**Core Concept**
High specificity is a measure of a diagnostic test's ability to correctly identify those without the disease (true negative rate). It is an essential component of a test's performance, as it helps clinicians avoid unnecessary treatments and interventions.

**Why the Correct Answer is Right**
A test with high specificity will have fewer false positives, meaning it is better at distinguishing between individuals with and without the disease. This is particularly important in clinical settings where a false positive result can lead to unnecessary treatment, anxiety, and increased healthcare costs. Specificity is often denoted by the symbol (1 - FPR), where FPR is the false positive rate.

**Why Each Wrong Option is Incorrect**
**Option A:** **Sensitivity** is the ability of a test to correctly identify those with the disease (true positive rate). While sensitivity is important, it does not directly relate to the concept of specificity.

**Option B:** **Positive Predictive Value (PPV)** is the probability that a positive test result actually corresponds to the presence of the disease. PPV is influenced by both the sensitivity and specificity of the test, but it is not a direct measure of specificity.

**Option C:** **Negative Predictive Value (NPV)** is the probability that a negative test result actually corresponds to the absence of the disease. Like PPV, NPV is influenced by both sensitivity and specificity, but it is not a direct measure of specificity.

**Clinical Pearl / High-Yield Fact**
A test with high specificity is not necessarily a good test if it has low sensitivity. This is because a highly specific test may miss many true positives, leading to a high false negative rate. Clinicians must carefully consider both the sensitivity and specificity of a test when making diagnostic decisions.

**Correct Answer: D. True negatives**