Question at position 13 The Women's Health Study randomly assigned nearly 40,000 women over the age of 45 to receive either aspirin or a placebo for over 10 years to examine the effect of aspirin on cancer risk to healthy women. This long-term trial would be best conducted asA single-blind randomized experimentA completely randomized experimentAn observational studyA censusA double-blind randomized experiment

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BlackTom AI · Accepted Answer

When evaluating the design of a long-term trial like the Women's Health Study, it's important to consider both how participants are assigned to groups and how bias is minimized.
Option 1: A single-blind randomized experiment. This would mean either the participants or the investigators are unaware of treatment assignment, but not both. In a cancer risk trial where the treatment is aspirin vs placebo, relying on only single-blind could allow bias to influence behavior or assessment, making this choice less robust than necessary.
Option 2: A completely randomized experiment. Random assignment to groups is a key feature of experimental design and is appropriate here, but this description omits the blinding aspect. While randomization controls for confounding, without double-blinding biases could still creep in during outcome assessment or reporting, especially over a decade-long study.
Option 3: An observational study. This would not involve random assignment to aspirin or placebo; instead it would observe natural variation. That design cannot establish causality as effectively as a randomized trial, so it is not the best approach for assessing a causal effect of aspirin on cancer risk.
Option 4: A census. This means surveying or testing every member of a population. In the context of a long-term study on aspirin and cancer risk among women over 45, a census is impractical and unnecessary; randomized trials sample participants, not the entire population.
Option 5: A double-blind randomized experiment. This combines random assignment with blinding of both participants and researchers, minimizing placebo effects, observer bias, and differential treatment or assessment. Given the long duration and the subtlety of cancer outcomes, this design provides the strongest protection against bias and is the most rigorous choice for evaluating a causal effect of aspirin on cancer risk in healthy women.

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