Depression is typically defined as a mood disorder, which is why people mostly think about it in terms of emotion. That’s certainly not an inaccurate conception, but it misses a crucial cognitive side to the problem. Emotions aren’t an isolated construct in the brain; they interact with every part of our life and change the way we think and make decisions.
Cognitive Behavioral Therapy (CBT) is one of the most effective treatments currently available for depression, and it seems to work well for people diagnosed with clinical depression and also people with milder depressive symptoms. One of the core tenets of CBT is that depression and other psychological problems are partly caused by maladaptive ways of thinking or “cognitive distortions”. Alleviating those distortions can help you feel better.
Research is now looking into how cognitive distortions affect everyday language by analyzing people’s social network messages. This naturalistic approach to language analysis is improving our understanding of the connection between how we think and how we feel. So here’s a look at that work, together with some examples of cognitive distortions that you might find in your own thinking.
🐦 Cognitive distortions on Twitter
In a study published in early 2021, a team of researchers at Indiana University Bloomington combed through Twitter looking for users who identified as clinically depressed. A computer program first identified tweets containing keywords such as “diagnosed” and “depressed”, and the researchers then checked that list manually to pick out clear expressions of a clinical diagnosis such as “I was just diagnosed with clinical depression”.
The researchers identified 1035 Twitter users who communicated that they were diagnosed with depression, and they analyzed a total of 1.5 million tweets from those users. They then compiled tweets from another random group of users who had created Twitter accounts on similar dates to the depressed group but had not identified themselves as clinically depressed. This allowed the research team to directly compare the language contained in each group’s tweets.
This approach to identifying people with depression is clearly not perfect. It’s possible that some people’s diagnosis statements aren’t accurate and it’s possible there’s some sampling bias between the groups too. For example, people who are open about their mental health on social media might have very different personalities to people who prefer privacy, and it might have nothing to do with depression.
However, the tweet identification method did pass a few sanity checks. Consistent with prior studies on clinical depression, the researchers found two times more females than males with depression, and the age distribution for depressed people also looked standard. So although the approach is far from perfect, the outcome at least made sense.
So how did tweet language differ between the groups? The researchers focused their analysis on a set of 200+ cognitive distortions and examined how often they appeared in each group’s tweets. Here are six cognitive distortions they mention in the paper, together with example quotes I’ve added, so you can understand what this looks like.
As the researchers predicted, the depression group tweeted more cognitive distortions than the control group did. In fact, 10% of people in the control group showed no cognitive distortions whatsoever in their tweets, compared to only 0.4% of people in the depressed group.
This pattern wasn’t necessarily related to a negative emotional bias in depressed people’s tweets. When the researchers analyzed the emotional sentiment of tweets, they found no difference between the two groups in how often they contained a positive vs negative emotional tone. They identified a surprisingly specific effect related to cognitive distortions rather than emotional language in online communication.
We use language to express our thoughts so it’s only natural that our words reflect how we think and feel. But it’s interesting that even in environments where we can carefully curate what we say—like with social media comments—our language still reveals a deeper truth about our condition. When we’re depressed, we think less clearly, and that lack of clarity affects how we communicate with others.
⭐️ Takeaway tips
Identify cognitive distortions: All of us are susceptible to cognitive distortions to some degree. The research above showed that 90% of people who didn’t identify as depressed still demonstrated cognitive distortions occasionally. Learning the common cognitive distortions I list above (here are more examples from a table in the research paper) may help you notice them in your own thinking.
Reinterpret distortions: The research above doesn’t identify a causal relationship between cognitive distortions and depression symptoms, and it therefore can’t say anything about what would happen if you amended distortions. However, there’s plenty of other research showing that the distortion-correction approach of CBT can improve depression symptoms. With that in mind, consider how you might reinterpret a situation when you notice your thinking leading you astray. For example, when you’re catastrophizing, realistically assess the worst case scenario and how likely it is to happen. When you’re mentally filtering for negative information, flip your attention to find some positives. When you’re mindreading or fortune-telling, focus your energy on present-moment reality instead of unknown possibilities.
Help others when you hear distortions: Helping others is often just as rewarding as helping yourself (sometimes, even more rewarding, as one of my previous newsletters explained!). When a friend expresses a cognitive distortion, help them understand why it might be unrealistic or harmful without appearing judgmental. It’s often much easier to identify distorted reasoning from an external perspective than a first-person perspective, which is why professional therapists can be so valuable.
💡 A final quote
“Folks are usually about as happy as they make their minds up to be.”
~ Abraham Lincoln
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👋 Until next time,
Erman Misirlisoy, PhD