I conducted an EFA with Maximum Likelihood and Direct Oblimin Rotation. Following the Kaiser Eigenvalue 1 rule, I identified 6 latent factors. 5 of them are positively loaded, while 1 is not.
Here an example to make it a little less abstract:
Let's say I measure the trust in Jesus (just an example). I got multiple factors like predisposition, how strongly the person believes into heaven, how much time the person spends with studying the bible, how much money the person donates to the church etc pp. Now for 5 of the latent factors the structure makes total sense, but one latent factor (whose items also have positive cross-loadings over 0,2) only has negative loadings. Can I say sth about this last latent factor and it's relation to the other latent factors?
How do I interpret this one negative factor in relation to the other ones?
All that I found so far was aiming at how to interpret negative and positive loadings within one factor, not between multiple factors.