extremera_2016_shs

4,500 responses from 1,125 respondents to 4 items.

One of 4 tables from the same source; this one is the shs table. The others are listed under Related tables.

About this table

DescriptionSubjective Happiness Scale (SHS, 4 items), unemployed adults, N=1125
ReferenceExtremera N, Rey L (2016). Attenuating the Negative Impact of Unemployment: The Interactive Effects of Perceived Emotional Intelligence and Well-Being on Suicide Risk. PLOS ONE, 11(9), e0163656. https://doi.org/10.1371/journal.pone.0163656
DOI10.1371/journal.pone.0163656
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0163656.s001

Size and shape

Responses4,500
Respondents1,125
Items4
Response categories7
Responses per respondent4
Responses per item1,125
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)spa

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, extremera_2016_unemployment_wellbeing.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.

ColumnWhat it isSource column
IRW standard columns
idIRW 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
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_ageCovariate age
cov_educationCovariate level_education
cov_length_unemploymentCovariate length_unemployment
cov_marital_statusCovariate marital_status
cov_sexCovariate sex
cov_unemployment_benefitsCovariate unemployment_benefits

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

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("extremera_2016_shs")
# Python
pip install irw

import irw
df = irw.fetch("extremera_2016_shs")

How to cite

@article{Extremera_2016, title={Attenuating the Negative Impact of Unemployment: The Interactive Effects of Perceived Emotional Intelligence and Well-Being on Suicide Risk}, volume={11}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0163656}, DOI={10.1371/journal.pone.0163656}, number={9}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Extremera, Natalio and Rey, Lourdes}, editor={Duan, Wenjie}, year={2016}, month=Sept, pages={e0163656} }

Version and provenance

IRW versionv557
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v40.0