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The Bangla Big Five Inventory-2:
a comprehensive psychometric
validation
Mushqul Anwar Siraji2, Fahria Karim2, Christopher J. Soto3 & Shamsul Haque1
The Big Five Inventory-2 (BFI-2) is a widely recognized tool for assessing personality traits across
ve domains and fteen facets. However, its psychometric properties in non-Western cultures like
Bangladesh remain unexplored. This study aimed to validate the Bangla BFI-2 (BFI-2-B) within a
Bangladeshi community sample to provide a culturally adapted personality assessment tool. A cross-
sectional survey was conducted on 1,095 participants, where 646 participants (59%; 358 female;
Agemean = 24.25 years, SD = 4.47) passed all attention checks. Participants responded to a demographic
questionnaire, Bangla Big Five-2 (BFI-2-B), and Bangla NEO Five-Factor Inventory (NEO FFI). The
domain-level structural validity was analyzed using Exploratory Structural Equation Modeling (ESEM).
A series of ve dierent latent models were tested by Conrmatory Factor Analysis (CFA) for facet-
level structural validity. Full Measurement invariance across gender, education level, and language
were tested. The item quality was assessed using Item Response Theory analysis (IRT). Convergent and
discriminant validity were assessed by correlating the BFI-2-B domains with the NEO-FFI. The BFI-
2-B demonstrated high internal consistency across domains (> 0.70) and facets (> 0.60; except energy
level, intellectual curiosity, and respectfulness). ESEM conrmed structural validity at the domain
level (CFI & TLI = 0.96). CFA analysis revealed that at the facet level, a three-facet structure with an
acquiescence factor yielded the most acceptable t (CFI& TLI
≥
0.95; RMSEA
≤
0.06; SRMR
≤
0.08).
Full measurement invariance was established across gender and educational levels, but only weak
invariance was found across languages, indicating linguistic challenges. The similar domains of BFI-
2-B and NEO-FFI had strong correlations (r
≥
0.59), and distinct domains exhibited low correlations,
indicating strong convergent and discriminant validity. IRT analysis showed that most items had high
to moderate discrimination. The BFI-2-B is a reliable and valid tool for assessing personality in the
Bangladeshi context, with robust psychometric properties across domains and most facets. Addressing
linguistic nuances and testing in more diverse samples can further enhance its cross-cultural
applicability.
The stage 1 protocol for this Registered Report was accepted in principle on 24/09/24. The protocol,
as accepted by the journal, can be found at: 10.17605/OSF.IO/7DTQG.
Personality traits are relatively enduring patterns of thoughts, emotions, and behaviors guiding an individual’s
tendency to respond in a certain way under a given circumstance1. ere is a consensus in the literature that
personality traits robustly inuence our health and wellness2, job performance3, and academic achievement4.
Hence, it is critically important to measure personality traits precisely. In that vein, a major psychometric
theory in the personality eld- Big Five (BF) theory5–7 was brought to light, which categorized personality traits
into ve independent bipolar dimensions: Extraversion, Neuroticism or Negative Emotionality, Agreeableness,
Consciousness, and Open mindedness. In addition to this ve-domain model of the BF, literature has extended
its support to the hierarchical nature of the BF domains with several facets nested under each domain8–10. e
main dierence between domain and facet is the degree of conceptual breadth they cover. Each personality trait
domain of the BF (e.g., BF-Extraversion) enjoys a higher bandwidth of conceptual breadth and represents a large
amount of behavioral information7. In contrast, personality trait facets are narrowly dened (e.g., the “sociable”
facet under the “BF-Extraversion” domain) and provide a specic description of behaviors.
Rooted in the BF theory, several personality assessment tools were developed, including the NEO Personality
Inventory-revised11, International Personality Item Pool-NEO8, and Big Five Aspect Scale12. ese long, in-
1Department of Psychology, Jerey Cheah School of Medicine and Health Sciences, Monash University Malaysia,
Subang Jaya, Malaysia. 2Department of History and Philosophy, School of Humanities and Social Sciences, North
South University, Dhaka, Bangladesh. 3Department of Psychology, Colby College, Waterville, USA. email:
shamsul@monash.edu
OPEN
REGISTERED
REPORT
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depth measures provide a clear picture of BF domains with incremental information regarding the facets within
each domain. However, over the years, researchers faced a major challenge of balancing the content adequacy
of the personality measures with the procedure’s length and cost-eectiveness. e Big Five Inventory-1 (BFI-
1) was introduced nearly 20years ago7,13 to address this. BFI-1 incorporates 44- brief, easy-to-understand trait
descriptive phrases representing the BF domains to facilitate coherence, clarity, and eciency with a substantial
reduction in completion time (5–10min depending on the reader’s ability) compared to other personality
measures14. However, the focus of BFI-1 was limited solely to the domain level of traits.
Recently, BFI-1 received a major revision14, in which the authors incorporated the hierarchical model of
personality traits by including three prominent facet traits under each BF domain. In the new BF Inventory
2 (BFI-2), the item number increased to 60 (15 facets with four items each, nested under ve domains) with
an equal number of positively and negatively keyed items (both at the domain and facet level) to address the
consenting responding style—participants’ tendency of consistently providing agree or disagree responses in
the survey items, regardless of the item content. With a more balanced item formulation, BFI-2 oers greater
predictive precision14. Soto and John14, in their validation study, reported satisfactory psychometric properties
of the BFI-2 among a U.S. student sample (n = 470). Despite the increase in length, BFI-2 remains economical
compared to other scales15 and has been widely used in research and applied elds. As of 1 November 2023, the
initial BFI-2 paper14 has been cited 2259 times (Google Scholar). BFI-2 has been translated into more than 30
languages and psychometrically validated in Chinese15, Turkish16, Danish17, Dutch18, Russian19, and German20.
It is important to acknowledge that the initial psychometric properties of the BFI-2 were obtained from
Western, Educated, Industrialized, Rich, and Democratic (WEIRD) populations. Given the observed dierences
in personality domain structures and other correlates of personality traits among the personality measures across
cultures, using them without proper psychometric validations on non-Western cultures would lead to erroneous
interpretation21,22. To what extent these ndings could be generalized to other countries, such as Bangladesh –
an Asian country – remains less explored. Zhang, et al.15, in their Chinese BFI-2 validation with four diverse
samples, successfully reproduced the BF domains however, two facets—trust (BF-Agreeableness domain) and
intellectual curiosity (BF-Open Mindedness)—exhibited relatively low reliability (n = 765). Ahya and Siaputra23,
in their validation work of Indonesian BFI-2, indicated that only 50 items exhibited satisfactory factor loadings
in an exploratory factor analysis. Additionally, the ve-domain structure did not yield adequate t through
conrmatory factor analysis. However, the facet-level model was successfully reproduced. Altogether, the ndings
of the adaptation work of BFI-2 in Asian countries indicate the necessity of psychometrically validating the
BFI-2 in the Bangladeshi context to increase the generalizability and precision of this measurement. Moreover,
there is a lack of published psychometrically valid scales in Bangla to measure personality. Only a Bangla ten-
item Personality Inventory24 is available in the published literature, developed based on BFI-1 and employing
only two items per domain. ough short measures are sometimes handy, a full-length measure of personality,
such as BFI-2, which accounts for both domains and facets, would facilitate an in-depth understanding of
the personality of the Bangladeshi community people. us, in this paper, we took the initiative to adapt and
psychometrically validate the BFI-2 in Bangla.
e BFI-1, which has been widely used globally for the last 20years in various cultural and linguistic settings,
is reported to be susceptible to gender dierences, where women tend to score higher than men in some trait
domains25–27. Further, Dahmann and Anger28 found that low education level led to more extraversion and
less emotional stability among young German adults, indicating the susceptibility of personality domain to
education level. ese measurement invariance (MI) issues across gender and education levels in BF-1 have
been studied robustly25,28. However, for the BFI-2, measurement invariance (MI) has been investigated mostly
cross-culturally (English vs Native language): U.S. student and internet validation sample (n = 1470) vs. Chinese
sample (n = 1718)15, and U.S. internet validation sample (n = 1000) vs. German sample (n = 1338)20. Research on
measurement invariance (MI) focusing on gender, education level, and language (Bangla vs. English) invariance
for BFI-2 is currently lacking but highly recommended.
Validation studies of BFI-2 following factor analytic strategies (exploratory and conrmatory) conducted
over the years could now be considered suboptimal methods. Many studies used Principal Component
Analysis (PCA) to report the domain-level factor structure of BFI-214,19,29. ough commonly used, PCA does
not dierentiate between common variance (variance due to the hypothesized factors) and unique variance
(variance attributed to the respondents’ characteristics). Hence, PCA is less suited to examine the factor
structure of personality measures. Furthermore, conventional reporting of Exploratory Factor Analysis (EFA)
lacks specic goodness-of-t criteria and follows some rules of thumb to investigate the factor structure. Factor
structures obtained by these conventional EFA are oen susceptible to sample size and do not replicate easily30.
