lme in R - how do I get differences in mean values?

Hi, my data structure is as follows:

Participants experienced 8 different situations and answered the same questionnaire about their experience in each situation (the questionnaire comprises 8 dimensions, e.g. "positivity"). I wanted to assess how they experienced each situation. Now I want to find out if there are mean differences in the dimensions between these situations. For example, was situation 1 more positively experienced compared to the others?
I figure that I need to calculate a lme because the questionnaire dimensions are nested within situations. However, an lme doesn't give me the results I need.

My R code (package lme4) is as follows:
model <- lmer(data = longdata, formula = value ~ Situation*Dimension + (1|VPCODE) + (1|Dimension))

If I run my analysis like this one situation and one dimension is used as a reference group and the others are compared to this one... But this is not what I want.
I actually want to compare the mean dimensions (e.g. "positivity) between all situations to find out if one situation was experienced more or less XY (e.g. positive) than the others. ...maybe lme is not the golden path here? Does anyone has an idea of a better solution?

God, I am desperate. I so much hope that someone can help me solve this issue.