The BFI-2 is a measure of the Big Five personality domains (which we label Extraversion, Agreeableness, Conscientiousness, Negative Emotionality, and Open-Mindedness) and 15 more-specific facet traits. The Big Five personality traits was the model to comprehend the relationship between personality and academic behaviors. This model was defined by several independent sets of researchers who used factor analysis of verbal descriptors of human behavior. These researchers began by studying relationships between a large number of verbal descriptors related to personality traits. They reduced the lists of these descriptors by 5–10 fold and then used factor analysis to group the remaining traits (using data mostly based upon people’s estimations, in self-report questionnaire and peer ratings) in order to find the underlying factors of personality
Item numbers for the BFI-2 domain and facet scales are listed below. Reverse-keyed items are denoted by “R.” For more information about the BFI-2, visit the Colby Personality Lab website (http://www.colby.edu/psych/personality-lab/).
Extraversion: 1, 6, 11R, 16R, 21, 26R, 31R, 36R, 41,
46, 51R, 56
Agreeableness: 2, 7, 12R, 17R, 22R, 27, 32, 37R, 42R,
47R, 52, 57
Conscientiousness: 3R, 8R, 13, 18, 23R, 28R, 33, 38,
43, 48R, 53, 58R
Negative Emotionality: 4R, 9R, 14, 19, 24R, 29R, 34,
39, 44R, 49R, 54, 59 Open-Mindedness: 5R, 10, 15, 20,
25R, 30R, 35, 40, 45R, 50R, 55R, 60
Sociability: 1, 16R, 31R, 46
Assertiveness: 6, 21, 36R, 51R
Energy Level: 11R, 26R, 41, 56
Compassion: 2, 17R, 32, 47R
Respectfulness: 7, 22R, 37R, 52
Trust: 12R, 27, 42R, 57
Organization: 3R, 18, 33, 48R
Productiveness: 8R, 23R, 38, 53
Responsibility: 13, 28R, 43, 58R
Anxiety: 4R, 19, 34, 49R
Depression: 9R, 24R, 39, 54
Emotional Volatility: 14, 29R, 44R, 59
Intellectual Curiosity: 10, 25R, 40, 55R
Aesthetic Sensitivity: 5R, 20, 35, 50R
Creative Imagination: 15, 30R, 45R, 60
Domain | Factor-pure facet | Complementary facets |
---|---|---|
E | Sociability | Assertiveness, Energy Level |
A | Compassion | Respectfulness, Trust |
C | Organization | Productiveness, Responsibility |
N | Anxiety | Depression, Emotional Volatility |
O | Aesthetic Sensitivity | Intellectual Curiosity, Creative Imagination |
The package functions expect the data to be named in a specific way, and to not contain data other than the BFI-2 data. Column names should be zero-leading two digits to indicate the question number, and they should end with these two digits. If this system is followed, then all functions work out of the box.
Examples that work:
bfi_01
bfi_02
… bfi_59
bfi_60
big_five_01
big_five_02
…
big_five_59
bbig_five_60
Examples that won’t work
bfi_1
bfi_2
… bfi_59
bfi_60
big_five_01_trust
big_five_02_change
…
big_five_59_test
bbig_five_60_lat
# Making some test data
test_data <- tibble(
id = rep(1:10, each = 60),
name = rep(sprintf("bfi_%02d", 1:60), 10),
value = lapply(1:10, function(x){
sample(1:5, size = 60, replace = TRUE)
}) %>% unlist()
) %>%
tidyr::pivot_wider()
test_data
To compute all the possible domains and facets, as long as the data is set up correctly, you can run a single function
bfi_compute(test_data)
You also have some options in terms of prefixing the data, and if you want to keep all the original data in the output as well.
bfi_compute(test_data, keep_all = TRUE)
bfi_compute(test_data, prefix = "bfi_")
There are two main ways you can compute domains alone. These two ways
are equivalent, and take prefix
and keep_all
arguments.
bfi_compute(test_data, type = "domains")
bfi_compute_domains(test_data)
You can also choose to compute only certain domains, either by calling on their own special function or by specifying a domain in the main domain function.
## Computes all
bfi_compute_domains(test_data, domains = c("extraversion",
"agreeableness",
"conscientiousness",
"negative emotionality",
"open-mindedness"))
## extraversion and agreeableness only
bfi_compute_domains(test_data, domains = c("extraversion",
"agreeableness"))
## only agreeableness, returned as a vector, not a data.frame
bfi_domain_agreeable(test_data)
## So it can be used in a mutate, but, awkwardly
mutate(test_data,
agree = bfi_domain_agreeable(test_data)) %>%
select(agree, everything())
There are two main ways you can compute facets alone. These two ways
are equivalent, and take prefix
and keep_all
arguments.
bfi_compute(test_data, type = "facets")
bfi_compute_facets(test_data)
You can also choose to compute only certain domains, either by calling on their own special function or by specifying a domain in the main domain function.
## Computes all
bfi_compute_facets(test_data,
facets = c("sociability",
"assertiveness",
"energy",
"compassion",
"respectful",
"trust",
"organization",
"productive",
"responsibility",
"anxiety",
"depression",
"emotional volatility",
"intellectual curiosity",
"aesthetic sensebility",
"creative imagination"))
## extraversion and agreeableness only
bfi_compute_facets(test_data,
facets = c("anxiety",
"depression"))
## only anxiety, returned as a vector, not a data.frame
bfi_facet_anxiety(test_data)
## So it can be used in a mutate, but, awkwardly
mutate(test_data,
anx = bfi_domain_agreeable(test_data)) %>%
select(anx, everything())
Soto, C. J., & John, O. P. (2017). 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