On the contrary, reporting changes relative to the standard deviation of a control group frees you from scales and their meanings, because it relates the observed change to the normal spread of scores before the intervention. In this way, you don't need to know the scale and its meaning to know if a change is big or small, and from a statistical perspective, that's (almost) all you need to find if a change is significant or due to random chance. Of course, looking back at the original scale and its meaning can help interpreting the meaning of the results in other ways
Standard deviation helps, but you still need to know: standard deviation of what? It's no different than saying someone scored 78% - 78% of what? What is it in the denominator? Also, different scales can represent the same thing differently.
Secondly, the impact of the difference isn't known - you don't know the curve representing the relationship of score to impact. In some contexts a little change is meaningless - the curve is flat; in others the curve is steep and it can be transformational. And impacts only sometimes scale linearly with performance or score, of course.
Without that knowledge, standard deviation means nothing beyond how unusual, in the given population, the subject's performance is.
