Item Response Warehouse / Tables / taylorabdulai_2025_incentivestaylorabdulai_2025_incentives
2,639 responses from 377 respondents to 7 items.
About this table
Description Factors that would increase COVID-19 vaccine acceptance, 7 Yes/No items, urban Ghana population Reference Taylor-Abdulai HB, Dzantor EK, Mensah NK, Asumah MN, Ocansey S, Arhin SK, et al. (2025) Coronavirus disease 2019 (COVID-19) vaccine acceptability in Ghana: An urban-based population study. PLoS ONE. DOI 10.1371/journal.pone.0319798 Licence CC BY 4.0 Source data https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0319798.s001
Size and shape
Responses 2,639 Respondents 377 Items 7 Response categories 2 Responses per respondent 7 Responses per item 377 Density 1 Longitudinal FALSE
Classification
age range Adult (18+) 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 COVID-19 vaccine acceptability questionnaire (Taylor-Abdulai et al. 2025; adapted from a WHO questionnaire): What will make you accept COVID-19 vaccine Mean words per item 3.571 Mean characters per item 27.143 Mean characters per response 2.500 Flesch-Kincaid grade level 12.707
Columns
cov_age cov_education cov_occupation cov_religion cov_sex id item resp
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("taylorabdulai_2025_incentives")
# Python
pip install irw
import irw
df = irw.fetch("taylorabdulai_2025_incentives")
Version and provenance
IRW version v393 Redivis dataset item_response_warehouse_4 v7.0 Redivis dataset DOI 10.57761/cpj5-vm97 Manifest pin for this IRW version v7.0 Metadata source irw_meta v23.0
Part of the Item Response Warehouse , IRW v393. This page describes the table as released in item_response_warehouse_4 v7.0.