Hence, it became a common practice in the personality domain to employ Conrmatory Factor Analysis (CFA),
which focuses on validating a hypothesized factor structure30. Yet reproducing the factor structure of personality
inventories, including BF, using the CFA method remains controversial30,31. e invariance of factor structure
across dierent populations could be attributed to the tenuous simple structure assumption of the CFA analysis
strategy, which typically requires items of BF measures to be trait-specic. is issue could be avoided by
employing the Exploratory Structure Equation Modeling (ESEM)32.
ESEM accounts for non-trivial cross-loading consistently found in personality measurements33. It’s
encouraging to observe that recent adaptation studies utilize the ESEM technique to investigate the hypothesized
factor structure, especially the domain-level structure of BFI-215,20,34,35. However, individual item quality
assessment of BFI-2 has scarcely been conducted using Item Response eory (IRT). In contrast to Classical
Test eory (CTT) approaches (ESEM, factor analysis) that assume all items’ contributions are equal, IRT
acknowledges that some items could be more dicult than others and considers the interaction of item diculty
and personal characteristics (latent traits) of the respondents while measuring psychological constructs, i.e.,
personality. By assessing item diculty, item discrimination, item bias, and item information carried across the
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latent trait, IRT-based analysis supplements the CTT-based analyses to increase the precision and accuracy of
a measure. Soto and John36 employed IRT-based analysis to develop short and extra-short forms of the BFI-2.
However, a full-scale examination of the BFI-2 using IRT principles is highly required.
is study aims to validate the Big Five Inventory-2 among Bangladeshi community samples. In that pursuit,
we seek answers to four questions: (Q1) What is the latent structure of the Bangla BFI-2 (BFI-2-B)? (Q2) What
is the extent of measurement invariance of the BFI-2-B across gender, education level, and language (English vs
Bangla language)? (Q3) What is the quality of items in the BFI-2-B when assessed using Item Response eory
(IRT)? (Q4) What is the convergent and discriminant validity of the BFI-2-B? e Table 1 summarizes the research
questions addressed in this study. To answer these four questions, we set four specic objectives for this study.
First, we will investigate the structural validity of the domain-level and facet-level structure of the Bangla BFI-2
(BFI-2-B; Q1). We hypothesize that the domain level and facet level structure of BFI-2 would be reproducible in
the Bangladeshi community sample (H1). Second, we will investigate the measurement invariance of the BFI-
2-B across gender, education level, and language (Q2). We hypothesize that full invariance of the BFI-2-B would
be established for gender, education, and language (H2). ird, we will employ item response theory (IRT) based
analysis to assess the item quality of the BFI-2-B (Q3). Lastly (Q4), we will gather convergent and discriminant
validity of the BFI-2-B by calculating correlations between the big ve domains of personality measured using
the BFI-2-B and the Bangla-translated NEO Five-Factor Inventory (NEO-FFI)37. Previous studies14,38 while
establishing the measurement properties of BFI-2, reported strong correlations (
≥.50)
between the similar
domains of BFI-2 and NEO-FFI (convergent validity, e.g., BFI-2 Extraversion with NEO-FFI Extraversion) and
very weak to moderate correlations between distinct domains (discriminant validity, e.g., BFI-2 Extraversion
with NEO-FFI Conscientiousness). Hence, we hypothesize strong (≥ 0.50) correlations between similar domains
(showing convergent validity) and discriminant validity (correlations between distinct domains) would be lower
than the convergent validity of BFI-2-B and Bangla-translated NEO-FFI (H3).
Methods
Ethics information
e project has obtained ethics clearance from the Monash University Human Research Ethics Committee
(Project ID: 41934). All methods were performed in accordance with the relevant guidelines and regulations.
Question Hypothesis (if
applicable) Sampling plan Analysis plan Interpretation given to dierent outcomes
Q.1. What is the
latent structure
of Bangla BFI-2?
H1: e domain
level and facet
level structure of
BFI-2 would be
reproducible in
the Bangladeshi
community
sample
For structural equation modeling framework-
based analysis it is to have 10 participants
per item. BFI-2-B has 60 items, at least
600 participants are required. Monte Carlo
Simulation studies suggested a sample size of
200–500 to evaluate the obtained result safely
when analyzing ordinal data with the “Weighted
Least Square with mean and variance”
(WLSMV) estimator. Hence, we target to attain
a sample size of 600. Data collection will be
stopped once we have 600 complete data
We would investigate the structural
validity of the BFI-2-B both at the
domain and facet levels. e domain-
level structural validity of BFI-2-B
would be investigated using Exploratory
Structural Analysis Modeling (ESEM).
Facet-level structural validity of each
domain, we would employ conrmatory
factor analysis (CFA) with the
“Weighted Least Square with mean and
variance” (WSMV) estimator
To assess the model t in ESEM and CFA we
would follow the popular suggestions of Hu
and Bentler51: Comparative t index (CFI)
and the Tucker Lewis index (TLI): good t
≥
0.95, acceptable t
≥
0.90); the root means
square error of approximation (RMSEA):
good t < .06, acceptable t < .08; and the
standardized root mean square (SRMR) good
t < 0.08, acceptable t < 0.10
Q.2. What is
the extent of
measurement
invariance of
the BFI-2-B
across gender,
education level
and language
(English Vs.
Bangla)?
H2: A full
measurement
invariance across
gender, education
level, and language
would be observed
We would follow the sampling plan of Q1 given
that the analyses strategies fall under same
family
ESEM-based ve-domain model
would be used investigate the full
measurement invariance using the
13-model taxonomy of Marsh, et al.52
To assess measurement invariance, we
would follow the suggestions of Cheung and
Rensvold55, where invariance between two
models would be indicated by ΔRMSEA
≤
0.01 and ΔCFA
≥
=-0.01
Q.3. What is the
quality of items
in BFI-2-B when
assessed using
Item Response
eory (IRT)?
Not applicable
Sampling adequacy for IRT analysis was
analyzed using a Monte Carlo Simulation using
the “SimDesign” package (Chalmers & Adkins,
2020) with a sample size varying from 100–600.
IRT models at the facet level with 4 items was
considered the average root mean squared error
(RMSE) was calculated to estimate the optimal
sample size for the graded response model. e
RMSE became stable with a range of 1.34–1.39
for N = 500 to 600. Our planned sample size
exceeds the requirement
We would subject each facet to item
response theory-based item analysis.
For each facet, we would t a graded
response-based IRT model57 with
a marginal maximum likelihood
estimation method with the MHRM
algorithm
We would report the item diculty and
item discrimination and categorize the
items based on discriminatory power
following the guidelines of Baker59: none = 0,
very low = 0.01–0.34, low = 0.35–0.64,
moderate = 0.65–1.34, high = 1.35–1.69, very
high > 1.70. e test information curve will
be inspected to identify the range of latent
continuum (
θ
) with the highest information
and least standard error of measurement.
We will estimate and report the marginal
reliability coecients for the tted IRT models
Q.4. What is the
convergent and
discriminant
validity of the
BFI-2-B
H3: We expect a
strong (≥ 0.50)
correlation for
convergent
validity.
Convergent
validity is expected
to be higher than
discriminant
validity (H3)
A power analysis with 80% power with
alpha = 0.05, at least 82 participants is required
for a person-product moment correlation
analysis. Our planned sample size exceeds the
requirement
Convergent validity:
Correlation of similar domains of BFI-2
and NEO-FFI, e.g., BFI-2 Extroversion
and Neo Extroversion
Discriminant validity:
Correlation of distinct domains of BFI-
2 and NEO-FFI, e.g., BFI-2 Extraversion
with NEO-FFI Conscientiousness
We would check the statistical signicance
(p < 0.05), directionality and strength of the
correlations. We expected that the correlation
of similar domains would be strong (
≥0.50
) and higher than the correlations of distinct
domains
Tab le 1. Design table.
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Digital informed consent from all participants were recorded at the beginning of the online survey. Participation
was voluntary, and participants could withdraw from participation at any time without being impacted negatively.
Participants received a gi worth 3 USD and feedback on their personality scores for their contribution.
Design
Materials
Demographic questionnaire. e demographic questionnaire asked about participants’ age, gender, socio-
economic status, religion, marital status, occupation, and education level.
