Emily Willingham (Twitter, Google+, blog) is a science writer and compulsive biologist whose work has appeared at Slate, Grist, Scientific American Guest Blog, and Double X Science, among others. She is science editor at the Thinking Person’s Guide to Autism and author of The Complete Idiot’s Guide to College Biology.
In March the US Centers for Disease Control and Prevention (CDC) the newly measured autism prevalences for 8-year-olds in the United States, and headlines roared about a “1 in 88 autism epidemic.” The fear-mongering has led some enterprising folk to latch onto our nation’s growing chemophobia and link the rise in autism to “toxins” or other alleged insults, and some to sell their research, books, and “cures.” On the other hand, some researchers say that what we’re really seeing is likely the upshot of more awareness about autism and ever-shifting diagnostic categories and criteria.
Even though autism is now widely discussed in the media and society at large, the public and some experts alike are still stymied be a couple of the big, basic questions about the disorder: What is autism, and how do we identify—and count—it? A close look shows that the unknowns involved in both of these questions suffice to explain the reported autism boom. The disorder hasn’t actually become much more common—we’ve just developed better and more accurate ways of looking for it.
Leo Kanner first described autism almost 70 years ago, in 1944. Before that, autism didn’t exist as far as clinicians were concerned, and its official prevalence was, therefore, zero. There were, obviously, people with autism, but they were simply considered insane. Kanner himself noted in a 1965 paper that after he identified this entity, “almost overnight, the country seemed to be populated by a multitude of autistic children,” a trend that became noticeable in other countries, too, he said.
In 1951, Kanner wrote, the “great question” became whether or not to continue to roll autism into schizophrenia diagnoses, where it had been previously tucked away, or to consider it as a separate entity. But by 1953, one autism expert was warning about the “abuse of the diagnosis of autism” because it “threatens to become a fashion.” Sixty years later, plenty of people are still asserting that autism is just a popular diagnosis du jour (along with ADHD), that parents and doctors use to explain plain-old bad behavior.
Asperger’s syndrome, a form of autism sometimes known as “little professor syndrome,” is in the same we-didn’t-see-it-before-and-now-we-do situation. In 1981, noted autism researcher Lorna Wing translated and revivified Hans Asperger’s 1944 paper describing this syndrome as separate from Kanner’s autistic disorder, although Wing herself argued that the two were part of a borderless continuum. Thus, prior to 1981, Asperger’s wasn’t a diagnosis, in spite of having been identified almost 40 years earlier. Again, the official prevalence was zero before its adoption by the medical community.
And so, here we are today, with two diagnoses that didn’t exist 70 years ago (plus a third, even newer one: PDD-NOS) even though the people with the conditions did. The CDC’s new data say that in the United States, 1 in 88 eight-year-olds fits the criteria for one of these three, up from 1 in 110 for its 2006 estimate. Is that change the result of an increase in some dastardly environmental “toxin,” as some argue? Or is it because of diagnostic changes and reassignments, as happened when autism left the schizophrenia umbrella?
The American Psychiatric Association have just published the latest update of the draft DSM-5 psychiatric diagnosis manual, which is due to be completed in 2013. The changes have provoked much comment, criticism, and heated debate, and many have used the opportunity to attack psychiatric diagnosis and the perceived failure to find “biological tests” to replace descriptions of mental phenomena. But to understand the strengths and weaknesses of psychiatric diagnosis, it’s important to know where the challenges lie.
Think of classifying mental illness like classifying literature. For the purposes of research and for the purposes of helping people with their reading, I want to be able to say whether a book falls within a certain genre—perhaps supernatural horror, romantic fiction, or historical biography. The problem is similar because both mental disorder and literature are largely defined at the level of meaning, which inevitably involves our subjective perceptions. For example, there is no objective way of defining whether a book is a love story or whether a person has a low mood. This fact is used by some to suggest that the diagnosis of mental illness is just “made up” or “purely subjective,” but this is clearly rubbish. Although the experience is partly subjective, we can often agree on classifications.
Speaking the same language
How well people can agree on a classification is known as inter-rater reliability and to have a diagnosis accepted, you should ideally demonstrate that different people can use the same definition to classify different cases in the same way. In other words, we want to be sure that we’re all speaking the same language—when one doctor says a patient has “depression,” another should agree. To do this, it’s important to have definitions that are easy to interpret and apply, and that rely on widely recognised features.
To return to our literature example, it’s possible to define romantic fiction in different ways, but if I want to make sure that other people can use my definition it’s important to choose criteria that are clear, concise, and easily applicable. It’s easier to decide whether the book has “a romantic relationship between two of the main characters” than whether the book involves “an exploration of love, loss and the yearning of the heart.” Similarly, “low mood” is easier to detect than a “melancholic temperament.”