How does high sensitivity affect the rate of false negatives in a test?

High sensitivity in a diagnostic test is defined as the test's ability to correctly identify individuals who have a particular condition. When a test has high sensitivity, it means that it is very good at detecting the presence of the disease. As a result, the rate of false negatives, which occurs when a test incorrectly indicates that a person does not have the condition despite actually having it, is decreased.

This relationship is crucial for scenarios where missing a diagnosis could have serious consequences. For instance, in screening tests for conditions like cancer, high sensitivity ensures that as many positive cases as possible are identified, thus minimizing the chances of a false negative result where a sick patient is mistakenly classified as healthy. Therefore, a test with high sensitivity is designed to "err on the side of caution," ensuring that it captures as many true positives as possible, while consequently lowering the incidence of false negatives.

In contrast, diagnostic tests that are not sensitive may miss a significant number of cases, leading to increased false negatives. Hence, high sensitivity directly correlates with a lower rate of false negatives in testing scenarios.