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PSYCHOLOGICAL MEASURES

Big Five Inventory:
Scoring and Interpretation

The Big Five Inventory (BFI) is a 44-item self-report measure of five broad personality domains, Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness, each scored as a mean from 1 to 5 (John et al., 1991). BFI scoring rests on a 16-item reverse key and a missing-data rule that the analyst has to state, and the newer 60-item BFI-2 needs its own key rather than this one. The syntax computes a domain mean only when all of that domain's items are answered, and the model paragraph reports reliability domain by domain.

ITEMS44

SUBSCALES5 domains

RESPONSE SCALE1 to 5, agreement

SCORE RANGE1 to 5 per domain mean

DEVELOPEDJohn et al., 1991

OnlineSPSS

Reviewed by a PhD-level statistician · Updated October 2026 · 9 min read

What the Big Five Inventory Measures

The Big Five Inventory (BFI) describes broad individual differences in personality through five domains: Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness to Experience. The domains cover tendencies such as sociability and assertiveness, cooperation, organization and self-discipline, proneness to negative emotion, and intellectual or aesthetic interests. Domain scores are dimensional descriptors of how a person typically thinks and behaves, not diagnoses. The 44-item form was built to measure the five-factor structure efficiently, without a long personality battery (John et al., 1991; John et al., 2008).

Researchers use the BFI in social, personality, educational, occupational and health psychology, for example in studies of well-being, health behavior and academic outcomes. The original BFI-44 remains heavily cited, but the newer BFI-2 is a different instrument, with 60 items and 15 facets, three within each domain, and its key cannot stand in for the BFI-44 key (Soto & John, 2017a). This page gives complete scoring steps for the BFI-44 and marks where the BFI-2 needs the developers’ own instructions.

Structure of the Big Five Inventory

Domains and items: Extraversion (8 items), Agreeableness (9), Conscientiousness (9), Neuroticism (8) and Openness (10), 44 in all. There is no combined personality total.
Response scale: five ordered categories coded 1 to 5, from strong disagreement to strong agreement.
Item keys (standard English BFI-44 order as published by the developers, John & Srivastava, 1999, and John et al., 2008; R marks a reverse-scored item): Extraversion 1, 6R, 11, 16, 21R, 26, 31R, 36; Agreeableness 2R, 7, 12R, 17, 22, 27R, 32, 37R, 42; Conscientiousness 3, 8R, 13, 18R, 23R, 28, 33, 38, 43R; Neuroticism 4, 9R, 14, 19, 24R, 29, 34R, 39; Openness 5, 10, 15, 20, 25, 30, 35R, 40, 41R, 44.
Reverse-scored items: 16 of the 44. No item is left unscored in the standard version.
Recall period: none. Respondents describe characteristic tendencies, not symptoms over a defined window.
Administration: self-report. An informant-report or altered format needs its own validation.
Versions: the BFI-2 (60 items, 15 facets), the BFI-2-S (30 items), the BFI-2-XS (15 items) and the 10-item BFI-10 derived from the BFI-44 (Rammstedt & John, 2007; Soto & John, 2017b). Do not apply the BFI-44 item numbers or reverse keys to any of them.
Translations: a Spanish version was evaluated by Benet-Martínez and John (1998), and the Berkeley laboratory lists other adaptations. Use validation evidence for the exact translation administered.

The instrument itself is available from the Berkeley Personality Lab (University of California, Berkeley).

How to Score the Big Five Inventory

Check that bfi1 to bfi44 hold numeric responses from 1 to 5, and confirm the dataset’s item order against the administered form, because the keys apply only to the standard English order. Treat blanks and invalid codes as missing and never reverse a special missing-value code.
Reverse-score items 2, 6, 8, 9, 12, 18, 21, 23, 24, 27, 31, 34, 35, 37, 41 and 43 as 6 minus the response.
Average the keyed items of each domain, using the key in Structure. Every domain mean runs from 1 to 5, and the five means are never added into one trait score.
Choose a missing-data rule before analysis. No universal BFI-44 cut-off for missing items exists, so the code below uses a complete-domain policy: a domain mean is computed only when every one of its items is present. That is an analysis choice, not a developer rule. If you plan partial-item means or imputation, document the justification and a sensitivity analysis in advance. Developer comments on mean substitution concern the BFI-2 and should not be read as a BFI-44 requirement.
Optionally convert a domain mean to the percentage of maximum possible (POMP) as 25 times (mean minus 1), giving a linear 0 to 100 scale. It creates neither a percentile nor a cut-off (Srivastava et al., 2003).
For the BFI-2, obtain the 60-item domain and facet key from the developers and write a separate script, taking the missing-item rule from that scoring document. The BFI-44 syntax below would run on BFI-2 responses without any error message and return wrong scores.

