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Big Five Personality Traits: The OCEAN Model Explained

“Who are you?”

It’s a simple enough question, but it’s one of the hardest ones to answer.

There are many ways to interpret that question. An answer could include your name, your job title, your role in your family, your hobbies or passions, and your place of residence or birth. A more comprehensive answer might include a description of your beliefs and values.

Every one of us has a different answer to this question, and each answer tells a story about who we are. While we may have a lot in common with our fellow humans, like race, religion, sexual orientation, skills, and eye color, there is one thing that makes us each unique: personality.

You can meet hundreds, thousands, or even tens of thousands of people, but no two will be exactly the same. Which raises the question: how do we categorize and classify something as widely varied as personality?

In this article, we’ll define what personality is, explore the different ways personalities can be classified (and how those classifications have evolved), and explain the OCEAN model, one of the most ubiquitous personality inventories in modern psychology.

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This Article Contains

What is personality, personality research: a brief review, ocean: the five factors, the trait network, assessing the big five, a take-home message, frequently asked questions.

Personality is an easy concept for most of us to grasp. It’s what makes you, you. It encompasses all the traits, characteristics, and quirks that set you apart from everyone else.

In the world of psychology research, personality is a little more complicated. The definition of personality can be complex, and the way it is defined can influence how it is understood and measured.

According to the researchers at the Personality Project, personality is “the coherent pattern of affect, cognition, and desires (goals) as they lead to behavior” (Revelle, 2013).

Meanwhile, the American Psychological Association (APA) defines personality as “individual differences in characteristic patterns of thinking, feeling, and behaving” (2017).

However you define personality, it’s an important part of who you are. In fact, personality shows a positive correlation with life satisfaction (Boyce, Wood, & Powdthavee, 2013). With personality having such a large impact on our lives, it’s important to have a reliable way to conceptualize and measure it.

The most prevalent personality framework is the Big Five, also known as the five-factor model of personality. Not only does this theory of personality apply to people in many countries and cultures around the world (Schmitt et al., 2007), it provides a reliable assessment scale for measuring personality.

To understand how we got to the Big Five, we have to go back to the beginning of personality research.

Ancient Greece

It seems that for as long as there have been humans with personalities, there have been personality theories and classification systems.

The ancient Greek physician Hippocrates hypothesized that two binaries define temperament: hot versus cold and moist versus dry. This theory resulted in four possible temperaments (hot/moist, hot/dry, cold/moist, cold/dry) called humors , which were thought to be key factors in both physical health issues and personality peculiarities.

Later, the philosopher Plato suggested a classification of four personality types or factors: artistic (iconic), sensible (pistic), intuitive (noetic), and reasoning (dianoetic).

Plato’s renowned student Aristotle mused on a possible connection between the physical body and personality, but this connection was not a widespread belief until the rise of phrenology and the shocking case of Phineas Gage.

Phrenology and Phineas Gage

Phrenology, a pseudoscience that is not based on any verifiable evidence, was promoted by a neuroanatomist named Franz Gall in the late 18th century. Phrenology hypothesizes a direct relationship between the physical properties of different areas of the brain (such as size, shape, and density) and opinions, attitudes, and behaviors.

While phrenology was debunked relatively quickly, it marked one of the first attempts to tether an individual’s traits and characteristics to the physical brain. And it wasn’t long before actual evidence of this connection presented itself.

In 1848, one man’s unfortunate accident forever changed mainstream views on the interconnectivity of the brain and personality.

A railroad construction worker named Phineas Gage was on the job when a premature detonation of explosive powder launched a 3.6 foot (1.1 m), 13.25 pound (6 kg) iron rod into Gage’s left cheek, through his head, and out the other side.

Gage, astonishingly, survived the incident, and his only physical ailments (at first) were blindness in his left eye and a wound where the rod penetrated his head.

However, his friends reported that his personality had completely changed after the accident—suddenly he could not keep appointments, showed little respect or compassion for others, and uttered “the grossest profanity.” He died in 1860 after suffering from a series of seizures (Twomey, 2010).

This was the first case that was widely recognized as clear evidence of a link between the physical brain and personality, and it gained national attention. Interest in the psychological conception of personality spiked, leading to the next phase in personality research.

Sigmund Freud

The Austrian neurologist Sigmund Freud is best known as the father of psychoanalysis , an intensive form of therapy that digs deep into an individual’s life—especially childhood—to understand and treat psychological ailments.

However, Freud also focused on personality, and some of his ideas are familiar to many people. One of his most fleshed-out theories held that the human mind consists of three parts: the id, the ego, and the superego.

The id is the primal part of the human mind that runs on instinct and aims for survival at all costs. The ego bridges the gap between the id and our day-to-day experiences, providing realistic ways to achieve the wants and needs of the id and coming up with justifications for these desires.

The superego is the part of the mind that represents humans’ higher qualities, providing the moral framework that humans use to regulate their baser behavior.

While scientific studies have largely not supported Freud’s idea of a three-part mind, this theory did bring awareness to the fact that at least some thoughts, behaviors, and motivations are unconscious. After Freud, people began to believe that behavior was truly the tip of the iceberg when assessing a person’s attitudes, opinions, beliefs, and unique personality.

Swiss psychiatrist Carl Jung was influenced by Freud, his mentor, but ultimately came up with his own system of personality. Jung believed that there were some overarching types of personality that each person could be classified into based on dichotomous variables.

For example, Jung believed that individuals were firmly within one of two camps:

• Introverts , who gain energy from the “internal world” or from solitude with the self;
• Extroverts, who gain energy from the “external world” or from interactions with others.

This idea is still prevalent today, and research has shown that this is a useful differentiator between two relatively distinct types of people. Today, most psychologists see introversion and extroversion as existing on a spectrum rather than a binary. It can also be situational, as some situations exhaust our energy one day and on other days, fuel us to be more social.

Jung also identified what he found to be four essential psychological functions:

He believed that each of these functions could be experienced in an introverted or extroverted fashion and that one of these functions is more dominant than the others in each person.

Jung’s work on personality had a huge impact on the field of personality research that’s still felt today. In fact, the popular Myers-Briggs Type Indicator® test is based in part on Jung’s theories of personality.

Abraham Maslow and Carl Rogers

American psychologist Abraham Maslow furthered an idea that Freud brought into the mainstream: At least some aspects or drivers of personality are buried deep within the unconscious mind.

Maslow hypothesized that personality is driven by a set of needs that each human has. He organized these needs into a hierarchy, with each level requiring fulfillment before a higher level can be fulfilled.

The pyramid is organized from bottom to top (pictured to the right), beginning with the most basic need (McLeod, 2007):

• Physiological needs (food, water, warmth, rest);
• Safety needs (security, safety);
• Belongingness and love needs (intimate relationships, friends);
• Esteem needs (prestige and feelings of accomplishment);
• Self-actualization needs (achieving one’s full potential, self-fulfillment).

Maslow believed that all humans aim to fulfill these needs, usually in order from the most basic to the most transcendent, and that these motivations result in the behaviors that make up a personality.

Carl Rogers , another American psychologist, built upon Maslow’s work, agreeing that all humans strive to fulfill needs, but Rogers disagreed that there is a one-way relationship between striving toward need fulfillment and personality. Rogers believed that the many different methods humans use to meet these needs spring from personality, rather than the other way around.

Rogers’ contributions to the field of personality research signaled a shift in thinking about personality. Personality was starting to be seen as a collection of traits and characteristics that were not necessarily permanent rather than a single, succinct construct that can be easily described.

Multiple Personality Traits

In the 1940s, German-born psychologist Hans Eysenck built off of Jung’s dichotomy of introversion versus extroversion, hypothesizing that there were only two defining personality traits : extroversion and neuroticism. Individuals could be high or low on each of these traits, leading to four key types of personalities.

Eysenck also connected personality to the physical body in a greater way than most earlier psychology researchers and philosophers. He posited that differences in the limbic system resulted in varying hormones and hormonal activation. Those who were already highly stimulated (introverts) would naturally seek out less stimulation while those who were naturally less stimulated (extroverts) would search for greater stimulation.

Eysenck’s thoroughness in connecting the body to the mind and personality pushed the field toward a more scientific exploration of personality based on objective evidence rather than solely philosophical musings.

American psychologist Lewis Goldberg may be the most prominent researcher in the field of personality psychology. His groundbreaking work whittled down Raymond Cattell’s 16 “fundamental factors” of personality into five primary factors, similar to the five factors found by fellow psychology researchers in the 1960s.

The five factors Goldberg identified as primary factors of personality are:

Extroversion

Agreeableness, conscientiousness, neuroticism.

• Openness to experience

This five-factor model caught the attention of two other renowned personality researchers, Paul Costa and Robert McCrae, who confirmed the validity of this model. This model was named the “Big Five” and launched thousands of explorations of personality within its framework, across multiple continents and cultures and with a wide variety of populations.

The Big Five brings us right up to the current era in personality research. The Big Five theory still holds sway as the prevailing theory of personality, but some salient aspects of current personality research include:

• Conceptualizing traits on a spectrum instead of as dichotomous variables;
• Contextualizing personality traits (exploring how personality shifts based on environment and time);
• Emphasizing the biological bases of personality and behavior.

Since the Big Five is still the most mainstream and widely accepted framework for personality, the rest of this piece will focus exclusively on this framework.

As noted above, the five factors grew out of decades of personality research, growing from the foundations of Cattell’s 16 factors and eventually becoming the most accepted model of personality to date. This model has been translated into several languages and applied in dozens of cultures, resulting in research that not only confirms its validity as a theory of personality but also establishes its validity on an international level.

These five factors do not provide completely exhaustive explanations of personality, but they are known as the Big Five because they encompass a large portion of personality-related terms. The five factors are not necessarily traits in and of themselves, but factors in which many related traits and characteristics fit.

For example, the factor agreeableness encompasses terms like generosity, amiability, and warmth on the positive side and aggressiveness and temper on the negative side. All of these traits and characteristics (and many more) make up the broader factor of agreeableness.

Below, we’ll explain each factor in more detail and provide examples and related terms to help you get a sense of what aspects and quirks of personality these factors cover.

A popular acronym for the Big Five is OCEAN. The five factors are laid out in that order here.

1. Openness to Experience

Openness to experience has been described as the depth and complexity of an individual’s mental life and experiences (John & Srivastava, 1999). It is also sometimes called intellect or imagination.

Openness to experience concerns people’s willingness to try to new things, their ability to be vulnerable, and their capability to think outside the box.

Common traits related to openness to experience include:

• Imagination;
• Insightfulness;
• Varied interests;
• Originality;
• Daringness;
• Preference for variety;
• Cleverness;
• Creativity;
• Perceptiveness;
• Complexity/depth.

An individual who is high in openness to experience is likely someone who has a love of learning, enjoys the arts, engages in a creative career or hobby, and likes meeting new people (Lebowitz, 2016a).

An individual who is low in openness to experience probably prefers routine over variety, sticks to what he or she knows, and prefers less abstract arts and entertainment.

2. Conscientiousness

Conscientiousness is a trait that can be described as the tendency to control impulses and act in socially acceptable ways, behaviors that facilitate goal-directed behavior (John & Srivastava, 1999). Conscientious people excel in their ability to delay gratification, work within the rules, and plan and organize effectively.

Traits within the conscientiousness factor include:

• Persistence;
• Thoroughness;
• Self-discipline ;
• Consistency;
• Predictability;
• Reliability;
• Resourcefulness;
• Perseverance;

People high in conscientiousness are likely to be successful in school and in their careers, to excel in leadership positions , and to doggedly pursue their goals with determination and forethought (Lebowitz, 2016a).

People low in conscientiousness are much more likely to procrastinate and to be flighty, impetuous, and impulsive.

3. Extroversion

It concerns where an individual draws their energy from and how they interact with others. In general, extroverts draw energy from or recharge by interacting with others, while introverts get tired from interacting with others and replenish their energy with solitude.

• Sociableness;
• Assertiveness ;
• Outgoing nature;
• Talkativeness;
• Ability to be articulate;
• Fun-loving nature;
• Tendency for affection;
• Friendliness;
• Social confidence.

The traits associated with extroversion are:

People high in extroversion tend to seek out opportunities for social interaction, where they are often the “life of the party.” They are comfortable with others, are gregarious, and are prone to action rather than contemplation (Lebowitz, 2016a).

People low in extroversion are more likely to be people “of few words who are quiet, introspective, reserved, and thoughtful.

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4. Agreeableness

This factor concerns how well people get along with others. While extroversion concerns sources of energy and the pursuit of interactions with others, agreeableness concerns one’s orientation to others. It is a construct that rests on how an individual generally interacts with others.

The following traits fall under the umbrella of agreeableness:

• Humbleness;
• Moderation;
• Politeness;
• Unselfishness;
• Helpfulness;
• Sensitivity;
• Amiability;
• Cheerfulness;
• Consideration.

People high in agreeableness tend to be well-liked, respected, and sensitive to the needs of others. They likely have few enemies and are affectionate to their friends and loved ones, as well as sympathetic to the plights of strangers (Lebowitz, 2016a).

People on the low end of the agreeableness spectrum are less likely to be trusted and liked by others. They tend to be callous, blunt, rude, ill-tempered, antagonistic, and sarcastic. Although not all people who are low in agreeableness are cruel or abrasive, they are not likely to leave others with a warm fuzzy feeling.

5. Neuroticism

These traits are commonly associated with neuroticism:

• Awkwardness;
• Pessimism ;
• Nervousness;
• Self-criticism;
• Lack of confidence ;
• Insecurity;
• Instability;
• Oversensitivity.

Those high in neuroticism are generally prone to anxiety, sadness, worry, and low self-esteem. They may be temperamental or easily angered, and they tend to be self-conscious and unsure of themselves (Lebowitz, 2016a).

Individuals who score on the low end of neuroticism are more likely to feel confident, sure of themselves, and adventurous. They may also be brave and unencumbered by worry or self-doubt.

Because the Big Five are so big, they encompass many other traits and bundle related characteristics into one cohesive factor.

Openness to Experience

Openness to experience has been found to contribute to one’s likelihood of obtaining a leadership position , likely due to the ability to entertain new ideas and think outside the box (Lebowitz, 2016a). Openness is also connected to universalism values, which include promoting peace and tolerance and seeing all people as equally deserving of justice and equality (Douglas, Bore, & Munro, 2016).

Further, research has linked openness to experience with broad intellectual skills and knowledge, and it may increase with age (Schretlen, van der Hulst, Pearlson, & Gordon, 2010). This indicates that openness to experience leads to gains in knowledge and skills, and it naturally increases as a person ages and has more experiences to learn from.

Not only has openness been linked to knowledge and skills, but it was also found to correlate positively with creativity, originality, and a tendency to explore their inner selves with a therapist or psychiatrist, and to correlate negatively with conservative political attitudes (Soldz & Vaillant, 1999).

Not only has openness been found to correlate with many traits, but it has also been found to be extremely stable over time—one study explored trait stability over 45 years and found participants’ openness to experience (along with extroversion and neuroticism) remained relatively stable over that period (Soldz & Vaillant, 1999)

Concerning the other Big Five factors, openness to experience is weakly related to neuroticism and extroversion and is mostly unrelated to agreeableness and conscientiousness (Ones, Viswesvaran, & Reiss, 1996).

Openness to experience is perhaps the trait that is least likely to change over time, and perhaps most likely to help an individual grow . Those high in openness to experience should capitalize on their advantage and explore the world, themselves, and their passions. These individuals make strong and creative leaders and are most likely to come up with the next big innovation.

This factor has been linked to achievement, conformity, and seeking out security, as well as being negatively correlated to placing a premium on stimulation and excitement (Roccas, Sagiv, Schwartz, & Knafo, 2002). Those high in conscientiousness are also likely to value order, duty, achievement, and self-discipline, and they consciously practice deliberation and work toward increased competence (Roccas, Sagiv, Schwartz, & Knafo, 2002).

In light of these correlations, it’s not surprising that conscientiousness is also strongly related to post-training learning (Woods, Patterson, Koczwara, & Sofat, 2016), effective job performance (Barrick & Mount, 1991), and intrinsic and extrinsic career success (Judge, Higgins, Thoresen, & Barrick, 1999).

The long-term study by Soldz and Vaillant (1999) found that conscientiousness was positively correlated with adjustment to life’s challenges and mature defensive responses, indicating that those high in conscientiousness are often well-prepared to tackle any obstacles that come their way.

Conscientiousness is negatively correlated with depression, smoking, substance abuse, and engagement in psychiatric treatment. The trait was also found to correlate somewhat negatively with neuroticism and somewhat positively with agreeableness, but it had no discernible relation to the other factors (Ones, Viswesvaran, & Reiss, 1996).

From these results, it’s clear that those gifted with high conscientiousness have a distinct advantage over those who are not. Those with high conscientiousness should attempt to use their strengths to the best of their abilities, including organization, planning, perseverance, and tendency towards high achievement.

As long as the highly conscientious do not fall prey to exaggerated perfectionism, they are likely to achieve many of the traditional markers of success.

Extroverts are often assertive, active, and sociable, shunning self-denial in favor of excitement and pleasure.

Considering these findings, it follows that high extroversion is a strong predictor of  leadership , and contributes to the success of managers and salespeople as well as the success of all job levels in training proficiency (Barrick & Mount, 1991).

Over a lifetime, high extroversion correlates positively with a high income, conservative political attitudes, early life adjustment to challenges, and social relationships (Soldz & Vaillant, 1999).

The same long-term study also found that extroversion was fairly stable across the years, indicating that extroverts and introverts do not often shift into the opposite state (Soldz & Vaillant, 1999).

Because of its ease of measurement and general stability over time, extroversion is an excellent predictor of effective functioning and general well-being (Ozer & Benet-Martinez, 2006), positive emotions (Verduyn & Brans, 2012), and overconfidence in task performance (Schaefer, Williams, Goodie, & Campbell, 2004).

When analyzed in relation to the other Big Five factors, extroversion correlated weakly and negatively with neuroticism and was somewhat positively related to openness to experience (Ones, Viswesvaran, & Reiss, 1996).

Those who score high in extroversion are likely to make friends easily and enjoy interacting with others, but they may want to pay extra attention to making well-thought-out decisions and considering the needs and sensitivities of others.

Agreeableness may be motivated by the desire to fulfill social obligations or follow established norms, or it may spring from a genuine concern for the welfare of others. Whatever the motivation, it is rarely accompanied by cruelty, ruthlessness, or selfishness (Roccas, Sagiv, Schwartz, & Knafo, 2002).

Those high in agreeableness are also more likely to have positive peer and family relationships, model  gratitude  and forgiveness , attain desired jobs, live long lives, experience relationship satisfaction, and volunteer in their communities (Ozer & Benet-Martinez, 2006).

Agreeableness affects many life outcomes because it influences any arena in which interactions with others are important—and that includes almost everything. In the long-term, high agreeableness is related to strong social support and healthy midlife adjustment but is slightly negatively correlated to creativity (Soldz & Vaillant, 1999).

Those who are friendly and endearing to others may find themselves without the motivation to achieve a traditional measure of success, and they might choose to focus on family and friends instead.

Agreeableness correlates weakly with extroversion and is somewhat negatively related to neuroticism and somewhat positively correlated to conscientiousness (Ones, Viswesvaran, & Reiss, 1996).

Individuals high in agreeableness are likely to have many close friends and a good relationship with family members, but there is a slight risk of consistently putting others before themselves and missing out on opportunities for success, learning, and development.

Those who are friendly and agreeable to others can leverage their strengths by turning to their social support networks for help when needed and finding fulfillment in positive engagement with their communities.

Neuroticism has been found to correlate negatively with self-esteem and general self-efficacy , as well as with an internal locus of control (feeling like one has control over his or her own life) (Judge, Erez, Bono, & Thoresen, 2002). In fact, these four traits are so closely related that they may fall under one umbrella construct.

In addition, neuroticism has been linked to poorer job performance and lower motivation, including motivation related to goal-setting and self-efficacy (Judge & Ilies, 2002). It likely comes as no surprise that instability and vulnerability to stress and anxiety do not support one’s best work.

The anxiety and self-consciousness components of neuroticism are also positively linked to more traditional values and are negatively correlated with achievement values.

The hostility and impulsiveness components of neuroticism relate positively to hedonism (or seeking pleasure without regards to the long-term and a disregard for right and wrong) and negatively relate to benevolence, tradition, and conformity (Roccas, Sagiv, Schwartz, & Knafo, 2002).

The 45-year-long study from researchers Soldz and Vaillant showed that neuroticism, over the course of the study, was negatively correlated with smoking cessation and healthy adjustment to life and correlated positively with drug usage, alcohol abuse, and mental health issues (1999).

Neuroticism was found to correlate somewhat negatively with agreeableness and conscientiousness, in addition to a weak, negative relationship with extroversion and openness to experience (Ones, Viswevaran, & Reiss, 1996).

Overall, high neuroticism is related to added difficulties in life, including addiction, poor job performance, and unhealthy adjustment to life’s changes. Scoring high on neuroticism is not an immediate sentence to a miserable life, but those in this group would benefit from investing in improvements to their self-confidence, building resources to draw on in times of difficulty, and avoiding any substances with addictive properties.

Big Five Inventory

This inventory was developed by Goldberg in 1993 to measure the five dimensions of the Big Five personality framework. It contains 44 items and measures each factor through its corresponding facets:

• Extroversion;
• Gregariousness;
• Assertiveness;
• Excitement-seeking;
• Positive emotions ;
• Agreeableness;
• Straightforwardness;
• Compliance;
• Tender-mindedness;
• Conscientiousness;
• Competence;
• Dutifulness;
• Achievement striving;
• Self-discipline;
• Deliberation;
• Neuroticism;
• Angry hostility;
• Depression;
• Self-consciousness;
• Impulsiveness;
• Vulnerability;
• Openness to experience;
• Aesthetics;

The responses to items concerning these facets are combined and summarized to produce a score on each factor. This inventory has been widely used in psychology research and is still quite popular, although the Revised NEO Personality Inventory has also gained much attention in recent years.

To learn more about the BFI or to see the items, click  here to find a PDF with more information.

Revised NEO Personality Inventory

The original NEO Personality Inventory was created by personality researchers Paul Costa Jr. and Robert McCrae in 1978. It was later revised several times to keep up with advancements (in 1990, 2005, and 2010). Initially, the NEO Personality Inventory was named for the three main domains as the researchers understood them at the time: neuroticism, extroversion, and openness.

This scale is also based on the six facets of each factor and includes 240 items rated on a 5-point scale. For a shorter scale, Costa and McCrae also offer the NEO Five-Factor Inventory, which contains only 60 items and measures just the overall domains instead of all facets.

The NEO PI-R requires only a 6th-grade reading level and can be self-administered without a scoring professional.

Access to the NEO PI-R isn’t as widely available as the BFI, so you will have to dig around to obtain it.

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Personality is a complex topic of research in psychology, and it has a long history of shifting philosophies and theories. While it’s easy to conceptualize personality on a day-to-day level, conducting valid scientific research on personality can be much more complex.

The Big Five can help you to learn more about your own personality and where to focus your energy and attention. The first step in effectively leveraging your strengths is to learn what your strengths are.

Whether you use the Big Five Inventory, the NEO PI-R, or something else entirely, we hope you’re able to learn where you fall on the OCEAN spectrums.

What do you think about the OCEAN model? Do you think the traits it describes apply to your personality? Let us know in the comments below.

We hope you enjoyed reading this article. Don’t forget to download our three Strengths Exercises for free .

The most widely used Big Five personality test is the Revised NEO Personality Inventory (NEO-PI-R), which contains a total of 240 questions (Costa & McCrae, 1992).

Yes, the Big Five personality test is generally considered to be reliable, with research indicating that the five dimensions of personality are consistent across different cultures and can reliably predict a range of behaviors and outcomes (Costa & McCrae, 2008).

A quick example of a few personality questions includes:

• Do you prefer spending time alone or with a large group of people?
• How often do you take risks or try new things?
• When faced with a problem, do you rely more on your intuition or your logical thinking?
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• Soldz, S., & Vaillant, G. E. (1999). The Big Five personality traits and the life course: A 45-year longitudinal study. Journal of Research in Personality, 33 , 208-232.
• Twomey, S. (2010, January). Phineas Gage: Neuroscience’s most famous patient. Smithsonian. Retrieved from http://www.smithsonianmag.com/history/phineas-gage-neurosciences-most-famous-patient-11390067/
• Verduyn, P., & Brans, K. (2012). The relationship between extroversion, neuroticism, and aspects of trait affect. Personality and Individual Differences, 52, 664-669.
• Woods, S. A., Patterson, F. C., Koczwara, A., & Sofat, J. A. (2016). The value of being a conscientious learner: Examining the effects of the big five personality traits on self-reported learning from training. Journal of Workplace Learning, 28 , 424-434.

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What our readers think.

To me the problem with the OCEAN model is that the Big Five have long lists of “positive” traits while the opposite has short “negative” traits. (See for example extroversion compared to introversion). I have noticed this in books on the topic as well. This seems biased to me as if some traits are preferred more than others.

This overview of the Big Five is the easiest to follow and comprehend for the not-so-psychology-educated psychology-interested person… Love it…

I agree with Mr. Bakker. This article leads me to questions I didn’t know I had! Thanks very much indeed.

There seem to be areas of the brain that become inactive, or drugged or damaged. It seems to me this topic is still trying to address mind/consciousness/soul? from a collection of factors that may intersect, have unions that are not exclusive. (not well expressed, sorry).

What part of the big five or the big five inventory can’t be attributed to genetics? How much of our personalities are inherited?

Interesting question! Research on the heritability of Big Five traits has shown genetic influence varying from 41-61% for each respective facet. This article outlines these findings nicely. If you are interested to read about the role of genetics in the manifestation of Big Five traits and the Dark Triad traits, then this article is also quite interesting.

I hope this helps!

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After nearly twenty years of reading blogs, this is the only one I continue to read (and I do it without fail each and every day). What a wonderful experience it has been to “get to know” about this platform and all of the excellent stuff that you guys are providing. Thank you. Weldon and I want to encourage you to keep up the fantastic effort.

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Big Five Personality Traits: The 5-Factor Model of Personality

Annabelle G.Y. Lim

Psychology Graduate

BA (Hons), Psychology, Harvard University

Annabelle G.Y. Lim is a graduate in psychology from Harvard University. She has served as a research assistant at the Harvard Adolescent Stress & Development Lab.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

The Big Five Personality Traits, also known as OCEAN or CANOE, are a psychological model that describes five broad dimensions of personality: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. These traits are believed to be relatively stable throughout an individual’s lifetime.

