Big Five Inventory (BFI-2)

library(questionnaires)

Background

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

Scoring

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/).

Domain Scales

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

Relational table

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

Data requirements

Column names

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

Data values

The data should be coded with the original scoring system 1-5. The data should not have implemented necessary reversal of answers for any of the questions, the functions will take care of this.

Using the `bfi` functions

Computing all domains and facets.

# 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_")

Domains

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())

Facets

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)