SPSS SYNTAX

* BFI-44 standard English item order. Verify variables and coding first.
* Input variables: bfi1 to bfi44, numeric 1 through 5.
* Flag values outside the valid 1-to-5 range as missing before scoring.
DO REPEAT item = bfi1 TO bfi44.
  IF (NOT MISSING(item) AND (item < 1 OR item > 5)) item = $SYSMIS.
END REPEAT.
EXECUTE.

RECODE bfi2 bfi6 bfi8 bfi9 bfi12 bfi18 bfi21 bfi23 bfi24 bfi27
       bfi31 bfi34 bfi35 bfi37 bfi41 bfi43
 (1=5) (2=4) (3=3) (4=2) (5=1)
 INTO bfi2_r bfi6_r bfi8_r bfi9_r bfi12_r bfi18_r bfi21_r bfi23_r
      bfi24_r bfi27_r bfi31_r bfi34_r bfi35_r bfi37_r bfi41_r bfi43_r.

* MEAN.n requires n nonmissing items: complete-domain scoring.
COMPUTE bfi_extraversion = MEAN.8(bfi1,bfi6_r,bfi11,bfi16,bfi21_r,bfi26,bfi31_r,bfi36).
COMPUTE bfi_agreeableness = MEAN.9(bfi2_r,bfi7,bfi12_r,bfi17,bfi22,bfi27_r,bfi32,bfi37_r,bfi42).
COMPUTE bfi_conscientiousness = MEAN.9(bfi3,bfi8_r,bfi13,bfi18_r,bfi23_r,bfi28,bfi33,bfi38,bfi43_r).
COMPUTE bfi_neuroticism = MEAN.8(bfi4,bfi9_r,bfi14,bfi19,bfi24_r,bfi29,bfi34_r,bfi39).
COMPUTE bfi_openness = MEAN.10(bfi5,bfi10,bfi15,bfi20,bfi25,bfi30,bfi35_r,bfi40,bfi41_r,bfi44).
EXECUTE.

DESCRIPTIVES VARIABLES=bfi_extraversion bfi_agreeableness
 bfi_conscientiousness bfi_neuroticism bfi_openness
 /STATISTICS=MEAN STDDEV MIN MAX.

# Data frame: df. Standard English BFI-44 item order and original 1..5 coding.
items <- paste0("bfi", 1:44)
stopifnot(all(items %in% names(df)))

for (nm in items) {
  stopifnot(is.numeric(df[[nm]]))
  df[[nm]][!is.na(df[[nm]]) & !(df[[nm]] %in% 1:5)] <- NA_real_
}

reverse_ids <- c(2,6,8,9,12,18,21,23,24,27,31,34,35,37,41,43)
scored <- df[items]
for (i in reverse_ids) scored[[paste0("bfi", i)]] <- 6 - scored[[paste0("bfi", i)]]

domains <- list(
  extraversion = c(1,6,11,16,21,26,31,36),
  agreeableness = c(2,7,12,17,22,27,32,37,42),
  conscientiousness = c(3,8,13,18,23,28,33,38,43),
  neuroticism = c(4,9,14,19,24,29,34,39),
  openness = c(5,10,15,20,25,30,35,40,41,44)
)
for (trait in names(domains)) {
  cols <- paste0("bfi", domains[[trait]])
  df[[paste0("bfi_", trait)]] <- rowMeans(scored[cols], na.rm = FALSE)
}
summary(df[paste0("bfi_", names(domains))])

Interpreting BFI Scores

BFI-44 domain mean	Interpretation
1.00	Lowest possible keyed endorsement of that trait
3.00	Scale midpoint, not necessarily a population-average or 50th-percentile level
5.00	Highest possible keyed endorsement of that trait
1.00 to 5.00	A continuous domain score, compared with suitable reference data when norms are needed

Source: John et al. (1991); John et al. (2008). These are scale endpoints, not validated score bands.

