When evaluating study results, it is important to have a thorough understanding of bias, which is a systematic error in conducting a study that threatens the validity of the results. Studies with a low risk of bias provide the most valid evidence for clinical decision making and health promotion interventions. The key sources of bias in clinical research are selection bias, performance bias, detection bias, and attrition bias.
Types of Biases Affecting Evidence
(1) Selection Bias
● Occurs when comparison groups have systematic differences in their baseline characteristics that can affect the outcome of the study
● Creates problems in interpreting observed differences in outcomes because they could result from the interventions or the baseline differences between groups
● Randomly allocating subjects to the intervention is the best approach to minimizing this bias
(2) Performance Bias
● Occurs when there are systematic differences in the care received between comparison groups (other than the intervention)
● Creates problems in interpreting outcome differences
● Blinding subjects and providers to the intervention is the best approach to minimizing this bias
(3) Detection Bias
● Occurs when there are systematic differences in efforts to diagnose or ascertain an outcome
● Blinding outcomes assessors (ensuring that they are unaware of the intervention received by the subject) is the best approach to minimizing this bias
(4) Attrition Bias
● Occurs when there are systematic differences in the comparison groups in the number of subjects who do not complete the study
● Failing to account for these differences can lead to incorrectly estimating the effectiveness of an intervention
● Using an intention-to-treat analysis, where all analyses consider all subjects who were assigned to a comparison group, regardless of whether they received or completed the intervention, can minimize this bias
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