A 2007 study showed that people who are depressed eat more chocolate. Does this mean that eating chocolate causes depression? Of course not. One of the first lessons young scientists learn is that correlation does not equal causation. Why not? For one, the opposite might be true – depression could lead people to eat more chocolate. It’s also possible that there is some factor that influences both chocolate consumption and depression that could explain why they’re correlated – for example, hormonal changes might lead to chocolate cravings and moodiness. A popular joke about the correlation-causation issue comes from the observation that as the number of pirates in the world has decreased over the past century, the average temperature has increased – clearly global warming didn’t result from the decline in piracy.
To show that consuming chocolate does cause depression, researchers would need to do more than show that the two are correlated. They would also need to: 1) show which comes first (since the cause should precede the effect), and 2) carefully rule out lots of alternative explanations for the association (such as the hormone account described above). The ideal way to meet ALL of these conditions is to conduct a true experiment – this allows the researchers to carefully control who gets the exposed to what, in order to isolate the precise effects of this exposure. In this case, psychologists could get a bunch of people and randomly divide them into two groups – one group would be fed chocolate everyday, and the other would get some appropriate comparison (such as candy that doesn’t have chocolate in it). Then, after an appropriate amount of time has passed, the reseachers could check to see how depressed the people in both groups are. Two elements of this proposed study are critical. First, it’s important that the groups are picked at random – this ensures that the people in the two groups are not different to begin with, before they start the experiment. Second, it’s important to have some sort of comparison condition – this helps the researchers rule out other possible explanation for the findings (for example, that it’s really sugar consumption that leads to depression, not chocolate consumption per se).
But if there were really good reason to think that eating chocolate causes people to become depressed, would this study be ethical? Probably not. And while this is just intended to be a fun and simple example, the truth is that there are lots of these sorts of scenarios in psychology, in particular research on psychological disorders. In other words, we can’t in good conscience expose people to potentially damaging conditions, like physical abuse or emotional trauma, just to see how these factors influence mental health – so most of the research that is done on these topics just looks at correlations. As a result, it takes a lot of time (and some creativity) to accurately hone in on the causes of mental health problems.
Why the science lesson? It’s not uncommon for findings from research on psychological disorders (and other topics of this sort) to get some attention in the popular media. And when this happens, the media sometimes gives their audience the false impression that the results DO tell us what is causing what. In some of these cases the mistake is pretty explicit – that is, the report actually uses the word cause (“a new study shows that eating chocolate causes depression”), or similar wording (“a new study shows that eating chocolate leads to depression”). Here is an example – even though the study discussed in this article doesn’t definitely show that dietary factors can cause depression, words like “influence”, “protective”, and “effect” are peppered throughout. When this happens, it’s a problem. But from my experience it doesn’t happen that often, especially when it comes to reputable media sources. A more common problem, at least in my perception, is that these reports often include implicit messages that are misleading in the same sort of way. For example, a report may end by say “be careful about eating too much chocolate”, or worse, “so if you’re depressed, cut back on the chocolate” – in both of these cases, there is a clear (but implicit) message that eating chocolate causes depression. Here is an example of this sort – again, the study discussed in this article doesn’t really show for certain that sitting for long periods of time causes people to have fatal heart attacks, and even though the author mentions (in passing) that we don’t know for sure why they’re related, he still rails on and on about how dangerous it is to sit for long periods of time. If sitting doesn’t really lead to heart problems, this warning could prove to be totally misguided.
So what can the popular media do to avoid these potential pitfalls when reporting on findings from correlational research? Three suggestions…
- Make sure to avoid using the word “cause”, as well as others words or phrases that are essentially synonymous (like “leads to” or “affects”). In fact, it can never hurt to explicitly point out that the study only shows a correlation, and that we do NOT know what is causing what.
- Don’t just tell the audience what the researchers found – give them a sense of what the researchers actually did. I realize that the media usually shies away from this because they want to keep their stories brief, and they are concerned that the audience won’t understand the technical details anyway. These are both reasonable concerns, but I think that its generally feasible to provide some of the most important details in a quick and digestible way – it just takes some work.
- Avoid the temptation to discuss grandiose implications that are purely speculative. While proposing these sorts of ideas can make the story more interesting, the audience may not be able to separate these speculations from what the researchers actually found. While researchers sometimes make these same sorts of speculations when they discuss their findings, their motivation is (usually) to stimulate more research. But the people learning about a research finding from the popular media generally aren’t going to be the ones pioneering future research on that topic, right?
Of course, consumers can also take the initiative to scrutinize the reports they hear or read in the popular media about these very issues. On the same note, if you see a commercial or read an op-ed piece about how we should bring back pirates to stop global warming, don’t listen. That said, I don’t want to give the impression that all popular media reports about correlational research are misleading – some do get it right (here is a good example about the association between chocolate consumption and depression). And while these sorts of reports may feel a bit less engaging, I would argue that the tradeoff is worth it.
Rose, N., Koperski, S., & Golomb, B. (2010). Mood Food: Chocolate and Depressive Symptoms in a Cross-sectional Analysis Archives of Internal Medicine, 170 (8), 699-703 DOI: 10.1001/archinternmed.2010.78
Sánchez-Villegas, Almudena, Verberne, Lisa, De Irala, Jokin, Ruíz-Canela, Miguel, Toledo, Estefanía, Serra-Majem, Lluis, & Martínez-González, Miguel Angel (2011). Dietary fat intake and the risk of depression: the SUN project. PLoS ONE, 26, 1-7 : 10.1371/journal.pone.0016268
KATZMARZYK, P., CHURCH, T., CRAIG, C., & BOUCHARD, C. (2009). Sitting Time and Mortality from All Causes, Cardiovascular Disease, and Cancer Medicine & Science in Sports & Exercise, 41 (5), 998-1005 DOI: 10.1249/MSS.0b013e3181930355