## **Core Concept**
The specificity of a screening test is a measure of its ability to correctly identify those without the disease, i.e., non-diseased persons. It is defined as the proportion of true negatives (non-diseased persons correctly identified as negative) among all non-diseased persons.

## **Why the Correct Answer is Right**
A test with 90% specificity means that out of 100 non-diseased persons, 90 will test negative (true negatives) and 10 will test positive (false positives). Therefore, 90% specificity implies that 90% of non-diseased persons will give a **negative** test result.

## **Why Each Wrong Option is Incorrect**
- **Option A:** This option is incorrect because a positive test result in a non-diseased person would be a false positive, which is not what specificity measures.
- **Option B:** This option might seem plausible but is incorrect because it does not directly relate to the definition of specificity.
- **Option C:** This option is incorrect because a "positive predictive value" relates to the probability that a person with a positive test result actually has the disease, which is not what is being asked here.
- **Option D:** This option is incorrect because it does not accurately describe what 90% specificity means.

## **Clinical Pearl / High-Yield Fact**
A key point to remember is that specificity and sensitivity are complementary. A test can have high sensitivity but low specificity, or vice versa. Understanding the predictive values and the characteristics of a test (sensitivity, specificity, PPV, NPV) is crucial in interpreting test results in clinical practice.

## **Correct Answer:** B. negative test result.