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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.

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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.

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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.

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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

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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

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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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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.
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• The Cambridge Handbook of Personality Psychology

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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."

Big 5 Personality Traits

Reviewed by Psychology Today Staff

The differences between people’s personalities can be broken down in terms of five major traits—often called the “Big Five.” Each one reflects a key part of how a person thinks, feels, and behaves. The Big Five traits are:

• Openness to experience (includes aspects such as intellectual curiosity and creative imagination )
• Conscientiousness (organization, productiveness, responsibility)
• Extroversion (sociability, assertiveness ; its opposite is Introversion )
• Agreeableness (compassion, respectfulness, trust in others)
• Neuroticism (tendencies toward anxiety and depression )

Individual personalities are thought to feature each of these five broad traits to some degree. When the traits are measured, some people rate higher and others rate lower: Someone can be more conscientious and less agreeable than most people, for instance, while scoring about average on the other traits. These traits remain fairly stable during adulthood.

People can also differ on the more specific facets that make up each of the Big Five traits. A relatively extroverted person might be highly sociable but not especially assertive .

The five-factor model is widely used by personality researchers, but it is not the only model. A more recently introduced six-factor model known as HEXACO adds the factor of honesty-humility to the original five traits.

• Measuring the Big Five
• Why the Big Five Matter
• Other Personality Tests

The Big Five traits are typically assessed using one of multiple questionnaires. While these tests vary in the exact terms they use for each trait, they essentially cover the same broad dimensions, providing high-to-low scores on each: openness to experience (also called open-mindedness or just openness), conscientiousness , extroversion (the reverse of which is introversion ), agreeableness , and neuroticism (sometimes negative emotionality or emotional stability).

One test, the latest version of the Big Five Inventory, asks how much a person agrees or disagrees that he or she is someone who exemplifies various specific statements, such as:

• “Is curious about many different things” (for openness, or open-mindedness)
• “Is systematic, likes to keep things in order” (for conscientiousness)
• “Is outgoing, sociable” (for extroversion)
• “Is compassionate, has a soft heart” (for agreeableness)
• “Is moody, has up and down mood swings” (for neuroticism, or negative emotionality)

Based on a person’s ratings for dozens of these statements (or fewer, for other tests), an average score can be calculated for each of the five traits.

Scores on a Big Five questionnaire provide a sense of how low or high a person rates on a continuum for each trait. Comparing those scores to a large sample of test takers—as some online tests do—offers a picture of how open, conscientious, extroverted (or introverted), agreeable, and neurotic one is relative to others. 

Analyzing English words used to describe personality traits, researchers used statistical techniques to identify clusters of related characteristics . This led to a small number of overarching trait dimensions that personality psychologists have scientifically tested in large population samples.

The Big Five were not determined by any one person—they have roots in the work of various researchers going back to the 1930s. In 1961, Ernest Tupes and Raymond Christal identified five personality factors that others would reanalyze and rename. Lewis Goldberg used the term Big Five in 1981 to describe these broad factors. 

Some Big Five questionnaires break the five main traits down into smaller sub-components or “facets,” which are correlated with each other but can be independently measured. In the Big Five Inventory, for instance, “sociability” and “ assertiveness ” are distinct facets of extroversion, while “organization” and “responsibility” are facets of conscientiousness.

The five-factor model not only helps people better understand how they compare to others and to put names to their characteristics. It’s also used to explore relationships between personality and many other life indicators. These include consequential outcomes such as physical health and well-being as well as success in social, academic, and professional contexts. Personality psychologists have observed reliable associations between how people rate on trait scales and how they fare or feel, on average, in various aspects of their lives.

Quite a lot , at least in Western samples. There is reliable evidence, for example, that extroversion is associated with subjective well-being, neuroticism with lower work commitment, and agreeableness with religiousness. Certain traits have been linked to mortality risk. However, these are overall patterns and don’t mean that a trait necessarily causes any of these outcomes.

Yes. While personality trait measures tend to be fairly consistent over short periods of time in adulthood, they do change over the course of a lifetime. There’s also reason to believe that deliberate personality change is possible.

Various ways of representing major traits have been proposed, and personality researchers continue to disagree on the number of distinct characteristics that can be measured. The five-factor model dominates the rest, as far as psychologists are concerned, although multiple types of assessments exist to measure the five traits.

Outside of academic psychology, tests that aim to sort people into personality types—including the Myers-Briggs/MBTI and Enneagram—are highly popular, though many experts take issue with such tests on scientific grounds. The five-factor model has conceptual and empirical strengths that others lack.

For a number of reasons , many personality psychologists consider Big Five tests superior to the Myers-Briggs Type Indicator . These include concerns about the reliability of the types assigned by the Myers-Briggs and the validity of the test—though there is some overlap between its dimensions (which include extroversion-introversion) and the Big Five.

It depends on how strictly you define a “type.” Research indicates that for any given trait, people fall at various points along a continuum rather than fitting neatly into categories. While some identify wholeheartedly as a total extrovert or introvert, for example, there are many shades in between, and most of us would score somewhere in the middle.

Yes. Some have criticized the five-factor model for its origins in data rather than in theory and argued that it does not encompass all fundamental traits (see HEXACO ). There is also evidence that current tests provide less reliable results outside of Western, industrialized countries.

To understand and predict human behavior, including your own, follow the affirmation: More than we admit, what we do is largely a function of where we're affirmed.

They have an answer for everything. How can you tell whether they're a know-it-all jerk? And wouldn't it be easier to just assume they are?

Good personality tests can predict average behavioral tendencies over time, but they cannot predict specific behaviors in specific situations.

A recent study of Greek-speaking participants assesses 17 possible predictors of an inability to form romantic relationships.

Art collecting is a multifaceted activity influenced by various personality traits and psychological motivations.

Explore the psychology of lies, self-deception, and their profound influence on human behaviour and survival.

Of all possible personality traits, one in particular seems invincible. However, new research suggests why there's no reason to envy those high in this quality.

Is your personality variable like a chameleon changing colors? Here’s how this may benefit your career—but also how this could backfire.

Recent developments in artificial intelligence have raised some concerns. New studies in psychology shed light on who fears AI and why.

We don't realize that anger is an evolutionary response that is no longer needed and can be controlled by forgiveness or understanding.

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• Published: 22 May 2020

Assessing the Big Five personality traits using real-life static facial images

• Alexander Kachur   ORCID: orcid.org/0000-0003-1165-2672 1 ,
• Evgeny Osin   ORCID: orcid.org/0000-0003-3330-5647 2 ,
• Denis Davydov   ORCID: orcid.org/0000-0003-3747-7403 3 ,
• Konstantin Shutilov 4 &
• Alexey Novokshonov 4  

Scientific Reports volume  10 , Article number:  8487 ( 2020 ) Cite this article

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• Human behaviour

There is ample evidence that morphological and social cues in a human face provide signals of human personality and behaviour. Previous studies have discovered associations between the features of artificial composite facial images and attributions of personality traits by human experts. We present new findings demonstrating the statistically significant prediction of a wider set of personality features (all the Big Five personality traits) for both men and women using real-life static facial images. Volunteer participants (N = 12,447) provided their face photographs (31,367 images) and completed a self-report measure of the Big Five traits. We trained a cascade of artificial neural networks (ANNs) on a large labelled dataset to predict self-reported Big Five scores. The highest correlations between observed and predicted personality scores were found for conscientiousness (0.360 for men and 0.335 for women) and the mean effect size was 0.243, exceeding the results obtained in prior studies using ‘selfies’. The findings strongly support the possibility of predicting multidimensional personality profiles from static facial images using ANNs trained on large labelled datasets. Future research could investigate the relative contribution of morphological features of the face and other characteristics of facial images to predicting personality.

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Introduction

A growing number of studies have linked facial images to personality. It has been established that humans are able to perceive certain personality traits from each other’s faces with some degree of accuracy 1 , 2 , 3 , 4 . In addition to emotional expressions and other nonverbal behaviours conveying information about one’s psychological processes through the face, research has found that valid inferences about personality characteristics can even be made based on static images of the face with a neutral expression 5 , 6 , 7 . These findings suggest that people may use signals from each other’s faces to adjust the ways they communicate, depending on the emotional reactions and perceived personality of the interlocutor. Such signals must be fairly informative and sufficiently repetitive for recipients to take advantage of the information being conveyed 8 .

Studies focusing on the objective characteristics of human faces have found some associations between facial morphology and personality features. For instance, facial symmetry predicts extraversion 9 . Another widely studied indicator is the facial width to height ratio (fWHR), which has been linked to various traits, such as achievement striving 10 , deception 11 , dominance 12 , aggressiveness 13 , 14 , 15 , 16 , and risk-taking 17 . The fWHR can be detected with high reliability irrespective of facial hair. The accuracy of fWHR-based judgements suggests that the human perceptual system may have evolved to be sensitive to static facial features, such as the relative face width 18 .

There are several theoretical reasons to expect associations between facial images and personality. First, genetic background contributes to both face and personality. Genetic correlates of craniofacial characteristics have been discovered both in clinical contexts 19 , 20 and in non-clinical populations 21 . In addition to shaping the face, genes also play a role in the development of various personality traits, such as risky behaviour 22 , 23 , 24 , and the contribution of genes to some traits exceeds the contribution of environmental factors 25 . For the Big Five traits, heritability coefficients reflecting the proportion of variance that can be attributed to genetic factors typically lie in the 0.30–0.60 range 26 , 27 . From an evolutionary perspective, these associations can be expected to have emerged by means of sexual selection. Recent studies have argued that some static facial features, such as the supraorbital region, may have evolved as a means of social communication 28 and that facial attractiveness signalling valuable personality characteristics is associated with mating success 29 .

Second, there is some evidence showing that pre- and postnatal hormones affect both facial shape and personality. For instance, the face is a visible indicator of the levels of sex hormones, such as testosterone and oestrogen, which affect the formation of skull bones and the fWHR 30 , 31 , 32 . Given that prenatal and postnatal sex hormone levels do influence behaviour, facial features may correlate with hormonally driven personality characteristics, such as aggressiveness 33 , competitiveness, and dominance, at least for men 34 , 35 . Thus, in addition to genes, the associations of facial features with behavioural tendencies may also be explained by androgens and potentially other hormones affecting both face and behaviour.

Third, the perception of one’s facial features by oneself and by others influences one’s subsequent behaviour and personality 36 . Just as the perceived ‘cleverness’ of an individual may lead to higher educational attainment 37 , prejudice associated with the shape of one’s face may lead to the development of maladaptive personality characteristics (i.e., the ‘Quasimodo complex’ 38 ). The associations between appearance and personality over the lifespan have been explored in longitudinal observational studies, providing evidence of ‘self-fulfilling prophecy’-type and ‘self-defeating prophecy’-type effects 39 .

Fourth and finally, some personality traits are associated with habitual patterns of emotionally expressive behaviour. Habitual emotional expressions may shape the static features of the face, leading to the formation of wrinkles and/or the development of facial muscles.

Existing studies have revealed the links between objective facial picture cues and general personality traits based on the Five-Factor Model or the Big Five (BF) model of personality 40 . However, a quick glance at the sizes of the effects found in these studies (summarized in Table  1 ) reveals much controversy. The results appear to be inconsistent across studies and hardly replicable 41 . These inconsistencies may result from the use of small samples of stimulus faces, as well as from the vast differences in methodologies. Stronger effect sizes are typically found in studies using composite facial images derived from groups of individuals with high and low scores on each of the Big Five dimensions 6 , 7 , 8 . Naturally, the task of identifying traits using artificial images comprised of contrasting pairs with all other individual features eliminated or held constant appears to be relatively easy. This is in contrast to realistic situations, where faces of individuals reflect a full range of continuous personality characteristics embedded in a variety of individual facial features.

Studies relying on photographic images of individual faces, either artificially manipulated 2 , 42 or realistic, tend to yield more modest effects. It appears that studies using realistic photographs made in controlled conditions (neutral expression, looking straight at the camera, consistent posture, lighting, and distance to the camera, no glasses, no jewellery, no make-up, etc.) produce stronger effects than studies using ‘selfies’ 25 . Unfortunately, differences in the methodologies make it hard to hypothesize whether the diversity of these findings is explained by variance in image quality, image background, or the prediction models used.

Research into the links between facial picture cues and personality traits faces several challenges. First, the number of specific facial features is very large, and some of them are hard to quantify. Second, the effects of isolated facial features are generally weak and only become statistically noticeable in large samples. Third, the associations between objective facial features and personality traits might be interactive and nonlinear. Finally, studies using real-life photographs confront an additional challenge in that the very characteristics of the images (e.g., the angle of the head, facial expression, makeup, hairstyle, facial hair style, etc.) are based on the subjects’ choices, which are potentially influenced by personality; after all, one of the principal reasons why people make and share their photographs is to signal to others what kind of person they are. The task of isolating the contribution of each variable out of the multitude of these individual variables appears to be hardly feasible. Instead, recent studies in the field have tended to rely on a holistic approach, investigating the subjective perception of personality based on integral facial images.

