5,664 responses from 472 respondents to 12 items.
| Description | NEO-FFI-3 Conscientiousness subscale (12 items), 1-5 Likert, N=472 nurses (Jordan/Saudi Arabia EHR continuance-intention study). |
|---|---|
| Reference | Alsyouf A, Alsubahi N, Alali H, Lutfi A, Al-Mugheed KA, Alrawad M, Almaiah MA, Anshasi RJ, Alhazmi FN, Sawhney D (2024). Nurses' continuance intention to use electronic health record systems: The antecedent role of personality and organisation support. PLOS ONE 19(10):e0300657. |
| DOI | 10.1371/journal.pone.0300657 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0300657 |
| Responses | 5,664 |
|---|---|
| Respondents | 472 |
| Items | 12 |
| Response categories | 5 |
| Responses per respondent | 12 |
| Responses per item | 472 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Personality |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ara |
| construct name | NEO Five-Factor Inventory (NEO-FFI) - Conscientiousness |
cov_agecov_departmentcov_educationcov_gendercov_hospitalcov_professional_experienceiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("alsyouf_2024_conscientiousness")
# Python
pip install irw
import irw
df = irw.fetch("alsyouf_2024_conscientiousness")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v7.0 |
| Redivis dataset DOI | 10.57761/pqqn-pm43 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |