Not only individuals but also entire groups of people have personalities. For example, we have a habit to talk about Italians, Germans, and Finns as if there is one person whose personality or character could represent the whole nation or an ethnic group. Like Montesquieu, many people believe in climatic theories according to which it is easy to distinguish a Southerner from a Northerner, as if they belong to two distinctive groups of people (Pennebaker, Rime, & Blankenship, 1996). While personality researchers are wrestling to collect enough data to compute the average scores of entire nations on at least some personality traits, laypersons seem to believe that they know exactly how Italians, Germans, or Finns typically feel, think, or behave in characteristic situations.
In this chapter, we provide an overview of cross-cultural studies of personality that have involved a sufficiently large number of different countries or territories. Although there is no definitive answer regarding the number of countries that is sufficient, we can rely on common sense. If researchers are lucky to recruit many participants from one country or a region, who have completed a personality questionnaire, then it is common to compute the mean scores of those responses in order to characterize the country or region as a whole on these personality traits. For example, let us suppose that researchers have decided to measure conscientiousness, which can be exemplified by an individual who is purposeful, strong-willed, reliable, and determined (McCrae & Costa, 2010). When we learn that the highest culture-level mean scores of conscientiousness, obtained by averaging the scores of all respondents in each cultural sample, are found in Benin and Burkina Faso, while the lowest scoring countries are Japan and Korea, one is immediately prompted by a question about the validity of these culture-level aggregate personality scores (Mõttus, Allik, Realo, Pullmann, et al., 2012). The aforementioned findings are certainly puzzling because they challenge our intuition about personality dispositions being in harmony or at least reflecting to some extent the countries’ socioeconomic progress. Since the construct and criterion-related validity of personality tests have been well established at the individual level, the intriguing question obviously pertains to the validity and meaningfulness of aggregate personality scores as indicators of the personality profiles of cultures. In this chapter we adopted the following premise: the best (but not necessarily only) way to answer this and related questions is to carry out and analyze large-scale personality studies involving many different countries or regions that differ not only in language but also in cultural values, religion, political regime, and economic development.
Most of today’s states are nation-states, which emerged over the past 200 years, replacing empires and kingdoms (Wimmer & Feinstein, 2010). Occupants of a certain territory or speakers of the same language become a nation if they share the same culture and recognize in each other membership in a system of ideas and signs (Gellner, 1983). However, a nation-state, especially in today’s world, is rarely homogeneous. Even Iceland, with its population of slightly above 300,000 people, cannot be regarded as a culturally and genetically homogeneous country any more, with the number of immigrants representing 9.5% of the total population in 2014. It is, however, even more questionable if we can represent heterogeneous giants like China with its 1.4 billion population and hundreds of ethnic groups as a single number (i.e., personality score), as it is customary to do in comparative surveys that involve multiple countries. Furthermore, many relatively small European states such as Belgium, Spain, or Switzerland are well known for being composed of two or even more culturally and linguistically heterogeneous regions. Sometimes historical traditions are pervasive, and we can see cultural boundaries even without language divisions. For example, recognizable cultural differences between the Southern and Northern United States can be detected (Vandello, Cohen, & Ransom, 2008). Hence, the boundaries of the nation-state are not always the most logical or meaningful dividers between people. Thus, this chapter is about cultural group differences, which do not always correspond with nation-state boundaries.
Cross-cultural research in personality has two seemingly opposite aspirations. One is to demonstrate the unity of human kind, which expresses itself, in part, in the largely universal organization or structure of personality. Another approach is to scrutinize a certain culture in order to find some indigenous traits that characterize only a given group of people.
Strictly speaking, universal means that something is characteristic of all members of a certain class, without any exceptions. Very little in the world meets this absolute criterion, but many characteristics appear to be relatively invariant (Allik, Realo, & McCrae, 2013). Psychologists are interested in universals at the level of both individuals (e.g., “all people have a brain”) and the group (e.g., “men are more aggressive than women”), but these levels must be distinguished. The claim that gender differences in personality are universal does not mean that every man is more aggressive than every woman; rather it means that in all groups of people, the same degree or direction of gender-related trait differences is found on average. Because only very few things exist without exceptions, the observed regularities are expected to hold not in all groups of people but in most of them. In this case, it is more appropriate to talk about near-universals. If personality traits are universal, then they are potentially universal at the group level and consequently near-universals. A realistic research task in each particular case is to establish, as accurately as possible, the exact degree of universality versus cultural uniqueness of various aspects of personality. Given the current status of research on cross-cultural personality structure, it seems reasonable to argue that the Five-Factor Model (FFM) of personality is a sound representation of personality trait structure for many cultures/groups around the world but not for all and that there might also be some indigenous personality traits, which are not well captured by the FFM (see Church, 2016; and McCrae, Chapter 2 in this volume for recent reviews).
Typically, personality researchers ask participants to describe their own personality. For example, they may ask the participants to agree or to disagree with an item such as “I act forcefully and energetically.” Researchers may also approach somebody who knows a given person well enough and ask his or her agreement with a statement such as “He/she acts forcefully and energetically.” However, besides describing one’s own or somebody else’s personality, people are quite willing to characterize not only particular individuals but also a group of people as a whole. For instance, participants could be asked to estimate a typical representative of his or her country or ethnic group. In this case, a questionnaire item asks how characteristic it is that a typical representative of one’s nation or ethnic group acts forcefully and energetically (Terracciano et al., 2005). Because these inquiries are about beliefs concerning national character, researchers also call them stereotypes. We are talking about auto-stereotypes if items point to a nation or ethnic group to which the participant belongs or hetero-stereotypes if some out-group is rated or judged.
Generally, it is presumed that self- and other-reports agree with each other. Because how people see themselves is not very different from how they see others, there is generally strong agreement between self- and other-reports on both the individual (Funder, 2012) and aggregate (Allik, Realo, et al., 2010) levels of analyses. Similar expectations existed for stereotype ratings. Because many stereotypes are believed to have at least a kernel of truth (Allport, 1954/1978; Lee, Jussim, & McCauley, 1995), national stereotypes of personality are also expected to reflect the differences in aggregate scores of self- and other-ratings of personality. In other words, if a given nation or ethnic group is stereotypically believed to be honest and industrious, then the mean level scores of honesty and industriousness of the members of this group should be also quite high (or at least higher than in nations that are seen as dishonest and not very industrious). Although several large-scale studies have shown that national character stereotypes are rather weakly related to personality profiles assessed as national means on personality measures (Hřebíčková & Graf, 2014; McCrae et al., 2013; Terracciano et al., 2005), there are also studies that have shown that national character stereotypes are moderately related to assessed personality traits if all assessments are made using the same measurement instrument (Allik, Mõttus, & Realo, 2010; Lönnqvist, Konstabel, Lönnqvist, & Verkasalo, 2014; Realo et al., 2009).
Personality questionnaires, however, are not the only tools for revealing personality traits. For some time researchers have thought that habits and social practices can and must reveal what people feel, think, and intend to do. Adolf Wagner and Alexander von Oettingen, two professors who worked in Tartu, Estonia, established what we know today as moral statistics (Lederer, 2013). Their idea was to explain frequency of what they considered social anomalies (e.g., murders, suicides, and divorces) not only by environmental or demographic (e.g., climate, population density) factors but also by what they called moral character (Oettingen, 1882). These inquiries led Wagner to the discovery of the “One Law” of sociology: Protestants kill themselves more often than Catholics (Wagner, 1864). Based on these data Émil Durkheim wrote his classical treatise Suicide (Durkheim, 1897/1952), which apparently supported the modernity thesis of his predecessors who associated the suicide rate with societal progress.
About a hundred years later, following the same tradition, Richard Lynn published his book Personality and National Character (1971), with the premise that incidences of suicide, mental illness, and tobacco consumption, as examples, can tell us something about personality. The main idea advanced by this book is that nations differ in the number of anxious people in the population. Thus, according to Lynn, the personal level of anxiety may be responsible for the instances of social maladies such as suicide, alcoholism, accidents, hypertension, and smoking, among others.
A modern society produces an astonishing number of sophisticated statistics. For example, statistical agencies follow carefully people’s tendency to deposit a fraction of their income. It is logical to expect that in countries where people are more introverted, the level of savings will be higher because introverts have a more pronounced tendency for saving money (Hirsh, 2015). Economists have also noticed that the propensity to invest abroad is related to openness to experience (Niszczota, 2014). Similarly, across 135 nations, helping strangers and donating money to charity are reliable indicators of prosocial behavior (Smith, 2015). It is also expected that innovation (including patents) is related to the societal level of openness to experience (G. D. Steel, Rinne, & Fairweather, 2012). On the other hand, nations scoring low on neuroticism and high on extraversion tend to be less corrupt (Connelly & Ones, 2008). Even prevalence of infectious diseases may be related to personality traits—extraverts are more likely to develop and maintain wide-ranging social networks, which also spread diseases (Murray & Schaller, 2010). Thus, besides well-studied anomalies, there are many more indicators at the national level, which could tell us—potentially at least—something about personality characteristics of members of a nationality.
