Depression is a very complex disorder and we simply have no good evidence that antidepressants help sufferers to improve.
Your grief and guilt overwhelm you. You are so tired you cannot think straight. Your simple joys are lost in an invisible agony. You have pain in your head and back and stomach, real pain. The swamp of your soul suffocates you with despair.
All this is your fault, you are worthless, and you might as well die. This is how depression can feel, though people’s experiences of it, including the severity of symptoms, can vary widely. This terrible disease affects about one person in 10 at some point in life and, to treat it, many millions of people have taken antidepressants. Unfortunately, we now have good reasons to think that antidepressants are not effective.
To know if antidepressants work we must, of course, pay close attention to the best evidence about these drugs. There have been many empirical trials of antidepressants, and in the past 10 years or so there have been some good meta-analyses of these trials (a meta-analysis pools data from multiple trials into a single analysis).
However, there is a problem: experts disagree about the merits and problems of these empirical studies, and about what we should conclude based on them. Philosophy can help. Philosophy of science is the discipline that studies the concepts and methods of science, and offers a lens through which we can understand what scientific evidence shows us about the world.
After witnessing the darkness of depression and the struggle by some of my dearest friends and family to treat this disease with drugs, I began to use my training as a philosopher to understand the evidence about antidepressants. Diving into the details of how antidepressant data are generated, analysed and reported tells us that these drugs are barely effective, if at all.
Depression affects many of us. To the extent that you find the arguments in this essay convincing, the message here could be disappointing. If you are already taking antidepressants, you might decide to stop, but I urge caution. We have little reliable evidence about coming off antidepressants, though there is evidence that people can suffer from withdrawal.
Moreover, we have little reliable evidence about alternative modes of intervention, such as talk therapy or lifestyle changes. So, patients should be extra cautious when considering changes to their medications, or foregoing them for other kinds of treatments. A quick essay on a difficult subject must sacrifice depth; for a fuller presentation of the arguments that follow, please see my book Medical Nihilism (2018). If you are depressed, your physician or psychiatrist has clinical experience and insight into your condition – despite the fact that most physicians overestimate the benefits and underestimate the harms of antidepressants, you should continue to consult with them, perhaps with this essay in hand.
The best evidence about the effectiveness of antidepressants comes from randomised trials and meta-analyses of these trials. The vast majority of these studies are funded and controlled by the manufacturers of antidepressants, which is an obvious conflict of interest. These trials often last only weeks – far less than the duration that most people are on antidepressants. The subjects in these trials are selected carefully, typically excluding patients who are elderly, who have other diseases, or who are on several other drugs – in other words, the very kinds of people who are often prescribed antidepressants – which means that extrapolating the evidence from these trials to real patients is unreliable.
The trials that generate evidence seeming to support antidepressants get published, while trials that generate evidence suggesting that antidepressants are ineffective often remain unpublished (this widespread phenomenon is called ‘publication bias’). To give one prominent example, in 2012 the UK pharmaceutical company GlaxoSmithKline pleaded guilty to criminal charges for promoting the use of its antidepressant Paxil in children (there was no evidence that it was effective in children), and for misreporting trial data.
Every trial on antidepressants uses a scale to measure the severity of depression of subjects before and after the trial. These scales are deeply flawed, and they bias the research toward overestimating the effectiveness of antidepressants. A typical scale that is often used is called the Hamilton Rating Scale for Depression. This scale has 17 questions, each of which has several possible answers. Each answer receives a particular score, and then the scores for all the questions are added together to give an overall measure of depression severity, for a maximum score of 52 points.
The hope when testing a new antidepressant in a trial is that the depression-severity score of subjects in the drug group will decrease more than the depression-severity score of subjects in the placebo group. The scale was invented in 1960 by the psychiatrist Max Hamilton in the UK, and has been in use ever since (from here on, when I mention depression-severity scores, I am talking about this scale).
The problem with this scale is that large changes in a subject’s score can occur as a result of trivial changes in a subject’s real depression. For example, there are three questions about the quality of a subject’s sleep, with a total of six possible points, and there is a question about how much a subject is fidgeting, with up to four points. So a drug that simply made people sleep better and fidget less could lower one’s depression score by 10 points.
To put this in context, recent clinical guidelines in the UK have required drugs to lower depression scores on this scale by an average of only three points. When a measurement scale measures what we want it to measure, we say the scale has ‘construct validity’. The general problem with depression-severity scales is that they lack construct validity, and this contributes to overestimating the effectiveness of antidepressants.
If a trial subject gained weight, she might accurately guess she was in the drug group
The placebo effect is when patients improve merely as a result of the medical care they have received rather than as a result of the biochemical properties of their drug. The idea is that the mere expectation that you will get better after receiving medical care can itself contribute to you getting better. Some diseases are more responsive to placebo than others, and depression is one of the most placebo-responsive of all diseases.
Since much clinical research aims at discovering the true biochemical effects of drugs, trials include a control group that receives a placebo (sometimes control groups receive competitor drugs), and the allocation of subjects to the drug group or the placebo group is concealed from subjects (this is sometimes called ‘blinding’). To estimate the active biochemical effects of the drug, the measured outcomes in the drug group are compared with the measured outcomes in the placebo group.