by Carl V Phillips
The title refers to a classic joke about economists, describing a common practice in the field: Something is observed in the real world — say, the collapse of the Greek economy, insurance prices dropping under the ACA, or people lining up to buy new iPhones in spite of already owning perfectly good old iPhones — and the theoretical economists scramble to figure out if their models can show that it can really happen. In fairness, that way of thinking is not as absurd as it sounds. Developing a theory to explain an observation is good science, so long as it is being done to try to improve our models and thus better understand reality and perhaps make better predictions. Obviously, the ability or inability to work out the model does not change what has happened in reality.
Note that the term “model” is generally misused in the tobacco research arena, so this observation might require some clarification. Most of what gets misidentified as “models” in tobacco research are actually just big deterministic calculations, something along the lines of “if this many people start smoking each year, this many quit, this many switch to e-cigarettes, etc., then the total number of smokers in 2020 will be….” A proper model, however, is a simplified representation of a part of reality that can tell us new things about the real world. Most scientific theories fit this description. So do most experiments, such as clinical trials. If you build a miniature of an airplane you have a model; you can put it in a wind tunnel and learn things about how the real airplane will fly. But if you just posit how fast an airplane goes, in order to “model” how long it will take to get somewhere, that is merely a calculation.
So coming up with a model of why some smokers switch to e-cigarettes and others do not is interesting (at least I think so), and if it is correct it can help us predict the future and better understand the details of what we have observed. It could also help us target research to answer open questions. For example, a model of people’s motives and choices could highlight that we are not really sure of, say, which features of an e-cigarette seem to be better at motivating complete smoking cessation.
A model/theory obviously cannot tell us whether what we observed actually occurred. It would be fairly silly to say “my model of the economy says that recent government actions would create high inflation, and therefore we have high inflation — never mind that reality shows otherwise.” Ok, people actually do say that, but it is obviously silly. Fortunately using data to prove (or improve) theories is what is normally done in science, even though politics sometimes drives people to go in the wrong direction, to act as if observed reality is subordinate to theoretical results. Sadly, when it comes to academic research on e-cigarette use, the wrong direction is the norm.
I did a radio interview this morning that was motivated by this study, a clinical trial where some smokers were assigned to substitute e-cigarettes, whose authors described the results to the press (e.g., here) in terms of e-cigarettes reducing the “craving” to smoke. Um, yeah. Can you imagine someone describing having a meal of fish as reducing the craving to then eat some beef, or describing owning a Samsung Galaxy as reducing the craving to buy an iPhone? E-cigarette users also did not have the elevated carbon monoxide levels of smokers (shocking!). Slightly more interesting, the study found that a lot of those assigned to substitute e-cigarettes remained abstinent from smoking through the follow-up period. I told the radio producer that I would be happy to talk about the study, though frankly it is a bit silly, so it might be better to just talk about the reality (and to their credit, they went that direction instead).
Why “slightly” and “silly”? Because ultimately studies like this are just a more subtle version of the economist joke. If e-cigarettes were a new invention and we wanted to predict what would happen if they were offered to smokers in advance of introducing them to the real world, such results would be interesting. They would help predict something we do not already know. But since we already know how e-cigarettes have been received in the real world, doing such a test simply shows that what happened in reality can be replicated in a theory (that is, in a model, the artificial simplification of reality created to do the study).
What is worse, the entire discussion of the topic tends to favor theory over reality, and most people do not seem bothered by that. This is a serious problem that interferes with having a reality-based discussion. Those who advocate for e-cigarettes and THR should not be treating these models as if they are more informative than reality (“see, this study proves that e-cigarettes really do work, like we have been saying”). Down that path lies the inevitability that some models will produce results contrary to reality, and accepting those also as more informative than reality.
But there is a potentially bigger problem, the waste of the potential to learn something. We know that a lot of real-world smokers will switch to e-cigarettes if given ample encouragement. We are even starting to have a pretty good estimate of how many. But we know woefully little about many important questions, such as how to identify optimal candidates for switching or exactly what variables in the experience change the probability of switching. We waste the opportunity to answer these questions every time someone implements a model (study) that is designed so that it can do nothing other than roughly replicate what we have already seen the real-world version of. It is the difference between a useful experiment and a mere demonstration. Yet if the models are treated as useful even when this is all they do, chances are it is going to keep happening.
The economist joke is not really fair because those building the theory to explain the reality are generally doing so in a way that can provide information about reality that we do not already have. They are asking “why?” or “exactly what is happening?”, not “did this really occur?” Economists seldom actually think the models answer the latter question, as the joke implies. Moreover, such efforts are a pretty cheap way to pursue further knowledge. It would seem that the real joke lies elsewhere, and it is not really so funny.