Be careful with intervention comparisons where people’s outcomes were not counted in the group to which they were assigned.
Deciding who gets which intervention by chance (randomly) – something like pulling out names from a hat or flipping a coin – helps to ensure that people in comparison groups are similar before they receive an intervention.
However, sometimes people in a study do not receive or take the intervention to which they were assigned. Those people may be different from those who do take the intervention to which they were assigned.
For example, in a study comparing intensive aphasia rehabilitation programmes to usual aphasia therapy, participants in the ‘intense’ group who do not have adequate social support may be vulnerable to dropping out and not attend the whole programme.
So, not including them in the results may mean that the people in the comparison groups are no longer similar- in our example, the ‘intense’ group are now only made up of ‘well socially-supported’ individuals. This may make the intervention appear less effective, than it would if everyone had taken it and be adequately supported. But there is less chance of the results being misleading because of dissimilar comparison groups.
To make sure that the comparison groups are similar in the results, and the comparison is fair, people should be counted in the group to which they were assigned.
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