Chapter 14. Tracking Mental Illness Online

14.1 Welcome

14.2 Introduction

This activity invites you to test the claim that we can track patterns of mental illness, like anxiety disorders, by analyzing online searches. First, you’ll conduct a search to explore what comes up when you Google “anxiety.” Then, you’ll look at evidence from a study that analyzed online searches to track patterns in mental illness. Next, you’ll explore alternative explanations for these findings based on your own online searches. Finally, you’ll examine internet search data—a type of “big data”—as a source of information about mental health patterns.

14.3 Identify the Claim

14.3.1 Tracking Mental Illness

Is depression more common in the winter? Are eating disorders more frequent in some countries than in others? Does anxiety spike around the holidays? Researchers often want to explore patterns related to the frequency of mental illness in the population. Unfortunately, many of the most common research techniques are flawed. Researchers can’t use treatment records because most people with a mental illness never get treated. Telephone surveys are often used, but they are expensive to conduct. There’s also the question about how people respond to telephone questions about their mental health. Would you tell a researcher your mental health history over the telephone?

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14.3.2 Take a Survey About Health Problems

One of the largest and longest-running telephone surveys is the Behavioral Risk Factor Surveillance System, run by the U.S. Centers for Disease Control (CDC). Participants are asked about different types of health problems, including mental health, physical health, and exposure to environmental hazards like mold. Click whether you would feel comfortable (or not) admitting to dealing with the issue mentioned in each of these questions from an interviewer.

14.3.3 Online Searches and Mental Illness

Can Google read your mind? Increasingly, researchers analyze what is known as “big data,” enormous amounts of computerized information. Some researchers speculate that our online search history, a treasure trove of big data, can provide a window into our thinking, behavior, and experiences. Could this be true for tracking mental health? If yes, then researchers could track patterns of mental illness by analyzing online searches. For example, an increased number of searches for bipolar disorder, anxiety, or depression could indicate higher occurrence rates for those mental illnesses. Researchers think we might Google “depression” even if we aren’t willing to tell a close friend we are suffering from the mental illness.

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14.4 Evaluate the Evidence

14.4.1 Testing the Claim

The claim that Google search frequencies mirror the frequencies of mental illness in the population has already been examined. Based on previous studies, researchers believed that searches for mental illness occurred when someone developed a disorder for the first time, had a recurrence of that disorder, or found their symptoms getting worse (Ayers & others, 2013). So, they analyzed all Google searches in the United States and Australia to determine the frequencies of the following search terms:

These researchers were particularly interested in whether mental illness is more common in the winter or in the summer.

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14.4.2 Summer vs. Winter

The researchers wanted to use Google to explore whether certain mental illnesses occur more in the summer or the winter. For all the mental illnesses they studied—depression, anxiety, schizophrenia, and so on—the researchers found increased searches in the winter and decreased searches in the summer. Even more interesting is that these findings couldn’t be attributed to something going on in the world—like a war, a drought, or a natural disaster—because the seasons in the United States and Australia are opposite of one another. And based on the months of the year, the U.S. and Australian results were completely opposite of each other. As you can see in the graph here, U.S. searches peaked when Australian searches were at their lowest. (Note that the tick marks on the graph represent 6-month intervals. The tick marks above the years are for January and those in between are for July.) Because summer in the United States occurs during the Australian winter, and winter in the United States coincides with the Australian summer—which turned out to be a very cool way for the researchers to replicate their own research.

14.5 Consider Alternative Explanations

14.5.1 What Do Google Searches Really Measure?

Do Google searches actually measure patterns of mental illness? Or is there an alternative explanation for these findings? The researchers think that Google searches are accurate measures of how common these disorders are in the population (Ayers & others, 2013). Their research methods eliminated some of the problems with other types of research, including people’s reluctance to answer questions truthfully, such as in a telephone survey. Their research methods also avoid the possibility of prompting a specific answer just by asking about mental illness. When asked about depression, for example, you think about depression, and you might report symptoms you hadn’t thought about otherwise. In an internet search, however, you provide information about a mental illness without being asked. So a Google search shows your natural behavior rather than your prompted behavior or your behavior in the laboratory.

Take a look at the graph below. In the United States (blue), anxiety is highest in January and December (winter in the northern hemisphere) at each end of the graph. In Australia (orange), anxiety is highest in June, July, and August (winter in the southern hemisphere) in the middle of the graph.