• Conscientiousness – impulsive, disorganized vs. disciplined, careful
• Agreeableness – suspicious, uncooperative vs. trusting, helpful
• Neuroticism – calm, confident vs. anxious, pessimistic
• Openness to Experience – prefers routine, practical vs. imaginative, spontaneous
• Extraversion – reserved, thoughtful vs. sociable, fun-loving

The Big Five remain relatively stable throughout most of one’s lifetime. They are influenced significantly by genes and the environment, with an estimated heritability of 50%. They also predict certain important life outcomes such as education and health.

Each trait represents a continuum. Individuals can fall anywhere on the continuum for each trait.

Unlike other trait theories that sort individuals into binary categories (i.e. introvert or extrovert ), the Big Five Model asserts that each personality trait is a spectrum.

Therefore, individuals are ranked on a scale between the two extreme ends of five broad dimensions:

For instance, when measuring Extraversion, one would not be classified as purely extroverted or introverted, but placed on a scale determining their level of extraversion.

By ranking individuals on each of these traits, it is possible to effectively measure individual differences in personality.

Conscientiousness

Conscientiousness describes a person’s ability to regulate impulse control to engage in goal-directed behaviors (Grohol, 2019). It measures elements such as control, inhibition, and persistence of behavior.

Facets of conscientiousness include the following (John & Srivastava, 1999):

• Dutifulness
• Achievement striving
• Self-disciplined
• Deliberation
• Incompetent
• Disorganized
• Procrastinates
• Indiscipline

Conscientiousness vs. Lack of Direction

Those who score high on conscientiousness can be described as organized, disciplined, detail-oriented, thoughtful, and careful. They also have good impulse control, which allows them to complete tasks and achieve goals.

Those who score low on conscientiousness may struggle with impulse control, leading to difficulty in completing tasks and fulfilling goals.

They tend to be more disorganized and may dislike too much structure. They may also engage in more impulsive and careless behavior.

Agreeableness

Agreeableness refers to how people tend to treat relationships with others. Unlike extraversion which consists of the pursuit of relationships, agreeableness focuses on people’s orientation and interactions with others (Ackerman, 2017).

Facets of agreeableness include the following (John & Srivastava, 1999):

• Trust (forgiving)
• Straightforwardness
• Altruism (enjoys helping)
• Sympathetic
• Insults and belittles others
• Unsympathetic
• Doesn’t care about how other people feel

Agreeableness vs. Antagonism

Those high in agreeableness can be described as soft-hearted, trusting, and well-liked. They are sensitive to the needs of others and are helpful and cooperative. People regard them as trustworthy and altruistic.

Those low in agreeableness may be perceived as suspicious, manipulative, and uncooperative. They may be antagonistic when interacting with others, making them less likely to be well-liked and trusted.

Extraversion

Extraversion reflects the tendency and intensity to which someone seeks interaction with their environment, particularly socially. It encompasses the comfort and assertiveness levels of people in social situations.

Additionally, it also reflects the sources from which someone draws energy.

Facets of extraversion include the following (John & Srivastava, 1999):

• Energized by social interaction
• Excitement-seeking
• Enjoys being the center of attention
• Prefers solitude
• Fatigued by too much social interaction
• Dislikes being the center of attention

Extraversion vs. Introversion

Those high on extraversion are generally assertive, sociable, fun-loving, and outgoing. They thrive in social situations and feel comfortable voicing their opinions. They tend to gain energy and become excited from being around others.

Those who score low in extraversion are often referred to as introverts . These people tend to be more reserved and quieter. They prefer listening to others rather than needing to be heard.

Introverts often need periods of solitude in order to regain energy as attending social events can be very tiring for them.

Of importance to note is that introverts do not necessarily dislike social events, but instead find them tiring.

Openness to Experience

Openness to experience refers to one’s willingness to try new things as well as engage in imaginative and intellectual activities. It includes the ability to “think outside of the box.”

Facets of openness include the following (John & Srivastava, 1999):

• Imaginative
• Open to trying new things
• Unconventional
• Predictable
• Not very imaginative
• Dislikes change
• Prefer routine
• Traditional

Openness vs. Closedness to Experience

Those who score high on openness to experience are perceived as creative and artistic. They prefer variety and value independence. They are curious about their surroundings and enjoy traveling and learning new things.

People who score low on openness to experience prefer routine. They are uncomfortable with change and trying new things, so they prefer the familiar over the unknown.

As they are practical people, they often find it difficult to think creatively or abstractly.

Neuroticism

Neuroticism describes the overall emotional stability of an individual through how they perceive the world. It takes into account how likely a person is to interpret events as threatening or difficult.

It also includes one’s propensity to experience negative emotions.

Facets of neuroticism include the following (John & Srivastava, 1999):

• Angry hostility (irritable)
• Experiences a lot of stress
• Self-consciousness (shy)
• Vulnerability
• Experiences dramatic shifts in mood
• Doesn”t worry much
• Emotionally stable
• Rarely feels sad or depressed

Neuroticism vs. Emotional Stability

Those who score high on neuroticism often feel anxious, insecure and self-pitying. They are often perceived as moody and irritable. They are prone to excessive sadness and low self-esteem.

Those who score low on neuroticism are more likely to calm, secure and self-satisfied. They are less likely to be perceived as anxious or moody. They are more likely to have high self-esteem and remain resilient.

Behavioral Outcomes

Relationships.

In marriages where one partner scores lower than the other on agreeableness, stability, and openness, there is likely to be marital dissatisfaction (Myers, 2011).

Neuroticism seems to be a risk factor for many health problems, including depression, schizophrenia, diabetes, asthma, irritable bowel syndrome, and heart disease (Lahey, 2009).

People high in neuroticism are particularly vulnerable to mood disorders such as depression . Low agreeableness has also been linked to higher chances of health problems (John & Srivastava, 1999).

There is evidence to suggest that conscientiousness is a protective factor against health diseases. People who score high in conscientiousness have been observed to have better health outcomes and longevity (John & Srivastava, 1999).

Researchers believe that such is due to conscientious people having regular and well-structured lives, as well as the impulse control to follow diets, treatment plans, etc.

A high score on conscientiousness predicts better high school and university grades (Myers, 2011). Contrarily, low agreeableness and low conscientiousness predict juvenile delinquency (John & Srivastava, 1999).

Conscientiousness is the strongest predictor of all five traits for job performance (John & Srivastava, 1999). A high score of conscientiousness has been shown to relate to high work performance across all dimensions.

The other traits have been shown to predict more specific aspects of job performance. For instance, agreeableness and neuroticism predict better performance in jobs where teamwork is involved.

However, agreeableness is negatively related to individual proactivity. Openness to experience is positively related to individual proactivity but negatively related to team efficiency (Neal et al., 2012).

Extraversion is a predictor of leadership, as well as success in sales and management positions (John & Srivastava, 1999).

Media Preference

Manolika (2023) examined how the Big Five personality traits relate to preferences for different genres of movies and books. The study surveyed 386 university students on their Big Five traits and preferences for 21 movie and 27 book types.

Results showed openness to experience predicted liking complex movies like documentaries and unconventional books like philosophy. This aligns with past research showing open people like cognitively challenging art (Swami & Furnham, 2019).

Conscientiousness predicted preferring informational books, while agreeableness predicted conventional genres like family movies and romance books.

Neuroticism only predicted preferring light books, not movies. Extraversion did not predict preferences, contrary to hypotheses.

Overall, the Big Five traits differentially predicted media preferences, suggesting people select entertainment that satisfies psychological needs and reflects aspects of their personalities (Rentfrow et al., 2011).

Open people prefer complex stimulation, conscientious people prefer practical content, agreeable people prefer conventional genres, and neurotic people use light books for mood regulation. Extraversion may relate more to social motivations for media use.

Critical Evaluation

Descriptor rather than a theory.

The Big Five was developed to organize personality traits rather than as a comprehensive theory of personality. Therefore, it is more descriptive than explanatory and does not fully account for differences between individuals (John & Srivastava, 1999). It also does not sufficiently provide a causal reason for human behavior.

Cross-Cultural Validity

Although the Big Five has been tested in many countries and its existence is generally supported by findings (McCrae, 2002), there have been some studies that do not support its model. Most previous studies have tested the presence of the Big Five in urbanized, literate populations.

A study by Gurven et al. (2013) was the first to test the validity of the Big Five model in a largely illiterate, indigenous population in Bolivia. They administered a 44-item Big Five Inventory but found that the participants did not sort the items in consistency with the Big Five traits.

More research on illiterate and non-industrialized populations is needed to clarify such discrepancies.

Gender Differences

Differences in the Big Five personality traits between genders have been observed, but these differences are small compared to differences between individuals within the same gender.

Costa et al. (2001) gathered data from over 23,000 men and women in 26 countries. They found that “gender differences are modest in magnitude, consistent with gender stereotypes, and replicable across cultures” (p. 328). Women reported themselves to be higher in Neuroticism, Agreeableness, Warmth (a facet of Extraversion), and Openness to Feelings compared to men. Men reported themselves to be higher in Assertiveness (a facet of Extraversion) and Openness to Ideas.

Another interesting finding was that bigger gender differences were reported in Western, industrialized countries. Researchers proposed that the most plausible reason for this finding was attribution processes.

They surmised that the actions of women in individualistic countries would be more likely to be attributed to their personality, whereas actions of women in collectivistic countries would be more likely to be attributed to their compliance with gender role norms.

Factors that Influence the Big 5

Like with all theories of personality , the Big Five is influenced by both nature and nurture . Twin studies have found that the heritability (the amount of variance that can be attributed to genes) of the Big Five traits is 40-60%.

Jang et al. (1996) conducted a study with 123 pairs of identical twins and 127 pairs of fraternal twins. They estimated the heritability of conscientiousness, agreeableness, neuroticism, openness to experience, and extraversion to be 44%, 41%, 41%, 61%, and 53%, respectively. This finding was similar to the findings of another study, where the heritability of conscientiousness, agreeableness, neuroticism, openness to experience and extraversion were estimated to be 49%, 48%, 49%, 48%, and 50%, respectively (Jang et al., 1998).

Such twin studies demonstrate that the Big Five personality traits are significantly influenced by genes and that all five traits are equally heritable. Heritability for males and females does not seem to differ significantly (Leohlin et al., 1998).

Studies from different countries also support the idea of a strong genetic basis for the Big Five personality traits (Riemann et al., 1997; Yamagata et al., 2006).

Roehrick et al. (2023) examined how Big Five traits (extraversion, agreeableness, conscientiousness, neuroticism, openness) and context relate to smartphone use. The study used surveys, experience sampling, and smartphone sensing to track college students’ personality, context, and hourly smartphone behaviors over one week.

They found extraverts used their phones more frequently once checked, but conscientious people were less likely to use their phone and used them for shorter durations. Smartphones were used in public, with weaker social ties, and during class/work activities. They were used less with close ties. Perceived situations didn’t relate much to use.

Most variability in use was within-person, suggesting context matters more than personality for smartphone behaviors. Comparisons showed context-explained duration of use over traits and demographics, but not frequency.

The key implication is that both personality and context are important to understanding digital behavior. Extraversion and conscientiousness were the most relevant of the Big Five for smartphone use versus non-use and degree of use. Contextual factors like location, social ties, and activities provided additional explanatory power, especially for the duration of smartphone use.

Stability of the Traits

People’s scores of the Big Five remain relatively stable for most of their life with some slight changes from childhood to adulthood. A study by Soto & John (2012) attempted to track the developmental trends of the Big Five traits.

They found that overall agreeableness and conscientiousness increased with age. There was no significant trend for extraversion overall although gregariousness decreased and assertiveness increased.

Openness to experience and neuroticism decreased slightly from adolescence to middle adulthood. The researchers concluded that there were more significant trends in specific facets (i.e. adventurousness and depression) rather than in the Big Five traits overall.

History and Background

The Big Five model resulted from the contributions of many independent researchers. Gordon Allport and Henry Odbert first formed a list of 4,500 terms relating to personality traits in 1936 (Vinney, 2018). Their work provided the foundation for other psychologists to begin determining the basic dimensions of personality.

In the 1940s, Raymond Cattell and his colleagues used factor analysis (a statistical method) to narrow down Allport’s list to sixteen traits.

However, numerous psychologists examined Cattell’s list and found that it could be further reduced to five traits. Among these psychologists were Donald Fiske, Norman, Smith, Goldberg, and McCrae & Costa (Cherry, 2019).

In particular, Lewis Goldberg advocated heavily for five primary factors of personality (Ackerman, 2017). His work was expanded upon by McCrae & Costa, who confirmed the model’s validity and provided the model used today: conscientiousness, agreeableness, neuroticism, openness to experience, and extraversion.

The model became known as the “Big Five” and has seen received much attention. It has been researched across many populations and cultures and continues to be the most widely accepted theory of personality today.

Each of the Big Five personality traits represents extremely broad categories which cover many personality-related terms. Each trait encompasses a multitude of other facets.

For example, the trait of Extraversion is a category that contains labels such as Gregariousness (sociable), Assertiveness (forceful), Activity (energetic), Excitement-seeking (adventurous), Positive emotions (enthusiastic), and Warmth (outgoing) (John & Srivastava, 1999).

Therefore, the Big Five, while not completely exhaustive, cover virtually all personality-related terms.

Another important aspect of the Big Five Model is its approach to measuring personality. It focuses on conceptualizing traits as a spectrum rather than black-and-white categories (see Figure 1). It recognizes that most individuals are not on the polar ends of the spectrum but rather somewhere in between.

Frequently Asked Questions

Is 5 really the magic number.

A common criticism of the Big Five is that each trait is too broad. Although the Big Five is useful in terms of providing a rough overview of personality, more specific traits are required to be of use for predicting outcomes (John & Srivastava, 1999).

There is also an argument from psychologists that more than five traits are required to encompass the entirety of personality.

A new model, HEXACO, was developed by Kibeom Lee and Michael Ashton, and expands upon the Big Five Model. HEXACO retains the original traits from the Big Five Model but contains one additional trait: Honesty-Humility, which they describe as the extent to which one places others’ interests above their own.

What are the differences between the Big Five and the Myers-Briggs Type Indicator?

The Big Five personality traits and the Myers-Briggs Type Indicator (MBTI) are both popular models used to understand personality. However, they differ in several ways.

The Big Five traits represent five broad dimensions of personality. Each trait is measured along a continuum, and individuals can fall anywhere along that spectrum.

In contrast, the MBTI categorizes individuals into one of 16 personality types based on their preferences for four dichotomies: extraversion/introversion, sensing/intuition, thinking/feeling, and judging/perceiving. This model assumes that people are either one type or another rather than being on a continuum.

Overall, while both models aim to describe and categorize personality, the Big Five is thought to have more empirical research and more scientific support, while the MBTI is more of a theory and often lacks strong empirical evidence.

Is it possible to improve certain Big Five traits through therapy or other interventions?

It can be possible to improve certain Big Five traits through therapy or other interventions.

For example, individuals who score low in conscientiousness may benefit from therapy that focuses on developing planning, organizational, and time-management skills. Those with high neuroticism may benefit from cognitive-behavioral therapy, which helps individuals manage negative thoughts and emotions.

Additionally, therapy such as mindfulness-based interventions may increase scores in traits such as openness and agreeableness. However, the extent to which these interventions can change personality traits long-term is still a topic of debate among psychologists.

Is it possible to have a high score in more than one Big Five trait?

Yes, it is possible to have a high score in more than one Big Five trait. Each trait is independent of the others, meaning that an individual can score high on openness, extraversion, and conscientiousness, for example, all at the same time.

Similarly, an individual can also score low on one trait and high on another. The Big Five traits are measured along a continuum, so individuals can fall anywhere along that spectrum for each trait.

Therefore, it is common for individuals to have a unique combination of high and low scores across the Big Five personality traits.

Ackerman, C. (2017, June 23). Big Five Personality Traits: The OCEAN Model Explained . PositivePsychology.com. https://positivepsychology.com/big-five-personality-theory

Cherry, K. (2019, October 14). What Are the Big 5 Personality Traits? Verywell Mind . Retrieved 12 June 2020, from https://www.verywellmind.com/the-big-five-personality-dimensions-2795422

Costa, P., Terracciano, A., & McCrae, R. (2001). Gender Differences in Personality Traits Across Cultures: Robust and Surprising Findings . Journal of Personality and Social Psychology, 81 (2), 322-331. https://doi.org/10.1037/0022-3514.81.2.322

Fiske, D. W. (1949). Consistency of the factorial structures of personality ratings from different sources. The Journal of Abnormal and Social Psychology, 44 (3), 329-344. https://doi.org/10.1037/h0057198

Grohol, J. M. (2019, May 30). The Big Five Personality Traits . PsychCentral. Retrieved 10 June 2020, from https://psychcentral.com/lib/the-big-five-personality-traits

Gurven, M., von Rueden, C., Massenkoff, M., Kaplan, H., & Lero Vie, M. (2013). How universal is the Big Five? Testing the five-factor model of personality variation among forager-farmers in the Bolivian Amazon . Journal of personality and social psychology, 104 (2), 354–370. https://doi.org/10.1037/a0030841

Jang, K. L., Livesley, W. J., & Vemon, P. A. (1996). Heritability of the Big Five Personality Dimensions and Their Facets: A Twin Study . Journal of Personality, 64 (3), 577–592. https://doi.org/10.1111/j.1467-6494.1996.tb00522.x

Jang, K. L., McCrae, R. R., Angleitner, A., Riemann, R., & Livesley, W. J. (1998). Heritability of facet-level traits in a cross-cultural twin sample: Support for a hierarchical model of personality. Journal of Personality and Social Psychology, 74 (6), 1556–1565.

John, O. P., & Srivastava, S. (1999). The Big-Five trait taxonomy: History, measurement, and theoretical perspectives. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (Vol. 2, pp. 102–138). New York: Guilford Press.

Lahey B. B. (2009). Public health significance of neuroticism. The American psychologist, 64 (4), 241–256. https://doi.org/10.1037/a0015309

Loehlin, J. C., McCrae, R. R., Costa, P. T., & John, O. P. (1998). Heritabilities of Common and Measure-Specific Components of the Big Five Personality Factors . Journal of Research in Personality, 32 (4), 431–453. https://doi.org/10.1006/jrpe.1998.2225

Manolika, M. (2023). The Big Five and beyond: Which personality traits do predict movie and reading preferences?  Psychology of Popular Media, 12 (2), 197–206

McCrae, R. R. (2002). Cross-Cultural Research on the Five-Factor Model of Personality . Online Readings in Psychology and Culture, 4 (4). https://doi.org/10.9707/2307-0919.1038

Myers, David G. (2011). Psychology (10th ed.) . Worth Publishers.

Neal, A., Yeo, G., Koy, A., & Xiao, T. (2012). Predicting the form and direction of work role performance from the Big 5 model of personality traits . Journal of Organizational Behavior, 33 (2), 175–192. https://doi.org/10.1002/job.742

Riemann, R., Angleitner, A., & Strelau, J. (1997). Genetic and Environmental Influences on Personality: A Study of Twins Reared Together Using the Self‐ and Peer Report NEO‐FFI Scales . Journal of Personality, 65 (3), 449-475.

Roehrick, K. C., Vaid, S. S., & Harari, G. M. (2023). Situating smartphones in daily life: Big Five traits and contexts associated with young adults’ smartphone use. Journal of Personality and Social Psychology, 125 (5), 1096–1118.

Soto, C. J., & John, O. P. (2012). Development of Big Five Domains and Facets in Adulthood: Mean-Level Age Trends and Broadly Versus Narrowly Acting Mechanism . Journal of Personality, 80 (4), 881–914. https://doi.org/10.1111/j.1467-6494.2011.00752.x

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Yamagata, S., Suzuki, A., Ando, J., Ono, Y., Kijima, N., Yoshimura, K., . . . Jang, K. (2006). Is the Genetic Structure of Human Personality Universal? A Cross-Cultural Twin Study From North America, Europe, and Asia. Journal of Personality and Social Psychology, 90 (6), 987-998. https://doi.org/10.1037/0022-3514.90.6.987

Keep Learning

• Minnesota Multiphasic Personality Inventory (MMPI)
• McCrae, R. R., & Terracciano, A. (2005). Universal features of personality traits from the observer’s perspective: data from 50 cultures. Journal of Personality and Social Psychology, 88 (3), 547.
• Cobb-Clark, DA & Schurer, S. The stability of big-five personality traits. Economics Letters. 2012; 115 (2): 11–15.
• Marsh, H. W., Nagengast, B., & Morin, A. J. (2013). Measurement invariance of big-five factors over the life span: ESEM tests of gender, age, plasticity, maturity, and la dolce vita effects. Developmental psychology, 49 (6), 1194.
• Power RA, Pluess M. Heritability estimates of the Big Five personality traits based on common genetic variants. Transl Psychiatry. 2015;5 :e604.
• Personality Theories Book Chapter
• The Cambridge Handbook of Personality Psychology

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What are the big 5 personality traits inside psychology's core personality system.

An individual's "personality" refers to their patterns of behaviors, thoughts, and feelings. To help capture the seemingly infinite number of personalities that appear across humankind, researchers have developed models for measuring their most common manifestations.

Many psychologists consider the so-called Big Five personality traits the most reputable. This model states that personality comes down to five core factors: openness, conscientiousness, extroversion, agreeableness, and neuroticism.

We asked psychology experts to help us unpack the Big 5 personality traits and the ways in which mental health professionals use them.

What are the Big Five personality traits?

The Big Five personality traits are openness, conscientiousness, extroversion, agreeableness, and neuroticism. These five fundamental traits attempt to summarize the human personality on a comparative scale. 

"Personality is defined as someone's usual patterns of behaviors, feelings, and thoughts. While these usual patterns are complex, there are some personality traits that organize our understanding of someone's personality," explains licensed clinical psychologist Ernesto Lira de la Rosa, Ph.D. , of the Hope for Depression Research Foundation . That's where personality frameworks like the Big Five, also known as the Five Factor model , come in.

According to the Big Five theory of personality, all human personalities are composed of these five core personality dimensions, and any individual's personality boils down to where they fall on each of these five scales. Although not without its criticisms, decades of research have validated this theory.

The Big Five personality framework was first developed in 1949 by personality psychologist D.W. Fiske. Later, other scientists, including Warren T. Norman, Robert McCrae & Paul Costa, Gene M. Smith, and Lewis R. Goldberg, further developed Fiske's theories and research.

As with any personality test, there is controversy over the model itself and how it is best applied, says psychotherapist Lee Phillips, Ed.D., LCSW, CST . That said, today the Big Five personality traits are widely accepted as an accurate way of understanding human personality among most psychologists in the United States and in the broader Western world, supported by ample research.

And as one 2020 paper in The Wiley Encyclopedia of Personality and Individual Differences notes, "The five factors have provided a framework for understanding psychopathology. Neuroscience has identified neural correlates of the five factors, and cross-cultural research has underscored how people across the globe are both similar and different."

Below is a breakdown of each of the Big Five personality traits: 

Openness 

Openness to experience represents intellectual curiosity, creative imagination, and valuable insights. This trait includes thinking outside the box and being willing to learn new things. 

According to Lira de la Rosa, "People who score high on openness tend to enjoy trying new things, playing with complex ideas, and considering alternative perspectives. Those who score lower on openness may dislike change, trying new things, and dislike abstract concepts."

Conscientiousness 

Conscientiousness indicates organization, productivity, responsibility, and impulse control. Highly conscientious people have goal-oriented behaviors. Phillips says, "Conscientiousness measures the organizational skills of the individual. For example, it looks at how careful, deliberate, and self-disciplined they are. Conscientiousness looks at the foretelling of employee productivity."

According to Lira de la Rosa, those who score high on conscientiousness may spend more time preparing for things. They pay close attention to detail and enjoy a set schedule. "However, those who score low on conscientiousness may dislike structure and schedules and may procrastinate on important tasks," he says.

Extroversion 

Extroversion looks at how sociable and outgoing a person is, and where they feel most energized. High scores indicate a person energized by the company of others and excited by being the center of attention. Low scores indicate a more reserved person who enjoys solitude.

Introverts don't necessarily dislike social gatherings; however, they may get fatigued by them and require time alone to regain their energy.

Agreeableness

Agreeableness is aligned with attributes like kindness, affection, and trust. People with high scores are interested in others. They are emphatic and enjoy contributing to others' happiness.

"Those who score high may feel empathy and concern for others, enjoy helping others and contributing to their happiness. They love to assist those who are in need. In contrast, those who score low on agreeableness may take little interest in others, insult or belittle others, and have little interest in other people's problems," says Lira de la Rosa.

Neuroticism 

Neuroticism indicates emotional instability. It often refers to sadness and moodiness . 

Phillips explains that "high scores indicate the person is anxious, irritable, they are capable of anger outbursts, and they can have dramatic shifts in their mood. Low scores indicate the person does not worry as much, they are calm and emotionally stable, and they rarely feel sad or depressed."

Why are the Big Five personality traits so important?

The Big Five personality traits model helps people identify on a spectrum, recognizing that all people exhibit some of these traits at some point in their lives.

"These traits are important because they are useful in understanding our social interactions with others. They are also helpful in increasing our self-awareness and how our personality traits may impact how others perceive or experience us," Lira de la Rosa tells mbg.

The Big Five model has evolved with time, research, and technology. These days, it's regularly applied in social, academic, and professional contexts. 

The Big Five personality traits are foundational to personality tests that have become popular in dating, family, and work. Drawing from the same scientific research that generated the Big Five, the Myers-Briggs (MBTI) , Likability Test , and the Difficult Person Test are related personality assessments meant to understand how an individual's traits manifest in relationships with others. Tools and tests like these are often used to build relationships, romantic or professional.

In the field of organizational behavior, tests based on the Big Five personality traits are often used in employee assessment tests, offering rubrics to understand employee character and to guide teams composed of diverse individuals.

Psychology and research.

The Big Five model of personality has been studied by psychologists over the course of nearly a century, starting with D.W. Fiske's research in 1949.

Gordon Allport, an American psychologist sometimes described as a founder of the field of personality psychology, published in the 1920s about what he termed "cardinal traits," core characteristics thought to define a person's personality. His research developed a lexicon of over 4,500 vocabulary words to describe personality traits. Then in 1949, through a study of clinical trainees, Fiske attempted to find consistent structural factors of personalities 1 . He identified a core group of four similar factors, with three distinct levels of behavioral ratings.

As the field of psychology developed, personality research became more refined and competing, but related frameworks developed—some with as many as 16 factors and others with as few as four. But, somehow the number five kept coming up. Robert Costa and Paul McCrae developed the so-called Five Factor Model in 1987, and Lewis Goldberg developed the " Big Five Model " in 1993, both using the same core personality factors: openness, conscientiousness, extroversion, agreeableness, and neuroticism. Since then, these Big Five personality traits have been studied and validated time and time again by many researchers over decades.

