falsopozitive

Falsopozitive, or false positives, refer to a test result that indicates the presence of a condition, attribute, or outcome when it is not actually present.

In diagnostic screening, false positives arise among individuals who do not have the condition but test positive. The false positive rate equals 1 minus the test's specificity. The practical impact of false positives depends on disease prevalence; with low prevalence, even tests with high specificity can generate a substantial share of false positives, reducing the positive predictive value.

Common contexts include medical tests (pregnancy tests, cancer screenings, infectious disease assays), security screenings, and automated systems such as spam filters or fraud detectors. Causes include cross-reactivity, measurement error, threshold settings, and issues with data quality or sample handling.

Mitigation strategies include confirmatory testing, using sequential or parallel testing with another assay, adjusting decision thresholds, and applying Bayesian interpretation that accounts for prevalence and prior information. Clear communication of uncertainty and the use of multiple independent criteria can also help reduce unnecessary follow-up actions and anxiety.

Understanding falsopozitive is essential for risk assessment, clinical decision-making, resource allocation, and informed counseling. It highlights the importance of test characteristics (sensitivity and specificity) and contextual factors (prevalence, prior probability) in interpreting screening results.

See also: false negative, specificity, sensitivity, positive predictive value, prevalence, Bayes' theorem.