Cross-cultural examination of the Big Five Personality Trait Short Questionnaire: Measurement invariance testing and associations with mental health

Autoři: Laura Mezquita aff001;  Adrian J. Bravo aff003;  Julien Morizot aff004;  Angelina Pilatti aff005;  Matthew R. Pearson aff006;  Manuel I. Ibáñez aff001;  Generós Ortet aff001;  Cross-Cultural Addictions Study Team
Působiště autorů: Department of Basic and Clinical Psychology and Psychobiology, Universitat Jaume I, Castelló de la Plana, Castelló, Spain aff001;  Centre for Biomedical Research Network on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Castelló de la Plana, Castellón, Spain aff002;  Department of Psychological Sciences, William & Mary, Williamsburg, Virginia, United States of America aff003;  School of Psychoeducation, University of Montreal, Montreal, Quebec, Canada aff004;  Facultad de Psicología, Universidad Nacional de Córdoba, Instituto de Investigaciones Psicológicas (IIPsi-UNC-CONICET), Córdoba, Córdoba, Argentina aff005;  Center on Alcoholism, Substance Abuse, and Addictions, University of New Mexico, Albuquerque, New Mexico, United States of America aff006
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226223


The present study examined the measurement invariance of the Big Five Personality Trait Short Questionnaire (BFPTSQ) across language (Spanish and English), Spanish-speaking country of origin (Argentina and Spain) and gender groups (female and male). Evidence of criterion-related validity was examined via associations (i.e., correlations) between the BFPTSQ domains and a wide variety of mental health outcomes. College students (n = 2158) from the USA (n = 1117 [63.21% female]), Argentina (n = 353 [65.72% female]) and Spain (n = 688 [66.86% female]) completed an online survey. Of the tested models, an Exploratory Structural Equation Model (ESEM) fit the data best. Multigroup ESEM and ESEM-within-CFA generally supported the measurement invariance of the questionnaire across groups. Internalizing symptomatology, rumination and low happiness were related mainly to low emotional stability across countries, while low agreeableness and low conscientiousness were related chiefly to externalizing symptomology (i.e., antisocial behavior and drug outcomes). Some correlational differences arose across countries and are discussed. Our findings generally support the BFPTSQ as an adequate measure to assess the Big Five personality domains in Spanish- and English-speaking young adults.

Klíčová slova:

Behavior – Emotions – Happiness – Marijuana – Mental health and psychiatry – Personality – Personality traits – Scanning electron microscopy


1. Engel GL. The need for a new medical model: A challenge for biomedicine. Science. 1977;196:129–36. doi: 10.1126/science.847460 847460

2. Kotov R, Gamez W, Schmidt F, Watson D. Linking “Big” personality traits to anxiety, depressive, and substance use disorders: A meta-analysis. Psychol Bull. 2010;136:768–821. doi: 10.1037/a0020327 20804236

3. Deneve KM, Copper H. The happy personality: A meta-analysis of 137 personality traits and subjective well-being. Psychol Bull. 1998;124:197–229. doi: 10.1037/0033-2909.124.2.197 9747186

4. Morizot J. The contribution of temperament and personality traits to antisocial behavior development and desistance. In: The development of criminal and antisocial behavior: Theory, research and practical applications. New York: Springer; 2015. p. 137–65.

5. Kuncel NR, Ones DS, Sackett PR. Individual differences as predictors of work, educational, and broad life outcomes. Pers Individ Dif. 2010;49:331–6.

6. Soto CJ. How replicable are links between personality traits and consequential life outcomes? The life outcomes of personality replication project. Psychol Sci. 2019.

7. John OP, Naumann LP, Soto CJ. Paradigm shift to the integrative big-five trait taxonomy: History, measurement, and conceptual issues. In: John OP, Robins RW, Pervin LA, editors. Handbook of personality: Theory and research. 3rd ed. New York: Guilford Press; 2008. p. 114–53.

8. Morizot J. Construct validity of adolescents’ self-reported big five personality traits: importance of conceptual breadth and initial validation of a short measure. Assessment. 2014;21:580–606. doi: 10.1177/1073191114524015 24619971

9. Barbaranelli C, Caprara GV, Rabasca A, Pastorelli C. A questionnaire for measuring the Big Five in late childhood. Pers Individ Dif. 2003;34:645–64.