One derivative from the postulate of the psychic unity of humankind is that all cultural or national differences in personality are small relative to individual variation within each culture or nation. An obvious way to test this postulate is to compare the variance of the national mean scores with the variance of the same trait within these nations. Based on published data using either the Revised NEO Personality Inventory (NEO-PI-R; McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005) or the Big Five Inventory (Schmitt et al., 2007), it turns out that the standard deviation of personality trait scores at the national (aggregate) level is about three times smaller than the standard deviation of individual level scores within cultures (Allik, 2005). This means that, on average, cultural or national differences are approximately nine times smaller than individual differences on the same traits within these cultures or nations. Even if this is not a very precise number, the main message is obvious—cross-cultural or geographical differences in personality are surprisingly small and one needs well-calibrated and sophisticated tools to measure these differences.
There are several models of how to carry out cross-cultural research (Allik, Massoudi, Realo, & Rossier, 2012). The anthropological model, for example, sends well-prepared expeditions to locations of interest. A serious limitation of this model is low productivity in terms of cross-cultural comparisons: obviously, these in-depth and valuable expeditions can cover only a limited number of ethnic groups and geographic locations. An even more serious obstacle, however, lies in the fact that many, if not most, anthropologists believe that cross-cultural comparisons are in fact not meaningful or even doable (see Berry, Poortinga, Breugelmans, Chasiotis, & Sam, 2011, for a review). Nevertheless, many cross-cultural psychologists have adopted the anthropological research model by applying it in two cultures, most often comparing some exotic culture with their own, and there is no doubt that this approach has produced some spectacular results. Contrasting two and occasionally more cultures has also substantially widened our understanding of cross-cultural differences in personality. For example, because Americans and Japanese have fairly different construals of the self, the contrast between these two cultures may be informative (Markus & Kitayama, 1991).
However, the most influential recent developments in cross-cultural psychology can be attributed to an alternative model of collecting data, which has its roots in a so-called missionary model. Charles Darwin, for instance, circulated in 1867 his printed leaflet “Queries about expression” among acquaintances (very often missionaries) who were in touch with “primitive” peoples all around the world in order to study how emotions are recognized and expressed in different cultures. The answers to these queries formed the basis of his book The Expression of the Emotions in Man and Animal (Darwin, 1872/1989), where on pp. 19–22 he even gave the names of the 29 correspondents who had kindly replied to his query (Freeman, 1977).
Instead of writing to Christian missions, nowadays researchers can recruit collaborators among their academic colleagues from different parts of the world, who translate questionnaires into their native languages and then collect data in their own countries. Such international research consortiums are often held together with the promise that the first two or three papers will be coauthored by all those who participate in collecting data. This model has produced a true revolution in cross-cultural research. It is only a small exaggeration that the most valuable personality data sets were collected using this more productive “technology” (e.g., Allik et al., 2009; McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005; Schmitt et al., 2007). One serious shortcoming of this method is that participants are usually recruited based on convenience rather than representativeness. Another problem is that not all places of interest have trained and motivated colleagues who are able to take part in the project. Finally, the translated questionnaires that are administered typically assess personality constructs first identified in source (typically Western) countries, with little, if any, attempt to identify indigenous constructs in the target cultures.
Instead of actively seeking out collaborators from different countries, it is also possible that cross-cultural data become available not because the author of a certain measurement instrument was interested in cross-cultural comparisons but simply because researchers in different countries found the instrument useful and relevant and wanted to adapt it to their culture. In personality psychology, Eysenck Personality Questionnaire (EPQ) was apparently the first instrument enjoying truly international popularity (Lynn & Martin, 1995). Other examples include Cloninger’s Tridimensional Personality Questionnaire (TPQ) and Temperament and Character Inventory (TCI), which have been translated into many languages (Miettunen, Kantojärvi, Veijola, Jarvelin, & Joukamaa, 2006). In 1992, Paul T. Costa Jr. and Robert R. McCrae published their NEO-PI-R (Costa & McCrae, 1992). Ten years later, it was possible to report use of the NEO-PI-R in 27 different languages and 36 different cultures or regions (McCrae, 2002; see also McCrae, Chapter 2 in this volume). Currently, NEO-PI-R profiles have been compared across more than 60 countries.
Sometimes large multinational corporations also contribute to cross-cultural personality research. Despite some criticisms on its approach, it is impossible to overestimate the impact of Hofstede’s (1980) pioneering study of work-related values in 40 IBM national subsidiaries, which was later expanded to 76 countries (Hofstede, Hofstede, & Minkov, 2010). Recently, results of a giant study were published involving more than 1 million participants from 31 countries who answered a personality questionnaire (Bartram, 2013).
In the age of the Internet, it would be foolish to ignore new cost-effective methods of data collection. During a relatively short period, it is possible to recruit huge numbers of participants from one country (Rentfrow, Gosling, & Potter, 2008) or from all over the world (Gebauer et al., 2015; Srivastava, John, Gosling, & Potter, 2003) without even leaving one’s office. Again, an obvious limitation is self-recruitment—most often the participants nominate themselves into the study so that participation is dependent on their motivation and access to the Internet (Pullmann, Allik, & Realo, 2009). Despite this and other problems (e.g., attention and compliance, ethnic issues), the Internet nevertheless holds great promise and offers great benefits over “traditional ways” of recruiting participants to collect diverse samples in different parts of the world with relatively low efforts and costs (Maniaci & Rogge, 2014).
People like rankings of countries on all possible grounds, ranging from precipitation amounts to the amount of savings in banks. It is fascinating to know, for example, that Columbia is the wettest and Egypt is the driest country in the world in terms of average annual rainfall. Another surprising fact is that Japanese have very few personal savings, while in Ireland people save a considerable percentage of their earnings. Like climatic or economic data, it is possible to compose rankings based on people’s opinions or reports about their feelings, values, attitudes, personality traits, and so forth. For example, one can interview a representative sample of people and ask them how happy they are. Aggregating all answers from one country (or territory) we obtain the national mean score of happiness (Helliwell, Layard, & Sachs, 2015). For example, in 2015, the three happiest countries in the world were Switzerland, Iceland, and Denmark. The least happy people, according to this report, live in Togo, Burundi, and Syria. These results make sense only if the aggregate scores represent an accurate statistical summary of how people really feel and think in these countries.
A propensity to experience positive emotions and to be satisfied with one’s own life is at least partly determined by personality traits (P. Steel, Schmidt, & Shultz, 2008). Consequently, these ratings reflect, partly at least, dispositions of how people feel, think, and behave in general—the way personality traits are usually defined. Theoretically, it is possible that we can compute average scores on personality traits such as neuroticism, agreeableness, and conscientiousness. However, sometimes these average national scores of personality are confusing. For example, even cultural experts may be perplexed by the fact that people living in Norway, Sweden, and Denmark score very high on E6: Positive Emotions—a subscale of Extraversion in the NEO-PI-R—while in Hong Kong, Portugal, and Italy people score among the lowest countries on this scale (McCrae & Terracciano, 2008). This finding, however, should not come as a surprise as the two Nordic countries, Norway and Denmark, are also among the five countries with the highest level of happiness as mentioned previously. In a similar vein, how plausible does it look—as we already argued at the beginning of this chapter—that the most dutiful, self-disciplined, and deliberate people live in Benin and Burkina Faso, who by their own ratings outperform Japanese and South Koreans on these traits by a considerable margin (Mõttus, Allik, Realo, Pullmann, et al., 2012)? Because some of these country rankings of aggregate personality traits look like gibberish, researchers have questioned the accuracy of national mean scores in general (Heine, Buchtel, & Norenzayan, 2008).
There is a wide range of potential reasons why the culture-level aggregate personality scores may be flawed, and there are many factors that could compromise their validity (Meisenberg, 2015). Some of these causes are “technical” and can be explained by, for example, how people in different cultures use the response scale. The average scores of two countries (or regions) may be different because respondents of one culture use extreme categories of the response scale more frequently compared to respondents from another culture, independent of the item content (Gilman et al., 2008; Mõttus, Allik, Realo, Rossier, et al., 2012). Researchers have also noticed that respondents in different cultures are more or less ready to agree with a posed question (also called acquiescence bias) irrespective of its content (He, Bartram, Inceoglu, & van de Vijver, 2014; Javeline, 1999; Mõttus, Allik, Realo, Rossier, et al., 2012).
The observed differences in the mean levels of personality traits may also be caused by sampling errors, which could occur when one of the samples under comparison attracted more participants who for any reason had initially higher or lower scores on the studied trait (Schmitt et al., 2007). However, some researchers maintain that the inaccuracy of the mean scores may be instigated by fundamental limitations of human judgment. For example, it is believed that people are systematically engaged in self-enhancement: they view themselves more favorably than they view others (Sedikides, Gaertner, & Cai, 2015). If the extent of the self-enhancement bias is different in different cultures, then self-reported personality traits may be substantially distorted. Although fears of self-enhancement biases in personality descriptions are largely exaggerated (Allik, Realo, et al., 2010), such biases can still distort self-reported personality scores.
Since Festinger’s (1954) seminal study, it is popular to believe that people often calibrate their judgments relative to some social standards or norms. In particular, it was proposed by Heine et al. (2008) that self-reported personality traits are compared with implicit standards accepted in a particular culture. Heine and his colleagues gave an example: one’s response to the item “I am not a very methodical person” would hinge greatly on one’s understanding of culturally prevalent norms for being methodical. A very methodical person in a culture with extremely high standards of punctuality may score lower than a haphazard person in a culture with relatively low standards of timeliness and punctuality. Because norms obviously differ across cultures, the reference-group effect is likely to distort any cultural differences in personality judgment. Although such implicit standards play a prominent role in political and health assessment (Beegle, Himelein, & Ravallion, 2012; King, Murray, Salomon, & Tandon, 2004; Leon, Arana, & de Leon, 2013), their effects were surprisingly negligible in a recent study of personality judgments (Mõttus, Allik, Realo, Pullmann, et al., 2012). Thus, despite its wide appeal and intuitiveness, the reference-group effect has proven to be surprisingly difficult to prove in cross-cultural personality research using valid and reliable data sets. The reference-group effect is not yet completely understood and requires a lot of further effort to resolve it.