Some of the most interesting recent research suggests that biological and environmental factors play a role in personality development. For example, a 2015 study of the personalities of twins 2 suggests that both nature and nurture affect the development of each of the Big Five personality traits. In that study, 127 pairs of fraternal twins and 123 pairs of identical twins were put to the Big Five test. The findings showed the heritability of openness and neuroticism, and subsequent research has been done to further explore the genetic basis for some of the other traits. 

There is also some valid criticism of the Big Five personality traits. "In particular, most of the research on personality is done with people from western, educated, industrialized, rich, and democratic countries," explains Lira de la Rosa. "As such, the Big Five personality traits may not capture personality traits across cultures." He says that research shows that some of the Big Five personality traits are not observed as often in some other cultures.

Phillips also adds that critics ask, "How can one test determine a person's personality?" After all, personalities may shift over time. And it's the mix of traits—not each one individually—that defines our personalities. So, tests like these—when not taken under the supervision of a trained professional—can sometimes be used to justify ill-conceived or overly simplified conclusions about people's characters.

How to use the Big Five personality system:

Get to know yourself better..

"Having awareness of ourselves can be critical to our sense of self and relationship with others," Lira de la Rosa says. The average person can use this framework of personality traits to better understand themselves and to recognize how some of these traits impact their day-to-day lives. 

Leverage your strengths.

Using newfound knowledge of your personality, you can craft relationships and opportunities around your strengths. People with a low openness score, for example, might target jobs in an office where they can become subject matter experts rather than roles that entail rotating into various areas of the company. In this way, their strengths and personality disposition are aligned with success in that context. Use what you know about your general tendencies to set yourself up for success at work and in your personal relationships.

Date thoughtfully.

Speaking of personal relationships, your Big Five personality traits could be a good conversation starter on a date—and even a good way to assess compatibility. Phillips says a person serious about dating "can take the test, and post the results on a dating app," adding, "By scoring high and low on these personality traits, a person can see if they match with another person's personality type." 

Help others understand you better.

Once you know yourself better, it becomes easier to explain your boundaries and reactions to co-workers, roommates, and romantic partners. Take the test together or simply share your own results. Sharing vulnerabilities and tendencies will help the people you spend the most time with better understand you and get ahead of any misunderstandings.

Why is the Big Five personality test important?

The Big Five model of personality determines where a person's personality traits stand on a spectrum in comparison to others, as well as how other people may perceive them. Self-awareness tools based on the model can help you adjust behaviors to better suit group contexts and wider society.

Are the Big Five personality traits genetic?

There are some indications that these traits could be genetically linked. According to one 2015 study, there is evidence of the heritability of at least two of the Big Five traits: openness and neuroticism.  

Can you change your Big Five personality traits?

Multiple studies and psychologists say these traits are not fixed and can be intentionally changed with effort, intentionality, and support from mental health care professionals. 

The takeaway.

The Big Five personality model is widely reputed; however, self-assessment tests always have an element of bias. Also, it is important not to take the results of any personality test as any kind of definitive diagnosis. These tests are simply meant to help you learn about yourself and identify possible areas for personal growth.

"The average person can use personality traits to better understand themselves and how some of these traits impact their day-to-day functioning," explains Lira de la Rosa. "It is important to note that these traits will not mean the same for each person, and it is the combination of these traits that informs our unique personalities."

• https://psycnet.apa.org/doiLanding?doi=10.1037%2Fh0057198
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5068715/

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What Are the Big 5 Personality Traits?

Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Verywell / Catherine Song

• Universality
• Influential Factors

Frequently Asked Questions

Many contemporary personality psychologists believe that there are five basic dimensions of personality, often referred to as the "Big 5" personality traits. The Big 5 personality traits are extraversion (also often spelled extroversion), agreeableness , openness , conscientiousness , and neuroticism .

Extraversion is sociability, agreeableness is kindness, openness is creativity and intrigue, conscientiousness is thoughtfulness, and neuroticism often involves sadness or emotional instability.

Understanding what each personality trait is and what it means to score high or low in that trait can give you insight into your own personality —without taking a personality traits test . It can also help you better understand others, based on where they fall on the continuum for each of the personality traits listed.

An Easy Way to Remember the Big 5

Some use the acronym OCEAN (openness, conscientiousness, extraversion, agreeableness, and neuroticism) to remember the Big 5 personality traits. CANOE (for conscientiousness, agreeableness, neuroticism, openness, and extraversion) is another option.

History of the Big 5 Personality Theory

Trait theories of personality have long attempted to pin down exactly how many traits exist. Earlier theories have suggested various numbers. For instance, Gordon Allport's list contained 4,000 personality traits, Raymond Cattell had 16 personality factors, and Hans Eysenck offered a three-factor theory.

Many researchers felt that Cattell's theory was too complicated and Eysenck's was too limited in scope. As a result, the Big 5 personality traits emerged and are used to describe the broad traits that serve as building blocks of personality .

Several researchers support the belief that there are five core personality traits. Evidence of this theory has been growing for many years in psychology, beginning with the research of D. W. Fiske (1949), and later expanded upon by others, including Norman (1967), Smith (1967), Goldberg (1981), and McCrae & Costa (1987).

The Big 5 Personality Traits

It is important to note that each of the five primary personality traits represents a range between two extremes. For example, extraversion represents a continuum between extreme extraversion and extreme introversion. In the real world, most people lie somewhere in between.

While there is a significant body of literature supporting these primary personality traits, researchers don't always agree on the exact labels for each dimension. That said, these five traits are usually described as follows.

Openness (also referred to as openness to experience) emphasizes imagination and insight the most out of all five personality traits. People who are high in openness tend to have a broad range of interests. They are curious about the world and other people and are eager to learn new things and enjoy new experiences.

People who are high in this personality trait also tend to be more adventurous and  creative . Conversely, people low in this personality trait are often much more traditional and may struggle with abstract thinking.

Very creative

Open to trying new things

Focused on tackling new challenges

Happy to think about abstract concepts

Dislikes change

Does not enjoy new things

Resists new ideas

Not very imaginative

Dislikes abstract or theoretical concepts

Conscientiousness

Among each of the personality traits, conscientiousness is one defined by high levels of thoughtfulness, good impulse control, and goal-directed behaviors. Highly conscientious people tend to be organized and mindful of details. They plan ahead, think about how their behavior affects others, and are mindful of deadlines.

Someone scoring lower in this primary personality trait is less structured and less organized. They may procrastinate to get things done, sometimes missing deadlines completely.

Spends time preparing

Finishes important tasks right away

Pays attention to detail

Enjoys having a set schedule

Dislikes structure and schedules

Makes messes and doesn't take care of things

Fails to return things or put them back where they belong

Procrastinates  important tasks

Fails to complete necessary or assigned tasks

Extraversion

Extraversion (or extroversion) is a personality trait characterized by excitability, sociability, talkativeness, assertiveness, and high amounts of emotional expressiveness. People high in extraversion are outgoing and tend to gain energy in social situations. Being around others helps them feel energized and excited.

People who are low in this personality trait or introverted tend to be more reserved. They have less energy to expend in social settings and social events can feel draining. Introverts often require a period of solitude and quiet in order to "recharge."

Enjoys being the center of attention

Likes to start conversations

Enjoys meeting new people

Has a wide social circle of friends and acquaintances

Finds it easy to make new friends

Feels energized when around other people

Say things before thinking about them

Prefers solitude

Feels exhausted when having to socialize a lot

Finds it difficult to start conversations

Dislikes making small talk

Carefully thinks things through before speaking

Dislikes being the center of attention

Agreeableness

This personality trait includes attributes such as trust,  altruism , kindness, affection, and other  prosocial behaviors . People who are high in agreeableness tend to be more cooperative while those low in this personality trait tend to be more competitive and sometimes even manipulative.

Has a great deal of interest in other people

Cares about others

Feels empathy and concern for other people

Enjoys helping and contributing to the happiness of other people

Assists others who are in need of help

Takes little interest in others

Doesn't care about how other people feel

Has little interest in other people's problems

Insults and belittles others

Manipulates others to get what they want

Neuroticism

Neuroticism is a personality trait characterized by sadness, moodiness, and emotional instability. Individuals who are high in neuroticism tend to experience mood swings , anxiety, irritability, and sadness. Those low in this personality trait tend to be more stable and emotionally resilient .

Experiences a lot of stress

Worries about many different things

Gets upset easily

Experiences dramatic shifts in mood

Feels anxious

Struggles to bounce back after stressful events

Emotionally stable

Deals well with stress

Rarely feels sad or depressed

Doesn't worry much

Is very relaxed

How to Use the Big 5 Personality Traits

Where you fall on the continuum for each of these five primary traits can be used to help identify whether you are more or less likely to have other more secondary personality traits. These other traits are often split into two categories: positive personality traits and negative personality traits.

Try our fast and free big 5 personality test to find out your most dominant traits:

Positive Personality Traits

Positive personality traits are traits that can be beneficial to have. These traits may help you be a better person or make it easier to cope with challenges you may face in life. Personality traits that are considered positive include:

• Considerate
• Cooperative
• Well-rounded

Negative Personality Traits

Negative personality traits are those that may be more harmful than helpful. These are traits that may hold you back in your life or hurt your relationships with others. (They're also good traits to focus on for personal growth.) Personality traits that fall in the negative category include:

• Egotistical

For example, if you score high in openness, you are more likely to have the positive personality trait of creativity. If you score low in openness, you may be more likely to have the negative personality trait of being unimaginative.

Universality of Primary Personality Traits

McCrae and his colleagues found that the Big 5 personality traits are remarkably universal. One study that looked at people from more than 50 different cultures found that the five dimensions could be accurately used to describe personality.

Based on this research, many psychologists now believe that the five personality dimensions are not only universal but that they also have biological origins. Psychologist David Buss has proposed an evolutionary explanation for these five core personality traits, suggesting that they represent the most important qualities that shape our social landscape.

Factors Influencing Personality Traits

Research suggests that both biological and environmental influences play a role in shaping our personalities. Twin studies suggest that both nature and nurture play a role in the development of each of the five personality traits.

One study of the genetic and environmental underpinnings of the five traits looked at 123 pairs of identical twins and 127 pairs of fraternal twins. The findings suggested that the heritability of each personality trait was 53% for extraversion, 41% for agreeableness, 44% for conscientiousness, 41% for neuroticism, and 61% for openness. 

Longitudinal studies also suggest that these big five personality traits tend to be relatively stable over the course of adulthood. One four-year study of working-age adults found that personality changed little as a result of adverse life events .

Studies show that maturation may have an impact on the five personality traits. As people age, they tend to become less extraverted, less neurotic, and less open to an experience. Agreeableness and conscientiousness, on the other hand, tend to increase as people grow older.

A Word From Verywell

Always remember that behavior involves an interaction between a person's underlying personality and situational variables. The situation that someone finds themselves in plays a role in how they might react . However, in most cases, people offer responses that are consistent with their underlying personality traits.

These dimensions represent broad areas of personality. But personality is also complex and varied. So, a person may display behaviors across several of these personality traits.

The big 5 personality theory is widely accepted today because this model presents a blueprint for understanding the main dimensions of personality. Experts have found that these traits are universal and provide an accurate portrait of human personality.

The big 5 personality model is not a typology system, so there are no specific "types" identified. Instead, these dimensions represent qualities that all people possess in varying amounts. One study found that most people do tend to fall into one of four main types based on the Big 5 traits:  

• Average (the most common type, characterized by high levels of extroversion and neuroticism and low levels of openness)
• Self-centered (high in extroversion and low in conscientiousness, openness, and agreeableness)
• Reserved (low on extroversion, neuroticism, and openness, and high on conscientiousness and agreeableness)
• Role models (high on every big 5 trait other than neuroticism)

Power RA, Pluess M. Heritability estimates of the Big Five personality traits based on common genetic variants . Translation Psychiatry . 2015;5:e604. doi:10.1038/tp.2015.96

Jang KL, Livesley WJ, Vernon PA. Heritability of the big five personality dimensions and their facets: a twin study . J Pers . 1996;64(3):577-91. doi:10.1111/j.1467-6494.1996.tb00522.x

Gerlach M, Farb B, Revelle W, Nunes Amaral LA. A robust data-driven approach identifies four personality types across four large data sets . Nat Hum Behav . 2018;2(10):735-742.

 doi:10.1038/s41562-018-0419-z

Cobb-Clark DA, Schurer S. The stability of big-five personality traits . Econ Letters . 2012;115(2):11–15. doi:10.1016/j.econlet.2011.11.015

Lang KL, Livesley WJ, Vemon PA. Heritability of the big five personality dimensions and their facets: A twin study . J Personal . 1996;64(3):577–591. doi:10.1111/j.1467-6494.1996.tb00522.x

Marsh HW, Nagengast B, Morin AJS. Measurement invariance of big-five factors over the lifespan: ESEM tests of gender, age, plasticity, maturity, and la dolce vita effects . Develop Psychol . 2013;49(6):1194-1218. doi:10.1037/a0026913

McCrae RR, Terracciano A, Personality Profiles of Cultures Project. Universal features of personality traits from the observer's perspective: Data from 50 different cultures . J Personal Soc Psychol. 2005;88:547-561. doi:10.1037/0022-3514.88.3.547

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Learn More Psychology

• Personality

Five-Factor Model of Personality

How the 'super traits' of the five factor model explain differences in personality and the way people behave..

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In psychology, five broad dimensions (the ‘Big Five’) are commonly used in the research and study of personality . Since the late 20th Century, these factors have been used to measure, and develop a better understanding of, individual differences in personality.

Personality Theories

• Personality Types (Friedman & Rosenman)
• Theories of Personality
• Eysenck's PEN Model of Personality

These five factors include:

O penness to experience

C onscientiousness

E xtraversion

A greeableness

N euroticism

The five factors may be easily remembered using the acronym ‘OCEAN’. They are measured on continua, whereby an individual may be highly extraverted, low in extraversion (introverted) or somewhere between these two extremes.

Early research into personality followed trait theory - the idea that a person’s temperament and behavior can be understood in terms of individual traits (e.g. self-confidence , friendliness or melancholy ).

Trait theory takes a lexical approach to personality, which assumes that traits can be described using single adjectives or descriptive phrases. If enough people regularly exhibit a form of behavior and no term exists in a given language to describe it, then according to the lexical hypothesis, a term will be created so that the trait may be considered and discussed with others.

In 1936, psychologists Gordon Allport and Henry Odbert extracted approximately 4,500 terms from Webster’s New International Dictionary which described types of behavior or personality traits. Many of these terms could be grouped under superordinate factors, and so later work focussed on the production of more concise trait inventories, which would be more practical the field of personality research.

In the 1940s, Raymond Cattell developed a 16-item inventory of personality traits and created the Sixteen Personality Factor Questionnaire (16PF) instrument to measure these traits.

Robert McCrae and Paul Costa later developed the Five-Factor Model , or FFM, which describes personality in terms of five broad factors. Psychologist Lewis Goldberg referred to these as the ‘Big Five’ factors of personality, and developed the International Personality Item Pool (IPIP) - an inventory of descriptive statements relating to each trait. Within each factor, a set of individual traits relate to more specific aspects of personality.

The five factors may be assessed using a number of measures, including self-report questionnaires.

A subject is asked to read a number of descriptions or adjectives and to rate the accuracy with which they describe their own personality on a Likert scale (e.g. 1 - Strongly Disagree to 2 - Strongly Agree).

Whilst self-report measures provide an insight into a person’s personality that behavioral observation alone cannot provide, they are also vulnerable to manipulation by a subject, who may provide more desirable answers to questions (known as social desirability bias ).

Five Factors at a Glance

Openness to experience.

The openness to experience dimension of personality is characterised by a willingness to try new activities. People with higher levels of openness are amenable to unconventional ideas and beliefs , including those which challenge their existing assumptions.

They enjoy artistic and cultural experiences , visiting art galleries, museums, theatres, listening to music and travelling to new destinations. They are more open to unfamiliar cultures and customs.

People with low levels of openness - those who are closed to experience - are wary of uncertainty and the unknown. They are more suspicious of beliefs and ideas which challenge their status quo .

They feel uncomfortable in unfamiliar situations and prefer familiar environments. Less open individuals value the safety of predictability , and like to adhere to well-known traditions and routines .

Openness to experience is often associated with intelligence when measuring personality factors.

Individuals who score highly on verbal/crystallized intelligence measures have been found to also report being more open to experience ( Schretlen et al, 2010 ).

One explanation is that people who are more open place themselves in environments where they are more likely to acquire new knowledge (e.g. during a visit to a museum) than those who remain in the same, familiar surroundings.

Whilst openness levels vary widely between individuals, a person’s own openness to experience can also change. For instance, openness to experience has been found to change with age. In a U.S. survey analysis, Costa et al (1986) reported that participants’ openness to experience gradually decreased as they grew older .

Learn more about Openness to Experience

Take the Openness to Experience Quiz

Conscientiousness

People who are conscientious are more aware of their actions and the consequences of their behavior than people who are unconscientious. They feel a sense of responsibility towards other and are generally careful to carry out the duties assigned to them.

Conscientious individuals like to keep a tidy environment and are well-organized. They are keen to maintain good timekeeping.

People with high conscientious levels also exhibit more goal-oriented behavior . They set ambitious goals and are motivated to achieve them. Undeterred by hard work, they are keen to driven to succeed in every aspect of their lives, including academic achievements and in furthering their careers.

Low levels of conscientiousness are reflected in less motivated behavior. Unconscientious individuals are less concerned by tidiness and punctuality. This may result in them arriving late to appointments and meetings, and being more relaxed in setting life goals.

Unconscientious people tend to engage in more impulsive behavior. They will act on a last-minute whim rather than considering the consequences of their choices .

Research suggests that both environmental factors and heritability may influence in conscientiousness.

One survey found that participants whose parents had displayed affectionate behavior towards them as children were likely to report higher levels of conscientiousness in adulthood ( McCrae and Costa, 1988 ).

However, the findings of a subsequent twin study suggest that conscientiousness may be in part influenced by the genes inherited from parents ( Jang et al, 1996 ).

Learn more about Conscientiousness

Take the Conscientiousness Quiz

Extraversion

Extraversion is characterised by outgoing , socially confident behavior. Extraverts are sociable , talkative and often forward in social situations. They enjoy being the center of a group and will often seek the attention of others.

Extraverts enjoy meeting new people and are happy to introduce themselves to strangers, thriving in company of others.

This personality trait is measured on a introversion-extraversion continuum. Individuals who fit in the middle of the two traits are described as ambiverts.

Introverts - people with low levels of extraversion, display contrasting behavior. They are quieter and often feel shy around other people. They may feel intimidated being in large groups such as parties, and will often try to avoid demanding social gatherings.

Introverts enjoy being a part of smaller social groups, preferably with familiar people.

Such behavior results in introverts tending to enjoy smaller social networks, but instead they maintain a close group of trusted friends.

German-born psychologist Hans Eysenck felt that extraversion, along with neuroticism, was a key personality factor, and included it in the PEN model of personality ( Eysenck and Eysenck, 1976 ).

Eysenck believed that extraverts experienced lower levels of cortical arousal than the general population.

As a result, they seek external stimulation in the form of socially engaging behavior. Cortical arousal is higher in introverts, according to Eysenck, resulting in them not requiring external stimuli to the same extent as extraverts ( Eysenck, 1979 ).

Swiss psychoanalyst Carl Jung explained extraversion in terms of psychic energy , which each individual directs differently. Jung wrote that extraverts direct such energy outwards, towards other people, whilst introverts concentrate their psychic energy on solitary activities such as thoughtful contemplation ( Jung, 1921 ).

Learn more about Extraversion

Take the Extraversion-Introversion Quiz

Agreeableness

Individuals who score highly on agreeableness measures are friendly and co-operative . Often considered more likeable by their peers and colleagues, agreeable people are trusting of others and are more altruistic , willing to help others during times of need.

Their ability to work with others means that they often work well as members of a team.

Agreeable people dislike being involved in arguments, conflict with others and other forms of confrontation. They seek to pacify and appease others, acting as the mediating ‘peace-maker’ of their group.

Individuals who are disagreeable score lower on this dimension of personality. They are less concerned with pleasing other people and making friends. Disagreeable individuals are more suspicious of other people’s intentions and are less charitable.

Instead, they are motivated to act in accordance with their self-interest , showing less regard for the needs of others. As a result, they are perceived by others as being more selfish than agreeable personalities.

Whilst disagreeable individuals find it easier to promote their own interests, those who are more agreeable tend to enjoy better relationships with others. From an early age, this can be beneficial: Jensen-Campbell et al (2002) found that children with higher levels of agreeableness were less likely to be subjected to bullying at school.

As with some of the other ‘Big Five’ personality factors, our agreeableness levels are fluid throughout our lives, tending to increase as we grow older ( Donnelan et al, 2008 ).

Learn more about Agreeableness

Take the Agreeableness Quiz

Neuroticism

This personality dimension is measured on a continuum ranging from emotional stability to emotional instability , or neuroticism . People with high neuroticism scores are often persistent worriers. They are more fearful and often feel anxious, over-thinking their problems and exaggerating their significance. Rather than seeing the positive in a situation, they may dwell on its negative aspects .

Neuroticism can result in a person coping less successfully with common stressors in their day-to-day lives. Instead, they will often become frustrated with others and may feel angry if events do not occur as they wish.

People with low neuroticism scores are less preoccupied by these negative concerns. They are able to remain more calm in response to stressful situations, and view problems in proportion to their importance. As a result, they tend to worry about such problems to a lesser extent.

A person’s neuroticism can have repercussions in terms of their relationship with others. A study found that people in relationships were less happy than other couples if their partner scored highly on the personality trait ( Headey et al, 2010 ).

One explanation for neuroticism was provided by psychologist Jeffrey Alan Gray’s biopsychological theory .

Gray suggested that human behavior is motivated by two systems. The first, the behavioral activation system (BAS), is motivated by the prospect of reward . A second system, the behavioral inhibition system (BIS) is driven by the need to avoid punishment for one’s behavior. Gray believed that the latter system exercises more influence over the behavior of individuals with high levels of neuroticism ( Gray, 1970 ).

Learn more about Neuroticism

Take the Neuroticism Quiz

• Schretlen, D. J., Hulst, E. J., Pearlson, G. D. and Gordon, B. (2010). Journal of clinical and experimental neuropsychology . 32 (10). 1068-1073.
• Costa, P. T., McCrae, R. R., Zonderman, A. B., Barbano, H. E., Lebowitz, B. and Larson, D. M. (1986). Cross-Sectional Studies of Personality in a National Sample: 2. Stability in Neuroticism, Extraversion, and Openness. Psychology and Aging . 1 (2). 144-149.
• McCrae, R. R. and Costa, P. T. (1988). Recalled Parent-Child Relations and Adult Personality. Journal of Personality . 56 (2). 417-434.
• Jang, K. L., Livesley, W. J. and Vernon, P. A. (1996). Heritability of the Big Five Personality Dimensions and Their Facets: A Twin Study. Journal of Personality . 64 (3).
• Eysenck, H. J. and Eysenck, S. B. G. (1976). Eysenck personality questionnaire . Educational and industrial testing service.
• Eysenck, H. J. (1979). Crime and personality. Medico-Legal Journal . 47(1). 18-32.
• Jung, C. G. and Godwin Baynes, H. (1921). Psychologische Typen . Zurich: Rascher.
• Donnellan, M. B. and Lucas, R. E. (2008). Age Differences in the Big Five Across the Life Span: Evidence from Two National Samples. Psychology and Aging . 23 (3). 558-566.
• Jensen-Campbell, L. A., Adams, R., Perry, D. G., Workman, K. A., Furdella, J. Q. and Egan, S. K. (2002). Agreeableness, Extraversion, and Peer Relations in Early Adolescence: Winning Friends and Deflecting Aggression. Journal of Research in Personality . 36 3 . 224-251.
• Headey, B., Muffels, R. and Wagner, G. G. (2010). Long-running German panel survey shows that personal and economic choices, not just genes, matter for happiness. Proceedings of the National Academy of Sciences of the United States of America . 107 (42). 17922-17926.
• Gray, J. A. (1970) The psychophysiological basis of introversion-extraversion. Behaviour Research and Therapy . 8 (3). 249-266.

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September 18, 2018

Big Data Gives the “Big 5” Personality Traits a Makeover

An analysis of 1.5 million people tries to more accurately categorize people’s character traits

By Dana G. Smith

Getty Images

From the ancient Greeks to Shakespeare to Hollywood, humans have attempted to understand their fellow man through labeling and categorization. There was Hippocrates’s blood, phlegm, yellow and black bile; the classic dramatic archetypes of hero, ingenue, jester and wise man; and, of course, Carrie, Charlotte, Samantha and Miranda from the famous HBO series

More rigorously, psychologists have worked to develop empirical tests that assess core aspects of personality. The “Big Five” traits (extroversion, neuroticism, openness, conscientiousness and agreeableness) emerged in the 1940s through studies of the English language for descriptive terms. Those categories were validated in the 1990s as a scientifically backed way to evaluate a person’s character.

Through a series of questions, researchers learn whether you are high, low, or in between in each one of those qualities. For example, a person could be low in extraversion, high in conscientiousness and openness, and medium in neuroticism and agreeableness. The combination of where you fall on the spectrum of the five traits provides a window into your general disposition and potentially your future behavior. Different combinations of trait scores could indicate aptitude for a particular kind of job, the strength of interpersonal relationships and even the likelihood of developing psychological or physical health issues.

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In theory, these traits are a continuum with thousands of permutations of scores that make up unique personalities. But new research published in Nature Human Behavior simplifies this classification process by identifying trait scores common to many individuals. The researchers believe these groupings reflect a set of prototypical personality types, which they’ve labeled role model, self-centered, reserved or the rather uninspiring “average.” The study is not the first attempt to create subgroups of Big Five traits, but it is the largest and most statistically rigorous effort to identify personality types. “The concept of these personality types has been very debated in the last 20 years. Many people…believed for a long time that [we] don't have enough empirical evidence [to show] that something like this really exists,” says Martin Gerlach, a postdoctoral fellow at Northwestern University and first author on the paper. “Having this much data, in total more than 1.5 million people from these newly available data sets, we could actually show that in fact there is robust evidence for at least four personality types.”

