Are the parametric analyses appropriate?

In an experimental study, the aesthetic value (independent var) of a picture is manipulated into (low and high quality). "Low Quality" -- to make it look less appealing; and "High Quality" to make it look "very attractive." I want to examine the effect of "Low" and "High" Quality images on the perception of Mood (dependent var 1) and Affective reation (dependent var 2) of participants. The same participants are exposed to the low quality and high qaulity images. It is one way MANOVA within-subject test design.

**(i) I want to examine if a variation of aesthetic level (low or high) will affect the two dependent var - mood perception and affective reaction.**

>>I am planning to run a MANOVA (since we have two dependent var), and report the "effect size" using Cohen's value, p-value and F-Statistics. What I am not sure is whether we need to run a regression to see how the independent var (two levels: low and high) would affect the two response var and report the value r and r-squared (variability shared among the two dependent var). Please advise how do I proceed.

**(ii) Next I want to measure the level of user engagement (dependent var 3). The user engagement scale has 3 set of components (items): Endurability, Novelty, Focused attention.**

>> Should I conduct a descriptive stastics to find the mean value, higher mean of certain components corresponding to a higher level of engagement with the low or high stimuli?

**(iii) I want to analyze how each of the three components are influenced by the 2 levels of the independent var.**
>>Should I conduct a multiple regression analysis to achieve this?

Kindly confirm that the above analyses are appropriate. Thanks