All aforementioned effects could invalidate comparisons of mean level personality traits across cultures. Two mean values corresponding to two different groups, for example nations, can be meaningfully compared only if these two measures are obtained with the help of scales that have equivalent properties (Davidov, Meuleman, Cieciuch, Schmidt, & Billiet, 2014). Only in recent years, testing for the measurement equivalence of personality scales across cultures has slowly become a usual standard in cross-cultural personality research.
The first step in ensuring that two instruments indeed measure the same set of traits is to compare their structures (Davidov et al., 2014; McCrae, Zonderman, Costa, Bond, & Paunonen, 1996). By structure, personality researchers usually mean the pattern of covariation between measured traits. If two instruments have similar or even identical webs of meanings (e.g., scale intercorrelations), then there may be good reason to compare the mean values (i.e., one prerequisite for cross-cultural mean comparisons has been met). One of the most basic facts is that all personality traits tend to group around a relatively small number of themes or factors. For example, it is a universal tendency that individuals who describe themselves as talkative in many situations are also frequently in a positive mood. Another example is intellectual curiosity, which very often goes hand in hand with aesthetic sensitivity. At a certain level of description, the number of reoccurring themes or basic personality traits is not very large. Substantial research evidence shows that five independent dimensions—the Big Five (Goldberg, 1993)—are well replicated across cultures (McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005; Zecca et al., 2013). It is useful to notice, however, that the replicability of the Big Five does not exclude the finding that other models—the Big Three (van Hemert, van de Vijver, Poortinga, & Georgas, 2002) or the Big Six (Thalmayer & Saucier, 2014)—demonstrate a similar level of replicability.
However, the invariance of factor structures is not enough for a legitimate comparison of mean scores across cultural groups. One can compare two means informatively only when these two measures have metric as well as scalar equivalence. In other words, the comparison of different mean scores is only possible when the respondents from different cultures not only have the same intervals between measurement units (i.e., metric equivalence) but also share origins (intercepts) for the items or subscales (i.e., scalar equivalence) that define the trait (Davidov et al., 2014). Scalar invariance, however, is often difficult to achieve because many items of popular personality questionnaires have noninvariances that carry forward to the scale level (Church et al., 2011). As a result, no study so far (e.g., Zecca et al., 2013) has been able to demonstrate scalar invariance for any five-factor personality measurement instrument across a wide range of different cultures and languages. Scalar invariance seems achievable only when the FFM personality questionnaire is being used in the same language and in culturally similar countries as was shown by Rossier, Hansenne, Baudin, and Morizot (2012), who examined the replicability of Zuckerman’s revised Alternative Five-Factor Model in four French-speaking countries (i.e., Belgium, Canada, France, and Switzerland). In short, the accuracy of the average personality scores for cultures or nations cannot be assumed; it should be demonstrated. There are two principal ways to demonstrate the accuracy of the average scores.
First, if two instruments are supposed to measure the same personality trait, they should give approximately the same result when applied to the same distinctive (e.g., cultural) group (not necessarily the same individuals). In the most robust way, if we have N groups, then the rank order of means for these N groups should be sufficiently similar for these two instruments. The convergent correlation between these two measures has to be substantial in size. For example, if the OPQ32 Extraversion scale ranks 31 countries on the basis of average scores, then this ranking is expected to be very similar to the ranking of the same set of countries based on average scores for NEO-PI-R Extraversion (Bartram, 2013). This again explains why we need data sets from at least 20 and preferably even more countries for the analysis.
The second method of validation of average scores is comparison with criterion variables. For example, the average score of Extraversion is usually correlated with the Human Development Index (HDI; Allik & McCrae, 2004). In fact, in countries where respondents report being optimistic, gregarious, and energetic, people are, according to statistics, wealthier, better educated, and healthier. Thus, the HDI serves as a criterion variable for Extraversion presuming that there is a causal link between these two variables. The use of external criterion variables to validate mean level personality scores, however, does not always succeed (see Heine et al., 2008, as an example) because we hardly ever “have solid theories on which to base our selection of the ‘objective’ external criteria” (Mõttus, Allik, & Realo, 2010, p. 631). In addition, we cannot predict the direction of causation based on correlation coefficients alone. It is possible that populations with a high concentration of extraverts are more capable of actions and social practices that lead to a higher level of human development compared with societies where introverts are more prevalent. It also can go the other way around: places with higher living standards may attract more extraverts. Another possibility is that in countries with higher living standards respondents regard extraversion as a particularly desirable trait, and they have a tendency to endorse items with this content more than some other items.
In two sections later in this chapter, we review the evidence for the accuracy of mean profiles of cultures, drawing on evidence of convergent validity of cultural rankings based on different instruments and culture-level correlations between mean traits and relevant criterion variables. But first, we overview the many large-scale data sets that have included personality surveys.
We compiled a list of the large-scale personality surveys that involve at least 20 countries or districts and minimally thousands of participants (Table 7.1). Personality is understood here as enduring and stable dispositions to feel, think, and behave in a distinctive way in typical situations (Allik & McCrae, 2002). One important inclusion criterion was that the study reported mean scores at the level of individual countries or regions (there were a few exceptions). Even the smallest number of participants (N = 2,480) is large compared with the usual standards of major journals in social-personality psychology (Fraley & Vazire, 2014). The largest sample had nearly 3 million participants (Gebauer et al., 2015). Included studies analyzed one particular trait (e.g., depression or subjective well-being) or the whole spectrum of traits according to some personality trait taxonomy (e.g., Cattell’s 16 personality factors, Eysenck’s Big Three, the Big Five, or the Big Six). The border between personality traits and some other constructs, such as well-being and values, is not clear. We included a few studies of well-being and emotional experience if they involved some other explicit personality measures (Fischer & Boer, 2011; Tay & Diener, 2011). However, we deliberately excluded perhaps the two largest cross-national projects—the World Value Survey and European Social Survey—because they did not include direct measures of personality.
Table 7.1 lists 33 large-scale studies in which country- or region-level mean scores are reported on certain personality traits. Perhaps we missed some relevant studies but hopefully this is a representative list. All these studies together involved approximately 6 million participants. We hope that this table will serve as a catalog of studies from which interested readers can obtain culture-level scores for their own studies examining culture-level profiles or convergent culture-level correlations of different personality measures.
Some of these data were collected during surveys carried out simultaneously in various study sites, while other studies are compilations of previously published data. Most of the studies listed in Table 7.1 used the self-report format: participants answered items describing how they think, feel, or act in some typical situations. Other studies used other-reports: participants were asked to describe the personality of someone they know sufficiently well. In two studies (Allik, Mõttus, & Realo, 2010; Terracciano et al., 2005) participants were instructed to describe not a particular individual but a prototypical representative of the whole nation (i.e., national stereotypes). In most of the listed studies, convenience or self-selected samples were used. The lack of representative or randomly chosen samples is one of the serious shortcomings of these studies.
