Study Information

Data Characteristics

  • Participants: 999 (community sample)
  • Time Points: 444
  • Days: 86
  • Beeps per Day: 6
  • Sampling Scheme: 6x/day pseudo-random one-hour intervals
  • Raw Timestamp: yes
  • Implicit Missingness: yes

Data Availability

Data Access

  • Zenodo DOI: 10.5281/zenodo.17347690
  • R: openesm::get_dataset("0018_bailon")
  • Python: openesm.get_dataset("0018_bailon")

Additional Comments

no beep information available; number of max. time points taken as maximum of observations in data

Citation

Bailon, C., Goicoechea, C., Banos, O., Damas, M., Pomares, H., Correa, A., Sanabria, D., & Perakakis, P. (2020). CoVidAffect, real-time monitoring of mood variations following the COVID-19 outbreak in Spain. Scientific Data, 7(1), 365. https://doi.org/10.1038/s41597-020-00700-1

Changelog

No changes yet.

Variables

NameDescriptionTypeAnswer CategoriesDetailsLabelsTransformationSourceAssessment TypeConstructComments
idParticipant IDcategoricalESM
dayDay of studyotherESM
beepBeep of the dayotherESM
timestamp_issuedTimestamp survey issuedPosixCtESM
timestamp_answerTimestamp survey answeredPosixCtESM
valenceValencerating_scale101How do you feel right now?-50 = Very bad
50 = Very good
the Feeling Scale
(https://doi.org/10.1123/jsep.11.3.304)
ESMvalence, affect
arousalArousalrating_scale101How physically active do you feel right now?0 = Not active
100 = Active
the Felt Arousal Scale
(https://doi.org/10.1123/jsep.11.3.304)
ESMarousal, affect
valence_slider_initialSlider initialisation valencerating_scale101ESMslider, measurement
arousal_slider_initialSlider initialisation arousalrating_scale101ESMslider, measurement
input_methodSurvey input methodcategorical3One of {‘App’, ‘Web’, ‘Both’}ESM