Disposition and demographic variables

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Disposition and demographic variables

Nikos Bozionelos*

Department of Human Resource Management, Strathclyde Business School,University of Strathclyde, The Graham Hills Building, 50 Richmond Street,

Glasgow G1 1XU, UK

Received 20 May 2002; received in revised form 2 April 2003; accepted 18 April 2003

Abstract

The study investigated the relationship of the Five Factor Model of personality and general mentalability with an array of demographic variables that included age, socio-economic origin, educationalattainment and marital status. Questionnaire data from 342 white-collar workers were analysed. Opennessand mental ability were related to educational attainment, while mental ability was the only dispositionaltrait that was associated with socio-economic origin. Married individuals scored lower on openness thantheir non-married counterparts, and scores on extraversion were associated with length of marriage. Thefindings suggested that the profile of the white-collar worker in the public sector is that of an emotionallystable, introverted, agreeable and conscientious individual. It is suggested that additional research isneeded, including studies to investigate the consistency of the identified relationship patterns acrossgenders, and studies to map the processes that are involved in the association between dispositional traitsand demographic group membership.# 2003 Elsevier Ltd. All rights reserved.

Keywords: Disposition; Personality; Mental ability; Demographic group; Association

1. Introduction

The society consists of demographically defined groups, where membership is determined byphysical or social attributes of individuals. Demographic group membership (e.g. Smith & Tyler,1997) and dispositional traits, which include personality traits and general mental ability (Brand,Egan, & Deary, 1993), are associated with individual differences in psychological processes andbehaviour.

0191-8869/03/$ - see front matter # 2003 Elsevier Ltd. All rights reserved.

doi:10.1016/S0191-8869(03)00199-5

Personality and Individual Differences 36 (2004) 1049–1058

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E-mail address: [email protected] (N. Bozionelos).

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Therefore, investigations on the relationship of dispositional characteristics withdemographic group membership provide information on the extent to which demographicvariables and disposition have shared effects on behaviour and life outcomes. Furthermore,personality traits and mental ability have strong heritability components (e.g. Bouchard,Lykken, McGue, Segal, & Tellegen, 1990; Jang, Livesley, & Vernon, 1996; McGue &Bouchard, 1998), hence, investigation of the relationship between dispositional traits anddemographic variables can reveal the extent to which inclusion in certain demographic groupsis influenced by heritability.1

The Five-Factor Model (FFM) or ‘‘Big-Five’’ of personality represents an emerging consensusthat human personality can be parsimoniously and comprehensively described by five basicpersonality traits. Despite legitimate criticism (Block, 1995; Eysenck, 1992) there is substantialempirical support for the model (e.g. McCrae & Costa, 1996; O’Connor, 2002; Wiggins &Trapnell, 1997), whose structure is consistent across cultures (McCrae & Costa, 1997) and itstraits have strong heritability components (Jang et al., 1996). The FFM includes the traits ofneuroticism, extraversion, openness, agreeableness and conscientiousness. Neuroticism andextraversion coincide with Eysenck’s initial dimensions, and the remaining traits largely overlapwith Eysenck’s third dimension, psychoticism (Eysenck, 1992; Ormerod, McKenzie, & Woods,1995). Therefore, the utilization of the FFM in research is appropriate.The scientific literature has provided empirical reports on the relationship between dispositional

traits and certain demographic variables, that is variables that indicate demographic groupmembership, including age and educational attainment. However, other important demographicvariables, including socio-economic origin and marital status, have been neglected in relevantresearch. Furthermore, those studies that reported on the relationship of age and educationalattainment with dispositional traits have mostly utilized samples from the general population.Working individuals may differ from the general population because work experiences affect theinterpretation of events and responses to social stimuli. For example, although empiricalresearch suggests that all FFM traits are associated with age in the general population (McCraeet al., 2000) in a recent systematic study with a sample drawn from the general US workforceGoldberg, Sweeney, Merenda, and Hughes (1998) found age to be associated only withconscientiousness. In addition, different jobs are associated with different mental and socialdemands. Therefore, certain occupational groups may be associated with distinct personalityprofiles because individuals with certain personality profiles may direct themselves towardscertain jobs or occupations.2 Hence, there is also a need for research on the relationship ofdispositional traits with demographic variables within occupational groups and within sectors ofthe economy.In an attempt to fill the research gaps presented earlier, the present study investigated the

relationship of dispositional traits with age, educational attainment, socio-economic origin andmarital status in a British sample of white-collar workers.