The holistic approach aims to mimic the mechanisms of human perception of the face and the ways in which people make judgements about each other’s personality. This approach is supported by studies of human face perception, showing that faces are perceived and encoded in a holistic manner by the human brain 43 , 44 , 45 , 46 . Put differently, when people identify others, they consider individual facial features (such as a person’s eyes, nose, and mouth) in concert as a single entity rather than as independent pieces of information 47 , 48 , 49 , 50 . Similar to facial identification, personality judgements involve the extraction of invariant facial markers associated with relatively stable characteristics of an individual’s behaviour. Existing evidence suggests that various social judgements might be based on a common visual representational system involving the holistic processing of visual information 51 , 52 . Thus, even though the associations between isolated facial features and personality characteristics sought by ancient physiognomists have emerged to be weak, contradictory or even non-existent, the holistic approach to understanding the face-personality links appears to be more promising.

An additional challenge faced by studies seeking to reveal the face-personality links is constituted by the inconsistency of the evaluations of personality traits by human raters. As a result, a fairly large number of human raters is required to obtain reliable estimates of personality traits for each photograph. In contrast, recent attempts at using machine learning algorithms have suggested that artificial intelligence may outperform individual human raters. For instance, S. Hu and colleagues 40 used the composite partial least squares component approach to analyse dense 3D facial images obtained in controlled conditions and found significant associations with personality traits (stronger for men than for women).

A similar approach can be implemented using advanced machine learning algorithms, such as artificial neural networks (ANNs), which can extract and process significant features in a holistic manner. The recent applications of ANNs to the analysis of human faces, body postures, and behaviours with the purpose of inferring apparent personality traits 53 , 54 indicate that this approach leads to a higher accuracy of prediction compared to individual human raters. The main difficulty of the ANN approach is the need for large labelled training datasets that are difficult to obtain in laboratory settings. However, ANNs do not require high-quality photographs taken in controlled conditions and can potentially be trained using real-life photographs provided that the dataset is large enough. The interpretation of findings in such studies needs to acknowledge that a real-life photograph, especially one chosen by a study participant, can be viewed as a holistic behavioural act, which may potentially contain other cues to the subjects’ personality in addition to static facial features (e.g., lighting, hairstyle, head angle, picture quality, etc.).

The purpose of the current study was to investigate the associations of facial picture cues with self-reported Big Five personality traits by training a cascade of ANNs to predict personality traits from static facial images. The general hypothesis is that a real-life photograph contains cues about personality that can be extracted using machine learning. Due to the vast diversity of findings concerning the prediction accuracy of different traits across previous studies, we did not set a priori hypotheses about differences in prediction accuracy across traits.

Prediction accuracy

We used data from the test dataset containing predicted scores for 3,137 images associated with 1,245 individuals. To determine whether the variance in the predicted scores was associated with differences across images or across individuals, we calculated the intraclass correlation coefficients (ICCs) presented in Table  2 . The between-individual proportion of variance in the predicted scores ranged from 79 to 88% for different traits, indicating a general consistency of predicted scores for different photographs of the same individual. We derived the individual scores used in all subsequent analyses as the simple averages of the predicted scores for all images provided by each participant.

The correlation coefficients between the self-report test scores and the scores predicted by the ANN ranged from 0.14 to 0.36. The associations were strongest for conscientiousness and weakest for openness. Extraversion and neuroticism were significantly better predicted for women than for men (based on the z test). We also compared the prediction accuracy within each gender using Steiger’s test for dependent sample correlation coefficients. For men, conscientiousness was predicted more accurately than the other four traits (the differences among the latter were not statistically significant). For women, conscientiousness was predicted more accurately, and openness was predicted less accurately compared to the three other traits.

The mean absolute error (MAE) of prediction ranged between 0.89 and 1.04 standard deviations. We did not find any associations between the number of photographs and prediction error.

Trait intercorrelations

The structure of the correlations between the scales was generally similar for the observed test scores and the predicted values, but some coefficients differed significantly (based on the z test) (see Table  3 ). Most notably, predicted openness was more strongly associated with conscientiousness (negatively) and extraversion (positively), whereas its association with agreeableness was negative rather than positive. The associations of predicted agreeableness with conscientiousness and neuroticism were stronger than those between the respective observed scores. In women, predicted neuroticism demonstrated a stronger inverse association with conscientiousness and a stronger positive association with openness. In men, predicted neuroticism was less strongly associated with extraversion than its observed counterpart.

To illustrate the findings, we created composite images using Abrosoft FantaMorph 5 by averaging the uploaded images across contrast groups of 100 individuals with the highest and the lowest test scores on each trait. The resulting morphed images in which individual features are eliminated are presented in Fig.  1 .

Composite facial images morphed across contrast groups of 100 individuals for each Big Five trait.

This study presents new evidence confirming that human personality is related to individual facial appearance. We expected that machine learning (in our case, artificial neural networks) could reveal multidimensional personality profiles based on static morphological facial features. We circumvented the reliability limitations of human raters by developing a neural network and training it on a large dataset labelled with self-reported Big Five traits.

We expected that personality traits would be reflected in the whole facial image rather than in its isolated features. Based on this expectation, we developed a novel two-tier machine learning algorithm to encode the invariant facial features as a vector in a 128-dimensional space that was used to predict the BF traits by means of a multilayer perceptron. Although studies using real-life photographs do not require strict experimental conditions, we had to undertake a series of additional organizational and technological steps to ensure consistent facial image characteristics and quality.

Our results demonstrate that real-life photographs taken in uncontrolled conditions can be used to predict personality traits using complex computer vision algorithms. This finding is in contrast to previous studies that mostly relied on high-quality facial images taken in controlled settings. The accuracy of prediction that we obtained exceeds that in the findings of prior studies that used realistic individual photographs taken in uncontrolled conditions (e.g., selfies 55 ). The advantage of our methodology is that it is relatively simple (e.g., it does not rely on 3D scanners or 3D facial landmark maps) and can be easily implemented using a desktop computer with a stock graphics accelerator.

In the present study, conscientiousness emerged to be more easily recognizable than the other four traits, which is consistent with some of the existing findings 7 , 40 . The weaker effects for extraversion and neuroticism found in our sample may be because these traits are associated with positive and negative emotional experiences, whereas we only aimed to use images with neutral or close to neutral emotional expressions. Finally, this appears to be the first study to achieve a significant prediction of openness to experience. Predictions of personality based on female faces appeared to be more reliable than those for male faces in our sample, in contrast to some previous studies 40 .

The BF factors are known to be non-orthogonal, and we paid attention to their intercorrelations in our study 56 , 57 . Various models have attempted to explain the BF using higher-order dimensions, such as stability and plasticity 58 or a single general factor of personality (GFP) 59 . We discovered that the intercorrelations of predicted factors tend to be stronger than the intercorrelations of self-report questionnaire scales used to train the model. This finding suggests a potential biological basis of GFP. However, the stronger intercorrelations of the predicted scores can be explained by consistent differences in picture quality (just as the correlations between the self-report scales can be explained by social desirability effects and other varieties of response bias 60 ). Clearly, additional research is needed to understand the context of this finding.

We believe that the present study, which did not involve any subjective human raters, constitutes solid evidence that all the Big Five traits are associated with facial cues that can be extracted using machine learning algorithms. However, despite having taken reasonable organizational and technical steps to exclude the potential confounds and focus on static facial features, we are still unable to claim that morphological features of the face explain all the personality-related image variance captured by the ANNs. Rather, we propose to see facial photographs taken by subjects themselves as complex behavioural acts that can be evaluated holistically and that may contain various other subtle personality cues in addition to static facial features.

The correlations reported above with a mean r = 0.243 can be viewed as modest; indeed, facial image-based personality assessment can hardly replace traditional personality measures. However, this effect size indicates that an ANN can make a correct guess about the relative standing of two randomly chosen individuals on a personality dimension in 58% of cases (as opposed to the 50% expected by chance) 61 . The effect sizes we observed are comparable with the meta-analytic estimates of correlations between self-reported and observer ratings of personality traits: the associations range from 0.30 to 0.49 when one’s personality is rated by close relatives or colleagues, but only from −0.01 to 0.29 when rated by strangers 62 . Thus, an artificial neural network relying on static facial images outperforms an average human rater who meets the target in person without any prior acquaintance. Given that partner personality and match between two personalities predict friendship formation 63 , long-term relationship satisfaction 64 , and the outcomes of dyadic interaction in unstructured settings 65 , the aid of artificial intelligence in making partner choices could help individuals to achieve more satisfying interaction outcomes.

There are a vast number of potential applications to be explored. The recognition of personality from real-life photos can be applied in a wide range of scenarios, complementing the traditional approaches to personality assessment in settings where speed is more important than accuracy. Applications may include suggesting best-fitting products or services to customers, proposing to individuals a best match in dyadic interaction settings (such as business negotiations, online teaching, etc.) or personalizing the human-computer interaction. Given that the practical value of any selection method is proportional to the number of decisions made and the size and variability of the pool of potential choices 66 , we believe that the applied potential of this technology can be easily revealed at a large scale, given its speed and low cost. Because the reliability and validity of self-report personality measures is not perfect, prediction could be further improved by supplementing these measures with peer ratings and objective behavioural indicators of personality traits.

The fact that conscientiousness was predicted better than the other traits for both men and women emerges as an interesting finding. From an evolutionary perspective, one would expect the traits most relevant for cooperation (conscientiousness and agreeableness) and social interaction (certain facets of extraversion and neuroticism, such as sociability, dominance, or hostility) to be reflected more readily in the human face. The results are generally in line with this idea, but they need to be replicated and extended by incorporating trait facets in future studies to provide support for this hypothesis.

Finally, although we tried to control the potential sources of confounds and errors by instructing the participants and by screening the photographs (based on angles, facial expressions, makeup, etc.), the present study is not without limitations. First, the real-life photographs we used could still carry a variety of subtle cues, such as makeup, angle, light facial expressions, and information related to all the other choices people make when they take and share their own photographs. These additional cues could say something about their personality, and the effects of all these variables are inseparable from those of static facial features, making it hard to draw any fundamental conclusions from the findings. However, studies using real-life photographs may have higher ecological validity compared to laboratory studies; our results are more likely to generalize to real-life situations where users of various services are asked to share self-pictures of their choice.

Another limitation pertains to a geographically bounded sample of individuals; our participants were mostly Caucasian and represented one cultural and age group (Russian-speaking adults). Future studies could replicate the effects using populations representing a more diverse variety of ethnic, cultural, and age groups. Studies relying on other sources of personality data (e.g., peer ratings or expert ratings), as well as wider sets of personality traits, could complement and extend the present findings.

Sample and procedure

The study was carried out in the Russian language. The participants were anonymous volunteers recruited through social network advertisements. They did not receive any financial remuneration but were provided with a free report on their Big Five personality traits. The data were collected online using a dedicated research website and a mobile application. The participants provided their informed consent, completed the questionnaires, reported their age and gender and were asked to upload their photographs. They were instructed to take or upload several photographs of their face looking directly at the camera with enough lighting, a neutral facial expression and no other people in the picture and without makeup.

Our goal was to obtain an out-of-sample validation dataset of 616 respondents of each gender to achieve 80% power for a minimum effect we considered to be of practical significance ( r  = 0.10 at p < 0.05), requiring a total of 6,160 participants of each gender in the combined dataset comprising the training and validation datasets. However, we aimed to gather more data because we expected that some online respondents might provide low-quality or non-genuine photographs and/or invalid questionnaire responses.

The initial sample included 25,202 participants who completed the questionnaire and uploaded a total of 77,346 photographs. The final combined dataset comprised 12,447 valid questionnaires and 31,367 associated photographs after the data screening procedures (below). The participants ranged in age from 18 to 60 (59.4% women, M = 27.61, SD = 12.73, and 40.6% men, M = 32.60, SD = 11.85). The dataset was split randomly into a training dataset (90%) and a test dataset (10%) used to validate the prediction model. The validation dataset included the responses of 505 men who provided 1224 facial images and 740 women who provided 1913 images. Due to the sexually dimorphic nature of facial features and certain personality traits (particularly extraversion 1 , 67 , 68 ), all the predictive models were trained and validated separately for male and female faces.

Ethical approval

The research was carried out in accordance with the Declaration of Helsinki. The study protocol was approved by the Research Ethics Committee of the Open University for the Humanities and Economics. We obtained the participants’ informed consent to use their data and photographs for research purposes and to publish generalized findings. The morphed group average images presented in the paper do not allow the identification of individuals. No information or images that could lead to the identification of study participants have been published.

Data screening

We excluded incomplete questionnaires (N = 3,035) and used indices of response consistency to screen out random responders 69 . To detect systematic careless responses, we used the modal response category count, maximum longstring (maximum number of identical responses given in sequence by participant), and inter-item standard deviation for each questionnaire. At this stage, we screened out the answers of individuals with zero standard deviations (N = 329) and a maximum longstring above 10 (N = 1,416). To detect random responses, we calculated the following person-fit indices: the person-total response profile correlation, the consistency of response profiles for the first and the second half of the questionnaire, the consistency of response profiles obtained based on equivalent groups of items, the number of polytomous Guttman errors, and the intraclass correlation of item responses within facets.

Next, we conducted a simulation by generating random sets of integers in the 1–5 range based on a normal distribution (µ = 3, σ = 1) and on the uniform distribution and calculating the same person-fit indices. For each distribution, we generated a training dataset and a test dataset, each comprised of 1,000 simulated responses and 1,000 real responses drawn randomly from the sample. Next, we ran a logistic regression model using simulated vs real responses as the outcome variable and chose an optimal cutoff point to minimize the misclassification error (using the R package optcutoff). The sensitivity value was 0.991 for the uniform distribution and 0.960 for the normal distribution, and the specificity values were 0.923 and 0.980, respectively. Finally, we applied the trained model to the full dataset and identified observations predicted as likely to be simulated based on either distribution (N = 1,618). The remaining sample of responses (N = 18,804) was used in the subsequent analyses.

