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What is the most likely explanation for the higher proportion of false-positive results in one population compared to another?

The specificity of the test is higher in population A

The specificity of the test is lower in population A

The prevalence of disease is higher in population A

The correct choice reflects the concept of how prevalence impacts the interpretation of test results in populations. When the prevalence of a disease is lower in a population, it inherently leads to a higher proportion of false-positive results. This occurs because the test's ability to accurately identify true positives is significantly affected by the number of actual cases present.

In a low-prevalence population, even tests that have good specificity can yield a substantial number of false-positive results simply because there are fewer true cases to identify. As a result, the likelihood of someone testing positive but not having the disease increases. This statistical phenomenon highlights the importance of considering the context of disease prevalence when evaluating health screening processes and interpreting results.

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The prevalence of disease is lower in population A

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