of a diagnostic test: among everyone who actually has the condition (confirmed by a reference standard), it is the fraction who test positive. It is calculated as true positives divided by all people with the disease. A highly sensitive test produces few false negatives, so a negative result helps rule the condition out, an idea captured by the mnemonic SnNout. When reading a study, check what reference standard defined true disease and in what population sensitivity was measured, because it can shift across settings and disease severity. Sensitivity does not by itself tell you the chance that a given positive result is correct; that depends on how common the disease is. For example, a screening test that is 99 percent sensitive will flag nearly everyone who has the disease, but on its own it says nothing about how many healthy people it wrongly flags, which is where specificity comes in.
This is a plain-language methodology definition for reading research. It is general education, not medical advice.