Using t-test for comparing Likert responses before and after intervention I am testing a hypothesis that states that participants after an intervention will be more likely to perceive themselves as being at risk for disease. Two questionnaires will be used.  One will consist of 5 questions and will measure perceived susceptibility and the the other will consist of 7 questions and will measure perceived disease severity.   
I think the best way though uncertain to analyze these two questionnaires which are rated on 5-point Likert scales is to use a $t$-test but I am not sure of how or the best way to do it. I am looking for suggestions. 
 A: T-tests assess a difference in mean outcome between two groups. In this case, I assume you intend to use your 5 level ordinal response scale as such an outcome. This means that responses will be literally coded as such with the 1 indicating a response of "not at all at risk" and 5 indicating "at very high risk". This is generally considered a valid approach for the analysis of such data.
Your study design allows you to use a special paired t-test for which software is available to compute and test for differences in pre/post responses. In a 1 sample case, without a control group, you might test whether the estimated pre/post difference is consistent with having no difference (a difference of 0). It's generally bad practice to do an intervention study without a control group. This gives rise to the Hawthorne effect.
If you have a control group, then you can use a 2 sample paired t-test to compare pre/post differences between the intervention and control groups. In a future study, it might be useful to consider adjusting for certain variables, like family history, for greater precision. This would require a regression framework.
