I think yes, your dependent variable is addiction.

You could do a factor validation (factor analysis) in the first instance.

I would do a multiple regression, taking sociodemographic variables and the var dep in its continuous-numeric form.

Another form of measurement would be loglinear analysis, transforming your dependent variable into a categorical variable with levels of addiction (high, medium, low) and cross-referencing it with other variables that appear important in the previous analyses.

Som Nath Adhikari ,

Before getting into all the technical details, please consider whether it makes common sense. If you are looking at the influence of something like Facebook addiction on academic performance then you need some way of measuring performance, and performance should be your dependent variable. If you are only measuring this once then there is a serious potential problem with your research: you appear to be assuming that there is no relationship between Facebook addiction and prior ability, which I suspect is not the case. For a variety of social factors I would expect that smarter people are less addicted to Facebook and therefore appear to perform better.

Why did you make it Facebook and not "social media" in general? for example. Go across the board and look at other popular sites such as twitter, IG, etc. It appears that you may have introduced bias into your study. Was it social media that started the addiction or did it start before? Which platform showed more of an addiction? How did it affect the person's life? Why do they use this platform? Do the people in your research use other platforms? How any hours per day/week?

By the way I have never done a quant study so I'm asking as a general reader but from a qual researcher mindset.

As Peter Samuels mentions, above, your dependent variable is actually 'performance' as this will depend on 'Facebook addiction' which will be the independent variable.

I agree with Philip and Peter - your DV is academic performance and Facebook addiction is your major IV of interest. A simple linear regression model would tell you the strength and direction of the relationship.

However, this is a 'crude' or unadjusted estimate and there are four things you need to consider next: mediators and moderators (which lie on the causal pathway) and confounders and covariates (which do not lie on the causal pathway). A series of regression models can be fitted to identify and control for the influence of other variables like age, gender, prior academic performance, use of Facebook for study groups versus watching cat videos, etc. A conceptual model showing how you think all the variables are related to each other and to the major IV---DV is a useful way of organizing your analyses and your interpretation of the results.

Academic performances depends on Facebook addiction