All the major meta-analyses come to roughly the same conclusion, which is that anti-depressants have modest positive effects. The paper you linked to finds exactly this, but argues that the effect size they found is insignificant because of the high risk of bias. Other studies have gone to extraordinary lengths to control for potential biases and come up with a very similar effect size. Reasoning about the data is quite challenging, because we're talking about relatively small shifts in a relatively broad statistical distribution.

"Number needed to treat" is a useful epidemiological concept in this case. A perfect drug that cures every single patient has an NNT of one - for each patient you treat, one patient is successfully treated. When you translate the results of SSRI meta-analyses, you get an NNT of about seven - for every seven patients who take SSRIs, one more patient will recover than if those patients were given a placebo.

It's hard to know what to do with that information. Is it worth prescribing antidepressants to 1,000,000 people to treat 142,000 of them? On a pure cost-benefit analysis, the answer is a resounding yes. Antidepressants are relatively cheap and safe. Are you willing to take a pill every day to get a one-in-seven chance of an effective treatment? Maybe. If you're in the throes of a deep depression, you might be willing to give anything a try. If you're just feeling a bit blue, maybe not. By the same token, if you're taking antidepressants and you don't think that they're helping, you're probably right.