We tend to suffer from a great deal of cognitive dissonance when it comes to health. Ask someone about health implications as they light a cigarette or plow through a cheesecake, and they'll probably be an optimist, citing the relatively low overall risks of various consequences. But if the same person has the sniffles and is given access to the Internet, chances are they'll become a raging pessimist and diagnose themselves with the bird flu.
Psychologists studying these conflicting results have had just as much trouble making sense out of them as I have, although it's clear that some forms of context matter. Now, a new study by researchers in Hong Kong has led to a unified framework that incorporates risk, perceived symptoms, and personal biases to explain why reactions to health risks can differ so dramatically. In the process, their results provide some insight into why the Internet is so good at enhancing hypochondria.
The uses of risk
Past studies have focused on a few different aspects of risk perception. One is what you might call "societal levels of risk"—things like the US having about 50,000 new HIV infections annually, or the risk of osteoporosis being higher in women. The second framework we use for evaluating health risks is what you might call "symptom matching." This is where, when presented with a set of individual risks and health problems (chest pain, family history of heart disease), we try to find a disease that might cause them all. Identifying health problems tends to involve a combination of these types of evidence, where health professionals will typically focus on the most common ailment that matches a reasonable number of symptoms.
But people in general don't work that way. As the authors put it in their introduction, "we fear the worst possible outcomes when it comes to our own health, while maintaining a calm objectivity (sometimes infuriatingly so!) with regard to others." This phenomenon is so well known that it has picked up a formal term: the "base rate fallacy." Given a list of symptoms and information on the general rates of risk, people will base their judgements almost entirely on the case information.
But, if we're only given information on risk factors, we not only manage to be objective more often, we sometimes take it to the other extreme and assume that risks will never catch up with us.
The authors of the new paper test two hypotheses to help make sense out of the confusion. The first is that psychological distance matters. If something doesn't affect us or someone we know, or won't affect us for years, we're more likely to focus on base rate information. If the risk seems more immediate, we'll focus on symptom matching. Layered on top of this is an optimism factor that only applies to personal risk. If the risk is high, but our symptoms don't match well, we'll be overly optimistic. If our risk is low but the symptoms match well, we'll be a pessimist.
The authors do some clever experiments to manipulate psychological distance. The undergrads used as participants were asked to consider osteoporosis, which shouldn't strike any of them for decades, at the earliest. Since they were from Hong Kong, the students were also asked to consider two cases, one named “Chris Chan” and the other “Chris Smith.” In a more blatant manipulation, they were also asked to consider a close friend with symptoms and a random stranger. In each case, psychological closeness made a difference: the students were more likely to use general risk numbers with random strangers or those with unfamiliar names, and for themselves when the disease wouldn't strike for decades.
The effect of personal risk was a bit harder to get at, but was clearly shown in an experiment that involved questions about behaviors that put people at risk of HIV. The participants were also asked to estimate the current risk of HIV infection in Hong Kong. Those who suspect there was a high base rate of infection but a low risk for themselves were optimists; they thought the chances of their getting infected were low compared to the general population. Those who thought the rate of infection was low but had engaged in risky behaviors were pessimists, in that they rated their own chances of infection as being higher than the general public's.
The results go a long way toward explaining why the Internet is such fertile ground for hypochondriacs. People tend to go searching for medical information only after symptoms affect them (or someone close to them)—a situation that is extremely close, psychologically. That would tend to bias them towards symptom matching and away from a general risk evaluation. And, by searching for symptoms, they're unlikely to come across broader risk information anyway. The whole situation seems designed to give people a match to some ailment, regardless of its probability.
The authors suggest this knowledge could be used by public health officials, who often have trouble getting people to take their own risks seriously. By focusing on the factors that make risk seem immediate and personal, it might be possible for public health campaigns to make a stronger impact. Of course, too much of an otherwise good thing might also turn people needlessly pessimistic.