# Sensitivity and specificity

**Definition**

*noun*

Statistical measures for assessing the results of diagnostics and screening tests wherein sensitivity measures the proportion of the actual positives and specificity measures the proportion of the negatives

**Supplement**

Sensitivity and specificity are concepts used to assess a clinical test. Sensitivity is a measure that determines the ability of a test to correctly classify an individual as sick or *diseased*. It can be calculated using this formula: ^{1}

Sensitivity = a / a+c where a (true positive) / a+c (true positive + false negative) Thus, sensitivity = probability of being test positive when disease present

Specificity is a measure of the ability of a test to correctly classify an individual as healthy or *disease-free*. The formula used to calculate for it is as follows: ^{1}

Specificity = d / b+d where d (true negative) / b+d (true negative + false positive) Thus, specificity = probability of being test negative when disease absent

Parikh and others reckons that sensitivity and specificity are inversely proportional, which means that as the value of sensitivity increases, the value of specificity decreases and vice versa.

*Reference(s):*
^{1} Parikh, R., Mathai, A., Parikh, S., Chandra Sekhar, G., & Thomas, R. (2008). Understanding and using sensitivity, specificity and predictive values. Indian Journal of Ophthalmology, 56(1), 45–50.