Science behind the test

How our tests are built

We use a public-domain, peer-reviewed personality instrument and stay open about its strengths, limits, and how we adapted it.

Our principle

We don't invent personality tests. When validated public-domain instruments exist, we use them, and tell you exactly which one, who developed it, and what its psychometric properties are. A test you can take seriously is a test that names its sources.

The Big Five framework

The Five Factor Model (Big Five) is the most replicated framework in personality science: five broad traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) that emerge consistently across instruments, observers, and cultures. McCrae & Costa (1987) established the cross-instrument validity; Goldberg (1990, 1992) developed the lexical foundation that became the public-domain item pool we use today.

The instrument we use: IPIP-NEO-120

Our Big Five test is the IPIP-NEO-120 (Johnson, 2014), a 120-item public-domain inventory measuring the same 30 facets as the proprietary NEO PI-R. Reliability data from the original paper:

  • Items: 120
  • Facets (sub-traits): 30
  • Cronbach's alpha (per domain): .81 – .90 (Johnson, 2014)
  • Validation sample: 619,150 (international online sample)
  • License: Public domain, free to use commercially

About the Quick (60-item) version

Our Quick form is a deterministic subset of the IPIP-NEO-120: two items per facet, balanced by direction when possible, drawn from the same Johnson (2014) item pool. It is not Johnson's published IPIP-NEO-60 (which substitutes 8 items from the IPIP-NEO-300). With 2 items per facet, facet-level reliability is lower than the full form, for any decision you care about, take the 120-item version.

Translations

The IPIP-NEO-120 has been translated into many languages by independent research groups (see ipip.ori.org). For the 7 locales we ship at launch (Portuguese-Brazilian, English, Spanish, French, German, Italian, Japanese), we use a forward-backward translation process and flag any locale that has not yet completed independent peer-reviewed validation. Translation status appears on each test's landing page.

What this test is not

Personality results describe statistical patterns in your self-report, they are not a clinical diagnosis. Big Five scores can be useful for self-reflection, career thinking, and conversations about how you operate; they do not replace evaluation by a licensed mental health professional. If you are in distress, contact a qualified clinician or crisis service.

Citations

Plain-language summary of why each source is here. Full APA references and DOI links below.

Foundational

  • Established that the five factors aren't an artifact of one method, they replicate across instruments and observers.

    McCrae, R. R., & Costa, P. T., Jr. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52(1), 81–90.

    doi:10.1037/0022-3514.52.1.81

  • The lexical foundation: why five dimensions, not three or seven, emerge from natural-language descriptions of personality.

    Goldberg, L. R. (1990). An alternative "description of personality": The Big-Five factor structure. Journal of Personality and Social Psychology, 59(6), 1216–1229.

    doi:10.1037/0022-3514.59.6.1216

  • Developed the marker items that became the public-domain pool we use today.

    Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4(1), 26–42.

    doi:10.1037/1040-3590.4.1.26

The instrument

  • The exact instrument we administer. Reports the alpha values, sample, and structural validity of the IPIP-NEO-120.

    Johnson, J. A. (2014). Measuring thirty facets of the Five Factor Model with a 120-item public domain inventory: Development of the IPIP-NEO-120. Journal of Research in Personality, 51, 78–89.

    doi:10.1016/j.jrp.2014.05.003

  • Why the IPIP exists and why public-domain personality measures matter for research and accessibility.

    Goldberg, L. R., Johnson, J. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., & Gough, H. G. (2006). The International Personality Item Pool and the future of public-domain personality measures. Journal of Research in Personality, 40(1), 84–96.

    doi:10.1016/j.jrp.2005.08.007

Validation and life-outcome predictions

  • Independent replication of the IPIP-NEO-120 factor structure on a different large sample.

    Kajonius, P. J., & Johnson, J. A. (2019). Assessing the structure of the Five Factor Model of personality (IPIP-NEO-120) in the public domain. Europe's Journal of Psychology, 15(2), 260–275.

    doi:10.5964/ejop.v15i2.1671

  • Big Five traits predict life outcomes (mortality, career success, relationships) as well as IQ and socioeconomic status do.

    Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg, L. R. (2007). The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Perspectives on Psychological Science, 2(4), 313–345.

    doi:10.1111/j.1745-6916.2007.00047.x

  • Big Five structure replicates across 50 cultures from the observer's perspective.

    McCrae, R. R., & Terracciano, A. (2005). Universal features of personality traits from the observer's perspective: Data from 50 cultures. Journal of Personality and Social Psychology, 88(3), 547–561.

    doi:10.1037/0022-3514.88.3.547

Limits and critical perspectives

  • Important critical perspective: Big Five measurement can be less reliable in lower-literacy and non-WEIRD populations. We disclose this limitation transparently.

    Laajaj, R., Macours, K., Hernandez, D. A. P., Arias, O., Gosling, S. D., Potter, J., Rubio-Codina, M., & Vakis, R. (2019). Challenges to capture the Big Five personality traits in non-WEIRD populations. Science Advances, 5(7), eaaw5226.

    doi:10.1126/sciadv.aaw5226
Full reference list (APA)
  1. McCrae, R. R., & Costa, P. T., Jr. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52(1), 81–90. doi:10.1037/0022-3514.52.1.81
  2. Goldberg, L. R. (1990). An alternative "description of personality": The Big-Five factor structure. Journal of Personality and Social Psychology, 59(6), 1216–1229. doi:10.1037/0022-3514.59.6.1216
  3. Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4(1), 26–42. doi:10.1037/1040-3590.4.1.26
  4. Johnson, J. A. (2014). Measuring thirty facets of the Five Factor Model with a 120-item public domain inventory: Development of the IPIP-NEO-120. Journal of Research in Personality, 51, 78–89. doi:10.1016/j.jrp.2014.05.003
  5. Goldberg, L. R., Johnson, J. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., & Gough, H. G. (2006). The International Personality Item Pool and the future of public-domain personality measures. Journal of Research in Personality, 40(1), 84–96. doi:10.1016/j.jrp.2005.08.007
  6. Kajonius, P. J., & Johnson, J. A. (2019). Assessing the structure of the Five Factor Model of personality (IPIP-NEO-120) in the public domain. Europe's Journal of Psychology, 15(2), 260–275. doi:10.5964/ejop.v15i2.1671
  7. Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg, L. R. (2007). The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Perspectives on Psychological Science, 2(4), 313–345. doi:10.1111/j.1745-6916.2007.00047.x
  8. McCrae, R. R., & Terracciano, A. (2005). Universal features of personality traits from the observer's perspective: Data from 50 cultures. Journal of Personality and Social Psychology, 88(3), 547–561. doi:10.1037/0022-3514.88.3.547
  9. Laajaj, R., Macours, K., Hernandez, D. A. P., Arias, O., Gosling, S. D., Potter, J., Rubio-Codina, M., & Vakis, R. (2019). Challenges to capture the Big Five personality traits in non-WEIRD populations. Science Advances, 5(7), eaaw5226. doi:10.1126/sciadv.aaw5226