Basically this question just asks "what is power" and asks you to explain that 80% power. Power is 1 - beta (type 2 error), basically when a difference exists and the null hypothesis is rejected is power. So if the Rx detects a mean difference of 0.4 in asthma in the patients in the treatment group, then that data falls in the 80% power range, and its significance is 95% (p<0.05), P value is just the probability of something happening by chance, so you what this to be less that 5% so whatever you observed isn't bullshit.

I hope this helped, and correct me if I'm wrong.

A NOTE TO SIMPLE MINDED STUDENTS LIKE MYSELF ! :

First Step : Power is probability or chance ( that a study will detect a true difference) . So cancel out every single option that says 80 % of subjects ( And I mean every single one of them !!) which is basically every single option from A to D

Second Step : this leaves you with only option E and F which are now questioning your understanding of the p value ( again a probability /chance thats a study will detect a difference when none exists ) In our study all the values obtained were associated with a p value of 0.035 i.e less than 0.05.
(OPTION F )

Third Step : Pick option F

You will find that most of these questions are just a play on words - 80 % probability vs 80 % of subjects to test whether you understand what the term really means

Power = ability to detect a difference between groups (if one exists) P value (<0.05) = probability that results were due to random chance

80% power = 80% chance of the study being able to detect symptom changes, which in this case was 0.4 (AKA 80% chance of detecting a significant p value)

80% chance (power) the study correctly identifies the existence of an association in reality. If an association is determined to exist, >95% chance the study and reality agree with each other (p<.05)