| Study | Participants | Countries/Regions | Measure/Data | Instrument | Language(s) | Type of Research | Traits |
|---|---|---|---|---|---|---|---|
| Krug & Kulhavy, 1973 | 6,444 | 36 states, 6 regions (USA) | Self-report | 16PF | English | Original | Cattell’s 16 personality factors |
| Barrett & Eysenck, 1984 | 13,334 | 25 | Self-report | EPQ | ? | Compilation | Eysenck’s Big Three |
| Lynn & Martin, 1995 | 39,285 | 37 | Self-report | EPQ | ? | Compilation | Eysenck’s Big Three |
| van Hemert, van de Vijver, Poortinga, & Georgas, 2002 | 68,574 | 38 | Self-report | EPQ | ? | Compilation | Eysenck’s Big Three |
| van Hemert, van de Vijver, & Poortinga, 2002 | 44,098 | 28 | Self-report | Beck Depression Inventory (BDI) | ? | Compilation | Depression |
| McCrae, 2001, 2002 | 27,944 | 36 | Self-report | NEO-PI-R | 27 languages | Compilation | Big Five (30 facets) |
| Srivastava et al., 2003 | 132,515 | 50+ | Self-report | BFI | English | Original | Big Five |
| McCrae & Terracciano, 2008; McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005 | 11,985 | 50 | Other-report | NEO-PI-R | 27 languages | Original | Big Five (30 facets) |
| Schmitt & Allik, 2005 | 16,998 | 53 | Self-report | RSES | 26 languages | Original | Self-Esteem |
| Terracciano et al., 2005 | 3,989 | 49 | Stereotype reports | NCS | 27 languages | Original | Big Five (National character) |
| Miettunen et al., 2006 | 16,003 | 20 | Self-report | TPQ, TCI | 16 languages | Compilation | Novelty seeking, harm avoidance, reward dependence, persistence |
| Kuppens, Ceulemans, Timmerman, Diener, & Kim-Prieto, 2006 | 9,300 | 48 | Self-report | Frequency experienced emotions | 31 languages | Original | 14 experienced emotions |
| Schmitt et al., 2007 | 17,837 | 56 | Self-report | BFI | 28 languages | Original | Big Five |
| Rentfrow et al., 2008 | 619,397 | 50 U.S. states | Self-report | BFI | English | Original | Big Five |
| De Fruyt et al., 2009; McCrae et al., 2010 | 5,109 | 24 | Other-report | NEO-PI-R, NEO-PI-3 | 19 languages | Original | Big Five |
| Allik et al., 2009 | 7,065 | 33 regions of Russia | Other-report | NEO-PI-3 | Russian | Original | Big Five (30 facets) |
| Allik, Mõttus, et al., 2010 | 10,770 | 34 regions of Russia | Stereotype reports | NCS | Russian | Original | Big Five (30 facets) |
| Lippa, 2010 | 255,144 | 53 | Self-reports | IPIP | English | Original | N, E, A |
| van Emmerik, Gardner, Wendt, & Fischer, 2010 | 17,538 | 24 | Self-reports | TAT, PSE | ? | Original | McClelland’s motives |
| Mõttus et al., 2010 | < 35,000 | 58 | Self- and other-reports | NEO PI-R | 42 languages | Compilation | Conscientiousness (6 facets) |
| McCrae et al., 2010 | 5,109 | 24 | Other-reports | NEO-PI-3 | 18 | Original | Big Five (30 facets) |
| Fischer & Boer, 2011 | 420,599 | 63 | Self-reports | SWB items, STAI | ? | Compilation | Subjective well-being, anxiety |
| Tay & Diener, 2011 | 60,865 | 123 | Self-report | SWB and basic needs items | < 100 languages | Original | Subjective well-being, basic needs |
| Mõttus, Allik, Realo, Pullmann, et al., 2012 | 2,965 | 21 | Self-reports, vignettes | NCS | 12 languages | Original | Conscientiousness (6 facets) |
| Bartram, 2013 | 1,002,907 | 31 | Self-reports | OPQ32 | 22 | Original | Big Five |
| Obschonka, Schmitt-Rodermund, Silbereisen, Gosling, & Potter, 2013 | 19,739 | 14 regions of Germany | Self-report | BFI | German | Original | Big Five Entrepreneurial personality profile |
| Thalmayer & Saucier, 2014 | 8,883 | 33 | Self-reports | 36QB6 | 19 languages | Original | Big Six (HEXACO) |
| Gebauer et al., 2014 | 1,129,334 20,885 1,057,342 386,315 |
66 15 German federal states 50 U.S. states 121 British urban areas |
Self-report | BFI | 4 languages German English |
Original | Big Five, religiosity |
| Rentfrow, Jokela, & Lamb, 2015 | 386,375 | 380 local authority districts of Great Britain | Self-reports | BPT | English | Original | Big Five |
| Greaves et al., 2015 | 6,518 | 63 general electorate districts of New Zealand | Self-reports | Mini-IPIP6 | English | Original | Big Six (HEXACO) |
| Demes & Geeraert, 2015 | 2,480 | 51 | Self-reports | 60-item HEXACO | 11 languages | Original | Big Six (HEXACO) |
| Gebauer et al., 2015 | 2,718,838 | 106 | Self-report | BFI and single-item self-esteem | 4 languages | Original | Big Five and self-esteem |
Note. IPIP = International Personality Item Pool; OPQ32 = Occupational Personality Questionnaire 32 Scales; BFI = 44-item Big Five Inventory; RSES = 10-item Rosenberg Self-Esteem Scale; BPT = Big Personality Test; NEO-PI-R = Revised NEO Personality Inventory; NEO-PI-3 = NEO Personality Inventory Three; EPQ = Eysenck Personality Questionnaire; 16PF = Cattell Sixteen Personality Factor Questionnaire; STAI = Spielberger State–Trait Anxiety Inventory; TAT/PSE = Thematic Apperception Test and Picture Story Exercise; 36QB6 = Saucier’s 36-item the Big Six Questionnaire; TCI = Cloninger’s Temperament and Character Inventory; TPQ = Cloninger’s Tridimensional Personality Questionnaire; Mini-IPIP6 = 24-item IPIP Six-Factor Scale; HEXACO = The Six Dimensional Model of Personality. |
|||||||
Typically, researchers were interested in data that were collected in countries with substantially different economic, linguistic, and cultural backgrounds. For example, the NEO-PI-R data were collected with at least 42 different languages (Mõttus et al., 2010). It is possible, however, to analyze different regions within one country. Recently, districts of the United States, Great Britain, Germany, New Zealand, and Russian Federation have been studied.
If something is measured on two different occasions or using two different instruments intended to measure the same attribute, we should expect these measures to converge. When the NEO-PI-R mean scores from 36 cultures or territories became available (McCrae, 2002), it was the first time that the convergent validity of alternative measures—in this case, the NEO-PI-R and Eysenck’s EPQ—could be examined. This was possible because both inventories define Neuroticism and Extraversion similarly. Across the 18 overlapping countries, the convergent correlation between self-ratings was remarkably high for Neuroticism (r = .80, p < .01) and more modest for Extraversion (r = .51, p < .05). This was the first positive sign that the national mean scores of personality may be meaningful rather than completely accidental.
The Personality Profiles of Cultures Project asked college students in 50 cultures to identify an adult or college-aged man or woman whom they knew well and to rate the 11,985 targets using the third-person version of the 240-item NEO-PI-R (McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005). The national mean scores of self- and other-ratings were available for 28 overlapping cultures. Three out of five converging correlations were significant: r = .52, p < .01 for Neuroticism; r = .60, p < .001 for Extraversion; and r = .50, p < .01 for Openness (McCrae, Terracciano, & 79 Members of the Personality Profiles of Cultures Project, 2005; Table 3). The convergent correlations for Agreeableness (r = .11) and Conscientiousness (r = .35) were not significant. Although personality profiles of self- and other-ratings are very similar within almost every country studied so far (Allik, Realo, et al., 2010), the existing disparities between self- and other-profiles across cultures are sufficiently large to make only three out of five convergent correlations significant.
David Schmitt directed one of the largest cross-cultural projects, in which 127 collaborators translated the 44-item Big Five Inventory (BFI) from English into 28 languages and administered it to 17,837 individuals from 56 nations (Schmitt et al., 2007). For 27 nations out of 56, national mean scores of self-reported NEO-PI-R data were also available (McCrae, 2002). The convergent correlations between the BFI and the NEO-PI-R nation-level scores were significant only for Neuroticism, r = .45, p < .05; Extraversion, r = .44, p < .05; and Conscientiousness, r = .45, p < .01. The corresponding convergent correlations were positive for Agreeableness (r = .22) and Openness (r = .27) but failed to reach the level of statistical significance at p < .05.
The Occupational Personality Questionnaire (OPQ32) measures 32 work-related personality traits, which also can be organized into the Big Five dimensions. The OPQ32 consists of 104 sets of forced-choice item quads. Recently, the OPQ32 was administered to over 1 million people from 31 countries involving 22 different languages (Bartram, 2013). Out of 31 countries, 21 overlapped with countries for which NEO-PI-R self-report scores were available (McCrae, 2002). The convergent validity between OPQ32I and NEO-PI-R nation-level scores for Neuroticism, r = .77, p < .05, and Extraversion, r = .74, p < .05 were again significant. However, the convergent correlations for Openness (r = .27), Agreeableness (r = .22), and Conscientiousness (r = .20) did not reach significance (Bartram, 2013; Table 9).
There were 23 overlapping countries/territories for the studies using the OPQ32 (Bartram, 2013) and the BFI (Schmitt et al., 2007). For these two instruments, the convergent correlation was again significant for Neuroticism, r = .55, p < .05, and, surprisingly, also for Conscientiousness, r = .48, p < .05. Unexpectedly, the convergent correlations for Extraversion (r = −.27), Openness (r = −.35), and Agreeableness (r = −.24) were actually negative (Bartram, 2013; Table 9).
Thus, even this limited set of comparisons demonstrates that the convergent correlations between different national mean scores are sometimes problematic. Only the mean scores for Neuroticism demonstrated a sufficient level of convergence in most cases. Extraversion failed to converge at least once. Three of the Big Five dimensions—Openness, Agreeableness, and Conscientiousness—failed to converge more often than not.
Although this poor convergence is disappointing, this is not necessarily a signal to abandon cross-cultural comparisons entirely. One should bear in mind that in all of the aforementioned cases convergence was examined between two different instruments. In theory, different personality measures of the same trait are expected to be similar, but they still appear to diverge. For example, even at the individual level, Konstabel, Lönnqvist, Walkowitz, Konstabel, and Verkasalo (2012) found only moderate agreement between self-reports provided on the NEO-PI-R (Costa & McCrae, 1992) and the National Character Survey (NCS; Terracciano et al., 2005); the correlations ranged between .19 and .74 with a median of .55. Moreover, Hřebíčková and Graf (2014) showed that the correlations between the NCS self-reports and NEO-PI-R self-reports and observer ratings in the Czech subsample were near zero (intraclass correlation [ICC] = .04 and .14, respectively). These not-so-small disparities between instruments at the individual level, however, are enough to compromise the convergent correlations between two different instruments at the cultural level. Unfortunately, there are few studies using the same instrument in two different studies. Recently, there was an attempt to study self-reported conscientiousness in 21 different countries or territories using the six NEO-PI-R subscales for Conscientiousness (Mõttus, Allik, Realo, Pullmann, et al., 2012). Out of these 21 countries, 16 were previously tested with the NEO-PI-R (McCrae, 2002). The convergent correlation between the summary scores of these overlapping 16 cases was r = .67, p < .005. This is a modest demonstration that if we administer the same personality instruments twice, at different moments of time and to different samples, the national mean scores can remain relatively stable.