1 It must be evident that the argument is not that demographic group membership is genetically determined. Geneticdetermination is different from heritability effects, as the latter include the effects of proactive and evocative interaction

(see, for instance, Bouchard et al., 1990).2 The possibility that the type of job may affect personality in the medium-term and the long-term is not dismissed.

However, as noted, personality traits have been found to be remarkably stable over the life course and to have strong

heritability components.

1050 N. Bozionelos / Personality and Individual Differences 36 (2004) 1049–1058

1.1. Hypotheses

The pattern of the relationship between age and personality in the general population appearsto be that age is negatively related to neuroticism, extraversion and openness and positivelyrelated to agreeableness and conscientiousness (e.g. McCrae et al., 2000). These patterns wereretained as hypotheses in the present study. However, taking into account Goldberg et al.’s (1998)finding in the US working population, the strongest expectation was held for the relationshipbetween age and conscientiousness.Empirical evidence is generally suggestive of deterioration in performance in mental ability tests

from early towards later adulthood (e.g. Schwartzman, Gold, Andres, Arbuckle, & Chaikelson,1987). Hence, a negative relationship between age and mental ability was expected.

Hypothesis 1. Age will be negatively associated with neuroticism (1a), extraversion (1b), openness(1c) and general mental ability (1d), and positively associated with agreeableness (1e) andconscientiousness (1f).Educational experiences intuitively relate to the broadness of one’s mental horizon. Empirical

reports with samples from the general population (e.g. Vassend & Skrondal, 1995) and the workingpopulation (Goldberg et al., 1998) suggest a positive relationship between educational attainmentand the trait of openness, which encompasses multiplicity of interests, open-mindedness andimagination. Furthermore, although educational attainment is presumably influenced by a host offactors, including socio-economic origin and personality traits, it cannot be denied that mentalability plays a role, as acquisition of knowledge is facilitated by the ability to understand concepts.

Hypothesis 2. Educational attainment will be positively associated with openness (2a) and generalmental ability (2b).As noted, the literature up-to-date has not systematically researched the relationship between

dispositional traits and socio-economic origin. Socio-economic origin relates to upbringingpractices and to early social and intellectual experiences; hence, it may relate to the development ofpersonality and mental ability. Furthermore, dispositional traits, including conscientiousness(Barrick & Mount, 1991; Salgado, 1997) and mental ability (Ree, Earles, & Teachout, 1994), areassociated with job performance, which, in turn should relate to career attainment and upwardssocio-economic mobility. Therefore, taking into account the strong heritability component ingeneral mental ability and personality traits (e.g. Bouchard et al., 1990), conscientious and morementally capable individuals should be more likely to be raised in homes that belong to highersocio-economic strata; as their parents should have been more upwards mobile socio-economically.

Hypothesis 3. Socio-economic origin will be positively associated with conscientiousness (3a) andgeneral mental ability (3b).As also noted, the literature has not reported on the relationship between dispositional traits

and variables that reflect involvement in marital relationships, including marital status and lengthof marriage. These are major demographic variables because most individuals are involved in amarital relationship at some point in their lives. It is logical to assume that individuals who aresociable, confident and have a positive outlook of life, which are characteristics of extraversion,are more likely to attract and retain a spouse.

N. Bozionelos / Personality and Individual Differences 36 (2004) 1049–1058 1051

Hypothesis 4. Extraversion will be positively associated with being married (4a) and with lengthof marriage (4b).

2. Method

2.1. Sample

The sample consisted of 342 (262 or 76.6% women) clerical and administrative workers in threeBritish universities who voluntarily completed questionnaires distributed through internal mail.The ratio of men to women in the sample was representative of the ratio of men to women amongwhite-collar workers in this particular setting. Mean age was 35.63 years (SD=9.54) and abouthalf (n=165 or 47.7%) of the participants were married. Of the participants, 75.3% had obtainedpost-secondary school qualifications (i.e. A-levels, HNC, HND, B.Tech., undergraduate, orgraduate degree).