The researchers, most of them engineers, borrowed methods developed to study particle physics to analyze the responses of 1.5 million people from four separate studies measuring the Big Five. Using machine-learning algorithms, they scanned the first data set of nearly 150,000 responses looking for clusters of people who scored similarly on the five traits. The algorithms initially identified 13 clusters, which the researchers then narrowed down to the four densest pockets that encompassed a higher than average number of people. When they applied their algorithms to the other three data sets, the same four clusters emerged, confirming the status of those trait scores as distinct personality types.

Interestingly, age and gender were strongly related to several of the types. The “role model” (low in neuroticism and high in openness, agreeableness, extroversion and conscientiousness) consisted mostly of women over the age of 40 whereas young men were much more likely to be “self-centered” (high extroversion, medium neuroticism, along with low openness, agreeableness and  conscientiousness). The majority of people, though, landed into the average category, with high neuroticism and extraversion, low openness, and medium agreeableness and conscientiousness.

It may be premature to change your dating profile to announce your new type just yet, though. “To say that you are a this or a that, that’s a mistake,” says William Revelle, also at Northwestern and the lone psychologist on the study. “What we’re saying is you can group more people in these four clusters than you’d expect by chance. People are fairly continuously distributed throughout the space, there are just higher densities in parts of the space.”

Revelle likened the types to the location and population of cities. More people live in New York, Chicago, Los Angeles and Houston than anywhere else in the country, but most of the country doesn’t live in any of those cities. And although you can easily lump someone in Newark into New York, a person in Pittsburgh is harder to classify because they are equally close to New York and Chicago.

The question remains, then, if these classifications provide any real insight into a person’s thoughts and behaviors. “This is by far the most valid estimate we have of how people cluster into types,” says Richard Robins, a personality researcher at the University of California, Davis, who was not involved in the study. “But whether those clusters, the four clusters they found, reflect some true underlying reality about people is something that requires other forms of evidence.”

In theory personality typing reveals how different sets of traits work together to create an integrated whole. A specific type is also easier to communicate than a list of five different dimensions. Robins cautions, though, there is a risk of “arbitrarily drawing a circle around a particular cluster of people, but there’s no meaningful underlying neurobiological underpinning to why those people are clustered together.”

Revelle agrees. “Breaking it down into one of four types would not allow me to understand you very well,” he says. “If I want to know what you’re like, I need to know how able you are to do something, how stable you are, how interested you are in things. I need to know all of that to predict or understand what you’re going to do.”

Whereas this new research does not settle the question of the validity of personality typing, for the moment the field of psychology does have two definitive categories: those who believe in personality types and those who don’t.

Big Five Personality Traits: Here’s What You Need to Know

Categories Personality

While there have been many different theories of personality, many psychologists today believe that personality is made of five broad dimensions, a notion often referred to as the big five theory of personality or the five-factor model. The Big 5 personality traits the theory describes are:

Conscientiousness

Extroversion, agreeableness, neuroticism.

Table of Contents

The Big Five Personality Traits

We mentioned these big five traits earlier, but let’s look at them in greater depth. One important thing to remember is that each dimension represents a continuum. Some people may be at one extreme or another on a particular dimension, with most lying somewhere in the middle.

Does this suggest that personality is made up of only five traits? Not at all. Remember, each of the five factors represents a broad spectrum of traits. Extroversion, for example, encompasses such qualities as talkativeness, outgoingness, assertiveness, and friendliness.

The Big 5 traits represent broad dimensions of personality. Each dimension is a continuum that includes those who are high, low, and in between.

The body of evidence supporting the Big Five theory has grown in recent decades, although it has also been the subject of critique.

Let’s take a closer look at each of the dimensions described by the Big Five theory:

This Big Five personality trait is also referred to as openness to experience and describes a spectrum between being curious and cautious.

High Openness Traits

People who rate high in openness tend to be creative, inventive, and adventurous.

They tend to have a great deal of intellectual curiosity, prefer to avoid routine, and seek out novel experiences. This can sometimes take the form of thrill-seeking and participating in high-risk activities such as sky diving, bungee jumping, and gambling.

Other characteristics of openness include:

• Open-minded
• Abstract thinker
• Unpredictable

Low Openness Traits

Those who rate low in openness tend to be careful and consistent. They appreciate routines and are often wary or even resistant to change.

They may base decisions on carefully considered data, avoid taking excessive risks and can sometimes be close-minded when encountering information that challenges existing beliefs.

Other characteristics of low levels of openness include:

• Enjoying structure
• Being dogmatic
• Resisting new ideas
• Avoiding risk

The conscientiousness big five personality trait describes a continuum between being highly efficient and very careless.

High Conscientiousness Traits

People who are high in conscientiousness are efficient and thoughtful.

Some characteristics of those who are high in this trait include:

• High achieving
• Perfectionistic
• Self-Disciplined

Low Conscientiousness Traits

Those who are low in this trait tend to be easy-going but often thoughtless. While they are often seen as relaxed, they can sometimes be perceived as sloppy or even lazy.

Some more characteristics of people low in conscientiousness include:

• Spontaneous
• Irresponsible
• Undependable

Extroversion, sometimes spelled extraversion, describes a continuum between being outgoing and reserved . Extroverts typically gain energy from social interactions – socializing with other people helps them feel recharged and inspired.

High Extroversion Traits

Some of the common characteristics of people high in extroversion include being:

• Domineering
• Attention-seeking

Low Extroversion Traits

Those who are low in extroversion are known as introverts . They have to expend energy in social settings, so spending lots of time with others can feel draining. Because of this, they often need periods of solitude to recharge.

Other characteristics include:

The big five personality trait of agreeableness refers to the tendency to be cooperative and helpful rather than antagonistic and disagreeable. It encompasses qualities such as trust, prosocial behaviors , and kindness.

High Agreeableness Traits

Agreeable people tend to be friendly, likable, and good-natured. Being very high in agreeableness is sometimes seen as gullible, naive, or overly trusting.

Some more characteristics of those who are high in agreeableness include:

• Even-tempered
• Cooperative
• Compassionate

Low Agreeableness Traits

People who are low in agreeableness tend to be distrustful and detached. Other characteristics of low agreeableness include:

• Antagonistic
• Untrustworthy
• Uncooperative
• Ill-tempered
• Argumentative

Neuroticism centers on emotional stability.

High Neuroticism Traits

People who are high in this trait are more likely to experience unpleasant emotions such as sadness, anger, and anxiety.

More characteristics of being high in neuroticism include:

• Sensitivity
• Nervousness

Low Neuroticism Traits

Those who are low in this dimension, on the other hand, tend to be calm and even-tempered. Other characteristics associated with being low on the neuroticism dimensions include:

Other Trait Theories

There are many different theories of personality. Trait theories attempt to describe personality as composed of a number of different traits which then influence how people behave.

Just how many traits are there? Theorists have proposed a variety of numbers to capture all of the traits that make up the human experience:

• An early psychologist named Gordon Allport, the man often credited with helping to popularize psychology in America, examined dictionary terms related to personality traits and concluded that there were more than 4,000.
• Later, the psychologist Raymond Cattell utilized a statistical technique known as factor analysis to whittle that list down to just 16.
• Hans Eysenck shortened that list to a mere three broad dimensions, but later researchers revised and expanded this to include five dimensions of personality.

Rather than focusing on individual terms that describe every aspect of a trait, the Big Five theory aims to instead focus on the broader aspects of human personality.

History of the Big 5 Personality Traits

It is important to remember that each dimension represents a spectrum. Each high and low pole represents the extremes of each trait, but people typically lie somewhere between the two sides.

The big five personality traits were derived from analyzing surveys of thousands of people to determine which traits tend to occur together. Using factor analysis, researchers were able to group related traits together under broad dimensions.

The five domains identified by the big five theory are thought to encompass all know personality traits.

As you might have already realized, exceptions are possible. A person who ranks high in introversion might be quiet but not necessarily reticent. A person who is highly extroverted might be sociable but not necessarily assertive.

The Big Five personality traits describe only a portion of what personality psychologists study. Other aspects of personality such as motivations, attitudes, self-concepts , and emotions also play a role in making you who you are, but the Big Five theory does not touch upon such subjects.

What Causes of the Big Five Personality Traits?

So what factors influence the development of the Big Five personality traits? As with many questions in psychology, both nature and nurture play a role.

In one large-scale twin study , researchers found that the heritability of the openness dimensions was the highest, with 61% being attributed to genetic influences. Conscientiousness was 44% due to genetics, with extroversion, agreeableness, and neuroticism being at 53%, 41%, and 41%, respectively.

Age is another factor that can influence the five core dimensions. As people age and mature, some of these traits tend to change.

For example, people typically become less extroverted as they grow older. It is also common to become less open and neurotic while also becoming more agreeable and conscientious.

Are the Big 5 Personality Traits Universal?

The Big Five personality traits, also known as the Five Factor Model (FFM), have been extensively researched and have gained widespread acceptance in the field of psychology. These traits are considered relatively universal. They offer a comprehensive framework for describing and understanding human personality across different cultures and societies.

Research has consistently shown that these traits can be identified and measured in various cultures and are relatively stable over time. That doesn’t mean there aren’t cultural variations in the expression and emphasis of these traits. However, the core dimensions themselves appear to transcend cultural boundaries.

For instance, traits like conscientiousness, which relates to organization and dependability, are universally valued in work and social contexts, although the specific behaviors associated with this trait may differ from culture to culture.

Similarly, extraversion and introversion may manifest differently in social behaviors and norms, but the underlying personality dimension remains relevant and applicable worldwide.

The takeaway is that the Big Five traits provide a valuable and cross-culturally valid framework for understanding human personality, highlighting the universal aspects of our individual differences while recognizing the influence of culture on their expression.

Using the Big Five Theory to Understand Your Own Personality

The Big Five theory isn’t just a tool that researchers use to assess personality traits. It can also be a tool for learning more about yourself, gaining deeper self-awareness, and achieving personal growth.

Take a Big 5 Personality Test

Start by taking a reliable Big Five personality assessment. There are many free and paid tests available online. These tests will provide you with scores on each of the five traits.

Reflect on Your Scores

Once you have your scores, reflect on what they mean. Consider the descriptions and characteristics associated with each trait.

For example, if you scored high in conscientiousness, you might be organized, goal-oriented, and detail-oriented. If you scored low in neuroticism, you are likely to be emotionally stable and resilient.

Identify Strengths and Weaknesses

Use your scores to identify your strengths and weaknesses. For example, if you score low in extraversion but high in agreeableness, you might excel in roles that require empathy and cooperation, such as a counselor or mediator.

Set Personal Goals

Use your understanding of your personality traits to set personal and professional goals. If you know you’re low in conscientiousness, you might work on developing better organizational skills to enhance your efficiency.

Improve Communication and Relationships

Understanding your personality traits can also help you communicate more effectively with others. If you know you’re highly openness to experience, you might be more accepting of different viewpoints, which can improve your relationships.

Adapt and Grow

Recognize that your personality is not fixed. While it’s influenced by genetics and upbringing, you can work on developing traits that are important to your personal and professional success.

For instance, if you score low in extraversion but want to become more socially adept, you can gradually practice social interactions.

Cobb-Clark, DA & Schurer, S. The stability of big-five personality traits. Economics Letters. 2012; 115(2): 11–15.

Gerlach M, Farb B, Revelle W, Nunes Amaral LA. A robust data-driven approach identifies four personality types across four large data sets . Nat Hum Behav . 2018;2(10):735-742. doi:10.1038/s41562-018-0419-z

Jang, K.L. et al. (1996). Heritability of the big five personality dimensions and their facets: A twin study. Journal of Personality, 64(3); 577-591.

Power RA, Pluess M. Heritability estimates of the Big Five personality traits based on common genetic variants . Translation Psychiatry . 2015;5:e604. doi:10.1038/tp.2015.96

Mental Illness Personality Disorders What are the big five personality traits?

What are the big five personality traits?

Over several decades, numerous researchers and scientists have devised tests to try and determine individual personality types. They have determined five main personality traits, known as the big five personality traits.

These traits include conscientiousness, agreeableness, neuroticism, openness, and extraversion. Each of these five traits can be tested for and scored from low-to-high to determine an individual’s personality [1] .

The descriptions of low and high scores for each trait reflect the extreme ends of the spectrum. Typically, most people fall somewhere between low and high scores for each trait rather than at either extreme.

While some descriptions of personality may appear negative, it is likely that individuals with these characteristics also hold many positive features. Furthermore, a personality feature that may seem negative, such as rigid thinking or cynicism, may be crucial for certain types of jobs that people on the other end of the spectrum may not be suited for [2] .

However, some negative traits can cause people to be at a higher risk of experiencing mental illness or causing harm to others. These traits may be the focus of professional intervention or self-reflection and self-improvement [2] [3] .

The five traits and their common characteristics

What is the history of the big five personality traits, what influences personality traits, how reliable are personality trait tests, conscientiousness.

People who score high on the test for conscientiousness are likely to have the following characteristics:

• Hardworking
• Strong sense of duty
• Often well prepared
• Goal-orientated
• Academically successful
• Low risk of mental illness
• Possess positive coping skills

People who score low on the test for conscientiousness are likely to have the following characteristics:

• Inattentive
• Dislikes schedules and routines
• Procrastinates
• Poor time management
• Struggles to find purpose
• Disorganized
• Likely to quit or change jobs regularly
• Higher risk of mental illness

Agreeableness

People who score high on the test for agreeableness are likely to have the following characteristics:

• Good-natured
• Cooperative
• Enjoys helping people
• Likely to work in a healthcare profession

People who score low on the test for agreeableness are likely to have the following characteristics:

• Critical of others
• Insensitive
• Competitive
• Rigid thinking
• Uninterested in the feelings or concerns of others
• More likely to work in a professional such as law

Neuroticism

People who score high on the test for neuroticism are likely to have the following characteristics:

• Self-conscious
• Self-critical
• Becomes stressed easily
• Often worries about things
• Emotionally labile
• Experiences mood swings
• Overthinks things
• High risk of depression

People who score low on the test for neuroticism are likely to have the following characteristics:

• Even-tempered
• Unemotional
• Doesn’t often worry or feel stressed
• Lower risk of anxiety and depression

People who score high on the test for openness are likely to have the following characteristics:

• Imaginative
• Enjoys new experiences
• Inquisitive
• Adventurous
• Emotionally intelligent
• Might be at a higher risk of depression due to introspection

People who score low on the test for openness are likely to have the following characteristics:

• Lacks creativity
• Traditional
• Conservative
• Prefers routines
• Uncurious about new things

Extraversion

People who score high on the test for extraversion are likely to have the following characteristics:

• Enjoys talking to people
• Affectionate
• Comfortable with large groups
• Energized by being around others
• Works well with others
• Finds it easy to make friends
• May be more likely to engage in risky or spontaneous activities
• Lower risk of mental illness

People who score low on the test for extraversion are likely to have the following characteristics:

• Uncomfortable with making conversations
• Prefers to work alone
• Prefers solitude
• Unaffectionate
• Independent
• Self-controlled
• Finds social situations draining
• Higher risk of mental illness [1] [2] [3] [4] [5] [6]

For many decades psychologists have researched and investigated patterns of thoughts, behaviors, and emotions in an attempt to determine specific aspects of individual personalities and their links to mental illness, academia, and professionalism [4] .

Paul Costa and Robert McCrae developed the Five-Factor Model of personality, often called the Big Five. This model was based on decades of research and theories around defining and distinguishing personality traits [1] .

This work is believed to have begun in the 1930s by Gordon Allport and Henry Odbert, who initially listed over 4500 traits [7] . Their list was then collated and grouped by Raymond Cattel in the 1940s, who developed a 16-item list of personality traits [8] .

Many psychologists continued to explore these concepts over the following years. This includes Hans Eysenck, who spent several decades researching personality traits. Hans Eysenck went on to develop the PEN Model, which includes psychoticism, extraversion, and neuroticism [9] .

His ideas were then expanded upon and developed by Costa and McCrae in the 1980s, who created the NEO Personality Inventory (NEO-PI), which included neuroticism, extraversion, and openness [10] .

Many continued to explore the ideas developed by Eysenck and Costa & McCrae, with further discussions and personality theories being proposed, including additional inventories by Eysenck [11] .

Costa and McCrae then went on to add agreeableness and conscientiousness to their personality inventory, thus becoming the Five-Factor Model of personality (FFM) [1] . Many psychologists agreed that the FFM was a valid and successful representation of personality, as it has been shown to be a reliable and consistent measurement tool amongst populations across the world [4] .

Several factors can influence personality traits, including genetics, environment, personal experiences, and age.

Research indicates that personality traits are largely linked to genetics. Twin studies show that the five traits of this model are between 40-60% inherited. As such, it can be surmised that a parent who scores very high in neuroticism is likely to pass this trait on to their children [12] [13] .

Environment

Similarly, these traits can be learned by children when exposed to behaviors and attitudes from their parents. Using the example of neuroticism, a neurotic parent is likely to display overt behaviors that will influence their child’s experiences and perspectives. This potentially increases the likelihood of the child going on to develop these neurotic traits themselves [12] [13] .

Experiences

Typically, life experiences will not entirely alter a person’s personality, but certain occurrences may cause an adjustment in how a person scores in each of the five domains [2] .

For example, experiencing a traumatic or life-threatening event could cause a decrease in openness and an increase in neuroticism. This person may become less willing to engage in new activities, be more rigid in their thinking or routines, and become more anxious and worried about the consequences of their actions and the behaviors of others.

Similarly, if someone experiences abuse or bullying, this could cause a decrease in extraversion and agreeableness. They may become more withdrawn, less comfortable in social situations, more suspicious and distrustful of others, and more cynical in how they view the world and others [14] .

It is thought that personality remains relatively consistent throughout a person’s lifetime, particularly after reaching adulthood. However, individual characteristics can change somewhat [2] .

For example, studies suggest that agreeableness and conscientiousness are likely to increase as a person ages and matures, while extraversion, neuroticism, and openness can decrease [15] [16] .

Physical or mental illness

Several medical illnesses and injuries could cause a change in personality , including thyroid problems, dementia, urinary tract infections, and traumatic brain injury. Similarly, many mental health conditions can cause a change in personality, such as schizophrenia, bipolar disorder, personality disorders , anxiety, and depression [17] .

Illnesses could cause changes in any of the five domains. For example, depression could cause a decrease in conscientiousness, extraversion, and openness. It is common for people with depression to become withdrawn, lose interest in activities and socializing, and lose motivation and functioning in academic or professional areas.

Similarly, certain types of dementia could cause a decrease in agreeableness and conscientiousness and increase neuroticism, as dementia can cause mood swings, irritability, suspiciousness, and impaired functioning and cognition.

Professional interventions

Medications and therapy for physical and mental illnesses could also cause changes in personality traits. These interventions can reduce the impact of the illness, thereby reversing any changes that the illness caused [3] [17] .

Additionally, some medications could cause side effects that impact personality, while some therapies may help reduce negative personality traits, such as neuroticism [13] .

Many different personality tests are available online, some of which have been created by psychologists throughout the decades of research into this topic. These tests tend to be of varying reliability, with those not based on scientific research and evidence being the least reliable.

Factors that can influence the reliability of a personality test include [2] [4] [18] :

• Self-reporting: Individuals completing a personality test themselves might be subjected to their own bias and be more inclined to choose personality traits they desire.
• Individual differences: People could produce very different responses to each question within the test due to aspects such as maturity and intellect, thus reducing the validity of certain results.
• Limited view of ‘personality’: Personality may not be entirely defined by a set list of traits as it is a combination of complex factors, thoughts, and behaviors that can change depending on the external environment or context.
• Cultural differences: Different cultures and nationalities may have different ways of describing or assigning certain traits and characteristics, skewing results.

The Big Five, or Five-Factor Model, is considered one of the most reliable personality trait tests. It has been tested within many communities and cultures, age groups, and genders, showing consistent and reliable results throughout [4] .

Most psychologists and professionals agree that this test is reliable despite some criticism that the test is generic or inaccurate [19] . However, the Five-Factor Model continues to be used to help determine academic and professional choices and clinical decisions while also influencing research and discussions around the topic of personality [4] .

• Costa, P.T., Jr., & McCrae, R.R. (1992). Revised NEO Personality Inventory (NEO–PI–R) and NEO Five-Factor Inventory (NEO–FFI) Professional Manual. Odessa, FL: Psychological Assessment Resources.
• McCrae, R.R., & Costa, P.T., Jr. (2003). Personality in Adulthood: A Five-Factor Theory Perspective(2nd ed.). Guilford Press. Retrieved from https://doi.org/10.4324/9780203428412
• Lewis, E.G., & Cardwell, J.M. (2020). The Big Five Personality Traits, Perfectionism and Their Association with Mental Health Among UK Students on Professional Degree Programmes. BMC Psychology, 8, 54. Retrieved from https://doi.org/10.1186/s40359-020-00423-3
• Grice, J.W. (Updated 2023). Five-Factor Model of Personality. Britannica. Retrieved from https://www.britannica.com/science/five-factor-model-of-personality
• Kotov, R., Gamez, W., Schmidt, F., & Watson, D. (2010). Linking “Big” Personality Traits to Anxiety, Depressive, and Substance Use Disorders: A Meta-Analysis. Psychological Bulletin, 136(5), 768–821. Retrieved from https://doi.org/10.1037/a0020327
• Chioqueta, A.P., & Stiles, T.C. (2005). Personality Traits and the Development of Depression, Hopelessness, and Suicide Ideation. Personality and Individual Difference, 38(6), 1283-1291. Retrieved from https://doi.org/10.1016/j.paid.2004.08.010
• Allport, G.W., & Odbert, H.S. (1936). Trait-Names: A Psycho-Lexical Study. Psychological Monographs, 47(1), i–171. Retrieved from https://doi.org/10.1037/h0093360
• Cattell, R.B. (1943). The Description of Personality: Basic Traits Resolved into Clusters. Journal of Abnormal and Social Psychology, 38(4), 476–506. Retrieved from https://doi.org/10.1037/h0054116
• Eysenck, H.J., & Eysenck, S.B.G. (1976). Psychoticism as a Dimension of Personality.London: Hodder and Stoughton.
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Gender Differences in Personality across the Ten Aspects of the Big Five

Yanna j. weisberg.

1 Department of Psychology, Linfield College, McMinnville, OR, USA

Colin G. DeYoung

2 Department of Psychology, University of Minnesota, Minneapolis, MN, USA

Jacob B. Hirsh

3 University of Toronto, Toronto, ON, Canada

This paper investigates gender differences in personality traits, both at the level of the Big Five and at the sublevel of two aspects within each Big Five domain. Replicating previous findings, women reported higher Big Five Extraversion, Agreeableness, and Neuroticism scores than men. However, more extensive gender differences were found at the level of the aspects, with significant gender differences appearing in both aspects of every Big Five trait. For Extraversion, Openness, and Conscientiousness, the gender differences were found to diverge at the aspect level, rendering them either small or undetectable at the Big Five level. These findings clarify the nature of gender differences in personality and highlight the utility of measuring personality at the aspect level.

Introduction

Men and women belong to different species and communications between them is still in its infancy . – Bill Cosby

Many people, including Bill Cosby, perceive the differences between men and women to be large – so large, in fact, that communication between genders may be difficult. Countless examples from popular culture reinforce this view of extreme differences between the sexes – but is it accurate? Men and women have obviously different biological roles when it comes to propagation of the species, but how much they differ psychologically is a more controversial question, one that requires empirical research to answer adequately. Whether the underlying causes of psychological gender differences are evolutionary or socio-cultural, understanding how men and women differ in the ways in which they think, feel, and behave can shed light on the human condition.

The study of personality is particularly useful in attempting to examine psychological differences between genders. Personality is often conceptualized as the extent to which someone displays high or low levels of specific traits. Traits are the consistent patterns of thoughts, feelings, motives, and behaviors that a person exhibits across situations (Fleeson and Gallagher, 2009 ). That is, someone who scores high on a trait will exhibit psychological states related to that trait more often and to a greater extent than individuals who score low on that trait.

Gender differences in personality traits are often characterized in terms of which gender has higher scores on that trait, on average. For example, women are often found to be more agreeable than men (Feingold, 1994 ; Costa et al., 2001 ). This means that women, on average, are more nurturing, tender-minded, and altruistic more often and to a greater extent than men. However, such a finding does not preclude the fact that men may also experience nurturing, tender-minded, and altruistic states, and that some men may even score higher in these traits than some women. The goal of investigating gender differences in personality, therefore, is to elucidate the differences among general patterns of behavior in men and women on average, with the understanding that both men and women can experience states across the full range of most traits. Gender differences in terms of mean differences do not imply that men and women only experience states on opposing ends of the trait spectrum; on the contrary, significant differences can exist along with a high degree of overlap between the distributions of men and women (Hyde, 2005 ).

A core mission of personality psychology has been the development of an adequate taxonomy of personality traits. Drawing on trait descriptors used in natural language (selected from dictionaries) and in personality questionnaires, a five factor structure has emerged to explain covariation among traits. The five factor model or Big Five categorizes traits into the broad domains of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness/Intellect (Digman, 1990 ; John et al., 2008 ).

Gender differences in personality are often examined in terms of the Big Five. However, the Big Five do not exhaust all of the important distinctions among personality traits. Traits are hierarchically organized such that more specific traits that vary together are grouped within higher-order factors, like the Big Five. In the study of gender differences, therefore, one can investigate gender differences in personality traits at multiple levels of resolution. Most trait research has focused on two levels of traits: (1) the broad Big Five domains and (2) many more specific traits, called facets, which are grouped together within the Big Five. Currently, there is no consensus as to the identity and number of facets within the Big Five. Different approaches have identified different sets of facets, based on rational review of psychological constructs (e.g., Costa and McCrae, 1992 ) or by systematic sampling from the space defined by pairs of Big Five factors (e.g., Soto and John, 2009 ). In the present study, we utilized an empirically identified level of personality traits that falls between narrow facets and broad domains. This level of personality organization has the potential to characterize gender differences with a finer grain of detail than the Big Five, revealing differences that are obscured in the Big Five. Additionally, it provides an empirically based taxonomy of lower-level traits, that is more likely to represent an adequate taxonomy of traits than existing facet models.

