It's worth reading the article in its entirety because of how much information is summarized in one place. > They also note that Kirsch’s study lumps all antid

It's worth reading the article in its entirety because of how much information is summarized in one place. > They also note that Kirsch’s study lumps all antidepressants together. This isn’t necessarily wrong. But it isn’t necessarily right, either. For example, his study used both Serzone (believed to be a weak antidepressant, rarely used) and Paxil (believed to be a stronger antidepressant, commonly used). And in fact, by his study, Paxil showed an effect size of 0.47, compared to Serzone’s 0.21. But since the difference was not statistically significant, he averaged them together and said that “antidepressants are ineffective”. In fact, his study showed that Paxil was effective, but when you average it together with a very ineffective drug, the effect disappears. He can get away with this because of the arcana of statistical significance, but by the same arcana I can get away with not doing that. > So. In conclusion, everyone has mapped HAM-D numbers into words like “moderate” in totally contradictory ways, such that one person’s “mild” is another person’s “very severe”. Another person randomly decided that we can only call things “clinically significant” if they go above the nice round number of 0.5, then retracted this. So when people say “the effects of antidepressants are only clinically significant in severe depression”, what they mean is “the effects of antidepressants only reach a totally arbitrary number one guy made up and then retracted, in people whose HAM-D score is above whatever number I make up right now.” Depending on what number you choose and what word you make up to describe it, you can find that antidepressants are useful in moderate depression, or severe depression, or super-duper double-dog-severe depression, or whatever.