Big Five Inventory- 2. e Big Five Inventory-2 (BFI-2)14 is a 60-item scale incorporating the hierarchical
structure with 15 facets nested under 5 major personality domains: BF-Extraversion, BF-Negative Emotionality,
BF-Agreeableness, BF-Conscientiousness, and BF-Open Mindedness. ese 60 items are short, easily understood
(e.g., “Is outgoing, sociable”, “is relaxed, handles stress well”) and use a 5-point Likert type response format
(1 = Disagree strongly; 2 = Disagree a little; 3 = Neutral; no opinion; 4 = Agree with a little; 5 = Agree strongly). Soto
and John14 reported satisfactory reliability (0.81–0.90 for domains and 0.59–0.86 for facets across the internet
validation sample-1000 adults and student validation sample-470 students).
Big Five Inventory-2-Bangla. e BFI-2-B was developed by translating and adapting BFI-2 items using the
International Test Commission (ITC) guidelines39. ree bilingual scholars, natives of Bangladesh, conducted
the forward translation of the BFI-2 to Bangla. e translated versions were judged and synthesized by the
authors. Subsequently, three bilingual scholars back-translated the Bangla scale into English. e authors
again synthesized the three back-translations, compared them with the original scale, and made necessary
amendments. Twelve mental health professionals assessed the content validity of the BFI-2-B by independently
evaluating the relevance of the 60 items using a 4-point Likert type scale (1: not at all relevant, 2: slightly relevant,
3: quite Relevant, 4: Highly Relevant). e item-level content validity (I-CVI) and scale-level content validity
index (S-CVI) were estimated as content validity indicators. Items with an I-CVI score > 0.83 and S-CVI > 0.90
indicate adequate content validity40,41. Eight items were below the cut-o value. ese eight items were readjusted
and re-evaluated by the same experts. Aer adjustment, I-CVI scores of all items were acceptable. e S-CVI
for the total scale was 0.94, estimated using the average method, and indicated satisfactory content validity40,41.
NEO Five-Factor Inventory. e NEO Five-Factor Inventory (NEO FFI)37 is a 60-item scale that measures
personality using the same ve domains as BFI-2: NEO-Extraversion, NEO-Negative Emotionality, NEO-
Agreeableness, NEO-Conscientiousness and NEO-Open Mindedness. NEO-FFI measures each of the ve domains
using 12 items with a 5-point Likert-type scale (1 = Disagree strongly; 2 = Disagree a little; 3 = Neutral; no opinion;
4 = Agree a little; 5 = Agree strongly). We translated the NEO-FFI into Bangla using the forward–backward
translation method and used it in the current study.
Procedure
We rst ran a pilot (N = 50) study to double-check the questionnaire translation and debug the R scripts for
analysis. Aer this, we launched a quantitative, cross-sectional, anonymous online survey. Participants were
recruited using social media platforms. On the online survey’s landing page, explanatory statements contained
information on inclusion and exclusion criteria and data condentiality statements. It was mentioned in the
explanatory statement that their participation would be voluntary and that they could withdraw from participation
at any time without being impacted negatively. If happy with the explanatory statements, participants agreed to
participate (oered consent online). Participants rst responded to a demographic questionnaire. Second, they
completed the 60-item BFI-2 and, nally, responded to the 60-item NEO-FFI-B. e survey required around
20–25min to complete. Participants received a gi worth 3 USD and feedback on their personality scores for
their contribution.
Sampling
As a rule of thumb, 10 participants per item were required for analysis based on the structural equation modeling
framework42,43. Since BFI-2-B has 60 items, at least 600 participants were required. Monte Carlo Simulation
studies suggested a sample size of 200–500 to evaluate the obtained result safely when analyzing ordinal data
with the Weighted Least Square with Mean and Variance (WLSMV) estimator. Further, we assessed the sampling
adequacy for IRT analysis using a Monte Carlo Simulation using the “SimDesign” package44 with a sample size
varying from 100–600. We simulated the IRT models at the facet level with 4 items. We calculated the average
root mean squared error (RMSE) to estimate the optimal sample size for the graded response model. e RMSE
became stable with a range of 1.38–1.40 for N = 500 to 600. Lastly, a power analysis using G*Power45 indicated
that 82 participants are required for a signicant correlation of medium eect (r = 0.3;α = 0.05) with 80% statistical
power. Our planned sample size well exceeded the requirement. We launched an online survey based on these
guidelines to collect data from 600 participants at least. Four items for attention checks were included in the
survey to ensure that participants are attentive while they respond to the survey (e.g., is is an attention check.
Please select “Strongly disagree”). Once we launched the survey, we checked weekly for completeness (100%
completeness with all attention checks correctly answered). We planned to stop data collection once we had at
least 600 participants and a 100% completion rate. In case of excess data, we incorporated them in our analysis.
Exclusion and inclusion criteria
Any Bangladeshi national living in Bangladesh, aged over 18, who could read and write the Bangla language
were eligible to participate in the survey. Bangladeshi nationals who did not permanently reside in Bangladesh
(settled overseas) were excluded due to their exposure to multiple social norms and cultures. Participants who
failed the attention check were excluded. Table 1 summarizes the design of the study.
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Analysis plan
We used R46 with RStudio for all the analysis. Several statistical packages, including psych47, esemComp48, and
lavaan49 were used. Figure1 summarizes the data analysis steps.
Descriptive statistics and reliability analysis
We reported the descriptive statistics and estimated the reliability of each domain and facet of the BFI-2-B in
our sample using the psych47 package. We reported Cronbach’s α and McDonald’s ωt coecient for reliability
estimates.
Domain and facet level structural validity
We investigated the structural validity of the BFI-2-B at both the domain and facet levels. e domain-level
structural validity of the BFI-2-B was investigated using Exploratory Structural Equation Modeling (ESEM)
using esemComp48 package. ESEM is a substantive-methodological synergy that integrates the computational
power of conrmatory factor analysis and exploratory factor analysis32,50. We examined whether the ve BFI-
2-B domains could be recovered in our sample at the item level (each item serves as an indicator of the Big
Fig. 1. Data analysis steps.
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Five domain). We allowed all items to load on all ve domains using a rotated target matrix (60 × 5) where the
primary loading’s positions were le unspecied, and the cross-loadings were set to zero. To assess the model
t, followed the popular suggestions of Hu and Bentler51: Comparative t index (CFI) and the Tucker Lewis
index (TLI): good t
≥
0.95, acceptable t
≥
0.90); the root means square error of approximation (RMSEA):
good t < 0.06, acceptable t < 0.08; and the standardized root mean square (SRMR) good t < 0.08, acceptable
t < 0.10.
To investigate the facet-level structural validity of each domain, we employed conrmatory factor analysis
(CFA) with the Weighted Least Square with Mean and Variance (WSMV) estimator. lavaan49 was used to run
the CFA. Here, we tested the ve models that Soto and John14 used in their study to investigate the facet level
structure of BFI-2: (M1) Single Domain Structure- all 12 items of a domain were allowed to load on a single
factor; (M2) Single Domain with acquiescence- in addition to the single domain factor an acquiescence method
factor were added. In line with their study, we constrained the factor loadings of all items on the acquiescence
factor equal to 1, making both true-keyed and false-keyed items load in the same direction. To ensure the proper
representation of individual dierences that were caused by response style but not due to personality content,
the acquiescence factor was not allowed to correlate with domain factors; (M3) positive and negative items—two
correlated factors where true keyed items were loaded on one factor, and false-keyed were loaded on another;
(M4) the three facets model- representing the three facets within each Big Five Domain; (M5) three facets plus
acquiescence model- An acquiescence factor were added to the three facets model. In this model, each item
was allowed to load on its corresponding facet and the acquiescence method factor. All factor loadings in the
acquiescence factor were constrained to 1, and no correlation will be allowed between the acquiescence factor
and the three facets. To assess the model t, we followed the aforementioned guidelines of Hu and Bentler51.
Measurement invariance
We extended the ESEM-based ve-domain model to investigate the full measurement invariance using the
13-model taxonomy of Marsh, et al.52 across gender, educational level, and language (English vs. Bangla).
lavaan49 was used to run the measurement invariance analyses. To assess the invariance across Bangla and
English versions of the test, we used the internet sample (N = 1000) collected by the third author and used to
nalize BFI-2 items, their domain, and facet structures14. We compared that data with the data accumulated
from Bangladeshi participants using the Bangla version of the test. For gender, language, and education level
full measurement invariance testing, we used the ESEM paradigm, which allowed us to compare the invariance
using raw data, thus accounting for individual item functioning. Typically, measurement invariance investigation
incorporates a sequence of model t, starting with the least restricted model—congural invariance with no
parameter invariance constraints53. Next, the weak measurement invariance model constrains factor loadings
to be equal across the groups. Strong measurement invariance assumes the indicator means and factor loadings
to be invariant over groups. Strict measurement invariance constrains the factor loadings, indicator means, and
item uniqueness to be equal over the groups. Marsh, et al.54 proposed a 13-model taxonomy that expands this
four-model-based invariance testing by integrating both factorial and measurement invariance techniques where
the sequence of testing propagates from congural invariance to a model of full invariance (Complete factorial
invariance) that posits strict invariance as well as the invariance of latent mean and factor variance–covariance
matrix. At least, strict measurement invariance would be required to compare the BFI-2-B scale’s scores across
dierent attributes such as gender, education levels, and language (For a more extended discussion of the 13
model taxonomy, please see Marsh, et al.52). To assess measurement invariance, we followed the suggestions of
Cheung and Rensvold55, where invariance between two models would be indicated by ΔRMSEA
≤
0.01 and
ΔCFA
≥−0.01
.