If the Big Five constituted the level of the personality hierarchy immediately above the facets, only one factor should be necessary to explain the shared variance of the facets within a given Big Five domain. However, a large behavioral genetic study revealed that two distinct factors were necessary to account for the shared genetic variance among the facets within each domain (Jang et al., 2002 ). In a separate study using factor analysis of 15 different facets within each domain, two phenotypic factors similar to the genetic factors were found for each of the Big Five dimensions (DeYoung et al., 2007 ). This research indicates that each of the Big Five contains two separable, though correlated, aspects, reflecting a level of personality below the broad domains but above the many facet scales. DeYoung et al. ( 2007 ) characterized these aspects by examining their factor-score correlations with over 2000 items from the International Personality Item Pool (IPIP). The aspects were labeled as follows: Volatility and Withdrawal for Neuroticism; Enthusiasm and Assertiveness for Extraversion; Intellect and Openness for Openness/Intellect; Industriousness and Orderliness for Conscientiousness; and Compassion and Politeness for Agreeableness. The aspect level of traits may be especially useful for the investigation of gender differences because these differences are sometimes unclear at the Big Five level and can be large and in opposite directions at the facet level. The aspects provide a non-arbitrary and parsimonious system for examining gender differences at a level of traits more specific than the Big Five.

Gender differences have been documented for a number of personality traits. Most meta-analyses and reviews examine gender differences in self-reports of personality on questionnaires that measure the Big Five, as well as facets within each (Feingold, 1994 ; Costa et al., 2001 ; Lippa, 2010 ). To our knowledge, however, no analyses have specifically examined the two aspects of each Big Five trait.

Gender differences in big five personality traits

The investigation of personality differences is important to our understanding of general human variation, though it is not without controversy. Research on individual differences in intelligence, for example, has sparked years of scientifically and emotionally motivated debate (Neisser et al., 1996 ). Gender differences research has also proven to be controversial, with much of the debate concerning the causes and precursors of differences. Biological and evolutionary approaches posit that gender differences are due to men and women's dimorphically evolved concerns with respect to reproductive issues, parental investment in offspring (Trivers, 1972 ; Buss, 2008 ). According to these theories, women should be more concerned with successfully raising children and should therefore be more cautious, agreeable, nurturing, and emotionally involved. Men, on the other hand, should be more concerned with obtaining viable mating opportunities and should therefore exhibit more Assertiveness, risk-taking, and aggression. Other theories suggest that gender norms are shaped by socio-cultural influences, such that women and men are expected to serve different roles in society and are therefore socialized to behave differently from one another (Wood and Eagly, 2002 ; Eagly and Wood, 2005 ). Of course, it may well be that both evolutionary and social forces have contributed to gender differences. Interestingly, recent studies have shown that gender differences in personality tend to be larger in more developed, Western cultures with less traditional sex roles (Costa et al., 2001 ; Schmitt et al., 2008 ). In our review, we focus on the patterns that have been found most consistently across cultures. The overall pattern for gender differences in personality measured by the Big Five is that existing differences are small to medium in size. For some domains, the gender differences are in the same direction across all measured facets; for others, however, the patterns are more divergent.

Neuroticism

Neuroticism describes the tendency to experience negative emotion and related processes in response to perceived threat and punishment; these include anxiety, depression, anger, self-consciousness, and emotional lability. Women have been found to score higher than men on Neuroticism as measured at the Big Five trait level, as well as on most facets of Neuroticism included in a common measure of the Big Five, the NEO-PI-R (Costa et al., 2001 ). Additionally, women also score higher than men on related measures not designed specifically to measure the Big Five, such as indices of anxiety (Feingold, 1994 ) and low self-esteem (Kling et al., 1999 ). The one facet of Neuroticism in which women do not always exhibit higher scores than men is Anger, or Angry Hostility (Costa et al., 2001 ).

Agreeableness

Agreeableness comprises traits relating to altruism, such as empathy and kindness. Agreeableness involves the tendency toward cooperation, maintenance of social harmony, and consideration of the concerns of others (as opposed to exploitation or victimization of others). Women consistently score higher than men on Agreeableness and related measures, such as tender-mindedness (Feingold, 1994 ; Costa et al., 2001 ).

Conscientiousness

Conscientiousness describes traits related to self-discipline, organization, and the control of impulses, and appears to reflect the ability to exert self-control in order to follow rules or maintain goal pursuit. Women score somewhat higher than men on some facets of Conscientiousness, such as order, dutifulness, and self-discipline (Feingold, 1994 ; Costa et al., 2001 ). These differences, however, are not consistent across cultures, and no significant gender difference has typically been found in Conscientiousness at the Big Five trait level (Costa et al., 2001 ).

Extraversion

Extraversion reflects sociability, Assertiveness, and positive emotionality, all of which have been linked to sensitivity to rewards (Depue and Collins, 1999 ; DeYoung and Gray, 2009 ). Whereas gender differences are small on the overall domain level of Extraversion (with women typically scoring higher), the small effect size could be due to the existence of gender differences in different directions at the facet level. Women tend to score higher than men on Warmth, Gregariousness, and Positive Emotions, whereas men score higher than women on Assertiveness and Excitement Seeking (Feingold, 1994 ; Costa et al., 2001 ).

Extraversion, together with Agreeableness, can be used to describe the two dimensions of the interpersonal circumplex (IPC; Wiggins, 1979 ), which contains descriptions of traits relevant to interpersonal interaction. Though originally posited to describe interpersonal traits using axes of Love and Status/Dominance, the IPC can also be conceptualized as a rotation of Big Five Extraversion and Agreeableness (McCrae and Costa, 1989 ). Given the importance of Extraversion to the interpersonal domain, it may be expected that women would consistently score higher than men. However the pole of the IPC often called Dominance contains traits such as bossy, domineering, and assertive. Men tend to be more dominant and agentic than women, and exhibit higher levels of these traits (Helgeson and Fritz, 1999 ). Gender differences in Extraversion may therefore switch directions depending on whether the specific traits measured fall closer or further from the dominance pole.

Openness/Intellect

Openness/Intellect reflects imagination, creativity, intellectual curiosity, and appreciation of esthetic experiences. Broadly, Openness/Intellect relates to the ability and interest in attending to and processing complex stimuli. No significant gender differences are typically found on Openness/Intellect at the domain level, likely due to the divergent content of the trait. For example, women have been found to score higher than men on the facets of Esthetics and Feelings (Costa et al., 2001 ), whereas men tend to score higher on the Ideas facet (Feingold, 1994 ; Costa et al., 2001 ).

Hypotheses regarding the 10 aspects

The pattern of gender differences reviewed above highlights the need to look beyond the Big Five level to traits at lower levels of analysis. Because the domains of the Big Five are so broad and encompass a variety of personality characteristics, greater specificity is needed to uncover where gender differences truly lie. The current research seeks to replicate previous findings regarding gender differences at the Big Five level, as well as to extend investigation into the intermediate sublevel of the two aspects within each domain.

Though no research has been done previously on gender differences at the aspect level of trait structure, we expect that the likely pattern of findings can be deduced from those reported for the Big Five and their facets. Because the aspects are more parsimonious and comprehensive than the facet models, however, they should provide a clearer and more systematic representation of gender differences in personality.

Our hypotheses were that women should score higher than men in both aspects of Neuroticism, Volatility, and Withdrawal, though the effect is likely to be stronger for Withdrawal, given the inclusion of anger within Volatility. Similarly, women should score higher than men in both aspects of Agreeableness, Compassion, and Politeness. Gender differences in the aspects of Conscientiousness, Industriousness, and Orderliness, may diverge, as research on facets suggests that women should score higher on Orderliness, but does not allow a clear prediction for Industriousness. The two aspects of Extraversion, Enthusiasm, and Assertiveness, should diverge because women should score higher than men in Enthusiasm (which combines sociability and positive emotionality), whereas men should score higher in Assertiveness. Gender differences should also be in opposite directions for the aspects of Openness/Intellect, Openness and Intellect. Women should score higher than men in Openness, whereas men should score higher than women in Intellect.

Use of the aspects has the additional advantage that one can easily examine the unique effects of one aspect while controlling for the other in each pair. In cases where gender differences on the two aspects diverge, this approach may reveal differences that are ordinarily suppressed by the shared variance of the two aspects within each Big Five domain. We implemented this approach through the use of residualized scores. Regressing one aspect on its complementary aspect and saving the residual produces a score that indicates unique variance in that aspect, without the variance it shares with its complement. For example, the residualized score for Compassion indicates differences in Compassion holding Politeness equal. If women are found, as predicted, to have higher Compassion residuals than men, that means that even if we take groups of men and women of equal Politeness, the women are nonetheless likely to be higher in Compassion on average.

Due to the diversity of our sample, we performed secondary analyses to investigate potential moderators of gender differences. For example, previous research has shown that gender differences are larger and more pronounced within Western cultures than Eastern cultures (Costa et al., 2001 ; Schmitt et al., 2008 ). Though our sample was collected mostly within North America, we were interested if similar patterns would emerge when considering gender differences among people of different ethnic backgrounds. We were able to test whether the pattern of gender differences was similar in participants of European versus Asian ethnic backgrounds.

Additionally, previous research has shown that gender differences in some traits (such as negative affect) may be larger in emerging adulthood than in later adulthood (Soto et al., 2011 ). Therefore, we investigated whether age moderated the gender difference in each trait. Finally, an increasing number of studies are using an online method to administer personality measures. Our sample included both laboratory and online methods of administration. Though previous research has not shown significant difference in personality between these two methods (Gosling et al., 2004 ), we investigated whether administration method moderated gender differences in our sample.

Materials and Methods

Participants.

Participants ( N  = 2643; 892 male, 1751 female) were drawn from a number of research projects, for which they received either monetary compensation or university course credit. Much of the data was collected in a large Canadian metropolitan area, either as an online survey or as a part of laboratory studies ( N  = 1826; 537 male, 1289 female). Some participants ( N  = 481; 200 male, 281 female) were members of the Eugene-Springfield community sample (ESCS). Lastly, 336 participants were recruited via Amazon's Mechanical Turk (MTurk; 155 male, 181 female) and completed the measures online. Participants ranged in age from 17 to 85 ( M  = 27.2, SD = 14.4). The majority of participants identified as White (39.9%) or Asian (27.5%), with 1% or less identifying as Native American, Hispanic, and Black. Twenty-five percent of participants identified as “other,” and 5% did not specify ethnicity. The demographic data for a number of our samples allowed participants to choose from only the above five ethnicity classifications or specify their ethnicity as “other.” Therefore, the classification of “Asian” contains individuals of both South-Asian and East-Asian ethnic backgrounds. Though South-Asian and East-Asian cultures are markedly different in many ways, both are more collectivist than Western cultures (Suh et al., 1998 ) and therefore provide an interesting contrast to the White/European ethnic background.

Personality measures

The Big Five aspect scales (BFAS) were designed specifically to assess the 10 aspects of the Big Five identified by DeYoung et al. ( 2007 ). Items were selected from the IPIP based on their correlation with the aspect factor scores and maintaining balanced keying. Items were chosen that differentiated the factor in question from all nine other aspect factors, by selecting items only if they were correlated with the aspect factor in question with a correlation at least 0.10 greater than the correlation with any other factor. This procedure has the consequence that the same items remain the best markers of each factor even when scores are residualized. Thus, the residualized scores retain the meaning of the construct in question. Ten items are used to assess each of the 10 aspects. Participants rate their agreement with how well each statement describes them using a five-point scale ranging from strongly disagree to strongly agree . Scores for each aspect are computed by taking the mean of the corresponding items. Scores for each domain are computed by taking the mean of the two aspect scores. The scales are all highly reliable (all α > 0.73) and have good test–retest reliability, all r  > 0.72 (DeYoung et al., 2007 ). Internal consistencies for the present data are shown in Table ​ Table1 1 .

Alpha reliabilities for Big Five domains and aspect scales by sample .

Table ​ Table2 2 summarizes the mean scores for men and women on each of the 10 aspects and the five domains. Because the two aspects within each domain are correlated (correlations range from r  = 0.39–0.62), analyses on the aspects were performed on both raw scores and residualized scores. Residualized scores were created by regressing one aspect within a domain on the other, and saving the residuals, thus creating an index of the variance of each aspect not associated with its complement in the same domain. For example, the residualized scores for Enthusiasm are the residuals resulting from the regression of Enthusiasm on Assertiveness, effectively partialing out the general Extraversion variance shared between Enthusiasm and Assertiveness. Table ​ Table3 3 presents the intercorrelations between aspects, analyzed separately for men and women.

Mean and SD for Big Five domains and raw and residualized aspect scores .

Bolded d values indicate statistically significant effect sizes .

Correlations among aspects (raw scores) .

Correlations above the diagonal are for males; females are below the diagonal .

Gender differences were analyzed using independent samples t -tests. Effect sizes are summarized in Table ​ Table2. 2 . Results were consistent with previous analyses, with significant effects found at the level of the Big Five domains of Neuroticism, Agreeableness, and Extraversion, but not Conscientiousness or Openness. The largest effect sizes were found for Neuroticism and Agreeableness. Unsurprisingly, Neuroticism and Agreeableness are the domains for which gender differences were significant and in the same direction for both underlying aspects.

Using the raw scores, gender differences were found in all of the aspects with the exception of Industriousness. Women scored higher than men on Enthusiasm, Compassion, Politeness, Orderliness, Volatility, Withdrawal, and Openness. Men scored higher than women on Assertiveness and Intellect. This indicates that the two aspects of Extraversion (Enthusiasm and Assertiveness) and the two aspects of Openness/Intellect display gender differences in opposite directions. Such divergence in gender differences at the aspect level helps to elucidate the small effect of the gender difference in overall Extraversion and the lack of a significant gender difference in Openness/Intellect. As in previous research, effect sizes were small to moderate (range: 0.06–0.48 in absolute value).

Results for the residualized scores differed from those on the raw scores in two ways. First, the gender difference in Industriousness was now significant, with men scoring higher than women. Since this is a residualized score, it indicates a gender difference in Industriousness among people with equal levels of Orderliness. Second, there was not a significant gender difference in residualized scores of Volatility. This indicates no difference between the average scores of men and women in Volatility when they are at equal levels of Withdrawal.

We performed regression analyses to see if ethnicity, age, and survey method moderated the gender differences we had found. Previous research suggests that gender differences are robust across cultures (Costa et al., 2001 ; McCrae et al., 2005 ), and may differ with age for some traits (Soto et al., 2011 ). Because the majority of the participants in our sample were White and Asian, we were able to make comparisons only for these two groups.

Ethnicity (coded as White or Asian) significantly moderated gender differences in the Big Five domain of Agreeableness, F (1, 1759) = 5.42, p  = 0.02, with a more pronounced gender difference found among Whites than among Asians (see Figure ​ Figure1). 1 ). Similar patterns were found for ethnicity moderating the gender difference in Compassion in both the raw scores, F (1, 1759) = 7.97, p  < 0.001, (see Figure ​ Figure2) 2 ) and the residualized scores, F (1, 1759) = 6.64, p  = 0.01, (see Figure ​ Figure3). 3 ). When Politeness was partialed out of the Compassion scores, there was no difference between White men and Asian men and a significant difference between White women and Asian women, such that the gender difference was more pronounced for Whites than for Asians.

Ethnicity moderates gender differences in Agreeableness .

Ethnicity moderates gender differences in Compassion .

Ethnicity moderates gender differences in Compassion (residualized) . Residualized scores are depicted as the scores plus 1, for ease of interpretation.

Ethnicity also moderated gender differences in the residualized scores for Volatility, F (1, 1759) = 5.09, p  = 0.02, though this pattern was somewhat different. The gender difference was significant for Asian participants such that women scored higher than men. However, for White participants, men scored higher than women (see Figure ​ Figure4). 4 ). No other moderations by ethnicity were observed.

Ethnicity moderates gender differences in Volatility (residualized) . Residualized scores are depicted as the scores plus 1, for ease of interpretation.

Age significantly moderated gender differences in the Big Five domains of Agreeableness, F (1, 2576) = 4.88, p  = 0.03, Neuroticism, F (1, 2576) = 11.35, p  < 0.001, and Openness, F (1, 2576) = 4.26, p  = 0.04. The gender difference in Agreeableness was larger for older ages, and the gender difference in Neuroticism was larger for younger ages. In addition, the gender difference seemed to reverse for Neuroticism, such that men had higher scores than women in older ages. For Openness/Intellect, the gender difference was non-existent at younger ages, and larger favoring women at older ages. These patterns were driven by specific aspects, as evidenced by age's moderating the gender difference in Compassion, F (1, 2576) = 7.64, p  = 0.01 (see Figure ​ Figure5), 5 ), Volatility, F (1, 2576) = 19.79, p  < 0.001 (see Figure ​ Figure6), 6 ), and Intellect, F (1, 2576) = 3.96, p  = 0.05 (see Figure ​ Figure7). 7 ). The pattern for Intellect is such that there is a larger gender difference for younger ages than for older, favoring men. At older ages, the gender difference is non-existent or slightly favors women.

Age moderates gender differences in Compassion .

Age moderates gender differences in Volatility .

Age moderates gender differences in Intellect .

Age also moderated gender differences in the residualized scores for Compassion, F (1, 2576) = 6.76, p  = 0.01, Orderliness, F (1,2576) = 5.02, p  = 0.03 (see Figure ​ Figure8), 8 ), and Volatility F (1, 2576) = 20.21, p  < 0.001. The pattern for Compassion was similar to that found for the raw scores, such that the gender difference in residualized Compassion increased with age. The gender difference in residualized Orderliness was small and favored women at younger ages, yet it decreased to non-existence and almost reversed to favor men in older ages. Finally, the pattern for Volatility was similar to that found for the raw scores, such that the gender difference favored women at younger ages and men at older.

Age moderates gender differences in Orderliness (residualized) . Residualized scores are depicted as the scores plus 1, for ease of interpretation.

The format of the administration of the surveys moderated gender differences in Compassion on both the raw, F (1, 2115) = 6.14, p  = 0.01 (see Figure ​ Figure9), 9 ), and residualized, F (1, 2115) = 6.63, p  = 0.01, metrics. Womens’ Compassion scores did not differ between the online and laboratory format. Men who completed the survey in the lab had higher average Compassion scores than did men who completed the survey online. The results for the residualized Compassion scores were nearly identical to those for the raw scores, depicted in Figure ​ Figure9 9 .

Administration method moderates gender differences in Compassion .

Gender differences were more pervasive at the aspect level of trait organization immediately below the Big Five than for the Big Five themselves. At the level of the Big Five our findings were similar to the typical pattern: gender differences were found only for Neuroticism, Agreeableness, and Extraversion. However, gender differences were found for every one of the 10 aspects, considering analyses of both raw and residualized scores. Even when examining raw scores alone, differences were significant in 9 out of 10 traits. Clearly, analysis of the aspects reveals the extent of gender differences across the whole spectrum of traits encompassed by the hierarchical Big Five model.

Consistent with previous findings, women scored higher than men in Neuroticism and in both of its aspects, Withdrawal and Volatility, when measured in terms of raw scores. This difference replicates previous findings for Neuroticism (e.g., Costa et al., 2001 ). Because Withdrawal and Volatility are correlated ( r  = 0.62 in our sample as a whole) but distinct traits, it is important to consider the unique variance that each does not share with the other. We therefore additionally examined gender differences in Withdrawal with Volatility partialed out, and vice versa . The gender difference remained for Withdrawal but was eliminated for Volatility. This contrast for the unique variance in these two aspects is not surprising if one considers the more specific content of each. At the facet level of Neuroticism, women have been found to show higher levels of anxiety, depression, self-consciousness, and vulnerability than men (Costa et al., 2001 ). All of these facets load primarily on Withdrawal rather than Volatility (DeYoung et al., 2007 ). This pattern is consistent with the fact that clinical diagnoses of depression and anxiety are considerably more common in women than men (Weissman et al., 1996 ).

In contrast, the lack of a significant gender difference in Volatility, when controlling for Withdrawal, is most likely due to the fact that an important component of Volatility is the tendency to be irritable and easily angered. Men have sometimes been found to score higher than women on traits such as Anger or Hostility (Scherwitz et al., 1991 ).

The gender difference in Neuroticism was moderated by age, such that the gender difference decreased with age. Neuroticism increases during emerging adulthood among females, but not males (Soto et al., 2011 ), which may explain this pattern of results. The gender difference in Volatility was moderated by both age and ethnicity. For age, the pattern was the same as for the overall domain of Neuroticism, and was seen for both Volatility on the raw scale metric and when controlling for Withdrawal. The moderating effect ethnicity had on residualized scores for Volatility was different, showing gender differences in opposite directions among White and Asian participants. Men scored higher in Volatility than women among White participants, whereas women scored higher among Asian participants. Given the fact that Volatility partly reflects traits related to irritability and anger, this difference may be due to cultural differences in social norms related to the expression of anger (Matsumoto and Fontaine, 2008 ).

Replicating previous findings, there was a significant gender difference in Agreeableness such that women tend to score higher than men, and this pattern was the same for the aspects, Compassion and Politeness, when measured in terms of raw scores or residualized scores. Compassion most clearly represents a tendency to invest in others emotionally and affiliate on an emotional level, encompassing traits such as warmth and empathy. Politeness describes the tendency to show respect to others and refrain from taking advantage of them, and is related to traits such as cooperation and compliance. Our findings that women score higher than men on both aspects are consistent with previous research showing women are more trusting and compliant than men (Costa et al., 2001 ).

Gender differences in Agreeableness may be related to gender differences in self-construal. Men tend to have an independent self-construal, or a sense of self that is separate from cognitive representations of others. Women have a more interdependent self-construal, in which their sense of self includes others (Markus and Kitayama, 1991 ). This gender difference is associated with motivational and behavioral differences, such as women having more interconnected and affiliative social groups (Cross and Madson, 1997 ). Women, therefore, may be more motivated than men to maintain social and emotional bonds by enacting more agreeable traits.

Age moderated gender differences in Agreeableness and Compassion on both the raw and residualized metric, such that gender differences were larger among older individuals.

Ethnicity moderated the gender differences in Agreeableness and its Compassion aspect, such that differences were larger among White participants than among Asian participants. This finding is consistent with previous research, which shows larger gender differences among more western and industrialized cultures (Costa et al., 2001 ; McCrae et al., 2005 ; Schmitt et al., 2008 ). Asian participants in general rated themselves as less agreeable than white participants, which may indicate a reference group effect. A reference group effect would occur if participants are comparing themselves to their own culture and there is a difference in Agreeableness between cultures. For example, someone who is more agreeable than the norm for Whites may be less agreeable than the norm for Asians. Asian participants could be comparing themselves to an allocentric cultural norm, in which consideration for others is central and therefore higher Agreeableness is normative (Triandis, 2001 ).

Method of administration of the measure also moderated the gender difference in Compassion on both the raw and residualized metric. The gender difference was larger in online administration than for laboratory administration. This is because men scored higher in Compassion on average when they completed the measure in the laboratory than when they completed it online. This may be due to social desirability effects’ causing men to report being higher in Compassion when they are in the laboratory, and not when they are completing the measure online.

Consistent with previous research, we did not find a significant gender difference in Conscientiousness at the level of the Big Five domain. When measuring the aspects of Industriousness and Orderliness in terms of raw scores, however, we found a significant gender difference for Orderliness, such that women score higher than men. The Orderliness aspect reflects traits related to maintaining order and organization, including perfectionism (DeYoung et al., 2007 ). Given the positive correlation between perfectionism and components of Neuroticism such as anxiety and depression (Dunkley et al., 2006 ; Sherry et al., 2007 ), and the well-established gender differences in Neuroticism, one possibility is that Neuroticism accounts for the gender difference in Orderliness. However, when we regressed Orderliness (either raw or residualized) on Neuroticism and gender, gender remained a significant predictor, indicating that gender differences in Orderliness are not simply due to differences in Neuroticism.

Age moderated the gender difference in residualized Orderliness, such that the gender difference favoring women seen at younger ages decreased to non-existence and reversal at older ages. The age trend for women indicated a decline in Orderliness relative to Industriousness, whereas the trend for men indicated an increase.

Though no gender difference was found for Industriousness when using the raw scores, we found a gender difference in Industriousness when using the residualized score that removed any variance shared with Orderliness. This gender difference was such that men scored higher than women in Industriousness. This difference in residualized scores but not raw scores can be interpreted as follows: if one examines a group of people with equal levels of Orderliness, the men in that group will on average score higher in Industriousness than the women.

We found a small but significant gender difference in overall Extraversion such that women score higher than men. However, the pattern was more complicated for the aspects, Enthusiasm and Assertiveness. Enthusiasm reflects sociability, gregariousness, and experiences of positive emotion. Our finding that women score higher than men in Enthusiasm was consistent with previous research showing similar patterns in Big Five facets of Gregariousness and Positive Emotions (Feingold, 1994 ; Costa et al., 2001 ). Assertiveness, on the other hand, reflects traits related to agency and dominance. Consistent with previous research showing a gender difference favoring men for facets such as Assertiveness and Excitement Seeking (Feingold, 1994 ; Costa et al., 2001 ), we found that men score higher than women in Assertiveness. This pattern of gender differences in opposite directions at the aspect level was also found for scores on the residualized metric.

Openness/intellect

Consistent with previous research, we did not find a significant difference in Openness/Intellect at the level of the Big Five domain. However, we found significant gender differences in both aspects of the Big Five domain (Intellect and Openness). On both the raw and residualized scores women scored higher than men in Openness. In contrast, on both types of score, men scored higher than women in Intellect. This pattern is consistent with previous reports of gender differences at the facet level, where women score higher than men on facets marking Openness (such as Esthetics and Feelings), but men score higher than women on the Ideas facet, which is a marker of Intellect (Feingold, 1994 ; Costa et al., 2001 ).

Although Intellect includes perceptions of cognitive ability and is more strongly associated with IQ scores than Openness (DeYoung et al., submitted), the fact that men score higher than women in Intellect should not be taken as indicative of greater intelligence for men than women. Gender differences in general intelligence are negligible, although men are typically found to show more variance in scores than women (Deary et al., 2007 ; van der Sluis et al., 2008 ). However, our findings are consistent with the finding that men show higher self-estimates of intelligence than women, across cultures (von Stumm et al., 2009 ). This pattern has been described as one of male hubris and female humility in relation to intelligence. The gender difference in Intellect probably reflects these biases related to confidence in intellectual abilities.

Age moderated the gender difference in Intellect such that the gender difference was smaller at higher ages. The pattern suggests that the difference in Intellect between older and younger women is larger than that between older and younger men. Since gender differences in intelligence are negligible across the lifespan, this pattern most likely indicates that women gain in perceptions of their own intelligence, perhaps reflecting increases in self-esteem or self-confidence (Orth et al., 2010 ).

Limitations and future directions

Our investigation was limited to one measure of personality, the BFAS. Although the Big Five organization of personality that it employs is reasonably comprehensive, there are traits that may not have good representation among the items in the BFAS, such as adult attachment style (Hazan and Shaver, 1987 ). It would be worthwhile for future research to investigate gender differences in these additional traits as well as how they relate to gender differences in the Big Five.