However, one of the main reasons for disappointment with low convergent correlations may be the unfounded expectations of researchers. For example, if we administer two personality questionnaires that presumably measure the same personality traits to the same group of individuals, the convergent correlations typically range from .70 to .80. As an example, in a study by John, Naumann, and Soto (2008), the convergent correlations between corresponding scales of the NEO Five-Factor Inventory (NEO-FFI; a shorter version of NEO-PI-R) and the BFI ranged from .72 (Openness) to .81 (Neuroticism). Compared with these values, convergent correlations between national mean scores in the range .30–.40 may look hopelessly low. However, we need to take into account the much smaller scale variances at the national level. As mentioned earlier, the national level variances may be up to nine times smaller than the individual level variances. Thus, if we want to compare correlations computed on data with restricted versus less restricted variances, we need to apply a formula such as the Thorndike Case 2 (Thorndike, 1949). For example, suppose that the correlation computed on data with unrestricted variance is .80. If the same data have the variance restricted by a factor of three, the expected correlation drops to .41. Or, in the extreme case, if the variance of the national mean scores is indeed restricted by a factor of nine relative to the individual level variance, then the correlation is expected to drop from .80 to .15. To put it bluntly, we cannot anticipate very high correlations when variables change in a very limited range.
In the previous section, we considered only the convergent correlations between different measures of particular traits. However, there are two basic ways to compute agreement between two set of judgments. Besides trait-by-trait congruence there is also profile agreement, in which profiles of scores across multiple traits are compared. Unfortunately, we know very few studies in which this form of convergence was tested (for exceptions see Hřebíčková & Graf, 2014; Realo et al., 2009).
As an example, the collaborators of the Adolescent Personality Profiles of Cultures Project asked participants in 24 cultures to rate the personality traits of a college student and a boy or girl, aged 12–17, that they knew sufficiently well using the NEO-PI-3 (De Fruyt et al., 2009; McCrae et al., 2010). Assuming that personality profiles do not change radically with age, it was expected that the country mean profiles of students resemble, to a certain degree at least, the mean profiles of adults from the same country. Previously, the nearly same NEO-PI-R instruments were used to obtain self-rated (McCrae, 2002; McCrae & Terracciano, 2008) or observer-rated (McCrae, Terracciano, & 78 Members of the Personality Profiles of Cultures Project, 2005; McCrae, Terracciano, & 79 Members of the Personality Profiles of Cultures Project, 2005) adult profiles in many of these 24 cultures. Thus, it was possible to estimate congruence between the adolescent and adult mean profiles. Agreement between the adolescent NEO-PI-3 profiles and the adult NEO-PI-R profiles was measured with ICC and Cohen’s rC, both of which are insensitive to the direction (low or high) in which the traits are coded. Across 24 cultures the median ICC = .48 and rC = .54 (McCrae et al., 2010; Table 4). In addition, for 16 of 24 cultures, self-rated NEO-PI-R profiles were available, with the median ICC = .40 and rC = .45. Thus, the mean personality profiles of countries tend to converge to one particular shape even if they are measured in different age groups and using different instructions (i.e., self- or other-ratings).
Thus, agreement between profiles provides a more optimistic picture regarding the convergence of culture-level mean trait scores. Although agreement between two profiles tells us very little about their accuracy, it is a required condition if we are to view the aggregate values of personality scores to represent something real.
One of the first studies in which the geography of personality was examined established two intuitively plausible rules (Allik & McCrae, 2004). First, it was noticed that geographically proximate cultures tend to be more similar than distant ones. In particular, a clear contrast of European and American cultures with Asian and African cultures was observed. The former were higher in extraversion and openness to experience and lower in agreeableness. Second, the distribution of personality traits was correlated with socioeconomic indicators. Countries or territories where people score high on extraversion are economically more prosperous and have higher levels of human development. As another example, high levels of neuroticism are usually associated with negative outcomes such as death from heart diseases or cancer (Rentfrow et al., 2008; Table 5). These studies left little room for doubt that personality and culture are indeed somehow connected.
Although some of the links between personality traits and criterion variables look very natural, each of these links requires an explicit theory explaining how these two variables are connected. There are two principal approaches to explaining the link between personality and culture (Hofstede & McCrae, 2004). Hofstede proposed that culture programs people’s minds and behavior, leading to personality traits that fit a particular culture. In the same paper, McCrae defended a radically different view according to which personality dispositions may shape culture. One specific mechanism underlying how this could happen is selective migration. For example, it was observed that countries that are inhabited by immigrants have higher levels of extraversion than the countries from which the immigrants came (Lynn & Martin, 1995). Indeed, an elegant study showed that individuals with higher levels of extraversion (and openness) are more ready to move from one place to another (Camperio Ciani & Capiluppi, 2011; Camperio Ciani, Capiluppi, Veronese, & Sartori, 2007). In spite of the sharp contrast between these two causal explanations, they do not exclude each other.
However, researchers soon noticed that some links between personality and culture are counterintuitive or even paradoxical. For example, Levine and Norenzayan (1999) measured the pace of life in large cities from 31 countries around the world. Three indicators of pace of life were observed: average walking speed in downtown locations, the speed with which postal clerks completed a simple request (work speed), and the accuracy of public clocks. Overall, pace of life was fastest in Japan and the countries of Western Europe and was slowest in economically less developed countries. However, when Heine et al. (2008) correlated the pace of life with self-reported measures of conscientiousness, the outcome was not in the direction of the authors’ expectations. In fact, the pace of life was faster in countries where people reported themselves to be less conscientious (i.e., less active in planning and organizing and carrying out their actions lackadaisically).
Indeed, some correlations between personality traits and criterion variables may look paradoxical (Mõttus et al., 2010). For example, analyzing the correlations between personality traits and socioeconomic indicators at the state level, Rentfrow et al. (2008) found that life expectancy is negatively related to conscientiousness, r = −.44, p < .05. Even more paradoxically, both robbery and murder per capita are higher in U.S. states where people score higher on openness to experience (Rentfrow et al., 2008; Table 6). These paradoxical correlations remained significant even after various socio-demographic characteristics were controlled. Perhaps most controversial is the finding that lower, not higher, levels of neuroticism are associated with higher American state suicide rates (McCann, 2010). Of course, nobody doubts that people commit suicide mainly because they feel depressed and desperately unhappy. However, at the aggregate national level, there is a tendency for a positive correlation between happiness and the suicide rate: in countries where more people are generally happy and satisfied with their lives (e.g., Iceland), the suicide rate is higher than in those countries where people tend to feel more miserable (Inglehart, 1990). To make sense of this paradox, one needs to take into account the very small number of people who commit suicide. Their feelings are unlikely to be significantly represented in aggregate scores, which are largely based on the responses of people who do not contemplate committing suicide. It may be the case that individuals who commit suicide are unable to cope with the social demand to be happy and that this demand is greater in societies with increasing levels of general happiness (Inglehart, 1990).
We need to admit that the link between mean levels of personality traits and relevant criterion variables is not entirely clear. In addition, there are few refined theories explaining this link. Instead of comprehensive theories, we have vague speculations, which very rarely go beyond common sense, which, as we all know, can often go astray.
In many cases, as we have already mentioned, the relationship looks confusing if not paradoxical. First, the relationship may contradict common sense. Nobody believes, for example, that high conscientiousness leads to criminal intent and high homicide rates. Second, individual-level data for conscientiousness obviously contradict aggregate or country-level data in terms of the signs of the correlations. Returning to an aforementioned example, although happy people have no inclination to commit suicide, countries where people are generally satisfied with their lives often have higher suicide rates.
There are some relatively simple prescriptions for how to handle paradoxes of this kind (Mõttus et al., 2010). The first prescription is to move from general traits to facets that are more specific. In some cases, a criterion variable may be related to different facets of the trait in the opposite direction. For example, Mõttus et al. (2010; Table 3) found that the HDI has a positive correlation with observer-rated Dutifulness (.58) but a negative correlation with Deliberation (−.40), although both are facets of a more general Conscientiousness trait.
The second remedy for paradoxes is to look for mediator variables (Baron & Kenny, 1986). There seems to be a strong link between personality traits and the socioeconomic conditions in which people live (Allik & McCrae, 2004; Hofstede & McCrae, 2004). Accordingly, it is possible that the association between a personality trait and criterion variable is mediated by economic conditions. This is why it is recommended that researchers examine the correlations between mean personality scores and criterion variables after controlling for the effect of economic wealth (e.g., Gross Domestic Product [GDP]). For example, somewhat surprisingly, democracy (r = −.50) and economic freedoms (r = −.48) are negatively related to aggregate scores of Conscientiousness (Mõttus et al., 2010; Table 3). However, these counterintuitive correlations disappear when the effect of GDP is partialled out. Thus, these spurious correlations were caused by economic factors, not personality per se.
