I am very new to statistics and am trying to figure out the appropriate statistical test to use for a small study.

We only have 38 participants. Half are in the control group (placebo), half are in the treatment group, and the groups are unpaired. Both groups have severity score outcomes assessed pre- and post- treatment/placebo. The severity score outcome is initially on a continuous scale, but these numbers are placed into functional groups (no disease, mild, moderate, severe, very severe). 0 is no disease, otherwise, the categories are separated at regular numeric intervals. The outcomes are not normally distributed, with most of the participants falling in the categories of no disease or mild disease. When looking at the raw data, all of the scores only changed by 1 category or didn't change at all, so the change scores are all either -1 (worse), 0 (no change), 1 (better).

The primary research question is what is the effect of treatment on severity score.

I think one way to do this would be to compare the change scores for the controls versus treatment groups to see if there is a significant difference. I think this would result in 2 independent variables (placebo, treatment) and 3 dependent variables (worse, no change, better). From my reading it seems like the sample size is too small for Chi square, so perhaps I should use Fisher's exact test? I am also wondering if the Wilcoxon-Mann Whitney test is appropriate for this? Or is there another more appropriate test that I haven't considered?

Please help direct me if I'm thinking about this the right way and what would be the most appropriate statistical test. I will be performing the analysis in Stata.

Thank you!