Item response theory-based analysis
We subjected each facet to item response theory (IRT)-based item analysis. mirt56 package was used to run
the IRT-based item analysis. We t a graded response-based IRT model57 for each facet using the marginal
maximum likelihood estimation method with the MHRM algorithm. We gathered information on item
diculty, discrimination, and test information. We assessed the local t of the items using int, outt, S-
χ2,
and S-
χ2
associated RMSEA statistics. Person t was evaluated using
Zh
statistics58.
Zh
< -2 was considered a
mist for each facet. We reported the item diculty and item discrimination and categorized the items based
on discriminatory power following the guidelines of Baker59 none = 0, very low = 0.01–0.34, low = 0.35–0.64,
moderate = 0.65–1.34, high = 1.35–1.69, very high > 1.70. e overall test information curves were inspected to
identify the range of latent continuum (
θ
) with the highest information and least standard error of measurement.
We estimated marginal reliability coecients for the tted IRT models.
Convergent and discriminant validity
Lastly, we investigated the convergent and discriminant validity of the BFI-2-B by using Pearson’s partial
product-moment correlation between the scores of BFI-2-B and the Bangla-translated NEO-FFI, controlling
for the gender and age of the participants. We expected strong (≥ 0.50) correlations between similar domains
for convergent validity. Discriminant validity (correlations between distinct domains) was expected to be lower
than convergent validity.
Deviations from the preregistered plan
We acknowledge two deviations from the preregistered plan. First, due to technological limitations, we aggregated
item scores for each facet and treated the facet scores as continuous indicators while tting the ESEM model for
full invariance testing, instead of analyzing item-level data as planned. Second, the pilot data, collected before
Stage 1 Acceptance of the manuscript, to evaluate the feasibility of the plan and the accuracy of the analysis code
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as requested by reviewers, were included in the full study sample rather than reported separately as initially
planned.
Results
Pilot
We conducted a pilot study with 50 participants to double-check the questionnaire translation and debug
the R scripts for analysis. e entire survey took approximately 20min to complete. To collect data from 50
participants with a 100% completion rate (attention check items included), we had to record data from 57
participants (87.72% success rate). Among the 50 participants, 28 were male (Agemean = 22.68; AgeSD = 1.83),
and 22 were female (Age: Mean = 23.59; SD = 4.24). e majority were undergraduate students (98%), Muslim
(98%) and unmarried (96%). In the pilot, the reliability of the ve domains of BF were extraversion: Cronbach’s
α = 0.76, McDonald’s ωt = 0.78; agreeableness: Cronbach’s α = 0.8, McDonald’s ωt = 0.80; conscientiousness:
Cronbach’s α = 0.76, McDonald’s ωt = 0.78; negative emotionality: Cronbach’s α = 0.83, McDonald’s ωt = 0.84;
open mindedness: Cronbach’s α = 0.80, McDonald’s ωt = 0.81. All analysis codes were executable. e pilot data
indicated that the proposed study is realistic and feasible.
Characteristics of study sample
We have collected 1095 participants’ responses (including the pilot sample), resulting in complete responses (100%
completion) of 646 participants who passed all four attention checks. Table 2 summarizes the characteristics
of the current sample. Among the participants, 358 were females (Agemean = 24.59 years; AgeSD = 4.69) and 288
males (Agemean = 23.33 years; AgeSD = 4.14). Most participants were Muslim (91%), with similar proportions
across genders (92% for females and 91% for males); 82% were unmarried, and 84% were university students.
Participants with government jobs represented 13% of the sample, while those in business or private sector jobs
were less common (1.7% and 1.2%, respectively). e mean score of participants’ social stance (an individual’s
perceived social position in a social hierarchy measured by a single-item 10-point Likert scale: 1 for the lowest
and 10 for the highest social position) was 6.65 (SD = 1.63), with females showing a slightly higher mean (6.72,
SD = 1.65) than males (6.56, SD = 1.61).
Characteristics of internet sample collected earlier
e internet validation sample (N = 1000) gathered for the development of BFI-214 earlier (English version)
was compared with our sample (completed the Bengali version) to investigate the measurement invariance for
language. 50% of that sample was female. eir age ranged from 18 to 74 (Mean = 28.73years, SD = 11.68), with
most (65%) under 30. ey were mostly White/Caucasian (66%) and residing in the United States (82%). A
detailed description of the sample is published elsewhere14.
Descriptive statistics and reliability analysis
Tables 3 and 4 present the descriptive statistics of BFI-2-B. All items violated the normality assumption, due
to most participants agreeing with more desirable items and disagreeing with undesirable items. e corrected
item-total correlations ranged between 0.12–0.57 (Mean = 0.35; SD = 0.10). Table 4 provides the descriptives of
Var iable O verall, N = 6461Female, N = 3581Male, N = 2881
Age 24.25 (4.47) 24.59 (4.69) 23.83 (4.14)
Religion
Islam 590 (91%) 329 (92%) 261 (91%)
Hindu 47 (7.3%) 23 (6.4%) 24 (8.3%)
Christian 5 (0.8%) 5 (1.4%) 0 (0%)
Others 3 (0.5%) 0 (0%) 3 (1.0%)
Budda 1 (0.2%) 1 (0.3%) 0 (0%)
Marital status
Unmarried 530 (82%) 272 (76%) 258 (90%)
Married 113 (17%) 84 (23%) 29 (10%)
Divorced 3 (0.5%) 2 (0.6%) 1 (0.3%)
Profession
Student 544 (84%) 285 (80%) 259 (90%)
Government job 83 (13%) 63 (18%) 20 (6.9%)
Business 11 (1.7%) 6 (1.7%) 5 (1.7%)
Private job 8 (1.2%) 4 (1.1%) 4 (1.4%)
Education
Undergraduate 555 (86%) 299 (84%) 256 (89%)
Post-graduate 91 (14%) 59 (16%) 32 (11%)
Perceived social status 6.65 (1.63) 6.72 (1.65) 6.56 (1.61)
Tab le 2. Characteristics of study sample (N = 646). 1Mean (SD); n (%)
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BFI-2-B at the domain and facet level with mean-level gender dierences within each sample. Women tend to
describe themselves as somewhat more agreeable, conscientious, and emotional (for all instances, p < 0.05). At
the facet level, women described themselves as more compassionate, trustworthy, organized, anxious, depressed,
and emotionally volatile than men (for all instances, p < 0.05). Men described themselves as more intellectual
and creative (for all instances, p < 0.05).
Table 5 presents the reliability coecients of BFI-2-B and NEO-FFI. e values of Cronbach’s α, and
McDonald’s Omega for all ve domains of BFI-2-B and NEO-FFI (except NEO- conscientiousness & NEO-
Open mindedness) were > 0.70. Supplementary Table S1 presents the reliability coecients of the 15 facets of
BFI-2-B. e reliability indices for the 15 facets ranged between 0.38 to 0.89 for Cronbach’s α and between 0.40
to 0.89 for McDonald’s ωt. All facets except energy level, responsibility, and intellectual curiosity had reliability
values > 0.60.
Domain and facet level structural validity
Table 6 presents the factor loading of domain-level validity analysis. e tted ESEM model with ve domains
exhibited good model t [χ2 = 3774.55, df = 1480, p < 0.001 CFI = 0.96, TLI = 0.96, RMSEA = 0.06 (90% CI:0.05–
0.05), SRMR = 05]. As shown in Table 6, all items under BF-Negative Emotionality exhibited the highest loadings
under the corresponding domain. Among the 12 items of the BF-Extraversion domain, 7 items had the highest
factor loading on the targeted Extraversion domain, one item (RBFI11) had the highest loading on Negative
Emotionality, and four items had the highest loading on Open Mindedness (BFI06, BFI21, BFI41, BFI56).