The third recommendation is to revise initial expectations and look for more nuanced explanations. As an example, consider again a hypothetical relationship between conscientiousness and democracy (Mõttus et al., 2010). As we already saw, the country mean score of self-rated conscientiousness was negatively related to the Democracy Index, which covers such aspects as fairness of electoral processes and pluralism, civil liberties, the functioning of government, political participation, and political culture. This result obviously contradicts the argument that the maintenance of democracy presupposes not only efficient regulation and a transparent legal system but also competent and responsible people. Therefore, one could expect that in countries that are more democratic, citizens are more responsible and disciplined, resulting in a positive correlation between the level of democracy and mean national scores of conscientiousness. In reality, nondemocratic regimes seem to endorse hard work, discipline, and order in society. According to Inglehart and Welzel (2005), effective democracy is much more likely to be found in cultures with a strong emphasis on self-expression values, whereas dutifulness, order, and hard work are the correlates of survival values, the opposite of self-expression values. Thus, it can be argued that in countries with higher scores of conscientiousness—that is, where people are rule-abiding, inhibited by social constraints, and keen on keeping order—people are not able to realize their potential for freedom and autonomy, which, in turn, are the cornerstones of democracy (Mõttus et al., 2010).
Because it is expensive and time consuming to collect personality data from a large number of countries or territories, the number of large-scale personality projects remains relatively modest. If we exclude compilations of already existing data, then the number of original studies is even smaller. In the largest project so far, respondents from 106 countries or territories were involved (Gebauer et al., 2015). Two studies were able to recruit more than 1 million participants who were willing to complete a personality questionnaire (Bartram, 2013; Gebauer et al., 2015).
All these studies, without exception, have demonstrated that geographical and hence cultural differences in personality are small compared to interindividual differences within samples. According to a preliminary estimate, between-country differences are typically nine times smaller than differences between any two individuals randomly chosen from the same country or territory. This huge difference is not trivial because it affects our potential ability to assess national differences in personality in an accurate manner. In other words, because geographical and cultural differences in personality are relatively small, their precise measurement is a complicated task. Personality judgments are notoriously noisy. Besides personality traits themselves, such judgments often reflect other realities such as social desirability, response biases, and stereotypes. Due to the unfavorable signal-to-noise ratio, many researchers have doubted if country mean personality scores can be trusted. Reflecting these fears, the convergence between different instruments (BFI vs. NEO-PI-R) and instructions (self-ratings vs. observer ratings) is not always exemplary. Measures of Neuroticism and Extraversion converge better than measures of the remaining Big Five traits: Openness, Agreeableness, and Conscientiousness. One likely reason for divergence is differences in how different instruments operationalize the Big Five traits. For example, it is unlikely that the OPQ32 (Bartram, 2013), which was devised to measure primarily work-related personality traits, conceptualizes Agreeableness and Conscientiousness exactly as it is done in the NEO-PI-R (Costa & McCrae, 1992). However, the picture is slightly more favorable when convergence between the same instruments is observed. In addition, instead of comparing the rankings of countries or territories on individual traits, it is also possible to compare profiles of the mean scores across multiple personality traits. The country mean personality profiles tend to converge to one particular shape that is characteristic of this country or territory (McCrae et al., 2010).
Rankings of countries or regions on personality traits are psychologically meaningful. Geographically or culturally proximate countries (or regions) tend to occupy similar positions in personality rankings. For example, European countries tend to have high aggregate scores for Extraversion, while many African and Asian countries are on the opposite pole of the scale. Consequently, regular patterns may occur in the geographic distribution of countries or regions (Allik & McCrae, 2004; Gelade, 2013; Obschonka et al., 2013; Rentfrow et al., 2008; Schmitt et al., 2007).
Researchers and thinkers long ago suspected that certain recordable social indicators such as habits and practices reflect personality traits that are prevalent in the society. Only after inventing personality questionnaires was it possible to demonstrate that some of these indicators are indeed related to personality dispositions. Many of these relations between personality traits and potential criterion variables are in the expected direction. For example, it is quite natural that countries with high aggregate scores for extraversion are also economically wealthy and have a well-educated population with good prospects for a long and healthy life (Allik & McCrae, 2004; Bartram, 2013). Regretfully, however, this apparently obvious link between extraversion and economic success was not always replicated in available data (Lynn & Martin, 1995; Rentfrow et al., 2008).
Like personality measures, some social indicators are collected using self-reports. With few exceptions, there is a strong positive correlation between extraversion and life satisfaction. In places where people are satisfied with their lives, they usually report higher levels of extraversion (Allik & McCrae, 2004; Jokela, Bleidorn, Lamb, Gosling, & Rentfrow, 2015). However, it is impossible to postulate a causal link between extraversion and life satisfaction. For instance, in order to demonstrate that high extraversion is a cause of greater life satisfaction, one should prove that the existence of one of them is not dependent upon the existence of the other. If positive emotions—the core of extraversion (Lucas, Diener, Grob, Suh, & Shao, 2000)—are an essential part of life satisfaction, then it makes no sense to postulate a causal link between these two concepts.
More often than expected, the relationships found between mean personality traits and criterion variables seem to be counterintuitive or paradoxical. We already mentioned that people do not commit suicide because they are happy. Nevertheless, in happy places to live, the percentage of those who commit suicide tends to be higher (McCann, 2010). Another example was conscientiousness, which seems to consistently form paradoxical relationships with criterion variables (Mõttus et al., 2010). As we already mentioned, it makes no sense that higher levels of conscientiousness in the society are behind murder and robbery per capita, to say nothing of the frequency of mortality from heart diseases (Rentfrow et al., 2008). All these examples tell us that the story behind the link between personality traits and their societal consequences is rarely a simple one. As a rule, the chain of events from personality dispositions to societal and real-life consequences is rather intricate. Most personality psychologists agree that personality has consequences (Ozer & Benet-Martinez, 2006). Unfortunately, we have very few examples of elaborated theories that can trace the whole chain of events from personality to observable consequences. Nonetheless, and despite the complexities noted here, we believe that large-scale cross-cultural comparisons have unique potential to reveal predictive relationships between personality and a variety of important outcomes.
Jüri Allik and Anu Realo, Department of Psychology, University of Tartu, Estonia. Writing of this chapter was supported by institutional research funding (IUT2-13) from the Estonian Ministry of Education and Science. Anu Realo was a Visiting Professor in the Health, Medical, and Neuropsychology department of the Faculty of Social and Behavioural Sciences at Leiden University (The Netherlands) during the writing of this article. We thank A. Timothy Church and Jérôme Rossier for their helpful comments on earlier drafts of this article.
Correspondence concerning this chapter should be addressed to Jüri Allik, Department of Psychology, University of Tartu, Näituse 2, Tartu 50409, Estonia. Electronic mail may be sent to juri.allik@ut.ee.
Allik, J. (2005). Personality dimensions across cultures. Journal of Personality Disorders, 19, 212–232.
Allik, J., Massoudi, K., Realo, A., & Rossier, J. (2012). Personality and culture: Cross-cultural psychology at the next crossroads. Swiss Journal of Psychology, 71, 5–12.
Allik, J., & McCrae, R. R. (2002). A Five-Factor Theory perspective. In R. R. McCrae & J. Allik (Eds.), The Five Factor Model of personality across cultures (pp. 303–322). New York, NY: Kluwer Academic/Plenum Publishers.
Allik, J., & McCrae, R. R. (2004). Toward a geography of personality traits: Patterns of profiles across 36 cultures Journal of Cross-Cultural Psychology, 35, 13–28.
Allik, J., Mõttus, R., & Realo, A. (2010). Does national character reflect mean personality traits when both are measured by the same instrument? Journal of Research in Personality, 44, 62–69.
Allik, J., Realo, A., & McCrae, R. R. (2013). Universality of the Five-Factor Model of personality. In P. T. Costa, Jr. & T. Widiger (Eds.), Personality disorders and the Five Factor Model of personality (pp. 61–74). Washington, DC: American Psychological Association.
Allik, J., Realo, A., Mõttus, R., Borkenau, P., Kuppens, P., & Hřebíčková, M. (2010). How people see others is different from how people see themselves: A replicable pattern across cultures. Journal of Personality and Social Psychology, 94, 168–182.
Allik, J., Realo, A., Mõttus, R., Pullmann, H., Trifonova, A., McCrae, R. R., & 56 Members of the Russian Character and Personality Survey. (2009). Personality traits of Russians from the observer’s perspective. European Journal of Personality, 23, 567–588.
Allport, G. W. (1954/1978). The nature of prejudice (25th Anniversary ed.). New York, NY: Basic Books.
Baron, R. M., & Kenny, D. A. (1986). The moderator mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.
Barrett, P., & Eysenck, S. B. G. (1984). The assessment of personality factors across 25 countries. Personality and Individual Differences, 5, 615–632.
Bartram, D. (2013). Scalar equivalence of OPQ32: Big Five profiles of 31 countries. Journal of Cross-Cultural Psychology, 44, 61–83.
Beegle, K., Himelein, K., & Ravallion, M. (2012). Frame-of-reference bias in subjective welfare. Journal of Economic Behavior & Organization, 81, 556–570.
Berry, J. W., Poortinga, Y. H., Breugelmans, S. M., Chasiotis, A., & Sam, D. L. (2011). Cross-cultural psychology: Research and applications (3rd ed.). New York, NY: Cambridge University Press.
