PurposeWhen individuals underreport risk behaviors, data gathered from public health research and practice will underestimate risk. To date, there is little guidance on if or how reports can be adjusted to better reflect true levels of a risk behavior in a given cohort, sample or, by extension, population. MethodsWe develop the underreporting correction factor (UCF), which can be used to correct estimates of the prevalence of a risk behavior using self-report of the behavior and a specific (but not necessarily sensitive) biomarker. The UCF rests on three assumptions: (1) there is no overreporting of the behavior, (2) the biomarker can only be acquired if the person engages in the behavior, and (3) the presence of the biomarker does not affect reporting of the behavior. We investigate the sensitivity of the UCF to violation of these assumptions and develop confidence intervals for the UCF and the corrected prevalence of the behavior. ResultsThe UCF is most sensitive to the second assumption (biomarker perfectly specific). We apply the UCF to estimates of sexual risk behaviors in various settings using a variety of biomarkers. ConclusionsImplementation of the UCF corrects for underreporting and more accurately quantifies risk in cohorts.