evans_2023_vaccination_norms
17,744 responses from 1,933 respondents to 5 items.
About this table
| Description | Pro-vaccination social norms scale (5 items 1-5 ordinal) 3 waves treat=campaign vs comparison state N=1933 Nigerian Facebook users |
|---|
| Reference | Evans WD et al. (2023) Outcomes of a social media campaign to promote COVID-19 vaccination in Nigeria. PLOS ONE. |
|---|
| DOI | 10.1371/journal.pone.0290757 |
|---|
| Licence | CC BY 4.0 |
|---|
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0290757.s003 |
|---|
Size and shape
| Responses | 17,744 |
|---|
| Respondents | 1,933 |
|---|
| Items | 5 |
|---|
| Response categories | 5 |
|---|
| Responses per respondent | 9.180 |
|---|
| Responses per item | 3548.800 |
|---|
| Density | 1.836 |
|---|
| Longitudinal | TRUE |
|---|
Classification
| sample | Internet-based, Program-based |
|---|
| measurement tool | Survey/questionnaire |
|---|
| item format | Likert Scale/selected response |
|---|
| primary language(s) | eng |
|---|
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Pro-Vaccination Social Norms Scale |
|---|
| Mean words per item | 16.800 |
|---|
| Mean characters per item | 93.200 |
|---|
| Mean characters per response | 15.080 |
|---|
| Flesch-Kincaid grade level | 8.721 |
|---|
Columns
cov_agegrpcov_educov_empsectcov_gendercov_religioniditemresptreatwave
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("evans_2023_vaccination_norms")
# Python
pip install irw
import irw
df = irw.fetch("evans_2023_vaccination_norms")
Version and provenance
| 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 |
|---|