Results showed that the items of BF-Agreeableness equally spread over two domains-Agreeableness (RBFI12,
RBFI17, RBFI22, RBFI37, RBFI42, RBFI47) and Open Mindedness (BFI02, BFI07, BFI27, BFI32, BFI52, BFI57).
Among the 12 items of BF-Conscientiousness, 9 were loaded highest on the corresponding factor, and three
were loaded highest on Open Mindedness (BFI13, BFI38, BFI43). Items of BF-Open Mindedness were spread
over Agreeableness ( RBFI5, RBFI20, BFI35, RBFI50, RBFI55), Open Mindedness (BFI10, BFI15, BFI40,
RBFI45, BFI60) and Extraversion (RBFI25, RBFI30) domains. ese results indicate that the BFI-2’s intended
multidimensional structure can be recovered from the BFI-2-B, but with cross-cultural dierences in the precise
location of some items.
Table 7 presents the model t statistics for the series of ve-facet models within each domain. For all tted
models, the CFIs were > 0.90 and SRMR < 0.10 (except single domain open-mindedness). For most cases, a better
t was observed for three facets plus acquiescence models (extraversion, agreeableness, conscientiousness, open-
mindedness). For negative emotionality, the RMSEA values were over the upper threshold (RMSEA > 0.08) for
all tted models, but all other t statistics were acceptable for the three facets plus acquiescence model. Taken
together, these results suggest that, within each Big Five domain, BFI-2-B item responses can be modeled using
a combination of three substantive facet factors and an acquiescence method factor.
Measurement invariance
Due to technological limitations, while tting the ESEM model for full invariance testing, we aggregated the item
scores for each facet and treated the facet scores as continuous indicators. Parallelling the domain structure, the
facets were rotated towards a 15 × 5 target matrix with unspecied primary loadings and secondary loadings
set to zero. Such a technique to reduce the computational power required to compare complex latent models is
common in the literature15,20 and does not hinder our ability to test the hypothesis that the full invariance of the
BFI-2-B would be established for gender, education, and language (H2).
Supplementary Table S2 presents the results of the full invariance analysis of BFI-2-B data. For gender-focused
measurement invariance (male vs. female), all ΔCFAs were
≥
= − 0.01 except M5 (strong factorial invariance),
M7 (strict factorial invariance), and all ΔRMSEAs were
≤
0.01 except M10. For education-focused measurement
invariance analysis, all ΔCFAs were
≥
= − 0.01 except M3, M5 (strong factorial invariance), M7 (strict factorial
invariance), and M9, and all ΔRMSEAs were
≤
=0.01. In all cases, CFIs were
≥
0.90, and RMSEAs were
≤
0.0.08.
No tted models were rejected by both the cuto values (ΔRMSEA
≤
0.01 and ΔCFA
≥−0.01
) simultaneously.
ese results suggest the highest level of measurement invariance—complete factorial invariance—for gender
and education levels. By contrast, for language-focused measurement invariance analysis, only M1, M2, and M5
models exhibited acceptable t indices (CFI > 0.90). us, only weak factorial invariance was observed across
language.
Item response theory-based analysis
Supplementary Table S3 presents the IRT parameters, including item discrimination (a), item diculty, and
item-t indices for each of the 15 facets. All items exhibited acceptable item t (int & outt < 1.4, S-χ2 associated
RMSEA statistics
≤0.06)
. Supplementary Fig. S1 indicates that for all 15 models, Zh statistics are larger than − 2
for most participants, suggesting a good person t. As shown in Supplementary Table S3, among the 60 items, 3
items were very low, 2 items were low, 21 items were moderate, 12 were high, and 22 had very high discrimination
scores. Test information curves (TIC) for the tted models (Supplementary Fig. S2 & Supplementary Table S4)
indicated that each facet had a good range of coverage across the underlying traits with some facets (Compassion:
− 4.5 to 1.8, Respectfulness: − 5.3 to 1.7, Intellectual Curiosity: − 4.5 to 2) skewed toward lower trait levels. Marginal
reliability ranged between 0.57 to 0.88. All facets had marginal reliability > 0.60 except the responsibility facet
(Supplementary Table 3S). Taken together, these results indicate that items of BFI-2-B are well-calibrated to
measure the intended traits across a wide range of the latent continuum, demonstrating adequate psychometric
properties for assessing personality facets within the Bangladeshi population.
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Items Mean SD Skew Kurtosis Normality Corrected item total correlation
BFI01 3.52 1.01 − 0.71 − 0.13 0.85* 0.3
BFI06 3.63 0.89 − 0.69 0.56 0.86* 0.45
RBFI11 3.17 1.1 − 0.11 − 1.01 0.89* 0.15
RBFI16 2.64 1.25 0.37 − 1.01 0.88* 0.17
BFI21 2.7 1.13 0.26 − 0.93 0.89* 0.17
RBFI26 3.27 1.12 − 0.19 − 1.05 0.88* 0.37
RBFI31 2.02 0.87 1.22 1.71 0.76* 0.22
RBFI36 2.85 1.07 0.14 − 0.93 0.89* 0.35
BFI41 3.28 1.01 − 0.18 − 0.77 0.90* 0.54
BFI46 3.47 1.12 − 0.51 − 0.59 0.88* 0.25
RBFI51 2.91 1.01 0.18 − 0.66 0.90* 0.31
BFI56 3.72 0.81 − 0.79 0.78 0.82* 0.48
BFI02 4.17 0.75 − 1.11 2.42 0.77* 0.22
BFI07 4.44 0.64 − 1.51 5.24 0.68* 0.31
RBFI12 3.48 1.13 − 0.3 − 1.01 0.88* 0.31
RBFI17 3.99 1.09 − 1.26 0.94 0.78* 0.31
RBFI22 4.1 0.95 − 0.98 0.3 0.80* 0.35
BFI27 4.02 0.9 − 1.05 1.17 0.81* 0.28
BFI32 4.02 0.76 − 0.77 1.03 0.81* 0.38
RBFI37 3.16 1.14 − 0.01 − 1.2 0.87* 0.38
RBFI42 2.64 1.08 0.41 − 0.74 0.88* 0.33
RBFI47 3.99 1.02 − 1.02 0.5 0.82* 0.4
BFI52 4.29 0.58 − 0.47 1.56 0.72* 0.38
BFI57 3.64 0.98 − 0.69 − 0.06 0.85* 0.34
RBFI03 3.34 1.21 − 0.33 − 1.02 0.88* 0.43
RBFI08 2.82 1.22 0.15 − 1.09 0.90* 0.57
BFI13 3.67 0.97 − 0.79 0.26 0.85* 0.19
BFI18 3.59 1.05 − 0.7 − 0.15 0.86* 0.36
RBFI23 2.98 1.16 − 0.06 − 1.1 0.89* 0.5
RBFI28 2.28 0.93 1.00 0.69 0.79* 0.29
BFI33 3.55 1.07 − 0.52 − 0.51 0.88* 0.46
BFI38 3.71 0.77 − 0.65 0.63 0.82* 0.49
BFI43 4.2 0.75 − 0.97 1.42 0.78* 0.34
RBFI48 3.84 1.1 − 0.86 − 0.05 0.84* 0.4
BFI53 3.66 0.99 − 0.71 0.03 0.86* 0.42
RBFI58 2.83 1.11 0.28 − 1.05 0.87* 0.39
RBFI04 2.75 1.11 0.27 − 0.73 0.91* 0.46
RBFI09 2.36 0.99 0.73 0.08 0.86* 0.46
BFI14 2.98 1.21 0.09 − 1.13 0.89* 0.35
BFI19 2.95 1.11 0.07 − 0.99 0.90* 0.44
RBFI24 2.41 1.09 0.67 − 0.24 0.87* 0.41
RBFI29 2.74 1.09 0.51 − 0.65 0.87* 0.49
BFI34 3.62 1.14 − 0.53 − 0.72 0.87* 0.45
BFI39 3.69 1.05 − 0.64 − 0.38 0.86* 0.34
RBFI44 2.45 1.06 0.62 − 0.35 0.87* 0.42
RBFI49 3.24 1.15 − 0.18 − 1.04 0.89* 0.26
BFI54 3.53 1.12 − 0.59 − 0.57 0.87* 0.41
BFI59 2.87 1.19 0.21 − 1.08 0.89* 0.52
RBFI05 3.26 1.23 − 0.19 − 1.15 0.89* 0.25
BFI10 4.03 0.8 − 0.79 0.7 0.82* 0.29
BFI15 3.71 0.82 − 0.72 0.56 0.83* 0.5
BFI20 3.93 0.98 − 1.1 1.02 0.81* 0.22
RBFI25 3.8 1.02 − 0.78 − 0.01 0.85* 0.35
RBFI30 3.42 1.06 − 0.49 − 0.63 0.87* 0.46
BFI35 4.13 0.75 − 0.98 1.88 0.78* 0.33
BFI40 3.73 0.91 − 0.65 0.07 0.85* 0.25
Continued
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Convergent and discriminant validity
Table 8 presents domain-level correlations of the BFI-2-B with NEO-FFI. Results indicated that BFI-2-B
converged strongly with NEO-FFI while controlling for gender and age. e correlations between the similar
domains were ≥ 0.59 for all instances. Correlations between distinct domains were ≤ 0.39 for all instances. ese
results indicate good convergent and discriminant validity for the BFI-2-B.
