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 |
| 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 |
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 |
dateiditemrespwave
Or load it directly in R or Python:
# 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 }
| IRW version | v470 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v4.0 |
| Redivis dataset DOI | 10.57761/4e8w-c240 |
| Manifest pin for this IRW version | v4.0 |
| Metadata source | irw_meta v29.0 |