**Core Concept**
Sensitivity, also known as the true positive rate, measures the proportion of actual positive cases correctly identified by a test. It reflects the ability of a test to detect disease in individuals who truly have it.

**Why the Correct Answer is Right**
Sensitivity is defined as the ratio of true positives (TP) to the sum of true positives and false negatives (FN). True positives represent cases where the disease is present and the test correctly identifies it. Thus, true positives directly contribute to sensitivity. A high sensitivity means the test rarely misses a true positive case.

**Why Each Wrong Option is Incorrect**
Option A: True negatives reflect the test’s ability to correctly identify healthy individuals and are related to specificity, not sensitivity.
Option C: False positives occur when the test incorrectly identifies healthy individuals as diseased and do not contribute to sensitivity.
Option D: False negatives are cases where the test fails to detect disease in individuals who actually have it; they reduce sensitivity and are thus the opposite of what defines it.

**Clinical Pearl / High-Yield Fact**
Remember: **Sensitivity = True Positives / (True Positives + False Negatives)**. Think of it as "how well the test catches the disease." A test with high sensitivity is crucial in screening to avoid missing cases.

✓ Correct Answer: B. True positives