Discussion
e current study aimed to validate the Bangla Big Five Inventory-2 (BFI-2-B) by examining important
psychometric properties, including reliability and validity (structural, convergent, and discriminant),
measurement invariance (across gender, education level and language), and item quality (item discrimination
and test information). e study was designed to test three specic hypotheses: (H1) that the domain and facet-
level structures of the BFI-2 would be reproducible in the Bangladeshi culture, (H2) that full measurement
invariance would be established across gender (male vs female), education levels (Undergrads vs Postgrads)
Cronbach’s α McDonald’s ωt
BFI-2-B NEO-FFI BFI-2-B NEO-FFI
Extraversion 0.76 0.84 0.83 0.84
Agreeableness 0.78 0.72 0.77 0.78
Conscientiousness 0.81 0.61 0.79 0.62
Negative emotionality 0.86 0.87 0.86 0.87
Open mindedness 0.76 0.58 0.77 0.64
Tab le 5. Reliability of the BFI-2-B and Bangla NEO-FFI.
Domain Combined1, N = 646 Female1, N = 358 Male1, N = 288 p
BF-extraversion 3.52 (1.01) 3.45 (1.01) 3.61 (1.02) 0.047
Sociability 3.52 (1.01) 3.45 (1.01) 3.61 (1.02) 0.047
Assertiveness 3.63 (0.89) 3.64 (0.90) 3.62 (0.87) 0.7
Energy level 3.17 (1.10) 3.24 (1.10) 3.09 (1.10) 0.070
BF-agreeableness 4.17 (0.75) 4.22 (0.72) 4.10 (0.79) 0.037
Compassion 4.17 (0.75) 4.22 (0.72) 4.10 (0.79) 0.037
Respectfulness 4.44 (0.64) 4.45 (0.64) 4.42 (0.65) 0.6
Tr ust 3.48 (1.13) 3.56 (1.11) 3.39 (1.16) 0.062
BF-conscientiousness 3.34 (1.21) 3.45 (1.20) 3.21 (1.21) 0.009
Organization 3.34 (1.21) 3.45 (1.20) 3.21 (1.21) 0.009
Productiveness 2.82 (1.22) 2.84 (1.25) 2.80 (1.18) 0.6
Responsibility 3.67 (0.97) 3.64 (0.99) 3.72 (0.94) 0.4
BF-negative emotionality 2.75 (1.11) 2.98 (1.10) 2.45 (1.04) < 0.001
Anxiety 2.75 (1.11) 2.98 (1.10) 2.45 (1.04) < 0.001
Depression 2.36 (0.99) 2.47 (1.01) 2.23 (0.96) < 0.001
Emotional volatility 2.98 (1.21) 3.14 (1.22) 2.77 (1.18) < 0.001
BF-open-mindedness 3.26 (1.23) 3.33 (1.19) 3.16 (1.28) 0.11
Intellectual curiosity 4.03 (0.80) 3.92 (0.82) 4.16 (0.76) < 0.001
Aesthetic sensitivity 3.26 (1.23) 3.33 (1.19) 3.16 (1.28) 0.11
Creative imagination 3.71 (0.82) 3.60 (0.85) 3.85 (0.76) < 0.001
Tab le 4. Descriptive statistics for BFI-2-B domains and facets. 1Mean (SD); p value is reported for independent
sample t-tests.
Items Mean SD Skew Kurtosis Normality Corrected item total correlation
RBFI45 3.93 0.97 − 0.81 0.02 0.83* 0.21
RBFI50 3.69 1.19 − 0.79 − 0.27 0.85* 0.26
RBFI55 3.37 0.91 − 0.08 − 0.6 0.89* 0.12
BFI60 3.42 0.97 − 0.42 − 0.3 0.89* 0.42
Tab le 3. Descriptives of BFI-2-B items. *p < 0.001.
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Negative Emotionality Conscientiousness Extraversion Open mindedness Agreeableness
BF-extraversion
BFI01 0.022 0.048 0.412 0.227 − 0.045
BFI06 − 0.228 0.135 0.116 0.314 − 0.006
RBFI11 0.369 − 0.044 0.190 0.151 − 0.090
RBFI16 0.151 − 0.065 0.802 − 0.199 0.075
BFI21 − 0.121 0.059 0.304 0.312 − 0.482
RBFI26 − 0.122 0.188 0.363 − 0.004 0.060
RBFI31 − 0.112 − 0.049 0.635 − 0.253 0.033
RBFI36 − 0.211 − 0.042 0.395 0.201 − 0.156
BFI41 − 0.243 0.300 0.218 0.375 − 0.191
BFI46 0.163 0.027 0.568 0.093 0.022
RBFI51 − 0.081 0.137 0.413 0.079 − 0.137
BFI56 − 0.072 0.095 0.336 0.468 − 0.056
BF-agreeableness
BFI02 0.080 0.168 − 0.265 0.454 0.130
BFI07 − 0.154 0.176 − 0.298 0.506 0.055
RBFI12 − 0.183 0.058 − 0.034 − 0.121 0.460
RBFI17 0.099 0.026 0.015 0.172 0.526
RBFI22 − 0.230 0.087 − 0.262 0.096 0.417
BFI27 − 0.142 0.191 − 0.323 0.368 0.050
BFI32 0.011 0.275 − 0.199 0.467 0.128
RBFI37 − 0.156 0.047 − 0.027 − 0.032 0.517
RBFI42 − 0.195 0.097 0.118 − 0.302 0.420
RBFI47 0.023 0.135 0.017 0.070 0.559
BFI52 − 0.111 0.221 − 0.313 0.539 0.137
BFI57 − 0.205 0.174 − 0.199 0.261 0.087
BF-conscientiousness
RBFI03 0.028 0.841 0.058 − 0.221 0.049
RBFI08 − 0.156 0.551 0.283 − 0.234 0.221
BFI13 0.013 0.083 − 0.004 0.338 − 0.003
BFI18 0.105 0.875 − 0.057 − 0.034 − 0.076
RBFI23 − 0.259 0.300 0.252 − 0.114 0.149
RBFI28 − 0.191 0.408 0.076 − 0.162 − 0.027
BFI33 0.114 0.960 − 0.023 − 0.074 0.001
BFI38 − 0.200 0.266 0.107 0.426 − 0.126
BFI43 − 0.041 0.297 − 0.173 0.495 − 0.053
RBFI48 0.138 0.806 0.015 − 0.157 0.163
BFI53 − 0.046 0.489 0.024 0.263 − 0.098
RBFI58 − 0.186 0.237 0.146 − 0.146 0.232
BF-negative emotionality
RBFI04 0.646 − 0.067 0.186 − 0.340 0.174
RBFI09 0.595 − 0.116 0.127 − 0.277 0.143
BFI14 0.434 − 0.023 − 0.074 0.178 − 0.198
BFI19 0.534 − 0.030 0.042 0.232 − 0.383
RBFI24 0.416 − 0.221 − 0.045 − 0.177 0.188
RBFI29 0.812 0.004 0.182 − 0.235 0.117
BFI34 0.747 0.095 − 0.126 0.150 − 0.083
BFI39 0.659 0.061 − 0.232 0.261 − 0.005
RBFI44 0.608 − 0.153 0.342 − 0.296 0.131
RBFI49 0.520 − 0.039 0.104 − 0.088 0.172
BFI54 0.665 0.018 − 0.223 0.170 0.033
BFI59 0.777 0.051 0.045 − 0.066 − 0.069
BF-open mindedness
RBFI05 0.107 − 0.198 0.301 0.002 0.517
BFI10 0.050 − 0.206 0.254 0.473 0.131
BFI15 − 0.137 0.081 0.180 0.541 − 0.006
Continued
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and language (Bangla vs English), (H3) that the BFI-2-B would show strong convergent validity (r
≥0.50)
for
similar domains measured using the Bangla NEO-FFI, as well as discriminant validity between distinct domains.
e BFI-2-B demonstrated satisfactory internal consistency for the ve major domains, with Cronbach’s α and
McDonald’s ωt values surpassing 0.76 for all domains. ese ndings align with the reliability indices reported for
the original English BFI-214 (α = 0.83–0.90) and adaptations in other languages, such as Chinese15 and Dutch18.