Camperio Ciani, A., & Capiluppi, C. (2011). Gene flow by selective emigration as a possible cause for personality differences between small islands and mainland populations. European Journal of Personality, 25, 53–64.
Camperio Ciani, A., Capiluppi, C., Veronese, A., & Sartori, G. (2007). The adaptive value of personality differences revealed by small island population dynamics. European Journal of Personality, 21, 3–22.
Church, A. T. (2016). Personality traits across cultures. In M. Gelfand & Y. Kashima (Eds.), Current Opinion in Psychology, 8, 22–30. doi: 10.1016/j.copsyc.2015.09.014
Church, A. T., Alvarez, J. M., Mai, N. T. Q., French, B. F., Katigbak, M. S., & Ortiz, F. A. (2011). Are cross-cultural comparisons of personality profiles meaningful? Differential item and facet functioning in the Revised NEO Personality Inventory. Journal of Personality and Social Psychology, 101, 1068–1089.
Connelly, B. S., & Ones, D. S. (2008). The personality of corruption: A national-level analysis. Cross-Cultural Research, 42, 353–385.
Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources.
Darwin, C. R. (1872/1989). The expression of the emotions in man and animals (P. Ekman Ed. 3rd ed.). London, England: Harper Collins.
Davidov, E., Meuleman, B., Cieciuch, J., Schmidt, P., & Billiet, J. (2014). Measurement equivalence in cross-national research. Annual Review of Sociology, 40, 55–75.
De Fruyt, F., De Bolle, M., McCrae, R. R., Terracciano, A., Costa, P. T., Jr., & Collaborators of the Adolescent Personality Profiles of Cultures Project. (2009). Assessing the universal structure of personality in early adolescence: The NEO PI-R and NEO PI-3 in 24 cultures. Assessment, 16, 301–311.
Demes, K. A., & Geeraert, N. (2015). The highs and lows of a cultural transition: A longitudinal analysis of sojourner stress and adaptation across 50 countries. Journal of Personality and Social Psychology, 109, 316–337.
Durkheim, E. (1897/1952). Suicide: A study in sociology. London, England: Routledge & K. Paul.
Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140.
Fischer, R., & Boer, D. (2011). What is more important for national well-being: Money or autonomy? A meta-analysis of well-being, burnout, and anxiety across 63 societies. Journal of Personality and Social Psychology, 101, 164–184.
Fraley, R. C., & Vazire, S. (2014). The N-Pact factor: Evaluating the quality of empirical journals with respect to sample size and statistical power. Plos One, 9(10). doi: 10.1371/journal.pone.0109019
Freeman, R. B. (1977). The works of Charles Darwin: An annotated bibliographical handlist (2nd ed.). Folkestone, England: Wm Dawson & Sons.
Funder, D. C. (2012). Accurate personality judgment. Current Directions in Psychological Science, 21, 177–182.
Gebauer, J. E., Bleidorn, W., Gosling, S. D., Rentfrow, P. J., Lamb, M. E., & Potter, J. (2014). Cross-cultural variations in Big Five relationships with religiosity: A sociocultural motives perspective. Journal of Personality and Social Psychology, 107, 1064–1091.
Gebauer, J. E., Sedikides, C., Wagner, J., Bleidorn, W., Rentfrow, P. J., Potter, J., & Gosling, S. D. (2015). Cultural norm fulfillment, interpersonal belonging, or getting ahead? A large-scale cross-cultural test of three perspectives on the function of self-esteem. Journal of Personality and Social Psychology, 109, 526–548.
Gelade, G. A. (2013). Personality and place. British Journal of Psychology, 104, 69–82.
Gellner, E. (1983). Nations and nationalism. Ithaca, NY: Cornell University Press.
Gilman, R., Huebner, E. S., Tian, L., Park, N., O’Byrne, J., Schiff, M., … Langknecht, H. (2008). Cross-national adolescent multidimensional life satisfaction reports: Analyses of mean scores and response style differences. Journal of Youth and Adolescence, 37, 142–154.
Goldberg, L. R. (1993). The structure of phenotypic personality traits. American Psychologist, 48, 26–34.
Greaves, L. M., Cowie, L. J., Fraser, G., Muriwai, E., Huang, Y., Milojev, P., … Clouston, A. (2015). Regional differences and similarities in the personality of New Zealanders. New Zealand Journal of Psychology, 44, 4–16.
He, J., Bartram, D., Inceoglu, I., & van de Vijver, F. J. R. (2014). Response styles and personality traits: A multilevel analysis. Journal of Cross-Cultural Psychology, 45, 1028–1045.
Heine, S. J., Buchtel, E. E., & Norenzayan, A. (2008). What do cross-national comparisons of personality traits tell us? The case of conscientiousness. Psychological Science, 19, 309–313.
Helliwell, J. F., Layard, R., & Sachs, J. (2015). World happiness report 2015. New York, NY: UN Sustainable Development Solutions Network.
Hirsh, J. B. (2015). Extraverted populations have lower savings rates. Personality and Individual Differences, 81, 162–168.
Hofstede, G. (1980). Culture’s consequences: International differences in work-related values. Beverly Hills, CA: Sage.
Hofstede, G., Hofstede, G.-J., & Minkov, M. (2010). Cultures and organizations: Software of the mind (3rd ed.). New York, NY: McGraw-Hill.
Hofstede, G., & McCrae, R. R. (2004). Personality and culture revisited: Linking traits and dimensions of culture. Cross-Cultural Research, 38, 52–88.
Hřebíčková, M., & Graf, S. (2014). Accuracy of national stereotypes in Central Europe: Outgroups are not better than ingroup in considering personality traits of real people. European Journal of Personality, 28, 60–72.
Inglehart, R. (1990). Culture shift in advanced industrial society. Princeton, NJ: Princeton University Press.
Inglehart, R., & Welzel, C. (2005). Modernization, cultural change, and democracy: The human development sequence. New York, NY: Cambridge University Press.
Javeline, D. (1999). Response effects in polite cultures: A test of acquiescence in Kazakhstan. Public Opinion Quarterly, 63, 1–28.
John, Oliver 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 (3rd ed., pp. 114–158). New York, NY: Guilford Press.
Jokela, M., Bleidorn, W., Lamb, M. E., Gosling, S. D., & Rentfrow, P. J. (2015). Geographically varying associations between personality and life satisfaction in the London metropolitan area. Proceedings of the National Academy of Sciences, 112, 725–730.
King, G., Murray, C. J. L., Salomon, J. A., & Tandon, A. (2004). Enhancing the validity and cross-cultural comparability of measurement in survey research. American Political Science Review, 98, 191–207.
Konstabel, K., Lönnqvist, J.-E., Walkowitz, G., Konstabel, K., & Verkasalo, M. (2012). The “Short Five” (S5): Measuring personality traits using comprehensive single items. European Journal of Personality, 26, 13–29.
Krug, S. E., & Kulhavy, R. W. (1973). Personality differences across regions of the United States. Journal of Social Psychology, 91, 73–79.
Kuppens, P., Ceulemans, E., Timmerman, M. E., Diener, E., & Kim-Prieto, C. (2006). Universal intracultural and intercultural dimensions of the recalled frequency of emotional experience. Journal of Cross-Cultural Psychology, 37, 491–515.
Lederer, D. (2013). Sociology’’s “one law”: Moral statistics, modernity, religion, and German nationalism in the suicide studies of Adolf Wagner and Alexander von Oettingen. Journal of Social History, 46, 684–699.
Lee, Y.-T., Jussim, L. J., & McCauley, C. R. (1995). Stereotype accuracy: Toward appreciating group differences. Washington, DC: American Psychological Association.
Leon, C. J., Arana, J. E., & de Leon, J. (2013). Correcting for scale perception bias in measuring corruption: An application to Chile and Spain. Social Indicators Research, 114, 977–995.
Levine, R. V., & Norenzayan, A. (1999). The pace of life in 31 countries. Journal of Cross-Cultural Psychology, 30, 178–205.
Lippa, R. A. (2010). Sex differences in personality traits and gender-related occupational preferences across 53 nations: Testing evolutionary and social-environmental theories. Archives of Sexual Behavior, 39, 619–636.
Lönnqvist, J. E., Konstabel, K., Lönnqvist, N., & Verkasalo, M. (2014). Accuracy, consensus, in-group bias, and cultural frame shifting in the context of national character stereotypes. Journal of Social Psychology, 154, 40–58.
Lucas, R. E., Diener, E., Grob, A., Suh, E. M., & Shao, L. (2000). Cross-cultural evidence for the fundamental features of Extraversion. Journal of Personality and Social Psychology, 79, 452–468.
Lynn, R. (1971). Personality and national character. Oxford, England: Pergamon Press.
Lynn, R., & Martin, T. (1995). National differences for thirty-seven nations in extraversion, neuroticism, psychoticism and economic, demographic and other correlates. Personality and Individual Differences, 19, 403–406.
Maniaci, M. R., & Rogge, R. D. (2014). Conducting research on the Internet. In H. T. Reis & C. M. Judd (Eds.), Handbook of research methods in social and personality psychology (2nd ed., pp. 443–470). New York, NY: Cambridge University Press.
Markus, H. R., & Kitayama, S. (1991). Culture and self: Implications for cognition, emotion, and motivation. Psychological Review, 98, 224–253.
