Look out for intervention comparisons that are sensitive to assumptions that are made.
Sometimes intervention claims depend on putting together different types of evidence and making assumptions. For example, a claim about the effects of using a screening test may depend on how accurate the test is, assumptions about how the test results will affect intervention choices, and evidence of the effects of the intervention.
When intervention claims depend on assumptions, it is important to consider the basis for the assumptions and to test how sensitive the results are to changes in the assumptions.
For example, a comparison of the effects of different tests (e.g. two different tests for detecting presence of a crop or livestock disease) might require an assumption about what actions farmers will take based on the test results (e.g. how a ‘positive’ test will be dealt with). If it is uncertain what action people will take, it is important to consider how changing that assumption might affect the results of the comparison.
REMEMBER: Whenever intervention claims depend on assumptions, think about whether the assumptions are well-founded and how sensitive the results are to changes in the assumptions that were made.