Model χ2df CFI TLI RMSEA
RMSEA 90%
CI
SRMRLower Upper
Extraversion
M1: single domain 483.24 54 0.906 0.885 0.111 0.102 0.120 0.084
M2:single domain plus acquiescence 481.66 53 0.908 0.883 0.112 0.103 0.121 0.084
M3: positive and negative items 470.55 53 0.908 0.886 0.111 0.101 0.120 0.081
M4: three facets 226.96 51 0.961 0.950 0.073 0.064 0.083 0.062
M5:three facets plus acquiescence 204.16 50 0.966 0.955 0.069 0.059 0.079 0.059
Agreeableness
M1: single domain 338.72 54 0.944 0.932 0.091 0.082 0.100 0.077
M2: single domain plus acquiescence 208.56 53 0.970 0.962 0.068 0.058 0.077 0.058
M3: positive and negative items 219.95 53 0.967 0.959 0.070 0.061 0.080 0.062
M4: three facets 282.47 51 0.955 0.941 0.084 0.075 0.094 0.071
M5: three facets plus acquiescence 196.57 50 0.971 0.962 0.068 0.058 0.078 0.057
Conscientiousness
M1:single domain 474.28 54 0.972 0.966 0.110 0.101 0.119 0.086
M2: single domain plus acquiescence 273.01 53 0.985 0.982 0.080 0.071 0.090 0.067
M3: positive and negative items 460.28 53 0.973 0.966 0.109 0.100 0.118 0.085
M4: three facets 227.67 51 0.988 0.985 0.073 0.064 0.083 0.064
M5: three facets plus acquiescence 119.34 50 0.995 0.994 0.047 0.036 0.058 0.045
Negative emotionality
M1: single domain 501.60 54 0.962 0.954 0.113 0.104 0.123 0.079
M2: single domain plus acquiescence 501.33 53 0.962 0.953 0.115 0.105 0.124 0.079
M3: positive and negative items 360.64 53 0.974 0.968 0.095 0.086 0.104 0.064
M4:three facets 398.11 51 0.971 0.962 0.103 0.093 0.112 0.074
M5: three facets plus acquiescence 386.65 50 0.972 0.962 0.102 0.093 0.112 0.074
Open-mindedness
M1: single domain 672.83 54 0.898 0.875 0.133 0.124 0.142 0.101
M2: single domain plus acquiescence 475.31 53 0.930 0.913 0.111 0.102 0.120 0.087
M3: positive and negative items 648.49 53 0.901 0.877 0.132 0.123 0.141 0.099
M4: three facets 163.74 51 0.981 0.976 0.059 0.049 0.069 0.053
M5: three facets plus acquiescence 158.76 50 0.982 0.982 0.058 0.048 0.068 0.053
Tab le 7. Fit statistics for conrmatory factor analysis of the BFI-2-B items. df = degrees of freedom;
CFI = Comparative t index; TLI = Tucker-Lewis Index; RMSEA = Root means square error of approximation,
CFI and TLI values
≥
0.900, RMSEA values
<0.080
, and SRMR values
<0.10
are bolded. All Chi-Square
values are signicant at p < 0.001.
Negative Emotionality Conscientiousness Extraversion Open mindedness Agreeableness
BFI20 0.482 − 0.267 0.517 0.047 0.790
RBFI25 − 0.066 − 0.171 0.267 0.259 0.249
RBFI30 − 0.061 − 0.064 0.318 0.288 0.271
BFI35 0.347 − 0.197 0.416 0.164 0.752
BFI40 − 0.174 0.205 − 0.256 0.416 − 0.169
RBFI45 0.061 − 0.202 0.171 0.354 0.158
RBFI50 0.300 − 0.206 0.392 − 0.117 0.780
RBFI55 0.068 − 0.276 0.242 0.065 0.306
BFI60 − 0.120 0.014 0.195 0.468 − 0.019
Tab le 6. ESEM factor loadings of the 60 items of BFI-2-B. e highest factor loading for each row is in bold.
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Most facets also demonstrated adequate reliability. However, intellectual curiosity under BF-Open Mindedness,
energy level under BF-Extraversion, and responsibility under BF-Conscientiousness exhibited lower reliability.
ese discrepancies may be due to cultural dierences in how personality traits are valued and expressed in Asian
versus Western contexts. Intellectual curiosity, which entails a desire for new ideas and intellectual engagement,
is a highly valued trait in many Western societies, where individualism and self-exploration are encouraged60.
Studies show that Western cultures emphasize intellectual pursuits for personal growth and self-expression61.
In contrast, intellectual curiosity may hold a dierent position within Asian cultures, where collectivist values
may prioritize conformity, respect for tradition, and group harmony over individual exploration62. is cultural
dierence could aect how respondents interpret items related to intellectual curiosity, leading to inconsistent
responses and lower reliability scores. e energy level facet within BF-Extraversion reects enthusiasm, vitality,
and social engagement, traits that are prominently valued in Western societies where extraversion is oen seen
as an asset in social and professional settings63. In Asian contexts, however, social restraint and modesty are
oen more valued, and high-energy behaviors may be interpreted dierently or even discouraged, especially
in social interactions64. Consequently, items measuring energy level might not resonate as strongly with
respondents in Asian cultures64. e lower reliability of the responsibility (BF-Conscientiousness) facet may
also reect cultural nuances in interpreting this trait. In Western cultures, responsibility is typically associated
with individual dependability and personal accountability65, traits that are seen as stable and integral to one’s
personality. However, in many Asian societies, responsibility may be viewed more contextually and may be tied
closely to roles within family and community structures61. Rather than being a stable, individual characteristic,
responsibility may be perceived as a situational obligation that one upholds in specic contexts (e.g., family
responsibilities) rather than as a broad, consistent trait . is variability in interpretation can lead to inconsistent
responses and lower reliability for responsibility-related items in Asian contexts.
e results supported our rst hypothesis that the domain and facet-level structures of the BFI-214 would
be reproducible in the Bangladeshi culture. It is reassuring that at the domain level, our results supported the
existence of the Big Five traits mirroring the results found in other international adaptations15,16,29. However,
some items were observed to have cross-loadings, especially for the BF-Open Mindedness and BF-Agreeableness
domains. is suggests that though the overall domain structure of BFI-2 is recognizable in its Bangla adaptation,
item-level variations were observed, which may be due to the cultural and linguistic contexts. For example,
certain items related to interpersonal behavior or emotional expressions might carry distinct connotations
in the Bangladeshi context, thus altering their interpretations. e translation process, while rigorous, may
not fully capture the subtleties embedded in the original items. At the facet level, consistent with the original
development work of the BFI-214, the best model t for the BFI-2-B was achieved when each of the ve major
personality domains was modeled with three distinct facets per domain and an additional acquiescence factor.
is approach aligns with the BFI-2’s design philosophy. Including an acquiescence factor is particularly
benecial as it accounts for response bias related to individuals’ tendency to agree with statements regardless of
content. is factor enhances the model’s robustness by adjusting for variance arising from acquiescent response
styles rather than true dierences in personality traits. us, structuring each domain with three specic facets
alongside an acquiescence factor mirrors the theoretical underpinnings and methodological rigor of the BFI-
2-B. is structure has proven eective across various languages and contexts, indicating that this facet-based,
multidimensional personality measurement approach is versatile and adaptable.
Supporting our second hypothesis, results showed that BFI-2-B demonstrated full measurement invariance
across gender (male vs. female) and education levels (undergraduates vs. postgraduates). Similar ndings were
reported in the Japanese adaptation29 of BFI-2, where the highest level (strict) of measurement invariance was
established across genders. e establishment of MI across gender and education level suggests that the BFI-B
items are interpreted similarly among male and female participants and individuals with dierent educational
levels within the Bangladeshi sample. is cross-group comparability highlights the scale’s suitability for diverse
applications, making it a valuable tool for research and practice in varied contexts. However, one important
NEO-agreeableness NEO-conscientiousness NEO-extraversion NEO-NE NEO-open mindedness
Correlation of BFI-2 and NEO-FFI (controlled for gender)
BF-agreeableness 0.59 0.35 0.25 − 0.29 0.09
BF-conscientiousness 0.19 0.79 0.32 − 0.35 − 0.01
BF-Extraversion − 0.05 0.38 0.73 − 0.35 0.10
BF-NE − 0.26 − 0.38 − 0.26 0.79 − 0.01
BF-Open mindedness 0.13 0.30 0.23 − 0.21 0.64
Correlation of BFI-2 and NEO-FFI (controlled for age)
BF-Agreeableness 0.59 0.32 − .23 − 0.24 0.10
BF-Conscientiousness 0.17 0.77 − .29 − 0.01 − 0.22
BF-Extraversion − 0.07 − .38 − 0.73 − 0.35 0.09
BF-NE − 0.18 − 0.33 − 0.24 0.78 0.01
BF-Open mindedness 0.13 0.30 0.23 − 0.21 0.64
Tab le 8. Correlations of the BFI-2-B domains with NEO-FFI. All correlations are signicant (p < 0.001). e
highest correlation in each row is in bold.