2.2. Measures

2.2.1. Five-factor model traitsThese were assessed with the five global factors of the British edition of the Cattell 16PF5

(Russell & Karol, 1995). Sten (standardized 10) scores on the British general population fornon-manual occupations (Smith, 1994, p. 29) were utilized. The global factors of the Cattell16PF5 have been empirically shown to tap the traits of the FFM (e.g. Byravan & Ramanaiah,1995; Conn & Rieke, 1994). The correspondence for openness (16PF5’s tough-mindedness) andagreeableness (16PF5’s independence) is negative, hence, the signs of the respective coefficientswere reversed in the results.

2.2.2. General mental abilityThis was assessed with raw scores on Factor B of the Cattell 16PF5 (Russell &Karol, 1995). Factor

B is measured with 15 items and demonstrates high concurrent validity with other establishedmeasures of mental ability, including the Wechsler Adult Intelligence Scale (Abel & Brown, 1998).

2.2.3. Socio-economic originThis was assessed with a single item in which respondents indicated the socio-economic level of

their family when they were ‘‘at the age of 15’’: upper class (coded 5); upper-middle class (coded4); middle class (coded 3); working-middle class (coded 2); working class (coded 1). Singleself-descriptive measures are highly associated with complex indices of socio-economic origin(Dreher, Dougherty, & Whitely, 1985).

2.2.4. Educational attainmentRespondents indicated all educational qualifications they had earned, and the highest

qualification was used as index of educational attainment. Responses were coded as follows: 1:CSE and/or O’levels/GCSE; 2: A-levels; 3: Postsecondary Diploma (e.g. B.Tech.); 4: Bachelordegree; 5: Graduate degree.


2.2.5. Marital status and length of marriageThese were assessed with single items in which respondents indicated whether they were single

(coded 1) or married (coded 2) and the length of their marriage in years and months, which wereconverted into months.Gender (coded 1: male and 2: female) and age were assessed with single items.

2.3. Results

Descriptive statistics are presented in Table 1. Two-tailed significance testing was utilized.Mental ability was not related to any of the personality traits. Age was strongly related toorganizational tenure (r=0.52, P<0.001).Hypothesis 1, which pertained to the relationships of dispositional traits with age, was tested by

means of Pearson product–moment correlation coefficients, presented in Table 2. Age wasnegatively related to neuroticism (r=�0.16, P<0.01) and extraversion (r=�0.24, P<0.001), andpositively related to agreeableness (r=0.16, P<0.01) and conscientiousness (r=0.25, P<0.001);but it was not related to openness (r=0.07, ns) or mental ability (r=0.04, ns). Hence, Hypotheses1a, 1b, 1e and 1f were supported, while hypotheses 1c and 1d were not supported. A stepwiseregression suggested that the dispositional traits accounted for 13.7% of the variance in age, F(4,337)=12.90, P<0.001.Hypothesis 2, which pertained to the relationship between dispositional traits and educational

attainment, was tested by means of partial correlation coefficients, with age as primary co-variatebecause the probability of having earned educational qualifications increases with age. Thecoefficients are presented in Table 2.The partial correlation coefficient between mental ability and educational attainment was

positive and significant (r=0.32, P<0.001, age as co-variate). Another partial correlationcoefficient was calculated with socio-economic origin added to the co-variates, because it isreasonable to assume that due to better conditions and more encouragement individuals fromhigher socio-economic backgrounds are more likely to pursue education. The addition of

Table 1Descriptive statistics (N=342)

Variable
M SD
Age
35.63 9.54 Educational attainment 3.23 1.03 Length of marriage (months)a 176.40 119.04
Socio-economic origin
1.95 0.86 General mental ability 10.09 2.22 Neuroticism 5.53 1.90
Extraversion
5.86 1.97 Opennessb 5.35 1.57 Agreeablenessb 5.08 1.70 Conscientiousness 4.65 1.48
a n=165.b Higher scores indicate lower levels of the trait and vice versa.


