34,894 responses from 999 respondents to 2 items.
| Description | CoVidAffect: momentary affect during the COVID-19 lockdown in Spain, experience sampling via app and web. Two visual analogue sliders per report: valence (-50 to +50, a modified Feeling Scale) and arousal (0 to 100, a modified Felt Arousal Scale). 999 people, 17,451 reports; wave is each person's report number in time order, date is Unix time. |
|---|---|
| Reference | Bailon C, Goicoechea C, Banos O, et al. (2020). CoVidAffect, real-time monitoring of mood variations following the COVID-19 outbreak in Spain. Scientific Data 7, 365. |
| DOI | 10.1038/s41597-020-00700-1 |
| Licence | CC BY 4.0 |
| Source data | https://zenodo.org/records/22763396 |
These data were found via openESM, where additional metadata for this dataset are available.
| Responses | 34,894 |
|---|---|
| Respondents | 999 |
| Items | 2 |
| Response categories | 151 |
| Responses per respondent | 34.929 |
| Responses per item | 17,447 |
| Density | 17.464 |
| Longitudinal | TRUE |
| sample | Internet-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Slider/continuous |
| primary language(s) | spa |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | CoVidAffect mood assessment questionnaire (Bailon et al. 2020): two visual analogue scales, valence and arousal |
|---|---|
| Mean words per item | 7 |
| Mean characters per item | 35 |
| Mean characters per response | 10 |
| Flesch-Kincaid grade level | 2.311 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, bailon_2020_covidaffect.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 | ||
date | IRW standard Calendar time in seconds — either seconds elapsed since data collection start (relative) or Unix time (absolute). | made in the build script |
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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
wave | IRW standard Longitudinal wave indicator. | made in the build script |
What item codes and covariate values stand for is in the source’s codebook, 0018_bailon_codebook.pdf.
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("bailon_2020_covidaffect")
# Python
pip install irw
import irw
df = irw.fetch("bailon_2020_covidaffect")
@article{Bailon_2020, title={CoVidAffect, real-time monitoring of mood variations following the COVID-19 outbreak in Spain}, volume={7}, ISSN={2052-4463}, url={http://dx.doi.org/10.1038/s41597-020-00700-1}, DOI={10.1038/s41597-020-00700-1}, number={1}, journal={Scientific Data}, publisher={Springer Science and Business Media LLC}, author={Bailon, Carlos and Goicoechea, Carmen and Banos, Oresti and Damas, Miguel and Pomares, Hector and Correa, Angel and Sanabria, Daniel and Perakakis, Pandelis}, year={2020}, month=Oct }
This table was found via openESM; please also cite:
@article{siepe2026openesm, title={Introducing openESM: A database of openly available experience sampling datasets}, author={Siepe, Bj{\"o}rn S. and Haslbeck, Jonas M. B. and Kloft, Matthias and B{\"u}chner, Anabel and Zhang, Yong and Fried, Eiko I. and Heck, Daniel W.}, journal={Behavior Research Methods}, volume={58}, number={8}, pages={240}, year={2026}, doi={10.3758/s13428-026-03112-y}}
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v5.10 |
| Redivis dataset DOI | 10.57761/8zbf-t397 |
| Manifest pin for this IRW version | v5.10 |
| Metadata source | irw_meta v39.0 |