I am currently testing a model in organizational behavior where I have several behaviors (B1, B2, B3) that impact positively an attitude (A1). I am trying to prove that another behavior (B4) impacts negatively this attitude.
I have limited knowledge in statistics, but it seems to me that it would be easier for me to prove that the opposite behavior of B4 impacts positively A1 than to prove that B4 impacts negatively A1.
I think these statements are the same. Proving that "B is decreasing A" seems like proving that "-B is increasing A". Both appear the same to me.
Hypothesis testing tries to show that two populations are different, by trying its best to prove that they are equal. Once the researcher failed to prove that those populations are equal, the researcher can be to some extent confident that the two populations are different. So, yes there are positions that for showing something, we try to prove its negative (i.e., the null hypothesis) wrong. But your case doesn't seem something like that.
However, we should hear Every detail about your study, and the nature of B4 and A1 etc. to be able to better discuss it.