What type of bias occurs from systematic errors in the assessment of exposure?

Information bias occurs when there are systematic errors in how exposure or outcome data is collected, measured, or classified in a study. This type of bias can lead to inaccurate conclusions about the relationship between exposure and disease because exposure may be misclassified, either overestimating or underestimating its true effect.

For instance, if a study is relying on self-reported data for exposure, individuals may inaccurately recall past events, leading to misclassification. This could skew results, as certain biases in information gathering create errors in the observed associations. As such, maintaining rigorous standards in data collection is critical for minimizing information bias and ensuring that the findings of a study are valid and reliable.

Other types of biases—like surveillance bias, selection bias, and recall bias—address different aspects of potential errors in research design and data collection but do not specifically relate to the systematic errors in assessment of exposure as directly as information bias does. Thus, information bias is the most accurate term describing the systematic errors in the assessment of exposure in epidemiological studies.