McCann, S. J. H. (2010). Suicide, Big Five personality factors, and depression at the American state level. Archives of Suicide Research, 14, 368–374.
McCrae, R. R. (2001). Trait psychology and culture: Exploring intercultural comparisons. Journal of Personality, 69, 819–846.
McCrae, R. R. (2002). NEO PI-R data from 36 cultures: Further intercultural comparisons. In R. R. McCrae & J. Allik (Eds.), The Five-Factor Model of personality across cultures (pp. 105–125). New York, NY: Kluwer Academic/Plenum Publishers.
McCrae, R. R., Chan, W., Jussim, L., De Fruyt, F., Löckenhoff, C. E., De Bolle, M., … Terracciano, A. (2013). The inaccuracy of national character stereotypes. Journal of Research in Personality, 47, 831–842.
McCrae, R. R., & Costa, P. T., Jr. (2010). NEO Inventories professional manual. Odessa, FL: Psychological Assessment Resources.
McCrae, R. R., & Terracciano, A. (2008). The Five-Factor Model and its correlates in individuals and cultures. In F. van de Vijver, D. A. van Hemert, & Y. H. Poortinga (Eds.), Multilevel analysis of individuals and cultures (pp. 249–283). New York, NY: Lawrence Erlbaum Associates.
McCrae, R. R., Terracciano, A., & 78 Members of the Personality Profiles of Cultures Project. (2005). Universal features of personality traits from the observer’s perspective: Data from 50 cultures. Journal of Personality and Social Psychology, 88, 547–561.
McCrae, R. R., Terracciano, A., & 79 Members of the Personality Profiles of Cultures Project. (2005). Personality profiles of cultures: Aggregate personality traits. Journal of Personality and Social Psychology, 89, 407–425.
McCrae, R. R., Terracciano, A., De Fruyt, F., De Bolle, M., Gelfand, M. J., Costa, P. T., Jr., & 42 Collaborators of the Adolescent Personality Profiles of Culture Project. (2010). The validity and structure of culture-level personality scores: Data from ratings of young adolescents. Journal of Personality, 78, 815–838.
McCrae, R. R., Zonderman, A. B., Costa, P. T., Jr., Bond, M. H., & Paunonen, S. V. (1996). Evaluating replicability of factors in the Revised NEO Personality Inventory: Confirmatory factor analysis versus Procrustes rotation. Journal of Personality and Social Psychology, 70, 552–566.
Meisenberg, G. (2015). Do we have valid country-level measures of personality? Mankind Quarterly, 55, 360–382.
Miettunen, J., Kantojärvi, L., Veijola, J., Jarvelin, M. R., & Joukamaa, M. (2006). International comparison of Cloninger’s temperament dimensions. Personality and Individual Differences, 41, 1515–1526.
Mõttus, R., Allik, J., & Realo, A. (2010). An attempt to validate national mean scores of conscientiousness: No necessarily paradoxical findings. Journal of Research in Personality, 44, 630–640.
Mõttus, R., Allik, J., Realo, A., Pullmann, H., Rossier, J., Zecca, G., … Tseung, C. N. (2012). Comparability of self-reported conscientiousness across 21 countries. European Journal of Personality, 26, 303–317.
Mõttus, R., Allik, J., Realo, A., Rossier, J., Zecca, G., Ah-Kion, J., … Johnson, W. (2012). The effect of response style on self-reported conscientiousness across 20 countries. Personality and Social Psychology Bulletin, 38, 1423–1436.
Murray, D. R., & Schaller, M. (2010). Historical prevalence of infectious diseases within 230 geopolitical regions: A tool for investigating origins of culture. Journal of Cross-Cultural Psychology, 41, 99–108.
Niszczota, P. (2014). Cross-country differences in personality and the foreign bias in international equity portfolios. European Journal of Finance, 20, 934–956. doi: 10.2139/ssm.2338131
Obschonka, M., Schmitt-Rodermund, E., Silbereisen, R. K., Gosling, S. D., & Potter, J. (2013). The regional distribution and correlates of an entrepreneurship-prone personality profile in the United States, Germany, and the United Kingdom: A socioecological perspective. Journal of Personality and Social Psychology, 105, 104–122.
Oettingen, A. K. V. (1882). Die moralstatistik in ihrer bedeutung für eine socialethik (3., vollständig umgearb. Aufl. ed.). Erlangen, Germany: A. Deichert.
Ozer, D. J., & Benet-Martinez, V. (2006). Personality and the prediction of consequential outcomes. Annual Review of Psychology, 57, 401–421.
Pennebaker, J. W., Rime, B., & Blankenship, V. E. (1996). Stereotypes of emotional expressiveness of northerners and southerners: A cross-cultural test of Montesquieu’s hypotheses. Journal of Personality and Social Psychology, 70, 372–380.
Pullmann, H., Allik, J., & Realo, A. (2009). Global self-esteem across the life span: A cross-sectional comparison between representative and self-selected internet samples. Experimental Aging Research, 35, 20–44.
Realo, A., Allik, J., Verkasalo, M., Lönnqvist, J. E., Kwiatkowska, A., Kööts, L., … Renge, V. (2009). Mechanisms of the national character stereotype: How people in six neighboring countries of Russia describe themselves and the typical Russian. European Journal of Personality, 23, 229–249.
Rentfrow, P. J., Gosling, S. D., & Potter, J. (2008). A theory of the emergence, persistence, and expression of geographic variation in psychological characteristics. Perspectives on Psychological Science, 3, 339–369.
Rentfrow, P. J., Jokela, M., & Lamb, M. E. (2015). Regional personality differences in Great Britain. Plos One, 10. doi: 10.137/journal.pone.0122245
Rossier, J., Hansenne, M., Baudin, N., & Morizot, J. (2012). Zuckerman’s Revised Alternative Five-Factor Model: Validation of the Zuckerman-Kuhlman-Aluja Personality Questionnaire in four French-speaking countries. Journal of Personality Assessment, 94(4), 358–365.
Schmitt, D. P., & Allik, J. (2005). Simultaneous administration of the Rosenberg Self-Esteem Scale in 53 nations: Exploring the universal and culture-specific features of global self-esteem. Journal of Personality and Social Psychology, 89, 623–642.
Schmitt, D. P., Allik, J., McCrae, R. R., Benet-Martínez, 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.
Sedikides, C., Gaertner, L., & Cai, H. (2015). On the panculturality of self-enhancement and self-protection motivation: The case for the universality of self-esteem. In A. J. Elliott (Ed.), Advances in motivation science (Vol. 2, pp. 185–241). San Diego, CA: Academic Press.
Smith, P. B. (2015). To lend helping hands: In-group favoritism, uncertainty avoidance, and the national frequency of prosocial behaviors. Journal of Cross-Cultural Psychology, 46, 759–771.
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.
Steel, G. D., Rinne, T., & Fairweather, J. (2012). Personality, nations, and innovation: Relationships between personality traits and national innovation scores. Cross-Cultural Research, 46, 3–30.
Steel, P., Schmidt, J., & Shultz, J. (2008). Refining the relationship between personality and subjective well-being. Psychological Bulletin, 134, 138–161.
Tay, L., & Diener, E. (2011). Needs and subjective well-being around the world. Journal of Personality and Social Psychology, 101, 354–365.
Terracciano, A., Abdel-Khalek, A. M., Adam, N., Adamovova, L., Ahn, C., Ahn, H. N., … McCrae, R. R. (2005). National character does not reflect mean personality trait levels in 49 cultures. Science, 310, 96–100.
Thalmayer, A. G., & Saucier, G. (2014). The questionnaire Big Six in 26 nations: Developing cross-culturally applicable Big Six, Big Five and Big Two Inventories. European Journal of Personality, 28, 482–496.
Thorndike, R. L. (1949). Personnel selection: Test and measurement techniques. New York, NY: J. Wiley.
van Emmerik, H., Gardner, W. L., Wendt, H., & Fischer, D. (2010). Associations of culture and personality with McClelland’s motives: A cross-cultural study of managers in 24 countries. Group & Organization Management, 35, 329–367.
van Hemert, D. A., van de Vijver, F. J. R., & Poortinga, Y. H. (2002). The Beck Depression Inventory as a measure of subjective well-being: A cross-national study. Journal of Happiness Studies, 3, 257–286.
van Hemert, D. A., van de Vijver, F. J. R., Poortinga, Y. H., & Georgas, J. (2002). Structural and functional equivalence of the Eysenck Personality Questionnaire within and between countries. Personality and Individual Differences, 33, 1229–1249.
Vandello, J. A., Cohen, D., & Ransom, S. (2008). U.S. southern and northern differences in perceptions of norms about aggression: Mechanisms for the perpetuation of a culture of honor. Journal of Cross-Cultural Psychology, 39, 162–177.
Wagner, A. (1864). Die gesetzmässigkeit in den scheinbar willkührlichen menschlichen handlungen vom standpunkte der statistik. Hamburg, Germany: Boyes & Geisler.
Wimmer, A., & Feinstein, Y. (2010). The rise of the nation-state across the world, 1816 to 2001. American Sociological Review, 75, 764–790.
Zecca, G., Verardi, S., Antonietti, J. P., Dahourou, D., Adjahouisso, M., Ah-Kion, J., … Rossier, J. (2013). African cultures and the Five-Factor Model of personality: Evidence for a specific Pan-African structure and profile? Journal of Cross-Cultural Psychology, 44, 684–700.