Scientists determine four personality types based on new data

EVANSTON, Ill. — Northwestern University researchers reviewed data from more than 1.5 million respondents and found that there are at least four types of personality types: average, reserved, egocentric, and model. The results challenge existing paradigms in psychology.

The new study, led by Luís Amaral of the McCormick School of Engineering, will be published on September 17 by the journal Human behavior nature. The findings could potentially be of interest to hiring managers and mental health providers.

"People have been trying to classify personality types since the time of Hippocrates, but previous scientific literature found this absurd," said co-author William Revelle, a professor of psychology at Weinberg College of Medicine. Arts and Sciences.

"Now these data show that there are higher densities of certain personality types," said Revelle, specializing in personality measurement, theory, and research.

At first, however, Revelle was skeptical about the premise of the study. The concept of personality types remains controversial in psychology, with scientific evidence difficult to find. Previous attempts based on small research groups have produced results that are often not reproducible.

"Personality types only existed in the self-help literature and had no place in scientific journals," said Amaral, professor of chemical and biological engineering at Ernstus Otis Haven at Northwestern Engineering. "Now we think that will change because of this study."

The new study combined an alternative computing approach with data from four questionnaires with over 1.5 million respondents from around the world, obtained from John Johnson's IPIP-NEO with respectively 120 and 300 elements, the myPersonality project. and the BBC Big Personality Test data sets. The questionnaires, developed by the research community over the decades, have between 44 and 300 questions. People voluntarily take online questionnaires attracted by the opportunity to receive comments about their own personality. These data are now available to other researchers for independent analysis.

"What's really great is that a study with a data set of this size would not have been possible before the web," said Amaral. "Previously, maybe the researchers would recruit undergraduates on campus, and maybe a few hundred people, now we have all these online resources available, and now the data is shared."

From these robust data sets, the team drew the five broadly accepted fundamental personality traits: neurosis, extroversion, openness, agreeableness, and dedication.

After developing new algorithms, four groups emerged:

Average

The average people are rich in neurotism and extroversion, but not very open. "I would expect the typical person to be part of this group," said Martin Gerlach, a postdoctoral fellow at Amaral's lab and first author of the journal. Women are more likely than men to fall into the average type.

Reserve

The Reserved type is emotionally stable, but not open or neurotic. They are not particularly extroverted but are rather pleasant and conscientious.

Role models

The models have a low neurosis score and a high level in all other traits. The probability that someone is a model increases considerably with age. "These are people who are reliable and open to new ideas," said Amaral. "They are good people to be in charge of things – in fact, life is easier if you have more relationships with models." More women than men are likely to be role models.

Self-centered

Self-centered people score very high on extroversion and below average in terms of openness, friendliness and awareness. "These are people you do not want to hang out with," said Revelle. There is a dramatic decrease in the number of egocentric types as people age, both in women and in men.

The group's first attempt to sort the data used traditional clustering algorithms, but this yielded inaccurate results, said Amaral.

"At first they came to me with 16 personality types, and there is enough literature that I'm aware of that says it's ridiculous," Revelle said. "I thought there was none at all."

He challenged Amaral and Gerlach to refine their data.

"Machine learning and data science are promising but can be considered a little religion," said Amaral. "You still have to test your results and we've developed a new method to guide people to solve the clustering problem to test the results."

Their algorithm first looked for many clusters using traditional clustering methods, and then reconverted them by imposing additional constraints. This procedure revealed the four groups reported.

"The data came back and they continued to have the same four clusters of higher density and density than you would expect by chance, and you can show by replication that this is statistically unlikely. "said Revelle.

"I like the data and I believe in these results," he added. "Methodology is the main part of the article's contribution to science."

To ensure that new type groups were accurate, researchers used a notoriously self-centered group – adolescents – to validate their information.

"We know that teenagers behave in an egocentric way," said Amaral. "If the data was correct and sorted according to demographic data, it would turn out to be the largest cluster of people."

Indeed, young men are overrepresented in the self-centered group, while women over 15 are significantly underrepresented.

In addition to being a tool that can help mental health providers assess personality types with extreme traits, Amaral said the study's findings could be useful to managers looking to ensure a potential candidate or to people who go out together. for a suitable partner.

And good news for teen parents everywhere: as people grow up, their personality types change often. For example, older people tend to be less neurotic but more conscientious and pleasant than those under 20 years of age.

"When we look at large groups of people, it is clear that there are trends, that some people may change some of these characteristics over time," Amaral said. "This could be the subject of future research."

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The research was funded by a donation from Mac and Leslie McQuown, with support from the Defense Research Bureau of the Defense Department and the National Science Foundation.

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