No universal clinical or diagnostic cut-off exists for any BFI domain, so the table describes the numerical scale and nothing more. A higher value means more of the named trait, not better health or a superior personality. The BFI-44 label Neuroticism corresponds to Negative Emotionality in the BFI-2, and Openness corresponds to Open-Mindedness, so scores from the two versions are not numerically exchangeable without supporting evidence or calibration.

Low, medium and high splits or quartile cut-points distort associations and cost statistical power, and a mean of 3 is not a universal norm. Describe scores against your own sample distribution and, where norms matter, against suitable reference data. The BFI does not screen for a psychiatric diagnosis, and a high Neuroticism score is not a diagnosis of depression or anxiety.

Psychometric Properties

Property	Published finding	Source
Internal consistency (developer data)	Domain alphas of .75 to .90 in US and Canadian samples, averaging above .80	John & Srivastava (1999); John et al. (2008)
Test-retest (developer data)	Three-month correlations of .80 to .90 (mean .85)	John & Srivastava (1999); John et al. (2008)
Internal consistency (independent sample)	Cronbach’s α of .78 to .87 at baseline across the five domains in a US longitudinal university sample (N = 264 with complete data on all three occasions); values differed by trait and occasion	Arterberry et al. (2014), Table 1
Temporal consistency	Intraclass correlations of .93 to .96 across the assessment occasions for the five domains; sample-specific, not a general figure for every interval or population	Arterberry et al. (2014)
Cross-language validity	Convergent, discriminant and factorial evidence for Spanish and English versions; translation and group comparability still need testing in each context	Benet-Martínez & John (1998)
BFI-44 and BFI-2 pooled	A reliability-generalization meta-analysis of 57 studies (43,715 participants) pooled BFI and BFI-2 domain coefficients at about .77 to .85, with significant heterogeneity; this is not BFI-44-only reliability	Husain et al. (2025)
BFI-2	Original validation supported five domains and 15 facets, designed to improve facet-level specificity; its 60-item structure differs from the BFI-44	Soto & John (2017a)
Diagnostic accuracy	Not applicable; no validated universal psychiatric screening threshold is provided for the BFI	Instrument construct and developer information (John et al., 2008)

These are source-specific results and cannot be assumed to hold as reliability or accuracy estimates in a new sample.

Using the Big Five Inventory in a Study

Treat the five domain means as separate continuous variables whose role the design assigns: outcome, predictor, moderator or covariate. In a cross-sectional study, Correlation Analysis (Pearson & Spearman) shows how the traits relate to each other and to an outcome, and Multiple Linear Regression adjusts those associations for prespecified covariates, with residual patterns and collinearity checked because the domains are correlated. Five traits tested together may warrant an explicit multiplicity plan or a joint multivariate model. When people are assessed repeatedly, Linear Mixed Models (Multilevel Modeling) respect the within-person structure, and the stability of the measurement structure over time deserves its own check.

Reliability describes scores in a particular sample, so calculate alpha or omega separately for each domain with Reliability Analysis (Cronbach’s Alpha). One coefficient across all 44 items would treat the inventory as unidimensional, which it is not. Before reading sex, age, language or cultural differences as trait differences, test Measurement Invariance. Any factor analysis needs a sample planned for the intended model, not a fixed participants-per-item ratio. No minimal clinically important difference has been established for the BFI as a general personality measure. Report the exact version and language, the score distributions, and the missingness.