10. John OP, Donahue EM, Kentle RL. The Big Five Inventory-Versions 4a and 54. Berkeley, CA: University of California, Berkeley, Institute of Personality and Social Research; 1991.

11. Gosling SD, Rentfrow PJ, Swann Jr. WB. A very brief measure of the Big-Five personality domains. J Res Pers. 2003;37:504–28.

12. Donnellan MB, Oswald FL, Baird BM, Lucas RE. The Mini-IPIP scales: Tiny-yet-effective measures of the Big Five Factors of personality. Psychol Assess. 2006;18:192–203. doi: 10.1037/1040-3590.18.2.192 16768595

13. Saucier G. Orthogonal markers for orthogonal factors: The case of the Big Five. J Res Pers. 2002;36:1–31.

14. McCrae RR, Costa Jr. PT. NEO Inventories for the NEO Personality Inventory-3 (NEO-PI-3), NEO Five-Factor Inventory-3 (NEO-FFI-3), NEO Personality Inventory-Revised (NEO-PI-R): Professional manual. Lutz, FL: Psychological Assessment Resources; 2010.

15. Ortet G, Ibáñez MI, Moya J, Villa H, Viruela A, Mezquita L. Assessing the five factors of personality in adolescents: the junior version of the Spanish NEO-PI-R. Assessment. 2012;19:114–30. doi: 10.1177/1073191111410166 21622482

16. Saucier G, Goldberg LR. Assessing the Big Five: Applications of 10 psychometric criteria to the development of marker scales. In: De Raad B, Perugini M, editors. Big five assessment. Ashland, OH US: Hogrefe & Huber Publishers; 2002. p. 30–54.

17. Ortet G, Martínez T, Mezquita L, Morizot J, Ibáñez MI. Big Five Personality Trait Short Questionnaire: Preliminary validation with Spanish adults. Span J Psychol. 2017;20:E7. doi: 10.1017/sjp.2017.8 28181474

18. D’Amico EJ, Tucker JS, Shih RA, Miles JNV. Does diversity matter? The need for longitudinal research on adolescent alcohol and drug use trajectories. Subst Use Misuse. 2014;49:1069–73. doi: 10.3109/10826084.2014.862027 24779507

19. Henrich J, Heine SJ, Norenzayan A. Most people are not WEIRD. Nature. 2010;466:29–29. doi: 10.1038/466029a 20595995

20. Spector PE, Liu C, Sanchez JI. Methodological and Substantive Issues in Conducting Multinational and Cross-Cultural Research. Annu Rev Organ Psychol Organ Behav. 2015;2:101–31.

21. Ziegler M, Kemper CJ, Kruyen P. Short scales–Five misunderstandings and ways to overcome them. J Individ Differ. 2014;35:185–9.

22. Miech RA, Patrick ME, O’Malley PM, Johnston LD. The Influence of College Attendance on Risk for Marijuana Initiation in the United States: 1977 to 2015. Am J Public Health. 2017;107:996–1002. doi: 10.2105/AJPH.2017.303745 28426314

23. Schulenberg JE, Johnston LD, O’Malley PM, Bachman JG, Miech RA, Patrick ME. Monitoring the Future national survey results on drug use, 1975–2017: Volume II, college students and adults ages 19–55. Ann Arbor: Institute for Social Research, The University of Michigan; 2018.

24. January J, Madhombiro M, Chipamaunga S, Ray S, Chingono A, Abas M. Prevalence of depression and anxiety among undergraduate university students in low- and middle-income countries: a systematic review protocol. Syst Rev. 2018;7:57. doi: 10.1186/s13643-018-0723-8 29636088

25. Bruffaerts R, Mortier P, Kiekens G, Auerbach RP, Cuijpers P, Demyttenaere K, et al. Mental health problems in college freshmen: Prevalence and academic functioning. J Affect Disord. 2018;225:97–103. doi: 10.1016/j.jad.2017.07.044 28802728

26. Bravo AJ, Villarosa-Hurlocker MC, Pearson MR, Protective Strategies Study Team. College student mental health: An evaluation of the DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure. Psychol Assess. 2018;30:1382–9. doi: 10.1037/pas0000628 30070557

27. Bravo AJ, Pearson MR, Pilatti A, Mezquita L, Cross-Cultural Addictions Study Team. Negative marijuana‐related consequences among college students in five countries: Measurement invariance of the Brief Marijuana Consequences Questionnaire. Addiction. 2019.