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pattern to be highlighted is that for some domains and facets, females tended to score higher than males (at the
mean level). In the current study, females described themselves as more agreeable, conscientious, and emotional.
At the facet level, women described themselves as more compassionate, trustworthy, organized, anxious,
depressed, and emotionally volatile than men. By contrast, men described themselves as more intellectually
creative. Such ndings are aligned with the existing literature14,15. Soto and John14 reported that females tend
to describe themselves as more extroverted, agreeable, conscientious, and emotional than males. Yoshino, et
al.29 while adapting BFI-2 in the Japanese language reported that within the BF-Extraversion domain, males
had a higher assertiveness score than females, while females had a higher sociability score. Future research is
warranted to investigate these gender-based dierences in personality traits.
In contrast to our expectation that full measurement invariance across language (English vs Bangla) would
be observed for BFI-2-B, our results supported only weak measurement invariance for language. Similar
challenges in language-based measurement invariance were also observed in the German adaptation20, where
exact measurement invariance was estimated using CFA, congural invariance was reported for agreeableness
and open-mindedness, and weak measurement invariance was reported for extraversion and conscientiousness.
ese ndings collectively point to potential challenges related to cultural and linguistic interpretations of specic
constructs and items. In Western cultures, traits like openness and extraversion are oen positively associated
with self-expression and individual achievement, whereas in Bangladesh and other South Asian cultures, these
traits may be viewed through a lens that emphasizes social harmony, modesty, and family obligations66,67.
Furthermore, words associated with traits like responsibility or intellectual curiosity may hold slightly dierent
connotations in Bangla than in English, potentially aecting how respondents interpret these items. e lack of
MI between Bangla and English BFI-2 may also be partly attributed to the dierences in response styles between
the two cultures. Research indicates that people from collectivist cultures, such as Bangladesh, may respond to
personality assessments in ways that reect social desirability or normative behaviors, prioritizing community-
oriented values over individual traits. In contrast, respondents in individualistic Western cultures might
prioritize self-expression, leading to dierent response patterns66,68. ese variations can aect item functioning,
as some BFI-2 items may resonate dierently in a collectivist versus an individualist cultural context, even if the
underlying construct is similar.
e Item Response eory (IRT) analysis of the BFI-2-B provided insights into item functioning and
measurement precision across the een personality facets. Overall, most items displayed acceptable t indices,
indicating their adequacy in capturing the underlying traits within each facet. Items demonstrated a range
of discrimination values, with 22 items showing very high discrimination, 12 items high, 21 items moderate,
and a few items with lower discrimination scores. e test information curves (TICs) further indicated that
most facets covered a wide range of the latent trait continuum, particularly around the mean levels of traits.
However, certain facets, such as compassion and respectfulness within BF-Agreeableness and aesthetic sensitivity
within BF-Open Mindedness, showed coverage skewed towards lower trait levels, suggesting that the BFI-
2-B items within these facets provide more reliable information for individuals with lower trait expressions.
Marginal reliability estimates were satisfactory for most facets, with values above 0.60 across facets, except for
responsibility (BF-Conscientiousness), which fell slightly below the threshold. e lower reliability of this facet
may reect that cultural interpretation of responsibility is context-dependent rather than a stable, individual
trait61. is variability suggests that further renement of items within these facets could enhance reliability in
the Bangladeshi setting.
e results of the current study supported our third hypothesis that the BFI-2-B would show strong convergent
validity (> 0.50) for the similar domains measured using the Bangla NEO-FFI, and discriminant correlations
between distinct domains would be lower than the convergent correlations. is reinforces the robustness of
the BFI-2-B as a valid personality assessment tool. e BFI-2-B demonstrated strong convergent validity, with
correlations for similar domains exceeding r = 0.59. ese high correlations suggest that the BFI-2-B eectively
measures personality constructs comparable to those captured by the NEO-FFI, aligning with expected patterns
based on the theoretical overlap between these two well-established personality models. Discriminant validity
was conrmed since the correlations between distinct domains were substantially lower than the correlations
between similar domains. is dierentiation among domains suggests that the BFI-2-B eectively distinguishes
between personality traits. ese ndings are consistent with results from the development work of English
BFI-214 that reported high convergent and discriminant validity with established personality measures. In both
Western and non-Western adaptations, high correlations between the BFI-2 and NEO-FFI domains underscore
the reliability of the BFI-2 structure across dierent cultural and linguistic settings, supporting the broad
applicability of the Big Five model.
Limitations and future directions
While the BFI-2-B has demonstrated promising psychometric properties in this study, several limitations must
be acknowledged. First, although the sample size was adequate, the study relied on an internet-based sample,
which may introduce sampling bias. Internet samples may not fully represent the diversity of the Bangladeshi
population, particularly regarding socioeconomic, geographical, and educational backgrounds. Additionally,
this study retained data from 646 participants out of the initial 1,095. is exclusion of 41% of the data due
to participants failing attention checks, may impact the representativeness and generalizability of the results.
Second, measurement invariance across languages showed only weak invariance, indicating potential cultural
and linguistic dierences in item interpretation between Bangla and English versions. is limitation suggests
that the translation process may not capture subtle cultural nuances in certain personality traits, potentially
impacting the cross-linguistic validity of the BFI-2-B. Furthermore, certain facets within domains, such as energy
level (BF-Extraversion), responsibility (BF- Conscientiousness), and intellectual curiosity (BF-Open-mindedness),
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exhibited lower reliability. is could indicate cultural dierences in trait interpretation, which may aect the
reliability of these facets in non-Western samples.
To address these limitations and enhance the robustness of the BFI-2-B, future studies should consider
employing mixed-method approaches, including cognitive interviews, to gain deeper insights into how
Bangladeshi respondents interpret specic items. is could help identify cultural nuances inuencing
responses and improve translation accuracy. Additionally, future research should seek to replicate these ndings
across more diverse samples, including rural populations and those from varied socioeconomic backgrounds,
to enhance generalizability. Finally, to improve cross-linguistic measurement invariance, researchers might
develop culture-specic items or adapt existing items to better align with local norms and values .
Conclusion
is study represents a comprehensive psychometric validation of the Bangla Big Five Inventory-2 (BFI-2-B),
providing a valuable tool for assessing personality traits in the Bangladeshi population. e BFI-2-B demonstrated
strong internal consistency (especially at the domain levels) and structural validity (at both the domain and facet
levels), reinforcing its alignment with the theoretical framework of the Big Five personality model. e study
successfully established full measurement invariance across gender and education levels, highlighting the BFI-2-
B’s suitability for diverse applications within these demographic groups in Bangladesh. Additionally, the strong
convergent and discriminant validity demonstrated by the BFI-2-B supports its capability to measure distinct
personality constructs eectively. However, challenges emerged in achieving full measurement invariance
across languages, suggesting potential cultural and linguistic nuances in item interpretation that warrant further
exploration. Lower reliability scores for specic facets, such as energy level and intellectual curiosity, underscore
the need for caution when interpreting these facets in Bangladeshi contexts. Overall, the BFI-2-B provides a
psychometrically robust, culturally adapted measure of personality that holds promise for research and applied
settings in Bangladesh. With continued research and adaptation, the BFI-2-B can serve as a foundational tool for
advancing personality assessment in Bangladesh, contributing to more nuanced understandings of personality
traits within this cultural context.
Data availability
All raw data and materials are publicly available on Open Science Framework (https://osf.io/7dtqg/) and GitHub
(https://github.com/mind-psychometry/BanglaBigFive2).
Code availability
Data analysis codes are publicly available on Open Science Framework (https://osf.io/7dtqg/) and GitHub
(https://github.com/mind-psychometry/BanglaBigFive2).
Received: 21 November 2023; Accepted: 11 February 2025
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Acknowledgements
is research project is supported by a Startup Grant for New Faculty (FY2024-2025) administered by the North
Soth University Oce of Research.
Author contributions
M.A.S., F.K., C.J.S, and S.H. designed the study. M.A.S. and F.K. curated the data. M.A.S. conducted the formal
analysis and prepared all gures and tables. M.A.S., F.K., C.J.S, and S.H. wrote and reviewed the main manuscript
text. All authors reviewed the manuscript.
Declarations
Competing interests
e authors declare no competing interests.
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