Which statement about test specificity is true?

Which statement about test specificity is true?

• A. It increases false negatives
• B. It has no impact on false positives
• C. A test with good specificity reduces false positives
• D. It is unrelated to disease prevalence

Answer: (C)

Specificity measures how well a test correctly identifies people who do not have the disease. A high specificity means only a small fraction of disease-free individuals test positive, so there are few false positives. That’s why a test with good specificity reduces false positives: among those without the disease, most are correctly labeled negative, leaving fewer misclassified positives. Sensitivity, by contrast, relates to false negatives, since it reflects the test’s ability to detect those who do have the disease. The statement about no impact on false positives conflicts with how specificity works. Prevalence affects predictive values (positive and negative results), not the test’s inherent ability to be specific.

Specificity measures how well a test correctly identifies people who do not have the disease. A high specificity means only a small fraction of disease-free individuals test positive, so there are few false positives. That’s why a test with good specificity reduces false positives: among those without the disease, most are correctly labeled negative, leaving fewer misclassified positives. Sensitivity, by contrast, relates to false negatives, since it reflects the test’s ability to detect those who do have the disease. The statement about no impact on false positives conflicts with how specificity works. Prevalence affects predictive values (positive and negative results), not the test’s inherent ability to be specific.