Big Five measure

We used a modified Russian version of the 5PFQ questionnaire 70 , which is a 75-item measure of the Big Five model, with 15 items per trait grouped into five three-item facets. To confirm the structural validity of the questionnaire, we tested an exploratory structural equation (ESEM) model with target rotation in Mplus 8.2. The items were treated as ordered categorical variables using the WLSMV estimator, and facet variance was modelled by introducing correlated uniqueness values for the items comprising each facet.

The theoretical model showed a good fit to the data (χ 2  = 147854.68, df = 2335, p < 0.001; CFI = 0.931; RMSEA = 0.040 [90% CI: 0.040, 0.041]; SRMR = 0.024). All the items showed statistically significant loadings on their theoretically expected scales (λ ranged from 0.14 to 0.87, M = 0.51, SD = 0.17), and the absolute cross-loadings were reasonably low (M = 0.11, SD = 0.11). The distributions of the resulting scales were approximately normal (with skewness and kurtosis values within the [−1; 1] range). To assess the reliability of the scales, we calculated two internal consistency indices, namely, robust omega (using the R package coefficientalpha) and algebraic greatest lower bound (GLB) reliability (using the R package psych) 71 (see Table  4 ).

Image screening and pre-processing

The images (photographs and video frames) were subjected to a three-step screening procedure aimed at removing fake and low-quality images. First, images with no human faces or with more than one human face were detected by our computer vision (CV) algorithms and automatically removed. Second, celebrity images were identified and removed by means of a dedicated neural network trained on a celebrity photo dataset (CelebFaces Attributes Dataset (CelebA), N > 200,000) 72 that was additionally enriched with pictures of Russian celebrities. The model showed a 98.4% detection accuracy. Third, we performed a manual moderation of the remaining images to remove images with partially covered faces, those that were evidently photoshopped or any other fake images not detected by CV.

The images retained for subsequent processing were converted to single-channel 8-bit greyscale format using the OpenCV framework (opencv.org). Head position (pitch, yaw, roll) was measured using our own dedicated neural network (multilayer perceptron) trained on a sample of 8 000 images labelled by our team. The mean absolute error achieved on the test sample of 800 images was 2.78° for roll, 1.67° for pitch, and 2.34° for yaw. We used the head position data to retain the images with yaw and roll within the −30° to 30° range and pitch within the −15° to 15° range.

Next, we assessed emotional neutrality using the Microsoft Cognitive Services API on the Azure platform (score range: 0 to 1) and used 0.50 as a threshold criterion to remove emotionally expressive images. Finally, we applied the face and eye detection, alignment, resize, and crop functions available within the Dlib (dlib.net) open-source toolkit to arrive at a set of standardized 224 × 224 pixel images with eye pupils aligned to a standard position with an accuracy of 1 px. Images with low resolution that contained less than 60 pixels between the eyes, were excluded in the process.

The final photoset comprised 41,835 images. After the screened questionnaire responses and images were joined, we obtained a set of 12,447 valid Big Five questionnaires associated with 31,367 validated images (an average of 2.59 images per person for women and 2.42 for men).

Neural network architecture

First, we developed a computer vision neural network (NNCV) aiming to determine the invariant features of static facial images that distinguish one face from another but remain constant across different images of the same person. We aimed to choose a neural network architecture with a good feature space and resource-efficient learning, considering the limited hardware available to our research team. We chose a residual network architecture based on ResNet 73 (see Fig.  2 ).

Layer architecture of the computer vision neural network (NNCV) and the personality diagnostics neural network (NNPD).

This type of neural network was originally developed for image classification. We dropped the final layer from the original architecture and obtained a NNCV that takes a static monochrome image (224 × 224 pixels in size) and generates a vector of 128 32-bit dimensions describing unique facial features in the source image. As a measure of success, we calculated the Euclidean distance between the vectors generated from different images.

Using Internet search engines, we collected a training dataset of approximately 2 million openly available unlabelled real-life photos taken in uncontrolled conditions stratified by race, age and gender (using search engine queries such as ‘face photo’, ‘face pictures’, etc.). The training was conducted on a server equipped with four NVidia Titan accelerators. The trained neural network was validated on a dataset of 40,000 images belonging to 800 people, which was an out-of-sample part of the original dataset. The Euclidean distance threshold for the vectors belonging to the same person was 0.40 after the training was complete.

Finally, we trained a personality diagnostics neural network (NNPD), which was implemented as a multilayer perceptron (see Fig.  2 ). For that purpose, we used a training dataset (90% of the final sample) containing the questionnaire scores of 11,202 respondents and a total of 28,230 associated photographs. The NNPD takes the vector of the invariants obtained from NNCV as an input and predicts the Big Five personality traits as the output. The network was trained using the same hardware, and the training process took 9 days. The whole process was performed for male and female faces separately.

Data availability

The set of photographs is not made available because we did not solicit the consent of the study participants to publish the individual photographs. The test dataset with the observed and predicted Big Five scores is available from the openICPSR repository: https://doi.org/10.3886/E109082V1 .

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Acknowledgements

We appreciate the assistance of Oleg Poznyakov, who organized the data collection, and we are grateful to the anonymous peer reviewers for their detailed and insightful feedback.

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A.K., E.O., D.D. and A.N. designed the study. K.S. and A.K. designed the ML algorithms and trained the ANN. A.N. contributed to the data collection. A.K., K.S. and D.D. contributed to data pre-processing. E.O., D.D. and A.K. analysed the data, contributed to the main body of the manuscript, and revised the text. A.K. prepared Figs. 1 and 2. All the authors contributed to the final version of the manuscript.

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A.K., K.S. and A.N. were employed by the company that provided the datasets for the research. E.O. and D.D. declare no competing interests.

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The Big Five Model of Personality Traits

(a) conceptual and measurement contributions.

Each field needs a taxonomy, or general structural model, of its subject matter. Much of my research has focused on the development of a general taxonomy of personality traits--the Big Five. As I have argued, the field of personality research has for years struggled with the question of what are the most important personality traits to study. I have been centrally involved in the effort that has now led to the tentative, but general, acceptance of the so-called Big Five Model. Previously, the field of personality was fragmented, with no generally accepted paradigm or framework, and even the experts had to follow the hundreds of instruments and concepts competing for research attention. The Big Five taxonomy conceptualizes personality traits as broad and generalized trends in the individual's mental states, affective experience, and behavioral expression, and it offers an initial descriptive taxonomy that defines, at the broadest level of abstraction, five relatively distinct domains of important individual differences. For mnemonic ease, I refer to these five domains by the acronym OCEAN: Openness to new experience; Conscientiousness; Extraversion; Agreeableness; and Neuroticism .

Benet-Mar ti nez, V., & John, O. P. (1998).  Los Cinco Grandes across cultures and ethnic groups: Multitrait multimethod analyses of the Big Five in Spanish and English.  Journal of Personality and Social Psychology, 75 , 729-750.

John, O. P. (1990).  The "Big Five" factor taxonomy:  Dimensions of personality in the natural language and in questionnaires.  In L. Pervin (Ed.), Handbook of personality: Theory and research (pp. 66-100).  New York: Guilford Press.

John, O. P., Naumann, L. P., & Soto, C. J. (2008). Paradigm Shift to the Integrative Big-Five Trait Taxonomy: History, Measurement, and Conceptual Issues. In O. P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality: Theory and research (pp. 114-158). New York, NY: Guilford Press.

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 (2nd ed., pp. 102-138). New York: Guilford.

(b) Big Five development during childhood and during adulthood

In my earlier work, I have focused on the development of the Big Five personality traits in adolescence, using personality ratings of adolescents ages 12 to 16 obtained from their parents (Measelle, John, Ablow, Cowan, & Cowan, 2005). This age range is an important period of development during which major cognitive and ecological changes have been linked to changes in self-representational capacities. Three central questions guided this work. First, do young children show a coherent sense of their own personality, and if so, when? Second, do young children's self-perceptions of their personality show any stability across time? Finally, do self-perceptions of personality in young children show some degree of external validity so that we might conclude that they could have behavioral implications for their lives?

Children's self-reports did show levels of consistency and differentiation that approached those of a college age sample. Children's personality self-reports demonstrated significant temporal stability correlations across the 1- and 2-year longitudinal intervals. Substantial and increasing convergence was found between children's self-reports of Extraversion, Agreeableness, and Conscientiousness and conceptually relevant behavior ratings provided by mothers, fathers, and teachers. Children's self-reports of Neuroticism were unrelated to adults' reports but did predict sadness and anxious behavior observed in the laboratory. The results provide the beginnings of an account of how the Big Five dimensions begin to be salient and emerge as coherent, stable, and valid self-perceptions in childhood.  

Measelle, J. R., John, O. P., Ablow, J. C., Cowan, P. A., & Cowan, C. P. (2005). Can children provide coherent, stable, and valid self-reports on the Big Five dimensions? A longitudinal study from ages 5 to 7.  Journal of Personality and Social Psychology , 89 , 90-106.

In my other work, I have focused on adult development of personality, taking a life-span perspective. One of the yet unresolved questions in the field is whether personality is fixed and immutable during adulthood or whether it can develop and change as a function of experience, so that changes may occur naturally as the adult life context evolves and take different shapes. Some researchers, like Costa and McCrae, have taken a very strong, seemingly biological, stance, arguing that personality traits are essentially fixed (or "set in plaster") by age 30. Interestingly, most of Costa and McCrae's own data involve only samples of older adults, and our literature review (see below) found that they tend to ignore data collected by others that do not use the NEO-PI-R, their own and thus preferred personality measure. Thus, to our surprise, we found that although relevant data are available, compelling tests of their age-30 hypothesis have yet to be performed.

Indeed, our literature review covered large studies of mean-level change in personality characteristics measured with broadband personality inventories, and includes both cross-sectional and cross-cohort longitudinal research. (Helson, Kwan, John, & Jones, 2002). The results show considerable generalizability across samples, cohorts, and studies. In particular, people score higher with age on characteristics such as conscientiousness, agreeableness, and norm-adherence, and they score lower with age on the social vitality facets of Extraversion. These findings provide evidence that personality does change during adulthood and that these changes are non-negligible in size, systematic, not necessarily linear, and theoretically important. To account for these changes, we advance a contextual perspective that emphasizes life changes in roles, tasks, and goals (e.g., from being single in adolescence and early adulthood to child-rearing in middle adulthood).

We followed up this theoretical work and literature review with a large-scale study (Srivastava, John, Gosling, & Potter, 2003) comparing theories that make different predictions about how mean levels of personality traits change in adulthood. We were particularly interested in examining whether change on all of the Big Five dimensions stops or slows in middle adulthood, as predicted by Costa & McCrae's five-factor theory, or whether change is ongoing and differentiated, as predicted by contextualist theories.

As expected, Conscientiousness and Agreeableness increased throughout early and middle adulthood at varying rates; Neuroticism declined among women but did not change among men. Moreover, our comparisons of age differences before and after age 30 provided no support for the view that mean level change is limited to early adulthood (i.e., the pre-30s). Moreover, the variety in patterns of change suggests that the Big Five traits are complex phenomena subject to a variety of developmental influences. Most generally, we find life-long change at least to age 60 and, on average, the direction of change is toward greater maturity. This increasing maturity facilitates the individual mastering and performing effectively normative role expectations of adulthood, such as forming a stable couple bond that permits child-birth and child-rearing, as well as providing resources for one's off-spring—ultimate human life tasks that themselves have an evolutionary basis.

Helson, R., Kwan, V. S. Y., John, O. P., & Jones, C. (2002). The growing evidence for personality change in adulthood: Findings from research with personality inventories. Jo urnal of Research in Personality , 36 , 287-306.

John, O. P., Caspi, A., Robins, R., Moffitt, T. E., & Stouthamer-Loeber, M. (1994).  The "Little Five": Exploring the nomological network of the five-factor model of personality in adolescent boys.  Child Development , 65 , 160-1 78.

Soto, C. J., John, O. P., Gosling, S. D., & Potter, J. (2008). The developmental psychometrics of Big Five self-reports: Acquiescence, factor structure, coherence, and differentiation from ages 10 to 20. Journal of Personality and Social Psychology , 94 , 718-737 .

Srivastava, S., John, O. P., Gosling, S. D., & Potter, J. (2003). Development of personality in early and middle adulthood: Set like plaster or persistent change? Journal of Personality and Social Psychology , 84 , 1041-1053.

Big five personality traits and performance: A quantitative synthesis of 50+ meta-analyses

Affiliation.

• 1 Department of Psychology, University of North Carolina at Greensboro, Greensboro, North Carolina, USA.
• PMID: 34687041
• DOI: 10.1111/jopy.12683

Objective: The connection between personality traits and performance has fascinated scholars in a variety of disciplines for over a century. The present research synthesizes results from 54 meta-analyses (k = 2028, N = 554,778) to examine the association of Big Five traits with overall performance.

Method: Quantitative aggregation procedures were used to assess the association of Big Five traits with performance, both overall and in specific performance categories.