Further, the personality scores used in our investigation were obtained via self-report. Our findings could therefore indicate gender differences in how men and women perceive and report on themselves, which do not necessarily reflect how they are perceived by others or their actual behavioral tendencies. Future research should explore gender differences in peer-reports of these personality traits. This might be especially interesting when the perceiver is of the opposite gender from the target. Additionally, behavioral or implicit measures of personality could be used to investigate whether the same pattern of gender differences exist when one moves beyond measuring personality through questionnaires.

Previous research has investigated gender differences among many different ethnicities, cultures, and types of societies (McCrae et al., 2005 ; Schmitt et al., 2008 ). Such an investigation is beyond the scope of the current research. The current sample was mainly North American, and sample sizes within each ethnic group were limited, such that we were only able to perform analyses comparing White participants to Asian participants. It would be beneficial for future research to investigate gender differences in personality at the aspect level in additional ethnicities and cultures.

Similarly, our research indicated that age moderated gender differences in a number of traits. Our sample was cross-sectional rather than longitudinal, hence our results may not accurately reflect the trajectories of personality change in men and women over time. Taken along with previous findings on age trends in personality (e.g., Roberts et al., 2006 ; Soto et al., 2011 ), our results suggest the utility of further investigation of how gender differences in personality may differ with increasing age.

Finally, though this and other studies have shown the existence of gender differences in personality, the question remains as to why these differences exist. Although the general consistency of gender differences across cultures may suggest evolutionary reasons for the existence of gender differences in personality traits, cross-cultural variation in gender differences for some trait may suggest that culture of origin or social roles and norms influence gender differences. Exactly how culture impacts personality is a complex question, worthy of future study.

By examining personality at the level of the 10 aspects of the Big Five, we demonstrated that gender differences in personality traits are even more pervasive than has typically been reported. In every one of the 10 traits assessed, significant gender differences were evident. For some Big Five domains, the aspect level traits showed gender differences in opposite directions, which helps to explain why gender differences are not typically evident for the Big Five domains of Conscientiousness and Openness/Intellect, and why the gender difference for Extraversion is typically very small.

Clearly the average personalities of men and women are systematically different. Does this mean, however, that Bill Cosby's metaphor, that men and women are from “different species,” is apt? We would caution against adopting such a dramatic interpretation of the pervasive gender differences in personality that we report in this study. All of the mean differences we found (and all of the differences that have been found in the past – e.g., Feingold, 1994 ; Costa et al., 2001 ) are small to moderate. This means that the distributions of traits for men and women are largely overlapping. To illustrate this fact, in Figure ​ Figure10 10 we present the male and female distributions from our sample for the trait which showed the largest gender difference, Agreeableness. One can see that both men and women can be found across a similar range of Agreeableness scores, such that, despite the fact that women score higher than men on average, there are many men who are more agreeable than many women, and many women who are less agreeable than many men. Given that Agreeableness showed the largest gender difference in our study, all other traits for which we reported significant gender differences would show even greater overlap in men's and women's distributions. Although the mean differences in personality between genders may be important in shaping human experience and human culture, they are probably not so large as to preclude effective communication between men and women. Unlike Bill Cosby, we are optimistic that any difficulties in communication between men and women are due primarily to cultural norms that are amenable to change, rather than to differences in basic personality traits, which are much more difficult to change.

Overlapping distributions of Agreeableness for men and women . Vertical axis indicates density, or the proportion of the sample in a given area under the curve.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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• Published: 17 October 2023

The impact of founder personalities on startup success

• Paul X. McCarthy 1 , 2 ,
• Xian Gong 3 ,
• Fabian Braesemann 4 , 5 ,
• Fabian Stephany 4 , 5 ,
• Marian-Andrei Rizoiu 3 &
• Margaret L. Kern 6  

Scientific Reports volume  13 , Article number:  17200 ( 2023 ) Cite this article

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An Author Correction to this article was published on 07 May 2024

This article has been updated

Startup companies solve many of today’s most challenging problems, such as the decarbonisation of the economy or the development of novel life-saving vaccines. Startups are a vital source of innovation, yet the most innovative are also the least likely to survive. The probability of success of startups has been shown to relate to several firm-level factors such as industry, location and the economy of the day. Still, attention has increasingly considered internal factors relating to the firm’s founding team, including their previous experiences and failures, their centrality in a global network of other founders and investors, as well as the team’s size. The effects of founders’ personalities on the success of new ventures are, however, mainly unknown. Here, we show that founder personality traits are a significant feature of a firm’s ultimate success. We draw upon detailed data about the success of a large-scale global sample of startups (n = 21,187). We find that the Big Five personality traits of startup founders across 30 dimensions significantly differ from that of the population at large. Key personality facets that distinguish successful entrepreneurs include a preference for variety, novelty and starting new things (openness to adventure), like being the centre of attention (lower levels of modesty) and being exuberant (higher activity levels). We do not find one ’Founder-type’ personality; instead, six different personality types appear. Our results also demonstrate the benefits of larger, personality-diverse teams in startups, which show an increased likelihood of success. The findings emphasise the role of the diversity of personality types as a novel dimension of team diversity that influences performance and success.

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Introduction.

The success of startups is vital to economic growth and renewal, with a small number of young, high-growth firms creating a disproportionately large share of all new jobs 1 , 2 . Startups create jobs and drive economic growth, and they are also an essential vehicle for solving some of society’s most pressing challenges.

As a poignant example, six centuries ago, the German city of Mainz was abuzz as the birthplace of the world’s first moveable-type press created by Johannes Gutenberg. However, in the early part of this century, it faced several economic challenges, including rising unemployment and a significant and growing municipal debt. Then in 2008, two Turkish immigrants formed the company BioNTech in Mainz with another university research colleague. Together they pioneered new mRNA-based technologies. In 2020, BioNTech partnered with US pharmaceutical giant Pfizer to create one of only a handful of vaccines worldwide for Covid-19, saving an estimated six million lives 3 . The economic benefit to Europe and, in particular, the German city where the vaccine was developed has been significant, with windfall tax receipts to the government clearing Mainz’s €1.3bn debt and enabling tax rates to be reduced, attracting other businesses to the region as well as inspiring a whole new generation of startups 4 .

While stories such as the success of BioNTech are often retold and remembered, their success is the exception rather than the rule. The overwhelming majority of startups ultimately fail. One study of 775 startups in Canada that successfully attracted external investment found only 35% were still operating seven years later 5 .

But what determines the success of these ‘lucky few’? When assessing the success factors of startups, especially in the early-stage unproven phase, venture capitalists and other investors offer valuable insights. Three different schools of thought characterise their perspectives: first, supply-side or product investors : those who prioritise investing in firms they consider to have novel and superior products and services, investing in companies with intellectual property such as patents and trademarks. Secondly, demand-side or market-based investors : those who prioritise investing in areas of highest market interest, such as in hot areas of technology like quantum computing or recurrent or emerging large-scale social and economic challenges such as the decarbonisation of the economy. Thirdly, talent investors : those who prioritise the foundation team above the startup’s initial products or what industry or problem it is looking to address.

Investors who adopt the third perspective and prioritise talent often recognise that a good team can overcome many challenges in the lead-up to product-market fit. And while the initial products of a startup may or may not work a successful and well-functioning team has the potential to pivot to new markets and new products, even if the initial ones prove untenable. Not surprisingly, an industry ‘autopsy’ into 101 tech startup failures found 23% were due to not having the right team—the number three cause of failure ahead of running out of cash or not having a product that meets the market need 6 .

Accordingly, early entrepreneurship research was focused on the personality of founders, but the focus shifted away in the mid-1980s onwards towards more environmental factors such as venture capital financing 7 , 8 , 9 , networks 10 , location 11 and due to a range of issues and challenges identified with the early entrepreneurship personality research 12 , 13 . At the turn of the 21st century, some scholars began exploring ways to combine context and personality and reconcile entrepreneurs’ individual traits with features of their environment. In her influential work ’The Sociology of Entrepreneurship’, Patricia H. Thornton 14 discusses two perspectives on entrepreneurship: the supply-side perspective (personality theory) and the demand-side perspective (environmental approach). The supply-side perspective focuses on the individual traits of entrepreneurs. In contrast, the demand-side perspective focuses on the context in which entrepreneurship occurs, with factors such as finance, industry and geography each playing their part. In the past two decades, there has been a revival of interest and research that explores how entrepreneurs’ personality relates to the success of their ventures. This new and growing body of research includes several reviews and meta-studies, which show that personality traits play an important role in both career success and entrepreneurship 15 , 16 , 17 , 18 , 19 , that there is heterogeneity in definitions and samples used in research on entrepreneurship 16 , 18 , and that founder personality plays an important role in overall startup outcomes 17 , 19 .

Motivated by the pivotal role of the personality of founders on startup success outlined in these recent contributions, we investigate two main research questions:

Which personality features characterise founders?

Do their personalities, particularly the diversity of personality types in founder teams, play a role in startup success?

We aim to understand whether certain founder personalities and their combinations relate to startup success, defined as whether their company has been acquired, acquired another company or listed on a public stock exchange. For the quantitative analysis, we draw on a previously published methodology 20 , which matches people to their ‘ideal’ jobs based on social media-inferred personality traits.

We find that personality traits matter for startup success. In addition to firm-level factors of location, industry and company age, we show that founders’ specific Big Five personality traits, such as adventurousness and openness, are significantly more widespread among successful startups. As we find that companies with multi-founder teams are more likely to succeed, we cluster founders in six different and distinct personality groups to underline the relevance of the complementarity in personality traits among founder teams. Startups with diverse and specific combinations of founder types (e. g., an adventurous ‘Leader’, a conscientious ‘Accomplisher’, and an extroverted ‘Developer’) have significantly higher odds of success.

We organise the rest of this paper as follows. In the Section " Results ", we introduce the data used and the methods applied to relate founders’ psychological traits with their startups’ success. We introduce the natural language processing method to derive individual and team personality characteristics and the clustering technique to identify personality groups. Then, we present the result for multi-variate regression analysis that allows us to relate firm success with external and personality features. Subsequently, the Section " Discussion " mentions limitations and opportunities for future research in this domain. In the Section " Methods ", we describe the data, the variables in use, and the clustering in greater detail. Robustness checks and additional analyses can be found in the Supplementary Information.

Our analysis relies on two datasets. We infer individual personality facets via a previously published methodology 20 from Twitter user profiles. Here, we restrict our analysis to founders with a Crunchbase profile. Crunchbase is the world’s largest directory on startups. It provides information about more than one million companies, primarily focused on funding and investors. A company’s public Crunchbase profile can be considered a digital business card of an early-stage venture. As such, the founding teams tend to provide information about themselves, including their educational background or a link to their Twitter account.

We infer the personality profiles of the founding teams of early-stage ventures from their publicly available Twitter profiles, using the methodology described by Kern et al. 20 . Then, we correlate this information to data from Crunchbase to determine whether particular combinations of personality traits correspond to the success of early-stage ventures. The final dataset used in the success prediction model contains n = 21,187 startup companies (for more details on the data see the Methods section and SI section  A.5 ).

Revisions of Crunchbase as a data source for investigations on a firm and industry level confirm the platform to be a useful and valuable source of data for startups research, as comparisons with other sources at micro-level, e.g., VentureXpert or PwC, also suggest that the platform’s coverage is very comprehensive, especially for start-ups located in the United States 21 . Moreover, aggregate statistics on funding rounds by country and year are quite similar to those produced with other established sources, going to validate the use of Crunchbase as a reliable source in terms of coverage of funded ventures. For instance, Crunchbase covers about the same number of investment rounds in the analogous sectors as collected by the National Venture Capital Association 22 . However, we acknowledge that the data source might suffer from registration latency (a certain delay between the foundation of the company and its actual registration on Crunchbase) and success bias in company status (the likeliness that failed companies decide to delete their profile from the database).

The definition of startup success

The success of startups is uncertain, dependent on many factors and can be measured in various ways. Due to the likelihood of failure in startups, some large-scale studies have looked at which features predict startup survival rates 23 , and others focus on fundraising from external investors at various stages 24 . Success for startups can be measured in multiple ways, such as the amount of external investment attracted, the number of new products shipped or the annual growth in revenue. But sometimes external investments are misguided, revenue growth can be short-lived, and new products may fail to find traction.

Success in a startup is typically staged and can appear in different forms and times. For example, a startup may be seen to be successful when it finds a clear solution to a widely recognised problem, such as developing a successful vaccine. On the other hand, it could be achieving some measure of commercial success, such as rapidly accelerating sales or becoming profitable or at least cash positive. Or it could be reaching an exit for foundation investors via a trade sale, acquisition or listing of its shares for sale on a public stock exchange via an Initial Public Offering (IPO).

For our study, we focused on the startup’s extrinsic success rather than the founders’ intrinsic success per se, as its more visible, objective and measurable. A frequently considered measure of success is the attraction of external investment by venture capitalists 25 . However, this is not in and of itself a good measure of clear, incontrovertible success, particularly for early-stage ventures. This is because it reflects investors’ expectations of a startup’s success potential rather than actual business success. Similarly, we considered other measures like revenue growth 26 , liquidity events 27 , 28 , 29 , profitability 30 and social impact 31 , all of which have benefits as they capture incremental success, but each also comes with operational measurement challenges.

Therefore, we apply the success definition initially introduced by Bonaventura et al. 32 , namely that a startup is acquired, acquires another company or has an initial public offering (IPO). We consider any of these major capital liquidation events as a clear threshold signal that the company has matured from an early-stage venture to becoming or is on its way to becoming a mature company with clear and often significant business growth prospects. Together these three major liquidity events capture the primary forms of exit for external investors (an acquisition or trade sale and an IPO). For companies with a longer autonomous growth runway, acquiring another company marks a similar milestone of scale, maturity and capability.

Using multifactor analysis and a binary classification prediction model of startup success, we looked at many variables together and their relative influence on the probability of the success of startups. We looked at seven categories of factors through three lenses of firm-level factors: (1) location, (2) industry, (3) age of the startup; founder-level factors: (4) number of founders, (5) gender of founders, (6) personality characteristics of founders and; lastly team-level factors: (7) founder-team personality combinations. The model performance and relative impacts on the probability of startup success of each of these categories of founders are illustrated in more detail in section  A.6 of the Supplementary Information (in particular Extended Data Fig.  19 and Extended Data Fig.  20 ). In total, we considered over three hundred variables (n = 323) and their relative significant associations with success.

The personality of founders

Besides product-market, industry, and firm-level factors (see SI section  A.1 ), research suggests that the personalities of founders play a crucial role in startup success 19 . Therefore, we examine the personality characteristics of individual startup founders and teams of founders in relationship to their firm’s success by applying the success definition used by Bonaventura et al. 32 .

Employing established methods 33 , 34 , 35 , we inferred the personality traits across 30 dimensions (Big Five facets) of a large global sample of startup founders. The startup founders cohort was created from a subset of founders from the global startup industry directory Crunchbase, who are also active on the social media platform Twitter.

To measure the personality of the founders, we used the Big Five, a popular model of personality which includes five core traits: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Emotional stability. Each of these traits can be further broken down into thirty distinct facets. Studies have found that the Big Five predict meaningful life outcomes, such as physical and mental health, longevity, social relationships, health-related behaviours, antisocial behaviour, and social contribution, at levels on par with intelligence and socioeconomic status 36 Using machine learning to infer personality traits by analysing the use of language and activity on social media has been shown to be more accurate than predictions of coworkers, friends and family and similar in accuracy to the judgement of spouses 37 . Further, as other research has shown, we assume that personality traits remain stable in adulthood even through significant life events 38 , 39 , 40 . Personality traits have been shown to emerge continuously from those already evident in adolescence 41 and are not significantly influenced by external life events such as becoming divorced or unemployed 42 . This suggests that the direction of any measurable effect goes from founder personalities to startup success and not vice versa.

As a first investigation to what extent personality traits might relate to entrepreneurship, we use the personality characteristics of individuals to predict whether they were an entrepreneur or an employee. We trained and tested a machine-learning random forest classifier to distinguish and classify entrepreneurs from employees and vice-versa using inferred personality vectors alone. As a result, we found we could correctly predict entrepreneurs with 77% accuracy and employees with 88% accuracy (Fig.  1 A). Thus, based on personality information alone, we correctly predict all unseen new samples with 82.5% accuracy (See SI section  A.2 for more details on this analysis, the classification modelling and prediction accuracy).

We explored in greater detail which personality features are most prominent among entrepreneurs. We found that the subdomain or facet of Adventurousness within the Big Five Domain of Openness was significant and had the largest effect size. The facet of Modesty within the Big Five Domain of Agreeableness and Activity Level within the Big Five Domain of Extraversion was the subsequent most considerable effect (Fig.  1 B). Adventurousness in the Big Five framework is defined as the preference for variety, novelty and starting new things—which are consistent with the role of a startup founder whose role, especially in the early life of the company, is to explore things that do not scale easily 43 and is about developing and testing new products, services and business models with the market.

Once we derived and tested the Big Five personality features for each entrepreneur in our data set, we examined whether there is evidence indicating that startup founders naturally cluster according to their personality features using a Hopkins test (see Extended Data Figure  6 ). We discovered clear clustering tendencies in the data compared with other renowned reference data sets known to have clusters. Then, once we established the founder data clusters, we used agglomerative hierarchical clustering. This ‘bottom-up’ clustering technique initially treats each observation as an individual cluster. Then it merges them to create a hierarchy of possible cluster schemes with differing numbers of groups (See Extended Data Fig.  7 ). And lastly, we identified the optimum number of clusters based on the outcome of four different clustering performance measurements: Davies-Bouldin Index, Silhouette coefficients, Calinski-Harabas Index and Dunn Index (see Extended Data Figure  8 ). We find that the optimum number of clusters of startup founders based on their personality features is six (labelled #0 through to #5), as shown in Fig.  1 C.

To better understand the context of different founder types, we positioned each of the six types of founders within an occupation-personality matrix established from previous research 44 . This research showed that ‘each job has its own personality’ using a substantial sample of employees across various jobs. Utilising the methodology employed in this study, we assigned labels to the cluster names #0 to #5, which correspond to the identified occupation tribes that best describe the personality facets represented by the clusters (see Extended Data Fig.  9 for an overview of these tribes, as identified by McCarthy et al. 44 ).

Utilising this approach, we identify three ’purebred’ clusters: #0, #2 and #5, whose members are dominated by a single tribe (larger than 60% of all individuals in each cluster are characterised by one tribe). Thus, these clusters represent and share personality attributes of these previously identified occupation-personality tribes 44 , which have the following known distinctive personality attributes (see also Table  1 ):

Accomplishers (#0) —Organised & outgoing. confident, down-to-earth, content, accommodating, mild-tempered & self-assured.

Leaders (#2) —Adventurous, persistent, dispassionate, assertive, self-controlled, calm under pressure, philosophical, excitement-seeking & confident.

Fighters (#5) —Spontaneous and impulsive, tough, sceptical, and uncompromising.

We labelled these clusters with the tribe names, acknowledging that labels are somewhat arbitrary, based on our best interpretation of the data (See SI section  A.3 for more details).

For the remaining three clusters #1, #3 and #4, we can see they are ‘hybrids’, meaning that the founders within them come from a mix of different tribes, with no one tribe representing more than 50% of the members of that cluster. However, the tribes with the largest share were noted as #1 Experts/Engineers, #3 Fighters, and #4 Operators.

To label these three hybrid clusters, we examined the closest occupations to the median personality features of each cluster. We selected a name that reflected the common themes of these occupations, namely:

Experts/Engineers (#1) as the closest roles included Materials Engineers and Chemical Engineers. This is consistent with this cluster’s personality footprint, which is highest in openness in the facets of imagination and intellect.

Developers (#3) as the closest roles include Application Developers and related technology roles such as Business Systems Analysts and Product Managers.

Operators (#4) as the closest roles include service, maintenance and operations functions, including Bicycle Mechanic, Mechanic and Service Manager. This is also consistent with one of the key personality traits of high conscientiousness in the facet of orderliness and high agreeableness in the facet of humility for founders in this cluster.

Founder-Level Factors of Startup Success. ( A ), Successful entrepreneurs differ from successful employees. They can be accurately distinguished using a classifier with personality information alone. ( B ), Successful entrepreneurs have different Big Five facet distributions, especially on adventurousness, modesty and activity level. ( C ), Founders come in six different types: Fighters, Operators, Accomplishers, Leaders, Engineers and Developers (FOALED) ( D ), Each founder Personality-Type has its distinct facet.

Together, these six different types of startup founders (Fig.  1 C) represent a framework we call the FOALED model of founder types—an acronym of Fighters, Operators, Accomplishers, Leaders, Engineers and D evelopers.

Each founder’s personality type has its distinct facet footprint (for more details, see Extended Data Figure  10 in SI section  A.3 ). Also, we observe a central core of correlated features that are high for all types of entrepreneurs, including intellect, adventurousness and activity level (Fig.  1 D).To test the robustness of the clustering of the personality facets, we compare the mean scores of the individual facets per cluster with a 20-fold resampling of the data and find that the clusters are, overall, largely robust against resampling (see Extended Data Figure  11 in SI section  A.3 for more details).

We also find that the clusters accord with the distribution of founders’ roles in their startups. For example, Accomplishers are often Chief Executive Officers, Chief Financial Officers, or Chief Operating Officers, while Fighters tend to be Chief Technical Officers, Chief Product Officers, or Chief Commercial Officers (see Extended Data Fig.  12 in SI section  A.4 for more details).

The ensemble theory of success

While founders’ individual personality traits, such as Adventurousness or Openness, show to be related to their firms’ success, we also hypothesise that the combination, or ensemble, of personality characteristics of a founding team impacts the chances of success. The logic behind this reasoning is complementarity, which is proposed by contemporary research on the functional roles of founder teams. Examples of these clear functional roles have evolved in established industries such as film and television, construction, and advertising 45 . When we subsequently explored the combinations of personality types among founders and their relationship to the probability of startup success, adjusted for a range of other factors in a multi-factorial analysis, we found significantly increased chances of success for mixed foundation teams:

Initially, we find that firms with multiple founders are more likely to succeed, as illustrated in Fig.  2 A, which shows firms with three or more founders are more than twice as likely to succeed than solo-founded startups. This finding is consistent with investors’ advice to founders and previous studies 46 . We also noted that some personality types of founders increase the probability of success more than others, as shown in SI section  A.6 (Extended Data Figures  16 and 17 ). Also, we note that gender differences play out in the distribution of personality facets: successful female founders and successful male founders show facet scores that are more similar to each other than are non-successful female founders to non-successful male founders (see Extended Data Figure  18 ).

The Ensemble Theory of Team-Level Factors of Startup Success. ( A ) Having a larger founder team elevates the chances of success. This can be due to multiple reasons, e.g., a more extensive network or knowledge base but also personality diversity. ( B ) We show that joint personality combinations of founders are significantly related to higher chances of success. This is because it takes more than one founder to cover all beneficial personality traits that ‘breed’ success. ( C ) In our multifactor model, we show that firms with diverse and specific combinations of types of founders have significantly higher odds of success.

Access to more extensive networks and capital could explain the benefits of having more founders. Still, as we find here, it also offers a greater diversity of combined personalities, naturally providing a broader range of maximum traits. So, for example, one founder may be more open and adventurous, and another could be highly agreeable and trustworthy, thus, potentially complementing each other’s particular strengths associated with startup success.

The benefits of larger and more personality-diverse foundation teams can be seen in the apparent differences between successful and unsuccessful firms based on their combined Big Five personality team footprints, as illustrated in Fig.  2 B. Here, maximum values for each Big Five trait of a startup’s co-founders are mapped; stratified by successful and non-successful companies. Founder teams of successful startups tend to score higher on Openness, Conscientiousness, Extraversion, and Agreeableness.

When examining the combinations of founders with different personality types, we find that some ensembles of personalities were significantly correlated with greater chances of startup success—while controlling for other variables in the model—as shown in Fig.  2 C (for more details on the modelling, the predictive performance and the coefficient estimates of the final model, see Extended Data Figures  19 , 20 , and 21 in SI section  A.6 ).

Three combinations of trio-founder companies were more than twice as likely to succeed than other combinations, namely teams with (1) a Leader and two Developers , (2) an Operator and two Developers , and (3) an Expert/Engineer , Leader and Developer . To illustrate the potential mechanisms on how personality traits might influence the success of startups, we provide some examples of well-known, successful startup founders and their characteristic personality traits in Extended Data Figure  22 .

Startups are one of the key mechanisms for brilliant ideas to become solutions to some of the world’s most challenging economic and social problems. Examples include the Google search algorithm, disability technology startup Fingerwork’s touchscreen technology that became the basis of the Apple iPhone, or the Biontech mRNA technology that powered Pfizer’s COVID-19 vaccine.

We have shown that founders’ personalities and the combination of personalities in the founding team of a startup have a material and significant impact on its likelihood of success. We have also shown that successful startup founders’ personality traits are significantly different from those of successful employees—so much so that a simple predictor can be trained to distinguish between employees and entrepreneurs with more than 80% accuracy using personality trait data alone.

Just as occupation-personality maps derived from data can provide career guidance tools, so too can data on successful entrepreneurs’ personality traits help people decide whether becoming a founder may be a good choice for them.

We have learnt through this research that there is not one type of ideal ’entrepreneurial’ personality but six different types. Many successful startups have multiple co-founders with a combination of these different personality types.

To a large extent, founding a startup is a team sport; therefore, diversity and complementarity of personalities matter in the foundation team. It has an outsized impact on the company’s likelihood of success. While all startups are high risk, the risk becomes lower with more founders, particularly if they have distinct personality traits.

Our work demonstrates the benefits of personality diversity among the founding team of startups. Greater awareness of this novel form of diversity may help create more resilient startups capable of more significant innovation and impact.

The data-driven research approach presented here comes with certain methodological limitations. The principal data sources of this study—Crunchbase and Twitter—are extensive and comprehensive, but there are characterised by some known and likely sample biases.

Crunchbase is the principal public chronicle of venture capital funding. So, there is some likely sample bias toward: (1) Startup companies that are funded externally: self-funded or bootstrapped companies are less likely to be represented in Crunchbase; (2) technology companies, as that is Crunchbase’s roots; (3) multi-founder companies; (4) male founders: while the representation of female founders is now double that of the mid-2000s, women still represent less than 25% of the sample; (5) companies that succeed: companies that fail, especially those that fail early, are likely to be less represented in the data.

Samples were also limited to those founders who are active on Twitter, which adds additional selection biases. For example, Twitter users typically are younger, more educated and have a higher median income 47 . Another limitation of our approach is the potentially biased presentation of a person’s digital identity on social media, which is the basis for identifying personality traits. For example, recent research suggests that the language and emotional tone used by entrepreneurs in social media can be affected by events such as business failure 48 , which might complicate the personality trait inference.

