In a piece at Aeon linked to at Daily Nous, philosopher of science Jacob Stegenga (University of Cambridge) contends that "we simply have no good evidence that antidepressants help sufferers to improve." I don't think the evidence available supports Stegenga's argument, and I made a comment to that effect in the comments section over at Aeon (which Stegenga replied to). Because I think this is a very important issue–one that could potentially affect people's choices and public attitudes regarding anti-depressants–I want to address Stegenga's argument here at the Cocoon.
I want to begin by noting two things. First, this issue is very personal to me. Mental illness not only runs in my family, affecting multiple people I am close to – it has also affected friends of mine. Second, I have experience working in the mental health field. As an undergraduate, I interned for a year in an out-patient day program utilized by dozens of individuals with serious mental illnesses: schizophrenia, bipolar disorder, depression, borderline personality disorder, and so on. Then, after graduation, I was Assistant Director of a group home that housed around a dozen residents with serious mental disorders. Among many other things, I was responsible on a day to day basis for dispensing medications, including importantly changes to patients' medications.
Bearing this in mind, let us turn to Stegenga's basic argument that "we simply have no good evidence that antidepressants help sufferers to improve." He contends, first, that "the best evidence about the effectiveness of antidepressants comes from randomised trials and meta-analyses of these trials." I will explain below why–on methodological grounds–I believe this to be false. Stegenga's argument then is that in randomized trials and meta-analyses, observed mean effect sizes are tiny:
In meta-analyses that include as much of the evidence as possible, the severity of depression among subjects who receive antidepressants goes down by approximately two points compared with subjects who receive a placebo. Two points…We saw above how clinical guidelines have held that drugs must lower severity-depression scores by three points to be deemed effective. On this standard, antidepressants do not pass.
So that's the argument:
- Randomized trials and meta-analyses are the best evidence for efficacy of anti-depressants.
- Randomized trials and meta-analysis indicate tiny mean effect-sizes for anti-depressants.
- If (1) and (2) are true, then we have no good evidence that anti-depressants help sufferers to improve.
- Thus (from 1-3), we have no good evidence that anti-depressants help sufferers to improve.
Here's the problem: (1) in this argument is arguably false, as is premise (3). Let me begin with (1).
It is widely thought that randomized clinical trials are the "gold standard" for determining efficacy of medical interventions. I believe this widespread assumption is false – and for a reason I gave in my comment over at Aeon. Randomized trials and meta-analyses at best record group-level effect-sizes, abstracting away from individual-level effects. Allow me to explain.
As I mentioned above, I have a lot of first-hand experience with mental illness and its treatment. Here, in my experience–with again a wide variety of patients–is how treatment often goes. A person has severe depression, or bi-polar disorder, or schizophrenia. They try a variety of interventions: talk therapy, exercise, cognitive-behavioral therapy, and so on. These interventions may have some effect on their symptoms, or none at all. Then the person is placed on a particular drug: say, an anti-depressant like Prozac. Because that drug does not alleviate their symptoms, their practitioner tries other drugs in the same class (Lexapro, Zoloft, etc.), as well as other classes of drugs (Buspar, etc.). Maybe a half-dozen of these drugs will worsen the person's symptoms. Another half-dozen have little effect. But then, after experimenting with a bunch of different possibilities, the doctor and patient finally happen on one anti-depressant that has profound effects. Whereas nothing else worked–the person was unable to function in everyday life, overcome with constant self-hatred ("I want to die")–that single drug appears to induce profound improvements in the person's symptoms. I am confident that any practitioner who actually works in mental health will tell you that this is what they have seen over and over again.
Here then is the problem. If you were to run statistics on this person, you would find that "anti-depressants have negligible effect." Why? Because most of the anti-depressants they tried either didn't work for them or had negative effects on their symptoms, and only one had strong positive effects. Now imagine, next, that you randomly assigned participants to receive particular anti-depressants. Across that random sample, you will find (statistically speaking) that "most antidepressants don't help most people" (and a small effect-size across the group sampled) even if, at an individual level, particular anti-depressants have immensely positively effects on particular individuals (and indeed, because people's brain chemistry differs, the one drug that works for one person might be a very drug that does not work "for most other people").
This is the basic problem with taking randomized trials and meta-analyses to be the "gold standard" for evaluating the causal effectiveness of medical interventions. Group-level statistical differences can be a good mark of causation. However, they can also miss genuine causation at the level of individuals–because they only infer causation from group differences. This is why, in actual medical research and practice, there are other methods for inferring causation, including clinical observational studies.
Stegenga can of course argue that this method of investigating individual-level causal efficacy is mistaken – as indeed he does later in his Aeon piece. However, Stegenga confidently pronounces that he is right about this, claiming that "if you hear of someone benefiting from antidepressants, this was likely due to the natural course of the disease fluctuating or improving over time, confounded by the placebo effect, and exaggerated by confirmation bias." As someone who has seen anti-depressants literally save lives–indeed, as someone who has seen people go from suicidal despite many other interventions to suddenly becoming stable after finding the right drug, and as someone who has seen people very close to me maintain their mental well-being and ability to function in society for years or decades until the moment they go off their meds (or their doctor changes their meds), suddenly lapsing back into depression until they take the same med again, and whose symptoms worsen when they try anything else—I am, to put it mildly, unpersuaded that it is chance fluctuations, confirmation bias, or placebo effect. The best explanation of ample clinical experience, it seems to me, is that anti-depressants can have genuine, and very powerful, individual-level effects. And I think it is unfortunate that Stegenga so confidently dismisses this kind of evidence in a piece for the broader public.
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