14.5.2 Googling Anxiety

But what does it really mean when you Google a mental illness? Can an online search engine know you’re anxious? Let’s explore alternative explanations for what online searches really indicate. Open another browser window or tab on your computer, and search for “anxiety” using a search engine. As you scroll through the first several pages of results, note the different types of Web sites. Then come back here and click off each of type of Web site you found. We’ll come back to your answers in the next screen.

14.5.3 What Are We Really Searching For?

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14.5.4 Who Is Conducting the Search?

As we just observed, it’s possible that some people who Google words like “anxiety” and “depression” are searching for something other than mental illnesses. But realistically, this probably only reflects a small proportion of searches. As you saw when you Googled “anxiety,” most of the results gave us information about anxiety disorders—definitions, symptoms, treatment, and other useful information. But what about the person doing the searching? A person who has symptoms of a mental illness may be searching to get more information. Who else might search? List three reasons that someone might search for a mental illness like anxiety, depression, or schizophrenia.

14.6 Consider the Source of the Research or Claim

14.6.1 Google Searches as a Source of Data: The Case of the Flu

The source of the data for tracking mental illness online was Google searches. So how good are Google searches as sources of data? To find out, let’s look at Google Flu Trends, a tool that reportedly could “detect regional outbreaks of the flu a week to 10 days before they are reported by the Centers for Disease Control and Prevention” (Helft, 2008). We know the flu numbers that Google Flu Trends predicted and the actual flu data from the CDC, so comparing them will tell us how well Google predicts an illness other than mental illness. With searches for mental illness, we have predictions, but not the actual numbers.

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14.6.2 Google Flu Trends vs. the CDC

A few years back, the media excitedly reported the success of Google Flu Trends (Helft, 2008). Based on these data, Google created maps that showed where the flu was spreading earlier than was ever before possible, which allowed for earlier public health efforts that helped to reduce flu outbreaks.

The graph below shows estimates for the number of people with the flu based on Google searches, and the actual number of people with the flu that was eventually reported by the CDC. (Note that the initials on the x-axis refer to months. For example, A=April.) So, at first glance, it seems that Google searches are good predictors for the flu, and might be for mental illness, too.

14.6.3 The Drawbacks of Google Flu Trends

Despite optimistic early results, it turns out Google Flu Trends was overhyped, an indication that we should be cautious with other types of online searches—such as those for mental illnesses. Researchers reported that Google Flu Trends predictions were routinely higher than the actual numbers reported later by the CDC—and substantially higher in 2012–2013 (Lazer & others, 2014a). They suggested one possible reason: Google’s model might have caused increased flu searches. Try it yourself. Open a new page or tab, and Google symptoms associated with the flu, like “fever” or “cough.” Pay attention to how many results on the first page mention the flu. Return here when you’re done.

14.6.4 Google Flu Trend Overestimates Outbreaks

Seeing results like these might make you more likely to search for additional information on the flu, even though you never intended to search for the flu. You may have noticed that a number of illnesses besides the flu came up in your search. You might only have a cold, which is a more likely diagnosis. Or, you might have something worse than the flu—like whooping cough, which is a less likely diagnosis. Google has since tweaked its flu-tracking tool so it works better, but it still overestimates the flu by about 30% (Lazer & others, 2014b). Some of the same kinds of problems might be occurring with searches for mental illness, although we don’t yet have data (like the CDC’s data on flu) to evaluate these searches.

14.6.5 Harnessing Big Data: A Compromise

Even though Google Flu Trends overestimates the number of people with the flu, it’s not completely off. Moreover, combining it with the CDC data leads to better predictions than either on its own. As one researcher pointed out, “the mash-up is the way to go” (Lohr, 2014). Researchers have also observed that more traditional methods, like survey research, can be improved by using methods from big data analyses, like increased use of the internet to conduct research (Lazer & others, 2014a). Their idea is to analyze data from both “traditional and new sources,” which provides “a deeper, clearer understanding of our world.” Other researchers can learn from this advice as they improve the tracking of mental illness. Early indicators from Google Flu Trends indicate that online searches—whether of physical illness or mental illnesses—might be useful predictors, particularly if they’re used along with other sources of information.

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14.7 Assessment

14.7.1 Assessment