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In a recent study, CU ��«����Ƶ’s Robert Moulder and colleagues find that individuals with trait neuroticism rarely modify how they respond to negative emotions 

Emotions, like temperatures, go up and down. Yet everyone copes with these ups and downs in his or her own way. Some use the same emotion-regulation strategies over and over—read a book, take a walk, watch a movie—while others change which strategy they use depending on the situation.

Research scientist Robert Moulder of the ��«����Ƶ Institute of Cognitive Science, along with , ,  and , wanted to know why: Why do some people frequently modify their regulation strategies? Why do others reuse the same strategies? And are there benefits to both approaches?

 

Institute of Cognitive Science research scientist Robert Moulder, a lecturer in the Department of Psychology and Neuroscience, notes that "that there are some times when it makes sense to become more adaptive" in regulating emotions.

Difficult questions, these, not least because they seek to identify patterns in what seem like random human behaviors. Which is why Moulder was particularly well-suited to the job of answering them. With a background in both mathematics and psychology, he uses chaos theory and nonlinear dynamics to understand human systems. “The way I like to describe it, I am like  from Jurassic Park, but for people instead of dinosaurs,” he jokes. “I do the ‘mathy math’ behind how psych works.”

Thanks to Moulder’s “mathy math,” he and his fellow researchers  a key distinction between those who rarely change up their emotion-regulation strategies and those who do so often: trait neuroticism.

Trait vs. state

Neuroticism, Moulder says, refers to “someone's overall tendency to engage in and ruminate on negative emotions like getting angry, getting upset, being distrustful. You can think about it as the propensity of an individual to experience and act upon negative emotions.”

There are two categories of neuroticism: state neuroticism and trait neuroticism, the differences between which Moulder illustrates with an analogy to extroversion.

“A state personality would be, say, how extroverted you are right now, or how extroverted you are in two or three days,” he says. “Have you ever gone to a party and felt really engaged but afterwards felt dead? During that party your extroversion was higher than it normally would be, and afterwards, it was probably a little lower.” 

Trait extroversion, on the other hand, takes the average of those individual moments over time. “It's kind of like your stable equilibrium,” says Moulder. “If you were going to describe to someone how extroverted you are, you'd be talking about your trait extroversion.”

The same thing goes for neuroticism. One person may have a high degree of neuroticism at any given moment but a low degree overall—high state, low trait—whereas another person may be exactly the opposite.

What Moulder and his colleagues found was that subjects with high levels of trait neuroticism tend not to experiment with their regulation strategies. “That means someone who is very high in neuroticism will consistently use the same tools over and over again, whether they’re working or not.”

A new mathematical model

Moulder and his colleagues arrived at these findings with the help of transition matrices, an analytical tool Moulder and Daniel developed in a . 

 

Examples of transition matrices developed by CU ��«����Ƶ scientist Robert Moulder and his research colleagues.

“Why people do the things they do after a negative event has thousands of components,” Moulder says. “There was not a good method for measuring that. So, we made one.”

Transition matrices are rectangular grids of rows and columns that enable study subjects to keep track of which emotion-regulation strategies they use and when they use them.

A subject who got into an argument with her boss at noon and then took a walk, for example, would put a “1” in the box in her matrix associated with taking a walk. If she received an angry email from her boss an hour later and chose this time to call a friend, she would put a “1” in the box associated with that regulation strategy.

“If someone used the exact same strategy all the time, you would just see one number in the matrix, and all the rest of the matrix would be ‘0,’” Moulder says, whereas someone who constantly switched from one regulation strategy to the next would have numbers all over his or her matrix.

These transition matrices provide two key metrics, Moulder explains: stability and spread. Higher stability means fewer regulation strategies; higher spread, more strategies. Subjects with high levels of trait neuroticism are therefore likely to have high stability. 

Just-in-time interventions

With this information about their own emotion-regulation behaviors, subjects can see which strategies they use and reuse; they get a snapshot of their own stability and spread. If they find they’re putting the same strategies on repeat, they can decide to change things up—play pickleball instead of binge-eating pickles, for instance.

“There are some times when it makes sense to choose the same strategy,” Moulder says, “but we know from prior research that there are some times when it makes sense to become more adaptive—to increase, to spread, to try other things.”

Moulder adds that the knowledge gleaned from transition matrices can also be turned toward potentially more effective approaches to emotion regulation. He and Daniel call one idea “just-in-time interventions.” 

“If we are, let’s say, giving individuals telehealth, which is a really big space right now for therapy, we want to do something called just-in-time interventions,” he says. By understanding a person’s regulation practices, “we can say to that person, ‘Hey, you keep going to drink almost every time something negative happens. Maybe this time go read a book or a call a friend.’ We can offer alternatives that research shows will lead to better outcomes.”

The power of such interventions lies in their precision. They’re based not purely on statistics, Moulder says, but on “person-specific analysis, which we can use to give people personalized messaging that would ideally best help them in the long run.”

There’s no guarantee that switching strategies will bring the desired outcome, Moulder admits, but experimentation is part of the process. “We’re never going to know what works until we try.” 

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