lin_2023_harsh_parenting

1,824 responses from 456 respondents to 4 items.

One of 4 tables from the same source; this one measures Harsh parenting (harsh discipline scale). The others are listed under Related tables.

About this table

DescriptionHarsh discipline scale, 4 items, 1-5; N = 456 students at a public junior high school in China (ages 12-15); cov_gender, cov_grade, cov_age.
ReferenceLin, W., Liang, H., Jiang, H., Mohd Nasir, M. A., & Zhou, H. (2023). Why is Smartphone Addiction More Common in Adolescents with Harsh Parenting? Depression and Experiential Avoidance's Multiple Mediating Roles. Psychology Research and Behavior Management, 16, 4817-4828. https://doi.org/10.2147/PRBM.S428167
DOI10.2147/PRBM.S428167
LicenceCC BY 4.0
Source datahttps://doi.org/10.6084/m9.figshare.24100509.v1

Size and shape

Responses1,824
Respondents456
Items4
Response categories5
Responses per respondent4
Responses per item456
Density1
LongitudinalFALSE

Classification

age rangeChild (<18y)
child age (for child-focused studies)Adolescent (12-18y)
sampleEducational, General/non-specific
construct typeBehavioral
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)chi
construct nameHarsh parenting (harsh discipline scale)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard. 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).not traced
itemIRW standard Item identifier.not traced
respIRW standard Response value.not traced
Respondent covariates
cov_ageCovariate not traced
cov_genderCovariate not traced
cov_gradeCovariate not traced

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("lin_2023_harsh_parenting")
# Python
pip install irw

import irw
df = irw.fetch("lin_2023_harsh_parenting")

How to cite

@article{Lin_2023, title={Why is Smartphone Addiction More Common in Adolescents with Harsh Parenting? Depression and Experiential Avoidance‘s Multiple Mediating Roles}, volume={Volume 16}, ISSN={1179-1578}, url={http://dx.doi.org/10.2147/PRBM.S428167}, DOI={10.2147/prbm.s428167}, journal={Psychology Research and Behavior Management}, publisher={Informa UK Limited}, author={Lin, Wanqing and Liang, Hanyu and Jiang, Huaibin and Mohd Nasir, Mohd Azrin and Zhou, Huiling}, year={2023}, month=Nov, pages={4817–4828} }

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_5 v8.5
Redivis dataset DOI10.57761/41xy-5k56
Manifest pin for this IRW versionv8.5
Metadata sourceirw_meta v44.0