Reporting the Big Five Inventory

Personality was assessed with the 44-item Big Five Inventory (BFI-44; John et al., 1991; John et al., 2008). Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness were each calculated as the mean of their appropriately reverse-keyed items, giving domain scores from 1 to 5, with higher scores indicating greater endorsement of the corresponding trait. In the present sample (N = [N]), internal consistency was [α or ω = XX] for Extraversion, [XX] for Agreeableness, [XX] for Conscientiousness, [XX] for Neuroticism and [XX] for Openness. Missing item responses were handled by [prespecified rule].

References

Arterberry, B. J., Martens, M. P., Cadigan, J. M., & Rohrer, D. (2014). Application of generalizability theory to the Big Five Inventory. Personality and Individual Differences, 69, 98-103. https://doi.org/10.1016/j.paid.2014.05.015

Benet-Martínez, V., & John, O. P. (1998). Los Cinco Grandes across cultures and ethnic groups: Multitrait-multimethod analyses of the Big Five in Spanish and English. Journal of Personality and Social Psychology, 75(3), 729-750. https://doi.org/10.1037/0022-3514.75.3.729

Berkeley Personality Lab. (n.d.). The Big Five Inventory. https://www.ocf.berkeley.edu/~johnlab/bfi.htm

Husain, W., Haddad, A. J., Husain, M. A., Ghazzawi, H., Trabelsi, K., Ammar, A., Saif, Z., Pakpour, A., & Jahrami, H. (2025). Reliability generalization meta-analysis of the internal consistency of the Big Five Inventory (BFI) by comparing BFI (44 items) and BFI-2 (60 items) versions controlling for age, sex, language factors. BMC Psychology, 13, Article 20. https://doi.org/10.1186/s40359-024-02271-x

John, O. P., Donahue, E. M., & Kentle, R. L. (1991). The Big Five Inventory: Versions 4a and 54 [Technical report]. Institute of Personality and Social Research, University of California, Berkeley.

John, O. P., Naumann, L. P., & Soto, C. J. (2008). Paradigm shift to the integrative Big Five trait taxonomy: History, measurement, and conceptual issues. In O. P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality: Theory and research (3rd ed., pp. 114-158). Guilford Press.

John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (2nd ed., pp. 102-138). Guilford Press.

Rammstedt, B., & John, O. P. (2007). Measuring personality in one minute or less: A 10-item short version of the Big Five Inventory in English and German. Journal of Research in Personality, 41(1), 203-212. https://doi.org/10.1016/j.jrp.2006.02.001

Soto, C. J., & John, O. P. (2017a). The next Big Five Inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power. Journal of Personality and Social Psychology, 113(1), 117-143. https://doi.org/10.1037/pspp0000096

Soto, C. J., & John, O. P. (2017b). Short and extra-short forms of the Big Five Inventory-2: The BFI-2-S and BFI-2-XS. Journal of Research in Personality, 68, 69-81. https://doi.org/10.1016/j.jrp.2017.02.004

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(5), 1041-1053. https://doi.org/10.1037/0022-3514.84.5.1041

Frequently Asked Questions

Is the Big Five Inventory a diagnostic test?

No. The BFI measures variation in five personality traits and offers no validated clinical cut-offs. A high Neuroticism mean describes a tendency toward negative emotional reactions, and it should not be read as a diagnosis of depression or an anxiety disorder.

How do I reverse-code the BFI in SPSS?

With the standard 1 to 5 coding, the 16 reverse-keyed items (2, 6, 8, 9, 12, 18, 21, 23, 24, 27, 31, 34, 35, 37, 41 and 43) become 6 minus the response, so a recorded 1 becomes 5. Check the item order of your own file against the administered form first, since the numbers hold only for the standard English order.

Should I report domain means or sums?

Means are usually easier to read because the domains have different numbers of items (8, 9, 9, 8 and 10), and all five means then share the same 1 to 5 metric. Sums would run from 8 to 40, 9 to 45, 9 to 45, 8 to 40 and 10 to 50. State the metric you chose. A 0 to 100 POMP score is also possible, but it is a rescaling, not a percentile rank.

Can the BFI-44 key be used on BFI-2 data?

No. The BFI-2 has 60 items grouped into five domains and 15 facets, with its own item keys and its own missing-item guidance. Use the BFI-2 scoring materials from the developers and keep the two versions in separate scripts and separate analyses.

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