socio-economic origin to the co-variates left the relationship virtually unaffected (r=0.31,P<0.001). Therefore, Hypothesis 2b was fully supported.To test Hypothesis 2a, which postulated a positive relationship between openness and

educational attainment, partial correlation coefficients controlling for age and mental ability,which was found to relate to educational attainment, were calculated. Openness, and no otherpersonality trait, was significantly related to educational attainment (r=0.21, P<0.001, age andmental ability as co-variates); hence, Hypothesis 2a was also supported. A hierarchical stepwiseregression, with age forcibly entered as co-variate in the first step, suggested that the dispositionaltraits accounted for 16.4% of the variance in educational attainment, F� (3,337)=21.04, P<0.001.Hypothesis 3, which pertained to the association between the dispositional traits and

socio-economic origin, was tested by means of Pearson correlation coefficients, presented inTable 2. Socio-economic origin was not related to conscientiousness (r=0.06, ns), or to any otherpersonality trait; but it was positively related to mental ability (r=0.11, P<0.05). Hence,Hypothesis 3a was not supported, while Hypothesis 3b was supported.Hypothesis 4a, which predicted that married individuals will report higher scores on extraversion,

was tested by means of multiple analysis of co-variance (MANCOVA) with age as co-variatebecause older individuals are more likely to be married. The results indicated no difference inscores on extraversion between married and non-married participants, F (1,339)=0.55, ns; hence,Hypothesis 4a was not supported. On the other hand, married participants scored lower onopenness than their non-married counterparts, F (1,339)=4, P<0.05, corrected means 5.15 and5.54 for non-married and married participants respectively,3 which was a relationship nothypothesized. The Z2 suggested that dispositional traits accounted for 1.2% of the variance inmarital status, over and above the contribution of age.Hypothesis 4b, which postulated a positive association between extraversion and length of

marriage, was tested by means of partial correlation with age as co-variate, because married

Table 2Correlation coefficients of the dispositional traits with age, socio-economic origin, educational attainment and length

of marriage (N=342)

Variable
Neuroticism Extraversion Openness Agreeableness Conscientiousness General mentalability
Age
�0.16** �0.24*** 0.07 0.16*** 0.25*** 0.04 Socio-economic origin �0.02 �0.03 0.01 �0.01 0.06 0.11* Educational attainment �0.04 �0.05 0.23*** �0.10 �0.12* 0.33***
Educational attainment(age as co-variate)

0
�0.10 0.27*** �0.16* �0.10 0.32***
Length of marriagea
�0.02 �0.11 0.04 0.08 0.11 �0.11
Length of marriagea

(age as co-variate)
0.10 0.17* 0.02 0.01 0.01 �0.09
a n=165.

* P<0.05.** P<0.01.*** P<0.001.

3 Lower scores indicate higher openness.


individuals who are older are more likely to be married for longer. The coefficient was significant(r=0.17, P<0.05, age as co-variate), hence, Hypothesis 4b was supported. No other dispositionaltrait was related to length of marriage (Table 2). A hierarchical stepwise regression, with age asforcibly entered co-variate, suggested that disposition accounted for 0.5% of the variance inlength of marriage, F� (1,162)=4.54, P<0.001.

3. Discussion

The study investigated relationships between an array of important demographic variables anddispositional traits in a sample of public sector white-collar workers. Some of the relationshipsinvestigated in the study, in particular those of dispositional traits with socio-economic origin,marital status and length of marriage, had not been investigated up-to-date, while those who had,had not been investigated in white-collar workers.The findings suggest that older white-collar workers tend to be more emotionally stable, more

introverted, more agreeable and more conscientious than their younger counterparts. This richrelationship between the FFM and age was in line with extant reports with samples from thegeneral population, but in contrast with the limited association identified by Goldberg et al.(1998) in the general US workforce. Nevertheless, the relationship between conscientiousness andage is consistently the strongest one across studies.Due to its strong relationship with organizational tenure, age can be used as a surrogate for

tenure for interpretative purposes. Therefore, the identified relationships between the personalitytraits and age can be explained in terms of individual job selectivity, that is individuals whochoose and remain in white-collar public sector jobs fit into the particular personality profileidentified in the results. It is intuitively sensible that introverted, conscientious and agreeableindividuals prefer office type public sector jobs from jobs in the highly volatile private sector.Further research with samples drawn from different sectors of the economy will expandknowledge on the issue.Both openness and general mental ability were related to educational attainment and made

