Which bias could lead to the misleading conclusion about a study's outcomes?

Detection bias occurs when there is a systematic difference in how outcomes are identified or measured among study groups. This bias can lead to misleading conclusions because it may result in an overestimation or underestimation of the true effects of an intervention or exposure. For instance, if one group is monitored more closely than another, the outcomes detected in that group may appear to be significantly different simply due to the level of scrutiny rather than any real difference in outcomes.

In research settings, where outcomes are often measured through assessments or tests, detection bias can impact the reliability of the results, as the way data is gathered may inadvertently favor one group over another. This can distort the true relationship between the intervention and the outcomes.

Understanding detection bias is crucial for the validity of research findings, as it can impact decision-making in healthcare if not addressed, leading to changes in practices or policies based on flawed evidence. Recognizing and minimizing detection bias is essential for ensuring that the conclusions drawn from a study reflect the true effects of the intervention rather than biases introduced during the data collection process.