**Core Concept**
The sensitivity of a diagnostic test refers to its ability to correctly identify those with the disease, expressed as a proportion of true positives out of all actual cases. In this context, it's essential to understand the relationship between true positives, false negatives, true negatives, and false positives in the context of a 2x2 table.

**Why the Correct Answer is Right**
To calculate the sensitivity, we need to determine the true positives (40) and the sum of true positives and false negatives (40 + 960 = 1000). The sensitivity is then calculated as the true positives divided by the total actual cases: 40/1000 = 0.04 or 4%. This low sensitivity suggests that the test is not effective in identifying individuals with diabetes.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect as it only considers the true positives (40) without accounting for the actual cases (1000).
**Option B:** This option incorrectly calculates the sensitivity as 40/80, which only considers the test results (40 positive out of 80) without accounting for the actual cases.

**Clinical Pearl / High-Yield Fact**
When evaluating the sensitivity of a diagnostic test, it's crucial to consider the actual number of cases, not just the test results. A low sensitivity may indicate a test that is not effective in identifying the disease, and further evaluation or revision of the test may be necessary.

**Correct Answer:** C. 4%