Results: Whereas conscientiousness yielded the strongest effect (ρ = 0.19), the remaining Big Five traits yielded comparable effects (ρ = 0.10, 0.10, -0.12, and 0.13 for extraversion, agreeableness, neuroticism, and openness). These associations varied dramatically by performance category. Whereas conscientiousness was more strongly associated with academic than job performance (0.28 vs 0.20), extraversion (-0.01 vs 0.14) and neuroticism (-0.03 vs -0.15) were less strongly associated with academic performance. Finally, associations of personality with specific performance outcomes largely replicated across independent meta-analyses.

Conclusions: Our comprehensive synthesis demonstrates that Big Five traits have robust associations with performance and documents how these associations fluctuate across personality and performance dimensions.

Keywords: Big Five; meta-analysis; performance; personality.

© 2021 Wiley Periodicals LLC.

• Extraversion, Psychological
• Meta-Analysis as Topic
• Neuroticism
• Personality Disorders
• Personality*

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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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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.

Before you continue, we thought you might like to download our three Strengths Exercises for free . These detailed, science-based exercises will help your clients realize their unique potential and create a life that feels energizing and authentic.

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.

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?
• American Psychological Association. (2017). Personality. Retrieved from http://www.apa.org/topics/personality/
• Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta‐analysis. Personnel Psychology, 44 (1), 1-26.
• Boyce, C. J., Wood, A. M., & Powdthavee, N. (2013). Is personality fixed? Personality changes as much as “variable” economic factors and more strongly predicts changes to life satisfaction. Social Indicators Research, 111, 287-305.
• Costa, P. T., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI): Professional manual . Psychological Assessment Resources.
• Costa, P. T., & McCrae, R. R. (2008). The revised NEO personality inventory (NEO-PI-R). In G. J. Boyle, G. Matthews, & D. H. Saklofske (Eds.), The SAGE handbook of personality theory and assessment: Vol. 2 . Personality measurement and testing (pp. 179-198). Sage Publications.
• Douglas, H. E., Bore, M., & Munro, D. (2016). Openness and intellect: An analysis of the motivational constructs underlying two aspects of personality. Personality and Individual Differences, 99 , 242-253.
• 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.
• Judge, T. A., Higgins, C. A., Thoresen, C. J., & Barrick, M. R. (1999). The Big Five personality traits, general mental ability, and career success across the life span. Personnel Psychology, 52 , 621-652.
• Judge, T. A., Erez, A., Bono, J. E., & Thoresen, C. J. (2002). Are measures of self-esteem, neuroticism, locus of control, and generalized self-efficacy indicators of a common core construct? Journal of Personality and Social Psychology, 83, 693-710.
• Judge, T. A., & Ilies, R. (2002). Relationship of personality to performance motivation: A meta-analytic review. Journal of Applied Psychology, 87, 797-807.
• Lebowitz, S. (2016a). The ‘Big 5’ personality traits could predict who will and won’t become a leader. Business Insider. Retrieved from http://www.businessinsider.com/big-five-personality-traits-predict-leadership-2016-12
• Lebowitz, S. (2016b). Scientists say your personality can be deconstructed into 5 basic traits. Business Insider. Retrieved from http://www.businessinsider.com/big-five-personality-traits-2016-12
• McLeod, S. (2007). Maslow’s hierarchy of needs. Simply Psychology. Retrieved from https://www.simplypsychology.org/maslow.html
• Ones, D. S., Viswesvaran, C., & Reiss, A. D. (1996). Role of social desirability in personality testing for personnel selection: The red herring. Journal of Applied Psychology, 81 , 660-679.
• Ozer, D. J., & Benet-Martinez, V. (2006). Personality and the prediction of consequential outcomes. Annual Review of Psychology, 57 , 401-421.
• Revelle, W. (2013). Personality theory and research. Personality Project. Retrieved from https://www.personality-project.org/index.html
• Roccas, S., Sagiv, L., Schwartz, S. H., & Knafo, A. (2002). The Big Five personality factors and personal values. Personality and Social Psychology, 28, 789-801.
• Schaefer, P. S., Williams, C. C., Goodie, A. S., & Campbell, W. K. (2004). Overconfidence and the Big Five. Journal of Research in Personality, 38 , 473-480.
• Schmitt, D. P., Allik, J., McCrae, R. R., Benet-Martinez, V., Alcalay, L., Ault, L., …, &  Zupanèiè, A. (2007). The geographic distribution of Big Five personality traits: Patterns and profiles of human self-description across 56 nations.  Journal of Cross-Cultural Psychology, 38 , 173-212.
• Schretlen, D. J., van der Hulst, E., Pearlson, G. D., & Gordon, B. (2010). A neuropsychological study of personality: Trait openness in relation to intelligence, fluency, and executive functioning. Journal of Clinical and Experimental Neuropsychology, 32, 1068-1073.
• 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.

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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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

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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

The Big Five model of personality, also known as the Five Factor Model (FFM), is a framework that outlines five core dimensions of personality. Based on decades of personality research and validity tests across the world, the Five Factor Model is the most commonly accepted theory of personality today. The five dimensions represent broad categories designed to capture much of the individual variation in personality and were determined by analyzing and grouping common adjectives used to describe peopleÕs personality and behavior. The Five Factor Model is also commonly referred to using the acronyms OCEAN and CANOE.

View All Term Definitions

Breakdown by Domain

Key features, context & culture.

• Originally developed through a lexical analysis of English terms, research has also been conducted in Chinese, Czech, Dutch, German, Greek, Hebrew, Hungarian, Italian, Polish, Russian, Spanish, Tagalog, Turkish, and more
• Research suggests the Big Five traits capture much of the variability in personality across cultures; however, languages other than English often produce additional important traits and there is some evidence to suggest that ÒopennessÓ in particular may be understood differently across cultures (e.g., intellect vs. rebelliousness)

Developmental Perspective

• Research on the validity of the Big Five traits has been conducted with all ages, but primarily with adults
• Research has shown that while relatively stable, traits develop and change with age
• No learning progression provided

Associated Outcomes

• Evidence suggests personality traits are correlated with life outcomes such as educational attainment, health, and labor market outcomes

Available Resources

Support materials.

• No materials provided

Programs & Strategies

• No programs or strategies provided

Measurement Tools

Personality traits are often measured through questionnaire scales such as:

• NEO Personality Inventory (NEO-PI-R)
• Big Five Inventory (BFI)
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• John, O.P., Naumann, L.P., & Soto, C.J. (2008), Paradigm Shift to the Integrative Big Five Trait Taxonomy in Handbook of Personality: Theory and Research, 114-156.
• McCrae, R. R. and John, O. P. (1992), An Introduction to the Five?Factor Model and Its Applications. Journal of Personality, 60: 175-215.

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To create a model of personality that encompasses as much variation in personality as possible using a manageable number of dimensions

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The Five Factor Model serves as a unifying taxonomy in the field of personality research; it is widely used in many countries throughout the world

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How Universal Is the Big Five? Testing the Five-Factor Model of Personality Variation Among Forager–Farmers in the Bolivian Amazon

Michael gurven.

Department of Anthropology, University of California, Santa Barbara

Christopher von Rueden

Maxim massenkoff, hillard kaplan.

Department of Anthropology, University of New Mexico

Marino Lero Vie

Tsimane Health and Life History Project, San Borja, Beni, Bolivia

Associated Data

The five-factor model (FFM) of personality variation has been replicated across a range of human societies, suggesting the FFM is a human universal. However, most studies of the FFM have been restricted to literate, urban populations, which are uncharacteristic of the majority of human evolutionary history. We present the first test of the FFM in a largely illiterate, indigenous society. Tsimane forager–horticulturalist men and women of Bolivia ( n = 632) completed a translation of the 44-item Big Five Inventory ( Benet-Martínez & John, 1998 ), a widely used metric of the FFM. We failed to find robust support for the FFM, based on tests of (a) internal consistency of items expected to segregate into the Big Five factors, (b) response stability of the Big Five, (c) external validity of the Big Five with respect to observed behavior, (d) factor structure according to exploratory and confirmatory factor analysis, and (e) similarity with a U.S. target structure based on Procrustes rotation analysis. Replication of the FFM was not improved in a separate sample of Tsimane adults ( n = 430), who evaluated their spouses on the Big Five Inventory. Removal of reverse-scored items that may have elicited response biases produced factors suggestive of Extraversion, Agreeableness, and Conscientiousness, but fit to the FFM remained poor. Response styles may covary with exposure to education, but we found no better fit to the FFM among Tsimane who speak Spanish or have attended school. We argue that Tsimane personality variation displays 2 principal factors that may reflect socioecological characteristics common to small-scale societies. We offer evolutionary perspectives on why the structure of personality variation may not be invariant across human societies.

The five-factor model (FFM) is a widely accepted construct describing personality variation along five dimensions (i.e., the Big Five): Extraversion, Openness, Conscientiousness, Neuroticism, and Agreeableness. Many researchers have argued that the structure of the FFM is a “biologically based human universal” that transcends language and other cultural differences ( Bouchard & Loehlin, 2001 ; McCrae & Costa, 1997 ; Wiggins & Trapnell, 1997 ; Yamagata et al., 2006 ). Cross-cultural tests of the FFM in over 50 societies across six continents have supported the existence and universality of the FFM ( McCrae, 2002 ; McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005 ; Schmitt et al., 2007 ). A universal structure suggests uniform covariance among traits in humans despite vastly different culture, history, economy, social life, ideology, and every other form of cultural and behavioral expression. The Big Five structure is even notable in captive chimpanzees, based on ratings by zoo employees ( King & Figueredo, 1997 ).

Despite the increasing consensus supporting the FFM, a five-factor structure does not robustly emerge everywhere, and some researchers have posited more than five personality factors within certain populations (e.g., Cheung & Leung, 1998 ; Lee & Ashton, 2004 ); however, these additional factors can often be subsumed under one of the Big Five factors ( Guanzon-Lapeña, Church, Carlota, & Katigbak, 1998 ). Thus, the FFM has yet to be robustly falsified, at least in literate, industrialized societies. If the FFM is a human universal and represents a “solid beginning for understanding personality everywhere” ( McCrae & Costa, 1997 , p. 515), it should replicate everywhere and under a broad range of environments and populations. To date, the FFM has yet to be tested in an indigenous, preliterate society. The vast majority of samples from cross-cultural studies are often urban students, glibly referred to as western, educated, industrialized, rich, democratic (WEIRD) populations ( Henrich, Heine, & Norenzayan, 2010 ). Despite the wide range of cultures and languages where the FFM has been tested, WEIRD populations might show a similar personality structure if trait covariance is an artifact of living in large urban, literate populations. There are important reasons for assessing the validity of the FFM in an indigenous, preliterate society. First, human psychological adaptations likely evolved in the ancestral context of a hunting and gathering lifestyle with a social life characterized by frequent face-to-face interactions, largely with kin. Although pure hunter–gatherers are exceedingly rare, many groups maintain traditional lifestyles and share many social and economic characteristics with hunter–gatherers. Testing the FFM in these populations would be particularly valuable for assessing the universality of the FFM. In the past, empirical patterns observed in WEIRD populations and assumed to be human universals have been contradicted (or at least qualified) by observations in small-scale societies ( Henrich et al., 2010 ). To date, no test of the FFM has ever been conducted among a small-scale population of foragers, farmers, or herders.

Second, the existence of the FFM is an inductively derived success of personality psychology, but to date, no extensive theory exists that can generate the FFM from first principles. There are no a priori reasons for expecting a particular number of trait dimensions or within-trait and intertrait correlations, although post hoc explanations of empirical regularities have been made (e.g., Denissen & Penke, 2008 ; Nettle, 2010 ). Thus, when the FFM receives less consistent support, as in several non-Western countries (e.g., Piedmont, Bain, McCrae, & Costa, 2002 ; Schmitt et al., 2007 ; Triandis, 1997 ), a common response from FFM advocates is to argue that methodological issues prevent FFM replication. However, without a comprehensive theory of personality formation, it is unclear whether different socioecological environments should generate veritable differences in personality structure in the first place. Are the tenuous results in non-Western societies genuine or artifactual?

We provide the first test of personality structure among an indigenous, largely illiterate population: the Tsimane forager– horticulturalists of lowland Bolivia. We use a Spanish translation of the Big Five Inventory, a widely used metric of the FFM first developed by Benet-Martínez and John (1998) . Our null prediction is that the Big Five should replicate in the Tsimane population. If certain features, such as literacy and education, are important for generating the Big Five pattern, we might find that the Big Five does not replicate among Tsimane. However, we should expect to find the Big Five structure to replicate among more educated and literate Tsimane. We test the validity of the five-factor model by assessing (a) internal reliability of each factor, (b) external validity of the factors, (c) 1-year test–retest factor correlations, (d) whether the FFM is generated from exploratory factor analysis, (e) whether confirmatory factor analysis supports the FFM, and (f) whether Procrustes rotation to a U.S-based sample indicates similar FFM structure. We determine whether the FFM is better replicated with (g) stratification of the sample into subgroups that might differ in familiarity with testing procedures, performance, and self-reflection (age, sex, schooling, and Spanish fluency), (h) selective removal of least internally consistent items, (i) selective removal of items that evidence socially desirable responding (i.e., highly positive or negative response scores), (j) correction for acquiescence bias (i.e., a tendency of subjects to affirm personality descriptors read to them), or (k) evaluation of a separate sample of subjects asked to evaluate the personality of their spouses. Peer-reported personality may improve internal reliability of the Big Five ( McCrae et al., 2005 ).

