69,450 responses from 23,150 respondents to 3 items.
One of 4 tables from the same source; this one measures COVID-19 self-efficacy. The others are listed under Related tables.
| Description | COVID-19 self-efficacy, 3 items, 0-4, 23,150 users of the Praditus assessment platform (ages 13-93, mostly French, US, German, Italian, Mexican, Spanish), 2020; cov_gender, cov_age, cov_nationality, cov_work_experience. |
|---|---|
| Reference | Meyer, N., Niemand, T., Davila, A., & Kraus, S. (2022). Biting the bullet: When self-efficacy mediates the stressful effects of COVID-19 beliefs. PLOS ONE, 17(1), e0263022. |
| DOI | 10.1371/journal.pone.0263022 |
| Licence | CC BY 4.0 |
| Source data | https://data.mendeley.com/datasets/b8zxmw5z3g/1 |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Responses | 69,450 |
|---|---|
| Respondents | 23,150 |
| Items | 3 |
| Response categories | 5 |
| Responses per respondent | 3 |
| Responses per item | 23,150 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| sample | General/non-specific, Internet-based |
| construct type | Personality |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | fre, eng |
| construct name | COVID-19 self-efficacy |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, meyer_2022_covid_beliefs.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | Unnamed: 0 |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | made in the build script |
cov_gender | Covariate | gender |
cov_nationality | Covariate | nationality |
cov_work_experience | Covariate | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("meyer_2022_covid_selfeff")
# Python
pip install irw
import irw
df = irw.fetch("meyer_2022_covid_selfeff")
@article{Meyer_2022, title={Biting the bullet: When self-efficacy mediates the stressful effects of COVID-19 beliefs}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0263022}, DOI={10.1371/journal.pone.0263022}, number={1}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Meyer, Natanya and Niemand, Thomas and Davila, Andrés and Kraus, Sascha}, editor={Fronzetti Colladon, Andrea}, year={2022}, month=Jan, pages={e0263022} }
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v5.11 |
| Redivis dataset DOI | 10.57761/qahq-j855 |
| Manifest pin for this IRW version | v5.11 |
| Metadata source | irw_meta v44.0 |