American Board of Surgery Qualifying Exam (ABS QE) Practice Test

What could introduce confounding bias in a research study?

1. The presence of an unrelated factor affecting both exposure and outcome

2. Awareness of participant group assignments during follow-up

3. Failure to obtain honest responses from subjects

4. Subject loss without accounting for event occurrence

The correct answer is: The presence of an unrelated factor affecting both exposure and outcome

The presence of an unrelated factor affecting both the exposure and outcome can lead to confounding bias in a research study. Confounding occurs when a variable that is not of primary interest influences both the independent variable (exposure) and the dependent variable (outcome). This can distort the perceived relationship between these two variables, making it look as though there is an association when one may not truly exist or altering the strength of a genuine association. For instance, if researchers are studying the effect of a new drug on a health outcome, but there is a third variable (like age) that independently affects both drug efficacy and the health outcome, it can mislead the interpretation of the results. This is why identifying and mitigating confounding variables is crucial in research design and data analysis to ensure that observed effects are truly due to the exposure being studied rather than some other external influence. In contrast, the other factors listed do not directly lead to confounding bias. While awareness of participant group assignments might lead to bias (especially in subjective measures), it does not necessarily confound results. Similarly, honest responses and subject loss are important for validity and reliability but do not inherently introduce confounding bias in the same manner.