28. Cohen J. A power primer. Psychol Bull. 1992;110:155–9

29. American Psychiatric Association. The DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure–Adult. 2013.

30. American Psychiatric Association. Manual diagnóstico y estadístico de los trastornos mentales. 5th ed. Madrid: Editorial Médica Panamericana; 2014.

31. Narrow WE, Clarke DE, Kuramoto SJ, Kraemer HC, Kupfer DJ, Greiner L, et al. DSM-5 Field Trials in the United States and Canada, Part III: Development and Reliability Testing of a Cross-Cutting Symptom Assessment for DSM-5. Am J Psychiatry. 2013;170:71–82. doi: 10.1176/appi.ajp.2012.12071000 23111499

32. Mezquita L, Ibáñez MI, Moya J, Villa H, Ortet G. A longitudinal examination of different etiological pathways to alcohol use and misuse. Alcohol Clin Exp Res. 2014;38:1770–9. doi: 10.1111/acer.12419 24797208

33. Mezquita L, Bravo AJ, Ortet G, Pilatti A, Pearson MR, Ibáñez MI. Cross-cultural examination of different personality pathways to alcohol use and misuse in emerging adulthood. Drug Alcohol Depend. 2018;192:193–200. doi: 10.1016/j.drugalcdep.2018.08.004 30268069

34. Simons JS, Dvorak RD, Merrill JE, Read JP. Dimensions and severity of marijuana consequences: Development and validation of the Marijuana Consequences Questionnaire (MACQ). Addict Behav. 2012;37:613–21. doi: 10.1016/j.addbeh.2012.01.008 22305645

35. Pearson MR, Marijuana Outcomes Study Team. Marijuana Use Grid: A brief, comprehensive measure of marijuana use. Manuscript Submitted to Publication. 2019.

36. Brinker JK, Dozois DJA. Ruminative thought style and depressed mood. J Clin Psychol. 2009;65:1–19. doi: 10.1002/jclp.20542 19048597

37. Bravo AJ, Pearson MR, Pilatti A, Mezquita L, Ibáñez MI, Ortet G. Ruminating in English, Ruminating in Spanish: Psychometric Evaluation and Validation of the Ruminative Thought Style Questionnaire in Spain, Argentina, and USA. Eur J Psychol Assess. 2018.

38. Muthén LK, Muthén BO. Mplus user’s guide. Eigth Edition. Muthén LK, Muthén BO, editors. Los Angeles, CA; 2018.

39. Marsh HW, Ludtke O, Muthén B, Asparouhov T, Morin AJS, Trautwein U. A new look at the big-five factor structure through exploratory factor structural equation modeling. Psychol Assess. 2010;22:471–91. doi: 10.1037/a0019227 20822261

40. West SG, Taylor AB, Wu W. Model fit and model selection in structural equation modeling. In: Hoyle RH, editor. Handbook of structural equation modeling. New York: Guildord Press; 2012. p. 209–31.

41. Bentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238–46. doi: 10.1037/0033-2909.107.2.238 2320703

42. Marsh HW, Hau K, Wen Z. In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Struct Equ Model. 2004;11:320–41.

43. MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychol Methods. 1996;1:130–49.

44. Marsh HW, Nagengast B, Morin AJS. Measurement invariance of big-five factors over the life span: ESEM tests of gender, age, plasticity, maturity, and la dolce vita effects. Dev Psychol. 2013;49:1194–218. doi: 10.1037/a0026913 22250996

45. Morin AJS, Marsh HW, Nagengast B. Exploratory Structure Equation Modeling. In: Hancock GR, Mueller RO, editors. Structural equation modeling: A second course (2nd ed) [Internet]. Charlotte, NC: Information Age Publishing, Inc; 2013. p. 269–314.

46. Satorra A, Bentler PM. A scaled difference chi-square test statistic for moment structure analysis. Psychometrika. 2001;66:507–14.