In addition to sampling biases within the data, there are also significant historical biases in startup culture. For many aspects of the entrepreneurship ecosystem, women, for example, are at a disadvantage 49 . Male-founded companies have historically dominated most startup ecosystems worldwide, representing the majority of founders and the overwhelming majority of venture capital investors. As a result, startups with women have historically attracted significantly fewer funds 50 , in part due to the male bias among venture investors, although this is now changing, albeit slowly 51 .

The research presented here provides quantitative evidence for the relevance of personality types and the diversity of personalities in startups. At the same time, it brings up other questions on how personality traits are related to other factors associated with success, such as:

Will the recent growing focus on promoting and investing in female founders change the nature, composition and dynamics of startups and their personalities leading to a more diverse personality landscape in startups?

Will the growth of startups outside of the United States change what success looks like to investors and hence the role of different personality traits and their association to diverse success metrics?

Many of today’s most renowned entrepreneurs are either Baby Boomers (such as Gates, Branson, Bloomberg) or Generation Xers (such as Benioff, Cannon-Brookes, Musk). However, as we can see, personality is both a predictor and driver of success in entrepreneurship. Will generation-wide differences in personality and outlook affect startups and their success?

Moreover, the findings shown here have natural extensions and applications beyond startups, such as for new projects within large established companies. While not technically startups, many large enterprises and industries such as construction, engineering and the film industry rely on forming new project-based, cross-functional teams that are often new ventures and share many characteristics of startups.

There is also potential for extending this research in other settings in government, NGOs, and within the research community. In scientific research, for example, team diversity in terms of age, ethnicity and gender has been shown to be predictive of impact, and personality diversity may be another critical dimension 52 .

Another extension of the study could investigate the development of the language used by startup founders on social media over time. Such an extension could investigate whether the language (and inferred psychological characteristics) change as the entrepreneurs’ ventures go through major business events such as foundation, funding, or exit.

Overall, this study demonstrates, first, that startup founders have significantly different personalities than employees. Secondly, besides firm-level factors, which are known to influence firm success, we show that a range of founder-level factors, notably the character traits of its founders, significantly impact a startup’s likelihood of success. Lastly, we looked at team-level factors. We discovered in a multifactor analysis that personality-diverse teams have the most considerable impact on the probability of a startup’s success, underlining the importance of personality diversity as a relevant factor of team performance and success.

Data sources

Entrepreneurs dataset.

Data about the founders of startups were collected from Crunchbase (Table  2 ), an open reference platform for business information about private and public companies, primarily early-stage startups. It is one of the largest and most comprehensive data sets of its kind and has been used in over 100 peer-reviewed research articles about economic and managerial research.

Crunchbase contains data on over two million companies - mainly startup companies and the companies who partner with them, acquire them and invest in them, as well as profiles on well over one million individuals active in the entrepreneurial ecosystem worldwide from over 200 countries and spans. Crunchbase started in the technology startup space, and it now covers all sectors, specifically focusing on entrepreneurship, investment and high-growth companies.

While Crunchbase contains data on over one million individuals in the entrepreneurial ecosystem, some are not entrepreneurs or startup founders but play other roles, such as investors, lawyers or executives at companies that acquire startups. To create a subset of only entrepreneurs, we selected a subset of 32,732 who self-identify as founders and co-founders (by job title) and who are also publicly active on the social media platform Twitter. We also removed those who also are venture capitalists to distinguish between investors and founders.

We selected founders active on Twitter to be able to use natural language processing to infer their Big Five personality features using an open-vocabulary approach shown to be accurate in the previous research by analysing users’ unstructured text, such as Twitter posts in our case. For this project, as with previous research 20 , we employed a commercial service, IBM Watson Personality Insight, to infer personality facets. This service provides raw scores and percentile scores of Big Five Domains (Openness, Conscientiousness, Extraversion, Agreeableness and Emotional Stability) and the corresponding 30 subdomains or facets. In addition, the public content of Twitter posts was collected, and there are 32,732 profiles that each had enough Twitter posts (more than 150 words) to get relatively accurate personality scores (less than 12.7% Average Mean Absolute Error).

The entrepreneurs’ dataset is analysed in combination with other data about the companies they founded to explore questions about the nature and patterns of personality traits of entrepreneurs and the relationships between these patterns and company success.

For the multifactor analysis, we further filtered the data in several preparatory steps for the success prediction modelling (for more details, see SI section  A.5 ). In particular, we removed data points with missing values (Extended Data Fig.  13 ) and kept only companies in the data that were founded from 1990 onward to ensure consistency with previous research 32 (see Extended Data Fig.  14 ). After cleaning, filtering and pre-processing the data, we ended up with data from 25,214 founders who founded 21,187 startup companies to be used in the multifactor analysis. Of those, 3442 startups in the data were successful, 2362 in the first seven years after they were founded (see Extended Data Figure  15 for more details).

Entrepreneurs and employees dataset

To investigate whether startup founders show personality traits that are similar or different from the population at large (i. e. the entrepreneurs vs employees sub-analysis shown in Fig.  1 A and B), we filtered the entrepreneurs’ data further: we reduced the sample to those founders of companies, which attracted more than US$100k in investment to create a reference set of successful entrepreneurs (n \(=\) 4400).

To create a control group of employees who are not also entrepreneurs or very unlikely to be of have been entrepreneurs, we leveraged the fact that while some occupational titles like CEO, CTO and Public Speaker are commonly shared by founders and co-founders, some others such as Cashier , Zoologist and Detective very rarely co-occur seem to be founders or co-founders. To illustrate, many company founders also adopt regular occupation titles such as CEO or CTO. Many founders will be Founder and CEO or Co-founder and CTO. While founders are often CEOs or CTOs, the reverse is not necessarily true, as many CEOs are professional executives that were not involved in the establishment or ownership of the firm.

Using data from LinkedIn, we created an Entrepreneurial Occupation Index (EOI) based on the ratio of entrepreneurs for each of the 624 occupations used in a previous study of occupation-personality fit 44 . It was calculated based on the percentage of all people working in the occupation from LinkedIn compared to those who shared the title Founder or Co-founder (See SI section  A.2 for more details). A reference set of employees (n=6685) was then selected across the 112 different occupations with the lowest propensity for entrepreneurship (less than 0.5% EOI) from a large corpus of Twitter users with known occupations, which is also drawn from the previous occupational-personality fit study 44 .

These two data sets were used to test whether it may be possible to distinguish successful entrepreneurs from successful employees based on the different patterns of personality traits alone.

Hierarchical clustering

We applied several clustering techniques and tests to the personality vectors of the entrepreneurs’ data set to determine if there are natural clusters and, if so, how many are the optimum number.

Firstly, to determine if there is a natural typology to founder personalities, we applied the Hopkins statistic—a statistical test we used to answer whether the entrepreneurs’ dataset contains inherent clusters. It measures the clustering tendency based on the ratio of the sum of distances of real points within a sample of the entrepreneurs’ dataset to their nearest neighbours and the sum of distances of randomly selected artificial points from a simulated uniform distribution to their nearest neighbours in the real entrepreneurs’ dataset. The ratio measures the difference between the entrepreneurs’ data distribution and the simulated uniform distribution, which tests the randomness of the data. The range of Hopkins statistics is from 0 to 1. The scores are close to 0, 0.5 and 1, respectively, indicating whether the dataset is uniformly distributed, randomly distributed or highly clustered.

To cluster the founders by personality facets, we used Agglomerative Hierarchical Clustering (AHC)—a bottom-up approach that treats an individual data point as a singleton cluster and then iteratively merges pairs of clusters until all data points are included in the single big collection. Ward’s linkage method is used to choose the pair of groups for minimising the increase in the within-cluster variance after combining. AHC was widely applied to clustering analysis since a tree hierarchy output is more informative and interpretable than K-means. Dendrograms were used to visualise the hierarchy to provide the perspective of the optimal number of clusters. The heights of the dendrogram represent the distance between groups, with lower heights representing more similar groups of observations. A horizontal line through the dendrogram was drawn to distinguish the number of significantly different clusters with higher heights. However, as it is not possible to determine the optimum number of clusters from the dendrogram, we applied other clustering performance metrics to analyse the optimal number of groups.

A range of Clustering performance metrics were used to help determine the optimal number of clusters in the dataset after an apparent clustering tendency was confirmed. The following metrics were implemented to evaluate the differences between within-cluster and between-cluster distances comprehensively: Dunn Index, Calinski-Harabasz Index, Davies-Bouldin Index and Silhouette Index. The Dunn Index measures the ratio of the minimum inter-cluster separation and the maximum intra-cluster diameter. At the same time, the Calinski-Harabasz Index improves the measurement of the Dunn Index by calculating the ratio of the average sum of squared dispersion of inter-cluster and intra-cluster. The Davies-Bouldin Index simplifies the process by treating each cluster individually. It compares the sum of the average distance among intra-cluster data points to the cluster centre of two separate groups with the distance between their centre points. Finally, the Silhouette Index is the overall average of the silhouette coefficients for each sample. The coefficient measures the similarity of the data point to its cluster compared with the other groups. Higher scores of the Dunn, Calinski-Harabasz and Silhouette Index and a lower score of the Davies-Bouldin Index indicate better clustering configuration.

Classification modelling

Classification algorithms.

To obtain a comprehensive and robust conclusion in the analysis predicting whether a given set of personality traits corresponds to an entrepreneur or an employee, we explored the following classifiers: Naïve Bayes, Elastic Net regularisation, Support Vector Machine, Random Forest, Gradient Boosting and Stacked Ensemble. The Naïve Bayes classifier is a probabilistic algorithm based on Bayes’ theorem with assumptions of independent features and equiprobable classes. Compared with other more complex classifiers, it saves computing time for large datasets and performs better if the assumptions hold. However, in the real world, those assumptions are generally violated. Elastic Net regularisation combines the penalties of Lasso and Ridge to regularise the Logistic classifier. It eliminates the limitation of multicollinearity in the Lasso method and improves the limitation of feature selection in the Ridge method. Even though Elastic Net is as simple as the Naïve Bayes classifier, it is more time-consuming. The Support Vector Machine (SVM) aims to find the ideal line or hyperplane to separate successful entrepreneurs and employees in this study. The dividing line can be non-linear based on a non-linear kernel, such as the Radial Basis Function Kernel. Therefore, it performs well on high-dimensional data while the ’right’ kernel selection needs to be tuned. Random Forest (RF) and Gradient Boosting Trees (GBT) are ensembles of decision trees. All trees are trained independently and simultaneously in RF, while a new tree is trained each time and corrected by previously trained trees in GBT. RF is a more robust and straightforward model since it does not have many hyperparameters to tune. GBT optimises the objective function and learns a more accurate model since there is a successive learning and correction process. Stacked Ensemble combines all existing classifiers through a Logistic Regression. Better than bagging with only variance reduction and boosting with only bias reduction, the ensemble leverages the benefit of model diversity with both lower variance and bias. All the above classification algorithms distinguish successful entrepreneurs and employees based on the personality matrix.

Evaluation metrics

A range of evaluation metrics comprehensively explains the performance of a classification prediction. The most straightforward metric is accuracy, which measures the overall portion of correct predictions. It will mislead the performance of an imbalanced dataset. The F1 score is better than accuracy by combining precision and recall and considering the False Negatives and False Positives. Specificity measures the proportion of detecting the true negative rate that correctly identifies employees, while Positive Predictive Value (PPV) calculates the probability of accurately predicting successful entrepreneurs. Area Under the Receiver Operating Characteristic Curve (AUROC) determines the capability of the algorithm to distinguish between successful entrepreneurs and employees. A higher value means the classifier performs better on separating the classes.

Feature importance

To further understand and interpret the classifier, it is critical to identify variables with significant predictive power on the target. Feature importance of tree-based models measures Gini importance scores for all predictors, which evaluate the overall impact of the model after cutting off the specific feature. The measurements consider all interactions among features. However, it does not provide insights into the directions of impacts since the importance only indicates the ability to distinguish different classes.

Statistical analysis

T-test, Cohen’s D and two-sample Kolmogorov-Smirnov test are introduced to explore how the mean values and distributions of personality facets between entrepreneurs and employees differ. The T-test is applied to determine whether the mean of personality facets of two group samples are significantly different from one another or not. The facets with significant differences detected by the hypothesis testing are critical to separate the two groups. Cohen’s d is to measure the effect size of the results of the previous t-test, which is the ratio of the mean difference to the pooled standard deviation. A larger Cohen’s d score indicates that the mean difference is greater than the variability of the whole sample. Moreover, it is interesting to check whether the two groups’ personality facets’ probability distributions are from the same distribution through the two-sample Kolmogorov-Smirnov test. There is no assumption about the distributions, but the test is sensitive to deviations near the centre rather than the tail.

Privacy and ethics

The focus of this research is to provide high-level insights about groups of startups, founders and types of founder teams rather than on specific individuals or companies. While we used unit record data from the publicly available data of company profiles from Crunchbase , we removed all identifiers from the underlying data on individual companies and founders and generated aggregate results, which formed the basis for our analysis and conclusions.

Data availability

A dataset which includes only aggregated statistics about the success of startups and the factors that influence is released as part of this research. Underlying data for all figures and the code to reproduce them are available on GitHub: https://github.com/Braesemann/FounderPersonalities . Please contact Fabian Braesemann ( [email protected] ) in case you have any further questions.

Change history

07 may 2024.

A Correction to this paper has been published: https://doi.org/10.1038/s41598-024-61082-7

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Acknowledgements

We thank Gary Brewer from BuiltWith ; Leni Mayo from Influx , Rachel Slattery from TeamSlatts and Daniel Petre from AirTree Ventures for their ongoing generosity and insights about startups, founders and venture investments. We also thank Tim Li from Crunchbase for advice and liaison regarding data on startups and Richard Slatter for advice and referrals in Twitter .

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All authors designed research; All authors analysed data and undertook investigation; F.B. and F.S. led multi-factor analysis; P.M., X.G. and M.A.R. led the founder/employee prediction; M.L.K. led personality insights; X.G. collected and tabulated the data; X.G., F.B., and F.S. created figures; X.G. created final art, and all authors wrote the paper.

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Relational aggression in romantic relationship: empirical evidence among young female adults in Malaysia

• Mohammad Rahim Kamaluddin 2 ,
• Shalini Munusamy 1 ,
• Chong Sheau Tsuey 2 &
• Hilwa Abdullah & Mohd Nor 2  

BMC Psychology volume  12 , Article number:  305 ( 2024 ) Cite this article

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Aggressive behaviour in romantic relationship is a social problem of great concern. Studies related to the influence of psychosocial factors on relational aggression are still limited. Furthermore, these factors have not been widely studied in the local context, resulting in the issue of relational aggression among young female adults still not being addressed. This study aims to explore whether psychosocial factors such as big five personality traits, adult attachment style and loneliness could predict relational aggression in romantic relationships among young female adults in Malaysia. In addition, this study aims to identify the moderating effect of social support in the relationship between psychosocial factors and relational aggression in romantic relationship.

A quantitative research approach was used with 424 young female adults in Malaysia aged between 18 and 30 years old (mean age = 24.18) were recruited through multistage sampling design by completing a questionnaire consisting of the Big Five Inventory (BFI), Experiences in Close Relationships Scale II (ECRS-II), Revised UCLA Loneliness Scale, Measure of Relational Aggression and Victimization (MRAV) and Multidimensional Scale of Perceived Social Support (MSPSS).

Multiple regression analysis predicted significant relationship between agreeableness personality, loneliness, avoidant attachment style and anxious attachment style with relational aggression in romantic relationships. Hierarchical regression analysis found a significant effect of social support as a moderator between loneliness with relational aggression in romantic relationships.

Conclusions

Thus, the results show that young female adults with low level of agreeableness, high level of loneliness, avoidant attachment style and anxious attachment style are at a higher risk of engaging in relational aggression in romantic relationships. The implication of this study can help in understanding the psychosocial factors that form the basis of relational aggression in romantic relationships. Hence, the gap in knowledge warrants further research.

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The development of romantic relationships among early adulthood is crucial in forming views about intimate relationships and exhibiting intimacy, power, and control [ 1 ]. Emerging adulthood is a key developmental stage for creating a healthy romantic relationship. Some romantic relationships involve aggressive behaviour between partners, which can manifest in various forms such as physical, non-physical, direct, or indirect aggression, overt or covert aggression [ 2 ]. Aggressive behaviour is a criminogenic trait linked to various violent crimes including dating violence [ 3 ]. Physical aggression involves intentionally using physical force to hurt the partner, ranging from mild actions like pushing to severe violence like choking, slapping or weapon use [ 4 ]. Emotional abuse is also a common form of abuse in romantic relationships [ 5 ]. The online dating scam is another alarming form of dating violence that can result in financial loss and severe emotional and psychological suffering ( 6 – 7 ). Relational aggression is a form of non-physical and covert aggression, involves threatening others by manipulating and acting to jeopardize romantic relationships [ 8 ]. Unlike physical aggression, relational aggression occurs without any physical force or physically threatening the individual and can be considered a type of psychological aggression, targeting perceptions, feelings, or behaviour in romantic relationship [ 9 ]. Relational aggression can be indirect, such as through negative facial expressions or spreading rumors about a partner. While there has been extensive research on physical aggression and violence in romantic relationships [ 10 , 11 , 12 ], there is relatively less research on relational aggression in romantic relationships.

Relational aggression in romantic relationships might appear as threats to end the relationship if the other person doesn’t cooperate, flirting with other people to make the other person envious, or treating the other person silently while upset [ 9 ]. In terms of relational aggression, females who utilized high levels of relational aggression had a strong tendency to see other people’s acts as hostile and malevolent, whereas males did not [ 13 ]. Examining relational aggression and its relationship with adaptive functioning in females may shed light on the critical mechanisms involved in females’ dating violence. In this study, we hope to study the psychosocial factors most related with relational aggression in females by looking at components known to relate to aggression in females, such as individual characteristics and environmental factors. There is little evidence from research on female gender to differentiate the experience of relational aggression in romantic relationships, female perpetrators will be the greatest risk of this aggressive behaviour and young female adults may experience greater psychological stress than men ( 13 – 14 ). Therefore, this study focuses only on female samples and will be done using Malaysian samples. Despite research, little is known about how relational aggression originate, persist, and have an impact on romantic relationships, including whether men and women experience these issues differently ( 13 – 14 ). Romantic relational aggression has also been linked to relationship quality, violence, psychosocial maladjustment, impulsivity, hostile attribution biases, loneliness, emotional sensitivity to relational incitements, and abuse history [ 13 ].

In addition, this study emphasizes the psychosocial aspect of a person that can cause the tendency to behave aggressively in romantic relationships. It is important to identify the psychosocial aspects of a person who tends to engage in relational aggression in romantic relationships. The link between relational aggression and psychosocial factors such as loneliness, attachment styles, and personality type has been established ( 15 – 16 ). Personality traits of aggressors have been known to be associated with dating violence ( 15 – 16 ). This study used the “Big Five” personality model (extraversion, agreeableness, openness, conscientiousness, and neuroticism) as one of the psychosocial factors. Each main trait from this model can be divided into several aspects to provide a more detailed analysis of a person’s personality. Several theorists argue that personality variable is an important predictor of aggressive behaviour in romantic relationship [ 17 , 18 , 19 ]. Agreeableness dimensions are often associated with aggressive behaviour [ 18 , 20 , 21 ]. Besides that, a study conducted by Ulloa et al. (2016) found individuals with a high neuroticism personality tend to be victims in relational aggression during intimate relationships [ 22 ]. The findings of this study are also supported by other research that neuroticism trait as the main personality trait that gives a strong influence on relational aggression ( 23 – 24 ).

In addition to personality traits, other factors such as the level of loneliness are also considered to be a strong predictive factor of relational aggression especially the tendency to be a victim [ 25 ]. Generally, loneliness can be associated with individuals having a lack of social support as well as showing no interest in social networks [ 25 ]. Many studies have linked aggressive behaviour with loneliness [ 26 , 27 , 28 ]. Loneliness is defined as a negative emotional response to the discrepancy between the desired and achieved quality of one’s social network [ 27 ]. In addition, relational aggression is caused by the loneliness faced by an individual [ 28 ]. Individuals who are lonely describe themselves negatively and have negative ideas about others. As a result, loneliness leads to a bad perception of oneself, such as being unwanted and unaccepted by others, and it leads to aggression, which is a means of using force to influence other people in interpersonal relationships [ 29 ]. Individuals with high level of loneliness are at high risk of engaging in relational aggression in romantic relationship ( 30 – 31 ). Another psychosocial aspect often associated with relational aggression is attachment style. Attachment style is said to be able to shape the probability of an individual being involved in incidents of relational aggression in romantic relationship.

An expanding corpus of research has highlighted attachment theory as a crucial paradigm for comprehending emotional and interpersonal processes that take place across the lifespan [ 32 , 33 , 34 ]. The foundation of attachment theory is the idea of an attachment behavioural system, in which attachment actions are grouped together to strengthen a particular attachment figure. A sense of personal security within the relationship can be established or maintained by intimate partner violence, according to the attachment theory. People feel startled when they sense a threat to their attachment connection, and the ensuing anxiety causes them to act in ways that protect their attachment system [ 35 ]. Individuals with different attachment style also have an influence strongly to the involvement of individuals in the occurrence of aggression ( 36 – 37 ). Besides that, individuals with avoidant attachment shows high relational aggression in romantic relationship ( 38 – 39 ). Besides that, individuals who often exhibit anxious attachment to their partners such as fear of rejection and dependency on their partner are more likely to experience relational aggression in romantic relationships ( 40 – 41 ).

The potentially moderating role of Social Support

In relation to that, social support is used as a moderator based on previous literature studies [ 42 , 43 , 44 ]. Social support is also defined as interpersonal relationships and support provided by social groups that aim to provide well-being to individuals [ 42 ]. Social support from family and friends is important in contributing to positive psychological health among early adulthood and influences the act of aggressive behaviour [ 45 ]. Previous studies have shown that social support has a significant relationship with big personality traits, especially with extraversion and agreeableness [ 45 , 46 , 47 , 48 , 49 ]. In addition, a few studies also found that family members with agreeableness trait also provide more social support [ 46 , 47 , 48 ]. Besides that, people who experience loneliness interact less with friends and family than people who do not feel lonely. In other words, the less social support a person has, the higher the level of loneliness [ 50 ]. According to earlier research, there have been negative association between relational aggression and social support as well positive association between relational aggression and psychosocial maladjustment during major developmental stages including childhood, adolescence, and young adulthood [ 51 , 52 , 53 ].

According to research, individuals with little social support from their parents were more likely to engage in verbal, physical, and relational aggression [ 54 ] whereas individuals who reported high perceived social support from peers were less likely to engage in overt and relational aggression [ 55 ]. Besides that, individuals who have supporting friends and family have lower relational aggression. Family and peer support can help to mitigate the harmful effects from using relational aggression behaviour in their romantic relationship. Adults with high levels of social support outperformed those with low levels of family and peer support in exhibiting relational aggression behaviour in romantic relationships [ 56 ]. Although both relational aggression and social support are empirically connected to maladjustment, research on the interaction effect of psychosocial factors and social support on relational aggression is still limited ( 57 – 58 ).

Besides that, a study done in US had found that there is no evidence of social support act as a moderator between psychosocial factors and dating violence [ 59 ]. Only a small amount is allocated in the extent literature to research the triad of the relationship. In accordance with that, this study will further explore to develop an understanding of the role of social support in the association between psychosocial factors and relational aggression. Among several theories of social behaviour, for this study we have used Albert Bandura (1986) social cognitive theory to help provide researchers with a comprehensive framework to understand the factors that may influence aggressive human behaviour. Although Bowlby (1969) prioritized and focused on understanding the nature of caregiver’s relationship with his infant, at the same time he also believed that bonding features are present in human life experience from “cradle to grave” [ 30 ]. Besides that, attachment style and social support combine the theory-based prediction that people with an insecure attachment style are more likely to evaluate others’ reactions negatively [ 60 ].

This study can give awareness to young female adults about the issue of relational aggression that can happen in a romantic relationship. This is because relational aggression is an issue that is not given attention in romantic relationships by women and only aggressive behaviour such as physical and sexual is considered more harmful in romantic relationships. This study can give awareness to young female adults about the characteristics of an individual who practices relational aggression in a romantic relationship and can help in finding a solution from practicing relational aggression in romantic relationship. This study can also help young adults to identify this issue so that it does not continue and affect romantic relationships in adulthood. Relational aggression is known to be a relevant social problem factor which can be a precursor to abusive romantic relationships in later adulthood [ 61 ].

A conceptual framework in this study was built based on the social cognitive theory introduced by Albert Bandura in 1986, attachment theory developed by John Bowlby (1907–1990) and the big five personality theory developed in 1949 by D. W. Fiske (1949) as well as from the findings of research on previous studies in the field of psychosocial factors and relational aggression in romantic relationship. In general, this study aims to explore whether psychosocial factors could predict relational aggression in romantic relationships. There is not much direct research that examines covert set of manipulative behaviors in romantic relationships such as relational aggression. Besides that, there are only a few studies conducted in Malaysia about relational aggression in romantic relationships compared to studies conducted in Western countries [ 53 , 54 , 55 , 60 , 61 , 62 ]. Therefore, it is important to conduct this study using respondents from Malaysia so that it can help psychologists and other parties involved to identify individuals using relational aggression in romantic relationships and from being involved in psychological problems.

The present study

This study was designed to explore whether psychosocial factors such as big five personality traits, attachment style and loneliness could predict relational aggression in romantic relationship among young female adults in Malaysian context and aims to extend findings from previous studies in this field. The researchers hypothesize that psychosocial factors, such as personality trait, attachment styles, and loneliness, will play a significant role in determining the presence and severity of relational aggression in romantic relationships. In addition, it is believed that social support will act as a moderating factor in the relationship between psychosocial factors and relational aggression. As a result, this study aims to shed light on the drivers behind relational aggression in romantic relationships and to better understand the relationship between psychosocial factors and relational aggression. This study is regarded novel because there are no known studies on relational aggression in romantic relationship in the Malaysian context as this will be the first Malaysian study to define the relational aggression in romantic relationship among the sample of young female adults in Malaysia.

