li_2024_trait_anxiety

10,896 responses from 681 respondents to 16 items.

One of 3 tables from the same source; this one measures Trait anxiety. The others are listed under Related tables.

About this table

DescriptionTrait anxiety block, 16 items (JL1-JL17, JL10 absent), 1-6; N = 681; same covariates.
ReferenceLi, Y., Ma, J., Xi, Y., & Li, J. (2024). Big Five personality and mind wandering in athletes: mediating role of trait anxiety. Frontiers in Psychology, 15, 1232312. https://doi.org/10.3389/fpsyg.2024.1232312
DOI10.3389/fpsyg.2024.1232312
LicenceCC BY 4.0
Source datahttps://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Big_Five_personality_and_mind_wandering_in_athletes_mediating_role_of_trait_anxiety_CSV/25210199

Size and shape

Responses10,896
Respondents681
Items16
Response categories6
Responses per respondent16
Responses per item681
Density1
LongitudinalFALSE

Classification

age rangeMixed
sampleTargeted/specific
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)chi
construct nameTrait anxiety

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, li_2024_athletes_mind_wandering.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 years
cov_genderCovariate gender
cov_levelCovariate level
cov_sports_groupCovariate sports group
cov_sports_yearsCovariate sports years

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("li_2024_trait_anxiety")
# Python
pip install irw

import irw
df = irw.fetch("li_2024_trait_anxiety")

How to cite

@article{Li_2024, title={Big Five personality and mind wandering in athletes: mediating role of trait anxiety}, volume={15}, ISSN={1664-1078}, url={http://dx.doi.org/10.3389/fpsyg.2024.1232312}, DOI={10.3389/fpsyg.2024.1232312}, journal={Frontiers in Psychology}, publisher={Frontiers Media SA}, author={Li, Yueming and Ma, Jifei and Xi, Yue and Li, Jieling}, year={2024}, month=Feb }

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_7 v1.1
Redivis dataset DOI10.57761/7pd3-sh31
Manifest pin for this IRW versionv1.0
Metadata sourceirw_meta v44.0