Is your dependent variable a scale in the sense that it is composed of several individual Likert-type questions?

If your dependent variable is on a scale with at least five response options you should be fine analyzing your data using ANOVA. If not, you can use a nonparametic approach (e.g., ordinal regression, Kruskal-Wallis, Wilcoxon-Mann-Whitney, and Friedman).

You need to describe your outcome more. It is common in some areas to use methods like ANOVA with a Likert scale, lets say 1-5. But that is generally a bad idea. You might get away with it if your scale is from 1-7 or greater, but still generally a bad idea. I attached research showing empirically why this is so and more appropriate models to apply depending on your outcome variable. Essentially, the distance between categories of 1 and 2 might not be the same as 2 and 3 or 3 and 4, etc. Even if there are numbers on the scale. The psychological distance could be different and different for some people. At best you miss relationships and at worst you have a model that makes no sense. For classic ordinal Likert scales I would go with generalized linear modeling using a cumulative distribution with a probit link function. But the article by Bürkner which is attached goes into more depth.

The outcome variables are 7-point Likert scale variables I use to measure trust from extremely low (1) to extremely high (7). I appreciate all the feedback.