Despite our rigorous set of tests and analyses, we do not find strong, consistent support for the Big Five. We instead find evidence of factor structure consistent with a “Big Two” oriented around prosociality and industriousness. Our findings put the universality of the FFM into question but, more important, heighten the need to develop models of how low-order traits should be coordinated to assemble into higher order factors, given cultural and socioecological variability.

The paper is organized into five sections. Section 1 provides an overview of cross-cultural studies of the FFM in order to contextualize the value of the current study. Section 2 briefly describes the Tsimane population. Section 3 discusses our methods, and Section 4 presents our results. Section 5 interprets our results and discusses personality and the FFM in small-scale indigenous societies.

Cross-Cultural Studies of the Big Five

The FFM has been assessed with both etic and emic approaches. In etic studies, a previously identified personality structure is applied in a different culture or context; in emic approaches, a personality structure is indigenously derived with a sampling of the target culture’s personality descriptors.

The FFM was derived in English using a lexical (emic) approach, which assumes that all relevant personality descriptors are found in a group’s vocabulary ( Digman, 1990 ; Goldberg, 1990 ; John, 1990 ). Although early research in personality structure yielded many competing constructs to describe personality variation, the FFM has emerged as the most widely accepted model ( Peabody & De Raad, 2002 ). The FFM has since been tested in many countries and in numerous languages with the Revised NEO Personality Inventory (NEO-PI–R) ( Costa & McCrae, 1992 ) and the Big Five Inventory (BFI) ( Benet-Martínez & John, 1998 ) protocols. Even a nonverbal protocol has confirmed the generalizability of the FFM in cross-cultural context ( Paunonen, Ashton, & Jackson, 2001 ).

Across cultures, etic studies have generally replicated the FFM (NEO-PI–R: McCrae, 2002 ; BFI: Schmitt et al., 2007 ), and factor scales show high internal reliability; however, Extraversion and Agreeableness are sometimes sensitive to “cultural effects” and are not always clearly differentiated ( Ortiz et al., 2007 ; Rolland, 2002 ). As a result, McCrae, Costa, Del Pilar, Rolland, and Parker (1998) have suggested that a universal FFM consists of the first three factors and an “interpersonal circumplex”—which subsumes elements of Extraversion and Agreeableness factors based on Procrustes analysis ( Rolland, 2002 ).

Among emic studies, an Openness factor is not consistently extracted ( De Raad, 1994 ; Di Blas & Forzi, 1998 ; Szirmák & De Raad, 1994 ). Furthermore, several emic studies have consistently yielded more than five factors ( Almagor, Tellegen, & Waller, 1995 ; Benet-Martínez & Waller, 1997 ). In China, Cheung and Leung (1998) have identified a “tradition” factor independent of the Big Five. However, results from emic studies do not always match the results from etic studies of the same population. For example, in Italy, studies using translated inventories have identified a Neuroticism factor ( Caprara, Barbaranelli, Borgogni, & Perugini, 1993 ; Perugini & Leone, 1996 ), but emic studies have not ( Caprara & Perugini, 1994 ; Di Blas & Forzi, 1998 ). Openness and Neuroticism are more robustly established in etic studies than in emic studies, which has led to a growing consensus that lexical approaches underlying emic studies are not comprehensive ( Church & Lonner, 1998 ; Rolland, 2002 ). As McCrae and Costa (1997) concluded, “It is simply not the case that all personality traits are encoded as adjectives … lexical studies confound differences in personality structure with differences in personality language” (p. 510).

In cross-cultural studies, reliability of the FFM has been highest in developed countries. In Allik and McCrae (2004) and Schmitt et al. (2007) , sample populations were predominantly college students and were often bilingual. In developing countries, the FFM has met with less success; whether this is due to methodological problems or to actual differences in personality structure remains to be determined. Methodological differences may arise due to translations not being equivalent, lack of item relevance in the local culture, differences in subject response styles, unfamiliarity with the test format, and unrepresentative samples ( Paunonen & Ashton, 1998 ).

In Schmitt et al. (2007) , internal consistency of factor items based on Cronbach’s alpha was sufficiently high in South American samples, with each country averaging above the standard benchmark of 0.70. However, several African countries fared worse: Average Cronbach’s alphas for Morocco, Tanzania, Ethiopia, and Congo were 0.62, 0.59, 0.48, and 0.48, respectively. Despite low internal consistency, the African and South American samples showed high levels of congruence with the American normative factor structure under Procrustes rotation ( Schmitt et al., 2007 ). However, of the seven countries in Africa reported in Schmitt et al. (2007) , six were administered the BFI in English, and four had samples restricted to college students. Similarly, the five South American countries in the study (including Bolivia) contained only college students.

Reliability is sometimes improved in studies that rely on third-party observer reports rather than self-reports. In a large cross-cultural study of this type in 50 different societies, McCrae et al. (2005) asked college students to give observer ratings on the NEO-PI–R for persons of all ages they knew well. Roughly 5% of the Cronbach alphas were lower than 0.70, with this 5% concentrated primarily in the samples from developing countries. Although relying on observer ratings helped improve internal consistency, it did not eliminate potential problems of evaluative bias common to self-report data in developing societies. For example, Openness did not cleanly emerge in Nigeria. McCrae et al. (2005) concluded that “it is possible that there is a minority of cultures in which the [FFM] structure is not found” (p. 552).

To our knowledge, only two studies have focused explicitly on ethnic populations in the developing world. Piedmont et al. (2002) tested the NEO-PI–R among the Shona, a sub-Saharan society in Zimbabwe. Within this mixed rural and suburban sample (predominantly college students bilingual in English and their native Shona), the average internal consistency for the five factors was 0.77, higher than for the African samples in Schmitt et al. (2007) . However, Openness produced a low reliability of 0.64, and only five of the 30 NEO-PI–R facets produced reliabilities above 0.60. Factor congruence with the American normative structure was high at 0.89, but only 15 facets produced congruence coefficients higher than 0.90. These results were obtained with the Shona language version of the NEO-PI–R; the English version of the test showed slightly higher reliability and congruence. Schmitt et al. identified translation problems as the main factor contributing to the less than ideal fit to the FFM: The Shona language lacks words equivalent to some of the English terms in the NEO-PI–R.

Alvergne, Jokela, and Lummaa (2010) administered the English Mini-Markers Big Five Inventory ( Thompson, 2008 ) in four agricultural Senegalese communities, among individuals with diverse ages and with low levels of education. The subsistence focus on cash cropping and the low fertility rate (5 births per woman) are not characteristic of more traditional human societies lacking agriculture and practicing natural fertility. The sample size was quite small ( n = 65 families), and the Mini-Markers Inventory used has not been validated among non-English speakers. After removal of hard-to-translate items and further shortening of the survey for brevity, the administered version of the BFI included only 27 items. Alvergne et al. retained about half of those items for analysis, with most factors based on only two or three adjectives. Reliability among these factors was still low, averaging 0.64.

Study Population

The Tsimane are forager–horticulturalists of central lowland Bolivia, located along the Maniqui, Quiquibey, Apere, and Matos Rivers and in adjacent forests of the Beni Department. Although families may spend weeks or months on hunting or fishing trips or cultivate fields some distance from their primary house in settled villages, the Tsimane are semisedentary and live in communities ranging from 30 to 500 individuals. Their population is estimated at 10,000 and is dispersed among over 90 villages. They cultivate plantains, rice, corn, and sweet manioc in small swiddens and regularly fish and hunt for meat. These foods together provide over 90% of the calories in the diet, with the remainder coming mainly from trade with itinerant merchants. Polygyny occurs at low frequencies (~5%) and is concentrated in more remote communities ( Gurven, Winking, Kaplan, von Rueden, & McAllister, 2009 ). Exclusive priority of access for individuals or small groups to certain rights and resources is minimal, but land close to village centers is de facto privately owned. More extensive ethnographic background can be found in Chicchón (1992) , Huánca (1999) , and Schniter (2009) .

Since the mid-20th century, the Tsimane have come into greater contact with modernizing influences. In Tsimane villages, especially those located near the town of San Borja (population ~25,000), incipient cattle ownership, wage labor with loggers and farmers, and produce sales to local markets are on the rise. Many Tsimane now have minimal access to health care through the services of a health post, a hospital in San Borja, and the Tsimane Health and Life History Project, but mortality rates remain high, particularly among infants. Approximately 20% of offspring never reach age 5 ( Gurven, Kaplan, & Zelada Supa, 2007 ). The Tsimane rarely use modern contraceptives; the total fertility rate is very high (~9 births per woman), and so the population growth rate is high (3.6% per year). Many Tsimane villages now have access to public schooling for their children taught largely by bilingual Tsimane teachers trained by local missionaries. Several secondary schools now exist in larger villages, and young Tsimane adults are starting to become high school graduates. However, the overall adult literacy rate remains low, at 25%. Fluency in the native Tsimane language is universal, and only 40% of adults are moderately fluent in Spanish. The Tsimane language is an isolate, together with Mosetene, and it is unrelated to the dominant indigenous languages of Bolivia.

Tsimane live in extended family clusters, within which occur the majority of food and labor sharing. Although social and cooperative in daily interactions with village co-residents, Tsimane families value their autonomy. Groups of family clusters compose villages, which were given formal geographic boundaries only in the late 20th century and lack a strong sense of identity ( Gurven, Zanolini, & Schniter, 2008 ). Village residents elect chiefs to organize community meetings and to represent their interests to outside political bodies, but chiefs lack any substantial authority, tend to have short tenure, and often are unable to effectively organize people for collective action ( Gurven & Winking, 2008 ; von Rueden, Gurven, & Kaplan, 2008 ). In the event of interpersonal conflict, Tsimane often “vote with their feet” by moving to other villages.

Tsimane often describe each other in valent terms, with judgments of good ( jäm’si ) and bad ( jam jäm’si or a’chis ) applying to numerous domains. Maintaining friendly relations ( jäm’yity muntyi ), being easygoing ( chuchuijtyi ), and avoiding direct confrontation and expression of anger ( chij facoij ) are viewed as proper ways of behaving and are ingrained in Tsimane culture. In their descriptions of others, Tsimane recognize the persistence of particular traits in individuals over time. Someone who speaks freely ( chij peyaquity ) but not too much or in a gossiping way ( chij peyacsity ) is a valued social partner, and jokesters are also recognized and viewed positively ( chij shevinyity ). Happy, cheerful individuals ( majoijbäyis ) are contrasted with serious, quiet individuals ( futy’dyety ) or those who are easily annoyed ( achiyity ). Other negative traits commonly described refer to those who react rapidly, usually in a bad way ( che’chei’si ), those who brag ( va’bunyis ), and those who are lazy ( shoyijyi’tyi or jamyedyedyetyi ). Laziness is often contrasted with demonstration of strong work effort ( setyi or chij carijtaqui ) and generosity in helping others ( chij notacsity ).

We administered a personality questionnaire based on the Big Five Inventory (BFI), a widely used 44-item metric of the five-factor model. The Spanish version of the BFI, previously validated by Benet-Martínez and John (1998) , was translated into the Tsimane language by two bilingual Tsimane research assistants (Marino Lero Vie [MLV] and Feliciano Cayuba Claros) and Michael Gurven (MG). As a test of the accuracy of the translation, the Tsimane questionnaire was then back-translated into Spanish by a different translator, and discussions among the three bilingual Tsimane and MG ensued until a workable translation was found that captured the essence of each item. Due to limitations of Tsimane vocabulary, several items required a definitional phrase in the local idiom rather than relying on a single word to capture the right meaning. In these cases, either an exact word did not exist or, taken out of context, the word could be misconstrued. For example, Item 31 (“is clever and analytical”) was translated as Mi buty chij cave'jedye judyeya jäm' yu' ban mi (literally, “Knows how to ‘see’ things and can make things turn good”), because the Tsimane word for “smart” reflects the state of being knowledgeable. Item 32 (“radiates enthusiasm”) was translated as Mi buty fer ma'je' ji'cave' jun'si chuc mi ma'je (literally, “You really show to others whatever it is you want” [to show]) because there are no Tsimane words for “radiate” or “enthusiasm.” Due to the lack of any word for “art” in Tsimane, Item 44 (“few artistic interests”) was translated more descriptively as “someone who does not like to play music, sing, tell stories, or draw.” Those are the main forms of artistic expression in Tsimane society. When necessary, translating the whole concept rather than the literal words enabled us to circumvent translation problems reported by other cross-cultural studies of the FFM (e.g., Piedmont et al., 2002 ). Only one item from the original BFI was removed (Item 30: “has an active imagination”) due to the inability to find a suitable expression to explain the concept in a manner that was consistently understood by Tsimane subjects. This item, alone among the BFI items, was found to be understood differently by bilinguals when presented in Spanish versus English, suggesting it should be revised or omitted from the BFI in the context of cross-cultural studies ( Ramírez-Esparza, Gosling, Benet-Martínez, Potter, & Pennebaker, 2006 ). Thus, the final Tsimane BFI instrument includes 43 items.

