There was an interesting article in Wired recently that spoke about the placebo effect getting stronger: that the pre-post difference from a placebo drug is greater than it was a decade or two ago and that it differs between countries. That is, if you are looking at antidepressants and your outcome measure is a score on the Beck Depression Inventory that measures how depressed someone is, the score before the drug minus the score after the drug is different now than it was 10 years ago.
One criticism of the article is that the placebo effect cannot be considered an effect unless it is compared with another experimental condition. Since drug trials don't include both patients who receive a placebo and patients who receive nothing, there is no such thing as a placebo effect unless we know what the pre-post difference would have been in the absence of the placebo. Without a nothing arm to compare with, the writer contends that the pre-post difference in the placebo arm of a trial is just by definition the background noise in the trial.
I think that he's making a semantic point because a true placebo effect is impossible to measure.
To break the problem down further:
We do not know what the pre-post difference in a nothing arm of a trial would be. In some trials and for some diseases, there would be spontaneous improvement in the patient's condition: in that case, the pre-post difference in the placebo might just be that spontaneous improvement that would have happened if nothing were done.
In some trials and for some diseases, there would not be much change in the patient's condition, so the nothing arm would have no difference: in that case, the pre-post difference in the placebo arm would represent an "effect" and we could say that we have a placebo effect.
The question is which diseases have spontaneous improvement and which don't. There are three ways I can think of to figure this out.
1. A randomized clinical trial with patients that actually have some disease in which half the patients get a sugar pill and half the patients get nothing. No human subjects board would authorize this trial. Second, the study would not measure what we want it to. Ethically patients have to be told that the two possibilities are sugar pill and nothing. The Wired article contends that the placebo "effect" is based on a patient's prior beliefs about a drug's effectiveness, so it's specific to the drug, rather than being just the effect of a plain sugar pill.
2. The placebo effect could in theory be measured with matching, were there any subjects to match them to. The placebo pre-post difference can be defined in two ways: the pre-post difference of the sugar pill plus the pre-post difference of enrolling in the trial, or just the pre-post difference of the sugar pill alone. I would say it's the former. In that case, where we want to measure the effect of enrolling in a trial and taking a sugar pill, we could match normal patients with placebo patients based on their records and compare their pre-post differences. Except for the fact that medical records of normal patients with a disease are there because the patients are getting some treatment from their doctors. So there's no group to compare the placebo patients to.
3. The one remaining possibility is for each drug trial to divide their control group into two unequal groups: one receiving a sugar pill would be the larger group and one being put on a waiting list for the drug would be a smaller group. The problem is that placebos serve two purposes: one is for the statistical purpose and one is to keep the participants in the study and encourage them against taking other treatments. Depending on the condition, a control participant put on a waiting list might leave the trial or take another treatment in addition to the waiting list. So you might lose a good portion of the nothing arm of the trial.
Given the impossibility of rigorous measurement of what would happen under no treatment, the best we can do is guess which are the diseases where symptoms spontaneously resolve and which are the diseases where they don't. And that's what we already do when we talk about a placebo effect. We compare the pre-post difference in the placebo arm of a trial with our beliefs about what the pre-post difference would be with no treatment. In that sense, the placebo effect is really an effect. It's just imprecise.
Further, it's reasonable to assume that whatever the pre-post difference under nothing is, it's not going to change with time in any systematic way. If we could put all the placebo arms of, say, antidepressant trials together and find a trend with time, that's not sampling error. And that's exactly what the Wired article is talking about.