Skip to Main Content

We have a new app!

Take the Access library with you wherever you go—easy access to books, videos, images, podcasts, personalized features, and more.

Download the Access App here: iOS and Android. Learn more here!

Screening and diagnostic testing are not primary activities of pharmacoepidemiology, but they are important functions of both public health and epidemiology. Assessing the usefulness of a screening or diagnostic test is based on the sensitivity, the specificity, and the predictive value of the test’s results compared with what is actually occurring. One example of testing that is very pertinent to drug use are tests (e.g., urine, hair, breath) designed to assess whether a person has been using certain psychoactive drugs. But, first, there must be a discussion of data quality, including the concepts of validity and reliability with regard to research results.

One of the most important aspects of research results pertains to their validity. Interpretation of research results begins with judgments about their accuracy. The validity of a measure refers to the degree to which it actually measures what it is designed to measure. Internal validity is the extent to which the results of a study accurately reflect the situation in reality, whereas external validity is the extent to which the study’s results are applicable to other populations.

One way of appraising validity is to compare a set of criteria known or believed to be close to reality. In the absence of this kind of criteria, it would be helpful to know the results of any follow-up study showing association between the results of the test and subsequent events (e.g., diseases, drug use problems). Associations between known criteria and other variables are one way of appraising validity, but there are others: developing a consensus of experts’ opinions; using a set of questions that covers all of the essential components of what they purport to measure (i.e., content validity); and using measures that give the same results when repeated (i.e., reliability of the measure).

Reliability is defined as the degree of stability exhibited when a measurement is repeated under identical conditions. In other words, reliability refers to the degree to which a measure or result can be replicated. Lack of reliability may arise from divergence among observers or instruments of measurement or from the instability of the attribute being measured. Reliability is not a guarantee of validity. It is usually measured by performing two or more independent measurements and comparing the findings. The goals of such independent measurements can include determination of whether the observers vary on their measurements (interrater variation), there are differences between measurements made by the same observer at different times (intrarater variation), the measurement instruments differ, or the attribute being measured is itself unstable.

Bias is systematic error in a study that leads to distortion of the results. When bias occurs, the study’s results do not accurately reflect reality. Bias can result during the selection of a study sample or during information and data collection, or it can result from the influence of a confounding variable. Selection bias is an especially important problem in case-control studies. In cohort studies ...

Pop-up div Successfully Displayed

This div only appears when the trigger link is hovered over. Otherwise it is hidden from view.