The Tsimane BFI was administered to 632 adults from 28 villages during the period January 2009 to December 2010. The sample was 48% female, the average age was 47 years (range = 20–88 years, SD = 14.4), and the average years of formal education was 1.2 years (range = 0–12 years, SD = 2.2). The age, years of formal education, and Spanish proficiency of all subjects were ascertained from demographic interviews (see Gurven et al., 2007 ). The Tsimane BFI was conducted verbally in a private location by a bilingual Tsimane research assistant (MLV) trained in the administration of anthropological and psychological interviews. As in the English version of the BFI, responses were given on a translated scale where 1 corresponds to strongly disagree and 5 corresponds to strongly agree . Subjects were first given a quick tutorial and comprehension test on the use of the scale, after which all subjects showed clear evidence of understanding the scale and the task at hand. The scale, depicted on a piece of cardboard placed in front of the subject, included drawings to help facilitate understanding. Five drawings of a person accompanied the five numbers on the scale; the drawings revealed more and more of the person as the scale ascended: a drawing of just a person’s legs accompanied 1 and a drawing of the whole body accompanied 5. Although many respondents were previously unfamiliar with Likert-type scales, few were new to formal interviews because of their extensive participation in the Tsimane Health and Life History project we have maintained continuously since 2002 (see http://www.unm.edu/~tsimane/ ). Indeed, our decade-long presence in the area has helped to establish trusting, collaborative relationships among study subjects.

After the interview, MLV used the same 5-point scale to rate respondents on four variables based on his observations during the fifteen or so minutes of the BFI interview together with an additional 30 minutes spent conducting a separate interview (on economic production and sharing): the extent to which the subject was talkative, shy, smiling and/or joking, and easily distracted. These were added to help gauge external validity of the FFM instrument. MLV performed multiple test runs in order to ensure consistency in his observations.

None of our interviews produced missing items. Thirty-four subjects (53% female) were interviewed twice, each interview roughly a year apart (average 14.2 ± 2.6 months), providing a test of response stability. The average age of this subsample is 52 years.

In addition to conducting our first-person interviews, we asked 430 Tsimane adults to rate their spouses on the Tsimane BFI. These interviews were conducted during the period from March 2011 to February 2012. The sample of spouses who were rated was 50% female, and the average age was 52 years (range = 16–89 years, SD = 11.6). The protocol did not differ from the self-report protocol except that with each item of the BFI verbalized to the raters, subjects were reminded to evaluate their spouse. The self-report and spouse-report samples overlap for 66 individuals (46% female; average age = 52 years). Although the spouse-report sample by definition excludes unmarried individuals, we do not expect significant differences across the samples due to marital status: Only 26 of the 632 adults in the self-report sample were single at the time of data collection.

Internal Reliability

We first test the reliability of each of the Big Five factors. The Cronbach’s alpha measures of internal reliability, factor means, ranges, and standard deviations are given in Table 1 . All items phrased in reverse (e.g., the Extraversion item “is shy”) were reverse scored prior to calculation of these statistics. Although the distributions of subjects’ scores on the Big Five factors do not conform to a normal distribution according to the Shapiro–Wilk test, the distributions do not exceed skew or kurtosis values of ± 1. Extraversion, Agreeableness, Conscientiousness, and Openness show moderate internal reliability (Cronbach’s α = 0.63, 0.58, 0.69, and 0.54, respectively), and Neuroticism shows low reliability (0.31).

Mean Response Score, Score Ranges and Standard Deviations, and Internal Reliability (Cronbach’s Alpha) for the Five Factors

Internal Reliability by Age, Sex, Education, and Spanish Fluency

We next examine whether internal reliability differs by age, sex, formal education, and Spanish fluency. If schooled adults are more familiar with testing and if Spanish speakers are more familiar with other ideas and cultures in a way that may promote self-reflection, then their item responses within factors might be more consistent than responses from unschooled or monolingual Tsimane speakers. Subjects were divided into several subgroups: those older and younger than 44 years (the median age), men and women, those with and without any formal schooling, and those who do or do not speak Spanish. Although internal reliability of several of the Big Five improves within particular subgroups, no subgroup shows consistent improvement across all of the Big Five (see Table 2 ). Averaged across the Big Five, differences in reliability between complementary subgroups (e.g., old vs. young) were close to zero. Extraversion and particularly Openness show higher internal reliability among men, the young, the educated, and those who speak Spanish. Agreeableness and Conscientiousness produce the opposite result.

Internal Reliability Based on Cronbach’s Alpha for Subgroups of Self-Report Sample

Removing Potentially Problematic Items and Correcting for Acquiescence Bias

We consider the possibility that despite our efforts at repeated translation and back-translation, certain items may still have been interpreted differently by subjects from their intended meaning. If certain items are driving the low reliability scores, we might expect them to load weakly on each factor. In an attempt to address this potential problem, we first drop the least reliable item (i.e., the item whose removal would most increase factor internal reliability) from each of the Big Five and recalculate Cronbach’s alpha. Extraversion and Conscientiousness now surpass the standard benchmark of 0.70, and internal reliability for Agreeableness and Openness improve but remain suboptimal. The reliability for Neuroticism remains quite low even after removal of the least reliable item (see Table 1 ). The least internally reliable items include, for Agreeableness, Item 22 (“is sometimes ill-mannered with others”); for Conscientiousness, Item 42 (“gets distracted easily”); for Extraversion, Item 6 (“is reserved”); for Neuroticism, Item 35 (“remains calm in difficult situations”); and for Openness, Item 12 (“likes routine”). Further removal of the weakest remaining item from each factor did not bring Agreeableness, Neuroticism, or Openness to acceptable levels of reliability.

The first and second least reliable items within each of the Big Five are all items that are reverse scored. This suggests these items may have been differentially susceptible to socially desirable responding. Alternatively, a low covariation among true- and reverse-scored items within each of the Big Five could arise through acquiescence bias, which is any tendency of individuals to respond affirmatively to questions posed them. We remove all reverse-scored items and recalculate Cronbach’s alpha for each of the Big Five. This eliminates 16 of the 43 items. Agreeableness, in addition to Extraversion and Conscientiousness, now produces acceptable internal reliability. The reliabilities for Neuroticism and Openness remain low (see Table 1 ).

We next assess internal reliability by removing other items that may have prompted socially desirable responding. These are items with high or low mean response values. Given the self-report nature of the BFI instrument, especially to a third-party (albeit neutral) Tsimane assistant, it may be that an individual less familiar with interviews (a) is uncomfortable conveying self-ratings for traits deemed highly negative or (b) gives biased responses for highly positive traits when speaking to another Tsimane (or even to him- or herself). We therefore remove items with mean response scores less than two or greater than four. This eliminates nine of the 43 items: two with strong disagreement (Item 2: “tends to be critical”; Item 13: “starts disputes with others”) and seven with strong agreement (Item 3: “is meticulous about work”; Item 10: “has diverse interests”; Item 11: “energetic”; Item 23: “is inventive”; Item 26: “worries about things”; Item 35: “maintains calm in difficult situations”; Item 37: “is considerate and friendly with everyone”). This exercise modestly increases internal reliability for Neuroticism yet decreases reliability for Agreeableness, Openness, Extraversion, and Conscientiousness (see Table 1 ). Thus, with this manipulation, none of the Big Five surpass a Cronbach’s alpha score of 0.70. It is noteworthy to mention that for at least five of these eliminated items, means distant from 3 are unsurprising and mesh with our expectations based on 12 years of experience living with Tsimane.

Finally, we attempt to correct for acquiescence bias not by removing problematic items but according to the method described in Hofstee, Ten Berge, and Hendriks (1998) . First, we average the response scores for each subject for 15 BFI item pairs with opposite implications for personality ( Soto, John, Gosling, & Potter, 2008 ). Second, we generate an acquiescence index by calculating the difference between each average and the scale midpoint. Third, we subtract each subject’s acquiescence score, whether positive or negative, from his or her responses. The average acquiescence score across the 632 subjects is 0.23 ( SD = 0.29), which is 5.84% of the scale range. Acquiescence in Western subjects is of a similar magnitude: Rammstedt, Goldberg, and Borg (2010) reported an average acquiescence score on the BFI of 0.11 ( SD = 0.28) for German adults with a high degree of formal education and an average score of 0.25 ( SD = 0.38) for those with little or no formal education. Among the Tsimane, correction for acquiescence bias generates acceptable internal reliability only for Conscientiousness. Internal reliability decreases significantly for Openness (see Table 1 ).

External Validity

The Big Five are correlated in expected directions with observed characteristics of subjects during interviews (see Table 3 ). Extraversion, Agreeableness, Conscientiousness, and Openness are positively correlated with smiling and negatively correlated with shyness. They also positively correlate with talkativeness and negatively correlate with distractedness, but the effect sizes are smaller. Neuroticism is positively correlated with the respondent’s shyness and negatively correlated with smiling.

Spearman Correlations of the Five Factors With Subjects’ Observed Characteristics (Self-Report Sample)

Response Stability

Test and retest responses were collected about a year apart from 34 subjects. The Tsimane average retest correlation (Spearman’s rho) is 0.431 and ranges from 0.274 ( p = .116, two-tailed) for Agreeableness, 0.370 ( p = .031) for Neuroticism, 0.420 ( p = .013) for Openness, 0.466 ( p = .005) for Conscientiousness, to 0.627 ( p < .001) for Extraversion.

Correlations Between Factors

Spearman correlations among the Big Five are presented in Table 4 . All correlations are significant at the 1% level. Neurotic individuals are less likely to be extraverted, agreeable, open, and conscientious. All other associations among other factors are positive. Extraversion is especially highly correlated with each of the other Big Five.

Spearman Correlations Between Factors (Self-Report Sample)

Note . All correlations are significant at p < .01 level.

Exploratory Factor Analysis

We perform an exploratory factor analysis (EFA) using varimax rotation and principal-components extraction to test whether our 43 BFI items inductively organize into the familiar Big Five. The unrestricted EFA results in 11 components with eigenvalues greater than one, and the eigenvalues decrease sharply after the first component (see Figure 1 ).

Scree plots for unrestricted exploratory factor analysis (self-and spouse-report samples).

Before factor rotation, the first factor explains 20.8% of the variance in the data, and the second factor explains only 5.2% of the variance. After factor rotation, this disparity is attenuated: The first factor explains 13.2% of the variance, the second explains 9.8%, and the third through fifth factors explain approximately 4.0% of the variance each. The rotated component matrix shows considerable cross-loading of items from the BFI, with no clear replication of any Big Five factor (see Table S1 of the supplemental materials ). Only the first and second factors are well defined based on the intercorrelations of items that load the highest on each factor. Cronbach’s alpha is 0.88 for the first factor, 0.83 for the second factor, and < 0.55 for subsequent factors in the unrestricted EFA. Restricting the EFA output to five factors does not noticeably improve replication of the Big Five (see Table 5 ).

Rotated Component Matrix Restricted to Five Factors (Self-Report Sample)

Note . Bolded numbers indicate on which factor items load the highest.

Stipulating a five-factor structure, we perform several EFAs with different subsets of the BFI items, with different subject subgroups, and with the data corrected for acquiescence bias. We (a) remove the 16 reverse-scored items; (b) remove items that may have prompted socially desirable or norm-conforming responses, as determined by item mean response scores of more than four or less than two; (c) transform the data to account for subjects’ degree of acquiescence bias; and (d) split the data by sex, age, schooling, and Spanish fluency. None of these manipulations clearly indicate a Big Five factor structure as determined by the rotated component matrices (see Tables S2–S12 of the supplemental materials ), and all exhibit a large first component that, prior to factor rotation, explains on average 3.2 times more of the variance in the data than the second component. Most Extraversion items load highly on the first derived factor, in addition to items from each of the other Big Five. Comparison of the items composing the derived factors ( Tables 5 , S2–S12 ) reveals a similar personality structure across most EFA subsets. Removing reverse-scored items ( Table S2 ) and correcting for acquiescence ( Table S4 ) produce factors suggestive of Agreeableness and Conscientiousness. However, many of the Agreeableness and Conscientiousness items continue to load highly on more than one factor. An EFA restricted to true-scored items from Extraversion, Agreeableness, and Conscientiousness comes closer to replicating those factors (see Table S13 of the supplemental materials ).

Confirmatory Factor Analysis

We use maximum likelihood estimation to test the fit of the self-report sample ( n = 632) to the FFM in a confirmatory factor analysis (CFA). The estimated model contains 96 free parameters, including 10 covariances among the Big Five latent variables, 38 paths from the latent variables to the observed BFI items, and 48 variances. Model fit is poor: χ 2 (850, N = 632) = 2,695.247, p < .001; root-mean-square error of approximation (RMSEA) = 0.059, 90% CI [0.056, 0.061]; comparative fit index (CFI) = 0.716; Akaike information criterion (AIC) = 2,887.247. We also perform a CFA with the 16 reverse-scored items removed, given their negative effects on internal reliability of the Big Five, particularly Extraversion, Agreeableness, and Conscientiousness. Model fit is improved but still a poor match to the data: χ 2 (314, N = 632) = 1,086.643, p < .001; RMSEA = 0.062, 90% CI [0.058, 0.067); CFI = 0.823; AIC = 1,214.643.

Procrustes Rotation

Standard protocol for assessing the comparability of personality structure across two populations involves a Procrustes rotation of sample data and estimation of factor congruence with another population that strongly displays the Big Five ( McCrae, Zonderman, Costa, Bond, & Paunonen, 1996 ; Piedmont et al., 2002 ; Schmitt et al., 2007 ). Despite our inability to reveal the Big Five using EFA or CFA, we consider the possibility that Tsimane personality structure may nonetheless be statistically similar to that in samples that typically do. We use Procrustes analysis to determine the factor congruence between our sample and a target structure, in this case a U.S. sample ( n = 2,793 college students, 64% female) from Schmitt et al. (2007) . McCrae et al. (1996) showed that Procrustes analysis is a more accurate test of replication than confirmatory factor analysis. It has since been used to successfully replicate the Big Five model within several novel samples (e.g., Piedmont et al., 2002 ; Schmitt et al., 2007 ). Congruence scores above 0.90 are indicative of good fit ( McCrae et al., 1996 ). As shown in Table 6 , Conscientiousness has the most congruence with the U.S. sample, and Neuroticism produces the least congruence. Although congruence does not improve to acceptable levels when using any of the subsamples described in previous sections, removing reverse-scored items from each of the Big Five does improve congruence (see Table 6 ). Splitting the data by age or sex does not notably improve congruence within any of the subgroups. Performing the same analysis on the loadings derived from the educated and Spanish-speaking subgroups actually decreases congruence for most factors. Removal of items with high and low average response scores and correction for acquiescence bias produce significant increases in congruence only for Neuroticism.

