If you want to conclude anything scientifically meaningful, you need to have a control group with a similar intervention but that should not have any effect on the outcome. You must compare the change observed in the intervention group to the change observed in the control group. Without the control group the change you observe may be attributable to anything (including, but not exclusively to, your intervention). By comparing the change between control and intervention group, the effects of everything but of the interventions should cancel out.

Another critical point in such studies is the sampling. It's next to impossible to get a real random sample. Some patients are willing to participate, others are not. If the selection (for whatever reason) is linked, directly or indirectly, to the outcome, then your result can be generalized only to people how would participate. This may severely restrict the value of your conclusions, particularly when you don't know the reasons why patients don't participate.

I strongly suggest to contact a (bio-)statistician to help you plan the study (and to analyze it). Otherwise you take a high risk of producing worthless data. Unless your supervisor has some contact details, this may be a good start to ask for help: https://www.imperial.nhs.uk/research/research-facilities/national-institute-for-health-and-care-research-imperial-clinical-research-facility

First I want to appreciate your question and emphasize that there is no silly question when we seek to gain knowledge. Secondly, your study may benefit from inferential statistics involving the use of paired T-test analysis.