independent contributions to it. However, although it is rather safe to conclude a causal effectfrom mental ability towards educational attainment, this may not hold for the relationshipof openness with educational attainment. It is likely that education partly cultivates thecharacteristics that are associated with openness, including imagination and multiplicity ofinterests and perspectives. Nevertheless, openness shows substantial, and the highest amongst theFFM traits, temporal stability from pubescence to middle life (Judge, Higgins, Thoresen, &Barrick, 1999) and has the strongest heritability coefficient amongst the traits of the FFM (Janget al., 1996). Therefore, to tentatively conclude a causality effect from openness towardseducational attainment may not be unreasonable.It is noteworthy that the relationship between mental ability and educational attainment was not

moderated by socio-economic origin. This suggests that mentally able individuals who come fromlower socio-economic strata are as likely to attain education as their more socio-economicallyprivileged counterparts. Although social stratification is evident in British society education at alllevels in Britain can be attained largely free of charge; hence, mentally able individuals have theopportunity to obtain educational qualifications regardless of their socio-economic background.


Therefore, relationships of similar pattern must be expected in other countries with charge freeeducation systems, but not in countries where more educational opportunities are available tothose who are socio-economically privileged. Future research should investigate the correctnessof this suggestion, which refers to an issue that is both interesting and important.Socio-economic origin was not related to conscientiousness or to any other personality trait,

but, in line with expectations, it was related to general mental ability. Taking into account thestrong heritability of mental ability and the high stability of individual differences in mentalability from childhood until late adulthood (Deary, Whalley, Lemmon, Crawford, & Starr, 2000),this finding implies that mental ability influences social stratification. However, it must be bornein mind that the identified effect is very weak, in the vicinity of 1% of total variance; hence, otherfactors must play a much stronger role in social stratification.The investigation of the relationship between the dispositional traits and the marital status

variables yielded an expected and an unexpected finding. Concurring with expectations, extraver-sion was related to length of marriage. However, it was low openness, instead of the hypothesizedextraversion, that was related to being married. Individuals who score low on openness tend to beconservative and they are not attracted by new experiences; hence, they may prefer formalromantic relationships within which they feel emotionally safer. This represents, however, only apost-hoc account for the finding, whose generalizability should be tested by future research.Although personality traits made a limited contribution to the marital relationship variables,

they may play a more extensive role in the context of partner similarity or complementarity inpersonality. Future research should also focus on this issue.A limitation of the study is its cross-sectional nature, which makes causality inferences

problematic. For example, a problem in the interpretation of findings regarding the relationshipbetween age and personality is the potential confounding by cohort effects. Although the hightemporal stability of the FFM and of individual differences in mental ability increase confidenceregarding causal relationships only longitudinal investigations, however difficult to conduct, canfully resolve the issue of causality.Furthermore, gender differences in the patterns of the hypothesized relationships were not

investigated because of the highly unbalanced numbers of women and men in the sample.However, this ought to be studied in future research because the socially desirable characteristicsfor men and women are different (e.g. Helgeson, 1994); hence, gender is likely to moderate therelationships of dispositional traits with demographic variables.As a final comment, although a range of significant relationships were identified most of those

relationships were relatively weak, concurring with the conclusion drawn by Goldberg et al. (1998).Nevertheless, the findings do suggest that in many cases knowledge of scores on dispositionaltraits can assist inferences regarding demographic group membership and vice versa. Futureresearch should, therefore, map the processes by which dispositional traits are linked withmembership in particular demographic groups.

References

Abel, M. H., & Brown, L. K. (1998). Validity of the 16PF reasoning ability scale. Psychological Reports, 83, 904–906.Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: a meta-analysis.

Personnel Psychology, 44, 1–26.


Block, J. (1995). A contrarian view of the five-factor approach to personality description. Psychological Bulletin, 117,

187–215.Bouchard, T. J., Lykken, D. T., McGue, M., Segal, N. L., & Tellegen, A. (1990). Sources of human psychologicaldifferences: the Minnesota study of twins reared apart. Science, 250, 223–228.

Brand, C. R., Egan, V., & Deary, I. J. (1993). Personality and general intelligence. In P.Bonaiuto G. L. van Heck, &W.Nowack I. J. Deary (Eds.), Personality psychology in Europe Vol. 4. Tilburg, the Netherlands: Tilburg UniversityPress.

Byravan, A., & Ramanaiah, N. V. (1995). Structure of the 16PF fifth edition from the perspective of the five-factormodel. Psychological Reports, 76, 555–560.