47. Brown TA. Confirmatory factor analysis for applied research. 2nd ed. New York: Guilford Press; 2015.

48. Chen FF. Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Model. 2007;14:464–504.

49. Cheung G, Rensvold R. Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Model. 2002;9:233–55.

50. Dunn TJ, Baguley T, Brunsden V. From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. Br J Psychol. 2014;105:399–412. doi: 10.1111/bjop.12046 24844115

51. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Model. 1999;6:1–55.

52. Ortet G, Mezquita L, Morizot J, Ibáñez MI. Assessment of the “Little” Big Five: The Spanish version of the Big Five Personality Traits Short Questionnaire in adolescents. Manuscript Submitted to Publication. 2019.

53. Aluja A, García O, García LF. Relationships among extraversion, openness to experience, and sensation seeking. Pers Individ Dif. 2003;35:671–680.

54. Roberti JW. A review of behavioral and biological correlates of sensation seeking. J Res Pers. 2004;38:256–279.

55. Suárez-Alvarez J, Pedrosa I, Lozano LM, García-Cueto E, Cuesta M, Muñiz J. Using reversed items in likert scales: A questionable practice. Psicothema. 2018;30:149–58. doi: 10.7334/psicothema2018.33 29694314

56. Millsap RE, Olivera-Aguilar M. Investigating measurement invariance using confirmatory factor analysis. In: Hoyle RH, editor. Handbook of Structural Equation Modeling. New York: Guilford; 2012. p. 209–31.

57. Spector PE, Liu C, Sanchez JI. Methodological and substantive issues in conducting multinational and cross-cultural research. Annu Rev Organ Psychol Organ Behav. 2015;2:101–31.

58. Fan X, Sivo SA. Sensitivity of fit indices to model misspecification and model types. Multivariate Behav Res. 2007;42:509–29.

59. Fan X, Sivo SA. Using goodness-of-fit indexes in assessing mean structure invariance. Struct Equ Model. 2009;16:54–69.

60. Malouff JM, Thorsteinsson EB, Schutte NS. The relationship between the Five-Factor Model of Personality and symptoms of clinical disorders: A meta-analysis. J Psychopathol Behav Assess. 2005;27:101–14.

61. Ruiz MA, Pincus AL, Schinka JA. Externalizing pathology and the Five-Factor Model: A meta-analysis of personality traits associated with antisocial personality disorder, substance use disorder, and their co-occurrence. J Pers Disord. 2008;22:365–88. doi: 10.1521/pedi.2008.22.4.365 18684050

62. Bogg T, Roberts BW. Conscientiousness and health-related behaviors: a meta-analysis of the leading behavioral contributors to mortality. Psychol Bull. 2004;130:887–919. doi: 10.1037/0033-2909.130.6.887 15535742

63. Allen J, Holder MD. Marijuana use and well-being in university students. J Happiness Stud. 2014;15:301–21.

64. Flory K, Lynam D, Milich R, Leukefeld C, Clayton R. The relations among personality, symptoms of alcohol and marijuana abuse, and symptoms of comorbid psychopathology: Results from a community sample. Exp Clin Psychopharmacol. 2002;10:425–34. doi: 10.1037//1064-1297.10.4.425 12498340

65. Terracciano A, Löckenhoff CE, Crum RM, Bienvenu OJ, Costa PT Jr. Five-factor model personality profiles of drug users. BMC Psychiatry. 2008;8:22. doi: 10.1186/1471-244X-8-22 18405382

66. Gale CR, Booth T, Mõttus R, Kuh D, Deary IJ. Neuroticism and Extraversion in youth predict mental wellbeing and life satisfaction 40 years later. J Res Pers. 2013;47:687–97. doi: 10.1016/j.jrp.2013.06.005 24563560

67. Steel P, Schmidt J, Shultz J. Refining the relationship between personality and subjective well-being. Psychol Bull. 2008;134:138–61. doi: 10.1037/0033-2909.134.1.138 18193998

68. Ozer DJ, Benet-Martínez V. Personality and the prediction of consequential outcomes. Annu Rev Psychol. 2006;57:401–21. doi: 10.1146/annurev.psych.57.102904.190127 16318601

Článek vyšel v časopise


2019 Číslo 12