Multilevel Mixed Effects Models: Help Nesting Observations I made an experingment were 100 individuals were exposed to 10 different situations (imagine they are watching 10 different paintings).
For each individual and painting we measured variables like body temperature and heart rate (bpm). See here an example of data structure:

Imagine I want to predict individual nevrotism, based on people reactions to the different paintings. And I would like to design this as a Multilevel Linear Model with fixed or random effects (the mixed command in Stata).
I need help with the model design, as we have repeated measures on same people (not independent among them), but also reactions are driven by the painting content (so there is a dependence of variables inducted by paintings)
How would you nest observations and interpret results? Would you make 2 or 3 levels? How?
UPDATE
Images are very different. Body response depends in part on the individual and in part on the image shown. So one image should slow the BPM and the other one should accelerate it, but still I want to use BPM to predict something else which is nevrotism.

If I understand your study design correctly, the only random effect you have is for individuals, so you would most likely want a random slope model across the three time period for each individual.
I don't believe you want to treat visual stimuli as a random effect. It is a condition within your experiment, and it seems like you would want to estimate that as a fixed effect. We expect individual to have some random variation, but we expect visual stimuli to have a systematic effect.
So, just 2 levels should be sufficient.