Participants

An online survey was conducted with a total of 424 females from early adulthood stage, aged between 18 and 30 years old in Malaysia. According to DOSM (2021), the total population of women in early adulthood in Malaysia is 15,758.2(‘000). From the entire population in each state, the respondents aged between 18 and 30 were selected in this study using Raosoft formula. Proportionate stratified random sampling was used to recruit respondents from 13 states in Malaysia to get sufficient sample size from each state through Raosoft formula calculation in July 2022. Then, convenience sampling was used to select a study sample from the population to get a sufficient sample from each state where an advertisement was posted in social media. Inclusion criteria: [ 1 ] participants must be Malaysian; [ 2 ] female participants aged between 18 to 30 years old only; [ 3 ] currently in a romantic relationship for more than 3 months; [ 4 ] must answer all questions in relation to the most recent partner or romantic relationship; [ 5 ] informed and voluntary participation in the study. The study sample for this research consists of different races, occupation, and education background so that they will have equal opportunity to be selected as a respondent.

Instruments

Big five inventory (bfi).

The Malay version of Big Five Inventory (BFI; 63) which was developed by Muhammad et al., [ 63 ] was used to measure the five basic personality dimensions, namely extraversion, agreeableness, conscientiousness, openness, and neuroticism. The 44-item BFI is rated on a 5-point Likert Scale from 1 (strongly disagree) to 5 (strongly agree). After reverse scoring, the mean score of each subscale is obtained. The Malay version of the BFI shows good internal consistency, convergent and discriminant validity [ 63 ]. The internal reliability of this scale in the current study was high, with a Cronbach’s alpha calculation of 0.78 to 0.88 with a mean of 0.81.

UCLA loneliness scale-3

The Malay version of the Rusell’s [ 64 ] UCLA Loneliness Scale [ 65 ] was used to measure loneliness. This tool consists of 20 items and is rated on a 4-point Likert scale from 1 (Never) to 4 (Always). Loneliness was assessed by averaging the scores of all items with higher scores indicating higher levels of loneliness. The internal reliability of this scale in the current study reported with a Cronbach’s alpha of 0.83.

Experiences in close relationships– II (ECR-II)

The Experiences in Close Relationships Scale II (ECRS-II; 67) assessed individual differences in anxious attachment style (i.e., the extent to which individuals feel secure versus insecure about romantic partner relationships and reactions) and avoidant attachment style (i.e., the extent to which individuals feel uncomfortable with having close relationships with others versus feel safe to rely on others). The Malay version of the ECR-II [ 66 ] was used in this study. The internal reliability of this scale in the current study was high, with a Cronbach’s alpha calculation of 0.82 to 0.83 with a mean of 0.83.

Measure of relational aggression and victimization (MRAV)

This instrument was developed by Linder et al. [ 67 ]. This 56-item instrument consists of six subscales that measure six dimensions of aggression, namely relational aggression, physical aggression, relational victimization, physical sacrifice, exclusivity, and prosocial behaviour. For this study, only the subscales of relational aggression (5 items) were used. Items in this tool are rated on a 7-point Likert-type scale from 1 (Not at all True) to 7 (Very True). This questionnaire was translated into Malay language using Forward-Backward translation method and followed by content validation. CVR technique was used to measure the content validity of this questionnaire. The CVR was in the range 0.7-1 for all items and the overall mean CVR values were 0.83. According to Rahim et al. [ 68 ], in the context of measuring psychological test, tools which are available in their own native language will be more appropriate and measurement will be more accurate compared to other languages. The internal reliability of this scale in the current study was high with a Cronbach’s alpha calculation of 0.88 with a mean of 0.89.

Multidimensional scale of perceived social support (MSPSS)

This questionnaire was developed by Zimet et al. [ 69 ] and was used to measure social support of an individual. The MSPSS consists of 12 items assessing three specific sources of social support namely family, friends, and others. This test tool uses a 7-point Likert scale where (1 = strongly disagree, 7 = strongly agree). In this study, the Malay version of the MSPSS tool was used which was translated and validated by Ng et al., [ 70 ]. The internal reliability of this scale in the current study was high, with a Cronbach’s alpha calculation of 0.93.

The survey was conducted from July 1 to July 26, 2022. According to Connelly [ 71 ], previous studies suggest that the sample size of the pilot study should be 10% of the sample size used for the actual study. Therefore, a pilot study was carried out before the real study with 44 respondents in the state of Selangor. The researcher chose Selangor because it is the state where the researcher is currently living, and this will make it easier to carry out the study. In the actual study, 424 participants were recruited based on Table  2 . This study was approved by the Research Ethics Committee of The National University of Malaysia (No: 2022 − 549). All participants were informed of the research objectives and their rights on the first screen (voluntary participation, the right to withdraw at any time and anonymity). This study was not conducted with any minors. At the start of the test, informed permission was acquired, this study only moved forward if the subject ticked the box that said, “Yes, I offer my consent to participate.” The participants’ privacy was guaranteed by the test’s anonymity and the numerical coding of their replies.

Data analysis

Descriptive statistics and inferential statistics were calculated using SPSS 26.0. For inferential statistics multiple regression and hierarchical regression has been used in this study. Multiple regression was used to explore whether psychosocial factors such as big five personality traits, attachment style and loneliness could predict relational aggression in romantic relationship. A single dependent variable and numerous independent variables can be analysed using the statistical method known as multiple regression. The value of R, the multiple correlation coefficient, is shown in the “R” column. The “R Square” column displays the R 2 value, also known as the coefficient of determination, which is the percentage of the dependent variable’s variance that can be explained by the independent variables. R can be thought of as one indicator of the accuracy of the dependent variable’s prediction [ 72 ]. It is the proportion of variation accounted for by the regression model above and beyond the mean model. Hierarchical regression was used to study the effect of social support as a moderator in the relationship between psychosocial factors (personality trait, attachment style and loneliness) with relational aggression in romantic relationship. The moderation effect analysis was carried out using SPSS hierarchical regression. The hierarchical regression is a more appropriate method for determining whether a quantitative variable has a moderating effect on the relationship between two other quantitative variables [ 72 ]. If the moderation test result fell within the 95% confidence interval and contained 0, it meant that the moderation impact of social support was not significant; if it did not, it meant that the moderation effect of social support was substantial. In this study, p  <.05 was regarded as statistically significant. In this study, SPSS 26.0 software were used to analyse the data.

Descriptive statistics

A total of 500 participants have completed the online survey but only 424 (M ± SD = 24.18 ± 3.21 years) participants’ responses were included after 76 questionnaires were rejected from this study as it did not meet the inclusion criteria. The highest level of education obtained by the participants is degree education. 18.2% of participants had engaged in aggression towards their romantic partner.

Inferential statistics

Table  2 shows the results of a multiple regression analysis in predicting relational aggression based on big five personality traits, attachment styles, and loneliness among young female adults in Malaysia. Among the five subscales of personality trait, agreeableness showed a significant predictor. In addition, loneliness, avoidant attachment style, and anxious-attachment style also showed significant prediction with relational aggression. Overall, the results of the regression analysis showed that agreeableness, loneliness, avoidant attachment style, and anxious attachment style together can predict 30.3% of the variance in relational aggression (R²=0.303), where [F (3,269) = 22.561, p  < 0 0.05]. The subscale of agreeableness showed negative prediction (β=-0.305, p  <.05) with relational aggression whereas loneliness (β = 0.364, p  <.05), avoidant attachment style (β = 0.420, p  <.05), and anxious attachment style (β = 0.321, p  <.05) showed positive prediction with relational aggression. These findings showed that higher level of agreeableness trait contributes to lower level of relational aggression in romantic relationships. Besides that, high levels of loneliness, avoidant attachment style, and anxious attachment style contribute to higher level of relational aggression in romantic relationship.

For hierarchical regression analysis, only those variables that were significant in the multiple regression analyses were entered into hierarchical regression models which are agreeableness trait, loneliness, avoidant attachment style, and anxious attachment style. Table  3 shows the hierarchical regression analysis where R² value for Model 1 is 0.097, F (25.735) = 22.545, p  <.05. This means that the agreeableness dimension accounts for 9.7% of the variance in relational aggression. While the R² value obtained for Model 2 is 0.098, F (17.410) = 15.240, p  <.05. This means that social support and agreeableness dimensions contribute as much as 9.8% of the variance to relational aggression in romantic relationships. These results showed that the percentage of variance only increases by 0.1% (9.8%– 9.7%) with the presence of a moderator in this model. The results in Table  3 showed that the dimension of agreeableness as a predictor is significant with a value of β =-0.296, t = -6.333, p  <.05. While social support as a predictor is not significant with β value = -0.062, t = -1.331, p  >.05. After entering the moderator, the interaction term of social support and agreeableness is not significant with a value of β = -0.406, t = − 0.816 and p  >.05. The agreeableness subscale was a significant predictor in the first block ( p  <.05) but did not reach significance in the second block ( p  =.415).

Table  4 shows the hierarchical regression analysis where R² value for Model 1 is 0.135, F (35.826) = 32.761, p  <.05. This means that the loneliness level dimension accounts for 13.5% of the variance in relational aggression. While the R² value obtained for Model 2 is 0.146, F (25.874) = 23.915, p  <.05. This means that social support and loneliness level dimensions contribute as much as 14.6% of the variance to relational aggression in romantic relationships. These results show that the percentage of variance only increases by 1.1% (14.6%– 13.5%) with the presence of a moderator in this model. The results in Table  4 show that the dimension of loneliness as a predictor is significant with a value of β = 0.383, t = 7.767, p  <.05. While social support as a predictor is not significant with a value of β = 0.048, t = 0.964, p  >.05. After entering the moderator, the interaction term of social support and loneliness is significant with a value of β = 0.550, t = 2.349 and p  <.05. The loneliness subscale was a significant predictor in all blocks ( p  <.05), with p  =.019 in the second block.

Table  5 shows the hierarchical regression analysis where R² value for Model 1 is 0.231, F (40.936) = 42.014, p  <.05. This means that the attachment style dimension accounts for 23.1% of the variance in relational aggression. While the R² value obtained for Model 2 is 0.237, F (25.225) = 25.976, p  <.05. This means that social support and attachment style dimensions account for 23.7% of the variance in relational aggression in romantic relationships. These results show that the percentage of variance only increases by 0.6% (23.7%– 23.1%) with the presence of a moderator in this model. The results in Table  5 show that the dimension of avoidant attachment style as a predictor is significant with a value of β = 0.368, t = 8.345, p  <.05 and the dimension of anxious attachment style as a predictor is significant with a value of β = 0.244, t = 5.364, p  <.05. While social support as a predictor is.

not significant with a value of β = 0.20, t = 0.447, p  >.05. After entering the moderator, the interaction term of social support and attachment style was not significant on the relational aggression with values ​​of β = 0.155, t = 0.676, p  >.05 and β = 0.520, t = 2.925, p  >.05. The ECR’s anxious and avoidant subscale were significant predictor in the first block ( p  <.05) but did not reach significance in the second block ( p  =.328;0.105).

The participants that have been selected for this study are young female adults between the age of 18 to 30 (M ± SD = 22.08 ± 3.21 years) who are currently in a romantic relationship for more than three months. Regression analysis was done, and it was found that only agreeableness trait showed significant predictor on relational aggression in romantic relationship and the other four dimensions of the big five personality in the psychosocial factor variable, which are extraversion, openness, neuroticism, and conscientiousness are not predictors or contributors to relational aggression in romantic relationships. Therefore, the findings prove that the importance of the relative contribution of personality traits of agreeableness. Generally, in an interpersonal context, personality is known to play an important role in determining the likelihood of engaging in an aggressive act. Negative emotions are generally harmful to romantic relationships. The result from our study is contradictory with the research findings by Burton et al. [ 73 ] where they have found that higher relational aggression was associated with higher levels of neuroticism and lower level of conscientiousness.

In addition, in some studies it has been found that individuals who tend to engage in relational aggression are more likely to show lower traits of agreeableness, openness and conscientiousness [ 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 ]. In our study, none of the big five personality traits except for agreeableness show significant prediction towards relational aggression in romantic relationships. This may be due to in general agreeableness traits may have stronger predictive utility than other personality traits ( 78 – 79 ). It has also been shown that agreeableness trait is negatively associated with relational aggression [ 80 , 81 , 82 ]. Agreeableness characterized as cooperation and understanding is an aspect related to motivation to maintain positive interpersonal relationships [ 83 ]. Likewise, the relationship between agreeableness and mind suggests that the former is responsible for processing social information.

Furthermore, agreeableness supports altruism while relational aggression is a type of destructive and hostile behaviour that has anti-social tendencies [ 84 ]. Therefore, this can further explain the evidence we found that agreeableness trait is associated with a negative influence on relational aggression. The trait of agreeableness has also been referred to as adaptability or reliability. There are differences in the interpretation of the dimension of agreeableness. The trait of agreeableness is considered reliable whereas Asian people generally support a collectivist culture, emphasizing social harmony and avoiding conflict [ 84 ]. Agreeableness represents the obligation to act as a group member and to make sacrifices. This cultural difference can lead to the irrelevance of agreeableness traits against relational aggression among young female adults in Malaysia. Besides that, those with higher levels of neuroticism are thought to be more likely to be aggressive. This individual is considered to have fewer stable emotions. Therefore, people who exhibit many neurotic personality traits are more prone to emotional instability and more prone to conflict with others. Conversely, agreeableness and aggressiveness are consistently negatively correlated [ 84 ].

Loneliness shows positively significant prediction towards relational aggression in romantic relationships. This is consistent with the study done by Prinstein et al., [ 55 ] which revealed that both relationally aggressive children and youth are more likely to be depressed, lonely, anxious, and socially isolated. However, according to the study done by Povedano et al., [ 85 ] found that the relationship between loneliness and relational aggression is significant and positive for boys, but not for girls. The involvement in violent behaviour would not act as a buffer for victimized girls experiencing strong feelings of loneliness, whereas it would be for boys. Lonely people usually have a negative perception of others’ intentions and behaviours in their interpersonal relationships. Along with these findings, lonely people tend to assume that their interpersonal failures stem from unchangeable and undesirable traits in their own personality, and they have a negative interpretation of other people’s intentions and interactions. Individuals who have developed a negative perception of themselves because of loneliness, feeling undesirable and unaccepted by others may resort to relational aggression, a powerful tool in which one uses force in interpersonal relationships to control other people [ 27 ].

The results of this study found a positive and significant prediction between avoidant and anxious attachment styles with relational aggression in romantic relationships. It has been established that the quality of communication between parents and children plays a crucial role in the development of a secure attachment. Our findings are in line with previous research that suggests that adolescents who have a positive relationship with their parents and communicate well with them are less likely to engage in aggressive behaviours and engage in risky activities [ 86 ]. Moreover, early attachments shape not only an individual’s sense of self and view of the world, but also their social skills, overall well-being, and future relationships. This is supported by the findings of Dervishi et al., [ 87 ] who found that adolescents with anxious attachments had higher levels of physical and verbal aggression. Studies have also shown that communication between parents and teens is strongly linked to the emergence of aggressive behaviours, with better communication resulting in a higher sense of security and an active exchange with others throughout life [ 88 , 89 , 90 ]. Essentially, individuals who are highly insecure may have difficulties controlling their anger and are more likely to engage in aggressive behaviour.

Previous research has demonstrated that individuals with insecure attachment patterns, particularly the anxious type, are at risk of experiencing negative consequences [ 91 , 92 , 93 ]. This can be attributed to a negative self-concept and high levels of rejection anxiety, leading to an over-reaction of excessive anger, and hurt in conflict situations. Research suggests that individuals with anxious attachment style have a history of persistent rejection from their partners and perceive themselves as unworthy of affection [ 94 ]. This can result in a perception of partners as untrustworthy and even threatening. It has been found that young adults with anxious attachment style are more prone to experiencing anger, compared to those with a secure or preoccupied attachment style who tend to have more positive expectations of their partners. In other words, those who have a strong sense of insecurity are likely to struggle with controlling their anger, while those with these insecurities are more likely to engage in aggressive behaviour.

Hierarchical regression analysis was carried out and it was found that social support as a moderator showed no significant effect between big five personality, avoidant and anxious attachment style with relational aggression in a romantic relationship except for loneliness subscale. The behaviour’s of loved ones that are in tune with the needs of the individual who is dealing with a stressful situation are referred to as social support [ 95 ]. The availability of support in the environment, the emotional response to stressful events, and the assessment of the consequences of these events can all be positively influenced by support from loved ones. Support from loved ones help to decrease the impact of stress by solving the victim’s problems, diminishing the perceived importance of the incident, facilitating the adoption of rational thoughts, and preventing or reducing inappropriate behaviour responses. According to previous research, social support may act as a moderator and buffer the effects of aggression and family functioning [ 96 ]. Due to the positive correlation between social support and a person’s family adjustment, social support helps to balance the negative effects of relational aggression on families [ 97 ].

This study’s finding is also consistent with the finding by Fortin et al. [ 98 ], where the moderating effect of social support is not present in female victims of physical violence. Thompson et al. [ 99 ] found that less women who have experienced relational aggression perceive the availability of social support, the more severe the violence they have experienced. The victim may also begin to blame herself more and ask for less support from her loved ones as the violence intensifies due to the bidirectional pattern of violence. Additionally, it seems that continuing in a relationship while having experienced physical abuse may have an impact on how satisfied they are with the assistance they have received [ 100 ]. These victims may also require additional forms of support, such as emotional, educational, and material support, even though they are generally happy with the assistance they have received.

Therefore, fewer confidants may have led to less robust social support. As a result, having fewer confidants may have led to social support that was insufficient and did not entirely satisfy the needs of the physical abuse victims. Besides that, social support is thought to be the most important factor that could significantly reduce loneliness [ 100 ], and it may be able to predict the trajectory of loneliness [ 101 ]. Indeed, numerous studies on the roles played by various forms of social support have found that perceived social support is more useful for predicting people’s mental health and may have a bigger impact on mental health than other forms of social support [ 102 , 103 , 104 ].

Both relational aggression and social support are empirically related to levels of loneliness, empirical literature is lacking on the interactive effects of relational aggression and social support on levels of loneliness [ 53 , 105 , 106 ]. Little is devoted in the existing literature to investigating the relationship triad. Ladd and Burgess [ 52 ] suggested that social support moderates the association between aggression and adjustment because it balances the dysfunction created by aggression. Family and peer support can act as a buffer in minimizing the negative effects of relational aggression in romantic relationships [ 107 ]. Adolescents who receive social support perform better in academic tasks and social interactions than individuals who do not have family and peer support [ 108 ]. Consistent with this research, social support, in general, and family support may act as moderating factors for the relationship between levels of loneliness and relational aggression.

Next in this study, it was found that there is no relationship between the role of social support as a moderator in the relationship between attachment style and relational aggression in romantic relationships among young female adults in Malaysia. This is contrary to the results of previous studies that suggest social support act as a moderator and minimizes or increases the effect of relational aggression on parental attachment style because social support is positively related to one’s family adjustment [ 99 ] and it has been hypothesized that social support moderates the relationship between relational aggression and parenting style. However, the findings of this current study highlight that social support as a moderator, relational aggression and parenting style are one of the factors that are very influential which affects the functioning of young people based on past studies [ 104 ]. The current findings show how social support moderates as an enhancer and buffer in attachment styles and relational aggression.

Results from previous studies differ from the current study due to several factors. Based on attachment style theory by Bowlby (1969), attachment style consists of secure attachment style, anxious attachment style, and avoidance attachment style but in this study only anxious attachment style, and avoidance attachment style alone were used to assess the attachment style of young adults. Avoidant attachment style involves fear of dependence and intimacy interpersonal, excessive need for independence and reluctance to self-disclosure. Anxious attachment styles involve fear of interpersonal rejection or neglect and distress when one’s partner is absent or unresponsive. People with an anxious attachment style always feel insecure about their romantic relationships and fear of abandonment by partner. Those with an avoidant attachment style have a common need to feel loved but not prepared emotionally to be in romantic relationships. Things like this can cause someone to use relational aggression in their romantic relationships such as manipulating partners, threatening partner to end the relationship. In addition, even if that individual has high social support but it does not affect if one is oriented in an avoidant attachment style and anxious attachment style.

Besides that, the findings of this study are consistent with a recent study by Egan and Bull [ 107 ] who found that there is no effect of social support as a moderator in the relationship between personality traits and relational aggression in romantic relationships. This is different from the perception based on personality theory developed by Goldberg [ 109 ] stating that social support is significantly associated with personality characteristics, especially extraversion, agreeableness, or emotional stability [ 107 ]. In general, from childhood to late adulthood, the relationships maintained by individuals with other people are related to individual differences in personality characteristics [ 110 ]. Personality traits that define interaction style can predict social interaction, available social support, and its perception. However, a supportive social context may also predict personality traits by providing individuals with opportunities to develop social skills, maintain social relationships, and foster prosocial behaviour. If personal experiences, roles, and social relationships can influence a person’s personality traits, social support is not only a proxy for the quality of social relationships but also a resource that can help to face the social challenges faced in middle adulthood and can predict personality traits by adapting to social roles expectations and developing social skills. Therefore, the relationship between the big five personalities and perceived social support is not only unidirectional but also reciprocal.

Limitations

As for limitations, all data used in this study were self-reported. The sensitive nature of some questions may have caused some participants to succumb to the social desirability bias and report. For instance, lower rates of relational aggression than their actual behaviour. Despite this, participants provided anonymous answers, making it less likely that they were prompted to provide biased answers. Furthermore, due to recall issues and inaccurate reporting it’s possible that both estimates of psychosocial factors and relational aggression contain measurement error. Another limitation for this study is the cross-sectional nature of these data, which precludes inferences about causal relationships is another drawback of this study.

Additionally, caution should be used when extrapolating the findings to all female samples since the participants in this study were a homogeneous sample of young female adults. Due to the study’s cross-sectional design, it is also impossible to draw conclusions about the cause-and-effect relationship between social support as a moderator in between psychosocial factors and relational aggression. To address the temporal ordering of people’s levels of social support from family and friends and their participation in relational aggression, longitudinal studies are required. Besides that, young female adults were not questioned regarding the opinions or involvement of friends in relational aggression. According to earlier studies, teenagers who have friends who engage in dating violence run a higher risk of doing so themselves [ 111 ]. Moreover, data was collected at one time point, so cause-and-effect conclusions could not be made. Besides that, the difference between the psychosocial factor’s groups couldn’t be identified clearly in relation to relational aggression in romantic relationship as only multiple regression has been conducted. A post hoc test can help in identifying the differences between specific groups and give a more meaningful finding.

Future studies

Future studies are needed on the impact of multiple placements, including their effects on unstable living situations, sibling attachment, adoption, frequent school changes, and difficulties. For instance, if an individual grew up in a family that shamed or condemned emotional expression or in a home with an abusive parent, this may associate anger with fear, danger, or damaged relationships, which will cause to develop more negative perception of their relationship with their parents and siblings. This study only focuses on female samples. Even though there are differences between the genders, both genders naturally experience anger. Men are thought to be more prone to rage despite evidence that women are more emotionally expressive. In addition, more research on gender disparities is necessary.

The current study suggests that preventive measures need to be taken to stop the symptoms of anger from getting worse. Uncontrollable anger can cause several problems, such as erratic behaviour, assault, abuse, addictions, and legal troubles. In these circumstances, anger impairs decision-making, harms relationships, and has other negative effects. Besides that, to manage anger and deal with triggers without repressing and storing it, as well as to deal without causing emotional harm, it’s crucial to recognize the warning signs of anger. Anger management techniques include breathing exercises under supervision, cognitive behavioural therapy, imagery, problem-solving, and the development of interpersonal and communication skills. Besides that, the findings of this study indicate that aimed at reducing and/or preventing relational aggression among young female adults should consider agreeableness traits ( 112 – 113 ). Young female adults who were less agreeable were likely to experience relational aggression. The findings highlight the need for additional research to pinpoint specific characteristics of the lower level of agreeableness female population that put them at risk for relational aggression in a romantic relationship.

The current study was novel in its examination of social support as a moderator of the association between psychosocial factor and relational aggression in romantic relationships. Future studies will need to test these associations further. Based on the findings from this study, there’s no evidence to support the prediction that social support would moderate this association, but future research with a better measure of social support or using different moderator variable may provide different results. Future research should investigate variables that are not included in this study that are possible predictors of relational aggression in romantic relationships. A post hoc test can be conducted further in identifying the differences between specific groups and give a more meaningful finding.

Relational forms of aggression tend to rise during adolescence (115), in part because more complex cognitive abilities are developed during this period that are necessary for successfully manipulating the relationships of others. We discovered a significant correlation between aggression and social support, which is crucial during adolescence. This research suggests that for some people, attachment style and relational aggression are highly overlapping, and possibly reciprocal. However, for some people, personality traits appear to be differentially linked to relational aggression. These results point to the need for additional research examining the moderating effects of significant correlates as well as a more nuanced strategy for relational forms of aggression during early adulthood’s prevention and intervention. Therefore, efforts to prevent young female adults from engaging in relational aggression should concentrate on all females and not just those who have been identified as perpetrators or victims. All females will be better equipped to spot relational aggression signs and help their friends if they are informed about the warning signs of relational aggression. Early adulthood could be taught about the warning signs of relational aggression through community-wide campaigns and in high school. This study will help to create awareness on the existence of relational aggression, public will be able to tackle this issue at an earlier stage rather than later and individuals will be able to identify the difference between a toxic and a non-toxic relationship.

In conclusion, many participants in this study reported having violent-free romantic relationships even though there are individuals who reported being the perpetrators of relational aggression. The current study was a first step in determining how psychosocial factors and relational aggression in romantic relationships are related to one another. Findings indicate that social support is also an important factor in understanding females’ relational aggression in romantic relationship. At the same time, results demonstrated that social support from friends and/or family has no significant effect with personality traits and attachment styles with relational aggression. This finding raises questions as to what may provide support to young female adults in relational aggression in romantic relationships. The current study’s greatest strength is the dialogue it has sparked about the importance of social support in romantic relationships between young female adults who is experiencing loneliness. This raised awareness could serve as a starting point for further study as well as the creation of programs and regulations that cater to the requirements of this population. It is necessary to create and carry out programs that encourage healthy dating interactions and inform young adults about dating violence which focuses on relational aggression. The findings also provide evidence for the significance of parental modelling in the development of romantic relationships in young adults. The findings are supported by social learning theory (Bandura, 1971), the concepts of which might be employed in investigating other areas of psychosocial factors on young adults’ relationships in the future.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Big Five Inventory

Experiences in Close Relationships– II

Multidimensional Scale of Perceived Social Support

Measure of Relational Aggression and Victimization

UCLA Loneliness Scale

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Kamaluddin, M.R., Munusamy, S., Sheau Tsuey, C. et al. Relational aggression in romantic relationship: empirical evidence among young female adults in Malaysia. BMC Psychol 12 , 305 (2024). https://doi.org/10.1186/s40359-024-01670-4

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