Conn, S. R., & Rieke, M. L. (1994). Construct validation of the 16PF fifth edition. In M. L.Rieke S. R. Conn (Ed.),The 16PF fifth edition technical manual (pp. 101–142). Champaign, IL: Institute for Personality and Ability Testing.

Deary, I. J., Whalley, L. J., Lemmon, H., Crawford, J. R., & Starr, J. M. (2000). The stability of individual differencesin mental ability from childhood to old age: follow-up of the 1932 Scottish Mental Survey. Intelligence, 28, 49–55.

Dreher, G. F., Dougherty, T. W., & Whitely, B. (1985). Generalizability of MBA degree and socio-economic effects on

business schools graduates’ salaries. Journal of Applied Psychology, 70, 769–773.Eysenck, H. J. (1992). Four ways five factors are not basic. Personality and Individual Differences, 13, 667–673.Goldberg, R. L., Sweeney, D., Merenda, P. F., & Hughes, J. E. Jr. (1998). Demographic variables and personality: the

effects of gender, age, education, and ethnic/racial status on self-descriptions of personality attributes. Personalityand Individual Differences, 24, 393–403.

Helgeson, V. S. (1994). Relation of agency and communion to well-being: evidence and potential explanations.

Psychological Bulletin, 116, 412–428.Jang, K. L., Livesley, W. J., & Vernon, P. A. (1996). Heritability of the Big Five personality dimensions and theirfacets: a twin study. Journal of Personality, 64, 577–591.

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.McCrae, R. R., & Costa, P. T. Jr. (1996). Toward a new generation of personality theories: theoretical contexts for thefive-factor model. In J. S. Wiggins (Ed.), The five factor model of personality: theoretical perspectives (pp. 51–87). New

York: Guilford.McCrae, R. R., & Costa, P. T. Jr. (1997). Personality trait structure as a human universal. American Psychologist, 52,509–516.

McCrae, R. R., Costa, P. T. Jr., Ostendorf, F., Angleitner, A., Hrebickova, M., Avia, M. D., Sanz, J., Sanchez-Bernardos, M. L., Kusdil, M. E., Woodfield, R., Saunders, P. R., & Smith, P. B. (2000). Nature over nurture:temperament, personality, and life-span development. Journal of Personality and Social Psychology, 78, 173–186.

McGue, M., & Bouchard, T. J. (1998). Genetic and environmental influences on human behavioral differences. AnnualReview of Neuroscience, 21, 1–24.

O’Connor, B. P. (2002). A quantitative review of the comprehensiveness of the five-factor model in relation to popularpersonality inventories. Assessment, 9, 188–203.

Ormerod, M. B., McKenzie, J., & Woods, A. (1995). Final report on research relating to the concept of five separatedimensions of personality—or six including intelligence. Personality and Individual Differences, 18, 451–461.

Ree, M. J., Earles, J. A., & Teachout, M. S. (1994). Predicting job performance: not much more than ‘‘g’’. Journal of

Applied Psychology, 79, 518–524.Russell, M. T., & Karol, D. L. (1995). The UK edition of the 16PF5: administrator’s manual. Windsor: NFER-NELSON.

Salgado, J. F. (1997). The five factor model of personality and job performance in the European Community. Journalof Applied Psychology, 82, 30–43.

Schwartzman, A. E., Gold, D., Andres, D., Arbuckle, T. Y., & Chaikelson, J. (1987). Stability of intelligence: a 40-yearfollow-up. Canadian Journal of Psychology, 41, 244–256.

Smith, P. (1994). The UK standardization of the 16PF5: a supplement of norms and technical data. Windsor, UK:NFER-NELSON.

Smith, H. J., & Tyler, T. R. (1997). Choosing the right pond: the impact of group membership on self-esteem and

group-oriented behaviors. Journal of Experimental Social Psychology, 33, 146–170.


Vassend, O., & Skrondal, A. (1995). Factor analytic studies of the NEO Personality Inventory and the five-factor

model: the problem of high structural complexity and conceptual indeterminacy. Personality and IndividualDifferences, 19, 135–147.

Wiggins, J. S., & Trapnell, P. D. (1997). Personality structure: the return of the Big Five. In R. Hogan, J. A. Johnson,

& S. R. Briggs (Eds.), Handbook of personality and social psychology (pp. 737–765). San Diego, CA: Academic Press.


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Disposition and demographic variables