Procrustes Congruence With U.S. Target Structure

Comparison With Spouse Reports

Finally, we assess whether spouse-reported personality improves replication of the Big Five among the Tsimane. Internal reliability of the Big Five is lower than in the self-report sample (see Table 1 ). Cronbach’s alpha scores do not climb above 0.70 even after removal of the least reliable item within each factor, removal of reverse-scored items, removal of items with average scores more than four or less than two, and correction for acquiescence bias. The exception is Conscientiousness, which reaches acceptable internal reliability with removal of reverse-scored items.

Exploratory factor analysis using varimax rotation and principal-components extraction produces 11 factors with eigenvalues greater than one. There is less disparity in variance explained between the first and second factors than in the self-report sample (see Figure 1 ). Before factor rotation, the first factor explains 17.5% of the variance in the data and the second factor explains 10.5% of the variance. After factor rotation, the first factor explains 10.4% of the variance, the second 10.2%, the third 7.0%, the fourth 4.4%, and the fifth factor 4.2% of the variance. As with the self-report sample, the rotated component matrix shows considerable cross-loading of items from the BFI, and internal consistency is high for only the first two factors (see Table S14 of the supplemental materials ). Cronbach’s alpha is 0.85 for the first factor, 0.81 for the second factor, and < 0.65 for subsequent factors. Restricting the EFA output to five factors does not improve replication of the Big Five (see Table 7 ).

Rotated Component Matrix Restricted to Five Factors (Spouse-Report Sample)

Procrustes analysis does not indicate factor congruence with a U.S. sample that strongly displays the Big Five (see Table 6 ). Conscientiousness has the highest congruence coefficient at 0.72, and Neuroticism produces the lowest congruence coefficient at 0.38. Average congruence is lower than for the self-report sample.

We use maximum likelihood estimation to test the fit of the spouse-report data to the FFM in a CFA. The estimated model contains 96 free parameters, including 10 covariances among the Big Five latent variables, 38 paths from the latent variables to the observed BFI items, and 48 variances. Model fit is poor: χ 2 (850, N = 431) = 3,126.172, p < .001; RMSEA = 0.079, 90% CI [0.076, 0.082]; CFI = 0.523. Akaike information criteria indicate that the self-report data (AIC = 2,887.247) is a better fit than the spouse-report data (AIC = 3,404.172) to the FFM.

As we report above, only the first two factors from the self- and spouse-report samples exhibit high internal reliability in an unrestricted EFA, based on the items that load the highest on each derived factor (see Tables S1 and S14 of supplemental materials ). Given the low intercorrelations of the items within factors beyond the first two, we consider these factors poorly defined (see Tabachnick & Fidell, 2001 ). A scree test corroborates the emergence of only two well-defined factors in the spouse-report sample but is more indicative of a single factor in the self-report sample (see Figure 1 ).

Using Procrustes analysis, we test congruence between the unrestricted EFA solutions for the self- and spouse-report samples. Congruence between the second self-report factor and the first spouse-report factor is high (0.91); seven of the eight items that load the highest on the latter also load the highest on the former (see Tables S1 and S14 of supplemental materials). Congruence is also high (0.89) between the first self-report factor and the second spouse-report factor, though this is nonobvious from comparison of Tables S1 and S14 . Only four of the items that load the highest on the second spouse-report factor load the highest on the first self-report factor. However, congruential rotation takes advantage of the fact that the additional items loading highly on the first self-report factor show considerable cross-loading across the spouse-report derived factors. Subsequent factors from the self-report data produce lower congruence with the spouse-report factors, with coefficients ranging from 0.70 to 0.34.

We find significant response stability for the first two derived factors, based on the 34 individuals who self-reported their personality in 2009 and again a year later. To generate individuals’ scores on a particular derived factor, we used least squares regression. The retest correlation (Spearman’s rho) is 0.741 ( p < .001) for the first derived factor and 0.361 ( p < .036) for the second derived factor.

The items composing the first two derived factors include traits from all Big Five factors, although Extraversion and Agreeable-ness items load more highly on one factor, whereas Conscientiousness items load more highly on the other (see Table 5 and S1 of the supplemental materials ). The Spearman correlation between the two factors is 0.019 ( p = .640).

Evidence for the five-factor structure of personality among the Tsimane of Bolivia is weak. Internal reliability is generally below levels found in developed countries. The five-factor model did not cleanly emerge in any of the exploratory or confirmatory factor analyses, and Procrustean rotations did not produce strong congruence with a U.S. sample. Procrustes analysis, which is arguably the most forgiving test for replication of the FFM ( McCrae et al., 1996 ), yielded an average congruence coefficient of 0.62. This is well below the benchmark of 0.90 and considerably less than most congruence scores found in other cross-cultural applications of the Big Five ( McCrae et al., 2005 ; Schmitt et al., 2007 ).

We were able to discount several possible explanations for our results. First, we found no significant differences in structure replication after stratifying the sample by education level, Spanish fluency, sex, or age cohort. Despite research showing that education increases abstract reflection as measured by IQ (e.g., Ceci, 1991 ), educated and Spanish-speaking subsamples did not produce better replication of the Big Five among the Tsimane. Younger individuals (who are also more educated and more fluent in Spanish) were no more likely than older adults to display the Big Five. Similarly, men (who are also more educated and more fluent in Spanish) were no more likely than women to display the Big Five. These results are not surprising, in light of the fairly limited variation in Tsimane lifestyles and participation in traditional village life. Even the youngest and most educated Tsimane remain deeply embedded in traditional practices of food production and social exchange within their villages, which may partly explain why we find minimal differences in factor structure across these subsamples.

Second, removal of items with high or low average response scores did not improve replication of the Big Five relative to the full set of BFI items. Approximately one quarter of the items in the Tsimane BFI produced average responses below two or above four; these items may have elicited more socially desirable responding than other items. Studies that claim evidence for one or two higher order personality factors (e.g., Digman, 1997 ; Musek, 2007 ) have been interpreted as artifacts of socially desirable responding ( Bäckström, Björklund, & Larsson, 2008 ; McCrae et al., 2008 ). However, removal of items with low and high average response scores did not produce any closer fit to the FFM.

Third, a correction for acquiescence bias did not provide better support for the FFM. Acquiescence bias is indicated by inconsistent responding to items describing similar personality traits ( Hofstee et al., 1998 ) and has been linked with lower educational attainment ( Narayan & Krosnick, 1996 ; Rammstedt et al., 2010 ). However, our correction for acquiescence bias did not improve internal reliability of the Big Five or produce a significantly better overall fit to the FFM in EFA or Procrustes analysis.

Fourth, removal of reverse-scored items improved fit to the FFM in confirmatory factor analysis, but the fit remained poor. The reverse-scored items were the least consistent items within the Big Five, suggesting they were differentially susceptible to response biases. With the reverse-scored items removed, Extraversion, Agreeableness, and Conscientiousness just exceeded the threshold for acceptable internal reliability, and they showed clearer differentiation in exploratory factor analysis. However, items composing these factors continued to load highly on more than one factor, and Extraversion and Agreeableness items retained substantial covariation. Congruence with a U.S. target structure was higher than with our other subsamples but remained well below the benchmark of 0.90.

Fifth, we find that subjects’ personality as reported by their spouses does not support the FFM. Compared to self-report, peer report may be less influenced by response styles and has been shown to increase internal reliability among the Big Five ( McCrae et al., 2005 ; Riemann, Angleitner, & Strelau, 1997 ). Among the Tsimane, however, spouse-reported personality produced a worse fit than did self-reported data to the FFM, based on tests of internal reliability, EFA, CFA, and Procrustes congruence analysis with comparison to a U.S. target structure.

Additional evidence supports the lack of the FFM among the Tsimane. Retest correlations amongst the 34 Tsimane respondents sampled twice are significant for all Big Five factors but Agree-ableness. However, the average retest value of 0.415 is substantially lower than the ~0.65 median retest correlation for the Big Five in Western adult samples ( Costa & McCrae, 1994 ). Furthermore, Agreeableness produced the lowest retest correlation even though Neuroticism and Openness fared worse in tests of internal reliability.

We find relatively high significant correlations across the Big Five (see Table 4 ), of higher magnitude than typically found in populations where the Big Five is evident. Thus, even though we find evidence that responses to the Tsimane BFI show external validity with observed characteristics of subjects, these observations are correlated across all Big Five factors. For example, Tsimane individuals who score higher in Neuroticism are observed to be more shy and to smile less. Individuals who score higher in Extraversion are observed to be less shy and to smile more often. However, these observations of extraverts also characterize individuals who score higher in Agreeableness, Conscientiousness, and Openness. Our evidence of external validity is therefore less indicative of the FFM than other factor structures.

A valid test of the Big Five requires both that the survey items were translated accurately and that the items bear similar cultural meaning in the target society. The care with which we translated and retranslated the BFI may not preclude culture-specific interpretations of some of the items. For example, the Extraversion item “is reserved” may have been interpreted less as taciturn and more as modesty. The BFI’s reliance on dispositional terms without reference to specific situations contributes to such differences in interpretation. Successful survey instruments developed in research among Tsimane and similar groups often require concrete questions with sufficient background details (e.g., On a scale of 1–7, “how often do you hunt?” will generate more confusion and misleading responses than “In the past seven days, how many of those days did you go hunting?”). Although adding specificity to each BFI item may limit the ability to capture broader aspects of personality dimensions, it may ensure greater reliability and more meaningful responses (see Denissen & Penke, 2008 ). On the other hand, the Tsimane often speak of their peers’ personalities in the abstract (see our description of the study population), so we do not anticipate that context-specific personality items will necessarily reveal a different personality structure than manifested with our current data.

Exploratory factor analysis yields a personality structure that is largely distinct from the Big Five. Unrestricted, the factor analysis yields 11 derived factors with significant eigenvalues. When restricted to five factors, the derived factors each subsume items from at least four of the Big Five. The first derived factor is largely a mix of Extraversion and Agreeableness items and reflects a general prosocial disposition. “Reserved” and “talkative” both load positively on the first factor, but this is not necessarily contradictory. Respondents likely interpreted “reserved” as not boasting, rather than being taciturn. An egalitarian ethic among the Tsimane often curtails verbal expression of personal achievement, as is the case in many small-scale societies ( Boehm, 1999 ). The Tsimane esteem individuals who talk confidently but modestly in public settings. The Openness items “original” and “ingenious” also load positively on the first derived factor, which suggests prosocial individuals are also the most creative.

Several items from Conscientiousness sort on the second derived factor, including “efficiency,” “perseverance,” and “thoroughness.” “Energetic” and “inventive” also load highly on this factor. These items may reflect industriousness in the context of subsistence labor. Because food production labor is pooled within Tsimane extended families, it is helpful to our interpretation that “unselfishness” and “reliability as a worker” also load highly on the second factor. The third derived factor subsumes undesirable traits, whether in the context of social gatherings or labor. The fourth and fifth derived factors are more difficult to interpret and also show the least internal consistency. “Calm in tense situations” and “quiet” load positively and “quarrelsome” loads negatively on the fifth factor, which may reflect deference or reservedness in social situations. The fourth derived factor includes the items “finds fault,” “moody,” “easily distracted,” and “curious,” which is suggestive of the Western notion of (teenage) angst or, as communicated by a reviewer, an imaginative personality thwarted by a conservative society. However, these four items come from four different factors (Agreeableness, Neuroticism, Conscientiousness, and Openness, respectively).

The internal reliability of the first two derived factors in Table 5 (five-factor solution) and Table S1 (unrestricted factor solution) is high, supporting the possibility of a “Tsimane Big Two” organized according to prosociality and industriousness, as described above. These two factors show significant response stability; response stability for the first derived factor is stronger than for any of the Big Five. The spouse-report sample also produces two factors that explain more of the variance and are more internally consistent than the other derived factors. Furthermore, congruence between the self- and spouse-report samples on these first two derived factors is high. The Tsimane Big Two are therefore consistent across both self- and spouse-report samples. However, these Big Two are not the two higher order factors of Digman (1997) , characterized as stability and plasticity by DeYoung (2006) , which neatly subsume the Big Five by merging Extraversion with Openness and Agreeableness with Conscientiousness and Neuroticism. Our factors instead cut across the Big Five domains. These results are consistent with the findings of Ashton, Lee, Goldberg, and de Vries (2009) , where higher order factors emerge because lower order facets load onto multiple factors. Not only do we find that items load onto multiple factors, but the loading coefficients in our exploratory factor analyses are generally lower than those found in previous studies of the Big Five.

