In a hypothetical randomized controlled trial with several biases (lack of allocation concealment, no blinding, and high dropout) identify at least three biases and their likely impact on results and interpretation.

In a hypothetical randomized controlled trial with several biases (lack of allocation concealment, no blinding, and high dropout) identify at least three biases and their likely impact on results and interpretation.

• A. Allocation bias may overestimate treatment effect; lack of blinding leads to performance and detection bias; high dropout causes attrition bias; overall harms internal validity.
• B. Only selection bias matters; others are negligible.
• C. Blinding has no effect on bias.
• D. Dropouts do not affect trial results.

Answer: (A)

In randomized trials, internal validity hinges on minimizing biases that can distort the estimated treatment effect. When allocation concealment is lacking, the person enrolling participants might anticipate future assignments and influence who goes into which group, creating systematic differences that can make the treatment look more effective than it is. Not having blinding introduces performance and detection biases: participants, clinicians, or outcome assessors may alter behavior, care, or outcome assessment based on knowledge of the assigned intervention, again biasing the observed effect. High dropout, especially if uneven between groups or related to the outcome, leads to attrition bias, which can skew results and weaken the reliability of the conclusions. Together, these biases threaten the trial’s interpretation by compromising the randomization’s balance and the objectivity of outcome measurement and follow-up. The other options misstate the impact of these biases or ignore their significance—blinding really does matter for bias reduction, and dropouts can substantially affect results, not just be ignored.

In randomized trials, internal validity hinges on minimizing biases that can distort the estimated treatment effect. When allocation concealment is lacking, the person enrolling participants might anticipate future assignments and influence who goes into which group, creating systematic differences that can make the treatment look more effective than it is. Not having blinding introduces performance and detection biases: participants, clinicians, or outcome assessors may alter behavior, care, or outcome assessment based on knowledge of the assigned intervention, again biasing the observed effect. High dropout, especially if uneven between groups or related to the outcome, leads to attrition bias, which can skew results and weaken the reliability of the conclusions.

Together, these biases threaten the trial’s interpretation by compromising the randomization’s balance and the objectivity of outcome measurement and follow-up. The other options misstate the impact of these biases or ignore their significance—blinding really does matter for bias reduction, and dropouts can substantially affect results, not just be ignored.