Our findings provide evidence that the Big Five model does not apply to the Tsimane. Our findings also bring into sharper focus past reports from developing societies where the FFM was not clearly replicated. Of the 50 countries reported in McCrae et al. (2005) , only India, Morocco, Botswana, and Nigeria produced average congruence scores less than 0.90. The lowest congruence scores reported by McCrae et al. are 0.53 and 0.56 for Openness in Botswana and Nigeria, respectively. In the African and South Asian countries from Schmitt et al. (2007) , internal reliability for Extraversion, Agreeableness, and Conscientiousness is similar to what we report for the Tsimane. Because the samples from the developing countries in Schmitt et al. and McCrae et al. are primarily college students, more representative samples from these countries may have produced even lower congruence scores and internal reliability.

If the Big Five (or any other number of fixed traits) are not pan-human universals, then what could explain variability in personality structure? Nettle (2010) argued that personality items covary because they act synergistically. For example, he suggests that the fitness payoff to ambition is positive if sociability is also high; these traits thus covary as part of the Extraversion continuum. Similarly, the fitness payoff to imagination is positive if intellect is also high; thus, both traits covary along the Openness continuum. If the synergism of particular personality traits has different fitness consequences in different socioecological environments, we may not expect a universal structure of personality covariation. Behavioral genetic data support this possibility: Two independent dimensions of genetic variance are necessary to explain variation in each of the Big Five factors ( Jang, Livesley, Angleitner, Riemann, & Vernon, 2002 ). In different socioecologies, these independent genetic sources may not contribute to the same behavioral dispositions or experience parallel selection pressures ( Penke, Denissen, & Miller, 2007 ).

Variation in personality structure across populations need not derive from different patterns of covariation among genetic polymorphisms. Instead, different personality structures may arise from the facultative responses of individuals living in different socioecologies. In other words, individuals in different populations can share the same personality-relevant genetic architecture, but these genes may produce different effects in different environments. A growing body of work within behavioral ecology interprets personality variation as reaction norms that respond over ontogeny to individual condition and socioecological context ( Dingemanse, Kazem, Reale, & Wright, 2010 ; Sih, Bell, Johnson, & Ziemba, 2004 ). A working hypothesis is that coordinated traits might be facultatively calibrated based on cues underlying individual circumstances during development. The bundle of particular items and traits constituting human personality might act like conditional strategies ( Buss, 2009 ; Figueredo et al., 2011; Gangestad & Simpson, 2000 ; Lukaszewski & Roney, 2011 ; Nettle, 2010 ; Penke, 2010 ; Tooby & Cosmides, 1990 ). For example, men who are stronger and rated as more attractive are more likely to be extraverted, independent of a genetic polymorphism that also explains some of the covariance ( Lukaszewski & Roney, 2011 ). Variation in susceptibility to stress, which may underlie differences in neuroticism, has been linked to facultative calibration to stressors early in life ( Ellis, Jackson, & Boyce, 2006 ). It is an intriguing possibility that pan-human reaction norms shape not only intersocietal differences in average personality scores but also the structure of personality covariation itself, due to sustained socioecological differences across human populations. This hypothesis cannot be rejected in light of recent cross-cultural studies finding universal evidence of the Big Five, given the WEIRD-ness of most of the study populations. Indeed, any model of personality that specifies a fixed set of biologically based trait dimensions would be inconsistent with the results we report here. A comprehensive theory of personality would need to explain how particular conditions might lead to different combinations of calibrated and coordinated items, which then generate multidimensional personality structure, in varied socioecological settings and circumstances. Under a wide range of conditions, the FFM might adequately describe personality variation and necessarily so, but we still do not know why! We therefore speculate about some conditions that differ between WEIRD and small-scale subsistence societies in order to help explain our findings.

What features of Tsimane socioecology cause divergence from the Big Five pattern found in WEIRD populations? Individuals in all human societies face similar goals of learning important productive skills, avoiding environmental dangers, cooperating and competing effectively in social encounters, and finding suitable mates. In small-scale societies, however, individuals tend to live in small groups of closely related individuals with greatly reduced choice in social or sexual partners. There are also a limited number of niches by which cultural success may be measured, and proficiency may require abilities that connect items from different traits, thereby leading to low trait reliability and a trait structure other than the FFM. Among the Tsimane, success is defined largely in terms of ability to produce food and provision one’s family. Spouses rank each other primarily on these traits and are assortatively matched based on work effort ( Gurven et al., 2009 ). Leadership and allies outside of the extended family accrue to men who are outgoing, trustworthy, and generous among community members ( von Rueden et al., 2008 ). Women’s reputations are linked to similar traits and affect their ability to marshal intravillage exchange partnerships ( Rucas et al., 2006 ). Our industriousness and prosociality factors may reflect the different blends of traits conducive to success in the domestic versus the public sphere of Tsimane life. Furthermore, the orthogonality of these factors suggests their effects on fitness are partially independent. Lifetime reproductive success is higher for better producers ( Gurven & von Rueden, 2006 ) and for higher status individuals ( von Rueden, Gurven, & Kaplan, 2011 ), and status has a strong effect on reproduction even after controlling for productivity. It is possible that traits may vary more independently in WEIRD societies because of their greater niche diversity and specialization, whether in terms of professional careers or social groups. Success may require a coordinated assortment of fewer items that thereby bundle together in a larger number of factors.

Other considerations might also help explain our findings and would be important to test in other similar societies. Although extended families have relative political autonomy in many small-scale communities, an egalitarian ethic often curtails verbal expression of personal achievement ( Boehm, 1999 ). Thus, the costs and benefits of being extraverted may hinge on one’s level of agreeableness, which is suggested by the covariance of Extraversion and Agreeableness items in our prosociality factor. Indeed, Tsimane men whose voiced opinions are most influential in community meetings have more allies and are rated by their peers as more prosocial ( von Rueden et al., 2008 ). McCrae et al. (1998) and Cheung et al. (2001) argued that Extraversion and Agreeableness items have shown different factor structure in East Asian societies because they are more collectivist cultures in which interpersonal affiliation and obedience to authority are more normative. Small-scale societies such as the Tsimane can be characterized as collectivist only in terms of interpersonal affiliation: Their reliance on interhousehold exchange to buffer risk promotes consensual decision making and suppresses the emergence of formal authority ( Boehm, 1999 ; Cashdan, 1980 ).

Given the day-to-day risks of underproduction relative to subsistence needs, members of small-scale societies tend to be more risk averse ( Cancian, 1989 ; Cashdan, 1990 ; Kuznar, 2001 ), and new ideas, values, or experiences are typically met with conservatism. Furthermore, Tsimane and other small-scale populations in the tropics experience high levels of a variety of infectious pathogens ( Vasunilashorn et al., 2010 ), so a cautious and conservative approach to novel people, foods, and practices may reduce the risk of disease ( Schaller & Murray, 2008 ). In our EFAs, the Openness items of “original” and “ingenious” covary with socially desirable Extraversion and Agreeableness items; perhaps individuals who are the most interpersonally imbedded can best manage the risks of being open to new experiences. Items gauging artistic interest also covary with socially desirable traits; playing music and telling stories are the principal forms of artistic expression among the Tsimane and are most overt as “performance” in group settings. It is our impression that Tsimane who are more outgoing tend to be the most eager and creative singers and musicians. On the other hand, the Openness items of “curious” and “likes to reflect” positively covaried, respectively, with the Neuroticism item “moody” and the Agreeableness items “quarrelsome” and “rude.” This latter result supports our impression from the Tsimane and other small-scale societies that traits such as introspection and reflection are sometimes viewed as signs of depression or are viewed with suspicion. Openness exhibited low internal reliability and factor congruence in our study, similar to results from other developing countries (e.g., McCrae et al., 2005 ; Piedmont et al., 2002 ). Openness does not typically replicate in emic studies with Chinese subjects (e.g., Leung, Cheung, Zhang, Song, & Xie, 1997 ), suggesting collectivist norms may limit entrepreneurship and expression in ways that mimic the limited opportunities individuals face in small-scale societies. Resolution of these issues requires more studies of personality in non-WEIRD populations.

Whether the Big Five personality structure replicates in small-scale societies is crucial to claims of the universality of the FFM or any other fixed factor construct (e.g., HEXACO: Lee & Ashton, 2004 ; Big Two: Digman, 1997 ; General Factor of Personality: Musek, 2007 ). More important, data from small-scale societies contributes to our understanding of the evolution of human personality differences. The FFM and other structural approaches to personality variation are often criticized for a lack of theoretical justification (e.g., Block, 1995 ); conceptualizing personality dimensions as evolved motivational systems calibrated based on state-based cues from a particular socioecology has the potential to fill this void. Framing adaptive explanations of this sort in the study of human personality has a precedent in behavioral ecology. Concurrent developments in the biological sciences increasingly show that stable personalities, or “behavioral syndromes,” exist in many nonhuman species and can have substantial fitness consequences (for reviews of models and evidence, see Dingemanse & Wolf, 2010 ; Sih & Bell, 2008 ; Sih et al., 2004 ; Wolf & Weissing, 2010 ). The empirical study of Big Five traits and fitness outcomes in humans is still in its infancy (e.g., Alvergne et al., 2010 ; Eaves, Martin, Heath, Hewitt, & Neale, 1990 ; Nettle, 2005 ; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007 ). Human personality research is therefore a ripe area for bridging theoretical models with rich empirical evidence ( Nettle & Penke, 2010 ). However, empirical evidence in humans must expand beyond the limited scope of WEIRD societies. What we can learn about personality variation in small-scale societies bears on arguments concerning the selection pressures responsible for shaping human personality traits and their structure. It is in small-scale societies that humans have lived for the majority of their existence; the socioecologies of ancestral hunter– gatherers and horticulturalists are the crucible that shaped much of human psychology and behavior. We therefore urge others to conduct similar studies of personality structure in other small-scale, indigenous societies.

We provide the first comprehensive test of the FFM in a small-scale, indigenous society—the Tsimane horticulturalists of Bolivia—and fail to robustly replicate the Big Five. We find significant covariance among items across the standard Big Five factors, based on two large samples of self- and spouse-reported personality. Tsimane personality variation may instead be organized along fewer and differently composed dimensions. We find evidence for a Tsimane Big Two organized according to prosociality and industriousness in the context of subsistence labor. Our current results require replication, with emic inventories and with other methods such as those based on behavioral observation or on peer reports by non-Tsimane. However, even if other methods were to reveal a Big Five structure, an explanation would still be needed for why verbal reports do not lead to the FFM among Tsimane, even after correction for response biases, but do almost everywhere else in the developed world.

Supplementary Material

Acknowledgments.

Funding was provided by the National Institutes of Health and the National Institute on Aging (Grants 2R01AG024119 and 2R56AG024119-06). We are grateful to the Tsimane for their hospitality and collaboration over the years. Gary Lewis provided helpful comments on a draft of this article. We also thank Aaron Lukaszewski for sharing ideas and commenting on a draft of the article.

Supplemental materials: http://dx.doi.org/10.1037/a0030841.supp

Contributor Information

Michael Gurven, Department of Anthropology, University of California, Santa Barbara.

Christopher von Rueden, Department of Anthropology, University of California, Santa Barbara.

Maxim Massenkoff, Department of Anthropology, University of California, Santa Barbara.

Hillard Kaplan, Department of Anthropology, University of New Mexico.

Marino Lero Vie, Tsimane Health and Life History Project, San Borja, Beni, Bolivia.

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Exploring the Links Between Personality and Relationship Satisfaction

In a fascinating study published in 2016, researchers delved into how the Big Five personality traits—neuroticism, agreeableness, conscientiousness, extraversion, and openness—play a significant role in romantic relationships, particularly when mediated by self-esteem.

Key Findings

Personality traits and relationship satisfaction.

• Neuroticism is negatively associated with relationship satisfaction, possibly because high neuroticism can lead to negative interpretations within the relationship.
• Agreeableness, Conscientiousness, and Extraversion are positively linked to relationship satisfaction. These traits contribute to better coping mechanisms during stress, which can enhance relationship quality.
• Openness showed mixed results, indicating that while it could introduce novelty into relationships, it might also lead to a lack of commitment.

Self-Esteem as a Mediator

• Self-esteem plays a crucial mediating role between personality traits and relationship satisfaction. Higher levels of self-esteem are linked to better relationship satisfaction across all personality traits.
• The study used the Actor-Partner Interdependence Mediation Model (APIMeM) to analyze both individual and partner effects, revealing intricate dynamics between personal traits, self-esteem, and relationship satisfaction.

Longitudinal Insights

• The study also examined the effects over a two-year period, finding that traits like agreeableness and (marginally) neuroticism could predict relationship satisfaction later. Interestingly, relationship satisfaction also influenced some personality traits over time, indicating a bidirectional relationship.

Theoretical Implications and Future Directions

The study highlights the importance of considering personality and self-esteem together in understanding relationship dynamics. It challenges previous models by suggesting that personality traits and self-esteem are not just outcomes but can be predictors of relationship satisfaction over time. Future research could explore these dynamics over longer periods and with different populations to validate and expand these findings.

The research underscores the complex interplay between individual personality traits, self-esteem, and their collective impact on relationship satisfaction. It opens new avenues for therapy and relationship counseling, where focus on improving self-esteem and understanding personality dynamics could lead to more fulfilling and stable relationships.

This groundbreaking study not only adds a new dimension to our understanding of relationship dynamics but also offers practical guidance for enhancing relationship satisfaction through personal growth and mutual understanding.

• Rebekka Weidmann and others: «Big Five traits and relationship satisfaction: The mediating role of self-esteem»